diff --git a/README.md b/README.md index 3009c24..b646e8f 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ ![GUI and PyPi releases](https://github.com/MannLabs/pydiaid/workflows/Publish%20on%20PyPi%20and%20release%20on%20GitHub/badge.svg) # py_diAID -The [Mann Labs at the Max Planck Institute of Biochemistry](https://www.biochem.mpg.de/mann) developed py_diAID generating dia-PASEF methods with an optimal window design. py_diAID stands for an open-source Python package for Data-Independent Acquisition with an Automated Isolation Design. To enable all hyperlinks in this document, please view it on [GitHub](https://github.com/MannLabs/pydiaid). +The [Mann Labs at the Max Planck Institute of Biochemistry](https://www.biochem.mpg.de/mann) developed py_diAID, a tool that facilitates the generation of dia-PASEF and synchro-PASEF methods with an optimal window design. py_diAID, an abbreviation for Data-Independent Acquisition with an Automated Isolation Design, is available as an open-source Python and Graphical User Interface (GUI) package. To access all the hyperlinks in this document, please view it on [GitHub](https://github.com/MannLabs/pydiaid). * [**About**](#about) * [**License**](#license) @@ -22,11 +22,11 @@ The [Mann Labs at the Max Planck Institute of Biochemistry](https://www.biochem. --- ## About -Data-independent acquisition coupled with parallel accumulation – serial fragmentation (dia-PASEF) has been gaining increasing traction, amongst proteomics researchers over the last years. dia-PASEF offers comprehensive proteome coverage, a high degree of reproducibility, and quantitative accuracy while using a much higher ion beam proportion than conventional DIA methods. Previous tools generated dia-PASEF methods with equidistant isolation widths and necessitated manual adjustment of the window design to the precursor density cloud. We present py_diAID, a Python-based package for Data-Independent Acquisition offering an Automated Isolation Design. py_diAID generates optimal dia-PASEF methods with variable isolation widths adjusted to the precursor density in m/z and automatically, optimally placed in the m/z – ion mobility (IM) plane. Variable isolation widths enable short acquisition cycles while covering essentially the complete m/z-IM-range. We found that the dia-PASEF methods, generated with py_diAID, are beneficial for optimizing proteomics workflows based on cell lines (HeLa) or clinical samples such as CSF and Plasma, as well as for studying post-translational modifications such as phosphorylation. +Over the last few years, Data-Independent Acquisition (DIA) coupled with Parallel Accumulation – Serial Fragmentation (PASEF) has been gaining interest among proteomics researchers. The scan mode dia-PASEF offers comprehensive proteome coverage, a high degree of reproducibility, and quantitative accuracy while utilizing a much larger ion beam proportion than conventional DIA methods. Its successor, synchro-PASEF, enables the creation of methods with even shorter cycle times, improving quantitative accuracy while also being highly specific due to the linking of fragment signals with precursor masses. Existing tools generate dia-PASEF and synchro-PASEF methods with equidistant isolation widths and necessitate manual adjustment of the window design to the precursor density cloud. -We offer py_diAID as a Python module, command-line interface (CLI) tool, and Graphical User Interface (GUI) on all major operating systems under an Apache 2.0 license. py_diAID generates dia-PASEF methods with an optimal window design. It also allows for quality control of the precursors’ distribution of a dataset in the m/z-IM plane and evaluating the suitability of already existing dia-PASEF methods for the individual experiment. +We present py_diAID, a Python-based package for Data-Independent Acquisition providing Automated Isolation Design. py_diAID optimally generates dia-PASEF and synchro-PASEF methods and places them optimally within the m/z – ion mobility (IM) plane. Additionally, it can generate variable isolation widths aligned to the precursor density in m/z, facilitating short acquisition cycles while covering virtually the entire m/z-IM-range. Our findings indicate that methods created with py_diAID are advantageous for studying deep proteomes from cell lines, clinical samples with regular and very low sample input, as well as for exploring post-translational modifications such as phosphorylation. -py_diAID is an open-source Python package from the [Mann Labs at the Max Planck Institute of Biochemistry](https://www.biochem.mpg.de/mann). +py_diAID is an open-source Python package and also offers a Graphical User Interface (GUI). It was developed by the [Mann Labs at the Max Planck Institute of Biochemistry](https://www.biochem.mpg.de/mann). py_diAID is designed to generate dia-PASEF and synchro-PASEF methods with an optimal window design. Furthermore, it aids in quality control by assessing the precursor distribution in the m/z-IM plane and evaluating existing dia-PASEF and synchro-PASEF methods. --- ## License @@ -36,7 +36,7 @@ py_diAID was developed by the [Mann Labs at the Max Planck Institute of Biochemi --- ## Installation -py_diAID can be installed and used on all major operating systems (Windows, macOS, and Linux). +py_diAID can be installed and used on the Windows operating system. There are three different types of installation possible: * [**One-click GUI installer:**](#one-click-gui) Choose this installation if you only want the GUI and/or keep things simple. @@ -45,15 +45,13 @@ There are three different types of installation possible: ### One-click GUI -The GUI of py_diAID is a stand-alone tool that requires no knowledge of Python or CLI tools. Click on one of the links below to download the latest release for: +The GUI of py_diAID is a stand-alone tool that requires no knowledge of Python or CLI tools. Click on the link below to download the latest release for: * [**Windows**](https://github.com/MannLabs/pydiaid/releases/latest/download/pydiaid_gui_installer_windows.exe) -* [**macOS**](https://github.com/MannLabs/pydiaid/releases/latest/download/pydiaid_gui_installer_macos.pkg) -* [**Linux**](https://github.com/MannLabs/pydiaid/releases/latest/download/pydiaid_gui_installer_linux.deb) Older releases remain available on the [release page](https://github.com/MannLabs/pydiaid/releases), but no backward compatibility is guaranteed. -**IMPORTANT: Please refer to the [GUI manual](https://github.com/MannLabs/pydiaid/blob/development/pydiaid/docs/manual.pdf) for detailed instructions on installing, troubleshooting, and using the stand-alone py_diAID GUI.** +**IMPORTANT: Please refer to the [GUI manual](https://github.com/MannLabs/pydiaid/blob/development/pydiaid/docs/manual.pdf) for detailed instructions on installing and using the stand-alone py_diAID GUI.** ### Pip @@ -115,10 +113,9 @@ By default this installs loose dependancies (no explicit versioning), although i --- ## Usage -There are three ways to use py_diAID: +There are two ways to use py_diAID: * [**GUI**](#gui) -* [**CLI**](#cli) * [**Python**](#python-and-jupyter-notebooks) NOTE: The first time you use a fresh installation of py_diAID, it is often relatively slow because some functions might still need compilation on your local operating system and architecture. Subsequent executions should be a lot faster. @@ -135,77 +132,32 @@ Note that this needs to be prepended with a `!` when you want to run this from w **IMPORTANT: Please refer to the [GUI manual](https://github.com/MannLabs/pydiaid/blob/development/pydiaid/docs/manual.pdf) for detailed instructions on installing, troubleshooting, and using the stand-alone py_diAID GUI.** -### CLI - -The CLI can be run with the following command (after activating the `conda` environment with `conda activate pydiaid` or if an alias was set to the pydiaid executable): - -```bash -pydiaid -h -``` - -It is possible to get help with each function and its (required) parameters by using the `-h` flag. For instance, the command ```pydiaid optimize -h``` will produce the following output: - -``` -****************** -* py_diAID 0.0.9 * -****************** -Usage: pydiaid optimize [OPTIONS] - - Optimize a dia-PASEF method. - -Options: - -p TEXT Parameter file (check out - d:\pydiaid\pydiaid\lib\default_parameters.json for an example) - [required] - -h, --help Show this message and exit. -``` - -py_diAID provides several options: -- charge: Evaluate a dia-PASEF method for multiply charged precursors. -- create: Create a specific dia-PASEF method. -- evaluate: Evaluate a dia-PASEF method. -- gui: Start graphical user interface. -- optimize: Optimize a dia-PASEF method. - -All options can be executed with ```pydiaid [option] -p [Text]```. The parameters are saved in a .json parameter file and have to be adjusted in this file. For instance, the command ```pydiaid optimize -p "d:\pydiaid\pydiaid\lib\default_parameters.json"``` will execute one complete optimization process. py_diAID will create a folder at the location specified in the .json parameter file with all generated information and print the following result in the terminal window: - -``` -****************** -* py_diAID 0.0.9 * -****************** -Using parameter file d:\pydiaid\pydiaid\lib\default_parameters.json -{'precursors within m/z-range [%]': 97.59} -RUN WITH: [0.7435820751492209, 0.9789579174732773, 1.73455196349983, 1.5945652845606708] | RESULT: 10823.0 -RUN WITH: [0.7468616079634967, 0.8864876711590428, 1.6545030790686948, 1.6033036772717069] | RESULT: 11168.0 -RUN WITH: [0.7346248237666703, 0.8734794138726382, 1.5853169071713897, 1.6400014924345845] | RESULT: 11138.0 -RUN WITH: [0.8118354704659128, 0.9634373141944189, 1.7636724593721786, 1.5662199385632] | RESULT: 10794.0 -RUN WITH: [0.8150009805616482, 1.0092137143383832, 1.274205264719582, 1.5310500464391847] | RESULT: 11918.0 -######## -BEST RESULT -INPUT: [0.8150009805616482, 1.0092137143383832, 1.274205264719582, 1.5310500464391847] -OUTPUT: 11918.0 -######## -``` - ### Python and Jupyter notebooks py_diAID can be imported as a Python package into any Python script or notebook with the command `import pydiaid`. -An ‘nbs’ folder in the GitHub repository contains several Jupyter Notebooks as tutorials on using py_diAID as a Python package. +An ‘nbs’ folder in the GitHub repository contains Jupyter Notebooks as tutorials on using py_diAID as a Python package. --- ## Troubleshooting In case of issues, check out the following links: +* [FAQ](https://github.com/MannLabs/pydiaid#faq): This section provides answers to issues of general interest. * [Issues](https://github.com/MannLabs/pydiaid/issues): Try a few different search terms to find out if a similar problem has been encountered before. * [Discussions](https://github.com/MannLabs/pydiaid/discussions): Check if your problem or feature request has been discussed earlier. +--- +## FAQ +- Where to find test libraries? The py_diAID package includes test libraries for quick workflow testing. These can be found at: py_diAID installation directory\pydiaid\diapasef\static\AlphaPept_results.csv for dia-PASEF and py_diAID installation directory\pydiaid\synchropasef\static\evidence_MaxQuant_270223.txt for synchro-PASEF. +- What is the best input for py_diAID method generation? In general, the best input for py_diAID method generation is dda-PASEF acquired with a wide ion mobility range, for instance, from 0.6-1.6. It provides a complete and unbiased view of the precursor cloud in m/z and the ion mobility plane. In contrast, the data collected with dia-PASEF will present a precursor cloud that is influenced by the position of their isolation windows. The dda-PASEF runs may be an analysis of a single-run representative of the study, or a fractionated peptide library. Both these approaches have yielded comparable isolation window schemes. Regardless of the strategy used, the most critical aspect is a precise ion mobility calibration. +- Using DIA-NN results as input for py_diAID: Regular DIA-NN output information, which does not contain m/z information for precursors, is not suitable as an input for py_diAID. However, we have now included an option to load DIA-NN libraries. These libraries, generated during the analysis of single-runs, can serve as possible input for py_diAID. +- How to specify multiple PTMs? The initial versions of py_diAID could only process one PTM or string input at a time. We have now updated it to allow for filtering of the input library for multiple PTMs. To do this, all PTMs need to be specified in a list of strings, for instance ["STY", "GlyGly"]. --- ## Citations -Check out the [paper](https://doi.org/10.1016/j.mcpro.2022.100279). +Check out the [dia-PASEF publication](https://doi.org/10.1016/j.mcpro.2022.100279) and [synchro-PASEF publication](https://doi.org/10.1016/j.mcpro.2022.100489). --- ## How to contribute diff --git a/nbs/20231129_diaPASEF_method _generation.ipynb b/nbs/20231129_diaPASEF_method _generation.ipynb index 3d24bc1..61e3a86 100644 --- a/nbs/20231129_diaPASEF_method _generation.ipynb +++ b/nbs/20231129_diaPASEF_method _generation.ipynb @@ -26,12 +26,12 @@ "metadata": {}, "outputs": [], "source": [ - "import synchroscan.diapasef.cli as cli #todo" + "import pydiaid.diapasef.cli as cli #todo" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 18, "id": "13911e3d", "metadata": {}, "outputs": [], @@ -40,7 +40,7 @@ " \"input\": {\n", " \"save_at\": r\"D:\\test_optimization\",\n", " \"PTM\": \"None\",\n", - " \"library_name\": r\"D:\\synchroscan\\synchroscan\\diapasef\\static\\AlphaPept_results.csv\",\n", + " \"library_name\": r\"D:\\pydiaid\\pydiaid\\pydiaid\\diapasef\\static\\AlphaPept_results.csv\",\n", " \"analysis_software\": \"AlphaPept\",\n", " },\n", " \"method_parameters\": {\n", @@ -74,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 19, "id": "6fccfdaa", "metadata": {}, "outputs": [ @@ -83,15 +83,15 @@ "output_type": "stream", "text": [ "{'precursors within m/z-range [%]': 97.59}\n", - "RUN WITH: [0.6969575716291646, 0.9748711772026823, 1.5452567104169774, 1.6946958510692274] | RESULT: 10382.0\n", - "RUN WITH: [0.8721722005125272, 1.0337095913227976, 1.6833992517617804, 1.975813036922797] | RESULT: 9758.0\n", - "RUN WITH: [0.5074842921766919, 0.7051156822319278, 0.9513839404192632, 1.342250435852634] | RESULT: 13590.0\n", - "RUN WITH: [0.8715839107761467, 1.179757113242113, 1.455810939638526, 1.6228852039007722] | RESULT: 9865.0\n", - "RUN WITH: [0.5203490354721292, 0.6439071825052647, 1.5106690183613598, 1.6349289377111038] | RESULT: 15560.000000000002\n", + "RUN WITH: [0.8764463330166317, 1.2630948905498791, 1.8024002131993178, 1.9073791106769722] | RESULT: 9758.0\n", + "RUN WITH: [0.8009630510739123, 1.1871295463646983, 1.5705559417639372, 1.629699477934951] | RESULT: 9912.0\n", + "RUN WITH: [0.854409300586086, 1.3363332937194896, 1.4018092556083424, 1.4648813487076182] | RESULT: 10285.0\n", + "RUN WITH: [0.8845853269978934, 1.280953367742227, 1.285317473127582, 1.418751914029719] | RESULT: 10847.0\n", + "RUN WITH: [0.7694987482402109, 1.1605328631452716, 1.6851513689467232, 1.5708094119528933] | RESULT: 10304.0\n", "########\n", "BEST RESULT\n", - "INPUT: [0.5203490354721292, 0.6439071825052647, 1.5106690183613598, 1.6349289377111038]\n", - "OUTPUT: 15560.000000000002\n", + "INPUT: [0.8845853269978934, 1.280953367742227, 1.285317473127582, 1.418751914029719]\n", + "OUTPUT: 10847.0\n", "########\n" ] }, @@ -187,17 +187,17 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 20, "id": "7a83c1ad", "metadata": {}, "outputs": [], "source": [ - "import synchroscan.diapasef.loader as loader" + "import pydiaid.diapasef.loader as loader" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 21, "id": "fc92fc97", "metadata": {}, "outputs": [], @@ -207,7 +207,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 22, "id": "f4e3e695", "metadata": {}, "outputs": [ @@ -363,7 +363,7 @@ "[5395 rows x 5 columns]" ] }, - "execution_count": 14, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -394,14 +394,14 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 23, "id": "63eef647", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", - "import synchroscan.diapasef.loader as loader\n", - "import synchroscan.diapasef.graphs as graphs" + "import pydiaid.diapasef.loader as loader\n", + "import pydiaid.diapasef.graphs as graphs" ] }, { @@ -414,18 +414,18 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 24, "id": "4f3d4c35", "metadata": {}, "outputs": [], "source": [ "lib_name = method_conf[\"input\"][\"library_name\"]\n", - "dia_PASEF = r\"D:\\synchroscan\\synchroscan\\diapasef\\static\\diaPASEF_method.txt\"" + "dia_PASEF = r\"D:\\pydiaid\\pydiaid\\pydiaid\\diapasef\\static\\diaPASEF_method.txt\"" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 25, "id": "a6a7b00d", "metadata": {}, "outputs": [], @@ -439,7 +439,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 26, "id": "b4806119", "metadata": {}, "outputs": [], @@ -458,7 +458,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 27, "id": "66a6a6c8", "metadata": {}, "outputs": [], @@ -471,7 +471,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 28, "id": "25eb8fef", "metadata": {}, "outputs": [ @@ -499,7 +499,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 29, "id": "c8ad871e", "metadata": {}, "outputs": [ @@ -533,26 +533,27 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 30, "id": "0b860e9b", "metadata": {}, "outputs": [ { "data": { "application/javascript": [ + "\n", "(function(root) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", " var force = true;\n", - " var py_version = '3.1.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n", - " var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n", - " var reloading = false;\n", - " var Bokeh = root.Bokeh;\n", - " var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n", "\n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", " root._bokeh_timeout = Date.now() + 5000;\n", " root._bokeh_failed_load = false;\n", " }\n", @@ -564,30 +565,26 @@ " callback();\n", " });\n", " } finally {\n", - " delete root._bokeh_onload_callbacks;\n", + " delete root._bokeh_onload_callbacks\n", " }\n", " console.debug(\"Bokeh: all callbacks have finished\");\n", " }\n", "\n", - " function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n", + " function load_libs(css_urls, js_urls, callback) {\n", " if (css_urls == null) css_urls = [];\n", " if (js_urls == null) js_urls = [];\n", - " if (js_modules == null) js_modules = [];\n", - " if (js_exports == null) js_exports = {};\n", "\n", " root._bokeh_onload_callbacks.push(callback);\n", - "\n", " if (root._bokeh_is_loading > 0) {\n", " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", " return null;\n", " }\n", - " if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n", + " if (js_urls == null || js_urls.length === 0) {\n", " run_callbacks();\n", " return null;\n", " }\n", - " if (!reloading) {\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", "\n", " function on_load() {\n", " root._bokeh_is_loading--;\n", @@ -596,63 +593,13 @@ " run_callbacks()\n", " }\n", " }\n", - " window._bokeh_on_load = on_load\n", "\n", " function on_error() {\n", " console.error(\"failed to load \" + url);\n", " }\n", "\n", - " var skip = [];\n", - " 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Object.keys(js_exports).length;\n", - " }\n", - "\n", - " var existing_stylesheets = []\n", - " var links = document.getElementsByTagName('link')\n", - " for (var i = 0; i < links.length; i++) {\n", - " var link = links[i]\n", - " if (link.href != null) {\n", - "\texisting_stylesheets.push(link.href)\n", - " }\n", - " }\n", " for (var i = 0; i < css_urls.length; i++) {\n", " var url = css_urls[i];\n", - " if (existing_stylesheets.indexOf(url) !== -1) {\n", - "\ton_load()\n", - "\tcontinue;\n", - " }\n", " const element = document.createElement(\"link\");\n", " element.onload = on_load;\n", " element.onerror = on_error;\n", @@ -661,83 +608,25 @@ " element.href = url;\n", " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", " document.body.appendChild(element);\n", - " } if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n", - " var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n", - " for (var i = 0; i < urls.length; i++) {\n", - " skip.push(urls[i])\n", - " }\n", - " } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n", - " var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n", - " for (var i = 0; i < urls.length; i++) {\n", - " skip.push(urls[i])\n", - " }\n", - " } if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n", - " var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n", - " for (var i = 0; i < urls.length; i++) {\n", - " skip.push(urls[i])\n", - " }\n", - " } var existing_scripts = []\n", - " var scripts = document.getElementsByTagName('script')\n", - " for (var i = 0; i < scripts.length; i++) {\n", - " var script = scripts[i]\n", - " if (script.src != null) {\n", - "\texisting_scripts.push(script.src)\n", - " }\n", + " }\n", + "\n", + " var skip = [];\n", + " if (window.requirejs) {\n", + " require([], function() {\n", + " })\n", " }\n", " for (var i = 0; i < js_urls.length; i++) {\n", " var url = js_urls[i];\n", - " if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n", - "\tif (!window.requirejs) {\n", - "\t on_load();\n", - "\t}\n", - "\tcontinue;\n", - " }\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " for (var i = 0; i < js_modules.length; i++) {\n", - " var url = js_modules[i];\n", - " if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n", - "\tif (!window.requirejs) {\n", - "\t on_load();\n", - "\t}\n", - "\tcontinue;\n", - " }\n", + " if (skip.indexOf(url) >= 0) { on_load(); continue; }\n", " var element = document.createElement('script');\n", " element.onload = on_load;\n", " element.onerror = on_error;\n", " element.async = false;\n", " element.src = url;\n", - " element.type = \"module\";\n", " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", " document.head.appendChild(element);\n", " }\n", - " for (const name in js_exports) {\n", - " var url = js_exports[name];\n", - " if (skip.indexOf(url) >= 0 || root[name] != null) {\n", - "\tif (!window.requirejs) {\n", - "\t on_load();\n", - "\t}\n", - "\tcontinue;\n", - " }\n", - " var element = document.createElement('script');\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.type = \"module\";\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " element.textContent = `\n", - " import ${name} from \"${url}\"\n", - " window.${name} = ${name}\n", - " window._bokeh_on_load()\n", - " `\n", - " document.head.appendChild(element);\n", - " }\n", - " if (!js_urls.length && !js_modules.length) {\n", + "\tif (!js_urls.length) {\n", " on_load()\n", " }\n", " };\n", @@ -748,75 +637,40 @@ " document.body.appendChild(element);\n", " }\n", "\n", - " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.1.1.min.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/panel.min.js\"];\n", - " var js_modules = [];\n", - " var js_exports = {};\n", - " var css_urls = [];\n", - " var inline_js = [ function(Bokeh) {\n", + " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\", \"https://unpkg.com/@holoviz/panel@^0.10.3/dist/panel.min.js\"];\n", + " var css_urls = [\"https://unpkg.com/@holoviz/panel@0.10.3/dist/css/alerts.css\", \"https://unpkg.com/@holoviz/panel@0.10.3/dist/css/card.css\", \"https://unpkg.com/@holoviz/panel@0.10.3/dist/css/dataframe.css\", \"https://unpkg.com/@holoviz/panel@0.10.3/dist/css/json.css\", \"https://unpkg.com/@holoviz/panel@0.10.3/dist/css/markdown.css\", \"https://unpkg.com/@holoviz/panel@0.10.3/dist/css/widgets.css\"];\n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", " Bokeh.set_log_level(\"info\");\n", " },\n", - "function(Bokeh) {} // ensure no trailing comma for IE\n", + " function(Bokeh) {} // ensure no trailing comma for IE\n", " ];\n", "\n", " function run_inline_js() {\n", " if ((root.Bokeh !== undefined) || (force === true)) {\n", " for (var i = 0; i < inline_js.length; i++) {\n", " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " // Cache old bokeh versions\n", - " if (Bokeh != undefined && !reloading) {\n", - "\tvar NewBokeh = root.Bokeh;\n", - "\tif (Bokeh.versions === undefined) {\n", - "\t Bokeh.versions = new Map();\n", - "\t}\n", - "\tif (NewBokeh.version !== Bokeh.version) {\n", - "\t Bokeh.versions.set(NewBokeh.version, NewBokeh)\n", - "\t}\n", - "\troot.Bokeh = Bokeh;\n", " }} else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(run_inline_js, 100);\n", " } else if (!root._bokeh_failed_load) {\n", " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", " root._bokeh_failed_load = true;\n", " }\n", - " root._bokeh_is_initializing = false\n", " }\n", "\n", - " function load_or_wait() {\n", - " // Implement a backoff loop that tries to ensure we do not load multiple\n", - " // versions of Bokeh and its dependencies at the same time.\n", - " // In recent versions we use the root._bokeh_is_initializing flag\n", - " // to determine whether there is an ongoing attempt to initialize\n", - " // bokeh, however for backward compatibility we also try to ensure\n", - " // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n", - " // before older versions are fully initialized.\n", - " if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n", - " root._bokeh_is_initializing = false;\n", - " root._bokeh_onload_callbacks = undefined;\n", - " console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n", - " load_or_wait();\n", - " } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n", - " setTimeout(load_or_wait, 100);\n", - " } else {\n", - " Bokeh = root.Bokeh;\n", - " bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n", - " root._bokeh_is_initializing = true\n", - " root._bokeh_onload_callbacks = []\n", - " if (!reloading && (!bokeh_loaded || is_dev)) {\n", - "\troot.Bokeh = undefined;\n", - " }\n", - " load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n", - "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - "\trun_inline_js();\n", - " });\n", - " }\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", " }\n", - " // Give older versions of the autoload script a head-start to ensure\n", - " // they initialize before we start loading newer version.\n", - " setTimeout(load_or_wait, 100)\n", "}(window));" ], - "application/vnd.holoviews_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n var py_version = '3.1.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n var reloading = false;\n var Bokeh = root.Bokeh;\n var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n run_callbacks();\n return null;\n }\n if (!reloading) {\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n var skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n })\n require([\"jspanel-modal\"], function() {\n\ton_load()\n })\n require([\"jspanel-tooltip\"], function() {\n\ton_load()\n })\n require([\"jspanel-hint\"], function() {\n\ton_load()\n })\n require([\"jspanel-layout\"], function() {\n\ton_load()\n })\n require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n })\n require([\"jspanel-dock\"], function() {\n\ton_load()\n })\n require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n })\n require([\"notyf\"], function() {\n\ton_load()\n })\n root._bokeh_is_loading = css_urls.length + 9;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n var existing_stylesheets = []\n var links = document.getElementsByTagName('link')\n for (var i = 0; i < links.length; i++) {\n var link = links[i]\n if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n }\n }\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } var existing_scripts = []\n var scripts = document.getElementsByTagName('script')\n for (var i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n\texisting_scripts.push(script.src)\n }\n }\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (var i = 0; i < js_modules.length; i++) {\n var url = js_modules[i];\n if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n var url = js_exports[name];\n if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.1.1.min.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/panel.min.js\"];\n var js_modules = [];\n var js_exports = {};\n var css_urls = [];\n var inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n // Cache old bokeh versions\n if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n root._bokeh_is_initializing = false\n }\n\n function load_or_wait() {\n // Implement a backoff loop that tries to ensure we do not load multiple\n // versions of Bokeh and its dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n Bokeh = root.Bokeh;\n bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n root._bokeh_is_initializing = true\n root._bokeh_onload_callbacks = []\n if (!reloading && (!bokeh_loaded || is_dev)) {\n\troot.Bokeh = undefined;\n }\n load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n });\n }\n }\n // Give older versions of the autoload script a head-start to ensure\n // they initialize before we start loading newer version.\n setTimeout(load_or_wait, 100)\n}(window));" + "application/vnd.holoviews_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function 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];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" }, "metadata": {}, "output_type": "display_data" @@ -1068,109 +922,6 @@ }, "metadata": {}, "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.holoviews_exec.v0+json": "", - "text/html": [ - "
\n", - "
\n", - "
\n", - "" - ] - }, - "metadata": { - "application/vnd.holoviews_exec.v0+json": { - "id": "4bba8a2d-088e-4512-aa56-30b358278100" - } - }, - "output_type": "display_data" } ], "source": [ @@ -1180,7 +931,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 31, "id": "133d881b", "metadata": {}, "outputs": [ @@ -1209,7 +960,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 32, "id": "7466bb09", "metadata": {}, "outputs": [ @@ -1222,70 +973,36 @@ "data": { "application/vnd.holoviews_exec.v0+json": "", "text/html": [ - "
\n", - "
\n", + "
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n", "
\n", "" ], @@ -1293,10 +1010,10 @@ "PNG(str, align='center', height=345, margin=(0, 20, 0, 0), sizing_mode='fixed', width=460)" ] }, - "execution_count": 34, + "execution_count": 32, "metadata": { "application/vnd.holoviews_exec.v0+json": { - "id": "9d5f7a1f-a339-40a1-8c93-40c7bc1690a2" + "id": "1001" } }, "output_type": "execute_result" @@ -1322,49 +1039,43 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 34, "id": "eef44047", "metadata": {}, "outputs": [], "source": [ - "import synchroscan.diapasef.method_evaluation as evaluator" + "import pydiaid.diapasef.method_evaluation as evaluator" ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 35, "id": "528b2f9e", "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "division by zero quadruply charged precursours are not present\n", - "division by zero singly charged precursours are not present\n" - ] - }, { "data": { "text/plain": [ - "{'unique proteins in the library': 3413,\n", - " 'unique precursors in the library': 19574,\n", + "{'unique proteins in the library': 3420,\n", + " 'unique precursors in the library': 19998,\n", " 'smallest diaPASEF window': 30.05,\n", " 'biggest diaPASEF window': 171.11,\n", " 'average diaPASEF window size': 54.92,\n", - " 'No. of covered proteins': 3386,\n", - " 'No. of covered precursors': 18595,\n", + " 'No. of covered proteins': 3393,\n", + " 'No. of covered precursors': 19004,\n", " 'all proteins covered': '99.2%',\n", " 'all precursors covered': '95.0%',\n", " 'No. of covered, doubly charged precursors': 14933,\n", " 'all doubly charged precursors covered': '96.1%',\n", " 'No. of covered, triply charged precursors': 3662,\n", " 'all triply charged precursors covered': '90.7%',\n", - " 'No. of covered, quadruply charged precursors': 0,\n", - " 'No. of covered, singly charged precursors': 0}" + " 'No. of covered, quadruply charged precursors': 233,\n", + " 'all quadruply charged precursors covered': '97.9%',\n", + " 'No. of covered, singly charged precursors': 171,\n", + " 'all singly charged precursors covered': '94.5%'}" ] }, - "execution_count": 32, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } @@ -1388,9 +1099,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python [conda env:synchro]", + "display_name": "Python [conda env:pydiaid_test]", "language": "python", - "name": "conda-env-synchro-py" + "name": "conda-env-pydiaid_test-py" }, "language_info": { "codemirror_mode": { diff --git a/nbs/20231201_synchroPASEF_method_generation.ipynb b/nbs/20231201_synchroPASEF_method_generation.ipynb index f965caf..5119c67 100644 --- a/nbs/20231201_synchroPASEF_method_generation.ipynb +++ b/nbs/20231201_synchroPASEF_method_generation.ipynb @@ -24,28 +24,38 @@ { "cell_type": "code", "execution_count": 2, + "id": "5a6d529f", + "metadata": {}, + "outputs": [], + "source": [ + "# !pip install pydiaid" + ] + }, + { + "cell_type": "code", + "execution_count": 3, "id": "9153263f", "metadata": {}, "outputs": [], "source": [ - "import synchroscan.synchropasef.loader_proteomics_library as loader_proteomics_library" + "import pydiaid.synchropasef.loader_proteomics_library as loader_proteomics_library" ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 6, "id": "7a83c2d5", "metadata": {}, "outputs": [], "source": [ - "library_name = r\"D:\\Patricia_nature_protocol_paper\\library\\MSFragger_whisper40_library.tsv\"\n", - "analysis_software = \"FragPipe\" #'MaxQuant'\n", - "ptm = \"None\" #Options: 'None', 'Phospho', 'DiGly', [\"EV\", \"LL\"]" + "library_name = r\"D:\\pydiaid\\pydiaid\\pydiaid\\synchropasef\\static\\evidence_MaxQuant_270223.txt\"\n", + "analysis_software = 'MaxQuant'\n", + "ptm = \"None\" #Options: 'None', 'Phospho', 'DiGly', [\"STY\"]" ] }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 7, "id": "98e9e438", "metadata": {}, "outputs": [], @@ -59,7 +69,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 8, "id": "e26441b2", "metadata": {}, "outputs": [ @@ -89,48 +99,54 @@ " Charge\n", " Proteins\n", " Peptide\n", + " IMlength\n", " \n", " \n", " \n", " \n", " 0\n", - " 344.816723\n", - " 0.706492\n", + " 790.074949\n", + " 1.135034\n", " 3\n", - " O43242\n", - " C(UniMod:4)YYYHAR\n", + " sp|P37108|SRP14_HUMAN\n", + " _AAAAAAAAAPAAAATAPTTAATTAATAAQ_\n", + " 0.019912\n", " \n", " \n", - " 7\n", - " 344.827511\n", - " 0.708812\n", - " 3\n", - " Q16658\n", - " GEHGFIGC(UniMod:4)R\n", + " 1\n", + " 478.779816\n", + " 0.885198\n", + " 2\n", + " sp|P36578|RL4_HUMAN\n", + " _AAAAAAALQAK_\n", + " 0.038769\n", " \n", " \n", - " 20\n", - " 345.171915\n", - " 0.709230\n", - " 4\n", - " P49736\n", - " THVDSHGHNVFK\n", + " 2\n", + " 895.991600\n", + " 1.238014\n", + " 2\n", + " sp|Q96P70|IPO9_HUMAN\n", + " _(Acetyl (Protein N-term))AAAAAAGAASGLPGPVAQGLK_\n", + " 0.049322\n", " \n", " \n", - " 41\n", - " 345.176028\n", - " 0.708088\n", - " 3\n", - " Q9Y3C8\n", - " IC(UniMod:4)LTDHFK\n", + " 3\n", + " 642.821886\n", + " 1.014905\n", + " 2\n", + " sp|P28482|MK01_HUMAN\n", + " _(Acetyl (Protein N-term))AAAAAAGAGPEMVR_\n", + " 0.024167\n", " \n", " \n", - " 48\n", - " 345.183072\n", - " 0.710790\n", - " 3\n", - " Q16543\n", - " SMVNTKPEK\n", + " 4\n", + " 659.806433\n", + " 1.008862\n", + " 2\n", + " sp|Q7L5D6|GET4_HUMAN\n", + " _(Acetyl (Protein N-term))AAAAAMAEQESAR_\n", + " 0.016121\n", " \n", " \n", " ...\n", @@ -139,83 +155,102 @@ " ...\n", " ...\n", " ...\n", + " ...\n", " \n", " \n", - " 2802620\n", - " 1279.596945\n", - " 1.276723\n", + " 22585\n", + " 702.867151\n", + " 1.057111\n", " 2\n", - " P43007\n", - " SNETNGYLDSAQAGPAAGPGAPGTAAGR\n", + " sp|P68104|EF1A1_HUMAN;sp|Q5VTE0|EF1A3_HUMAN\n", + " _YYVTIIDAPGHR_\n", + " 0.124890\n", " \n", " \n", - " 2802644\n", - " 1279.658022\n", - " 1.175395\n", + " 22586\n", + " 636.671988\n", + " 0.921844\n", " 3\n", - " P26368\n", - " AM(UniMod:35)QAAGQIPATALLPTM(UniMod:35)TPDGLAV...\n", + " sp|P68104|EF1A1_HUMAN;sp|Q5VTE0|EF1A3_HUMAN\n", + " _YYVTIIDAPGHRDFIK_\n", + " 0.030493\n", " \n", " \n", - " 2802679\n", - " 1280.046716\n", - " 1.279134\n", - " 2\n", - " Q7L2E3\n", - " PSDC(UniMod:4)TLASAQC(UniMod:4)NEYSEEEELVK\n", + " 22587\n", + " 477.755810\n", + " 0.827934\n", + " 4\n", + " sp|P68104|EF1A1_HUMAN;sp|Q5VTE0|EF1A3_HUMAN\n", + " _YYVTIIDAPGHRDFIK_\n", + " 0.016403\n", " \n", " \n", - " 2802695\n", - " 1280.137914\n", - " 1.275783\n", + " 22588\n", + " 934.406374\n", + " 1.137024\n", " 2\n", - " Q4KMQ1\n", - " GDLGPASPSQELGSQPVPGGDGAPALGK\n", + " sp|Q9H501|ESF1_HUMAN\n", + " _YYYAVVDCDSPETASK_\n", + " 0.023890\n", " \n", " \n", - " 2802702\n", - " 1280.156106\n", - " 1.282645\n", + " 22589\n", + " 569.284400\n", + " 0.923876\n", " 2\n", - " Q9UQ35\n", - " TPAALAALSLTGSGTPPTAANYPSSSR\n", + " sp|Q8N183|NDUF2_HUMAN\n", + " _YYYIPQYK_\n", + " 0.024377\n", " \n", " \n", "\n", - "

167850 rows × 5 columns

\n", + "

21878 rows × 6 columns

\n", "
" ], "text/plain": [ - " mz IM Charge Proteins \\\n", - "0 344.816723 0.706492 3 O43242 \n", - "7 344.827511 0.708812 3 Q16658 \n", - "20 345.171915 0.709230 4 P49736 \n", - "41 345.176028 0.708088 3 Q9Y3C8 \n", - "48 345.183072 0.710790 3 Q16543 \n", - "... ... ... ... ... \n", - "2802620 1279.596945 1.276723 2 P43007 \n", - "2802644 1279.658022 1.175395 3 P26368 \n", - "2802679 1280.046716 1.279134 2 Q7L2E3 \n", - "2802695 1280.137914 1.275783 2 Q4KMQ1 \n", - "2802702 1280.156106 1.282645 2 Q9UQ35 \n", + " mz IM Charge \\\n", + "0 790.074949 1.135034 3 \n", + "1 478.779816 0.885198 2 \n", + "2 895.991600 1.238014 2 \n", + "3 642.821886 1.014905 2 \n", + "4 659.806433 1.008862 2 \n", + "... ... ... ... \n", + "22585 702.867151 1.057111 2 \n", + "22586 636.671988 0.921844 3 \n", + "22587 477.755810 0.827934 4 \n", + "22588 934.406374 1.137024 2 \n", + "22589 569.284400 0.923876 2 \n", + "\n", + " Proteins \\\n", + "0 sp|P37108|SRP14_HUMAN \n", + "1 sp|P36578|RL4_HUMAN \n", + "2 sp|Q96P70|IPO9_HUMAN \n", + "3 sp|P28482|MK01_HUMAN \n", + "4 sp|Q7L5D6|GET4_HUMAN \n", + "... ... \n", + "22585 sp|P68104|EF1A1_HUMAN;sp|Q5VTE0|EF1A3_HUMAN \n", + "22586 sp|P68104|EF1A1_HUMAN;sp|Q5VTE0|EF1A3_HUMAN \n", + "22587 sp|P68104|EF1A1_HUMAN;sp|Q5VTE0|EF1A3_HUMAN \n", + "22588 sp|Q9H501|ESF1_HUMAN \n", + "22589 sp|Q8N183|NDUF2_HUMAN \n", "\n", - " Peptide \n", - "0 C(UniMod:4)YYYHAR \n", - "7 GEHGFIGC(UniMod:4)R \n", - "20 THVDSHGHNVFK \n", - "41 IC(UniMod:4)LTDHFK \n", - "48 SMVNTKPEK \n", - "... ... \n", - "2802620 SNETNGYLDSAQAGPAAGPGAPGTAAGR \n", - "2802644 AM(UniMod:35)QAAGQIPATALLPTM(UniMod:35)TPDGLAV... \n", - "2802679 PSDC(UniMod:4)TLASAQC(UniMod:4)NEYSEEEELVK \n", - "2802695 GDLGPASPSQELGSQPVPGGDGAPALGK \n", - "2802702 TPAALAALSLTGSGTPPTAANYPSSSR \n", + " Peptide IMlength \n", + "0 _AAAAAAAAAPAAAATAPTTAATTAATAAQ_ 0.019912 \n", + "1 _AAAAAAALQAK_ 0.038769 \n", + "2 _(Acetyl (Protein N-term))AAAAAAGAASGLPGPVAQGLK_ 0.049322 \n", + "3 _(Acetyl (Protein N-term))AAAAAAGAGPEMVR_ 0.024167 \n", + "4 _(Acetyl (Protein N-term))AAAAAMAEQESAR_ 0.016121 \n", + "... ... ... \n", + "22585 _YYVTIIDAPGHR_ 0.124890 \n", + "22586 _YYVTIIDAPGHRDFIK_ 0.030493 \n", + "22587 _YYVTIIDAPGHRDFIK_ 0.016403 \n", + "22588 _YYYAVVDCDSPETASK_ 0.023890 \n", + "22589 _YYYIPQYK_ 0.024377 \n", "\n", - "[167850 rows x 5 columns]" + "[21878 rows x 6 columns]" ] }, - "execution_count": 44, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -224,38 +259,6 @@ "library" ] }, - { - "cell_type": "code", - "execution_count": 45, - "id": "7c62e4a5-1dd1-488a-8b90-bb71d1e1b90e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0 O43242\n", - "7 Q16658\n", - "20 P49736\n", - "41 Q9Y3C8\n", - "48 Q16543\n", - " ... \n", - "2780443 P68363\n", - "2785727 Q9H165\n", - "2785938 Q8IYI0\n", - "2790263 Q9UGM3\n", - "2800457 Q9ULK2\n", - "Name: Proteins, Length: 9137, dtype: object" - ] - }, - "execution_count": 45, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "library[\"Proteins\"].drop_duplicates()" - ] - }, { "cell_type": "markdown", "id": "6669d67f", @@ -266,14 +269,14 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 24, "id": "8651feb8", "metadata": {}, "outputs": [], "source": [ - "import synchroscan.synchropasef.method_creator as method_creator\n", - "folder_paths = \"D\\synchro_scan_test\"\n", - "method_creator.create_folder(folder_paths)" + "import pydiaid.synchropasef.method_creator as method_creator\n", + "folder_paths = \"D:\\synchro_scan_test\"\n", + "method_creator.create_folder([folder_paths])" ] }, { @@ -286,17 +289,17 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 25, "id": "0ee7593f", "metadata": {}, "outputs": [], "source": [ - "import synchroscan.synchropasef.plots as plots" + "import pydiaid.synchropasef.plots as plots" ] }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 26, "id": "03db56d0", "metadata": {}, "outputs": [], @@ -306,13 +309,13 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 27, "id": "5e3c40a2", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -349,18 +352,18 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 28, "id": "cc82b311", "metadata": {}, "outputs": [], "source": [ - "import synchroscan.synchropasef.method_creator as method_creator\n", - "import synchroscan.synchropasef.method_evaluator as method_evaluator" + "import pydiaid.synchropasef.method_creator as method_creator\n", + "import pydiaid.synchropasef.method_evaluator as method_evaluator" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 29, "id": "40202826", "metadata": {}, "outputs": [], @@ -379,7 +382,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 30, "id": "6dc8631f", "metadata": {}, "outputs": [ @@ -387,43 +390,43 @@ "name": "stdout", "output_type": "stream", "text": [ - "original scan area [(-350.0, 0.38659160885034766), (1610.0, 1.6467084804522232), (-50.0, 0.38659160885034766), (1910.0, 1.6467084804522232)]\n", + "original scan area [(-350.0, 0.3877685793245741), (1610.0, 1.6800081671134248), (-50.0, 0.3877685793245741), (1910.0, 1.6800081671134248)]\n", "please wait\n", "coverage_tests shift_in_mz coverage\n", - "0 -50 0.927220\n", - "1 -45 0.932137\n", - "2 -40 0.936906\n", - "3 -35 0.941454\n", - "4 -30 0.945544\n", - "5 -25 0.949587\n", - "6 -20 0.953391\n", - "7 -15 0.956933\n", - "8 -10 0.960160\n", - "9 -5 0.963101\n", - "10 0 0.965708\n", - "11 5 0.967762\n", - "12 10 0.969507\n", - "13 15 0.970971\n", - "14 20 0.971495\n", - "15 25 0.971412\n", - "16 30 0.970787\n", - "17 35 0.969816\n", - "18 40 0.967977\n", - "19 45 0.965560\n", - "20 50 0.962666\n", + "0 -50 0.913658\n", + "1 -45 0.919097\n", + "2 -40 0.924810\n", + "3 -35 0.930570\n", + "4 -30 0.935232\n", + "5 -25 0.939574\n", + "6 -20 0.943825\n", + "7 -15 0.948761\n", + "8 -10 0.953652\n", + "9 -5 0.957674\n", + "10 0 0.960005\n", + "11 5 0.962154\n", + "12 10 0.963845\n", + "13 15 0.965079\n", + "14 20 0.966222\n", + "15 25 0.965993\n", + "16 30 0.964713\n", + "17 35 0.962337\n", + "18 40 0.959594\n", + "19 45 0.956212\n", + "20 50 0.952921\n", "best_shift 20\n" ] }, { "data": { "text/plain": [ - "[(-330.0, 0.38659160885034766),\n", - " (1630.0, 1.6467084804522232),\n", - " (-30.0, 0.38659160885034766),\n", - " (1930.0, 1.6467084804522232)]" + "[(-330.0, 0.3877685793245741),\n", + " (1630.0, 1.6800081671134248),\n", + " (-30.0, 0.3877685793245741),\n", + " (1930.0, 1.6800081671134248)]" ] }, - "execution_count": 13, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } @@ -447,18 +450,18 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 31, "id": "ca342025", "metadata": {}, "outputs": [ { "data": { - "image/png": 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pb968Dvc3e77cf29juW3bNn3wwQdq1qyZSpQooezZsyt9+vTKli2bSpcurVatWmnChAk6fvy4y+fArSy95MKFC4bj+fPnt+wYefIYPyssNQRzx44d09SpUw3n3n77bRUrVszHHfmfXIUe0PhfhyhvEfN79x7547j6NxmpW1GEcgCM1XqyqgbNfdthKDf1ja992BUAAAAAAEgJ/P06eHKe38WLF3X37l3DW4JevHjRtJ5VvQUHByt79uyGz3M7deqUSpQoYclxXHHo0CEtWLDAcK5FixZO1bAXzN29e1eff/65PvvsM9MVidHR0YqOjtbhw4e1cOFC9enTRw0aNNCgQYP02GOPOdUDK+a8JCIiwnDc7JvMHWa1Ll++bNkxvKV///6Ki4tLMp4nTx4NHDgwGTryL4RyAKxQq6UTodzHhHIAAAAAAKRV/n4dPDnPz2az6erVqy71lTVrVmXMmNHrvSVXBtG/f38lJiYaznXu3NmpGjt37jQcP336tMqUKaNevXqZhnJm1q1bp4YNG+q5554zvEvgfxHMeYnZN0Z4eLhlxwgLCzMcN0qwU5Lff/9d8+bNM5x77733lDlzZh935F9yF87pMJQ7/DuhHAD7arWsqkE/OhHKvUkoBwAAAABI4ZL9mXBeeKUQ/n4dPDnPTzI/R1/0JaWsDOLHH3/UokWLDOcaNWqkypUrO1XHbMXcwIEDDZ8954off/xRDz/8sMPnAxLMeUF8fLyio6MN57JkyWLZccxqpfRgbtiwYYbjDz74oLp27erjbvxL7sI5NW7NYIeh3DtPEMoBMOdMKDdv0lJCOQAAAAAA0rC0cB382rVrhuNWnl9wcLCCg4MN58zO0Rd92avn6wzizJkz6tGjh+FcYGCgPvjgA6fqxMbGurwazlWnT5/WI488oh07dphuQzDnBXfu3DGds/IbIzQ01HD89u2UG7j8+eefWrp0qeHc0KFDTX8AwbF7K+Uch3L9m4wglANgqlbLqhrs4PaV8yYt1advfeO7pgAAAAAAQIqTFq6Dm52j1QGYq+eYUvvyhlu3bqlVq1amYeRrr72matWqOVVr//79ho/Y+q/8+fPr7bff1tKlS3XixAlFRkbqzJkz+uOPP/T555/r6aefNnz2333Xr19X8+bNTZ+DaH7VDW67e/eu6VxQUJBlx0mf3vjL58wHK7kMHz7ccLx06dJ6/vnnfdrL5cuXdeXKFZf2OXbsmJe68cz9UC7Pg45Duds3YnzYGYDUpPZT1TTox95KH2T+nwc/f7REn/We4cOuAAAAAACAPe5cs8yZM6dy5TK/luiMtHAd3OwcrTw/yfVzTKl9WS02NlZt2rQxfS5cyZIlNW7cOKfrmd3G8r6QkBCNHj1a3bt3T7KIKHv27CpYsKCqVKmirl276tSpU3r33Xc1e/Zsw1oRERHq0KGD1q9fn+R9JJjzgtjYWNM5sw+yO5L7m8JVR44cMb0HbJ8+fRQY6NsFnFOnTjW9rWZq4kwod2j7Mb3zxEhCOXhF/Jnzyd0CPBFw72dv7aeqatAPbzkI5Zbqs7e/+3sfAAAAAICvBUop5/FiSCFatWrl8j5DhgzR0KFDPTpuWrgObnaOVp6fvXpm55hS+7JSfHy8OnTooJUrVxrOh4aGau7cucqcObPTNc0CPkkqVaqU5s6dqwoVKjhV68EHH9SsWbNUp04d9erVSwkJCUm22bJli6ZOnapevXr9a5wra15g70Ppix9I8fHxlh3DSlOmTJHN4MGkefLkUadOnZKho9TPmVDu4LajhHIA7KrTqprDUO6nD5fos7e/9WFXAAAAAABYxGbzv1cKkBaug5udo68CMLNzTKl9WSUuLk7t27fXzz//bDgfGBio7777ThUrVnSprtmKucKFC2vjxo1Oh3L/1KNHD02bNs10ftiwYUlu/cmKOS9Ily6d6ZxRauousw9/SnxO261btzRjhvGtz3r27Gn3fqwwlufBnBr/6xDlLpzTdJuD245qQNMPCOUAmKrTqprem/Omw1BuWp/vfNgVAAAAAABI6dLCdXCzc7Ty/CTXzzGl9mWFu3fvqk2bNlqyZInpNtOmTXNrpeioUaN06NAhnThx4u/XxYsXtWDBAj3wwANu9/zyyy/rt99+03ffJb1+FhkZqRkzZqhHjx5/jxHMeYG9D6WVSbJZrZQYcn377beKjo5OMp45c2Z17949GTq6l2Q/++yzLu1z7Ngxt77hreZsKPfOEyMVE/2XDzsDkJrUfbq63v3+Dfuh3MQlmtaXUA4AAAAAgJRqwYIFKl68uEv75Mxpfl3RWWnhOrjZOVq9YszVc0ypfXnqxo0beuqpp/Tbb7+ZbvPhhx/qlVdecat+nTp1VKdOHXfbs2vMmDH68ccfDZ//N3v2bII5b7P3A8nKe6+mpmDuyy+/NBxv3769smfP7uNu7smVK5fHDzhNDnmK5NL4NYMJ5QB4hFAOAAAAAAD/ULx4cZUrV87nx00L18HNztHqZ6xZFcwld1+euHDhgpo1a6bdu3cbzgcEBGjy5Ml6/fXXLT+2FfLmzatOnTpp+vTpSea2bNmiqKgohYWFSeIZc14RGhqqgIAAw7n/3kvUEzdv3jQcT2nB3IEDB0wfqvjyyy/7uJvUzalQbiuhHAD76rZ2HMrNnbCYUA4AAAAA4B8S/fCVAqSF6+BZsmQxHLfy/CTXzzGl9uWuffv2qUaNGqahXLp06fT555+n2FDuvpYtWxqOJyYmatu2bX//m2DOC9KlS6ds2bIZzpl9kN1x69Ytw/EcOXJYdgwrzJw503C8bNmyqlmzpo+7Sb3yFMmlCY5uX7n1qN5pSigHwFzd1tX13vf2nyk3d8Jifd7P+Gc3AAAAAACAlDaug5sdw8rzi42NNV3pZnZ8X/Ql+ea9X7FiherUqaNz584ZzmfIkEFz5851+/aVvlSvXj0FBhrHbocOHfr7fxPMeUl4eLjheFRUlGXHuH79uuF47ty5LTuGp2w2m2bPnm0499JLL/m4m9TrfiiXq5D5AygPbDlCKAfArvuhXLr05g9n/nH8IkI5AAAAAADgFH+/Dp6c5yeZn6Mv+pK8/95PmTJFLVq0UHR0tOF81qxZtWLFCj399NOWHM/bsmfPbvre/DN4JJjzknz58hmOR0REWHYMs1op6blpv//+u06fPp1kPDAwUJ06dUqGjlKfvEVzOxXKDWj2AaEcAFP1nqnhMJT7YdwifdF/lg+7AgAAAAAAqZm/XwdPzvMLCgpS9uzZXeorMjLS9LlwVvbm6XufkJCgN954Qz179lRCQoLhNgULFtTGjRvVoEEDj47la86sZiSY85IiRYoYjl+8eNGyY1y6dMlw3OybMjksWbLEcLxu3bopamVfSpW3aG6NXzPYcSjXlFAOgLl6z9TQu7PfcBjKffkOoRwAAAAAwB/ZFGDzn5dkS+439G/+fh08Oc8vb968pvsUKlTI8JaJNpvNtJ6r7t69a7pizpP3PiYmRq1atdLHH39suk2lSpW0detWVahQwe3jJBez27vabP/3fUsw5yVFixY1HD9x4oRlxzh+/LjheJkyZSw7hqeWLl1qON66dWsfd5L65C2aW+N/dTKUu0koB8DYI21qOg7lxi4klAMAAAAAAC7z9+vgZud35swZ05VernLn/IKCglSwYEHDOavee7M6GTNmVOHChd2qef36dTVq1Mh0QY8kPfHEE9qwYUOKWoDkCrPbcv5zJR3BnJeULVvWcPzo0aOWHcOsVrly5Sw7hicuXLignTt3Gs4RzNmXr9j/D+UKmody+zcfJpQDYNcjbWpq4KxejkO5AcbPAgUAAAAAALDH36+DFypUSKGhoUnG4+LidOrUKUuO4e75efu9N6tTpkwZw9V6jly6dEn16tXTli1bTLfp3r27lixZoixZsrhcP6WIjIw0HP9nMJfeV82kNVWrVjUc37Nnj2w2mwICAjyqf/r0acNlpOnTp1epUqU8qm2VVatW/Wt55n1Vq1Y1TfNxL5Qbt8ZxKDew2ShCOQCmHnm2pgbOtB/KzRmzQNMHfu/DrgAAAAAAgD/x9+vggYGBqly5sjZs2JBkbteuXSpWrJjHxzBb3OIomKtataqWL19u2JcV3O3LyKVLl9SgQQMdPnzYcD4wMFDjxo1T7969Xa7trJMnTyoiIkKXL1/+16tZs2Zq3LixJce4c+eOLl++bDj3z1uTEsx5SdGiRZUjRw5du3btX+PR0dE6dOiQx8tst2/fbjherVo1BQcHe1TbKkY/rCTp8ccf93Enqce9lXJDlLOA8QMiJWn/psMa2JxQDoA5QjkAAAAAAOALaeE6eLVq1QyvdW/fvl3PPPOMR7UTEhK0Y8cOw7m6des67MuI2XvmKrM6jvr6r6tXr+rRRx81DeVCQkI0c+ZMj99LRxo1amR4e85bt25ZFsxt27ZNcXFxhnO1atX6+39zK0svatiwoeH4qlWrPK69YsUKw/FGjRp5XNsqZsFcgwYNfNtIKkEoB8AK9dvWchjKfT+aUA4AAAAAkIbYbP73SkH8/Tq42bGsOL/Nmzfr5s2bScYLFiyokiVL2t23fv36CgoKSjK+Y8cO09spOuvu3bv67bffDOdcee9jYmL05JNP6tChQ4bz2bNn1y+//OL1UE6Sypcvbzi+detWy46xbt06w/H8+fOrSJEif/+bYM6LmjZtajg+b948j+rGxcWZPhzRqmTXUxEREYb3oA0KClKdOnWSoaOULX/xPE6FcgOa8Uw5AObqt62lAd/1dBjKffUuoRwAAAAAALCGv18Hb9CggUJCQpKM79q1y3AFlivmz59vOO7M+WXNmlW1a9dOMp6QkKCFCxd61NfKlSt1+/btJOPFihVT0aJFna7TpUsX0+ArT548+u2333yWF1SoUMFwfP/+/Tp48KDH9ePj4/Xll18azv03vCaY86KWLVsqQ4YMScbXr1+vAwcOuF133rx5hvcpLVq0aIoJvcy+2cqUKaPMmTP7uJuULX/xPBq3ZrB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"text/plain": [ "" ] }, - "execution_count": 14, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" }, @@ -486,27 +489,27 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 32, "id": "a622935c", "metadata": {}, "outputs": [], "source": [ - "import synchroscan.synchropasef.method_evaluator as method_evaluator" + "import pydiaid.synchropasef.method_evaluator as method_evaluator" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 33, "id": "ad2310fa", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.9714950795077721" + "0.9662217752993875" ] }, - "execution_count": 16, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -549,39 +552,20 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 44, "id": "4cf3291f", "metadata": {}, "outputs": [], "source": [ - "import synchroscan.synchropasef.method_creator as method_creator" + "import pydiaid.synchropasef.method_creator as method_creator" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 63, "id": "898f5dc9", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{} (-30.0, 0.38659160885034766) (1930.0, 1.6467084804522232)\n", - "{} (-330.0, 0.38659160885034766) (1630.0, 1.6467084804522232)\n" - ] - }, - { - "data": { - "text/plain": [ - "([1, 1, 1, 1], 4)" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "save_at = r\"D:\\synchro_scan_test\"\n", "\n", @@ -593,7 +577,7 @@ "}\n", "\n", "method_parameters = {\n", - " \"scans\": 4,\n", + " \"scans\": 3,\n", " \"window_type\": \"equidistant\",\n", " \"scan_ratio\": [1, 1, 1, 1, 1],\n", " \"scan_mode\": 'classical_synchro-PASEF',\n", @@ -607,7 +591,7 @@ " \"dict_im_limits\": {'low_limit_IM': 0.7,'up_limit_IM': 1.3}\n", "}\n", "\n", - "method_creator.create_method(\n", + "_ = method_creator.create_method(\n", " save_at,\n", " scan_area_dict[\"scan_area\"],\n", " method_parameters,\n", @@ -626,664 +610,17 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 64, "id": "50d1ff59", "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - " var py_version = '3.1.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n", - " var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n", - " var reloading = false;\n", - " var Bokeh = root.Bokeh;\n", - " var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n", - "\n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks;\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - " if (js_modules == null) js_modules = [];\n", - " if (js_exports == null) js_exports = {};\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - "\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " if (!reloading) {\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " }\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - " window._bokeh_on_load = on_load\n", - "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " var skip = [];\n", - " if (window.requirejs) {\n", - " window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n", - " require([\"jspanel\"], function(jsPanel) {\n", - "\twindow.jsPanel = jsPanel\n", - "\ton_load()\n", - " })\n", - " require([\"jspanel-modal\"], function() {\n", - "\ton_load()\n", - " })\n", - " require([\"jspanel-tooltip\"], function() {\n", - "\ton_load()\n", - " })\n", - " require([\"jspanel-hint\"], function() {\n", - "\ton_load()\n", - " })\n", - " require([\"jspanel-layout\"], function() {\n", - "\ton_load()\n", - " })\n", - " require([\"jspanel-contextmenu\"], function() {\n", - "\ton_load()\n", - " })\n", - " require([\"jspanel-dock\"], function() {\n", - "\ton_load()\n", - " })\n", - " require([\"gridstack\"], function(GridStack) {\n", - "\twindow.GridStack = GridStack\n", - "\ton_load()\n", - " })\n", - " require([\"notyf\"], function() {\n", - "\ton_load()\n", - " })\n", - " root._bokeh_is_loading = css_urls.length + 9;\n", - " } else {\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n", - " }\n", - "\n", - " var existing_stylesheets = []\n", - " var links = document.getElementsByTagName('link')\n", - " for (var i = 0; i < links.length; i++) {\n", - " var link = links[i]\n", - " if (link.href != null) {\n", - "\texisting_stylesheets.push(link.href)\n", - " }\n", - " }\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " if (existing_stylesheets.indexOf(url) !== -1) {\n", - "\ton_load()\n", - "\tcontinue;\n", - " }\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " } if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n", - " var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n", - " for (var i = 0; i < urls.length; i++) {\n", - " skip.push(urls[i])\n", - " }\n", - " } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n", - " var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n", - " for (var i = 0; i < urls.length; i++) {\n", - " skip.push(urls[i])\n", - " }\n", - " } if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n", - " var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n", - " for (var i = 0; i < urls.length; i++) {\n", - " skip.push(urls[i])\n", - " }\n", - " } var existing_scripts = []\n", - " var scripts = document.getElementsByTagName('script')\n", - " for (var i = 0; i < scripts.length; i++) {\n", - " var script = scripts[i]\n", - " if (script.src != null) {\n", - "\texisting_scripts.push(script.src)\n", - " }\n", - " }\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n", - "\tif (!window.requirejs) {\n", - "\t on_load();\n", - "\t}\n", - "\tcontinue;\n", - " }\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " for (var i = 0; i < js_modules.length; i++) {\n", - " var url = js_modules[i];\n", - " if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n", - "\tif (!window.requirejs) {\n", - "\t on_load();\n", - "\t}\n", - "\tcontinue;\n", - " }\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " element.type = \"module\";\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " for (const name in js_exports) {\n", - " var url = js_exports[name];\n", - " if (skip.indexOf(url) >= 0 || root[name] != null) {\n", - "\tif (!window.requirejs) {\n", - "\t on_load();\n", - "\t}\n", - "\tcontinue;\n", - " }\n", - " var element = document.createElement('script');\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.type = \"module\";\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " element.textContent = `\n", - " import ${name} from \"${url}\"\n", - " window.${name} = ${name}\n", - " window._bokeh_on_load()\n", - " `\n", - " document.head.appendChild(element);\n", - " }\n", - " if (!js_urls.length && !js_modules.length) {\n", - " on_load()\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.1.1.min.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/panel.min.js\"];\n", - " var js_modules = [];\n", - " var js_exports = {};\n", - " var css_urls = [];\n", - " var inline_js = [ function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - "function(Bokeh) {} // ensure no trailing comma for IE\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " if ((root.Bokeh !== undefined) || (force === true)) {\n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " // Cache old bokeh versions\n", - " if (Bokeh != undefined && !reloading) {\n", - "\tvar NewBokeh = root.Bokeh;\n", - "\tif (Bokeh.versions === undefined) {\n", - "\t Bokeh.versions = new Map();\n", - "\t}\n", - "\tif (NewBokeh.version !== Bokeh.version) {\n", - "\t Bokeh.versions.set(NewBokeh.version, NewBokeh)\n", - "\t}\n", - "\troot.Bokeh = Bokeh;\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " }\n", - " root._bokeh_is_initializing = false\n", - " }\n", - "\n", - " function load_or_wait() {\n", - " // Implement a backoff loop that tries to ensure we do not load multiple\n", - " // versions of Bokeh and its dependencies at the same time.\n", - " // In recent versions we use the root._bokeh_is_initializing flag\n", - " // to determine whether there is an ongoing attempt to initialize\n", - " // bokeh, however for backward compatibility we also try to ensure\n", - " // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n", - " // before older versions are fully initialized.\n", - " if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n", - " root._bokeh_is_initializing = false;\n", - " root._bokeh_onload_callbacks = undefined;\n", - " console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n", - " load_or_wait();\n", - " } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n", - " setTimeout(load_or_wait, 100);\n", - " } else {\n", - " Bokeh = root.Bokeh;\n", - " bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n", - " root._bokeh_is_initializing = true\n", - " root._bokeh_onload_callbacks = []\n", - " if (!reloading && (!bokeh_loaded || is_dev)) {\n", - "\troot.Bokeh = undefined;\n", - " }\n", - " load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n", - "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - "\trun_inline_js();\n", - " });\n", - " }\n", - " }\n", - " // Give older versions of the autoload script a head-start to ensure\n", - " // they initialize before we start loading newer version.\n", - " setTimeout(load_or_wait, 100)\n", - "}(window));" - ], - "application/vnd.holoviews_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n var py_version = '3.1.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n var reloading = false;\n var Bokeh = root.Bokeh;\n var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n run_callbacks();\n return null;\n }\n if (!reloading) {\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n var skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n })\n require([\"jspanel-modal\"], function() {\n\ton_load()\n })\n require([\"jspanel-tooltip\"], function() {\n\ton_load()\n })\n require([\"jspanel-hint\"], function() {\n\ton_load()\n })\n require([\"jspanel-layout\"], function() {\n\ton_load()\n })\n require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n })\n require([\"jspanel-dock\"], function() {\n\ton_load()\n })\n require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n })\n require([\"notyf\"], function() {\n\ton_load()\n })\n root._bokeh_is_loading = css_urls.length + 9;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n var existing_stylesheets = []\n var links = document.getElementsByTagName('link')\n for (var i = 0; i < links.length; i++) {\n var link = links[i]\n if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n }\n }\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 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\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "import synchroscan.synchropasef.loader_MS_parameter_file as loader_MS_parameter_file" + "import pydiaid.synchropasef.loader_MS_parameter_file as loader_MS_parameter_file" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 65, "id": "b8a9fe3f", "metadata": {}, "outputs": [ @@ -1330,37 +667,28 @@ " 1\n", " vista\n", " 0.7\n", - " 157.5\n", - " 232.5\n", + " 143.6\n", + " 243.6\n", " 1.3\n", - " 1090.7\n", + " 1053.6\n", " \n", " \n", " 2\n", " vista\n", " 0.7\n", - " 232.5\n", - " 307.5\n", + " 243.6\n", + " 343.6\n", " 1.3\n", - " 1165.7\n", + " 1153.6\n", " \n", " \n", " 3\n", " vista\n", " 0.7\n", - " 307.5\n", - " 382.5\n", + " 343.6\n", + " 443.6\n", " 1.3\n", - " 1240.7\n", - " \n", - " \n", - " 4\n", - " vista\n", - " 0.7\n", - " 382.5\n", - " 457.5\n", - " 1.3\n", - " 1315.7\n", + " 1253.6\n", " \n", " \n", "\n", @@ -1369,26 +697,24 @@ "text/plain": [ " type mobility pos.1 [1/K0] mass pos.1 start [m/z] mass pos.1 end [m/z] \\\n", "0 ms - - - \n", - "1 vista 0.7 157.5 232.5 \n", - "2 vista 0.7 232.5 307.5 \n", - "3 vista 0.7 307.5 382.5 \n", - "4 vista 0.7 382.5 457.5 \n", + "1 vista 0.7 143.6 243.6 \n", + "2 vista 0.7 243.6 343.6 \n", + "3 vista 0.7 343.6 443.6 \n", "\n", " mobility pos.2 [1/K0] mass pos.2 start [m/z] \n", "0 - - \n", - "1 1.3 1090.7 \n", - "2 1.3 1165.7 \n", - "3 1.3 1240.7 \n", - "4 1.3 1315.7 " + "1 1.3 1053.6 \n", + "2 1.3 1153.6 \n", + "3 1.3 1253.6 " ] }, - "execution_count": 20, + "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "open_name = r\"D:\\synchro_scan_test\\synchroScan.txt\"\n", + "open_name = r\"D:\\synchro_scan_test\\synchroPasef.txt\"\n", "\n", "df_parameters_final = loader_MS_parameter_file.load_MS_method_from_txt_file(\n", " open_name,\n", @@ -1406,28 +732,28 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 66, "id": "04845c85", "metadata": {}, "outputs": [], "source": [ - "import synchroscan.synchropasef.plots as plots" + "import pydiaid.synchropasef.plots as plots" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 74, "id": "5ad80537", "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ "" ] }, - "execution_count": 22, + "execution_count": 74, "metadata": {}, "output_type": "execute_result" }, @@ -1444,25 +770,25 @@ "source": [ "plots.plot_acquisition_scheme(\n", " df_parameters_final,\n", - " folder_paths + \"acquisition_scheme.png\"\n", + " folder_paths + \"/acquisition_scheme.png\"\n", ")\n", - "Image(folder_paths + \"acquisition_scheme.png\")" + "Image(folder_paths + \"/acquisition_scheme.png\")" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 75, "id": "b3c9e9fe", "metadata": {}, "outputs": [ { "data": { - "image/png": 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S3xc6qtwtrk/0OXXsrIZ0HKe9fxF9AwAAAAAAAP6Gxsx3TJ970/jYDqbXTs3zntkff1qYht8dOnTg0OY0SkhIMJoLCAhQZGTkvz9nx0L/lSdPHsXGxlqOvx0Ox9XoOyYmRj///LMmTpyosLAwmzeGK0WKFDF+F42vXhxNrxseHq4SJVyfPAVr/vjjD6O5mjVr2rwJAACAPRwOhx59+0Gj6Hsy0TdSgegbduvfoLaalClhFH2PJ/qGRcEhQeo7vJNR9D2003iibwAAAAAAAMBP0Zj5TrVq1YzmMkL4XLFiRcv3ndkff2qtXbtW+/btM5rt0KGDzdv4vyNHjhjN5c2bV4GB//6+sVfC75SLx8bGqmzZskbxd0rwLUk1atTQhg0b1LJlS2+sCgM1atQwmlu7dq3Nm9zYmjVrjOYqVap03T8USJvZs2cbzd1yyy02bwIAAOB5KdF3677NXM6lRN9/EX3DouKRVqLvgUTfsMw4+t5E9A3rgkMCr0TfNV3/GNFTx85qKCd9AwAAAAAAAH6Pxsw3TA/k3Llzp+Lj423e5sZMn3vTiPtapo/fV193p0+f1p49e4xmU/P4U+u3334zmsudO7duu+02m7fxf/v37zeaK1y48HWf81r4LV2Jv+fOnWs5/l6/fr0WL17spS1hwvTFcfny5TZvkrbrVq9e3eZNMh/T8Lthw4Y2bwIAAOBZDodDj00h+oZ9SkQW0KOlrUTfJ7y0GfxF/wZ11LRsSYPoe5/Gv0v0DWuCQwL10OO3m0ffWw97aTMAAAAAAAAAvkJj5hv58+dXvnz53M4lJydr5cqVXtjo3xISErRhwwaj2dQ891bC74sXL1q+/7RasWLF1UORXYmMjFTp0qW9sNEVCxYsMJpr1qxZun0jRFJSkg4fPqx169Zpzpw5+vTTTzV+/Hg988wz6tu3r9q2bau6detq1qxZPt3zzJkzOnTI7HCcG30NBHl6IXdS4u/GjRtry5Yt/zrZ+1opYbjD4dDFixfVuXNnfffdd2rRooW3V8YNmJ7WvGLFCps3uTHTP5Tr1atn8yaZy8aNG7Vr1y63c6GhoTz3AAAgQ0mJvu94wCD6fuID/bVih5c2g7+4En3frUCib9jkkYZ11KSM+x9DuXbTPk14d579C8GvXI2+KxVyOXfy6BkN6zSe6BsAAAAAAADIJGjMfOeWW27R999/73ZuxYoVatSokf0LXePPP//U5cuX3c6Fh4enKvwuVaqUsmbNqjNnzricu3jxotauXWv8deoppl93derU8Vpg7XQ6tWjRIqPZxo0b27xN6sybN09NmjQxiurnzp2rli1bemGrG/vzzz+N9pRu/JMTvHrid4q8efMqNjbW7cnfKQ/M4XAoMTFR7du319y5nDiVHtSvX9/tCWGStHnzZh05csQLG/1j//792r7d7HTFBg0a2LyNvS5fvqyDBw/qzz//1M8//6z33ntPr7zyij799FOf7GN63dtuu03h4eE2bwMAAOAZptF3YsJFom+kSonIAnq0DNE37DOA6Bs2CgkJIvoGAAAAAAAAcEM0Zr5juvO8efPsXSQN16xTp46Cg4Mt37/D4dBtt93m0V08yfSa3vy6W79+vU6dOmU0m17D78KFCxvH1MuWLbN5G9diY2ONZ290gr1Pwm9JiomJUWxsrMqUKWMcfyckJOiuu+4yfmcB7JM7d26jH4ngdDr1888/e2Gjf/z4449Gc6VKlVLhwoVt3sazEhIS1KJFC1WuXFl58uRRSEiIChQooBo1aqh169a6//779cwzz+j111/3+m5Op9M4/O7QoYPN2wAAAHiGw+HQ4+88ZBR9v030jVS4Gn07iL5hjwEN66qxQfS9ZiPRN6wLCQnSg4+3MIq+h3Yk+gYAAAAAAMhIHJIcTj5s+fD1b64X0Zj5TqtWrYzm5s6dq4SEBJu3+bcffvjBaK5ZM9ffo3XF9PGbfh14SlxcnObPn280m5bHb9WCBQuM5goWLKiSJUvavE3qFC5cWCEhIUazq1atMjp13i6mr3fR0dGqXbv2dZ/3WfgtXYm/586dayn+PnfunFq3bq2lS5d6c1XcgOmLo+kLtaeYvhjfeeedNm/ieeHh4frzzz+1fv16HTt27KbvUFm/fr3i4uK8utvs2bO1c+dOt3MBAQGE3wAAIENIib5b3d/U5VxiwkVNfpzoG9ZZi74HEH3DsgGN6qpxmeJu59Zs3KeJ782zfyH4FSsnfQ/tOF77thF9AwAAAAAAAJkRjZlvlC9fXkWKFHE7l5CQoN9++80LG11x5MgRrVixwmg2Lc+96dfd4sWLdfLkyVRfx6rZs2fr0qVLbudy586tOnXqeGGjK0zD70aNGtm7SBoEBQWpWrVqRrPx8fH69ddfbd7oxjZs2KA///zTaLZ58+YKCgq67vPXf8bLUuLvRo0aadu2bXI4HDeMWVPCcIfDobi4OLVq1Uq///67atSo4YOtIUl33HGHRowY4Xbup59+0rFjx5Q7d27bdzpw4IBmz55tNNu+fXubt7FH+fLltXDhQpczSUlJ+uOPP9SyZUsvbSWNGzfOaK5ly5bKmzevvcsAAAD/57D3PaxXou8H1eq+Ji7nEhMuavIT07V11U7J4ZAjwHXA6ysB2aJ9vcJ1Dt4S7usVbujLIj9550JB5eTI+pgcxtG39/7CydSyxPT39b51e35fr3BD2Q+a/Vg5T3qw3a26rbT76Hvt2r2aPHmO7/+C6G/JgenzrJvAhCRfr3CdgBNnfXbtkJAg9R3eXmUrFXQ5d/LIaQ2+41Xt++uQlza7MefFiz69/k05k329AQAAAAAAAGA7GjPfadWqld5++223c++//77uuusuL2wkffDBB0pOdv93oyVLllSlSpVSfZ1ixYqpbNmy2rJli8u5y5cva8aMGXr00UdTfS0r3n33XaO5u+66SwEB3jvXedGiRUZzt956q82bpE3dunW1bNkyo9kPPvhAd9xxh80bXW/y5MnGs507d77h53164neKmJgYzZs3T6VKlZIko5O/z5w5oxYtWmjdunVe2xP/VqtWLRUrVszt3MWLFzVt2jQvbCRNmTLF6Aj+smXLqn79+l7YyPNM38nz2Wef2bzJP5YsWWL8L0MPPvigzdsAAACkjeXoeyUnfcOioPJyZB0hh8N1autMPp9uo2+kbw+1v1W3VTU46XvtXr01eY4XNoI/CQkJ0oPD26tstaIu504eOa3BrXwffQMAAAAAAADwLRoz3+nSpYvR3A8//KD9+/fbvI2UnJxsFKJL0v3335/m65k+ftOd0mrHjh3Gjd0DDzxg8zb/OHjwoA4dMvu7/IoVK9q8Tdo0b97cePb777/XqVOnbNzmenv37jWO/3PkyKF27drd8NfSRfgt/XPyt5X4+9SpU2rWrJk2bdrktT3xD4fDofvuu89odsKECYqLi7N1n5MnT+qtt94ymu3bt6+tu9jptttuM5r76quvFB8fb/M2Vzz55JNGc8WKFVObNm1s3gYAACD1HA6Hnpj6kFH0/dbjRN9IhaDycmR90TD6Hkj0Dcsean+r6ldxH32v2rxPk4m+YVFK9F3GTfR94vDf0fdWom8AAAAAAAAgs6Mx851GjRqpZMmSbueSkpI0atQo2/eZMWOGdu/e7XYuODhYffr0SfP17rvvPqNTs7ds2aIvv/wyzddzZ+TIkVf7V1cqVapkfDisJ6xZs8Z4Nr2H302bNlVUVJTRbGJiot544w2bN/q3wYMHKzEx0Wi2V69eCg0NveGvpZvwW5Ly5ctnOf4+fvy4mjZtqq1bt3ptT/yjT58+Cgx0/+O9Dx8+bPQjO9Li+eef14kTJ9zOhYaG6t5777V1Fzs1btxYYWFhbufOnTunjz/+2PZ9Jk2apCVLlhjNPvXUU0ZfLwAAAL6QEn237NPY5VxK9L1tFdE3LAqqQPQNW/XrYBZ9r9y8T+M+n++FjeBPrETfQ+4g+gYAAAAAAADwDxoz3zE9OXvKlClat26dbXvExcVp6NChRrN33nmn8ubNm+ZrFi5c2PgE6P/9739KSEhI8zVvZvny5Zo+fbrRrLffcLB27VqjuQIFCih79uw2b5M2oaGh6tixo/H8m2++qZ07d9q40T9mzpypzz//3Gg2NDTU5WG86Sr8lv6Jv1PeaWISfx85ckRNmjTRjh2EF95WoEAB4xOcx40bp4ULF9qyx6+//qrJkycbzXbu3Fm5cuWyZQ9vyJIli1q0aGE0O3z4cFvfBbdu3ToNHjzYaLZQoUIeeScWAACAHSxF3499QPQN64IqyJF1ONE3bNOvw62qV9ks+h5P9A2LQkKC9OCLHdxG3yePnCH6BgAAAAAAAHAdGjPf6d27901PDb5WUlKS7r33Xtvi5/79++vw4cPGs57Sr18/o7m9e/fqscce89h1rxUfH69evXoZnfadJUsW9ezZ05Y9bsb0xO/0ftp3igEDBhjPJiYmauDAgUa/N2mxefNm4598IF15w0aBAgVu+uvpLvyWrsTf8+bNsxR/Hzx4UE2bNtWePXu8tieueOGFF276e3Sty5cvq0uXLtq/f79Hr79r1y51795dycnJbmeDg4M1fPhwj17fF3r16mU0d/jwYb300ku27LB37161atXK+A/7UaNGGZ1UDgAA4G0BAQ49Oa2f2+j7QkLilej7T++84xd+xFL0PYDoG5Y93KEe0TdsExL6d/RdtYjLuZNHzmhw54lE3wAAAAAAAP7EyYctH5kUjZlvxMTEGMfPa9eu1UMPPeTxHSZNmqSPPvrIaLZJkyZq2rSpx67dtm1bVa1a1Wj2nXfe0bvvvuuxa0tXGtf77rtPW7ZsMZofPHiwsmXL5tEd3DENvytUqGDvIh5So0YNNWzY0Hj+559/1lNPPWXbPnv37lXr1q119uxZo/kcOXLoxRdfdDmTLsNv6d8nfzudTqP4e+/evWrSpIkOHDjgzVUzvWrVqhkfj3/o0CE1a9ZMR48e9ci1Dx48qGbNmun48eNG8/3791e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usHmav7r99tuN6pYsWeJxj3Xr1uncuXNGtdm5/iJFiqhp06ZGtd6sHwAAwClxcXFq2bKlOnXqpM2bN3t0jtKlS2vlypXq2bOnj6fzjd9++83ogVIpe//WDAwMVOfOnY1qvflb85tvvjHaMTxfvnzq2LGjx32sqlOnjsqVK5dl3ZUrV7Ry5UqP+5g+YNqyZUsVLlzY4z5Wmf531rp163Tx4kV7hwHw/9q78zgt67Jv/MfMwAzDIoggq6KEyKIiiBai4QLOiCtplKWolWa2uD09bo+Vjz6Wd3dlpdVdbpl3WZqmqc2IOyopogJugSK4obLIvs7y+6Nf3Voy871mro2Z9/v18lWvzuP8HsfB9Md5yWfOCwAAgDZE8BsAAKBAnnvuuaS6thD8njlzZtJb7EpLS5MDAtmS2m/69OmxZcuWFvW4//77k+r22muvGDRoUIt6tFQ+gu8AAIXypz/9KR577LEW33/QQQfFM888E/vvv38Wp8qu1GfNnj17xgEHHJDjaT4sH8+aqftPnDgxKisrW9ynJY444oikunzsf/TRR7e4R0t87GMfi2HDhjVbV1dXF7W1tXmYCAAAAKBtEPwGAAAokPYU/E796vYRI0YkfR18No0dOza6dOnSbN3q1avj8ccfb1GP1P0/+clPtuj81pgwYUJS3cMPPxwbN27M8TQAAMWhvLw8vvvd78YDDzwQffr0KfQ4TUp91tx///2jrKwsx9N8WOqz5ssvvxyLFi1qUY+28Kz9l7/8pUXnL168OF5//fWk2ra4PwAAAEB7JPgNAABQIKlfx94Wgt+pgelCvEmxrKwsxowZk1Q7Y8aMjM+vq6uLJ598Mqm2EPuPHj06Onbs2Gzdxo0bY9asWXmYCACgsPbee+946qmn4oILLojS0uL/a5Riftbu27dv7LTTTkm1LXnWfvvtt5MD44XYf7/99kuqW7x4cbzxxhsZn5/6s+/cuXOMGjUq4/NbK3X/lvzsAQAAANqr4v83lgAAAG1Uyhu/+/btG/3798/9MDn2zDPPJNWNGzcux5N8tNRAwsyZMzM++6WXXooNGzYk1RZi/4qKithrr72SaluyPwDAtqJLly7xn//5n/H0008XJCTbEqtXr45XXnklqbYtPmvPnj07qa68vDz5lz2zafDgwdGrV6+k2lzuv++++0aHDh0yPr+1Un/2CxcujPfeey/H0wAAAAC0DYLfAAAABbB+/fpYsGBBs3Vt4W3fr7/+eixfvjyptlABm7333jupLiWs/6+effbZpLru3bvHLrvskvH52ZDL/QEAtgXHH398vPjii3HeeedFWVlZocdJ9txzz0VjY2NSbXt+1h42bFhUVFRkfH42pP6553L/Qv3sR4wYEeXl5Um1PmsAAAAApBH8BgAAKIB58+ZFQ0NDs3VtIfj9wgsvJNWVlJTE7rvvnuNpPtpuu+2WVLdkyZJYtmxZRmen7l+o3SPS9587d26OJwEAyK8xY8bEo48+GrfeemvsvPPOhR4nY6nPmjvuuGNsv/32OZ7mo6U+a86bNy/js1P3HzZsWMZnZ0sun7WLff/S0tIYPHhwUq3PGgAAAABpBL8BAAAKIPVtZm0h+D1//vykup122ik6d+6c42k+2pAhQ5JrU/fJtL6QYZTU/V955ZWkX1gAACh2Q4cOjd/97nfx9NNPx4EHHljocVqsLT1rrl27Nt5+++2Mzm5L+2f6OWPVqlXx3nvvJdW2xf0BAAAA2qsOhR4AAACgPcpG8LuxsTFmz54dTzzxRMyePTsWLFgQr7/+eqxatSo2bNgQ5eXl0aVLl9h+++1j8ODBMWTIkBg7dmx88pOfTH7rWjYsWLAgqa6Qb7zeYYcdYvvtt4/333+/2doFCxbE/vvvn3z2trB/6lsIN23aFG+88UYMGjQoxxMBAOTG7rvvHueff35MmzYtysrKCj1Oq7WlZ82Iv+/Tv3//5PpXXnklqW5b2P+1116Lurq66NAh7a/uUn/2EdvG/pnsAwAAANCeCX4DAAAUwJw5c5qt6dOnTwwYMODf/veZM2fGDTfcEHfeeWeTb3jbsGFDbNiwIZYtWxYLFiyI2traf14bPHhwfPazn40TTzwxhg8f3rIlEi1evDipbuDAgTmdozn9+/dPCn6//vrrGZ27LeyfSbjm9ddfF/wGALY5Bx54YJx99tkxZcqUKCkpKfQ4WbMtPGtut9120aVLl1i3bl2ztZk8ay9fvjzWrl2bVLstPGvX1dXFkiVLYqeddkqqT/3Zl5WVRd++fZNqcyF1/0w/ZwEAAAC0V6WFHgAAAKC9aWhoiHnz5jVb98G3fdfX18ctt9wSe++9d+y///7xq1/9KvlrvT/KwoUL44orrogRI0bEEUccEU888USLz2rOm2++mVTXr1+/nM2QIjUM8cYbbySfuWrVquQwSiH332GHHZLfLJjJ/gAAhTZp0qR48cUX49FHH41PfepTbSr0HdG+n7VTd48o7P6ZhK5zsX+fPn2itLRwfx2Yuv9bb70VjY2NOZ4GAAAAYNsn+A0AAJBnr776alIY+B/B79ra2th7773jhBNOSHpTeKbuvffeGD9+fEydOjXeeuutrJ+femahwyh9+vRJqluyZEnymZn8eRZy/5KSkthxxx2TajPZHwCg0MaPH5/zb7gplPXr18fKlSuTaj1rF27/HXfcMfkXDnKx/7bys9+0aVOsWLEix9MAAAAAbPsEvwEAAPLsueeeS6obOHBgTJ06Naqrq+P555/P7VARceutt8awYcPipptuytqZDQ0NsWzZsqTaQgcSUt9El7pPRMS7776bXNsW9wcAIHfa+7Nm6v5du3aNrl27Jp+bbeXl5bH99tsn1eZi/23lZx/hswYAAABACsFvAACAPEsNfn/jG9+IW2+9NbfD/Iu1a9fGySefHF/60pdi06ZNrT7v/fffT/667h49erS6X2t07949qW758uXJZ2byxrq2uD8AALnT3p81U/cv9O4R7Xv/1N0jfNYAAAAASCH4DQAAkGdz5sxJqstG8LqlrrvuujjiiCNi7dq1rTonk7+432677VrVq7W6deuWVLdy5crkM1P379y5c5SVlSWfmwu52B8AgNzxrJ22f6F3j2jf+6fuHuGzBgAAAEAKwW8AAIA8S33jd6E98MADcfDBB8fq1atbfMaqVauSa7eVQMKaNWuSz0zdv9C7R+RmfwAAcsezdvt+1t5W9s8k+O2zBgAAAEDzBL8BAADyaNmyZfHWW28VeoxkTz/9dEyZMiU2b97covvXrVuXXJvJV4DnQmogYePGjVFfX59Um7p/oXePSN+/tW+BBwAgO1KfNSsqKqKioiLH0zQtF8+a7f1Ze1vZv0OHDtGpU6ekWp81AAAAAJrXodADAAAAtCdz5szJyjkjRoyII488MkaPHh177rln9OrVK3r06BElJSWxfv36eOedd2LhwoXx9NNPx6OPPhqPPPJI1NXVtajXgw8+GKeddlr8+te/zvjeTILfnTt3zvj8bMqk/8aNG6NLly7N1qXuX+jdM5lh48aNOZ4EAIAU7f1Z0/7b1v4pu/msAQAAANA8wW8AAIA8eu6551p8b0VFRZx66qlx1llnxbBhw7ZaV15eHj169Ihhw4bF5MmTIyJi+fLl8etf/zquuuqqeOONNzLufdNNN8UhhxwSJ598ckb3bdiwIbm2Q4fCfkQtKytLrk0NfqfuX+jdI9L3F8YAACgO7f1Z0/7te38AAACA9qq00AMAAAC0Jy0Nfk+dOjUWLlwYP//5z5sMfW/NDjvsEOeee24sWLAgLr/88uSv2v6gr33ta7Fo0aKM7snkLeOFDiRk0n/Lli1Jdan7F3r3TGZI3R0AgNxq78+a9m/f+wMAAAC0V4LfAAAAeTRnzpyM6rt37x533HFH/P73v4/+/fu3un9FRUVcfPHF8eSTT8Zuu+2W0b1r166N8847L6N76uvrk2sLHUjIpH/qXql1hd49kxky+ZkCAJA77f1Z0/7te38AAACA9krwGwAAIE82bdoUL7/8cnL94MGDY+bMmXHsscdmfZa99torZs6cGfvuu29G991+++3xyCOPJNen/sV9SUlJlJYW9iOq4LcwBgDAtqS9P2vav33vDwAAANBeCX4DAADkyQsvvJD81dU77bRTPPTQQzF8+PCczbPDDjvEfffdFyNGjMjoviuuuCK5tqSkJKt125r2vj8AALnT3p817d++9wcAAABorwS/AQAA8mT58uUxZMiQKC8vb7KuS5cuUVtbGzvvvHPOZ+rRo0fcfffdsd122yXfc99998Xzzz+fVNuxY8ekuoaGhmhsbEyeIRfq6uqSa1PfWJe6fya9cyV1hmJ4YyAAAJ417d++9wcAAABor/wbFAAAgDyZNGlSLFiwIBoaGuLNN9+M1157LV577bVYuHDhh/7z8ssvz+mbvv/VrrvuGj/+8Y/j1FNPTb7nuuuuix/96EfN1jUXcv+gurq65PBCLmQSiCgrK0uqS91/WwpjpO4OAEButfdnTfuXx6ZNm7LWO5d81gAAAADIHsFvAACAPCstLY2dd945dt5555gwYUKhx4mIiJNPPjmuueaaePrpp5Pqb7/99qTgdyZB7vr6+m0m+J3tN37X19cn984Vb+EDANi2tPdnTfu37/0BAAAA2qvSQg8AAABA4ZWUlMSll16aXP/666/H7Nmzm63L9I3fhZRJIKJz585JddvSWwhT90/dHQCA3Grvz5r2b9/7AwAAALRXgt8AAABERMThhx8egwcPTq5//PHHm63p1KlT8nkbNmxIrs2FdevWJdWVlpZGZWVlUm3q/oXePSJ9/y5duuR4EgAAUrT3Z037t+/9AQAAANorwW8AAAAi4u9v/Z46dWpy/cyZM5ut6d69e/J5a9asSa7NhbVr1ybVpYa+I9L3L/TuEen7ewsfAEBxSH3WXL9+fUbfbpMLuXjWbO/P2tvK/nV1dbFp06akWp81AAAAAJon+A0AAMA/HXnkkcm1c+bMabZmhx12SD6v0IGE1P49evRIPjN1/0LvnskMmewPAEDuZPKsnRo8zhXP2u13/0z6+6wBAAAA0DzBbwAAAP5pn332iY4dOybVLlq0qNmathj8zmSnbSWMkckMmewPAEDueNZu38/a28r+mfT3WQMAAACgeYLfAAAA/FOnTp1i+PDhSbUbNmyId999t8mazp07R6dOnZLOW7lyZVJdrqT2zySM0LNnz6S6+vr6gr+FMRf7AwCQO6nPmhHt+1m70LtnMkNb3D+T/j5rAAAAADRP8BsAAIAP2WWXXZJrV6xY0WxN6l/eNxciz7V33nknqW7HHXdMPrNXr17JtW1xfwAAcieTkGxbfNZMfdZesWJF1NXVJZ+bbZs3b473338/qTYX+28rP/uIiN69e+dwEgAAAIC2QfAbAACADxkwYEBy7fr165utGThwYNJZ20ogIZM/nwEDBkRJSUlSbSH3b2hoiKVLlybVZrI/AAC507Fjx+jTp09SbVt81k79nNHY2Bjvvfde8rnZlknwORf7bys/+549e0ZlZWWOpwEAAADY9gl+AwAA8CFdunRJrt2wYUOzNYMHD046K5NARC6kBiIyCWNUVlZG3759k2oLuf/y5cuT34Io+A0AUDza87P2rrvumvxLloXcP5PgdSb7t+efPQAAAEB7JvgNAADAh2TylrWOHTs2W5MaSHjrrbeS++ZCav9ddtklo3O3hf0z6Z3p/gAA5M628Ky5cuXKpG8KisjsWbOioiL69++fVLstPGt369YtevbsmXxu6s9+zZo1sWbNmuRzsy1Xn7MAAAAA2ivBbwAAAD5k06ZNybUpIfFdd9016axXXnkluW+2LV26NFatWpVUu9tuu2V09raw/4IFC5LqevbsmVEYBQCA3GpLz5oR7ftZO9PdBw0aFKWlaX/N1xb3BwAAAGivBL8BAAD4kA0bNiTXduvWrdmaIUOGJJ31yiuvRGNjY3LvbEoNI5SUlGQcSEjdP5NATLal9t59991zPAkAAJloS8+a/fr1S/p88UFtaf9Mn7U7duwYO++8c1ZnyAWfNQAAAACyS/AbAACAD3n33XeT6kpKSpK+Wn3vvfeOkpKSZuvWr18fb7/9dlLvbEsNIwwZMiQ6deqU0dmjR4/O6gy5kNp7jz32yPEkAABkIvVZc+HChdHQ0JDjaT5aLp812/uzdrHvX1dXF4sWLUqq9VkDAAAAII3gNwAAAB/y5ptvJtXtuOOOUVFR0Wxd9+7dk9/EN2fOnKS6bHvuueeS6lKDFR80duzYpLqFCxfG2rVrMz4/G3K5PwAAuTNy5MiorKxstm7Tpk3x8ssv52Gif1cMz9qF+pyRSe+2uP8LL7wQW7ZsabautLQ0Ro0alYeJAAAAALZ9HQo9AAAAQHvQ0NAQy5cvj/fee+/f/lm6dOk///sXvvCF+MIXvlDQWVMDIUOHDk0+c+zYsUlvmXvqqadi8uTJyedmy1NPPZVUN2bMmIzP7t+/f/Tr1y+WLFnSZF1DQ0M8/fTTcdBBB2XcozU2bNgQzz//fFJtS/YHACB3ysrKYu+9946ZM2c2W/vUU0/FiBEj8jDVv/dN0ZJnzdGjR0dZWVnU19c3Wbd06dJYtGhR7LLLLhn3aI0FCxbE+++/n1Sby+B36s8g21L7Dh06NLp06ZLjaQAAAADaBsFvAACAHFu4cGEMHTq02TBCRMSAAQMKGvx+7bXXYsWKFUm1++yzT/K5++67b/zud79rtm7WrFnJZ2ZLXV1dPPvss0m148ePb1GPfffdN+66665m62bNmpX34PczzzwTdXV1zdZVVlYKfgMAFKF99903Kfg9a9asOOWUU3I/0Ae89dZb8fbbbyfVtuRZu7KyMkaOHBlz585ttnbWrFl5D36nBp8/9rGPRd++fTM+PzX4vXjx4li6dGn07t074x6tkbp/Sz9nAQAAALRHpYUeAAAAoK3baaedkmuffPLJHE7SvAcffDC5NjVkEBHxyU9+Mqnu8ccfTwohZ9OTTz4ZGzZsaLauU6dOsd9++7WoR+r+Dz/8cIvOb43Unp/4xCeiY8eOuR0GAICMtYVnzV133TUGDhzYoh5tYf/UHf5Vz549Y4899sjqLNmU6/0BAAAA2iPBbwAAgBzr2LFjDBo0KKl28eLF8c477+R4oq279957k+pKSkpi4sSJyeeOGTMmdtxxx2brVq1aFTNmzEg+Nxv+/Oc/J9UdeOCBUV5e3qIehx9+eFLdQw89lBRCz6bU/TP5eQMAkD8TJ06MDh2a/4LXF198MV577bU8TPQ/8vGsmfqsfc8997S4R0s0NjYm98zH/nfffXeLe7TEyy+/HK+88kpS7aGHHprjaQAAAADaDsFvAACAPNh3332Ta2+//fYcTrJ1y5cvTw4mjBkzJvr06ZN8dklJSVRXVyfVpoZDsiU1AHHUUUe1uMeIESOSwv8bNmyI6dOnt7hPpt59992YNWtWUm1r9gcAIHe6d+8e+++/f1JtPp+1t2zZErW1tUm1rXnWPPjgg6NTp07N1i1evDjmzp3b4j6Zmj17dixZsqTZug4dOiSHtz9K6r1/+ctfor6+vsV9MpX6OWvMmDExYMCAHE8DAAAA0HYIfgMAAOTBuHHjkmtvvPHG3A3ShOuvvz42bdqUVPvpT3864/MnT56cVPfb3/42Nm/enPH5LfHkk0/GCy+80GxdaWlpHHPMMa3qlRrIuOGGG1rVJxM33nhjNDQ0NFs3ZMiQ2HPPPfMwEQAALZH6rJ3Pzxq33357rFy5stm6bt26teqN15WVlXHQQQcl1ebzWfu6665LqpswYUJsv/32Le5zwAEHRLdu3ZqtW7p0aV7f+n399dcn1U2ZMiXHkwAAAAC0LYLfAAAAeTBp0qTk2lmzZsVLL72Uw2n+3dq1a+P73/9+Um1ZWVlMmzYt4x5HHHFEdO3atdm6d999N/74xz9mfH5LXHPNNUl1kyZNip133rlVvT7zmc8k1f35z3+ON998s1W9UjQ0NMQvfvGLpNovfvGLOZ4GAIDWmDp1apSUlDRb9+yzz8bMmTPzMFH6s/bnPve5qKysbFWv1GftG2+8MTZs2NCqXilWr14dN998c1Ltl770pVb16tixY3zqU59Kqv3Zz37Wql6pHnzwwaTPtGVlZXHqqafmYSIAAACAtkPwGwAAIA9GjBgRQ4cOTa6/7LLLcjjNv7v88stj6dKlSbVHH3109OvXL+MeXbt2TQ5kfO9738v515AvWLAgfv/73yfVnn766a3ud9BBB8WQIUOarauvr4/vfve7re7XnN/85jexaNGiZus6duwojAEAUOR23XXXOOSQQ5JqL7/88hxPE/HII4/EjBkzkmqz8aw9derU2G677ZqtW7lyZVx99dWt7tecH/3oR7F27dpm63r16pUc2m5Kanh8+vTp8dRTT7W6X3NS/z82efLkGDBgQI6nAQAAAGhbBL8BAADy5HOf+1xy7e9+97t47LHHcjjN/3jqqafiP//zP5PrL7roohb3Sg0kzJ07N/lt1C11zjnnxObNm5ut69OnTxx11FFZ6Zn65uz/+q//irlz52al50dZs2ZNXHDBBUm1Rx11VPTp0ydnswAAkB2pz9r33ntv3HPPPTmbo76+Pr7xjW8k1Y4ZMybGjBnT6p6dO3eOE044Ian2sssui3feeafVPbfm9ddfjyuvvDKpdtq0aVFeXt7qngcccEDsvvvuzdY1NjbG17/+9WhsbGx1z6257bbb4qGHHkqqPe2003I2BwAAAEBbJfgNAACQJ6effnp07Ngxuf7rX/96bNq0KYcTRbzzzjtx3HHHJb9de/LkyTF27NgW9/vEJz4Ro0aNSqq98MILY/78+S3u1ZRrr702Oexy2mmnZfRza8opp5wSFRUVzdbV19fHtGnTcvY19GeeeWZy2OXMM8/MyQwAAGTXlClTYscdd0yqPeOMM5K/8SdT3/72t5N/iTGbz5pf/vKXk+rWrFkTp556ak7Cz5k8x5eWlibPnOKMM85Iqnvqqafie9/7Xtb6ftDbb78dX/3qV5NqBw0aFJMnT87JHAAAAABtmeA3AABAnvTr1y+jt34/99xzMW3atJy9jW3lypVx5JFHxptvvplUX15eHj/4wQ9a3fc73/lOUt2aNWviU5/6VKxatarVPT9o1qxZ8fWvfz2ptmfPnnHeeedlrXffvn2TAxlz5szJahDkH66++uq4+eabk2oPOeSQOPTQQ7M+AwAA2VdRUREXXnhhUu2bb74Zn/3sZ5O+AScTd911V1xxxRVJtUOHDo2TTz45a71Hjx4dxxxzTFJtTU1NfOtb38pa7384//zz45FHHkmqPeWUU2Lo0KFZ6/3lL385+vXrl1R7ySWXxH333Ze13hERGzdujKlTp8Z7772XVH/ZZZdFWVlZVmcAAAAAaA8EvwEAAPLo0ksvTXrj8z/84Q9/iLPPPjvrc7zzzjsxceLEmD17dvI95513XgwbNqzVvY899tjYd999k2pfeOGFOOKII2LdunWt7hsR8eKLL8bhhx8eGzduTKq/5JJLokePHlnp/Q8XXnhhdOnSJan2N7/5TZxzzjlZ6/273/0uzjrrrKTakpKS+P73v5+13gAA5N5XvvKVGDhwYFLtgw8+GJ///OeTv/2nOQ8//HB85jOfSf7F1SuvvDI6dOiQld7/cNlll0VJSUlS7eWXXx4//vGPs9b7yiuvTP5F2c6dO8dll12Wtd4REZWVlXHxxRcn1dbX18enPvWpeOKJJ7LSu66uLqZOnRqPP/54Uv3o0aPjxBNPzEpvAAAAgPZG8BsAACCPBg0aFOeee25G9/zkJz+JY489NlauXJmVGWbOnBn77rtvRqHvUaNGZfWNeKlvAYyIePzxx+Pggw+Od955p1U9H3300TjwwANj+fLlSfUf+9jHsvrV8//Qp0+fjML8V111VXzxi1+MLVu2tKrvT37ykzjxxBOjoaEhqf7zn/98jBkzplU9AQDIr4qKivj2t7+dXH/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"text/plain": [ "" ] }, - "execution_count": 23, + "execution_count": 75, "metadata": {}, "output_type": "execute_result" }, @@ -1483,26 +809,39 @@ " zi,\n", " {'plot_mz': [100, 1400], 'plot_IM': [0.6, 1.4]},\n", " df_parameters_final,\n", - " folder_paths + \"acquisition_scheme_and_density_plot_polygone.png\",\n", + " folder_paths + \"/acquisition_scheme_and_density_plot_polygone.png\",\n", "# alpha=0.1,\n", "# window_color = \"green\",\n", "# color_scheme_name = \"white_scheme\"\n", ")\n", - "Image(folder_paths + \"acquisition_scheme_and_density_plot_polygone.png\")" + "Image(folder_paths + \"/acquisition_scheme_and_density_plot_polygone.png\")" ] }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 77, "id": "ca586211", "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "here\n" - ] + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -1520,34 +859,17 @@ " library,\n", " acquisition_parameters,\n", " df_parameters_final,\n", - " folder_paths + \"/final_method/histogram_slicing.png\"\n", + " folder_paths + \"/histogram_slicing.png\"\n", " )\n", - " Image(folder_paths + \"/final_method/histogram_slicing.png\")" + "Image(folder_paths + \"/histogram_slicing.png\")" ] }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 78, "id": "6345f4f6-4bec-4e9c-a5ca-2b35050af082", "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "here2\n", - "division by zero singly charged precursours are not present\n", - "here2\n", - "division by zero singly charged precursours are not present\n", - "here2\n", - "division by zero singly charged precursours are not present\n", - "here2\n", - "division by zero singly charged precursours are not present\n", - "here2\n", - "division by zero singly charged precursours are not present\n", - "{'scan': ['all synchro scans', '#synchro scan 1', '#synchro scan 2', '#synchro scan 3', '#synchro scan 4'], 'unique proteins in the library': 9137, 'unique precursors in the library': 167850, 'No. of covered proteins': [9101, 8513, 8121, 4940, 1676], 'No. of covered precursors': [159760, 81335, 62477, 13411, 2537], 'No. of covered, singly charged precursors': [0, 0, 0, 0, 0], 'No. of covered, doubly charged precursors': [119080, 73529, 42429, 3075, 47], 'No. of covered, triply charged precursors': [36701, 6454, 18081, 9739, 2427], 'No. of covered, quadruply charged precursors': [3731, 1222, 1863, 584, 62], 'proteins covered [%]': [99.6, 93.2, 88.9, 54.1, 18.3], 'precursors covered [%] (counting IM peak at center)': [95.2, 48.5, 37.2, 8.0, 1.5], 'singly charged precursors covered [%]': [0, 0, 0, 0, 0], 'doubly charged precursors covered [%]': [94.3, 58.2, 33.6, 2.4, 0.0], 'triply charged precursors covered [%]': [97.9, 17.2, 48.2, 26.0, 6.5], 'quadruply charged precursors covered [%]': [97.0, 31.8, 48.4, 15.2, 1.6]}\n" - ] - }, { "data": { "text/html": [ @@ -1573,121 +895,134 @@ " #synchro scan 1\n", " #synchro scan 2\n", " #synchro scan 3\n", - " #synchro scan 4\n", " \n", " \n", " \n", " \n", " unique proteins in the library\n", - " 9137\n", - " 9137\n", - " 9137\n", - " 9137\n", - " 9137\n", + " 3874\n", + " 3874\n", + " 3874\n", + " 3874\n", " \n", " \n", " unique precursors in the library\n", - " 167850\n", - " 167850\n", - " 167850\n", - " 167850\n", - " 167850\n", + " 21878\n", + " 21878\n", + " 21878\n", + " 21878\n", " \n", " \n", " No. of covered proteins\n", - " 9101\n", - " 8513\n", - " 8121\n", - " 4940\n", - " 1676\n", + " 3850\n", + " 2461\n", + " 3300\n", + " 1429\n", " \n", " \n", " No. of covered precursors\n", - " 159760\n", - " 81335\n", - " 62477\n", - " 13411\n", - " 2537\n", + " 21139\n", + " 6435\n", + " 12266\n", + " 2438\n", " \n", " \n", " No. of covered, singly charged precursors\n", + " 1\n", " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 1\n", " 0\n", " \n", " \n", " No. of covered, doubly charged precursors\n", - " 119080\n", - " 73529\n", - " 42429\n", - " 3075\n", - " 47\n", + " 14264\n", + " 5760\n", + " 8368\n", + " 136\n", " \n", " \n", " No. of covered, triply charged precursors\n", - " 36701\n", - " 6454\n", - " 18081\n", - " 9739\n", - " 2427\n", + " 6130\n", + " 573\n", + " 3368\n", + " 2189\n", " \n", " \n", " No. of covered, quadruply charged precursors\n", - " 3731\n", - " 1222\n", - " 1863\n", - " 584\n", - " 62\n", + " 744\n", + " 102\n", + " 529\n", + " 113\n", " \n", " \n", " proteins covered [%]\n", - " 99.6\n", - " 93.2\n", - " 88.9\n", - " 54.1\n", - " 18.3\n", + " 99.4\n", + " 63.5\n", + " 85.2\n", + " 36.9\n", " \n", " \n", " precursors covered [%] (counting IM peak at center)\n", - " 95.2\n", - " 48.5\n", - " 37.2\n", - " 8.0\n", - " 1.5\n", + " 96.6\n", + " 29.4\n", + " 56.1\n", + " 11.1\n", " \n", " \n", " singly charged precursors covered [%]\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", - " 0\n", + " 50.0\n", + " 0.0\n", + " 50.0\n", + " 0.0\n", " \n", " \n", " doubly charged precursors covered [%]\n", - " 94.3\n", - " 58.2\n", - " 33.6\n", - " 2.4\n", - " 0.0\n", + " 97.7\n", + " 39.5\n", + " 57.3\n", + " 0.9\n", " \n", " \n", " triply charged precursors covered [%]\n", - " 97.9\n", - " 17.2\n", - " 48.2\n", - " 26.0\n", - " 6.5\n", + " 94.5\n", + " 8.8\n", + " 51.9\n", + " 33.7\n", " \n", " \n", " quadruply charged precursors covered [%]\n", - " 97.0\n", - " 31.8\n", - " 48.4\n", - " 15.2\n", - " 1.6\n", + " 93.8\n", + " 12.9\n", + " 66.7\n", + " 14.2\n", + " \n", + " \n", + " covered and sliced precursors [%] (counting complete IM peak width)\n", + " 49.57\n", + " 75.55\n", + " 58.34\n", + " 65.33\n", + " \n", + " \n", + " average fragment coverage [%] (counting complete IM peak width)\n", + " 97.84\n", + " 60.15\n", + " 73.42\n", + " 64.08\n", + " \n", + " \n", + " sliced precursors [%] (counting complete IM peak width)\n", + " 48.72\n", + " 37.61\n", + " 43.71\n", + " 11.66\n", + " \n", + " \n", + " covered precursors [%] (counting complete IM peak width)\n", + " 98.28\n", + " 49.78\n", + " 74.92\n", + " 17.84\n", " \n", " \n", "\n", @@ -1695,87 +1030,87 @@ ], "text/plain": [ " all synchro scans \\\n", - "unique proteins in the library 9137 \n", - "unique precursors in the library 167850 \n", - "No. of covered proteins 9101 \n", - "No. of covered precursors 159760 \n", - "No. of covered, singly charged precursors 0 \n", - "No. of covered, doubly charged precursors 119080 \n", - "No. of covered, triply charged precursors 36701 \n", - "No. of covered, quadruply charged precursors 3731 \n", - "proteins covered [%] 99.6 \n", - "precursors covered [%] (counting IM peak at cen... 95.2 \n", - "singly charged precursors covered [%] 0 \n", - "doubly charged precursors covered [%] 94.3 \n", - "triply charged precursors covered [%] 97.9 \n", - "quadruply charged precursors covered [%] 97.0 \n", + "unique proteins in the library 3874 \n", + "unique precursors in the library 21878 \n", + "No. of covered proteins 3850 \n", + "No. of covered precursors 21139 \n", + "No. of covered, singly charged precursors 1 \n", + "No. of covered, doubly charged precursors 14264 \n", + "No. of covered, triply charged precursors 6130 \n", + "No. of covered, quadruply charged precursors 744 \n", + "proteins covered [%] 99.4 \n", + "precursors covered [%] (counting IM peak at cen... 96.6 \n", + "singly charged precursors covered [%] 50.0 \n", + "doubly charged precursors covered [%] 97.7 \n", + "triply charged precursors covered [%] 94.5 \n", + "quadruply charged precursors covered [%] 93.8 \n", + "covered and sliced precursors [%] (counting com... 49.57 \n", + "average fragment coverage [%] (counting complet... 97.84 \n", + "sliced precursors [%] (counting complete IM pea... 48.72 \n", + "covered precursors [%] (counting complete IM pe... 98.28 \n", "\n", " #synchro scan 1 \\\n", - "unique proteins in the library 9137 \n", - "unique precursors in the library 167850 \n", - "No. of covered proteins 8513 \n", - "No. of covered precursors 81335 \n", + "unique proteins in the library 3874 \n", + "unique precursors in the library 21878 \n", + "No. of covered proteins 2461 \n", + "No. of covered precursors 6435 \n", "No. of covered, singly charged precursors 0 \n", - "No. of covered, doubly charged precursors 73529 \n", - "No. of covered, triply charged precursors 6454 \n", - "No. of covered, quadruply charged precursors 1222 \n", - "proteins covered [%] 93.2 \n", - "precursors covered [%] (counting IM peak at cen... 48.5 \n", - "singly charged precursors covered [%] 0 \n", - "doubly charged precursors covered [%] 58.2 \n", - "triply charged precursors covered [%] 17.2 \n", - "quadruply charged precursors covered [%] 31.8 \n", + "No. of covered, doubly charged precursors 5760 \n", + "No. of covered, triply charged precursors 573 \n", + "No. of covered, quadruply charged precursors 102 \n", + "proteins covered [%] 63.5 \n", + "precursors covered [%] (counting IM peak at cen... 29.4 \n", + "singly charged precursors covered [%] 0.0 \n", + "doubly charged precursors covered [%] 39.5 \n", + "triply charged precursors covered [%] 8.8 \n", + "quadruply charged precursors covered [%] 12.9 \n", + "covered and sliced precursors [%] (counting com... 75.55 \n", + "average fragment coverage [%] (counting complet... 60.15 \n", + "sliced precursors [%] (counting complete IM pea... 37.61 \n", + "covered precursors [%] (counting complete IM pe... 49.78 \n", "\n", " #synchro scan 2 \\\n", - "unique proteins in the library 9137 \n", - "unique precursors in the library 167850 \n", - "No. of covered proteins 8121 \n", - "No. of covered precursors 62477 \n", - "No. of covered, singly charged precursors 0 \n", - "No. of covered, doubly charged precursors 42429 \n", - "No. of covered, triply charged precursors 18081 \n", - "No. of covered, quadruply charged precursors 1863 \n", - "proteins covered [%] 88.9 \n", - "precursors covered [%] (counting IM peak at cen... 37.2 \n", - "singly charged precursors covered [%] 0 \n", - "doubly charged precursors covered [%] 33.6 \n", - "triply charged precursors covered [%] 48.2 \n", - "quadruply charged precursors covered [%] 48.4 \n", + "unique proteins in the library 3874 \n", + "unique precursors in the library 21878 \n", + "No. of covered proteins 3300 \n", + "No. of covered precursors 12266 \n", + "No. of covered, singly charged precursors 1 \n", + "No. of covered, doubly charged precursors 8368 \n", + "No. of covered, triply charged precursors 3368 \n", + "No. of covered, quadruply charged precursors 529 \n", + "proteins covered [%] 85.2 \n", + "precursors covered [%] (counting IM peak at cen... 56.1 \n", + "singly charged precursors covered [%] 50.0 \n", + "doubly charged precursors covered [%] 57.3 \n", + "triply charged precursors covered [%] 51.9 \n", + "quadruply charged precursors covered [%] 66.7 \n", + "covered and sliced precursors [%] (counting com... 58.34 \n", + "average fragment coverage [%] (counting complet... 73.42 \n", + "sliced precursors [%] (counting complete IM pea... 43.71 \n", + "covered precursors [%] (counting complete IM pe... 74.92 \n", "\n", - " #synchro scan 3 \\\n", - "unique proteins in the library 9137 \n", - "unique precursors in the library 167850 \n", - "No. of covered proteins 4940 \n", - "No. of covered precursors 13411 \n", - "No. of covered, singly charged precursors 0 \n", - "No. of covered, doubly charged precursors 3075 \n", - "No. of covered, triply charged precursors 9739 \n", - "No. of covered, quadruply charged precursors 584 \n", - "proteins covered [%] 54.1 \n", - "precursors covered [%] (counting IM peak at cen... 8.0 \n", - "singly charged precursors covered [%] 0 \n", - "doubly charged precursors covered [%] 2.4 \n", - "triply charged precursors covered [%] 26.0 \n", - "quadruply charged precursors covered [%] 15.2 \n", - "\n", - " #synchro scan 4 \n", - "unique proteins in the library 9137 \n", - "unique precursors in the library 167850 \n", - "No. of covered proteins 1676 \n", - "No. of covered precursors 2537 \n", + " #synchro scan 3 \n", + "unique proteins in the library 3874 \n", + "unique precursors in the library 21878 \n", + "No. of covered proteins 1429 \n", + "No. of covered precursors 2438 \n", "No. of covered, singly charged precursors 0 \n", - "No. of covered, doubly charged precursors 47 \n", - "No. of covered, triply charged precursors 2427 \n", - "No. of covered, quadruply charged precursors 62 \n", - "proteins covered [%] 18.3 \n", - "precursors covered [%] (counting IM peak at cen... 1.5 \n", - "singly charged precursors covered [%] 0 \n", - "doubly charged precursors covered [%] 0.0 \n", - "triply charged precursors covered [%] 6.5 \n", - "quadruply charged precursors covered [%] 1.6 " + "No. of covered, doubly charged precursors 136 \n", + "No. of covered, triply charged precursors 2189 \n", + "No. of covered, quadruply charged precursors 113 \n", + "proteins covered [%] 36.9 \n", + "precursors covered [%] (counting IM peak at cen... 11.1 \n", + "singly charged precursors covered [%] 0.0 \n", + "doubly charged precursors covered [%] 0.9 \n", + "triply charged precursors covered [%] 33.7 \n", + "quadruply charged precursors covered [%] 14.2 \n", + "covered and sliced precursors [%] (counting com... 65.33 \n", + "average fragment coverage [%] (counting complet... 64.08 \n", + "sliced precursors [%] (counting complete IM pea... 11.66 \n", + "covered precursors [%] (counting complete IM pe... 17.84 " ] }, - "execution_count": 55, + "execution_count": 78, "metadata": {}, "output_type": "execute_result" } @@ -1810,7 +1145,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 79, "id": "4ff4f543", "metadata": {}, "outputs": [], @@ -1821,7 +1156,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 86, "id": "cc88b531", "metadata": { "scrolled": true @@ -1841,7 +1176,7 @@ "save_at = 'D:/synchro_scan_gif/'\n", "method_creator.create_folder([save_at])\n", "\n", - "boxes, df_temp_reset_index = plots.generate_boxes(df_parameters_final, im_steps=100)\n", + "boxes, df_temp_reset_index = plots.generate_boxes(df_parameters_final, im_steps=3)\n", "\n", "plots.generate_gif_single_windows(\n", " xi,\n", @@ -1852,14 +1187,14 @@ " range(1, len(df_temp_reset_index)+1),\n", " save_at,\n", " facecolor=\"#FF0098\",\n", - " window_color = None,\n", + " window_color = \"white_grey\",\n", " scans_plotted_at_once=1,\n", ")" ] }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 87, "id": "31ca48b4", "metadata": {}, "outputs": [], @@ -1869,7 +1204,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 88, "id": "5bc160ea", "metadata": {}, "outputs": [ @@ -1903,9 +1238,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python [conda env:synchro] *", + "display_name": "Python [conda env:pydiaid_test]", "language": "python", - "name": "conda-env-synchro-py" + "name": "conda-env-pydiaid_test-py" }, "language_info": { "codemirror_mode": { diff --git a/nbs/20231207_synchroPASEF_quadrupole_isolation.ipynb b/nbs/20231207_synchroPASEF_quadrupole_isolation.ipynb deleted file mode 100644 index 8cdfbb8..0000000 --- a/nbs/20231207_synchroPASEF_quadrupole_isolation.ipynb +++ /dev/null @@ -1,4279 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "6e992ca5", - "metadata": {}, - "outputs": [], - "source": [ - "%reload_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "ee44e060-8379-472b-a785-38a01805aa90", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - 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- " ---------------------------------------- 0.0/1.1 MB ? eta -:--:--\n", - " --------------------------------------- 1.1/1.1 MB 70.3 MB/s eta 0:00:01\n", - " --------------------------------------- 1.1/1.1 MB 70.3 MB/s eta 0:00:01\n", - " --------------------------------------- 1.1/1.1 MB 70.3 MB/s eta 0:00:01\n", - " --------------------------------------- 1.1/1.1 MB 70.3 MB/s eta 0:00:01\n", - " --------------------------------------- 1.1/1.1 MB 70.3 MB/s eta 0:00:01\n", - " ---------------------------------------- 1.1/1.1 MB 4.5 MB/s eta 0:00:00\n", - " Downloading dask-2022.2.1-py3-none-any.whl (1.1 MB)\n", - " ---------------------------------------- 0.0/1.1 MB ? eta -:--:--\n", - " --------------------------------------- 1.1/1.1 MB 33.7 MB/s eta 0:00:01\n", - " --------------------------------------- 1.1/1.1 MB 33.7 MB/s eta 0:00:01\n", - " --------------------------------------- 1.1/1.1 MB 33.7 MB/s eta 0:00:01\n", - " --------------------------------------- 1.1/1.1 MB 33.7 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d:\\maria\\anaconda\\envs\\synchro3\\lib\\site-packages (from distributed==2022.02.1->dask[complete]>=0.18.0->datashader==0.12.1->alphatims[plotting-stable]) (68.2.2)\n", - "Requirement already satisfied: charset-normalizer<4,>=2 in d:\\maria\\anaconda\\envs\\synchro3\\lib\\site-packages (from requests->panel>=0.8.0->holoviews>=1.11.0->hvplot==0.7.1->alphatims[plotting-stable]) (3.3.2)\n", - "Requirement already satisfied: idna<4,>=2.5 in d:\\maria\\anaconda\\envs\\synchro3\\lib\\site-packages (from requests->panel>=0.8.0->holoviews>=1.11.0->hvplot==0.7.1->alphatims[plotting-stable]) (3.6)\n", - "Requirement already satisfied: certifi>=2017.4.17 in d:\\maria\\anaconda\\envs\\synchro3\\lib\\site-packages (from requests->panel>=0.8.0->holoviews>=1.11.0->hvplot==0.7.1->alphatims[plotting-stable]) (2023.11.17)\n", - "Using cached numba-0.58.1-cp38-cp38-win_amd64.whl (2.6 MB)\n", - "Using cached alphatims-1.0.8-py3-none-any.whl (10.3 MB)\n", - "Using cached h5py-3.10.0-cp38-cp38-win_amd64.whl (2.7 MB)\n", - "Using cached pyzstd-0.15.9-cp38-cp38-win_amd64.whl (245 kB)\n", - "Using cached llvmlite-0.41.1-cp38-cp38-win_amd64.whl (28.1 MB)\n", - "Downloading cloudpickle-3.0.0-py3-none-any.whl (20 kB)\n", - "Downloading fsspec-2023.12.2-py3-none-any.whl (168 kB)\n", - " ---------------------------------------- 0.0/169.0 kB ? eta -:--:--\n", - " -------------------------------------- - 163.8/169.0 kB ? eta -:--:--\n", - " -------------------------------------- - 163.8/169.0 kB ? eta -:--:--\n", - " ---------------------------------------- 169.0/169.0 kB 1.5 MB/s eta 0:00:00\n", - "Downloading multipledispatch-1.0.0-py3-none-any.whl (12 kB)\n", - "Downloading partd-1.4.1-py3-none-any.whl (18 kB)\n", - "Downloading msgpack-1.0.7-cp38-cp38-win_amd64.whl (222 kB)\n", - " ---------------------------------------- 0.0/222.8 kB ? eta -:--:--\n", - " -------------------------------------- - 215.0/222.8 kB ? eta -:--:--\n", - " ---------------------------------------- 222.8/222.8 kB 3.4 MB/s eta 0:00:00\n", - "Downloading tblib-3.0.0-py3-none-any.whl (12 kB)\n", - "Building wheels for collected packages: bokeh, datashape\n", - " Building wheel for bokeh (setup.py): started\n", - " Building wheel for bokeh (setup.py): finished with status 'done'\n", - " Created wheel for bokeh: filename=bokeh-2.2.3-py3-none-any.whl size=9296333 sha256=bfc12847c68567596ef76c99680c69c8e501c0192537f8164052573d28d6c50e\n", - " Stored in directory: c:\\users\\metaboscape\\appdata\\local\\pip\\cache\\wheels\\44\\48\\ac\\5cde9e6d0b1e0afb4cff564eaf59462468abe37cfc83cbb5ed\n", - " Building wheel for datashape (setup.py): started\n", - " Building wheel for datashape (setup.py): finished with status 'done'\n", - " Created wheel for datashape: filename=datashape-0.5.2-py3-none-any.whl size=59450 sha256=e1b70d25a6eee0bc0c5b23a7587bc8949b96547d3cff0efe8c6676426697338d\n", - " Stored in directory: c:\\users\\metaboscape\\appdata\\local\\pip\\cache\\wheels\\6d\\79\\c4\\c425774559165f472d32e5ef592ff9a71179abb31f05dbc98b\n", - "Successfully built bokeh datashape\n", - "Installing collected packages: sortedcontainers, multipledispatch, zict, toolz, tblib, selenium, pyzstd, param, msgpack, locket, llvmlite, jinja2, h5py, fsspec, cloudpickle, partd, numba, datashape, bokeh, xarray, panel, dask, alphatims, holoviews, distributed, hvplot, datashader\n", - " Attempting uninstall: param\n", - " Found existing installation: param 2.0.1\n", - " Uninstalling param-2.0.1:\n", - " Successfully uninstalled param-2.0.1\n", - " Attempting uninstall: jinja2\n", - " Found existing installation: Jinja2 3.1.2\n", - " Uninstalling Jinja2-3.1.2:\n", - " Successfully uninstalled Jinja2-3.1.2\n", - " Attempting uninstall: bokeh\n", - " Found existing installation: bokeh 3.1.1\n", - " Uninstalling bokeh-3.1.1:\n", - " Successfully uninstalled bokeh-3.1.1\n", - " Attempting uninstall: panel\n", - " Found existing installation: panel 1.2.3\n", - " Uninstalling panel-1.2.3:\n", - " Successfully uninstalled panel-1.2.3\n", - " Attempting uninstall: holoviews\n", - " Found existing installation: holoviews 1.17.1\n", - " Uninstalling holoviews-1.17.1:\n", - " Successfully uninstalled holoviews-1.17.1\n", - "Successfully installed alphatims-1.0.8 bokeh-2.2.3 cloudpickle-3.0.0 dask-2022.2.1 datashader-0.12.1 datashape-0.5.2 distributed-2022.2.1 fsspec-2023.12.2 h5py-3.10.0 holoviews-1.14.9 hvplot-0.7.1 jinja2-3.0.2 llvmlite-0.41.1 locket-1.0.0 msgpack-1.0.7 multipledispatch-1.0.0 numba-0.58.1 panel-0.10.3 param-1.13.0 partd-1.4.1 pyzstd-0.15.9 selenium-3.141.0 sortedcontainers-2.4.0 tblib-3.0.0 toolz-0.12.0 xarray-2023.1.0 zict-3.0.0\n" - ] - } - ], - "source": [ - "!pip install \"alphatims[plotting-stable]\"" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "eff243a9", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "application/javascript": [ - "\n", - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls == null || js_urls.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " var skip = [];\n", - " if (window.requirejs) {\n", - " require([], function() {\n", - " })\n", - " }\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " if (skip.indexOf(url) >= 0) { on_load(); continue; }\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - "\tif (!js_urls.length) {\n", - " on_load()\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " var js_urls = [];\n", - " var css_urls = [];\n", - "\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " inject_raw_css(\".bk.alert {\\n padding: 0.75rem 1.25rem;\\n border: 1px solid transparent;\\n border-radius: 0.25rem;\\n /* Don't set margin because that will not render correctly! */\\n /* margin-bottom: 1rem; */\\n margin-top: 15px;\\n margin-bottom: 15px;\\n}\\n.bk.alert a {\\n color: rgb(11, 46, 19); /* #002752; */\\n font-weight: 700;\\n text-decoration: rgb(11, 46, 19);\\n text-decoration-color: rgb(11, 46, 19);\\n text-decoration-line: none;\\n text-decoration-style: solid;\\n text-decoration-thickness: auto;\\n }\\n.bk.alert a:hover {\\n color: rgb(11, 46, 19);\\n font-weight: 700;\\n text-decoration: underline;\\n}\\n\\n.bk.alert-primary {\\n color: #004085;\\n background-color: #cce5ff;\\n border-color: #b8daff;\\n}\\n.bk.alert-primary hr {\\n border-top-color: #9fcdff;\\n}\\n\\n.bk.alert-secondary {\\n color: #383d41;\\n background-color: #e2e3e5;\\n border-color: #d6d8db;\\n }\\n.bk.alert-secondary hr {\\n border-top-color: #c8cbcf;\\n}\\n\\n.bk.alert-success {\\n color: #155724;\\n background-color: #d4edda;\\n border-color: #c3e6cb;\\n }\\n\\n.bk.alert-success hr {\\n border-top-color: #b1dfbb;\\n}\\n\\n.bk.alert-info {\\n color: #0c5460;\\n background-color: #d1ecf1;\\n border-color: #bee5eb;\\n }\\n.bk.alert-info hr {\\n border-top-color: #abdde5;\\n}\\n\\n.bk.alert-warning {\\n color: #856404;\\n background-color: #fff3cd;\\n border-color: #ffeeba;\\n }\\n\\n.bk.alert-warning hr {\\n border-top-color: #ffe8a1;\\n}\\n\\n.bk.alert-danger {\\n color: #721c24;\\n background-color: #f8d7da;\\n border-color: #f5c6cb;\\n}\\n.bk.alert-danger hr {\\n border-top-color: #f1b0b7;\\n}\\n\\n.bk.alert-light {\\n color: #818182;\\n background-color: #fefefe;\\n border-color: #fdfdfe;\\n }\\n.bk.alert-light hr {\\n border-top-color: #ececf6;\\n}\\n\\n.bk.alert-dark {\\n color: #1b1e21;\\n background-color: #d6d8d9;\\n border-color: #c6c8ca;\\n }\\n.bk.alert-dark hr {\\n border-top-color: #b9bbbe;\\n}\\n\\n\\n/* adjf\\u00e6l */\\n\\n.bk.alert-primary a {\\n color: #002752;\\n}\\n\\n.bk.alert-secondary a {\\n color: #202326;\\n}\\n\\n\\n.bk.alert-success a {\\n color: #0b2e13;\\n}\\n\\n\\n.bk.alert-info a {\\n color: #062c33;\\n}\\n\\n\\n.bk.alert-warning a {\\n color: #533f03;\\n}\\n\\n\\n.bk.alert-danger a {\\n color: #491217;\\n}\\n\\n.bk.alert-light a {\\n color: #686868;\\n}\\n\\n.bk.alert-dark a {\\n color: #040505;\\n}\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".bk.card {\\n border: 1px solid rgba(0,0,0,.125);\\n border-radius: 0.25rem;\\n}\\n.bk.accordion {\\n border: 1px solid rgba(0,0,0,.125);\\n}\\n.bk.card-header {\\n align-items: center;\\n background-color: rgba(0, 0, 0, 0.03);\\n border-radius: 0.25rem;\\n display: flex;\\n justify-content: space-between;\\n padding: 0 1.25rem 0 0;\\n width: 100%;\\n}\\n.bk.accordion-header {\\n align-items: center;\\n background-color: rgba(0, 0, 0, 0.03);\\n border-radius: 0;\\n display: flex;\\n justify-content: space-between;\\n padding: 0 1.25rem 0 0;\\n width: 100%;\\n}\\np.bk.card-button {\\n background-color: transparent;\\n font-size: 1.25rem;\\n font-weight: 700;\\n margin: 0;\\n margin-left: -15px;\\n}\\n.bk.card-header-row {\\n position: relative !important;\\n}\\n.bk.card-title {\\n align-items: center;\\n display: flex !important;\\n font-size: 1.4em;\\n font-weight: bold;\\n padding: 0.25em;\\n position: relative !important;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\"table.panel-df {\\n margin-left: auto;\\n margin-right: auto;\\n border: none;\\n border-collapse: collapse;\\n border-spacing: 0;\\n color: black;\\n font-size: 12px;\\n table-layout: fixed;\\n width: 100%;\\n}\\n\\n.panel-df tr, .panel-df th, .panel-df td {\\n text-align: right;\\n vertical-align: middle;\\n padding: 0.5em 0.5em !important;\\n line-height: normal;\\n white-space: normal;\\n max-width: none;\\n border: none;\\n}\\n\\n.panel-df tbody {\\n display: table-row-group;\\n vertical-align: middle;\\n border-color: inherit;\\n}\\n\\n.panel-df tbody tr:nth-child(odd) {\\n background: #f5f5f5;\\n}\\n\\n.panel-df thead {\\n border-bottom: 1px solid black;\\n vertical-align: bottom;\\n}\\n\\n.panel-df tr:hover {\\n background: lightblue !important;\\n cursor: pointer;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-row,\\n.json-formatter-row a,\\n.json-formatter-row a:hover {\\n color: black;\\n text-decoration: none;\\n}\\n.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-row .json-formatter-string,\\n.json-formatter-row .json-formatter-stringifiable {\\n color: green;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-row .json-formatter-number {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-boolean {\\n color: red;\\n}\\n.json-formatter-row .json-formatter-null {\\n color: #855A00;\\n}\\n.json-formatter-row .json-formatter-undefined {\\n color: #ca0b69;\\n}\\n.json-formatter-row .json-formatter-function {\\n color: #FF20ED;\\n}\\n.json-formatter-row .json-formatter-date {\\n background-color: rgba(0, 0, 0, 0.05);\\n}\\n.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: blue;\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-bracket {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-key {\\n color: #00008B;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n.json-formatter-dark.json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-dark.json-formatter-row,\\n.json-formatter-dark.json-formatter-row a,\\n.json-formatter-dark.json-formatter-row a:hover {\\n color: white;\\n text-decoration: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-string,\\n.json-formatter-dark.json-formatter-row .json-formatter-stringifiable {\\n color: #31F031;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-number {\\n color: #66C2FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-boolean {\\n color: #EC4242;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-null {\\n color: #EEC97D;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-undefined {\\n color: #ef8fbe;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-function {\\n color: #FD48CB;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-date {\\n background-color: rgba(255, 255, 255, 0.05);\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: #027BFF;\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-bracket {\\n color: #9494FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-key {\\n color: #23A0DB;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-dark.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-dark.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".codehilite .hll { background-color: #ffffcc }\\n.codehilite { background: #f8f8f8; }\\n.codehilite .c { color: #408080; font-style: italic } /* Comment */\\n.codehilite .err { border: 1px solid #FF0000 } /* Error */\\n.codehilite .k { color: #008000; font-weight: bold } /* Keyword */\\n.codehilite .o { color: #666666 } /* Operator */\\n.codehilite .ch { color: #408080; font-style: italic } /* Comment.Hashbang */\\n.codehilite .cm { color: #408080; font-style: italic } /* Comment.Multiline */\\n.codehilite .cp { color: #BC7A00 } /* Comment.Preproc */\\n.codehilite .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */\\n.codehilite .c1 { color: #408080; font-style: italic } /* Comment.Single */\\n.codehilite .cs { color: #408080; font-style: italic } /* Comment.Special */\\n.codehilite .gd { color: #A00000 } /* Generic.Deleted */\\n.codehilite .ge { font-style: italic } /* Generic.Emph */\\n.codehilite .gr { color: #FF0000 } /* Generic.Error */\\n.codehilite .gh { color: #000080; font-weight: bold } /* Generic.Heading */\\n.codehilite .gi { color: #00A000 } /* Generic.Inserted */\\n.codehilite .go { color: #888888 } /* Generic.Output */\\n.codehilite .gp { color: #000080; font-weight: bold } /* Generic.Prompt */\\n.codehilite .gs { font-weight: bold } /* Generic.Strong */\\n.codehilite .gu { color: #800080; font-weight: bold } /* Generic.Subheading */\\n.codehilite .gt { color: #0044DD } /* Generic.Traceback */\\n.codehilite .kc { color: #008000; font-weight: bold } /* Keyword.Constant */\\n.codehilite .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */\\n.codehilite .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */\\n.codehilite .kp { color: #008000 } /* Keyword.Pseudo */\\n.codehilite .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */\\n.codehilite .kt { color: #B00040 } /* Keyword.Type */\\n.codehilite .m { color: #666666 } /* Literal.Number */\\n.codehilite .s { color: #BA2121 } /* Literal.String */\\n.codehilite .na { color: #7D9029 } /* Name.Attribute */\\n.codehilite .nb { color: #008000 } /* Name.Builtin */\\n.codehilite .nc { color: #0000FF; font-weight: bold } /* Name.Class */\\n.codehilite .no { color: #880000 } /* Name.Constant */\\n.codehilite .nd { color: #AA22FF } /* Name.Decorator */\\n.codehilite .ni { color: #999999; font-weight: bold } /* Name.Entity */\\n.codehilite .ne { color: #D2413A; font-weight: bold } /* Name.Exception */\\n.codehilite .nf { color: #0000FF } /* Name.Function */\\n.codehilite .nl { color: #A0A000 } /* Name.Label */\\n.codehilite .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */\\n.codehilite .nt { color: #008000; font-weight: bold } /* Name.Tag */\\n.codehilite .nv { color: #19177C } /* Name.Variable */\\n.codehilite .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */\\n.codehilite .w { color: #bbbbbb } /* Text.Whitespace */\\n.codehilite .mb { color: #666666 } /* Literal.Number.Bin */\\n.codehilite .mf { color: #666666 } /* Literal.Number.Float */\\n.codehilite .mh { color: #666666 } /* Literal.Number.Hex */\\n.codehilite .mi { color: #666666 } /* Literal.Number.Integer */\\n.codehilite .mo { color: #666666 } /* Literal.Number.Oct */\\n.codehilite .sa { color: #BA2121 } /* Literal.String.Affix */\\n.codehilite .sb { color: #BA2121 } /* Literal.String.Backtick */\\n.codehilite .sc { color: #BA2121 } /* Literal.String.Char */\\n.codehilite .dl { color: #BA2121 } /* Literal.String.Delimiter */\\n.codehilite .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */\\n.codehilite .s2 { color: #BA2121 } /* Literal.String.Double */\\n.codehilite .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */\\n.codehilite .sh { color: #BA2121 } /* Literal.String.Heredoc */\\n.codehilite .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */\\n.codehilite .sx { color: #008000 } /* Literal.String.Other */\\n.codehilite .sr { color: #BB6688 } /* Literal.String.Regex */\\n.codehilite .s1 { color: #BA2121 } /* Literal.String.Single */\\n.codehilite .ss { color: #19177C } /* Literal.String.Symbol */\\n.codehilite .bp { color: #008000 } /* Name.Builtin.Pseudo */\\n.codehilite .fm { color: #0000FF } /* Name.Function.Magic */\\n.codehilite .vc { color: #19177C } /* Name.Variable.Class */\\n.codehilite .vg { color: #19177C } /* Name.Variable.Global */\\n.codehilite .vi { color: #19177C } /* Name.Variable.Instance */\\n.codehilite .vm { color: #19177C } /* Name.Variable.Magic */\\n.codehilite .il { color: #666666 } /* Literal.Number.Integer.Long */\\n\\n.markdown h1 { margin-block-start: 0.34em }\\n.markdown h2 { margin-block-start: 0.42em }\\n.markdown h3 { margin-block-start: 0.5em }\\n.markdown h4 { margin-block-start: 0.67em }\\n.markdown h5 { margin-block-start: 0.84em }\\n.markdown h6 { margin-block-start: 1.17em }\\n.markdown ul { padding-inline-start: 2em }\\n.markdown ol { padding-inline-start: 2em }\\n.markdown strong { font-weight: 600 }\\n.markdown a { color: -webkit-link }\\n.markdown a { color: -moz-hyperlinkText }\\n\");\n", - " },\n", - " function(Bokeh) {\n", - " inject_raw_css(\".bk.panel-widget-box {\\n\\tmin-height: 20px;\\n\\tbackground-color: #f5f5f5;\\n\\tborder: 1px solid #e3e3e3;\\n\\tborder-radius: 4px;\\n\\t-webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.05);\\n\\tbox-shadow: inset 0 1px 1px rgba(0,0,0,.05);\\n\\toverflow-x: hidden;\\n\\toverflow-y: hidden;\\n}\\n\\n.scrollable {\\n overflow: scroll;\\n}\\n\\nprogress {\\n\\tappearance: none;\\n\\t-moz-appearance: none;\\n\\t-webkit-appearance: none;\\n\\n\\tborder: none;\\n\\theight: 20px;\\n\\tbackground-color: whiteSmoke;\\n\\tborder-radius: 3px;\\n\\tbox-shadow: 0 2px 3px rgba(0,0,0,.5) inset;\\n\\tcolor: royalblue;\\n\\tposition: relative;\\n\\tmargin: 0 0 1.5em;\\n}\\n\\nprogress[value]::-webkit-progress-bar {\\n\\tbackground-color: whiteSmoke;\\n\\tborder-radius: 3px;\\n\\tbox-shadow: 0 2px 3px rgba(0,0,0,.5) inset;\\n}\\n\\nprogress[value]::-webkit-progress-value {\\n\\tposition: relative;\\n\\n\\tbackground-size: 35px 20px, 100% 100%, 100% 100%;\\n\\tborder-radius:3px;\\n}\\n\\nprogress.active:not([value])::before {\\n\\tbackground-position: 10%;\\n\\tanimation-name: stripes;\\n\\tanimation-duration: 3s;\\n\\tanimation-timing-function: linear;\\n\\tanimation-iteration-count: infinite;\\n}\\n\\nprogress[value]::-moz-progress-bar {\\n\\tbackground-size: 35px 20px, 100% 100%, 100% 100%;\\n\\tborder-radius:3px;\\n}\\n\\nprogress:not([value])::-moz-progress-bar {\\n\\tborder-radius:3px;\\n\\tbackground:\\n\\tlinear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n\\n}\\n\\nprogress.active:not([value])::-moz-progress-bar {\\n\\tbackground-position: 10%;\\n\\tanimation-name: stripes;\\n\\tanimation-duration: 3s;\\n\\tanimation-timing-function: linear;\\n\\tanimation-iteration-count: infinite;\\n}\\n\\nprogress.active:not([value])::-webkit-progress-bar {\\n\\tbackground-position: 10%;\\n\\tanimation-name: stripes;\\n\\tanimation-duration: 3s;\\n\\tanimation-timing-function: linear;\\n\\tanimation-iteration-count: infinite;\\n}\\n\\nprogress.primary[value]::-webkit-progress-value { background-color: #007bff; }\\nprogress.primary:not([value])::before { background-color: #007bff; }\\nprogress.primary:not([value])::-webkit-progress-bar { background-color: #007bff; }\\nprogress.primary::-moz-progress-bar { background-color: #007bff; }\\n\\nprogress.secondary[value]::-webkit-progress-value { background-color: #6c757d; }\\nprogress.secondary:not([value])::before { background-color: #6c757d; }\\nprogress.secondary:not([value])::-webkit-progress-bar { background-color: #6c757d; }\\nprogress.secondary::-moz-progress-bar { background-color: #6c757d; }\\n\\nprogress.success[value]::-webkit-progress-value { background-color: #28a745; }\\nprogress.success:not([value])::before { background-color: #28a745; }\\nprogress.success:not([value])::-webkit-progress-bar { background-color: #28a745; }\\nprogress.success::-moz-progress-bar { background-color: #28a745; }\\n\\nprogress.danger[value]::-webkit-progress-value { background-color: #dc3545; }\\nprogress.danger:not([value])::before { background-color: #dc3545; }\\nprogress.danger:not([value])::-webkit-progress-bar { background-color: #dc3545; }\\nprogress.danger::-moz-progress-bar { background-color: #dc3545; }\\n\\nprogress.warning[value]::-webkit-progress-value { background-color: #ffc107; }\\nprogress.warning:not([value])::before { background-color: #ffc107; }\\nprogress.warning:not([value])::-webkit-progress-bar { background-color: #ffc107; }\\nprogress.warning::-moz-progress-bar { background-color: #ffc107; }\\n\\nprogress.info[value]::-webkit-progress-value { background-color: #17a2b8; }\\nprogress.info:not([value])::before { background-color: #17a2b8; }\\nprogress.info:not([value])::-webkit-progress-bar { background-color: #17a2b8; }\\nprogress.info::-moz-progress-bar { background-color: #17a2b8; }\\n\\nprogress.light[value]::-webkit-progress-value { background-color: #f8f9fa; }\\nprogress.light:not([value])::before { background-color: #f8f9fa; }\\nprogress.light:not([value])::-webkit-progress-bar { background-color: #f8f9fa; }\\nprogress.light::-moz-progress-bar { background-color: #f8f9fa; }\\n\\nprogress.dark[value]::-webkit-progress-value { background-color: #343a40; }\\nprogress.dark:not([value])::-webkit-progress-bar { background-color: #343a40; }\\nprogress.dark:not([value])::before { background-color: #343a40; }\\nprogress.dark::-moz-progress-bar { background-color: #343a40; }\\n\\nprogress:not([value])::-webkit-progress-bar {\\n\\tborder-radius: 3px;\\n\\tbackground:\\n\\tlinear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\nprogress:not([value])::before {\\n\\tcontent:\\\" \\\";\\n\\tposition:absolute;\\n\\theight: 20px;\\n\\ttop:0;\\n\\tleft:0;\\n\\tright:0;\\n\\tbottom:0;\\n\\tborder-radius: 3px;\\n\\tbackground:\\n\\tlinear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\n\\n@keyframes stripes {\\n from {background-position: 0%}\\n to {background-position: 100%}\\n}\\n\\n.bk.loader::after {\\n content: \\\"\\\";\\n border-radius: 50%;\\n -webkit-mask-image: radial-gradient(transparent 50%, rgba(0, 0, 0, 1) 54%);\\n width: 100%;\\n height: 100%;\\n left: 0;\\n top: 0;\\n position: absolute;\\n}\\n\\n.bk-root .bk.loader.dark::after {\\n background: #0f0f0f;\\n}\\n\\n.bk-root .bk.loader.light::after {\\n background: #f0f0f0;\\n}\\n\\n.bk-root .bk.loader.spin::after {\\n animation: spin 2s linear infinite;\\n}\\n\\n.bk-root div.bk.loader.spin.primary-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #007bff 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.secondary-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #6c757d 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.success-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #28a745 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.danger-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #dc3545 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.warning-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #ffc107 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.info-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #17a2b8 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.light-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #f8f9fa 50%);\\n}\\n\\n.bk-root div.bk.loader.dark-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #343a40 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.primary-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #007bff 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.secondary-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #6c757d 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.success-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #28a745 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.danger-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #dc3545 50%)\\n}\\n\\n.bk-root div.bk.loader.spin.warning-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #ffc107 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.info-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #17a2b8 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.light-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #f8f9fa 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.dark-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #343a40 50%);\\n}\\n\\n/* Safari */\\n@-webkit-keyframes spin {\\n 0% { -webkit-transform: rotate(0deg); }\\n 100% { -webkit-transform: rotate(360deg); }\\n}\\n\\n@keyframes spin {\\n 0% { transform: rotate(0deg); }\\n 100% { transform: rotate(360deg); }\\n}\\n\\n.dot div {\\n height: 100%;\\n width: 100%;\\n border: 1px solid #000 !important;\\n background-color: #fff;\\n border-radius: 50%;\\n display: inline-block;\\n}\\n\\n.dot-filled div {\\n height: 100%;\\n width: 100%;\\n border: 1px solid #000 !important;\\n border-radius: 50%;\\n display: 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this list of conditions and the following disclaimer.\n", - " * \n", - " * Redistributions in binary form must reproduce the above copyright notice,\n", - " * this list of conditions and the following disclaimer in the documentation\n", - " * and/or other materials provided with the distribution.\n", - " * \n", - " * Neither the name of Anaconda nor the names of any contributors\n", - " * may be used to endorse or promote products derived from this software\n", - " * without specific prior written permission.\n", - " * \n", - " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", - " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", - " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", - " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", - " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", - " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", - " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", - " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", - " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", - " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", - " * THE POSSIBILITY OF SUCH DAMAGE.\n", - " */\n", - " (function(root, factory) {\n", - " const bokeh = factory();\n", - " bokeh.__bokeh__ = true;\n", - " if (typeof root.Bokeh === \"undefined\" || typeof root.Bokeh.__bokeh__ === \"undefined\") {\n", - " root.Bokeh = bokeh;\n", - " }\n", - " const Bokeh = root.Bokeh;\n", - " Bokeh[bokeh.version] = bokeh;\n", - " })(this, function() {\n", - " var define;\n", - " var parent_require = typeof require === \"function\" && require\n", - " return (function(modules, entry, aliases, externals) {\n", - " if (aliases === undefined) aliases = {};\n", - " if (externals === undefined) externals = {};\n", - "\n", - " var cache = {};\n", - "\n", - " var normalize = function(name) {\n", - " if (typeof name === \"number\")\n", - " return name;\n", - "\n", - " if (name === \"bokehjs\")\n", - " return entry;\n", - "\n", - " var prefix = \"@bokehjs/\"\n", - " if (name.slice(0, prefix.length) === prefix)\n", - " name = name.slice(prefix.length)\n", - "\n", - " var alias = aliases[name]\n", - " if (alias != null)\n", - " return alias;\n", - "\n", - " var trailing = name.length > 0 && name[name.lenght-1] === \"/\";\n", - " var index = aliases[name + (trailing ? \"\" : \"/\") + \"index\"];\n", - " if (index != null)\n", - " return index;\n", - "\n", - " return name;\n", - " }\n", - "\n", - " var require = function(name) {\n", - " var mod = cache[name];\n", - " if (!mod) {\n", - " var id = normalize(name);\n", - "\n", - " mod = cache[id];\n", - " if (!mod) {\n", - " if (!modules[id]) {\n", - " if (externals[id] === false || (externals[id] == true && parent_require)) {\n", - " try {\n", - " mod = {exports: externals[id] ? parent_require(id) : {}};\n", - " cache[id] = cache[name] = mod;\n", - " return mod.exports;\n", - " } catch (e) {}\n", - " }\n", - "\n", - " var err = new Error(\"Cannot find module '\" + name + \"'\");\n", - " err.code = 'MODULE_NOT_FOUND';\n", - " throw err;\n", - " }\n", - "\n", - " mod = {exports: {}};\n", - " cache[id] = cache[name] = mod;\n", - " modules[id].call(mod.exports, require, mod, mod.exports);\n", - " } else\n", - " cache[name] = mod;\n", - " }\n", - "\n", - " return mod.exports;\n", - " }\n", - " require.resolve = function(name) {\n", - " return \"\"\n", - " }\n", - "\n", - " var main = require(entry);\n", - " main.require = require;\n", - "\n", - " if (typeof Proxy !== \"undefined\") {\n", - " // allow Bokeh.loader[\"@bokehjs/module/name\"] syntax\n", - " main.loader = new Proxy({}, {\n", - " get: function(_obj, module) {\n", - " return require(module);\n", - " }\n", - " });\n", - " }\n", - "\n", - " main.register_plugin = function(plugin_modules, plugin_entry, plugin_aliases, plugin_externals) {\n", - " if (plugin_aliases === undefined) plugin_aliases = {};\n", - " if (plugin_externals === undefined) plugin_externals = {};\n", - "\n", - " for (var name in plugin_modules) {\n", - " modules[name] = plugin_modules[name];\n", - " }\n", - "\n", - " for (var name in plugin_aliases) {\n", - " aliases[name] = plugin_aliases[name];\n", - " }\n", - "\n", - " for (var name in plugin_externals) {\n", - " externals[name] = plugin_externals[name];\n", - " }\n", - "\n", - " var plugin = require(plugin_entry);\n", - "\n", - " for (var name in plugin) {\n", - " main[name] = plugin[name];\n", - " }\n", - "\n", - " return plugin;\n", - " }\n", - "\n", - " return main;\n", - " })\n", - " ([\n", - " function _(e,t,_){Object.defineProperty(_,\"__esModule\",{value:!0});e(1).__exportStar(e(2),_)},\n", - " function _(t,e,n){\n", - " /*! *****************************************************************************\n", - " Copyright (c) Microsoft Corporation.\n", - " \n", - " Permission to use, copy, modify, and/or distribute this software for any\n", - " purpose with or without fee is hereby granted.\n", - " \n", - " THE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\n", - " REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\n", - " AND FITNESS. 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v.Model&&s.name==e&&t.push(s);switch(t.length){case 0:return null;case 1:return t[0];default:throw new Error(`Multiple models are named '${e}'`)}}on_message(e,t){const s=this._message_callbacks.get(e);null==s?this._message_callbacks.set(e,new Set([t])):s.add(t)}remove_on_message(e,t){var s;null===(s=this._message_callbacks.get(e))||void 0===s||s.delete(t)}_trigger_on_message(e,t){const s=this._message_callbacks.get(e);if(null!=s)for(const e of s)e(t)}on_change(e,t=!1){this._callbacks.has(e)||this._callbacks.set(e,t)}remove_on_change(e){this._callbacks.delete(e)}_trigger_on_change(e){for(const[t,s]of this._callbacks)if(!s&&e instanceof b.DocumentEventBatch)for(const s of e.events)t(s);else t(e)}_notify_change(e,t,s,o,n){this._trigger_on_change(new b.ModelChangedEvent(this,e,t,s,o,null==n?void 0:n.setter_id,null==n?void 0:n.hint))}static _references_json(e,t=!0){const s=[];for(const o of e){const e=o.struct();e.attributes=o.attributes_as_json(t),delete e.attributes.id,s.push(e)}return s}static _instantiate_object(e,t,s){const o=Object.assign(Object.assign({},s),{id:e,__deferred__:!0});return new(n.Models(t))(o)}static _instantiate_references_json(e,t){const s=new Map;for(const o of e){const e=o.id,n=o.type,r=o.attributes||{};let i=t.get(e);null==i&&(i=j._instantiate_object(e,n,r),null!=o.subtype&&i.set_subtype(o.subtype)),s.set(i.id,i)}return s}static _resolve_refs(e,t,s,o){function n(e){if(c.is_ref(e)){if(t.has(e.id))return t.get(e.id);if(s.has(e.id))return s.get(e.id);throw new Error(`reference ${JSON.stringify(e)} isn't known (not in Document?)`)}return h.is_NDArray_ref(e)?h.decode_NDArray(e,o):g.isArray(e)?function(e){const t=[];for(const s of e)t.push(n(s));return t}(e):g.isPlainObject(e)?function(e){const t={};for(const[s,o]of f.entries(e))t[s]=n(o);return t}(e):e}return n(e)}static _initialize_references_json(e,t,s,o){const n=new Map;for(const{id:r,attributes:i}of e){const e=!t.has(r),_=e?s.get(r):t.get(r),a=j._resolve_refs(i,t,s,o);_.setv(a,{silent:!0}),n.set(r,{instance:_,is_new:e})}const r=[],i=new Set;function _(e){if(e instanceof a.HasProps){if(n.has(e.id)&&!i.has(e.id)){i.add(e.id);const{instance:t,is_new:s}=n.get(e.id),{attributes:o}=t;for(const e of f.values(o))_(e);s&&(t.finalize(),r.push(t))}}else if(g.isArray(e))for(const t of e)_(t);else if(g.isPlainObject(e))for(const t of f.values(e))_(t)}for(const e of n.values())_(e.instance);for(const e of r)e.connect_signals()}static _event_for_attribute_change(e,t,s,o,n){if(o.get_model_by_id(e.id).property(t).syncable){const r={kind:\"ModelChanged\",model:{id:e.id},attr:t,new:s};return a.HasProps._json_record_references(o,s,n,{recursive:!0}),r}return null}static _events_to_sync_objects(e,t,s,o){const n=Object.keys(e.attributes),r=Object.keys(t.attributes),_=d.difference(n,r),a=d.difference(r,n),l=d.intersection(n,r),c=[];for(const e of _)i.logger.warn(`Server sent key ${e} but we don't seem to have it in our JSON`);for(const n of a){const r=t.attributes[n];c.push(j._event_for_attribute_change(e,n,r,s,o))}for(const n of l){const r=e.attributes[n],i=t.attributes[n];null==r&&null==i||(null==r||null==i?c.push(j._event_for_attribute_change(e,n,i,s,o)):m.isEqual(r,i)||c.push(j._event_for_attribute_change(e,n,i,s,o)))}return c.filter(e=>null!=e)}static _compute_patch_since_json(e,t){const s=t.to_json(!1);function o(e){const t=new Map;for(const s of e.roots.references)t.set(s.id,s);return t}const n=o(e),r=new Map,i=[];for(const t of e.roots.root_ids)r.set(t,n.get(t)),i.push(t);const _=o(s),a=new Map,l=[];for(const e of s.roots.root_ids)a.set(e,_.get(e)),l.push(e);if(i.sort(),l.sort(),d.difference(i,l).length>0||d.difference(l,i).length>0)throw new Error(\"Not implemented: computing add/remove of document roots\");const c=new Set;let h=[];for(const e of t._all_models.keys())if(n.has(e)){const s=j._events_to_sync_objects(n.get(e),_.get(e),t,c);h=h.concat(s)}return{references:j._references_json(c,!1),events:h}}to_json_string(e=!0){return JSON.stringify(this.to_json(e))}to_json(e=!0){const t=this._roots.map(e=>e.id),s=this._all_models.values();return{version:r.version,title:this._title,roots:{root_ids:t,references:j._references_json(s,e)}}}static from_json_string(e){const t=JSON.parse(e);return j.from_json(t)}static from_json(e){i.logger.debug(\"Creating Document from JSON\");const t=e.version,s=-1!==t.indexOf(\"+\")||-1!==t.indexOf(\"-\"),o=`Library versions: JS (${r.version}) / Python (${t})`;s||r.version.replace(/-(dev|rc)\\./,\"$1\")==t?i.logger.debug(o):(i.logger.warn(\"JS/Python version mismatch\"),i.logger.warn(o));const n=e.roots,_=n.root_ids,a=n.references,l=j._instantiate_references_json(a,new Map);j._initialize_references_json(a,new Map,l,new Map);const c=new j;for(const e of _){const t=l.get(e);null!=t&&c.add_root(t)}return 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ready(){return this._ready}connect(t,e){return t.connect((t,s)=>{const i=Promise.resolve(e.call(this,t,s));this._ready=this._ready.then(()=>i)},this)}disconnect(t,e){return t.disconnect(e,this)}initialize(){this._has_finished=!1,this.is_root&&(this._stylesheet=n.stylesheet);for(const t of this.styles())this.stylesheet.append(t)}async lazy_initialize(){}remove(){this._parent=void 0,this.disconnect_signals(),this.removed.emit()}toString(){return`${this.model.type}View(${this.model.id})`}serializable_state(){return{type:this.model.type}}get parent(){if(void 0!==this._parent)return this._parent;throw new Error(\"parent of a view wasn't configured\")}get is_root(){return null===this.parent}get root(){return this.is_root?this:this.parent.root}assert_root(){if(!this.is_root)throw new Error(this.toString()+\" is not a root layout\")}has_finished(){return this._has_finished}get is_idle(){return 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t=/^\\s*(?=(?:(?:[-a-z]+\\s*){0,2}(italic|oblique))?)(?=(?:(?:[-a-z]+\\s*){0,2}(small-caps))?)(?=(?:(?:[-a-z]+\\s*){0,2}(bold(?:er)?|lighter|[1-9]00))?)(?:(?:normal|\\1|\\2|\\3)\\s*){0,3}((?:xx?-)?(?:small|large)|medium|smaller|larger|[.\\d]+(?:\\%|in|[cem]m|ex|p[ctx]))(?:\\s*\\/\\s*(normal|[.\\d]+(?:\\%|in|[cem]m|ex|p[ctx])))?\\s*([-,\\'\\\"\\sa-z0-9]+?)\\s*$/i.exec(this.font),e={style:t[1]||\"normal\",size:t[4]||\"10px\",family:t[6]||\"sans-serif\",weight:t[3]||\"normal\",decoration:t[2]||\"normal\"};return\"underline\"===this.__fontUnderline&&(e.decoration=\"underline\"),null!=this.__fontHref&&(e.href=this.__fontHref),e}__wrapTextLink(t,e){if(t.href){const i=this.__createElement(\"a\");return i.setAttributeNS(\"http://www.w3.org/1999/xlink\",\"xlink:href\",t.href),i.appendChild(e),i}return e}__applyText(t,e,i,s){const n=this.__parseFont(),r=this.__createElement(\"text\",{\"font-family\":n.family,\"font-size\":n.size,\"font-style\":n.style,\"font-weight\":n.weight,\"text-decoration\":n.decoration,x:e,y:i,\"text-anchor\":o(this.textAlign),\"dominant-baseline\":l(this.textBaseline)},!0);r.appendChild(this.__document.createTextNode(t)),this._apply_transform(r),this.__currentElement=r,this.__applyStyleToCurrentElement(s),this.__root.appendChild(this.__wrapTextLink(n,r))}fillText(t,e,i){null!=t&&isFinite(e+i)&&this.__applyText(t,e,i,\"fill\")}strokeText(t,e,i){null!=t&&isFinite(e+i)&&this.__applyText(t,e,i,\"stroke\")}measureText(t){return this.__ctx.font=this.font,this.__ctx.measureText(t)}arc(t,e,i,s,n,r=!1){if(!isFinite(t+e+i+s+n))return;if(s===n)return;(s%=2*Math.PI)===(n%=2*Math.PI)&&(n=(n+2*Math.PI-.001*(r?-1:1))%(2*Math.PI));const a=t+i*Math.cos(n),o=e+i*Math.sin(n),l=t+i*Math.cos(s),h=e+i*Math.sin(s),c=r?0:1;let _=0,u=n-s;u<0&&(u+=2*Math.PI),_=r?u>Math.PI?0:1:u>Math.PI?1:0,this.lineTo(l,h);const p=i,d=i,[m,f]=this._transform.apply(a,o);this.__addPathCommand(m,f,`A ${p} ${d} 0 ${_} ${c} ${m} ${f}`)}clip(){const t=this.__createElement(\"clipPath\"),e=a(this.__ids);this.__applyCurrentDefaultPath(),t.setAttribute(\"id\",e),t.appendChild(this.__currentElement),this.__defs.appendChild(t),this._clip_path=`url(#${e})`}drawImage(t,...e){let i,s,n,r,a,o,l,h;if(2==e.length){if([i,s]=e,!isFinite(i+s))return;a=0,o=0,l=t.width,h=t.height,n=l,r=h}else if(4==e.length){if([i,s,n,r]=e,!isFinite(i+s+n+r))return;a=0,o=0,l=t.width,h=t.height}else{if(8!==e.length)throw new Error(\"Inavlid number of arguments passed to drawImage: \"+arguments.length);if([a,o,l,h,i,s,n,r]=e,!isFinite(a+o+l+h+i+s+n+r))return}const c=this.__root,_=\"translate(\"+i+\", \"+s+\")\",u=this._transform.clone().translate(i,s);if(t instanceof p||t instanceof SVGSVGElement){const e=(t instanceof SVGSVGElement?t:t.get_svg()).cloneNode(!0);let i;u.is_identity?i=c:(i=this.__createElement(\"g\"),this._apply_transform(i,u),c.appendChild(i));for(const t of[...e.childNodes])if(t instanceof SVGDefsElement){for(const e of[...t.childNodes])if(e instanceof Element){const t=e.getAttribute(\"id\");this.__ids[t]=t,this.__defs.appendChild(e)}}else i.appendChild(t)}else if(t instanceof HTMLImageElement||t instanceof SVGImageElement){const e=this.__createElement(\"image\");if(e.setAttribute(\"width\",\"\"+n),e.setAttribute(\"height\",\"\"+r),e.setAttribute(\"preserveAspectRatio\",\"none\"),a||o||l!==t.width||h!==t.height){const e=this.__document.createElement(\"canvas\");e.width=n,e.height=r;e.getContext(\"2d\").drawImage(t,a,o,l,h,0,0,n,r),t=e}e.setAttribute(\"transform\",_);const i=t instanceof HTMLCanvasElement?t.toDataURL():t.getAttribute(\"src\");e.setAttributeNS(\"http://www.w3.org/1999/xlink\",\"xlink:href\",i),c.appendChild(e)}else if(t instanceof HTMLCanvasElement){const e=this.__createElement(\"image\");e.setAttribute(\"width\",\"\"+n),e.setAttribute(\"height\",\"\"+r),e.setAttribute(\"preserveAspectRatio\",\"none\");const i=this.__document.createElement(\"canvas\");i.width=n,i.height=r;const s=i.getContext(\"2d\");s.imageSmoothingEnabled=!1,s.drawImage(t,a,o,l,h,0,0,n,r),t=i,e.setAttribute(\"transform\",_),e.setAttributeNS(\"http://www.w3.org/1999/xlink\",\"xlink:href\",t.toDataURL()),c.appendChild(e)}}createPattern(t,e){const i=this.__document.createElementNS(\"http://www.w3.org/2000/svg\",\"pattern\"),s=a(this.__ids);if(i.setAttribute(\"id\",s),i.setAttribute(\"width\",\"\"+this._to_number(t.width)),i.setAttribute(\"height\",\"\"+this._to_number(t.height)),i.setAttribute(\"patternUnits\",\"userSpaceOnUse\"),t instanceof HTMLCanvasElement||t instanceof HTMLImageElement||t instanceof SVGImageElement){const e=this.__document.createElementNS(\"http://www.w3.org/2000/svg\",\"image\"),s=t instanceof HTMLCanvasElement?t.toDataURL():t.getAttribute(\"src\");e.setAttributeNS(\"http://www.w3.org/1999/xlink\",\"xlink:href\",s),i.appendChild(e),this.__defs.appendChild(i)}else if(t instanceof p){for(const e of[...t.__root.childNodes])e instanceof SVGDefsElement||i.appendChild(e);this.__defs.appendChild(i)}else{if(!(t instanceof SVGSVGElement))throw new Error(\"unsupported\");for(const e of[...t.childNodes])e instanceof SVGDefsElement||i.appendChild(e);this.__defs.appendChild(i)}return new u(i,this)}setLineDash(t){t&&t.length>0?this.lineDash=t.join(\",\"):this.lineDash=null}_to_number(t){return n.isNumber(t)?t:t.baseVal.value}}i.SVGRenderingContext2D=p,p.__name__=\"SVGRenderingContext2D\"},\n", - " function _(t,s,r){Object.defineProperty(r,\"__esModule\",{value:!0});const{sin:e,cos:n}=Math;class i{constructor(t=1,s=0,r=0,e=1,n=0,i=0){this.a=t,this.b=s,this.c=r,this.d=e,this.e=n,this.f=i}toString(){const{a:t,b:s,c:r,d:e,e:n,f:i}=this;return`matrix(${t}, ${s}, ${r}, ${e}, ${n}, 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d.SVGRenderingContext2D;this._ctx=e,this._canvas=e.get_svg(),this._el=r.div({style:v},this._canvas);break}}_.fixup_ctx(this._ctx)}get canvas(){return this._canvas}get ctx(){return this._ctx}get el(){return this._el}resize(e,t){this.bbox=new c.BBox({left:0,top:0,width:e,height:t});const i=this._ctx instanceof d.SVGRenderingContext2D?this._ctx:this.canvas;i.width=e*this.pixel_ratio,i.height=t*this.pixel_ratio}prepare(){const{ctx:e,hidpi:t,pixel_ratio:i}=this;e.save(),t&&(e.scale(i,i),e.translate(.5,.5)),this.clear()}clear(){const{x:e,y:t,width:i,height:s}=this.bbox;this.ctx.clearRect(e,t,i,s)}finish(){this.ctx.restore()}to_blob(){const{_canvas:e}=this;if(e instanceof HTMLCanvasElement)return null!=e.msToBlob?Promise.resolve(e.msToBlob()):new Promise((t,i)=>{e.toBlob(e=>null!=e?t(e):i(),\"image/png\")});{const e=this._ctx.get_serialized_svg(!0),t=new Blob([e],{type:\"image/svg+xml\"});return Promise.resolve(t)}}}i.CanvasLayer=b,b.__name__=\"CanvasLayer\";class g extends n.DOMView{constructor(){super(...arguments),this.bbox=new c.BBox}initialize(){super.initialize();const{output_backend:e,hidpi:t}=this.model;\"webgl\"==e&&(this.webgl=p),this.underlays_el=r.div({style:v}),this.primary=new b(e,t),this.overlays=new b(e,t),this.overlays_el=r.div({style:v}),this.events_el=r.div({class:\"bk-canvas-events\",style:v});const i=[this.underlays_el,this.primary.el,this.overlays.el,this.overlays_el,this.events_el];h.extend(this.el.style,v),r.append(this.el,...i),l.logger.debug(\"CanvasView initialized\")}add_underlay(e){this.underlays_el.appendChild(e)}add_overlay(e){this.overlays_el.appendChild(e)}add_event(e){this.events_el.appendChild(e)}get pixel_ratio(){return this.primary.pixel_ratio}resize(e,t){this.bbox=new c.BBox({left:0,top:0,width:e,height:t}),this.primary.resize(e,t),this.overlays.resize(e,t)}prepare_webgl(e){const{webgl:t}=this;if(null!=t){const{width:i,height:s}=this.bbox;t.canvas.width=this.pixel_ratio*i,t.canvas.height=this.pixel_ratio*s;const{gl:a}=t;a.enable(a.SCISSOR_TEST);const[n,l,o,r]=e,{xview:h,yview:c}=this.bbox,_=h.compute(n),d=c.compute(l+r),p=this.pixel_ratio;a.scissor(p*_,p*d,p*o,p*r),a.enable(a.BLEND),a.blendFuncSeparate(a.SRC_ALPHA,a.ONE_MINUS_SRC_ALPHA,a.ONE_MINUS_DST_ALPHA,a.ONE)}}clear_webgl(){const{webgl:e}=this;if(null!=e){const{gl:t,canvas:i}=e;t.viewport(0,0,i.width,i.height),t.clearColor(0,0,0,0),t.clear(t.COLOR_BUFFER_BIT||t.DEPTH_BUFFER_BIT)}}blit_webgl(e){const{webgl:t}=this;if(null!=t&&(l.logger.debug(\"Blitting WebGL canvas\"),e.restore(),e.drawImage(t.canvas,0,0),e.save(),this.model.hidpi)){const t=this.pixel_ratio;e.scale(t,t),e.translate(.5,.5)}}compose(){const{output_backend:e,hidpi:t}=this.model,{width:i,height:s}=this.bbox,a=new b(e,t);return a.resize(i,s),a.ctx.drawImage(this.primary.canvas,0,0),a.ctx.drawImage(this.overlays.canvas,0,0),a}to_blob(){return this.compose().to_blob()}}i.CanvasView=g,g.__name__=\"CanvasView\";class x extends a.HasProps{constructor(e){super(e)}static init_Canvas(){this.prototype.default_view=g,this.internal({hidpi:[o.Boolean,!0],output_backend:[o.OutputBackend,\"canvas\"]})}}i.Canvas=x,x.__name__=\"Canvas\",x.init_Canvas()},\n", - " function _(e,s,t){Object.defineProperty(t,\"__esModule\",{value:!0});const i=e(71),r=e(72);class n extends i.View{initialize(){super.initialize(),this.el=this._createElement()}remove(){r.remove(this.el),super.remove()}css_classes(){return[]}render(){}renderTo(e){e.appendChild(this.el),this.render()}_createElement(){return r.createElement(this.tagName,{class:this.css_classes()})}}t.DOMView=n,n.__name__=\"DOMView\",n.prototype.tagName=\"div\"},\n", - " function _(t,i,e){Object.defineProperty(e,\"__esModule\",{value:!0});const h=t(24),{min:r,max:s}=Math;e.empty=function(){return{x0:1/0,y0:1/0,x1:-1/0,y1:-1/0}},e.positive_x=function(){return{x0:Number.MIN_VALUE,y0:-1/0,x1:1/0,y1:1/0}},e.positive_y=function(){return{x0:-1/0,y0:Number.MIN_VALUE,x1:1/0,y1:1/0}},e.union=function(t,i){return{x0:r(t.x0,i.x0),x1:s(t.x1,i.x1),y0:r(t.y0,i.y0),y1:s(t.y1,i.y1)}};class n{constructor(t){if(null==t)this.x0=0,this.y0=0,this.x1=0,this.y1=0;else if(\"x0\"in t){const{x0:i,y0:e,x1:h,y1:r}=t;if(!(i<=h&&e<=r))throw new Error(`invalid bbox {x0: ${i}, y0: ${e}, x1: ${h}, y1: ${r}}`);this.x0=i,this.y0=e,this.x1=h,this.y1=r}else if(\"x\"in t){const{x:i,y:e,width:h,height:r}=t;if(!(h>=0&&r>=0))throw new Error(`invalid bbox {x: ${i}, y: ${e}, width: ${h}, height: ${r}}`);this.x0=i,this.y0=e,this.x1=i+h,this.y1=e+r}else{let i,e,h,r;if(\"width\"in t)if(\"left\"in t)i=t.left,e=i+t.width;else if(\"right\"in t)e=t.right,i=e-t.width;else{const h=t.width/2;i=t.hcenter-h,e=t.hcenter+h}else i=t.left,e=t.right;if(\"height\"in t)if(\"top\"in t)h=t.top,r=h+t.height;else if(\"bottom\"in t)r=t.bottom,h=r-t.height;else{const i=t.height/2;h=t.vcenter-i,r=t.vcenter+i}else h=t.top,r=t.bottom;if(!(i<=e&&h<=r))throw new Error(`invalid bbox {left: ${i}, top: ${h}, right: ${e}, bottom: ${r}}`);this.x0=i,this.y0=h,this.x1=e,this.y1=r}}toString(){return`BBox({left: ${this.left}, top: ${this.top}, width: ${this.width}, height: ${this.height}})`}get left(){return this.x0}get top(){return this.y0}get right(){return this.x1}get bottom(){return this.y1}get p0(){return[this.x0,this.y0]}get p1(){return[this.x1,this.y1]}get x(){return this.x0}get y(){return this.y0}get width(){return this.x1-this.x0}get height(){return this.y1-this.y0}get rect(){return{x0:this.x0,y0:this.y0,x1:this.x1,y1:this.y1}}get box(){return{x:this.x,y:this.y,width:this.width,height:this.height}}get h_range(){return{start:this.x0,end:this.x1}}get v_range(){return{start:this.y0,end:this.y1}}get ranges(){return[this.h_range,this.v_range]}get aspect(){return this.width/this.height}get hcenter(){return(this.left+this.right)/2}get vcenter(){return(this.top+this.bottom)/2}relativize(){const{width:t,height:i}=this;return new n({x:0,y:0,width:t,height:i})}contains(t,i){return t>=this.x0&&t<=this.x1&&i>=this.y0&&i<=this.y1}clip(t,i){return tthis.x1&&(t=this.x1),ithis.y1&&(i=this.y1),[t,i]}union(t){return new n({x0:r(this.x0,t.x0),y0:r(this.y0,t.y0),x1:s(this.x1,t.x1),y1:s(this.y1,t.y1)})}equals(t){return this.x0==t.x0&&this.y0==t.y0&&this.x1==t.x1&&this.y1==t.y1}get xview(){return{compute:t=>this.left+t,v_compute:t=>{const i=new h.NumberArray(t.length),e=this.left;for(let h=0;hthis.bottom-t,v_compute:t=>{const i=new h.NumberArray(t.length),e=this.bottom;for(let h=0;he.getLineDash(),set:t=>e.setLineDash(t)})}(e),function(e){e.setImageSmoothingEnabled=t=>{e.imageSmoothingEnabled=t,e.mozImageSmoothingEnabled=t,e.oImageSmoothingEnabled=t,e.webkitImageSmoothingEnabled=t,e.msImageSmoothingEnabled=t},e.getImageSmoothingEnabled=()=>{const t=e.imageSmoothingEnabled;return null==t||t}}(e),function(e){e.measureText&&null==e.html5MeasureText&&(e.html5MeasureText=e.measureText,e.measureText=t=>{const n=e.html5MeasureText(t);return n.ascent=1.6*e.html5MeasureText(\"m\").width,n})}(e),function(e){e.ellipse||(e.ellipse=function(t,n,o,a,i,l,m,r=!1){const u=.551784;e.translate(t,n),e.rotate(i);let s=o,g=a;r&&(s=-o,g=-a),e.moveTo(-s,0),e.bezierCurveTo(-s,g*u,-s*u,g,0,g),e.bezierCurveTo(s*u,g,s,g*u,s,0),e.bezierCurveTo(s,-g*u,s*u,-g,0,-g),e.bezierCurveTo(-s*u,-g,-s,-g*u,-s,0),e.rotate(-i),e.translate(-t,-n)})}(e)}},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const n=e(1),c=e(14),i=n.__importStar(e(18)),a=e(8),r=e(13),o=e(19);class l extends c.HasProps{constructor(e){super(e)}static init_Model(){this.define({tags:[i.Array,[]],name:[i.String],js_property_callbacks:[i.Any,{}],js_event_callbacks:[i.Any,{}],subscribed_events:[i.Array,[]]})}initialize(){super.initialize(),this._js_callbacks=new Map}connect_signals(){super.connect_signals(),this._update_property_callbacks(),this.connect(this.properties.js_property_callbacks.change,()=>this._update_property_callbacks()),this.connect(this.properties.js_event_callbacks.change,()=>this._update_event_callbacks()),this.connect(this.properties.subscribed_events.change,()=>this._update_event_callbacks())}_process_event(e){for(const t of this.js_event_callbacks[e.event_name]||[])t.execute(e);null!=this.document&&this.subscribed_events.some(t=>t==e.event_name)&&this.document.event_manager.send_event(e)}trigger_event(e){null!=this.document&&(e.origin=this,this.document.event_manager.trigger(e))}_update_event_callbacks(){null!=this.document?this.document.event_manager.subscribed_models.add(this):o.logger.warn(\"WARNING: Document not defined for updating event callbacks\")}_update_property_callbacks(){const e=e=>{const[t,s=null]=e.split(\":\");return null!=s?this.properties[s][t]:this[t]};for(const[t,s]of this._js_callbacks){const n=e(t);for(const e of s)this.disconnect(n,e)}this._js_callbacks.clear();for(const[t,s]of r.entries(this.js_property_callbacks)){const n=s.map(e=>()=>e.execute(this));this._js_callbacks.set(t,n);const c=e(t);for(const e of n)this.connect(c,e)}}_doc_attached(){r.isEmpty(this.js_event_callbacks)&&0==this.subscribed_events.length||this._update_event_callbacks()}_doc_detached(){this.document.event_manager.subscribed_models.delete(this)}select(e){if(a.isString(e))return[...this.references()].filter(t=>t instanceof l&&t.name===e);if(e.prototype instanceof c.HasProps)return[...this.references()].filter(t=>t instanceof e);throw new Error(\"invalid selector\")}select_one(e){const t=this.select(e);switch(t.length){case 0:return null;case 1:return t[0];default:throw new Error(\"found more than one object matching given selector\")}}}s.Model=l,l.__name__=\"Model\",l.init_Model()},\n", - " function _(e,s,_){Object.defineProperty(_,\"__esModule\",{value:!0});class t{constructor(e,s){this.x_scale=e,this.y_scale=s,this.x_range=this.x_scale.source_range,this.y_range=this.y_scale.source_range,this.ranges=[this.x_range,this.y_range],this.scales=[this.x_scale,this.y_scale]}map_to_screen(e,s){return[this.x_scale.v_compute(e),this.y_scale.v_compute(s)]}map_from_screen(e,s){return[this.x_scale.v_invert(e),this.y_scale.v_invert(s)]}}_.CoordinateTransform=t,t.__name__=\"CoordinateTransform\"},\n", - " function _(t,e,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=t(1),a=t(36),o=t(84),r=t(85),n=t(28),_=i.__importStar(t(18)),h=t(10);class c extends a.AnnotationView{initialize(){super.initialize(),null==this.model.source&&(this.model.source=new r.ColumnDataSource),this.set_data(this.model.source)}connect_signals(){super.connect_signals(),this.connect(this.model.change,()=>this.set_data(this.model.source)),this.connect(this.model.source.streaming,()=>this.set_data(this.model.source)),this.connect(this.model.source.patching,()=>this.set_data(this.model.source)),this.connect(this.model.source.change,()=>this.set_data(this.model.source))}set_data(t){super.set_data(t),this.visuals.warm_cache(t),this.plot_view.request_render()}_map_data(){const{frame:t}=this.plot_view;let e,s,i,a;return\"data\"==this.model.start_units?(e=this.coordinates.x_scale.v_compute(this._x_start),s=this.coordinates.y_scale.v_compute(this._y_start)):(e=t.xview.v_compute(this._x_start),s=t.yview.v_compute(this._y_start)),\"data\"==this.model.end_units?(i=this.coordinates.x_scale.v_compute(this._x_end),a=this.coordinates.y_scale.v_compute(this._y_end)):(i=t.xview.v_compute(this._x_end),a=t.yview.v_compute(this._y_end)),[[e,s],[i,a]]}_render(){const{ctx:t}=this.layer;t.save();const[e,s]=this._map_data();null!=this.model.end&&this._arrow_head(t,\"render\",this.model.end,e,s),null!=this.model.start&&this._arrow_head(t,\"render\",this.model.start,s,e),t.beginPath();const{x:i,y:a,width:o,height:r}=this.plot_view.frame.bbox;t.rect(i,a,o,r),null!=this.model.end&&this._arrow_head(t,\"clip\",this.model.end,e,s),null!=this.model.start&&this._arrow_head(t,\"clip\",this.model.start,s,e),t.closePath(),t.clip(),this._arrow_body(t,e,s),t.restore()}_arrow_head(t,e,s,i,a){for(let o=0,r=this._x_start.length;onew o.OpenHead({})],source:[_.Instance]})}}s.Arrow=d,d.__name__=\"Arrow\",d.init_Arrow()},\n", - " function _(i,e,s){Object.defineProperty(s,\"__esModule\",{value:!0});const t=i(1),o=i(36),l=i(74),n=i(28),h=t.__importStar(i(18));class a extends o.Annotation{constructor(i){super(i)}static init_ArrowHead(){this.define({size:[h.Number,25]})}initialize(){super.initialize(),this.visuals=new l.Visuals(this)}}s.ArrowHead=a,a.__name__=\"ArrowHead\",a.init_ArrowHead();class r extends a{constructor(i){super(i)}static init_OpenHead(){this.mixins(n.LineVector)}clip(i,e){this.visuals.line.set_vectorize(i,e),i.moveTo(.5*this.size,this.size),i.lineTo(.5*this.size,-2),i.lineTo(-.5*this.size,-2),i.lineTo(-.5*this.size,this.size),i.lineTo(0,0),i.lineTo(.5*this.size,this.size)}render(i,e){this.visuals.line.doit&&(this.visuals.line.set_vectorize(i,e),i.beginPath(),i.moveTo(.5*this.size,this.size),i.lineTo(0,0),i.lineTo(-.5*this.size,this.size),i.stroke())}}s.OpenHead=r,r.__name__=\"OpenHead\",r.init_OpenHead();class z extends a{constructor(i){super(i)}static init_NormalHead(){this.mixins([n.LineVector,n.FillVector]),this.override({fill_color:\"black\"})}clip(i,e){this.visuals.line.set_vectorize(i,e),i.moveTo(.5*this.size,this.size),i.lineTo(.5*this.size,-2),i.lineTo(-.5*this.size,-2),i.lineTo(-.5*this.size,this.size),i.lineTo(.5*this.size,this.size)}render(i,e){this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(i,e),this._normal(i,e),i.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(i,e),this._normal(i,e),i.stroke())}_normal(i,e){i.beginPath(),i.moveTo(.5*this.size,this.size),i.lineTo(0,0),i.lineTo(-.5*this.size,this.size),i.closePath()}}s.NormalHead=z,z.__name__=\"NormalHead\",z.init_NormalHead();class _ extends a{constructor(i){super(i)}static init_VeeHead(){this.mixins([n.LineVector,n.FillVector]),this.override({fill_color:\"black\"})}clip(i,e){this.visuals.line.set_vectorize(i,e),i.moveTo(.5*this.size,this.size),i.lineTo(.5*this.size,-2),i.lineTo(-.5*this.size,-2),i.lineTo(-.5*this.size,this.size),i.lineTo(0,.5*this.size),i.lineTo(.5*this.size,this.size)}render(i,e){this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(i,e),this._vee(i,e),i.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(i,e),this._vee(i,e),i.stroke())}_vee(i,e){i.beginPath(),i.moveTo(.5*this.size,this.size),i.lineTo(0,0),i.lineTo(-.5*this.size,this.size),i.lineTo(0,.5*this.size),i.closePath()}}s.VeeHead=_,_.__name__=\"VeeHead\",_.init_VeeHead();class c extends a{constructor(i){super(i)}static init_TeeHead(){this.mixins(n.LineVector)}render(i,e){this.visuals.line.doit&&(this.visuals.line.set_vectorize(i,e),i.beginPath(),i.moveTo(.5*this.size,0),i.lineTo(-.5*this.size,0),i.stroke())}clip(i,e){}}s.TeeHead=c,c.__name__=\"TeeHead\",c.init_TeeHead()},\n", - " function _(t,n,e){Object.defineProperty(e,\"__esModule\",{value:!0});const s=t(1),o=t(86),r=s.__importStar(t(18)),i=t(8),l=t(13),a=s.__importStar(t(119)),c=t(120),u=t(121);function h(t,n,e){if(i.isArray(t)){const s=t.concat(n);return null!=e&&s.length>e?s.slice(-e):s}if(i.isTypedArray(t)){const s=t.length+n.length;if(null!=e&&s>e){const o=s-e,r=t.length;let i;t.lengthnew _.UnionRenderers]}),this.internal({selection_manager:[c.Instance,t=>new l.SelectionManager({source:t})],inspected:[c.Instance,()=>new g.Selection]})}initialize(){super.initialize(),this._select=new i.Signal0(this,\"select\"),this.inspect=new i.Signal(this,\"inspect\"),this.streaming=new i.Signal0(this,\"streaming\"),this.patching=new i.Signal(this,\"patching\")}get_column(t){const e=this.data[t];return null!=e?e:null}columns(){return h.keys(this.data)}get_length(t=!0){const e=u.uniq(h.values(this.data).map(t=>t.length));switch(e.length){case 0:return null;case 1:return e[0];default:{const n=\"data source has columns of inconsistent lengths\";if(t)return r.logger.warn(n),e.sort()[0];throw new Error(n)}}}get length(){var t;return null!==(t=this.get_length())&&void 0!==t?t:0}clear(){const t={};for(const e of this.columns())t[e]=new this.data[e].constructor(0);this.data=t}}n.ColumnarDataSource=d,d.__name__=\"ColumnarDataSource\",d.init_ColumnarDataSource()},\n", - " function _(e,t,a){Object.defineProperty(a,\"__esModule\",{value:!0});const c=e(1),n=e(81),o=e(88),i=c.__importStar(e(18));class r extends n.Model{constructor(e){super(e)}static init_DataSource(){this.define({selected:[i.Instance,()=>new o.Selection]})}}a.DataSource=r,r.__name__=\"DataSource\",r.init_DataSource()},\n", - " function _(i,e,s){Object.defineProperty(s,\"__esModule\",{value:!0});const t=i(1),n=i(81),l=t.__importStar(i(18)),c=i(9),h=i(13);class d extends n.Model{constructor(i){super(i)}get_view(){return this.view}static init_Selection(){this.define({indices:[l.Array,[]],line_indices:[l.Array,[]],multiline_indices:[l.Any,{}]}),this.internal({selected_glyphs:[l.Array,[]],view:[l.Any],image_indices:[l.Array,[]]})}initialize(){super.initialize()}get selected_glyph(){return this.selected_glyphs.length>0?this.selected_glyphs[0]:null}add_to_selected_glyphs(i){this.selected_glyphs.push(i)}update(i,e=!0,s=\"replace\"){switch(s){case\"replace\":this.indices=i.indices,this.line_indices=i.line_indices,this.selected_glyphs=i.selected_glyphs,this.view=i.view,this.multiline_indices=i.multiline_indices,this.image_indices=i.image_indices;break;case\"append\":this.update_through_union(i);break;case\"intersect\":this.update_through_intersection(i);break;case\"subtract\":this.update_through_subtraction(i)}}clear(){this.indices=[],this.line_indices=[],this.multiline_indices={},this.view=null,this.selected_glyphs=[]}is_empty(){return 0==this.indices.length&&0==this.line_indices.length&&0==this.image_indices.length}update_through_union(i){this.indices=c.union(this.indices,i.indices),this.selected_glyphs=c.union(i.selected_glyphs,this.selected_glyphs),this.line_indices=c.union(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=h.merge(i.multiline_indices,this.multiline_indices)}update_through_intersection(i){this.indices=c.intersection(this.indices,i.indices),this.selected_glyphs=c.union(i.selected_glyphs,this.selected_glyphs),this.line_indices=c.union(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=h.merge(i.multiline_indices,this.multiline_indices)}update_through_subtraction(i){this.indices=c.difference(this.indices,i.indices),this.selected_glyphs=c.union(i.selected_glyphs,this.selected_glyphs),this.line_indices=c.union(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=h.merge(i.multiline_indices,this.multiline_indices)}}s.Selection=d,d.__name__=\"Selection\",d.init_Selection()},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=e(1),n=e(14),o=e(88),c=e(90),r=e(116),l=i.__importStar(e(18));class p extends n.HasProps{constructor(e){super(e),this.inspectors=new Map}static init_SelectionManager(){this.internal({source:[l.Any]})}select(e,t,s,i=\"replace\"){const n=[],o=[];for(const t of e)t instanceof c.GlyphRendererView?n.push(t):t instanceof r.GraphRendererView&&o.push(t);let l=!1;for(const e of o){const n=e.model.selection_policy.hit_test(t,e);l=l||e.model.selection_policy.do_selection(n,e.model,s,i)}if(n.length>0){const e=this.source.selection_policy.hit_test(t,n);l=l||this.source.selection_policy.do_selection(e,this.source,s,i)}return l}inspect(e,t){let s=!1;if(e instanceof c.GlyphRendererView){const i=e.hit_test(t);if(null!=i){s=!i.is_empty();const n=this.get_or_create_inspector(e.model);n.update(i,!0,\"replace\"),this.source.setv({inspected:n},{silent:!0}),this.source.inspect.emit([e,{geometry:t}])}}else if(e instanceof r.GraphRendererView){const i=e.model.inspection_policy.hit_test(t,e);s=s||e.model.inspection_policy.do_inspection(i,t,e,!1,\"replace\")}return s}clear(e){this.source.selected.clear(),null!=e&&this.get_or_create_inspector(e.model).clear()}get_or_create_inspector(e){let t=this.inspectors.get(e);return null==t&&(t=new o.Selection,this.inspectors.set(e,t)),t}}s.SelectionManager=p,p.__name__=\"SelectionManager\",p.init_SelectionManager()},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=e(1),l=e(91),n=e(92),h=e(110),o=e(111),a=e(113),c=e(114),_=e(24),d=s.__importStar(e(18)),r=e(12),p=e(9),g=e(13),u=e(115),y=e(98),m={fill:{},line:{}},v={fill:{fill_alpha:.3,fill_color:\"grey\"},line:{line_alpha:.3,line_color:\"grey\"}},f={fill:{fill_alpha:.2},line:{}};class w extends l.DataRendererView{async lazy_initialize(){await super.lazy_initialize();const e=this.model.glyph,t=p.includes(e._mixins,\"fill\"),i=p.includes(e._mixins,\"line\"),s=g.clone(e.attributes);function l(l){const n=g.clone(s);return t&&g.extend(n,l.fill),i&&g.extend(n,l.line),new e.constructor(n)}delete s.id,this.glyph=await this.build_glyph_view(e);let{selection_glyph:n}=this.model;null==n?n=l({fill:{},line:{}}):\"auto\"===n&&(n=l(m)),this.selection_glyph=await this.build_glyph_view(n);let{nonselection_glyph:h}=this.model;null==h?h=l({fill:{},line:{}}):\"auto\"===h&&(h=l(f)),this.nonselection_glyph=await this.build_glyph_view(h);const{hover_glyph:o}=this.model;null!=o&&(this.hover_glyph=await this.build_glyph_view(o));const{muted_glyph:a}=this.model;null!=a&&(this.muted_glyph=await this.build_glyph_view(a));const c=l(v);this.decimated_glyph=await this.build_glyph_view(c),this.set_data(!1)}async build_glyph_view(e){return u.build_view(e,{parent:this})}remove(){var e,t;this.glyph.remove(),this.selection_glyph.remove(),this.nonselection_glyph.remove(),null===(e=this.hover_glyph)||void 0===e||e.remove(),null===(t=this.muted_glyph)||void 0===t||t.remove(),this.decimated_glyph.remove(),super.remove()}connect_signals(){super.connect_signals(),this.connect(this.model.change,()=>this.request_render()),this.connect(this.model.glyph.change,()=>this.set_data()),this.connect(this.model.data_source.change,()=>this.set_data()),this.connect(this.model.data_source.streaming,()=>this.set_data()),this.connect(this.model.data_source.patching,e=>this.set_data(!0,e)),this.connect(this.model.data_source.selected.change,()=>this.request_render()),this.connect(this.model.data_source._select,()=>this.request_render()),null!=this.hover_glyph&&this.connect(this.model.data_source.inspect,()=>this.request_render()),this.connect(this.model.properties.view.change,()=>this.set_data()),this.connect(this.model.view.properties.indices.change,()=>this.set_data()),this.connect(this.model.view.properties.masked.change,()=>this.set_visuals()),this.connect(this.model.properties.visible.change,()=>this.plot_view.update_dataranges());const{x_ranges:e,y_ranges:t}=this.plot_view.frame;for(const[,t]of e)t instanceof y.FactorRange&&this.connect(t.change,()=>this.set_data());for(const[,e]of t)e instanceof y.FactorRange&&this.connect(e.change,()=>this.set_data());this.connect(this.model.glyph.transformchange,()=>this.set_data())}_update_masked_indices(){const e=this.glyph.mask_data();return this.model.view.masked=e,e}set_data(e=!0,t=null){const i=this.model.data_source;this.all_indices=this.model.view.indices;const{all_indices:s}=this;this.glyph.set_data(i,s,t),this.set_visuals(),this._update_masked_indices();const{lod_factor:l}=this.plot_model,n=this.all_indices.count;this.decimated=new _.Indices(n);for(let e=0;e!_||_.is_empty()?[]:_.selected_glyph?this.model.view.convert_indices_from_subset(i):_.indices.length>0?_.indices:Object.keys(_.multiline_indices).map(e=>parseInt(e)))()),g=r.filter(i,e=>d.has(t[e])),{lod_threshold:u}=this.plot_model;let y,m,v;if(null!=this.model.document&&this.model.document.interactive_duration()>0&&!e&&null!=u&&t.length>u?(i=[...this.decimated],y=this.decimated_glyph,m=this.decimated_glyph,v=this.selection_glyph):(y=this.model.muted&&null!=this.muted_glyph?this.muted_glyph:this.glyph,m=this.nonselection_glyph,v=this.selection_glyph),null!=this.hover_glyph&&g.length&&(i=p.difference(i,g)),c.length){const e={};for(const t of c)e[t]=!0;const l=new Array,h=new Array;if(this.glyph instanceof n.LineView)for(const i of t)null!=e[i]?l.push(i):h.push(i);else for(const s of i)null!=e[t[s]]?l.push(s):h.push(s);m.render(s,h,this.glyph),v.render(s,l,this.glyph),null!=this.hover_glyph&&(this.glyph instanceof n.LineView?this.hover_glyph.render(s,this.model.view.convert_indices_from_subset(g),this.glyph):this.hover_glyph.render(s,g,this.glyph))}else if(this.glyph instanceof n.LineView)this.hover_glyph&&g.length?this.hover_glyph.render(s,this.model.view.convert_indices_from_subset(g),this.glyph):y.render(s,t,this.glyph);else if(this.glyph instanceof h.PatchView||this.glyph instanceof o.HAreaView||this.glyph instanceof a.VAreaView)if(0==_.selected_glyphs.length||null==this.hover_glyph)y.render(s,t,this.glyph);else for(const e of _.selected_glyphs)e==this.glyph.model&&this.hover_glyph.render(s,t,this.glyph);else y.render(s,i,this.glyph),this.hover_glyph&&g.length&&this.hover_glyph.render(s,g,this.glyph);s.restore()}draw_legend(e,t,i,s,l,n,h,o){null==o&&(o=this.model.get_reference_point(n,h)),this.glyph.draw_legend_for_index(e,{x0:t,x1:i,y0:s,y1:l},o)}hit_test(e){if(!this.model.visible)return null;const t=this.glyph.hit_test(e);return null==t?null:this.model.view.convert_selection_from_subset(t)}}i.GlyphRendererView=w,w.__name__=\"GlyphRendererView\";class b extends l.DataRenderer{constructor(e){super(e)}static init_GlyphRenderer(){this.prototype.default_view=w,this.define({data_source:[d.Instance],view:[d.Instance,()=>new c.CDSView],glyph:[d.Instance],hover_glyph:[d.Instance],nonselection_glyph:[d.Any,\"auto\"],selection_glyph:[d.Any,\"auto\"],muted_glyph:[d.Instance],muted:[d.Boolean,!1]})}initialize(){super.initialize(),null==this.view.source&&(this.view.source=this.data_source,this.view.compute_indices())}get_reference_point(e,t){let i=0;if(null!=e){const s=this.data_source.get_column(e);if(null!=s){const e=r.indexOf(s,t);-1!=e&&(i=e)}}return i}get_selection_manager(){return this.data_source.selection_manager}}i.GlyphRenderer=b,b.__name__=\"GlyphRenderer\",b.init_GlyphRenderer()},\n", - " function _(e,r,t){Object.defineProperty(t,\"__esModule\",{value:!0});const a=e(70);class n extends a.RendererView{get xscale(){return this.coordinates.x_scale}get yscale(){return this.coordinates.y_scale}}t.DataRendererView=n,n.__name__=\"DataRendererView\";class s extends a.Renderer{constructor(e){super(e)}static init_DataRenderer(){this.override({level:\"glyph\"})}}t.DataRenderer=s,s.__name__=\"DataRenderer\",s.init_DataRenderer()},\n", - " function _(e,i,t){Object.defineProperty(t,\"__esModule\",{value:!0});const s=e(1),n=e(93),l=e(100),_=e(102),r=s.__importStar(e(28)),o=s.__importStar(e(101)),h=e(88);class a extends n.XYGlyphView{initialize(){super.initialize();const{webgl:e}=this.renderer.plot_view.canvas_view;null!=e&&(this.glglyph=new _.LineGL(e.gl,this))}_render(e,i,{sx:t,sy:s}){let n=!1,l=null;this.visuals.line.set_value(e);for(const _ of i){if(n){if(!isFinite(t[_]+s[_])){e.stroke(),e.beginPath(),n=!1,l=_;continue}null!=l&&_-l>1&&(e.stroke(),n=!1)}n?e.lineTo(t[_],s[_]):(e.beginPath(),e.moveTo(t[_],s[_]),n=!0),l=_}n&&e.stroke()}_hit_point(e){const i=new h.Selection,t={x:e.sx,y:e.sy};let s=9999;const n=Math.max(2,this.visuals.line.line_width.value()/2);for(let e=0,l=this.sx.length-1;et/2);a=new Float64Array(_);for(let i=0;i<_;i++)a[i]=e[i]-t[i];r=new Float64Array(_);for(let i=0;i<_;i++)r[i]=e[i]+t[i]}else{a=e,r=new Float64Array(_);for(let t=0;t<_;t++)r[t]=a[t]+i[t]}const l=t.v_compute(a),o=t.v_compute(r);return n?d.map(l,(t,e)=>Math.ceil(Math.abs(o[e]-l[e]))):d.map(l,(t,e)=>Math.abs(o[e]-l[e]))}draw_legend_for_index(t,e,i){}hit_test(t){switch(t.type){case\"point\":if(null!=this._hit_point)return this._hit_point(t);break;case\"span\":if(null!=this._hit_span)return this._hit_span(t);break;case\"rect\":if(null!=this._hit_rect)return this._hit_rect(t);break;case\"poly\":if(null!=this._hit_poly)return this._hit_poly(t)}return this._nohit_warned.has(t.type)||(o.logger.debug(`'${t.type}' selection not available for ${this.model.type}`),this._nohit_warned.add(t.type)),null}_hit_rect_against_index(t){const{sx0:e,sx1:i,sy0:s,sy1:n}=t,[a,r]=this.renderer.coordinates.x_scale.r_invert(e,i),[_,l]=this.renderer.coordinates.y_scale.r_invert(s,n),o=[...this.index.indices({x0:a,x1:r,y0:_,y1:l})];return new p.Selection({indices:o})}_project_data(){}set_data(t,e,i){var s,a;const{x_range:r,y_range:_}=this.renderer.coordinates;this._data_size=null!==(s=t.get_length())&&void 0!==s?s:1;for(const i of this.model){if(!(i instanceof n.VectorSpec))continue;if(i.optional&&null==i.spec.value&&!i.dirty)continue;const s=i.attr,a=i.array(t);let l=e.select(a);if(i instanceof n.BaseCoordinateSpec){const t=\"x\"==i.dimension?r:_;if(t instanceof u.FactorRange)if(i instanceof n.CoordinateSpec)l=t.v_synthetic(l);else if(i instanceof n.CoordinateSeqSpec)for(let e=0;e>1;n[s]>e?i=s:t=s+1}return n[t]}class x extends i.default{search_indices(e,n,t,i){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let o=this._boxes.length-4;const x=[],h=new s.Indices(this.numItems);for(;void 0!==o;){const s=Math.min(o+4*this.nodeSize,d(o,this._levelBounds));for(let d=o;d>2];tthis._boxes[d+2]||n>this._boxes[d+3]||(o<4*this.numItems?h.set(s):x.push(s)))}o=x.pop()}return h}}x.__name__=\"_FlatBush\";class h{constructor(e){this.index=null,e>0&&(this.index=new x(e))}add(e,n,t,i){var s;null===(s=this.index)||void 0===s||s.add(e,n,t,i)}add_empty(){var e;null===(e=this.index)||void 0===e||e.add(1/0,1/0,-1/0,-1/0)}finish(){var e;null===(e=this.index)||void 0===e||e.finish()}_normalize(e){let{x0:n,y0:t,x1:i,y1:s}=e;return n>i&&([n,i]=[i,n]),t>s&&([t,s]=[s,t]),{x0:n,y0:t,x1:i,y1:s}}get bbox(){if(null==this.index)return o.empty();{const{minX:e,minY:n,maxX:t,maxY:i}=this.index;return{x0:e,y0:n,x1:t,y1:i}}}indices(e){if(null==this.index)return new s.Indices(0);{const{x0:n,y0:t,x1:i,y1:s}=this._normalize(e);return this.index.search_indices(n,t,i,s)}}bounds(e){const n=o.empty();for(const t of this.indices(e)){const e=this.index._boxes,i=e[4*t+0],s=e[4*t+1],o=e[4*t+2],d=e[4*t+3];on.x1&&(n.x1=i),dn.y1&&(n.y1=s)}return n}}t.SpatialIndex=h,h.__name__=\"SpatialIndex\"},\n", - " function _(t,s,i){Object.defineProperty(i,\"__esModule\",{value:!0});const e=t(1).__importDefault(t(97)),h=[Int8Array,Uint8Array,Uint8ClampedArray,Int16Array,Uint16Array,Int32Array,Uint32Array,Float32Array,Float64Array];class n{static from(t){if(!(t instanceof ArrayBuffer))throw new Error(\"Data must be an instance of ArrayBuffer.\");const[s,i]=new Uint8Array(t,0,2);if(251!==s)throw new Error(\"Data does not appear to be in a Flatbush format.\");if(i>>4!=3)throw new Error(`Got v${i>>4} data when expected v3.`);const[e]=new Uint16Array(t,2,1),[o]=new Uint32Array(t,4,1);return new n(o,e,h[15&i],t)}constructor(t,s=16,i=Float64Array,n){if(void 0===t)throw new Error(\"Missing required argument: numItems.\");if(isNaN(t)||t<=0)throw new Error(`Unpexpected numItems value: ${t}.`);this.numItems=+t,this.nodeSize=Math.min(Math.max(+s,2),65535);let o=t,r=o;this._levelBounds=[4*o];do{o=Math.ceil(o/this.nodeSize),r+=o,this._levelBounds.push(4*r)}while(1!==o);this.ArrayType=i||Float64Array,this.IndexArrayType=r<16384?Uint16Array:Uint32Array;const a=h.indexOf(this.ArrayType),_=4*r*this.ArrayType.BYTES_PER_ELEMENT;if(a<0)throw new Error(`Unexpected typed array class: ${i}.`);n&&n instanceof ArrayBuffer?(this.data=n,this._boxes=new this.ArrayType(this.data,8,4*r),this._indices=new this.IndexArrayType(this.data,8+_,r),this._pos=4*r,this.minX=this._boxes[this._pos-4],this.minY=this._boxes[this._pos-3],this.maxX=this._boxes[this._pos-2],this.maxY=this._boxes[this._pos-1]):(this.data=new ArrayBuffer(8+_+r*this.IndexArrayType.BYTES_PER_ELEMENT),this._boxes=new this.ArrayType(this.data,8,4*r),this._indices=new this.IndexArrayType(this.data,8+_,r),this._pos=0,this.minX=1/0,this.minY=1/0,this.maxX=-1/0,this.maxY=-1/0,new Uint8Array(this.data,0,2).set([251,48+a]),new Uint16Array(this.data,2,1)[0]=s,new Uint32Array(this.data,4,1)[0]=t),this._queue=new e.default}add(t,s,i,e){const h=this._pos>>2;return this._indices[h]=h,this._boxes[this._pos++]=t,this._boxes[this._pos++]=s,this._boxes[this._pos++]=i,this._boxes[this._pos++]=e,tthis.maxX&&(this.maxX=i),e>this.maxY&&(this.maxY=e),h}finish(){if(this._pos>>2!==this.numItems)throw new Error(`Added ${this._pos>>2} items when expected ${this.numItems}.`);if(this.numItems<=this.nodeSize)return this._boxes[this._pos++]=this.minX,this._boxes[this._pos++]=this.minY,this._boxes[this._pos++]=this.maxX,void(this._boxes[this._pos++]=this.maxY);const t=this.maxX-this.minX,s=this.maxY-this.minY,i=new Uint32Array(this.numItems);for(let e=0;e=Math.floor(n/o))return;const r=s[h+n>>1];let _=h-1,d=n+1;for(;;){do{_++}while(s[_]r);if(_>=d)break;a(s,i,e,_,d)}t(s,i,e,h,d,o),t(s,i,e,d+1,n,o)}(i,this._boxes,this._indices,0,this.numItems-1,this.nodeSize);for(let t=0,s=0;t>2]=t,this._boxes[this._pos++]=e,this._boxes[this._pos++]=h,this._boxes[this._pos++]=n,this._boxes[this._pos++]=o}}}search(t,s,i,e,h){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let n=this._boxes.length-4;const o=[],a=[];for(;void 0!==n;){const _=Math.min(n+4*this.nodeSize,r(n,this._levelBounds));for(let r=n;r<_;r+=4){const _=0|this._indices[r>>2];ithis._boxes[r+2]||s>this._boxes[r+3]||(n<4*this.numItems?(void 0===h||h(_))&&a.push(_):o.push(_)))}n=o.pop()}return a}neighbors(t,s,i=1/0,e=1/0,h){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let n=this._boxes.length-4;const a=this._queue,_=[],d=e*e;for(;void 0!==n;){const e=Math.min(n+4*this.nodeSize,r(n,this._levelBounds));for(let i=n;i>2],r=o(t,this._boxes[i],this._boxes[i+2]),_=o(s,this._boxes[i+1],this._boxes[i+3]),d=r*r+_*_;n<4*this.numItems?(void 0===h||h(e))&&a.push(-e-1,d):a.push(e,d)}for(;a.length&&a.peek()<0;){if(a.peekValue()>d)return a.clear(),_;if(_.push(-a.pop()-1),_.length===i)return a.clear(),_}n=a.pop()}return a.clear(),_}}function o(t,s,i){return t>1;s[h]>t?e=h:i=h+1}return s[i]}function a(t,s,i,e,h){const n=t[e];t[e]=t[h],t[h]=n;const o=4*e,r=4*h,a=s[o],_=s[o+1],d=s[o+2],x=s[o+3];s[o]=s[r],s[o+1]=s[r+1],s[o+2]=s[r+2],s[o+3]=s[r+3],s[r]=a,s[r+1]=_,s[r+2]=d,s[r+3]=x;const l=i[e];i[e]=i[h],i[h]=l}function _(t,s){let i=t^s,e=65535^i,h=65535^(t|s),n=t&(65535^s),o=i|e>>1,r=i>>1^i,a=h>>1^e&n>>1^h,_=i&h>>1^n>>1^n;i=o,e=r,h=a,n=_,o=i&i>>2^e&e>>2,r=i&e>>2^e&(i^e)>>2,a^=i&h>>2^e&n>>2,_^=e&h>>2^(i^e)&n>>2,i=o,e=r,h=a,n=_,o=i&i>>4^e&e>>4,r=i&e>>4^e&(i^e)>>4,a^=i&h>>4^e&n>>4,_^=e&h>>4^(i^e)&n>>4,i=o,e=r,h=a,n=_,a^=i&h>>8^e&n>>8,_^=e&h>>8^(i^e)&n>>8,i=a^a>>1,e=_^_>>1;let d=t^s,x=e|65535^(d|i);return d=16711935&(d|d<<8),d=252645135&(d|d<<4),d=858993459&(d|d<<2),d=1431655765&(d|d<<1),x=16711935&(x|x<<8),x=252645135&(x|x<<4),x=858993459&(x|x<<2),x=1431655765&(x|x<<1),(x<<1|d)>>>0}i.default=n},\n", - " function _(s,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});i.default=class{constructor(){this.ids=[],this.values=[],this.length=0}clear(){this.length=0}push(s,t){let i=this.length++;for(this.ids[i]=s,this.values[i]=t;i>0;){const s=i-1>>1,h=this.values[s];if(t>=h)break;this.ids[i]=this.ids[s],this.values[i]=h,i=s}this.ids[i]=s,this.values[i]=t}pop(){if(0===this.length)return;const s=this.ids[0];if(this.length--,this.length>0){const s=this.ids[0]=this.ids[this.length],t=this.values[0]=this.values[this.length],i=this.length>>1;let h=0;for(;h=t)break;this.ids[h]=e,this.values[h]=l,h=s}this.ids[h]=s,this.values[h]=t}return s}peek(){if(0!==this.length)return this.ids[0]}peekValue(){if(0!==this.length)return this.values[0]}}},\n", - " function _(t,e,n){Object.defineProperty(n,\"__esModule\",{value:!0});const s=t(1),i=t(99),r=s.__importStar(t(18)),a=t(24),o=t(9),p=t(8),g=t(11);function c(t,e,n=0){const s=new Map;for(let i=0;ia.get(t).value));r.set(t,{value:u/i,mapping:a}),p+=i+e+l}return[r,(a.size-1)*e+g]}function u(t,e,n,s,i=0){var r;const a=new Map,p=new Map;for(const[e,n,s]of t){const t=null!==(r=p.get(e))&&void 0!==r?r:[];p.set(e,[...t,[n,s]])}let g=i,c=0;for(const[t,i]of p){const r=i.length,[p,u]=l(i,n,s,g);c+=u;const h=o.sum(i.map(([t])=>p.get(t).value));a.set(t,{value:h/r,mapping:p}),g+=r+e+u}return[a,(p.size-1)*e+c]}n.map_one_level=c,n.map_two_levels=l,n.map_three_levels=u;class h extends i.Range{constructor(t){super(t)}static init_FactorRange(){this.define({factors:[r.Array,[]],factor_padding:[r.Number,0],subgroup_padding:[r.Number,.8],group_padding:[r.Number,1.4],range_padding:[r.Number,0],range_padding_units:[r.PaddingUnits,\"percent\"],start:[r.Number],end:[r.Number]}),this.internal({levels:[r.Number],mids:[r.Array,null],tops:[r.Array,null]})}get min(){return this.start}get max(){return this.end}initialize(){super.initialize(),this._init(!0)}connect_signals(){super.connect_signals(),this.connect(this.properties.factors.change,()=>this.reset()),this.connect(this.properties.factor_padding.change,()=>this.reset()),this.connect(this.properties.group_padding.change,()=>this.reset()),this.connect(this.properties.subgroup_padding.change,()=>this.reset()),this.connect(this.properties.range_padding.change,()=>this.reset()),this.connect(this.properties.range_padding_units.change,()=>this.reset())}reset(){this._init(!1),this.change.emit()}_lookup(t){switch(t.length){case 1:{const[e]=t,n=this._mapping.get(e);return null!=n?n.value:NaN}case 2:{const[e,n]=t,s=this._mapping.get(e);if(null!=s){const t=s.mapping.get(n);if(null!=t)return t.value}return NaN}case 3:{const[e,n,s]=t,i=this._mapping.get(e);if(null!=i){const t=i.mapping.get(n);if(null!=t){const e=t.mapping.get(s);if(null!=e)return e.value}}return NaN}default:g.unreachable()}}synthetic(t){if(p.isNumber(t))return t;if(p.isString(t))return this._lookup([t]);let e=0;const n=t[t.length-1];return p.isNumber(n)&&(e=n,t=t.slice(0,-1)),this._lookup(t)+e}v_synthetic(t){const e=t.length,n=new a.NumberArray(e);for(let s=0;s{if(o.every(this.factors,p.isString)){const t=this.factors,[e,n]=c(t,this.factor_padding);return{levels:1,mapping:e,tops:null,mids:null,inside_padding:n}}if(o.every(this.factors,t=>p.isArray(t)&&2==t.length&&p.isString(t[0])&&p.isString(t[1]))){const t=this.factors,[e,n]=l(t,this.group_padding,this.factor_padding),s=[...e.keys()];return{levels:2,mapping:e,tops:s,mids:null,inside_padding:n}}if(o.every(this.factors,t=>p.isArray(t)&&3==t.length&&p.isString(t[0])&&p.isString(t[1])&&p.isString(t[2]))){const t=this.factors,[e,n]=u(t,this.group_padding,this.subgroup_padding,this.factor_padding),s=[...e.keys()],i=[];for(const[t,n]of e)for(const e of n.mapping.keys())i.push([t,e]);return{levels:3,mapping:e,tops:s,mids:i,inside_padding:n}}g.unreachable()})();this._mapping=n,this.tops=s,this.mids=i;let a=0,h=this.factors.length+r;if(\"percent\"==this.range_padding_units){const t=(h-a)*this.range_padding/2;a-=t,h+=t}else a-=this.range_padding,h+=this.range_padding;this.setv({start:a,end:h,levels:e},{silent:t}),\"auto\"==this.bounds&&this.setv({bounds:[a,h]},{silent:!0})}}n.FactorRange=h,h.__name__=\"FactorRange\",h.init_FactorRange()},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=e(1),s=e(81),a=n.__importStar(e(18));class r extends s.Model{constructor(e){super(e),this.have_updated_interactively=!1}static init_Range(){this.define({bounds:[a.Any],min_interval:[a.Any],max_interval:[a.Any]}),this.internal({plots:[a.Array,[]]})}get is_reversed(){return this.start>this.end}get is_valid(){return!isNaN(this.min)&&!isNaN(this.max)}}i.Range=r,r.__name__=\"Range\",r.init_Range()},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=e(1).__importStar(e(101));i.generic_line_legend=function(e,t,{x0:i,x1:n,y0:c,y1:o},r){t.save(),t.beginPath(),t.moveTo(i,(c+o)/2),t.lineTo(n,(c+o)/2),e.line.doit&&(e.line.set_vectorize(t,r),t.stroke()),t.restore()},i.generic_area_legend=function(e,t,{x0:i,x1:n,y0:c,y1:o},r){const l=.1*Math.abs(n-i),a=.1*Math.abs(o-c),s=i+l,_=n-l,h=c+a,v=o-a;e.fill.doit&&(e.fill.set_vectorize(t,r),t.fillRect(s,h,_-s,v-h)),null!=e.hatch&&e.hatch.doit&&(e.hatch.set_vectorize(t,r),t.fillRect(s,h,_-s,v-h)),e.line&&e.line.doit&&(t.beginPath(),t.rect(s,h,_-s,v-h),e.line.set_vectorize(t,r),t.stroke())},i.line_interpolation=function(e,t,i,c,o,r){const{sx:l,sy:a}=t;let s,_,h,v;\"point\"==t.type?([h,v]=e.yscale.r_invert(a-1,a+1),[s,_]=e.xscale.r_invert(l-1,l+1)):\"v\"==t.direction?([h,v]=e.yscale.r_invert(a,a),[s,_]=[Math.min(i-1,o-1),Math.max(i+1,o+1)]):([s,_]=e.xscale.r_invert(l,l),[h,v]=[Math.min(c-1,r-1),Math.max(c+1,r+1)]);const{x,y}=n.check_2_segments_intersect(s,h,_,v,i,c,o,r);return[x,y]}},\n", - " function _(t,n,e){function i(t,n){return(t.x-n.x)**2+(t.y-n.y)**2}function r(t,n,e){const r=i(n,e);if(0==r)return i(t,n);const s=((t.x-n.x)*(e.x-n.x)+(t.y-n.y)*(e.y-n.y))/r;if(s<0)return i(t,n);if(s>1)return i(t,e);return i(t,{x:n.x+s*(e.x-n.x),y:n.y+s*(e.y-n.y)})}Object.defineProperty(e,\"__esModule\",{value:!0}),e.point_in_poly=function(t,n,e,i){let r=!1,s=e[e.length-1],o=i[i.length-1];for(let u=0;u0&&_<1&&l>0&&l<1,x:t+_*(e-t),y:n+_*(i-n)}}}},\n", - " function _(t,e,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=t(103),a=t(107),n=t(108),o=t(109),_=t(22);class h{constructor(t){this._atlas=new Map,this._width=256,this._height=256,this.tex=new i.Texture2d(t),this.tex.set_wrapping(t.REPEAT,t.REPEAT),this.tex.set_interpolation(t.NEAREST,t.NEAREST),this.tex.set_size([this._width,this._height],t.RGBA),this.tex.set_data([0,0],[this._width,this._height],new Uint8Array(4*this._width*this._height)),this.get_atlas_data([1])}get_atlas_data(t){const e=t.join(\"-\");let s=this._atlas.get(e);if(null==s){const[i,a]=this.make_pattern(t),n=this._atlas.size;this.tex.set_data([0,n],[this._width,1],new Uint8Array(i.map(t=>t+10))),s=[n/this._height,a],this._atlas.set(e,s)}return s}make_pattern(t){t.length>1&&t.length%2&&(t=t.concat(t));let e=0;for(const s of t)e+=s;const s=[];let i=0;for(let e=0,a=t.length+2;es[r]?-1:0,o=s[r-1],i=s[r]),n[4*t+0]=s[r],n[4*t+1]=_,n[4*t+2]=o,n[4*t+3]=i}return[n,e]}}h.__name__=\"DashAtlas\";const r={miter:0,round:1,bevel:2},l={\"\":0,none:0,\".\":0,round:1,\")\":1,\"(\":1,o:1,\"triangle in\":2,\"<\":2,\"triangle out\":3,\">\":3,square:4,\"[\":4,\"]\":4,\"=\":4,butt:5,\"|\":5};class g extends a.BaseGLGlyph{init(){const{gl:t}=this;this._scale_aspect=0;const e=n.vertex_shader,s=o.fragment_shader;this.prog=new i.Program(t),this.prog.set_shaders(e,s),this.index_buffer=new i.IndexBuffer(t),this.vbo_position=new i.VertexBuffer(t),this.vbo_tangents=new i.VertexBuffer(t),this.vbo_segment=new i.VertexBuffer(t),this.vbo_angles=new i.VertexBuffer(t),this.vbo_texcoord=new i.VertexBuffer(t),this.dash_atlas=new h(t)}draw(t,e,s){const i=e.glglyph;if(i.data_changed&&(i._set_data(),i.data_changed=!1),this.visuals_changed&&(this._set_visuals(),this.visuals_changed=!1),i._update_scale(1,1),this._scale_aspect=1,this.prog.set_attribute(\"a_position\",\"vec2\",i.vbo_position),this.prog.set_attribute(\"a_tangents\",\"vec4\",i.vbo_tangents),this.prog.set_attribute(\"a_segment\",\"vec2\",i.vbo_segment),this.prog.set_attribute(\"a_angles\",\"vec2\",i.vbo_angles),this.prog.set_attribute(\"a_texcoord\",\"vec2\",i.vbo_texcoord),this.prog.set_uniform(\"u_length\",\"float\",[i.cumsum]),this.prog.set_texture(\"u_dash_atlas\",this.dash_atlas.tex),this.prog.set_uniform(\"u_pixel_ratio\",\"float\",[s.pixel_ratio]),this.prog.set_uniform(\"u_canvas_size\",\"vec2\",[s.width,s.height]),this.prog.set_uniform(\"u_scale_aspect\",\"vec2\",[1,1]),this.prog.set_uniform(\"u_scale_length\",\"float\",[Math.sqrt(2)]),this.I_triangles=i.I_triangles,this.I_triangles.length<65535)this.index_buffer.set_size(2*this.I_triangles.length),this.index_buffer.set_data(0,new Uint16Array(this.I_triangles)),this.prog.draw(this.gl.TRIANGLES,this.index_buffer);else{t=Array.from(this.I_triangles);const e=this.I_triangles.length,s=64008,a=[];for(let t=0,i=Math.ceil(e/s);t1)for(let e=0;e0||console.log(`Variable ${t} is not an active attribute`));else if(this._unset_variables.has(t)&&this._unset_variables.delete(t),this.activate(),i instanceof s.VertexBuffer){const[s,n]=this.ATYPEINFO[e],h=\"vertexAttribPointer\",l=[s,n,!1,a,r];this._attributes.set(t,[i.handle,o,h,l])}else{const s=this.ATYPEMAP[e];this._attributes.set(t,[null,o,s,i])}}_pre_draw(){this.activate();for(const[t,e,i]of this._samplers.values())this.gl.activeTexture(this.gl.TEXTURE0+i),this.gl.bindTexture(t,e);for(const[t,e,i,s]of this._attributes.values())null!=t?(this.gl.bindBuffer(this.gl.ARRAY_BUFFER,t),this.gl.enableVertexAttribArray(e),this.gl[i].apply(this.gl,[e,...s])):(this.gl.bindBuffer(this.gl.ARRAY_BUFFER,null),this.gl.disableVertexAttribArray(e),this.gl[i].apply(this.gl,[e,...s]));this._validated||(this._validated=!0,this._validate())}_validate(){if(this._unset_variables.size&&console.log(\"Program has unset variables: \"+this._unset_variables),this.gl.validateProgram(this.handle),!this.gl.getProgramParameter(this.handle,this.gl.VALIDATE_STATUS))throw console.log(this.gl.getProgramInfoLog(this.handle)),new Error(\"Program validation error\")}draw(t,e){if(!this._linked)throw new Error(\"Cannot draw program if code has not been set\");if(e instanceof s.IndexBuffer){this._pre_draw(),e.activate();const i=e.buffer_size/2,s=this.gl.UNSIGNED_SHORT;this.gl.drawElements(t,i,s,0),e.deactivate()}else{const[i,s]=e;0!=s&&(this._pre_draw(),this.gl.drawArrays(t,i,s))}}}i.Program=a,a.__name__=\"Program\"},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});class i{constructor(e){this.gl=e,this._usage=35048,this.buffer_size=0,this.handle=this.gl.createBuffer()}delete(){this.gl.deleteBuffer(this.handle)}activate(){this.gl.bindBuffer(this._target,this.handle)}deactivate(){this.gl.bindBuffer(this._target,null)}set_size(e){e!=this.buffer_size&&(this.activate(),this.gl.bufferData(this._target,e,this._usage),this.buffer_size=e)}set_data(e,t){this.activate(),this.gl.bufferSubData(this._target,e,t)}}s.Buffer=i,i.__name__=\"Buffer\";class r extends i{constructor(){super(...arguments),this._target=34962}}s.VertexBuffer=r,r.__name__=\"VertexBuffer\";class a extends i{constructor(){super(...arguments),this._target=34963}}s.IndexBuffer=a,a.__name__=\"IndexBuffer\"},\n", - " function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});const a=t(11);class r{constructor(t){this.gl=t,this._target=3553,this._types={Int8Array:5120,Uint8Array:5121,Int16Array:5122,Uint16Array:5123,Int32Array:5124,Uint32Array:5125,Float32Array:5126},this.handle=this.gl.createTexture()}delete(){this.gl.deleteTexture(this.handle)}activate(){this.gl.bindTexture(this._target,this.handle)}deactivate(){this.gl.bindTexture(this._target,0)}_get_alignment(t){const e=[4,8,2,1];for(const i of e)if(t%i==0)return i;a.unreachable()}set_wrapping(t,e){this.activate(),this.gl.texParameterf(this._target,this.gl.TEXTURE_WRAP_S,t),this.gl.texParameterf(this._target,this.gl.TEXTURE_WRAP_T,e)}set_interpolation(t,e){this.activate(),this.gl.texParameterf(this._target,this.gl.TEXTURE_MIN_FILTER,t),this.gl.texParameterf(this._target,this.gl.TEXTURE_MAG_FILTER,e)}set_size([t,e],i){var a,r,s;t==(null===(a=this._shape_format)||void 0===a?void 0:a.width)&&e==(null===(r=this._shape_format)||void 0===r?void 0:r.height)&&i==(null===(s=this._shape_format)||void 0===s?void 0:s.format)||(this._shape_format={width:t,height:e,format:i},this.activate(),this.gl.texImage2D(this._target,0,i,t,e,0,i,this.gl.UNSIGNED_BYTE,null))}set_data(t,[e,i],a){this.activate();const{format:r}=this._shape_format,[s,h]=t,l=this._types[a.constructor.name];if(null==l)throw new Error(`Type ${a.constructor.name} not allowed for texture`);const _=this._get_alignment(e);4!=_&&this.gl.pixelStorei(this.gl.UNPACK_ALIGNMENT,_),this.gl.texSubImage2D(this._target,0,s,h,e,i,r,l,a),4!=_&&this.gl.pixelStorei(this.gl.UNPACK_ALIGNMENT,4)}}i.Texture2d=r,r.__name__=\"Texture2d\"},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});class s{constructor(e,t){this.gl=e,this.glyph=t,this.nvertices=0,this.size_changed=!1,this.data_changed=!1,this.visuals_changed=!1,this.init()}set_data_changed(){const{data_size:e}=this.glyph;e!=this.nvertices&&(this.nvertices=e,this.size_changed=!0),this.data_changed=!0}set_visuals_changed(){this.visuals_changed=!0}render(e,t,i){if(0==t.length)return!0;const{width:s,height:h}=this.glyph.renderer.plot_view.canvas_view.webgl.canvas,a={pixel_ratio:this.glyph.renderer.plot_view.canvas_view.pixel_ratio,width:s,height:h};return this.draw(t,i,a),!0}}i.BaseGLGlyph=s,s.__name__=\"BaseGLGlyph\"},\n", - " function _(n,e,t){Object.defineProperty(t,\"__esModule\",{value:!0}),t.vertex_shader=\"\\nprecision mediump float;\\n\\nconst float PI = 3.14159265358979323846264;\\nconst float THETA = 15.0 * 3.14159265358979323846264/180.0;\\n\\nuniform float u_pixel_ratio;\\nuniform vec2 u_canvas_size, u_offset;\\nuniform vec2 u_scale_aspect;\\nuniform float u_scale_length;\\n\\nuniform vec4 u_color;\\nuniform float u_antialias;\\nuniform float u_length;\\nuniform float u_linewidth;\\nuniform float u_dash_index;\\nuniform float u_closed;\\n\\nattribute vec2 a_position;\\nattribute vec4 a_tangents;\\nattribute vec2 a_segment;\\nattribute vec2 a_angles;\\nattribute vec2 a_texcoord;\\n\\nvarying vec4 v_color;\\nvarying vec2 v_segment;\\nvarying vec2 v_angles;\\nvarying vec2 v_texcoord;\\nvarying vec2 v_miter;\\nvarying float v_length;\\nvarying float v_linewidth;\\n\\nfloat cross(in vec2 v1, in vec2 v2)\\n{\\n return v1.x*v2.y - v1.y*v2.x;\\n}\\n\\nfloat signed_distance(in vec2 v1, in vec2 v2, in vec2 v3)\\n{\\n return cross(v2-v1,v1-v3) / length(v2-v1);\\n}\\n\\nvoid rotate( in vec2 v, in float alpha, out vec2 result )\\n{\\n float c = cos(alpha);\\n float s = sin(alpha);\\n result = vec2( c*v.x - s*v.y,\\n s*v.x + c*v.y );\\n}\\n\\nvoid main()\\n{\\n bool closed = (u_closed > 0.0);\\n\\n // Attributes and uniforms to varyings\\n v_color = u_color;\\n v_linewidth = u_linewidth;\\n v_segment = a_segment * u_scale_length;\\n v_length = u_length * u_scale_length;\\n\\n // Scale to map to pixel coordinates. The original algorithm from the paper\\n // assumed isotropic scale. We obviously do not have this.\\n vec2 abs_scale_aspect = abs(u_scale_aspect);\\n vec2 abs_scale = u_scale_length * abs_scale_aspect;\\n\\n // Correct angles for aspect ratio\\n vec2 av;\\n av = vec2(1.0, tan(a_angles.x)) / abs_scale_aspect;\\n v_angles.x = atan(av.y, av.x);\\n av = vec2(1.0, tan(a_angles.y)) / abs_scale_aspect;\\n v_angles.y = atan(av.y, av.x);\\n\\n // Thickness below 1 pixel are represented using a 1 pixel thickness\\n // and a modified alpha\\n v_color.a = min(v_linewidth, v_color.a);\\n v_linewidth = max(v_linewidth, 1.0);\\n\\n // If color is fully transparent we just will discard the fragment anyway\\n if( v_color.a <= 0.0 ) {\\n gl_Position = vec4(0.0,0.0,0.0,1.0);\\n return;\\n }\\n\\n // This is the actual half width of the line\\n float w = ceil(u_antialias+v_linewidth)/2.0;\\n\\n vec2 position = a_position;\\n\\n vec2 t1 = normalize(a_tangents.xy * abs_scale_aspect); // note the scaling for aspect ratio here\\n vec2 t2 = normalize(a_tangents.zw * abs_scale_aspect);\\n float u = a_texcoord.x;\\n float v = a_texcoord.y;\\n vec2 o1 = vec2( +t1.y, -t1.x);\\n vec2 o2 = vec2( +t2.y, -t2.x);\\n\\n // This is a join\\n // ----------------------------------------------------------------\\n if( t1 != t2 ) {\\n float angle = atan (t1.x*t2.y-t1.y*t2.x, t1.x*t2.x+t1.y*t2.y); // Angle needs recalculation for some reason\\n vec2 t = normalize(t1+t2);\\n vec2 o = vec2( + t.y, - t.x);\\n\\n if ( u_dash_index > 0.0 )\\n {\\n // Broken angle\\n // ----------------------------------------------------------------\\n if( (abs(angle) > THETA) ) {\\n position += v * w * o / cos(angle/2.0);\\n float s = sign(angle);\\n if( angle < 0.0 ) {\\n if( u == +1.0 ) {\\n u = v_segment.y + v * w * tan(angle/2.0);\\n if( v == 1.0 ) {\\n position -= 2.0 * w * t1 / sin(angle);\\n u -= 2.0 * w / sin(angle);\\n }\\n } else {\\n u = v_segment.x - v * w * tan(angle/2.0);\\n if( v == 1.0 ) {\\n position += 2.0 * w * t2 / sin(angle);\\n u += 2.0*w / sin(angle);\\n }\\n }\\n } else {\\n if( u == +1.0 ) {\\n u = v_segment.y + v * w * tan(angle/2.0);\\n if( v == -1.0 ) {\\n position += 2.0 * w * t1 / sin(angle);\\n u += 2.0 * w / sin(angle);\\n }\\n } else {\\n u = v_segment.x - v * w * tan(angle/2.0);\\n if( v == -1.0 ) {\\n position -= 2.0 * w * t2 / sin(angle);\\n u -= 2.0*w / sin(angle);\\n }\\n }\\n }\\n // Continuous angle\\n // ------------------------------------------------------------\\n } else {\\n position += v * w * o / cos(angle/2.0);\\n if( u == +1.0 ) u = v_segment.y;\\n else u = v_segment.x;\\n }\\n }\\n\\n // Solid line\\n // --------------------------------------------------------------------\\n else\\n {\\n position.xy += v * w * o / cos(angle/2.0);\\n if( angle < 0.0 ) {\\n if( u == +1.0 ) {\\n u = v_segment.y + v * w * tan(angle/2.0);\\n } else {\\n u = v_segment.x - v * w * tan(angle/2.0);\\n }\\n } else {\\n if( u == +1.0 ) {\\n u = v_segment.y + v * w * tan(angle/2.0);\\n } else {\\n u = v_segment.x - v * w * tan(angle/2.0);\\n }\\n }\\n }\\n\\n // This is a line start or end (t1 == t2)\\n // ------------------------------------------------------------------------\\n } else {\\n position += v * w * o1;\\n if( u == -1.0 ) {\\n u = v_segment.x - w;\\n position -= w * t1;\\n } else {\\n u = v_segment.y + w;\\n position += w * t2;\\n }\\n }\\n\\n // Miter distance\\n // ------------------------------------------------------------------------\\n vec2 t;\\n vec2 curr = a_position * abs_scale;\\n if( a_texcoord.x < 0.0 ) {\\n vec2 next = curr + t2*(v_segment.y-v_segment.x);\\n\\n rotate( t1, +v_angles.x/2.0, t);\\n v_miter.x = signed_distance(curr, curr+t, position);\\n\\n rotate( t2, +v_angles.y/2.0, t);\\n v_miter.y = signed_distance(next, next+t, position);\\n } else {\\n vec2 prev = curr - t1*(v_segment.y-v_segment.x);\\n\\n rotate( t1, -v_angles.x/2.0,t);\\n v_miter.x = signed_distance(prev, prev+t, position);\\n\\n rotate( t2, -v_angles.y/2.0,t);\\n v_miter.y = signed_distance(curr, curr+t, position);\\n }\\n\\n if (!closed && v_segment.x <= 0.0) {\\n v_miter.x = 1e10;\\n }\\n if (!closed && v_segment.y >= v_length)\\n {\\n v_miter.y = 1e10;\\n }\\n\\n v_texcoord = vec2( u, v*w );\\n\\n // Calculate position in device coordinates. Note that we\\n // already scaled with abs scale above.\\n vec2 normpos = position * sign(u_scale_aspect);\\n normpos += 0.5; // make up for Bokeh's offset\\n normpos /= u_canvas_size / u_pixel_ratio; // in 0..1\\n gl_Position = vec4(normpos*2.0-1.0, 0.0, 1.0);\\n gl_Position.y *= -1.0;\\n}\\n\"},\n", - " function _(n,t,e){Object.defineProperty(e,\"__esModule\",{value:!0}),e.fragment_shader=\"\\nprecision mediump float;\\n\\nconst float PI = 3.14159265358979323846264;\\nconst float THETA = 15.0 * 3.14159265358979323846264/180.0;\\n\\nuniform sampler2D u_dash_atlas;\\n\\nuniform vec2 u_linecaps;\\nuniform float u_miter_limit;\\nuniform float u_linejoin;\\nuniform float u_antialias;\\nuniform float u_dash_phase;\\nuniform float u_dash_period;\\nuniform float u_dash_index;\\nuniform vec2 u_dash_caps;\\nuniform float u_closed;\\n\\nvarying vec4 v_color;\\nvarying vec2 v_segment;\\nvarying vec2 v_angles;\\nvarying vec2 v_texcoord;\\nvarying vec2 v_miter;\\nvarying float v_length;\\nvarying float v_linewidth;\\n\\n// Compute distance to cap ----------------------------------------------------\\nfloat cap( int type, float dx, float dy, float t, float linewidth )\\n{\\n float d = 0.0;\\n dx = abs(dx);\\n dy = abs(dy);\\n if (type == 0) discard; // None\\n else if (type == 1) d = sqrt(dx*dx+dy*dy); // Round\\n else if (type == 3) d = (dx+abs(dy)); // Triangle in\\n else if (type == 2) d = max(abs(dy),(t+dx-abs(dy))); // Triangle out\\n else if (type == 4) d = max(dx,dy); // Square\\n else if (type == 5) d = max(dx+t,dy); // Butt\\n return d;\\n}\\n\\n// Compute distance to join -------------------------------------------------\\nfloat join( in int type, in float d, in vec2 segment, in vec2 texcoord, in vec2 miter,\\n in float linewidth )\\n{\\n // texcoord.x is distance from start\\n // texcoord.y is distance from centerline\\n // segment.x and y indicate the limits (as for texcoord.x) for this segment\\n\\n float dx = texcoord.x;\\n\\n // Round join\\n if( type == 1 ) {\\n if (dx < segment.x) {\\n d = max(d,length( texcoord - vec2(segment.x,0.0)));\\n //d = length( texcoord - vec2(segment.x,0.0));\\n } else if (dx > segment.y) {\\n d = max(d,length( texcoord - vec2(segment.y,0.0)));\\n //d = length( texcoord - vec2(segment.y,0.0));\\n }\\n }\\n // Bevel join\\n else if ( type == 2 ) {\\n if (dx < segment.x) {\\n vec2 x = texcoord - vec2(segment.x,0.0);\\n d = max(d, max(abs(x.x), abs(x.y)));\\n\\n } else if (dx > segment.y) {\\n vec2 x = texcoord - vec2(segment.y,0.0);\\n d = max(d, max(abs(x.x), abs(x.y)));\\n }\\n /* Original code for bevel which does not work for us\\n if( (dx < segment.x) || (dx > segment.y) )\\n d = max(d, min(abs(x.x),abs(x.y)));\\n */\\n }\\n\\n return d;\\n}\\n\\nvoid main()\\n{\\n // If color is fully transparent we just discard the fragment\\n if( v_color.a <= 0.0 ) {\\n discard;\\n }\\n\\n // Test if dash pattern is the solid one (0)\\n bool solid = (u_dash_index == 0.0);\\n\\n // Test if path is closed\\n bool closed = (u_closed > 0.0);\\n\\n vec4 color = v_color;\\n float dx = v_texcoord.x;\\n float dy = v_texcoord.y;\\n float t = v_linewidth/2.0-u_antialias;\\n float width = 1.0; //v_linewidth; original code had dashes scale with line width, we do not\\n float d = 0.0;\\n\\n vec2 linecaps = u_linecaps;\\n vec2 dash_caps = u_dash_caps;\\n float line_start = 0.0;\\n float line_stop = v_length;\\n\\n // Apply miter limit; fragments too far into the miter are simply discarded\\n if( (dx < v_segment.x) || (dx > v_segment.y) ) {\\n float into_miter = max(v_segment.x - dx, dx - v_segment.y);\\n if (into_miter > u_miter_limit*v_linewidth/2.0)\\n discard;\\n }\\n\\n // Solid line --------------------------------------------------------------\\n if( solid ) {\\n d = abs(dy);\\n if( (!closed) && (dx < line_start) ) {\\n d = cap( int(u_linecaps.x), abs(dx), abs(dy), t, v_linewidth );\\n }\\n else if( (!closed) && (dx > line_stop) ) {\\n d = cap( int(u_linecaps.y), abs(dx)-line_stop, abs(dy), t, v_linewidth );\\n }\\n else {\\n d = join( int(u_linejoin), abs(dy), v_segment, v_texcoord, v_miter, v_linewidth );\\n }\\n\\n // Dash line --------------------------------------------------------------\\n } else {\\n float segment_start = v_segment.x;\\n float segment_stop = v_segment.y;\\n float segment_center= (segment_start+segment_stop)/2.0;\\n float freq = u_dash_period*width;\\n float u = mod( dx + u_dash_phase*width, freq);\\n vec4 tex = texture2D(u_dash_atlas, vec2(u/freq, u_dash_index)) * 255.0 -10.0; // conversion to int-like\\n float dash_center= tex.x * width;\\n float dash_type = tex.y;\\n float _start = tex.z * width;\\n float _stop = tex.a * width;\\n float dash_start = dx - u + _start;\\n float dash_stop = dx - u + _stop;\\n\\n // Compute extents of the first dash (the one relative to v_segment.x)\\n // Note: this could be computed in the vertex shader\\n if( (dash_stop < segment_start) && (dash_caps.x != 5.0) ) {\\n float u = mod(segment_start + u_dash_phase*width, freq);\\n vec4 tex = texture2D(u_dash_atlas, vec2(u/freq, u_dash_index)) * 255.0 -10.0; // conversion to int-like\\n dash_center= tex.x * width;\\n //dash_type = tex.y;\\n float _start = tex.z * width;\\n float _stop = tex.a * width;\\n dash_start = segment_start - u + _start;\\n dash_stop = segment_start - u + _stop;\\n }\\n\\n // Compute extents of the last dash (the one relatives to v_segment.y)\\n // Note: This could be computed in the vertex shader\\n else if( (dash_start > segment_stop) && (dash_caps.y != 5.0) ) {\\n float u = mod(segment_stop + u_dash_phase*width, freq);\\n vec4 tex = texture2D(u_dash_atlas, vec2(u/freq, u_dash_index)) * 255.0 -10.0; // conversion to int-like\\n dash_center= tex.x * width;\\n //dash_type = tex.y;\\n float _start = tex.z * width;\\n float _stop = tex.a * width;\\n dash_start = segment_stop - u + _start;\\n dash_stop = segment_stop - u + _stop;\\n }\\n\\n // This test if the we are dealing with a discontinuous angle\\n bool discontinuous = ((dx < segment_center) && abs(v_angles.x) > THETA) ||\\n ((dx >= segment_center) && abs(v_angles.y) > THETA);\\n //if( dx < line_start) discontinuous = false;\\n //if( dx > line_stop) discontinuous = false;\\n\\n float d_join = join( int(u_linejoin), abs(dy),\\n v_segment, v_texcoord, v_miter, v_linewidth );\\n\\n // When path is closed, we do not have room for linecaps, so we make room\\n // by shortening the total length\\n if (closed) {\\n line_start += v_linewidth/2.0;\\n line_stop -= v_linewidth/2.0;\\n }\\n\\n // We also need to take antialias area into account\\n //line_start += u_antialias;\\n //line_stop -= u_antialias;\\n\\n // Check is dash stop is before line start\\n if( dash_stop <= line_start ) {\\n discard;\\n }\\n // Check is dash start is beyond line stop\\n if( dash_start >= line_stop ) {\\n discard;\\n }\\n\\n // Check if current dash start is beyond segment stop\\n if( discontinuous ) {\\n // Dash start is beyond segment, we discard\\n if( (dash_start > segment_stop) ) {\\n discard;\\n //gl_FragColor = vec4(1.0,0.0,0.0,.25); return;\\n }\\n\\n // Dash stop is before segment, we discard\\n if( (dash_stop < segment_start) ) {\\n discard; //gl_FragColor = vec4(0.0,1.0,0.0,.25); return;\\n }\\n\\n // Special case for round caps (nicer with this)\\n if( dash_caps.x == 1.0 ) {\\n if( (u > _stop) && (dash_stop > segment_stop ) && (abs(v_angles.y) < PI/2.0)) {\\n discard;\\n }\\n }\\n\\n // Special case for round caps (nicer with this)\\n if( dash_caps.y == 1.0 ) {\\n if( (u < _start) && (dash_start < segment_start ) && (abs(v_angles.x) < PI/2.0)) {\\n discard;\\n }\\n }\\n\\n // Special case for triangle caps (in & out) and square\\n // We make sure the cap stop at crossing frontier\\n if( (dash_caps.x != 1.0) && (dash_caps.x != 5.0) ) {\\n if( (dash_start < segment_start ) && (abs(v_angles.x) < PI/2.0) ) {\\n float a = v_angles.x/2.0;\\n float x = (segment_start-dx)*cos(a) - dy*sin(a);\\n float y = (segment_start-dx)*sin(a) + dy*cos(a);\\n if( x > 0.0 ) discard;\\n // We transform the cap into square to avoid holes\\n dash_caps.x = 4.0;\\n }\\n }\\n\\n // Special case for triangle caps (in & out) and square\\n // We make sure the cap stop at crossing frontier\\n if( (dash_caps.y != 1.0) && (dash_caps.y != 5.0) ) {\\n if( (dash_stop > segment_stop ) && (abs(v_angles.y) < PI/2.0) ) {\\n float a = v_angles.y/2.0;\\n float x = (dx-segment_stop)*cos(a) - dy*sin(a);\\n float y = (dx-segment_stop)*sin(a) + dy*cos(a);\\n if( x > 0.0 ) discard;\\n // We transform the caps into square to avoid holes\\n dash_caps.y = 4.0;\\n }\\n }\\n }\\n\\n // Line cap at start\\n if( (dx < line_start) && (dash_start < line_start) && (dash_stop > line_start) ) {\\n d = cap( int(linecaps.x), dx-line_start, dy, t, v_linewidth);\\n }\\n // Line cap at stop\\n else if( (dx > line_stop) && (dash_stop > line_stop) && (dash_start < line_stop) ) {\\n d = cap( int(linecaps.y), dx-line_stop, dy, t, v_linewidth);\\n }\\n // Dash cap left - dash_type = -1, 0 or 1, but there may be roundoff errors\\n else if( dash_type < -0.5 ) {\\n d = cap( int(dash_caps.y), abs(u-dash_center), dy, t, v_linewidth);\\n if( (dx > line_start) && (dx < line_stop) )\\n d = max(d,d_join);\\n }\\n // Dash cap right\\n else if( dash_type > 0.5 ) {\\n d = cap( int(dash_caps.x), abs(dash_center-u), dy, t, v_linewidth);\\n if( (dx > line_start) && (dx < line_stop) )\\n d = max(d,d_join);\\n }\\n // Dash body (plain)\\n else {// if( dash_type > -0.5 && dash_type < 0.5) {\\n d = abs(dy);\\n }\\n\\n // Line join\\n if( (dx > line_start) && (dx < line_stop)) {\\n if( (dx <= segment_start) && (dash_start <= segment_start)\\n && (dash_stop >= segment_start) ) {\\n d = d_join;\\n // Antialias at outer border\\n float angle = PI/2.+v_angles.x;\\n float f = abs( (segment_start - dx)*cos(angle) - dy*sin(angle));\\n d = max(f,d);\\n }\\n else if( (dx > segment_stop) && (dash_start <= segment_stop)\\n && (dash_stop >= segment_stop) ) {\\n d = d_join;\\n // Antialias at outer border\\n float angle = PI/2.+v_angles.y;\\n float f = abs((dx - segment_stop)*cos(angle) - dy*sin(angle));\\n d = max(f,d);\\n }\\n else if( dx < (segment_start - v_linewidth/2.)) {\\n discard;\\n }\\n else if( dx > (segment_stop + v_linewidth/2.)) {\\n discard;\\n }\\n }\\n else if( dx < (segment_start - v_linewidth/2.)) {\\n discard;\\n }\\n else if( dx > (segment_stop + v_linewidth/2.)) {\\n discard;\\n }\\n }\\n\\n // Distance to border ------------------------------------------------------\\n d = d - t;\\n if( d < 0.0 ) {\\n gl_FragColor = color;\\n } else {\\n d /= u_antialias;\\n gl_FragColor = vec4(color.rgb, exp(-d*d)*color.a);\\n }\\n}\\n\"},\n", - " function _(e,i,t){Object.defineProperty(t,\"__esModule\",{value:!0});const s=e(1),l=e(93),_=e(100),n=s.__importStar(e(101)),o=s.__importStar(e(28)),a=e(88);class h extends l.XYGlyphView{_inner_loop(e,i,t,s,l){for(const _ of i)0!=_?isNaN(t[_]+s[_])?(e.closePath(),l.apply(e),e.beginPath()):e.lineTo(t[_],s[_]):(e.beginPath(),e.moveTo(t[_],s[_]));e.closePath(),l.call(e)}_render(e,i,{sx:t,sy:s}){this.visuals.fill.doit&&(this.visuals.fill.set_value(e),this._inner_loop(e,i,t,s,e.fill)),this.visuals.hatch.doit2(e,0,()=>this._inner_loop(e,i,t,s,e.fill),()=>this.renderer.request_render()),this.visuals.line.doit&&(this.visuals.line.set_value(e),this._inner_loop(e,i,t,s,e.stroke))}draw_legend_for_index(e,i,t){_.generic_area_legend(this.visuals,e,i,t)}_hit_point(e){const i=new a.Selection;return n.point_in_poly(e.sx,e.sy,this.sx,this.sy)&&(i.add_to_selected_glyphs(this.model),i.view=this),i}}t.PatchView=h,h.__name__=\"PatchView\";class r extends l.XYGlyph{constructor(e){super(e)}static init_Patch(){this.prototype.default_view=h,this.mixins([o.Line,o.Fill,o.Hatch])}}t.Patch=r,r.__name__=\"Patch\",r.init_Patch()},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=e(1),r=e(24),n=e(112),a=i.__importStar(e(101)),_=i.__importStar(e(18)),h=e(88);class l extends n.AreaView{_index_data(e){const{min:t,max:s}=Math,{data_size:i}=this;for(let r=0;r=0;t--)e.lineTo(s[t],i[t]);e.closePath(),r.call(e)}_render(e,t,{sx1:s,sx2:i,sy:r}){this.visuals.fill.doit&&(this.visuals.fill.set_value(e),this._inner(e,s,i,r,e.fill)),this.visuals.hatch.doit2(e,0,()=>this._inner(e,s,i,r,e.fill),()=>this.renderer.request_render())}_hit_point(e){const t=this.sy.length,s=new r.NumberArray(2*t),i=new r.NumberArray(2*t);for(let e=0,r=t;e=0;s--)e.lineTo(t[s],i[s]);e.closePath(),r.call(e)}_render(e,t,{sx:s,sy1:i,sy2:r}){this.visuals.fill.doit&&(this.visuals.fill.set_value(e),this._inner(e,s,i,r,e.fill)),this.visuals.hatch.doit2(e,0,()=>this._inner(e,s,i,r,e.fill),()=>this.renderer.request_render())}scenterxy(e){return[this.sx[e],(this.sy1[e]+this.sy2[e])/2]}_hit_point(e){const t=this.sx.length,s=new r.NumberArray(2*t),i=new r.NumberArray(2*t);for(let e=0,r=t;ethis.compute_indices());const i=()=>{const i=()=>this.compute_indices();null!=this.source&&(this.connect(this.source.change,i),this.source instanceof _.ColumnarDataSource&&(this.connect(this.source.streaming,i),this.connect(this.source.patching,i)))};let e=null!=this.source;e?i():this.connect(this.properties.source.change,()=>{e||(i(),e=!0)})}compute_indices(){var i;const{source:e}=this;if(null==e)return;const s=null!==(i=e.get_length())&&void 0!==i?i:1,t=r.Indices.all_set(s);for(const i of this.filters)t.intersect(i.compute_indices(e));this.indices=t,this._indices=[...t],this.indices_map_to_subset()}indices_map_to_subset(){this.indices_map={};for(let i=0;ithis._indices[i]);return new o.Selection(Object.assign(Object.assign({},i.attributes),{indices:e}))}convert_selection_to_subset(i){const e=i.indices.map(i=>this.indices_map[i]);return new o.Selection(Object.assign(Object.assign({},i.attributes),{indices:e}))}convert_indices_from_subset(i){return i.map(i=>this._indices[i])}}s.CDSView=a,a.__name__=\"CDSView\",a.init_CDSView()},\n", - " function _(e,n,t){Object.defineProperty(t,\"__esModule\",{value:!0});const o=e(9);async function i(e,n,t){const o=new e(Object.assign(Object.assign({},t),{model:n}));return o.initialize(),await o.lazy_initialize(),o}t.build_view=async function(e,n={parent:null},t=(e=>e.default_view)){const o=await i(t(e),e,n);return o.connect_signals(),o},t.build_views=async function(e,n,t={parent:null},s=(e=>e.default_view)){const c=o.difference([...e.keys()],n);for(const n of c)e.get(n).remove(),e.delete(n);const a=[],f=n.filter(n=>!e.has(n));for(const n of f){const o=await i(s(n),n,t);e.set(n,o),a.push(o)}for(const e of a)e.connect_signals();return a},t.remove_views=function(e){for(const[n,t]of e)t.remove(),e.delete(n)}},\n", - " function _(e,r,n){Object.defineProperty(n,\"__esModule\",{value:!0});const t=e(1),i=e(91),s=e(117),a=t.__importStar(e(18)),o=e(115),_=e(11);class l extends i.DataRendererView{async lazy_initialize(){await super.lazy_initialize();const e=this.model;let r=null,n=null;const t={v_compute(n){_.assert(null==r);const[t]=r=e.layout_provider.get_edge_coordinates(n);return t}},i={v_compute(e){_.assert(null!=r);const[,n]=r;return r=null,n}},s={v_compute(r){_.assert(null==n);const[t]=n=e.layout_provider.get_node_coordinates(r);return t}},a={v_compute(e){_.assert(null!=n);const[,r]=n;return n=null,r}},{edge_renderer:l,node_renderer:d}=this.model;l.glyph.properties.xs.internal=!0,l.glyph.properties.ys.internal=!0,d.glyph.properties.x.internal=!0,d.glyph.properties.y.internal=!0,l.glyph.xs={expr:t},l.glyph.ys={expr:i},d.glyph.x={expr:s},d.glyph.y={expr:a};const{parent:p}=this;this.edge_view=await o.build_view(l,{parent:p}),this.node_view=await o.build_view(d,{parent:p})}connect_signals(){super.connect_signals(),this.connect(this.model.layout_provider.change,()=>{this.edge_view.set_data(!1),this.node_view.set_data(!1),this.request_render()})}remove(){this.edge_view.remove(),this.node_view.remove(),super.remove()}_render(){this.edge_view.render(),this.node_view.render()}}n.GraphRendererView=l,l.__name__=\"GraphRendererView\";class d extends i.DataRenderer{constructor(e){super(e)}static init_GraphRenderer(){this.prototype.default_view=l,this.define({layout_provider:[a.Instance],node_renderer:[a.Instance],edge_renderer:[a.Instance],selection_policy:[a.Instance,()=>new s.NodesOnly],inspection_policy:[a.Instance,()=>new s.NodesOnly]})}get_selection_manager(){return this.node_renderer.data_source.selection_manager}}n.GraphRenderer=d,d.__name__=\"GraphRenderer\",d.init_GraphRenderer()},\n", - " function _(e,t,n){Object.defineProperty(n,\"__esModule\",{value:!0});const d=e(81),s=e(12),o=e(9),_=e(88);class i extends d.Model{constructor(e){super(e)}_hit_test_nodes(e,t){if(!t.model.visible)return null;const n=t.node_view.glyph.hit_test(e);return null==n?null:t.node_view.model.view.convert_selection_from_subset(n)}_hit_test_edges(e,t){if(!t.model.visible)return null;const n=t.edge_view.glyph.hit_test(e);return null==n?null:t.edge_view.model.view.convert_selection_from_subset(n)}}n.GraphHitTestPolicy=i,i.__name__=\"GraphHitTestPolicy\";class r extends i{constructor(e){super(e)}hit_test(e,t){return this._hit_test_nodes(e,t)}do_selection(e,t,n,d){if(null==e)return!1;const s=t.node_renderer.data_source.selected;return s.update(e,n,d),t.node_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,n,d,s){if(null==e)return!1;const o=n.model.get_selection_manager().get_or_create_inspector(n.node_view.model);return o.update(e,d,s),n.node_view.model.data_source.setv({inspected:o},{silent:!0}),n.node_view.model.data_source.inspect.emit([n.node_view,{geometry:t}]),!o.is_empty()}}n.NodesOnly=r,r.__name__=\"NodesOnly\";class c extends i{constructor(e){super(e)}hit_test(e,t){return this._hit_test_nodes(e,t)}get_linked_edges(e,t,n){let d=[];\"selection\"==n?d=e.selected.indices.map(t=>e.data.index[t]):\"inspection\"==n&&(d=e.inspected.indices.map(t=>e.data.index[t]));const s=[];for(let e=0;es.indexOf(e.data.index,t));return new _.Selection({indices:r})}do_selection(e,t,n,d){if(null==e)return!1;const s=t.edge_renderer.data_source.selected;s.update(e,n,d);const o=t.node_renderer.data_source.selected,_=this.get_linked_nodes(t.node_renderer.data_source,t.edge_renderer.data_source,\"selection\");return o.update(_,n,d),t.edge_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,n,d,s){if(null==e)return!1;const o=n.edge_view.model.data_source.selection_manager.get_or_create_inspector(n.edge_view.model);o.update(e,d,s),n.edge_view.model.data_source.setv({inspected:o},{silent:!0});const _=n.node_view.model.data_source.selection_manager.get_or_create_inspector(n.node_view.model),i=this.get_linked_nodes(n.node_view.model.data_source,n.edge_view.model.data_source,\"inspection\");return _.update(i,d,s),n.node_view.model.data_source.setv({inspected:_},{silent:!0}),n.edge_view.model.data_source.inspect.emit([n.edge_view,{geometry:t}]),!o.is_empty()}}n.EdgesAndLinkedNodes=a,a.__name__=\"EdgesAndLinkedNodes\"},\n", - " function _(e,t,n){Object.defineProperty(n,\"__esModule\",{value:!0});const s=e(81);class o extends s.Model{do_selection(e,t,n,s){return null!==e&&(t.selected.update(e,n,s),t._select.emit(),!t.selected.is_empty())}}n.SelectionPolicy=o,o.__name__=\"SelectionPolicy\";class r extends o{hit_test(e,t){const n=[];for(const s of t){const t=s.hit_test(e);null!==t&&n.push(t)}if(n.length>0){const e=n[0];for(const t of n)e.update_through_intersection(t);return e}return null}}n.IntersectRenderers=r,r.__name__=\"IntersectRenderers\";class c extends o{hit_test(e,t){const n=[];for(const s of t){const t=s.hit_test(e);null!==t&&n.push(t)}if(n.length>0){const e=n[0];for(const t of n)e.update_through_union(t);return e}return null}}n.UnionRenderers=c,c.__name__=\"UnionRenderers\"},\n", - " function _(t,e,n){Object.defineProperty(n,\"__esModule\",{value:!0}),n.concat=function(t,...e){let n=t.length;for(const t of e)n+=t.length;const o=new t.constructor(n);o.set(t,0);let c=t.length;for(const t of e)o.set(t,c),c+=t.length;return o}},\n", - " function _(n,o,e){function t(...n){const o=new Set;for(const e of n)for(const n of e)o.add(n);return o}Object.defineProperty(e,\"__esModule\",{value:!0}),e.union=t,e.intersection=function(n,...o){const e=new Set;n:for(const t of n){for(const n of o)if(!n.has(t))continue n;e.add(t)}return e},e.difference=function(n,...o){const e=new Set(n);for(const n of t(...o))e.delete(n);return e}},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const n=e(14);class o{constructor(e){this.document=e}}s.DocumentEvent=o,o.__name__=\"DocumentEvent\";class r extends o{constructor(e,t,s){super(e),this.events=t,this.setter_id=s}}s.DocumentEventBatch=r,r.__name__=\"DocumentEventBatch\";class d extends o{}s.DocumentChangedEvent=d,d.__name__=\"DocumentChangedEvent\";class _ extends d{constructor(e,t,s){super(e),this.msg_type=t,this.msg_data=s}json(e){const t=this.msg_data,s=n.HasProps._value_to_json(t),o=new Set;return n.HasProps._value_record_references(t,o,{recursive:!0}),{kind:\"MessageSent\",msg_type:this.msg_type,msg_data:s}}}s.MessageSentEvent=_,_.__name__=\"MessageSentEvent\";class i extends d{constructor(e,t,s,n,o,r,d){super(e),this.model=t,this.attr=s,this.old=n,this.new_=o,this.setter_id=r,this.hint=d}json(e){if(\"id\"===this.attr)throw new Error(\"'id' field should never change, whatever code just set it is wrong\");if(null!=this.hint)return this.hint.json(e);const t=this.new_,s=n.HasProps._value_to_json(t),o=new Set;n.HasProps._value_record_references(t,o,{recursive:!0}),o.has(this.model)&&this.model!==t&&o.delete(this.model);for(const t of o)e.add(t);return{kind:\"ModelChanged\",model:this.model.ref(),attr:this.attr,new:s}}}s.ModelChangedEvent=i,i.__name__=\"ModelChangedEvent\";class a extends d{constructor(e,t,s){super(e),this.column_source=t,this.patches=s}json(e){return{kind:\"ColumnsPatched\",column_source:this.column_source,patches:this.patches}}}s.ColumnsPatchedEvent=a,a.__name__=\"ColumnsPatchedEvent\";class c extends d{constructor(e,t,s,n){super(e),this.column_source=t,this.data=s,this.rollover=n}json(e){return{kind:\"ColumnsStreamed\",column_source:this.column_source,data:this.data,rollover:this.rollover}}}s.ColumnsStreamedEvent=c,c.__name__=\"ColumnsStreamedEvent\";class h extends d{constructor(e,t,s){super(e),this.title=t,this.setter_id=s}json(e){return{kind:\"TitleChanged\",title:this.title}}}s.TitleChangedEvent=h,h.__name__=\"TitleChangedEvent\";class u extends d{constructor(e,t,s){super(e),this.model=t,this.setter_id=s}json(e){return n.HasProps._value_record_references(this.model,e,{recursive:!0}),{kind:\"RootAdded\",model:this.model.ref()}}}s.RootAddedEvent=u,u.__name__=\"RootAddedEvent\";class l extends d{constructor(e,t,s){super(e),this.model=t,this.setter_id=s}json(e){return{kind:\"RootRemoved\",model:this.model.ref()}}}s.RootRemovedEvent=l,l.__name__=\"RootRemovedEvent\"},\n", - " function _(e,s,t){Object.defineProperty(t,\"__esModule\",{value:!0});const i=e(1),l=e(123),_=i.__importStar(e(28));class o extends l.UpperLowerView{connect_signals(){super.connect_signals();const e=()=>this.set_data(this.model.source);this.connect(this.model.change,e),this.connect(this.model.source.streaming,e),this.connect(this.model.source.patching,e),this.connect(this.model.source.change,e)}_render(){this._map_data();const{ctx:e}=this.layer;e.beginPath(),e.moveTo(this._lower_sx[0],this._lower_sy[0]);for(let s=0,t=this._lower_sx.length;s=0;s--)e.lineTo(this._upper_sx[s],this._upper_sy[s]);e.closePath(),this.visuals.fill.doit&&(this.visuals.fill.set_value(e),e.fill()),e.beginPath(),e.moveTo(this._lower_sx[0],this._lower_sy[0]);for(let s=0,t=this._lower_sx.length;snew r.ColumnDataSource]})}}i.UpperLower=a,a.__name__=\"UpperLower\",a.init_UpperLower()},\n", - " function _(t,i,s){Object.defineProperty(s,\"__esModule\",{value:!0});const e=t(1),o=t(36),n=t(15),l=e.__importStar(t(28)),a=e.__importStar(t(18)),h=t(79);s.EDGE_TOLERANCE=2.5;class r extends o.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,()=>this.plot_view.request_paint(this)),this.connect(this.model.data_update,()=>this.plot_view.request_paint(this))}_render(){if(null==this.model.left&&null==this.model.right&&null==this.model.top&&null==this.model.bottom)return;const{frame:t}=this.plot_view,i=this.coordinates.x_scale,s=this.coordinates.y_scale,e=(t,i,s,e,o)=>{let n;return n=null!=t?this.model.screen?t:\"data\"==i?s.compute(t):e.compute(t):o,n};this.sleft=e(this.model.left,this.model.left_units,i,t.xview,t.bbox.left),this.sright=e(this.model.right,this.model.right_units,i,t.xview,t.bbox.right),this.stop=e(this.model.top,this.model.top_units,s,t.yview,t.bbox.top),this.sbottom=e(this.model.bottom,this.model.bottom_units,s,t.yview,t.bbox.bottom),this._paint_box(this.sleft,this.sright,this.sbottom,this.stop)}_paint_box(t,i,s,e){const{ctx:o}=this.layer;o.save(),o.beginPath(),o.rect(t,e,i-t,s-e),this.visuals.fill.doit&&(this.visuals.fill.set_value(o),o.fill()),this.visuals.line.doit&&(this.visuals.line.set_value(o),o.stroke()),o.restore()}interactive_bbox(){const t=this.model.properties.line_width.value()+s.EDGE_TOLERANCE;return new h.BBox({x0:this.sleft-t,y0:this.stop-t,x1:this.sright+t,y1:this.sbottom+t})}interactive_hit(t,i){if(null==this.model.in_cursor)return!1;return this.interactive_bbox().contains(t,i)}cursor(t,i){return Math.abs(t-this.sleft)<3||Math.abs(t-this.sright)<3?this.model.ew_cursor:Math.abs(i-this.sbottom)<3||Math.abs(i-this.stop)<3?this.model.ns_cursor:t>this.sleft&&tthis.stop&&ithis.plot_view.request_render()),this.connect(this.model.formatter.change,()=>this.plot_view.request_render()),null!=this.model.color_mapper&&this.connect(this.model.color_mapper.change,()=>{this._set_canvas_image(),this.plot_view.request_render()})}_get_size(){if(null==this.model.color_mapper)return{width:0,height:0};{const{width:t,height:e}=this.compute_legend_dimensions();return{width:t,height:e}}}_set_canvas_image(){if(null==this.model.color_mapper)return;let t,e,{palette:i}=this.model.color_mapper;switch(\"vertical\"==this.model.orientation&&(i=g.reversed(i)),this.model.orientation){case\"vertical\":[t,e]=[1,i.length];break;case\"horizontal\":[t,e]=[i.length,1]}const o=document.createElement(\"canvas\");o.width=t,o.height=e;const a=o.getContext(\"2d\"),s=a.getImageData(0,0,t,e),r=new n.LinearColorMapper({palette:i}).rgba_mapper.v_compute(g.range(0,i.length));s.data.set(r),a.putImageData(s,0,0),this.image=o}compute_legend_dimensions(){const t=this._computed_image_dimensions(),[e,i]=[t.height,t.width],o=this._get_label_extent(),a=this._title_extent(),s=this._tick_extent(),{padding:r}=this.model;let n,l;switch(this.model.orientation){case\"vertical\":n=e+a+2*r,l=i+s+o+2*r;break;case\"horizontal\":n=e+a+s+o+2*r,l=i+2*r}return{width:l,height:n}}compute_legend_location(){const t=this.compute_legend_dimensions(),[e,i]=[t.height,t.width],o=this.model.margin,a=null!=this.panel?this.panel:this.plot_view.frame,[s,r]=a.bbox.ranges,{location:n}=this.model;let l,_;if(f.isString(n))switch(n){case\"top_left\":l=s.start+o,_=r.start+o;break;case\"top_center\":l=(s.end+s.start)/2-i/2,_=r.start+o;break;case\"top_right\":l=s.end-o-i,_=r.start+o;break;case\"bottom_right\":l=s.end-o-i,_=r.end-o-e;break;case\"bottom_center\":l=(s.end+s.start)/2-i/2,_=r.end-o-e;break;case\"bottom_left\":l=s.start+o,_=r.end-o-e;break;case\"center_left\":l=s.start+o,_=(r.end+r.start)/2-e/2;break;case\"center\":l=(s.end+s.start)/2-i/2,_=(r.end+r.start)/2-e/2;break;case\"center_right\":l=s.end-o-i,_=(r.end+r.start)/2-e/2}else if(f.isArray(n)&&2==n.length){const[t,i]=n;l=a.xview.compute(t),_=a.yview.compute(i)-e}else b.unreachable();return{sx:l,sy:_}}_render(){if(null==this.model.color_mapper)return;const{ctx:t}=this.layer;t.save();const{sx:e,sy:i}=this.compute_legend_location();t.translate(e,i),this._draw_bbox(t);const o=this._get_image_offset();t.translate(o.x,o.y),this._draw_image(t);const a=this.tick_info();this._draw_major_ticks(t,a),this._draw_minor_ticks(t,a),this._draw_major_labels(t,a),this.model.title&&this._draw_title(t),t.restore()}_draw_bbox(t){const e=this.compute_legend_dimensions();t.save(),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(t),t.fillRect(0,0,e.width,e.height)),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(t),t.strokeRect(0,0,e.width,e.height)),t.restore()}_draw_image(t){const e=this._computed_image_dimensions();t.save(),t.setImageSmoothingEnabled(!1),t.globalAlpha=this.model.scale_alpha,t.drawImage(this.image,0,0,e.width,e.height),this.visuals.bar_line.doit&&(this.visuals.bar_line.set_value(t),t.strokeRect(0,0,e.width,e.height)),t.restore()}_draw_major_ticks(t,e){if(!this.visuals.major_tick_line.doit)return;const[i,o]=this._normals(),a=this._computed_image_dimensions(),[s,r]=[a.width*i,a.height*o],[n,l]=e.coords.major,_=this.model.major_tick_in,h=this.model.major_tick_out;t.save(),t.translate(s,r),this.visuals.major_tick_line.set_value(t);for(let e=0,a=n.length;ei.measureText(t.toString()).width));break;case\"horizontal\":e=u.measure_font(this.visuals.major_label_text.font_value()).height}e+=this.model.label_standoff,i.restore()}return e}_get_image_offset(){return{x:this.model.padding,y:this.model.padding+this._title_extent()}}_normals(){return\"vertical\"==this.model.orientation?[1,0]:[0,1]}_title_extent(){const t=this.model.title_text_font+\" \"+this.model.title_text_font_size+\" \"+this.model.title_text_font_style;return this.model.title?u.measure_font(t).height+this.model.title_standoff:0}_tick_extent(){return g.max([this.model.major_tick_out,this.model.minor_tick_out])}_computed_image_dimensions(){const t=this.plot_view.frame.bbox.height,e=this.plot_view.frame.bbox.width,i=this._title_extent();let o,a;switch(this.model.orientation){case\"vertical\":\"auto\"==this.model.height?null!=this.panel?o=t-2*this.model.padding-i:(o=g.max([25*this.model.color_mapper.palette.length,.3*t]),o=g.min([o,.8*t-2*this.model.padding-i])):o=this.model.height,a=\"auto\"==this.model.width?25:this.model.width;break;case\"horizontal\":o=\"auto\"==this.model.height?25:this.model.height,\"auto\"==this.model.width?null!=this.panel?a=e-2*this.model.padding:(a=g.max([25*this.model.color_mapper.palette.length,.3*e]),a=g.min([a,.8*e-2*this.model.padding])):a=this.model.width}return{width:a,height:o}}_tick_coordinate_scale(t){const e={source_range:new m.Range1d({start:this.model.color_mapper.metrics.min,end:this.model.color_mapper.metrics.max}),target_range:new m.Range1d({start:0,end:t})},{color_mapper:i}=this.model;if(i instanceof n.LinearColorMapper)return new l.LinearScale(e);if(i instanceof n.LogColorMapper)return new h.LogScale(e);if(i instanceof n.ScanningColorMapper){const{binning:t}=i.metrics;return new _.LinearInterpolationScale(Object.assign(Object.assign({},e),{binning:t}))}b.unreachable()}_format_major_labels(t,e){const i=this.model.formatter.doFormat(t,null);for(let t=0,o=e.length;tr||(h[o].push(l[t]),h[a].push(0));for(let t=0,e=_.length;tr||(m[o].push(_[t]),m[a].push(0));const d={major:this._format_major_labels(h[o],l)},c={major:[[],[]],minor:[[],[]]};return c.major[o]=i.v_compute(h[o]),c.minor[o]=i.v_compute(m[o]),c.major[a]=h[a],c.minor[a]=m[a],\"vertical\"==this.model.orientation&&(c.major[o]=p.map(c.major[o],t=>e-t),c.minor[o]=p.map(c.minor[o],t=>e-t)),{coords:c,labels:d}}}i.ColorBarView=v,v.__name__=\"ColorBarView\";class w extends a.Annotation{constructor(t){super(t)}static init_ColorBar(){this.prototype.default_view=v,this.mixins([[\"major_label_\",d.Text],[\"title_\",d.Text],[\"major_tick_\",d.Line],[\"minor_tick_\",d.Line],[\"border_\",d.Line],[\"bar_\",d.Line],[\"background_\",d.Fill]]),this.define({location:[c.Any,\"top_right\"],orientation:[c.Orientation,\"vertical\"],title:[c.String],title_standoff:[c.Number,2],width:[c.Any,\"auto\"],height:[c.Any,\"auto\"],scale_alpha:[c.Number,1],ticker:[c.Instance,()=>new s.BasicTicker],formatter:[c.Instance,()=>new r.BasicTickFormatter],major_label_overrides:[c.Any,{}],color_mapper:[c.Instance],label_standoff:[c.Number,5],margin:[c.Number,30],padding:[c.Number,10],major_tick_in:[c.Number,5],major_tick_out:[c.Number,0],minor_tick_in:[c.Number,0],minor_tick_out:[c.Number,0]}),this.override({background_fill_color:\"#ffffff\",background_fill_alpha:.95,bar_line_color:null,border_line_color:null,major_label_text_align:\"center\",major_label_text_baseline:\"middle\",major_label_text_font_size:\"11px\",major_tick_line_color:\"#ffffff\",minor_tick_line_color:null,title_text_font_size:\"13px\",title_text_font_style:\"italic\"})}}i.ColorBar=w,w.__name__=\"ColorBar\",w.init_ColorBar()},\n", - " function _(e,c,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=e(127);class r extends i.AdaptiveTicker{constructor(e){super(e)}}s.BasicTicker=r,r.__name__=\"BasicTicker\"},\n", - " function _(t,i,e){Object.defineProperty(e,\"__esModule\",{value:!0});const a=t(1),s=t(128),n=t(9),r=a.__importStar(t(18));class _ extends s.ContinuousTicker{constructor(t){super(t)}static init_AdaptiveTicker(){this.define({base:[r.Number,10],mantissas:[r.Array,[1,2,5]],min_interval:[r.Number,0],max_interval:[r.Number]})}initialize(){super.initialize();const t=n.nth(this.mantissas,-1)/this.base,i=n.nth(this.mantissas,0)*this.base;this.extended_mantissas=[t,...this.mantissas,i],this.base_factor=0===this.get_min_interval()?1:this.get_min_interval()}get_interval(t,i,e){const a=i-t,s=this.get_ideal_interval(t,i,e),r=Math.floor(function(t,i=Math.E){return Math.log(t)/Math.log(i)}(s/this.base_factor,this.base)),_=this.base**r*this.base_factor,h=this.extended_mantissas,m=h.map(t=>Math.abs(e-a/(t*_))),o=h[n.argmin(m)];return c=o*_,l=this.get_min_interval(),u=this.get_max_interval(),Math.max(l,Math.min(u,c));var c,l,u}}e.AdaptiveTicker=_,_.__name__=\"AdaptiveTicker\",_.init_AdaptiveTicker()},\n", - " function _(t,i,e){Object.defineProperty(e,\"__esModule\",{value:!0});const n=t(1),r=t(129),s=n.__importStar(t(18)),o=t(9);class _ extends r.Ticker{constructor(t){super(t)}static init_ContinuousTicker(){this.define({num_minor_ticks:[s.Number,5],desired_num_ticks:[s.Number,6]})}get_ticks(t,i,e,n,r){return this.get_ticks_no_defaults(t,i,n,this.desired_num_ticks)}get_ticks_no_defaults(t,i,e,n){const r=this.get_interval(t,i,n),s=Math.floor(t/r),_=Math.ceil(i/r);let c;c=isFinite(s)&&isFinite(_)?o.range(s,_+1):[];const u=c.map(t=>t*r).filter(e=>t<=e&&e<=i),a=this.num_minor_ticks,l=[];if(a>0&&u.length>0){const e=r/a,n=o.range(0,a).map(t=>t*e);for(const e of n.slice(1)){const n=u[0]-e;t<=n&&n<=i&&l.push(n)}for(const e of u)for(const r of n){const n=e+r;t<=n&&n<=i&&l.push(n)}}return{major:u,minor:l}}get_min_interval(){return this.min_interval}get_max_interval(){return null!=this.max_interval?this.max_interval:1/0}get_ideal_interval(t,i,e){return(i-t)/e}}e.ContinuousTicker=_,_.__name__=\"ContinuousTicker\",_.init_ContinuousTicker()},\n", - " function _(e,c,n){Object.defineProperty(n,\"__esModule\",{value:!0});const o=e(81);class r extends o.Model{constructor(e){super(e)}}n.Ticker=r,r.__name__=\"Ticker\"},\n", - " function _(i,t,e){Object.defineProperty(e,\"__esModule\",{value:!0});const r=i(1),s=i(131),n=r.__importStar(i(18));class o extends s.TickFormatter{constructor(i){super(i),this.last_precision=3}static init_BasicTickFormatter(){this.define({precision:[n.Any,\"auto\"],use_scientific:[n.Boolean,!0],power_limit_high:[n.Number,5],power_limit_low:[n.Number,-3]})}get scientific_limit_low(){return 10**this.power_limit_low}get scientific_limit_high(){return 10**this.power_limit_high}_need_sci(i){if(!this.use_scientific)return!1;const{scientific_limit_high:t}=this,{scientific_limit_low:e}=this,r=i.length<2?0:Math.abs(i[1]-i[0])/1e4;for(const s of i){const i=Math.abs(s);if(!(i<=r)&&(i>=t||i<=e))return!0}return!1}_format_with_precision(i,t,e){const r=new Array(i.length);if(t)for(let t=0,s=i.length;t=1;r?s++:s--){if(t){e[0]=i[0].toExponential(s);for(let t=1;tu(e,d))),s=g<0||g>=t.length?r:t[g],c[_]=s}}},\n", - " function _(t,e,r){Object.defineProperty(r,\"__esModule\",{value:!0});const n=t(1),o=t(136),_=n.__importStar(t(18)),i=t(8),l=t(22),c=t(32);function a(t){return i.isNumber(t)?t:(\"#\"!=t[0]&&(t=l.color2hex(t)),9!=t.length&&(t+=\"ff\"),parseInt(t.slice(1),16))}function s(t){const e=new Uint32Array(t.length);for(let r=0,n=t.length;rt)),e}get rgba_mapper(){const t=this,e=s(this.palette),r=this._colors(a);return{v_compute(n){const o=new Uint32Array(n.length);return t._v_compute(n,o,e,r),p(o)}}}_colors(t){return{nan_color:t(this.nan_color)}}}r.ColorMapper=u,u.__name__=\"ColorMapper\",u.init_ColorMapper()},\n", - " function _(e,r,n){Object.defineProperty(n,\"__esModule\",{value:!0});const o=e(137);class s extends o.Transform{constructor(e){super(e)}compute(e){throw new Error(\"mapping single values is not supported\")}}n.Mapper=s,s.__name__=\"Mapper\"},\n", - " function _(e,n,o){Object.defineProperty(o,\"__esModule\",{value:!0});const r=e(81);class s extends r.Model{constructor(e){super(e)}}o.Transform=s,s.__name__=\"Transform\"},\n", - " function _(r,e,a){Object.defineProperty(a,\"__esModule\",{value:!0});const t=r(1),s=r(134),i=r(136),c=t.__importStar(r(18));class n extends i.Mapper{constructor(r){super(r)}static init_CategoricalMarkerMapper(){this.define({factors:[c.Array],markers:[c.Array],start:[c.Number,0],end:[c.Number],default_value:[c.MarkerType,\"circle\"]})}v_compute(r){const e=new Array(r.length);return s.cat_v_compute(r,this.factors,this.markers,e,this.start,this.end,this.default_value),e}}a.CategoricalMarkerMapper=n,n.__name__=\"CategoricalMarkerMapper\",n.init_CategoricalMarkerMapper()},\n", - " function _(t,e,a){Object.defineProperty(a,\"__esModule\",{value:!0});const r=t(1),n=t(134),s=t(136),i=r.__importStar(t(18));class c extends s.Mapper{constructor(t){super(t)}static init_CategoricalPatternMapper(){this.define({factors:[i.Array],patterns:[i.Array],start:[i.Number,0],end:[i.Number],default_value:[i.HatchPatternType,\" \"]})}v_compute(t){const e=new Array(t.length);return n.cat_v_compute(t,this.factors,this.patterns,e,this.start,this.end,this.default_value),e}}a.CategoricalPatternMapper=c,c.__name__=\"CategoricalPatternMapper\",c.init_CategoricalPatternMapper()},\n", - " function _(t,o,e){Object.defineProperty(e,\"__esModule\",{value:!0});const n=t(135),s=t(90),l=t(9),i=t(8);class c extends n.ColorMapper{constructor(t){super(t),this._scan_data=null}static init_ContinuousColorMapper(){this.define(({Number:t,String:o,Null:e,Ref:n,Color:l,Or:i,Tuple:c,Array:a})=>({high:[i(t,e),null],low:[i(t,e),null],high_color:[i(l,e),null],low_color:[i(l,e),null],domain:[a(c(n(s.GlyphRenderer),i(o,a(o)))),[]]}))}connect_signals(){super.connect_signals();const t=()=>{for(const[t]of this.domain)this.connect(t.view.change,()=>this.update_data()),this.connect(t.data_source.selected.change,()=>this.update_data())};this.connect(this.properties.domain.change,()=>t()),t()}update_data(){const{domain:t,palette:o}=this,e=[...this._collect(t)];this._scan_data=this.scan(e,o.length),this.change.emit()}get metrics(){return null==this._scan_data&&this.update_data(),this._scan_data}*_collect(t){for(const[o,e]of t)for(const t of i.isArray(e)?e:[e]){let e=o.data_source.get_column(t);e=o.view.indices.select(e);const n=o.view.masked,s=o.data_source.selected.indices;let c;if(null!=n&&s.length>0?c=l.intersection([...n],s):null!=n?c=[...n]:s.length>0&&(c=s),null!=c&&(e=l.map(c,t=>e[t])),e.length>0&&!i.isNumber(e[0]))for(const t of e)yield*t;else yield*e}}_v_compute(t,o,e,n){const{nan_color:s}=n;let{low_color:i,high_color:c}=n;null==i&&(i=e[0]),null==c&&(c=e[e.length-1]);const{domain:a}=this,r=l.is_empty(a)?t:[...this._collect(a)];this._scan_data=this.scan(r,e.length);for(let n=0,l=t.length;na?e:r[l]}}o.LinearColorMapper=a,a.__name__=\"LinearColorMapper\"},\n", - " function _(o,t,n){Object.defineProperty(n,\"__esModule\",{value:!0});const e=o(140),r=o(12);class l extends e.ContinuousColorMapper{constructor(o){super(o)}scan(o,t){const n=null!=this.low?this.low:r.min(o),e=null!=this.high?this.high:r.max(o);return{max:e,min:n,scale:t/(Math.log(e)-Math.log(n))}}cmap(o,t,n,e,r){const l=t.length-1;if(o>r.max)return e;if(o==r.max)return t[l];if(ol&&(s=l),t[s]}}n.LogColorMapper=l,l.__name__=\"LogColorMapper\"},\n", - " function _(n,e,r){Object.defineProperty(r,\"__esModule\",{value:!0});const i=n(140),o=n(12);class t extends i.ContinuousColorMapper{constructor(n){super(n)}cmap(n,e,r,i,t){if(nt.binning[t.binning.length-1])return i;return e[o.left_edge_index(n,t.binning)]}}r.ScanningColorMapper=t,t.__name__=\"ScanningColorMapper\"},\n", - " function _(n,t,e){Object.defineProperty(e,\"__esModule\",{value:!0});const i=n(1),o=n(143),r=n(12),s=n(9),a=i.__importStar(n(18)),l=n(19);class p extends o.ScanningColorMapper{constructor(n){super(n)}static init_EqHistColorMapper(){this.define({bins:[a.Int,65536]})}scan(n,t){const e=null!=this.low?this.low:r.min(n),i=null!=this.high?this.high:r.max(n),o=this.bins,a=s.linspace(e,i,o+1),p=r.bin_counts(n,a),c=new Array(o);for(let n=0,t=a.length;nn/u);let m=t-1,_=[],M=0,f=2*t;for(;m!=t&&M<4&&0!=m;){const n=f/m;if(n>1e3)break;f=Math.round(Math.max(t*n,t));const e=s.range(0,f),i=r.map(g,n=>n*(f-1));_=r.interpolate(e,i,c);m=s.uniq(_).length-1,M++}if(0==m){_=[e,i];for(let n=0;nthis._sorted_dirty=!0)}v_compute(t){const e=new i.NumberArray(t.length);for(let r=0;rs*(e[t]-e[r])),this._x_sorted=new i.NumberArray(n),this._y_sorted=new i.NumberArray(n);for(let t=0;tthis._x_sorted[this._x_sorted.length-1])return NaN}else{if(tthis._x_sorted[this._x_sorted.length-1])return this._y_sorted[this._y_sorted.length-1]}if(t==this._x_sorted[0])return this._y_sorted[0];const s=_.find_last_index(this._x_sorted,s=>sthis._x_sorted[this._x_sorted.length-1])return NaN}else{if(tthis._x_sorted[this._x_sorted.length-1])return this._y_sorted[this._y_sorted.length-1]}let e;switch(this.mode){case\"after\":e=i.find_last_index(this._x_sorted,e=>t>=e);break;case\"before\":e=i.find_index(this._x_sorted,e=>t<=e);break;case\"center\":{const r=this._x_sorted.map(e=>Math.abs(e-t)),s=i.min(r);e=i.find_index(r,t=>s===t);break}default:throw new Error(\"unknown mode: \"+this.mode)}return-1!=e?this._y_sorted[e]:NaN}}r.StepInterpolator=n,n.__name__=\"StepInterpolator\",n.init_StepInterpolator()},\n", - " function _(e,t,n){Object.defineProperty(n,\"__esModule\",{value:!0});const r=e(1),a=e(147),i=e(24),s=e(9),o=e(12),c=r.__importStar(e(18));class _ extends a.Scale{constructor(e){super(e)}static init_LinearInterpolationScale(){this.internal({binning:[c.Array]})}compute(e){return e}v_compute(e){const t=o.norm(e,this.source_range.start,this.source_range.end),n=s.linspace(0,1,this.binning.length),r=o.interpolate(t,n,this.binning),a=o.norm(r,this.source_range.start,this.source_range.end),c=this.target_range.end-this.target_range.start,_=o.map(a,e=>this.target_range.start+e*c);return new i.NumberArray(_)}invert(e){return e}v_invert(e){return new i.NumberArray(e)}}n.LinearInterpolationScale=_,_.__name__=\"LinearInterpolationScale\",_.init_LinearInterpolationScale()},\n", - " function _(t,e,o){Object.defineProperty(o,\"__esModule\",{value:!0});const a=t(146),r=t(24);class s extends a.ContinuousScale{constructor(t){super(t)}compute(t){const[e,o,a,r]=this._compute_state();let s;if(0==a)s=0;else{const n=(Math.log(t)-r)/a;s=isFinite(n)?n*e+o:NaN}return s}v_compute(t){const[e,o,a,s]=this._compute_state(),n=new r.NumberArray(t.length);if(0==a)for(let e=0;ethis.render()):this.connect(this.model.change,()=>this.plot_view.request_render())}render(){this.model.visible||\"css\"!=this.model.render_mode||a.undisplay(this.el),super.render()}_calculate_text_dimensions(e,t){const{width:s}=e.measureText(t),{height:i}=o.measure_font(this.visuals.text.font_value());return[s,i]}_calculate_bounding_box_dimensions(e,t){const[s,i]=this._calculate_text_dimensions(e,t);let l,a;switch(e.textAlign){case\"left\":l=0;break;case\"center\":l=-s/2;break;case\"right\":l=-s;break;default:r.unreachable()}switch(e.textBaseline){case\"top\":a=0;break;case\"middle\":a=-.5*i;break;case\"bottom\":a=-1*i;break;case\"alphabetic\":a=-.8*i;break;case\"hanging\":a=-.17*i;break;case\"ideographic\":a=-.83*i;break;default:r.unreachable()}return[l,a,s,i]}_canvas_text(e,t,s,i,l){this.visuals.text.set_value(e);const a=this._calculate_bounding_box_dimensions(e,t);e.save(),e.beginPath(),e.translate(s,i),l&&e.rotate(l),e.rect(a[0],a[1],a[2],a[3]),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(e),e.fill()),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(e),e.stroke()),this.visuals.text.doit&&(this.visuals.text.set_value(e),e.fillText(t,0,0)),e.restore()}_css_text(e,t,s,i,l){const{el:n}=this;r.assert(null!=n),a.undisplay(n),this.visuals.text.set_value(e);const o=this._calculate_bounding_box_dimensions(e,t),_=this.visuals.border_line.line_dash.value().length<2?\"solid\":\"dashed\";this.visuals.border_line.set_value(e),this.visuals.background_fill.set_value(e),n.style.position=\"absolute\",n.style.left=s+o[0]+\"px\",n.style.top=i+o[1]+\"px\",n.style.color=\"\"+this.visuals.text.text_color.value(),n.style.opacity=\"\"+this.visuals.text.text_alpha.value(),n.style.font=\"\"+this.visuals.text.font_value(),n.style.lineHeight=\"normal\",l&&(n.style.transform=`rotate(${l}rad)`),this.visuals.background_fill.doit&&(n.style.backgroundColor=\"\"+this.visuals.background_fill.color_value()),this.visuals.border_line.doit&&(n.style.borderStyle=\"\"+_,n.style.borderWidth=this.visuals.border_line.line_width.value()+\"px\",n.style.borderColor=\"\"+this.visuals.border_line.color_value()),n.textContent=t,a.display(n)}}s.TextAnnotationView=_,_.__name__=\"TextAnnotationView\";class u extends l.Annotation{constructor(e){super(e)}static init_TextAnnotation(){this.define({render_mode:[n.RenderMode,\"canvas\"]})}}s.TextAnnotation=u,u.__name__=\"TextAnnotation\",u.init_TextAnnotation()},\n", - " function _(t,e,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=t(1),o=t(161),l=t(85),a=i.__importStar(t(28)),n=t(72),r=i.__importStar(t(18));class _ extends o.TextAnnotationView{initialize(){if(super.initialize(),this.set_data(this.model.source),\"css\"==this.model.render_mode)for(let t=0,e=this._text.length;t{this.set_data(this.model.source),this.render()}),this.connect(this.model.source.streaming,()=>{this.set_data(this.model.source),this.render()}),this.connect(this.model.source.patching,()=>{this.set_data(this.model.source),this.render()}),this.connect(this.model.source.change,()=>{this.set_data(this.model.source),this.render()})):(this.connect(this.model.change,()=>{this.set_data(this.model.source),this.plot_view.request_render()}),this.connect(this.model.source.streaming,()=>{this.set_data(this.model.source),this.plot_view.request_render()}),this.connect(this.model.source.patching,()=>{this.set_data(this.model.source),this.plot_view.request_render()}),this.connect(this.model.source.change,()=>{this.set_data(this.model.source),this.plot_view.request_render()}))}set_data(t){super.set_data(t),this.visuals.warm_cache(t)}_map_data(){const t=this.coordinates.x_scale,e=this.coordinates.y_scale,s=null!=this.panel?this.panel:this.plot_view.frame;return[\"data\"==this.model.x_units?t.v_compute(this._x):s.xview.v_compute(this._x),\"data\"==this.model.y_units?e.v_compute(this._y):s.yview.v_compute(this._y)]}_render(){const t=\"canvas\"==this.model.render_mode?this._v_canvas_text.bind(this):this._v_css_text.bind(this),{ctx:e}=this.layer,[s,i]=this._map_data();for(let o=0,l=this._text.length;onew l.ColumnDataSource]}),this.override({background_fill_color:null,border_line_color:null})}}s.LabelSet=h,h.__name__=\"LabelSet\",h.init_LabelSet()},\n", - " function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=t(1),l=t(36),n=s.__importStar(t(28)),h=s.__importStar(t(18)),a=t(15),_=t(159),o=t(79),r=t(9),d=t(8),c=t(11);class g extends l.AnnotationView{cursor(t,e){return\"none\"==this.model.click_policy?null:\"pointer\"}get legend_padding(){return null!=this.visuals.border_line.line_color.value()?this.model.padding:0}connect_signals(){super.connect_signals(),this.connect(this.model.change,()=>this.plot_view.request_render()),this.connect(this.model.item_change,()=>this.plot_view.request_render())}compute_legend_bbox(){const t=this.model.get_legend_names(),{glyph_height:e,glyph_width:i}=this.model,{label_height:s,label_width:l}=this.model;this.max_label_height=r.max([_.measure_font(this.visuals.label_text.font_value()).height,s,e]);const{ctx:n}=this.layer;n.save(),this.visuals.label_text.set_value(n),this.text_widths=new Map;for(const e of t)this.text_widths.set(e,r.max([n.measureText(e).width,l]));this.visuals.title_text.set_value(n),this.title_height=this.model.title?_.measure_font(this.visuals.title_text.font_value()).height+this.model.title_standoff:0,this.title_width=this.model.title?n.measureText(this.model.title).width:0,n.restore();const h=Math.max(r.max([...this.text_widths.values()]),0),a=this.model.margin,{legend_padding:g}=this,m=this.model.spacing,{label_standoff:b}=this.model;let u,f;if(\"vertical\"==this.model.orientation)u=t.length*this.max_label_height+Math.max(t.length-1,0)*m+2*g+this.title_height,f=r.max([h+i+b+2*g,this.title_width+2*g]);else{let e=2*g+Math.max(t.length-1,0)*m;for(const[,t]of this.text_widths)e+=r.max([t,l])+i+b;f=r.max([this.title_width+2*g,e]),u=this.max_label_height+this.title_height+2*g}const x=null!=this.panel?this.panel:this.plot_view.frame,[p,w]=x.bbox.ranges,{location:v}=this.model;let y,k;if(d.isString(v))switch(v){case\"top_left\":y=p.start+a,k=w.start+a;break;case\"top_center\":y=(p.end+p.start)/2-f/2,k=w.start+a;break;case\"top_right\":y=p.end-a-f,k=w.start+a;break;case\"bottom_right\":y=p.end-a-f,k=w.end-a-u;break;case\"bottom_center\":y=(p.end+p.start)/2-f/2,k=w.end-a-u;break;case\"bottom_left\":y=p.start+a,k=w.end-a-u;break;case\"center_left\":y=p.start+a,k=(w.end+w.start)/2-u/2;break;case\"center\":y=(p.end+p.start)/2-f/2,k=(w.end+w.start)/2-u/2;break;case\"center_right\":y=p.end-a-f,k=(w.end+w.start)/2-u/2}else if(d.isArray(v)&&2==v.length){const[t,e]=v;y=x.xview.compute(t),k=x.yview.compute(e)-u}else c.unreachable();return new o.BBox({left:y,top:k,width:f,height:u})}interactive_bbox(){return this.compute_legend_bbox()}interactive_hit(t,e){return this.interactive_bbox().contains(t,e)}on_hit(t,e){let i;const{glyph_width:s}=this.model,{legend_padding:l}=this,n=this.model.spacing,{label_standoff:h}=this.model;let a=i=l;const _=this.compute_legend_bbox(),r=\"vertical\"==this.model.orientation;for(const d of this.model.items){const c=d.get_labels_list_from_label_prop();for(const g of c){const c=_.x+a,m=_.y+i+this.title_height;let b,u;[b,u]=r?[_.width-2*l,this.max_label_height]:[this.text_widths.get(g)+s+h,this.max_label_height];if(new o.BBox({left:c,top:m,width:b,height:u}).contains(t,e)){switch(this.model.click_policy){case\"hide\":for(const t of d.renderers)t.visible=!t.visible;break;case\"mute\":for(const t of d.renderers)t.muted=!t.muted}return!0}r?i+=this.max_label_height+n:a+=this.text_widths.get(g)+s+h+n}}return!1}_render(){if(0==this.model.items.length)return;for(const t of this.model.items)t.legend=this.model;const{ctx:t}=this.layer,e=this.compute_legend_bbox();t.save(),this._draw_legend_box(t,e),this._draw_legend_items(t,e),this.model.title&&this._draw_title(t,e),t.restore()}_draw_legend_box(t,e){t.beginPath(),t.rect(e.x,e.y,e.width,e.height),this.visuals.background_fill.set_value(t),t.fill(),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(t),t.stroke())}_draw_legend_items(t,e){const{glyph_width:i,glyph_height:s}=this.model,{legend_padding:l}=this,n=this.model.spacing,{label_standoff:h}=this.model;let a=l,_=l;const o=\"vertical\"==this.model.orientation;for(const d of this.model.items){const c=d.get_labels_list_from_label_prop(),g=d.get_field_from_label_prop();if(0==c.length)continue;const m=(()=>{switch(this.model.click_policy){case\"none\":return!0;case\"hide\":return r.every(d.renderers,t=>t.visible);case\"mute\":return r.every(d.renderers,t=>!t.muted)}})();for(const r of c){const c=e.x+a,b=e.y+_+this.title_height,u=c+i,f=b+s;o?_+=this.max_label_height+n:a+=this.text_widths.get(r)+i+h+n,this.visuals.label_text.set_value(t),t.fillText(r,u+h,b+this.max_label_height/2);for(const e of d.renderers){this.plot_view.renderer_views.get(e).draw_legend(t,c,u,b,f,g,r,d.index)}if(!m){let s,n;[s,n]=o?[e.width-2*l,this.max_label_height]:[this.text_widths.get(r)+i+h,this.max_label_height],t.beginPath(),t.rect(c,b,s,n),this.visuals.inactive_fill.set_value(t),t.fill()}}}}_draw_title(t,e){this.visuals.title_text.doit&&(t.save(),t.translate(e.x0,e.y0+this.title_height),this.visuals.title_text.set_value(t),t.fillText(this.model.title,this.legend_padding,this.legend_padding-this.model.title_standoff),t.restore())}_get_size(){const{width:t,height:e}=this.compute_legend_bbox();return{width:t+2*this.model.margin,height:e+2*this.model.margin}}}i.LegendView=g,g.__name__=\"LegendView\";class m extends l.Annotation{constructor(t){super(t)}initialize(){super.initialize(),this.item_change=new a.Signal0(this,\"item_change\")}static init_Legend(){this.prototype.default_view=g,this.mixins([[\"label_\",n.Text],[\"title_\",n.Text],[\"inactive_\",n.Fill],[\"border_\",n.Line],[\"background_\",n.Fill]]),this.define({orientation:[h.Orientation,\"vertical\"],location:[h.Any,\"top_right\"],title:[h.String],title_standoff:[h.Number,5],label_standoff:[h.Number,5],glyph_height:[h.Number,20],glyph_width:[h.Number,20],label_height:[h.Number,20],label_width:[h.Number,20],margin:[h.Number,10],padding:[h.Number,10],spacing:[h.Number,3],items:[h.Array,[]],click_policy:[h.Any,\"none\"]}),this.override({border_line_color:\"#e5e5e5\",border_line_alpha:.5,border_line_width:1,background_fill_color:\"#ffffff\",background_fill_alpha:.95,inactive_fill_color:\"white\",inactive_fill_alpha:.7,label_text_font_size:\"13px\",label_text_baseline:\"middle\",title_text_font_size:\"13px\",title_text_font_style:\"italic\"})}get_legend_names(){const t=[];for(const e of this.items){const i=e.get_labels_list_from_label_prop();t.push(...i)}return t}}i.Legend=m,m.__name__=\"Legend\",m.init_Legend()},\n", - " function _(e,r,n){Object.defineProperty(n,\"__esModule\",{value:!0});const t=e(1),l=e(81),i=e(86),s=e(165),o=t.__importStar(e(18)),_=e(19),a=e(9);class u extends l.Model{constructor(e){super(e)}static init_LegendItem(){this.define({label:[o.StringSpec,null],renderers:[o.Array,[]],index:[o.Number,null]})}_check_data_sources_on_renderers(){if(null!=this.get_field_from_label_prop()){if(this.renderers.length<1)return!1;const e=this.renderers[0].data_source;if(null!=e)for(const r of this.renderers)if(r.data_source!=e)return!1}return!0}_check_field_label_on_data_source(){const e=this.get_field_from_label_prop();if(null!=e){if(this.renderers.length<1)return!1;const r=this.renderers[0].data_source;if(null!=r&&!a.includes(r.columns(),e))return!1}return!0}initialize(){super.initialize(),this.legend=null,this.connect(this.change,()=>{var e;return null===(e=this.legend)||void 0===e?void 0:e.item_change.emit()});this._check_data_sources_on_renderers()||_.logger.error(\"Non matching data sources on legend item renderers\");this._check_field_label_on_data_source()||_.logger.error(\"Bad column name on label: \"+this.label)}get_field_from_label_prop(){const{label:e}=this;return s.isField(e)?e.field:null}get_labels_list_from_label_prop(){if(s.isValue(this.label)){const{value:e}=this.label;return null!=e?[e]:[]}const e=this.get_field_from_label_prop();if(null!=e){let r;if(!this.renderers[0]||null==this.renderers[0].data_source)return[\"No source found\"];if(r=this.renderers[0].data_source,r instanceof i.ColumnarDataSource){const n=r.get_column(e);return null!=n?a.uniq(Array.from(n)):[\"Invalid field\"]}}return[]}}n.LegendItem=u,u.__name__=\"LegendItem\",u.init_LegendItem()},\n", - " function _(e,i,n){Object.defineProperty(n,\"__esModule\",{value:!0});const t=e(8);n.isValue=function(e){return t.isPlainObject(e)&&\"value\"in e},n.isField=function(e){return t.isPlainObject(e)&&\"field\"in e}},\n", - " function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=t(1),s=t(36),o=n.__importStar(t(28)),l=t(15),a=n.__importStar(t(18));class r extends s.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,()=>this.plot_view.request_render()),this.connect(this.model.data_update,()=>this.plot_view.request_render())}_render(){const{xs:t,ys:e}=this.model;if(t.length!=e.length)return;if(t.length<3||e.length<3)return;const{frame:i}=this.plot_view,{ctx:n}=this.layer;for(let s=0,o=t.length;sthis.plot_view.request_render())}_render(){const e=this.model.gradient,t=this.model.y_intercept;if(null==e||null==t)return;const{frame:i}=this.plot_view,n=this.coordinates.x_scale,o=this.coordinates.y_scale,s=i.bbox.top,l=s+i.bbox.height,r=(o.invert(s)-t)/e,_=(o.invert(l)-t)/e,a=n.compute(r),c=n.compute(_),{ctx:p}=this.layer;p.save(),p.beginPath(),this.visuals.line.set_value(p),p.moveTo(a,s),p.lineTo(c,l),p.stroke(),p.restore()}}i.SlopeView=r,r.__name__=\"SlopeView\";class _ extends o.Annotation{constructor(e){super(e)}static init_Slope(){this.prototype.default_view=r,this.mixins(s.Line),this.define({gradient:[l.Number,null],y_intercept:[l.Number,null]}),this.override({line_color:\"black\"})}}i.Slope=_,_.__name__=\"Slope\",_.init_Slope()},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=e(1),o=e(36),s=n.__importStar(e(28)),a=n.__importStar(e(18));class l extends o.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,()=>this.plot_view.request_paint(this))}_render(){const{location:e}=this.model;if(null==e)return;const{frame:t}=this.plot_view,i=this.coordinates.x_scale,n=this.coordinates.y_scale,o=(t,i)=>\"data\"==this.model.location_units?t.compute(e):this.model.for_hover?e:i.compute(e);let s,a,l,r;\"width\"==this.model.dimension?(l=o(n,t.yview),a=t.bbox.left,r=t.bbox.width,s=this.model.properties.line_width.value()):(l=t.bbox.top,a=o(i,t.xview),r=this.model.properties.line_width.value(),s=t.bbox.height);const{ctx:_}=this.layer;_.save(),_.beginPath(),this.visuals.line.set_value(_),_.moveTo(a,l),\"width\"==this.model.dimension?_.lineTo(a+r,l):_.lineTo(a,l+s),_.stroke(),_.restore()}}i.SpanView=l,l.__name__=\"SpanView\";class r extends o.Annotation{constructor(e){super(e)}static init_Span(){this.prototype.default_view=l,this.mixins(s.Line),this.define({render_mode:[a.RenderMode,\"canvas\"],location:[a.Number,null],location_units:[a.SpatialUnits,\"data\"],dimension:[a.Dimension,\"width\"]}),this.override({line_color:\"black\"}),this.internal({for_hover:[a.Boolean,!1]})}}i.Span=r,r.__name__=\"Span\",r.init_Span()},\n", - " function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});const l=t(1),s=t(161),a=t(74),n=l.__importStar(t(28)),o=l.__importStar(t(18));class r extends s.TextAnnotationView{initialize(){super.initialize(),this.visuals.text=new a.Text(this.model)}_get_location(){const t=this.panel,e=this.model.offset;let i,l;const{bbox:s}=t;switch(t.side){case\"above\":case\"below\":switch(this.model.vertical_align){case\"top\":l=s.top+5;break;case\"middle\":l=s.vcenter;break;case\"bottom\":l=s.bottom-5}switch(this.model.align){case\"left\":i=s.left+e;break;case\"center\":i=s.hcenter;break;case\"right\":i=s.right-e}break;case\"left\":switch(this.model.vertical_align){case\"top\":i=s.left-5;break;case\"middle\":i=s.hcenter;break;case\"bottom\":i=s.right+5}switch(this.model.align){case\"left\":l=s.bottom-e;break;case\"center\":l=s.vcenter;break;case\"right\":l=s.top+e}break;case\"right\":switch(this.model.vertical_align){case\"top\":i=s.right-5;break;case\"middle\":i=s.hcenter;break;case\"bottom\":i=s.left+5}switch(this.model.align){case\"left\":l=s.top+e;break;case\"center\":l=s.vcenter;break;case\"right\":l=s.bottom-e}}return[i,l]}_render(){const{text:t}=this.model;if(null==t||0==t.length)return;this.model.text_baseline=this.model.vertical_align,this.model.text_align=this.model.align;const[e,i]=this._get_location(),l=this.panel.get_label_angle_heuristic(\"parallel\");(\"canvas\"==this.model.render_mode?this._canvas_text.bind(this):this._css_text.bind(this))(this.layer.ctx,t,e,i,l)}_get_size(){const{text:t}=this.model;if(null==t||0==t.length)return{width:0,height:0};{this.visuals.text.set_value(this.layer.ctx);const{width:e,ascent:i}=this.layer.ctx.measureText(t);return{width:e,height:i*this.visuals.text.text_line_height.value()+10}}}}i.TitleView=r,r.__name__=\"TitleView\";class c extends s.TextAnnotation{constructor(t){super(t)}static init_Title(){this.prototype.default_view=r,this.mixins([[\"border_\",n.Line],[\"background_\",n.Fill]]),this.define({text:[o.String],text_font:[o.Font,\"helvetica\"],text_font_size:[o.StringSpec,\"13px\"],text_font_style:[o.FontStyle,\"bold\"],text_color:[o.ColorSpec,\"#444444\"],text_alpha:[o.NumberSpec,1],text_line_height:[o.Number,1],vertical_align:[o.VerticalAlign,\"bottom\"],align:[o.TextAlign,\"left\"],offset:[o.Number,0]}),this.override({background_fill_color:null,border_line_color:null}),this.internal({text_align:[o.TextAlign,\"left\"],text_baseline:[o.TextBaseline,\"bottom\"]})}}i.Title=c,c.__name__=\"Title\",c.init_Title()},\n", - " function _(e,i,t){Object.defineProperty(t,\"__esModule\",{value:!0});const o=e(1),l=e(36),s=e(115),a=e(72),n=e(79),r=o.__importStar(e(18));class _ extends l.AnnotationView{constructor(){super(...arguments),this.rotate=!0,this._invalidate_toolbar=!0,this._previous_bbox=new n.BBox}initialize(){super.initialize(),this.el=a.div(),this.plot_view.canvas_view.add_event(this.el)}async lazy_initialize(){this._toolbar_view=await s.build_view(this.model.toolbar,{parent:this}),this.plot_view.visibility_callbacks.push(e=>this._toolbar_view.set_visibility(e))}remove(){this._toolbar_view.remove(),a.remove(this.el),super.remove()}render(){this.model.visible||a.undisplay(this.el),super.render()}_render(){const{bbox:e}=this.panel;this._previous_bbox.equals(e)||(a.position(this.el,e),this._previous_bbox=e),this._invalidate_toolbar&&(this.el.style.position=\"absolute\",this.el.style.overflow=\"hidden\",this._toolbar_view.render(),a.empty(this.el),this.el.appendChild(this._toolbar_view.el),this._invalidate_toolbar=!1),a.display(this.el)}_get_size(){const{tools:e,logo:i}=this.model.toolbar;return{width:30*e.length+(null!=i?25:0),height:30}}}t.ToolbarPanelView=_,_.__name__=\"ToolbarPanelView\";class h extends l.Annotation{constructor(e){super(e)}static init_ToolbarPanel(){this.prototype.default_view=_,this.define({toolbar:[r.Instance]})}}t.ToolbarPanel=h,h.__name__=\"ToolbarPanel\",h.init_ToolbarPanel()},\n", - " function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=t(1),l=t(36),o=t(72),n=s.__importStar(t(18)),a=t(172),h=t(173),r=s.__importDefault(t(174));class c extends l.AnnotationView{initialize(){super.initialize(),this.el=o.div({class:a.bk_tooltip}),o.undisplay(this.el),this.plot_view.canvas_view.add_overlay(this.el)}remove(){o.remove(this.el),super.remove()}connect_signals(){super.connect_signals(),this.connect(this.model.properties.content.change,()=>this.render()),this.connect(this.model.properties.position.change,()=>this._reposition())}styles(){return[...super.styles(),r.default]}render(){this.model.visible||o.undisplay(this.el),super.render()}_render(){const{content:t}=this.model;null!=t?(o.empty(this.el),o.classes(this.el).toggle(a.bk_tooltip_custom,this.model.custom),this.el.appendChild(t),this.model.show_arrow&&this.el.classList.add(a.bk_tooltip_arrow)):o.undisplay(this.el)}_reposition(){const{position:t}=this.model;if(null==t)return void o.undisplay(this.el);const[e,i]=t,s=(()=>{const t=this.parent.layout.bbox.relativize(),{attachment:s}=this.model;switch(s){case\"horizontal\":return eo.div()],custom:[n.Any]})}clear(){this.position=null}}i.Tooltip=d,d.__name__=\"Tooltip\",d.init_Tooltip()},\n", - " function _(o,t,l){Object.defineProperty(l,\"__esModule\",{value:!0}),l.bk_tooltip=\"bk-tooltip\",l.bk_tooltip_arrow=\"bk-tooltip-arrow\",l.bk_tooltip_custom=\"bk-tooltip-custom\",l.bk_tooltip_row_label=\"bk-tooltip-row-label\",l.bk_tooltip_row_value=\"bk-tooltip-row-value\",l.bk_tooltip_color_block=\"bk-tooltip-color-block\"},\n", - " function _(e,b,k){Object.defineProperty(k,\"__esModule\",{value:!0}),k.bk_active=\"bk-active\",k.bk_inline=\"bk-inline\",k.bk_left=\"bk-left\",k.bk_right=\"bk-right\",k.bk_above=\"bk-above\",k.bk_below=\"bk-below\",k.bk_up=\"bk-up\",k.bk_down=\"bk-down\",k.bk_side=function(e){switch(e){case\"above\":return k.bk_above;case\"below\":return k.bk_below;case\"left\":return k.bk_left;case\"right\":return k.bk_right}}},\n", - " function _(o,n,t){Object.defineProperty(t,\"__esModule\",{value:!0});t.default='\\n.bk-root {\\n /* Same border color used everywhere */\\n /* Gray of icons */\\n}\\n.bk-root .bk-tooltip {\\n font-weight: 300;\\n font-size: 12px;\\n position: absolute;\\n padding: 5px;\\n border: 1px solid #e5e5e5;\\n color: #2f2f2f;\\n background-color: white;\\n pointer-events: none;\\n opacity: 0.95;\\n z-index: 100;\\n}\\n.bk-root .bk-tooltip > div:not(:first-child) {\\n /* gives space when multiple elements are being hovered over */\\n margin-top: 5px;\\n border-top: #e5e5e5 1px dashed;\\n}\\n.bk-root .bk-tooltip.bk-left.bk-tooltip-arrow::before {\\n position: absolute;\\n margin: -7px 0 0 0;\\n top: 50%;\\n width: 0;\\n height: 0;\\n border-style: solid;\\n border-width: 7px 0 7px 0;\\n border-color: transparent;\\n content: \" \";\\n display: block;\\n left: -10px;\\n border-right-width: 10px;\\n border-right-color: #909599;\\n}\\n.bk-root .bk-tooltip.bk-left::before {\\n left: -10px;\\n border-right-width: 10px;\\n border-right-color: #909599;\\n}\\n.bk-root .bk-tooltip.bk-right.bk-tooltip-arrow::after {\\n position: absolute;\\n margin: -7px 0 0 0;\\n top: 50%;\\n width: 0;\\n height: 0;\\n border-style: solid;\\n border-width: 7px 0 7px 0;\\n border-color: transparent;\\n content: \" \";\\n display: block;\\n right: -10px;\\n border-left-width: 10px;\\n border-left-color: #909599;\\n}\\n.bk-root .bk-tooltip.bk-right::after {\\n right: -10px;\\n border-left-width: 10px;\\n border-left-color: #909599;\\n}\\n.bk-root .bk-tooltip.bk-above::before {\\n position: absolute;\\n margin: 0 0 0 -7px;\\n left: 50%;\\n width: 0;\\n height: 0;\\n border-style: solid;\\n border-width: 0 7px 0 7px;\\n border-color: transparent;\\n content: \" \";\\n display: block;\\n top: -10px;\\n border-bottom-width: 10px;\\n border-bottom-color: #909599;\\n}\\n.bk-root .bk-tooltip.bk-below::after {\\n position: absolute;\\n margin: 0 0 0 -7px;\\n left: 50%;\\n width: 0;\\n height: 0;\\n border-style: solid;\\n border-width: 0 7px 0 7px;\\n border-color: transparent;\\n content: \" \";\\n display: block;\\n bottom: -10px;\\n border-top-width: 10px;\\n border-top-color: #909599;\\n}\\n.bk-root .bk-tooltip-row-label {\\n text-align: right;\\n color: #26aae1;\\n /* blue from toolbar highlighting */\\n}\\n.bk-root .bk-tooltip-row-value {\\n color: default;\\n /* seems to be necessary for notebook */\\n}\\n.bk-root .bk-tooltip-color-block {\\n width: 12px;\\n height: 12px;\\n margin-left: 5px;\\n margin-right: 5px;\\n outline: #dddddd solid 1px;\\n display: inline-block;\\n}\\n'},\n", - " function _(e,s,t){Object.defineProperty(t,\"__esModule\",{value:!0});const i=e(1),r=e(123),o=e(84),h=e(28),n=i.__importStar(e(18));class l extends r.UpperLowerView{connect_signals(){super.connect_signals(),this.connect(this.model.source.streaming,()=>this.set_data(this.model.source)),this.connect(this.model.source.patching,()=>this.set_data(this.model.source)),this.connect(this.model.source.change,()=>this.set_data(this.model.source))}_render(){this._map_data();const{ctx:e}=this.layer;if(this.visuals.line.doit)for(let s=0,t=this._lower_sx.length;snew o.TeeHead({level:\"underlay\",size:10})],upper_head:[n.Instance,()=>new o.TeeHead({level:\"underlay\",size:10})]}),this.override({level:\"underlay\"})}}t.Whisker=_,_.__name__=\"Whisker\",_.init_Whisker()},\n", - " function _(i,a,e){Object.defineProperty(e,\"__esModule\",{value:!0});var r=i(177);e.Axis=r.Axis;var s=i(179);e.CategoricalAxis=s.CategoricalAxis;var x=i(182);e.ContinuousAxis=x.ContinuousAxis;var A=i(183);e.DatetimeAxis=A.DatetimeAxis;var o=i(184);e.LinearAxis=o.LinearAxis;var t=i(197);e.LogAxis=t.LogAxis;var n=i(200);e.MercatorAxis=n.MercatorAxis},\n", - " function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=t(1),a=t(178),l=s.__importStar(t(28)),n=s.__importStar(t(18)),o=t(9),r=t(8),_=t(98),{abs:h,min:c,max:d}=Math;class m extends a.GuideRendererView{constructor(){super(...arguments),this.rotate=!0}get panel(){return this.layout}get is_renderable(){const[t,e]=this.ranges;return t.is_valid&&e.is_valid}_render(){var t;if(!this.is_renderable)return;const e={tick:this._tick_extent(),tick_label:this._tick_label_extents(),axis_label:this._axis_label_extent()},{tick_coords:i}=this,s=this.layer.ctx;s.save(),this._draw_rule(s,e),this._draw_major_ticks(s,e,i),this._draw_minor_ticks(s,e,i),this._draw_major_labels(s,e,i),this._draw_axis_label(s,e,i),null===(t=this._paint)||void 0===t||t.call(this,s,e,i),s.restore()}connect_signals(){super.connect_signals(),this.connect(this.model.change,()=>this.plot_view.request_layout())}get_size(){if(this.model.visible&&null==this.model.fixed_location&&this.is_renderable){const t=this._get_size();return{width:0,height:Math.round(t)}}return{width:0,height:0}}_get_size(){return this._tick_extent()+this._tick_label_extent()+this._axis_label_extent()}get needs_clip(){return null!=this.model.fixed_location}_draw_rule(t,e){if(!this.visuals.axis_line.doit)return;const[i,s]=this.rule_coords,[a,l]=this.coordinates.map_to_screen(i,s),[n,o]=this.normals,[r,_]=this.offsets;this.visuals.axis_line.set_value(t),t.beginPath(),t.moveTo(Math.round(a[0]+n*r),Math.round(l[0]+o*_));for(let e=1;ec&&(c=o)}return c>0&&(c+=s),c}get normals(){return this.panel.normals}get dimension(){return this.panel.dimension}compute_labels(t){const e=this.model.formatter.doFormat(t,this);for(let i=0;ih(n-o)?(t=d(c(a,l),n),s=c(d(a,l),o)):(t=c(a,l),s=d(a,l)),[t,s]}}get rule_coords(){const t=this.dimension,e=(t+1)%2,[i]=this.ranges,[s,a]=this.computed_bounds,l=[new Array(2),new Array(2)];return l[t][0]=Math.max(s,i.min),l[t][1]=Math.min(a,i.max),l[t][0]>l[t][1]&&(l[t][0]=l[t][1]=NaN),l[e][0]=this.loc,l[e][1]=this.loc,l}get tick_coords(){const t=this.dimension,e=(t+1)%2,[i]=this.ranges,[s,a]=this.computed_bounds,l=this.model.ticker.get_ticks(s,a,i,this.loc,{}),n=l.major,o=l.minor,r=[[],[]],_=[[],[]],[h,c]=[i.min,i.max];for(let i=0;ic||(r[t].push(n[i]),r[e].push(this.loc));for(let i=0;ic||(_[t].push(o[i]),_[e].push(this.loc));return{major:r,minor:_}}get loc(){const{fixed_location:t}=this.model;if(null!=t){if(r.isNumber(t))return t;const[,e]=this.ranges;if(e instanceof _.FactorRange)return e.synthetic(t);throw new Error(\"unexpected\")}const[,e]=this.ranges;switch(this.panel.side){case\"left\":case\"below\":return e.start;case\"right\":case\"above\":return e.end}}serializable_state(){return Object.assign(Object.assign({},super.serializable_state()),{bbox:this.layout.bbox.box})}}i.AxisView=m,m.__name__=\"AxisView\";class b extends a.GuideRenderer{constructor(t){super(t)}static init_Axis(){this.prototype.default_view=m,this.mixins([[\"axis_\",l.Line],[\"major_tick_\",l.Line],[\"minor_tick_\",l.Line],[\"major_label_\",l.Text],[\"axis_label_\",l.Text]]),this.define({bounds:[n.Any,\"auto\"],ticker:[n.Instance],formatter:[n.Instance],axis_label:[n.String,\"\"],axis_label_standoff:[n.Int,5],major_label_standoff:[n.Int,5],major_label_orientation:[n.Any,\"horizontal\"],major_label_overrides:[n.Any,{}],major_tick_in:[n.Number,2],major_tick_out:[n.Number,6],minor_tick_in:[n.Number,0],minor_tick_out:[n.Number,4],fixed_location:[n.Any,null]}),this.override({axis_line_color:\"black\",major_tick_line_color:\"black\",minor_tick_line_color:\"black\",major_label_text_font_size:\"11px\",major_label_text_align:\"center\",major_label_text_baseline:\"alphabetic\",axis_label_text_font_size:\"13px\",axis_label_text_font_style:\"italic\"})}}i.Axis=b,b.__name__=\"Axis\",b.init_Axis()},\n", - " function _(e,r,d){Object.defineProperty(d,\"__esModule\",{value:!0});const i=e(70);class n extends i.RendererView{}d.GuideRendererView=n,n.__name__=\"GuideRendererView\";class t extends i.Renderer{constructor(e){super(e)}static init_GuideRenderer(){this.override({level:\"guide\"})}}d.GuideRenderer=t,t.__name__=\"GuideRenderer\",t.init_GuideRenderer()},\n", - " function _(t,s,o){Object.defineProperty(o,\"__esModule\",{value:!0});const e=t(1),i=t(177),r=t(180),a=t(181),l=e.__importStar(t(28)),_=e.__importStar(t(18));class n extends i.AxisView{_paint(t,s,o){this._draw_group_separators(t,s,o)}_draw_group_separators(t,s,o){const[e]=this.ranges,[i,r]=this.computed_bounds;if(!e.tops||e.tops.length<2||!this.visuals.separator_line.doit)return;const a=this.dimension,l=(a+1)%2,_=[[],[]];let n=0;for(let t=0;ti&&ht[1]),s=this.model.formatter.doFormat(t,this);a.push([s,r.major,this.model.major_label_orientation,this.visuals.major_label_text]),a.push([i.tops,r.tops,this.model.group_label_orientation,this.visuals.group_text])}else if(3==t.levels){const t=i.major.map(t=>t[2]),s=this.model.formatter.doFormat(t,this),o=i.mids.map(t=>t[1]);a.push([s,r.major,this.model.major_label_orientation,this.visuals.major_label_text]),a.push([o,r.mids,this.model.subgroup_label_orientation,this.visuals.subgroup_text]),a.push([i.tops,r.tops,this.model.group_label_orientation,this.visuals.group_text])}return a}get tick_coords(){const t=this.dimension,s=(t+1)%2,[o]=this.ranges,[e,i]=this.computed_bounds,r=this.model.ticker.get_ticks(e,i,o,this.loc,{}),a={major:[[],[]],mids:[[],[]],tops:[[],[]],minor:[[],[]]};return a.major[t]=r.major,a.major[s]=r.major.map(t=>this.loc),3==o.levels&&(a.mids[t]=r.mids,a.mids[s]=r.mids.map(t=>this.loc)),o.levels>1&&(a.tops[t]=r.tops,a.tops[s]=r.tops.map(t=>this.loc)),a}}o.CategoricalAxisView=n,n.__name__=\"CategoricalAxisView\";class h extends i.Axis{constructor(t){super(t)}static init_CategoricalAxis(){this.prototype.default_view=n,this.mixins([[\"separator_\",l.Line],[\"group_\",l.Text],[\"subgroup_\",l.Text]]),this.define({group_label_orientation:[_.Any,\"parallel\"],subgroup_label_orientation:[_.Any,\"parallel\"]}),this.override({ticker:()=>new r.CategoricalTicker,formatter:()=>new a.CategoricalTickFormatter,separator_line_color:\"lightgrey\",separator_line_width:2,group_text_font_style:\"bold\",group_text_font_size:\"11px\",group_text_color:\"grey\",subgroup_text_font_style:\"bold\",subgroup_text_font_size:\"11px\"})}}o.CategoricalAxis=h,h.__name__=\"CategoricalAxis\",h.init_CategoricalAxis()},\n", - " function _(t,c,e){Object.defineProperty(e,\"__esModule\",{value:!0});const o=t(129);class s extends o.Ticker{constructor(t){super(t)}get_ticks(t,c,e,o,s){return{major:this._collect(e.factors,e,t,c),minor:[],tops:this._collect(e.tops||[],e,t,c),mids:this._collect(e.mids||[],e,t,c)}}_collect(t,c,e,o){const s=[];for(const r of t){const t=c.synthetic(r);t>e&&tnew r.DatetimeTicker,formatter:()=>new a.DatetimeTickFormatter})}}i.DatetimeAxis=_,_.__name__=\"DatetimeAxis\",_.init_DatetimeAxis()},\n", - " function _(e,i,s){Object.defineProperty(s,\"__esModule\",{value:!0});const t=e(177),n=e(182),r=e(130),a=e(126);class _ extends t.AxisView{}s.LinearAxisView=_,_.__name__=\"LinearAxisView\";class c extends n.ContinuousAxis{constructor(e){super(e)}static init_LinearAxis(){this.prototype.default_view=_,this.override({ticker:()=>new a.BasicTicker,formatter:()=>new r.BasicTickFormatter})}}s.LinearAxis=c,c.__name__=\"LinearAxis\",c.init_LinearAxis()},\n", - " function _(t,s,e){Object.defineProperty(e,\"__esModule\",{value:!0});const r=t(1),i=r.__importDefault(t(186)),n=t(131),o=t(19),a=r.__importStar(t(18)),c=t(187),m=t(9),u=t(8);function h(t){return i.default(t,\"%Y %m %d %H %M %S\").split(/\\s+/).map(t=>parseInt(t,10))}function d(t,s){if(u.isFunction(s))return s(t);{const e=c.sprintf(\"$1%06d\",function(t){return Math.round(t/1e3%1*1e6)}(t));return-1==(s=s.replace(/((^|[^%])(%%)*)%f/,e)).indexOf(\"%\")?s:i.default(t,s)}}const l=[\"microseconds\",\"milliseconds\",\"seconds\",\"minsec\",\"minutes\",\"hourmin\",\"hours\",\"days\",\"months\",\"years\"];class _ extends n.TickFormatter{constructor(t){super(t),this.strip_leading_zeros=!0}static init_DatetimeTickFormatter(){this.define({microseconds:[a.Array,[\"%fus\"]],milliseconds:[a.Array,[\"%3Nms\",\"%S.%3Ns\"]],seconds:[a.Array,[\"%Ss\"]],minsec:[a.Array,[\":%M:%S\"]],minutes:[a.Array,[\":%M\",\"%Mm\"]],hourmin:[a.Array,[\"%H:%M\"]],hours:[a.Array,[\"%Hh\",\"%H:%M\"]],days:[a.Array,[\"%m/%d\",\"%a%d\"]],months:[a.Array,[\"%m/%Y\",\"%b %Y\"]],years:[a.Array,[\"%Y\"]]})}initialize(){super.initialize(),this._update_width_formats()}_update_width_formats(){const t=+i.default(new Date),s=function(s){const e=s.map(s=>d(t,s).length),r=m.sort_by(m.zip(e,s),([t])=>t);return m.unzip(r)};this._width_formats={microseconds:s(this.microseconds),milliseconds:s(this.milliseconds),seconds:s(this.seconds),minsec:s(this.minsec),minutes:s(this.minutes),hourmin:s(this.hourmin),hours:s(this.hours),days:s(this.days),months:s(this.months),years:s(this.years)}}_get_resolution_str(t,s){const e=1.1*t;switch(!1){case!(e<.001):return\"microseconds\";case!(e<1):return\"milliseconds\";case!(e<60):return s>=60?\"minsec\":\"seconds\";case!(e<3600):return s>=3600?\"hourmin\":\"minutes\";case!(e<86400):return\"hours\";case!(e<2678400):return\"days\";case!(e<31536e3):return\"months\";default:return\"years\"}}doFormat(t,s){if(0==t.length)return[];const e=Math.abs(t[t.length-1]-t[0])/1e3,r=e/(t.length-1),i=this._get_resolution_str(r,e),[,[n]]=this._width_formats[i],a=[],c=l.indexOf(i),m={};for(const t of l)m[t]=0;m.seconds=5,m.minsec=4,m.minutes=4,m.hourmin=3,m.hours=3;for(const s of t){let t,e;try{e=h(s),t=d(s,n)}catch(t){o.logger.warn(\"unable to format tick for timestamp value \"+s),o.logger.warn(\" - \"+t),a.push(\"ERR\");continue}let r=!1,u=c;for(;0==e[m[l[u]]];){let n;if(u+=1,u==l.length)break;if((\"minsec\"==i||\"hourmin\"==i)&&!r){if(\"minsec\"==i&&0==e[4]&&0!=e[5]||\"hourmin\"==i&&0==e[3]&&0!=e[4]){n=this._width_formats[l[c-1]][1][0],t=d(s,n);break}r=!0}n=this._width_formats[l[u]][1][0],t=d(s,n)}if(this.strip_leading_zeros){let s=t.replace(/^0+/g,\"\");s!=t&&isNaN(parseInt(s))&&(s=\"0\"+s),a.push(s)}else a.push(t)}return a}}e.DatetimeTickFormatter=_,_.__name__=\"DatetimeTickFormatter\",_.init_DatetimeTickFormatter()},\n", - " function _(e,t,n){!function(e){\"object\"==typeof t&&t.exports?t.exports=e():\"function\"==typeof define?define(e):this.tz=e()}((function(){function e(e,t,n){var r,o=t.day[1];do{r=new Date(Date.UTC(n,t.month,Math.abs(o++)))}while(t.day[0]<7&&r.getUTCDay()!=t.day[0]);return(r={clock:t.clock,sort:r.getTime(),rule:t,save:6e4*t.save,offset:e.offset})[r.clock]=r.sort+6e4*t.time,r.posix?r.wallclock=r[r.clock]+(e.offset+t.saved):r.posix=r[r.clock]-(e.offset+t.saved),r}function t(t,n,r){var o,a,u,i,l,s,c,f=t[t.zone],h=[],T=new Date(r).getUTCFullYear(),g=1;for(o=1,a=f.length;o=T-g;--c)for(o=0,a=s.length;o=h[o][n]&&h[o][h[o].clock]>u[h[o].clock]&&(i=h[o])}return i&&((l=/^(.*)\\/(.*)$/.exec(u.format))?i.abbrev=l[i.save?2:1]:i.abbrev=u.format.replace(/%s/,i.rule.letter)),i||u}function n(e,n){return\"UTC\"==e.zone?n:(e.entry=t(e,\"posix\",n),n+e.entry.offset+e.entry.save)}function r(e,n){return\"UTC\"==e.zone?n:(e.entry=r=t(e,\"wallclock\",n),0<(o=n-r.wallclock)&&o9)t+=s*l[c-10];else{if(a=new Date(n(e,t)),c<7)for(;s;)a.setUTCDate(a.getUTCDate()+i),a.getUTCDay()==c&&(s-=i);else 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a.AdaptiveTicker({mantissas:[1,2,4,6,8,12],base:24,min_interval:m.ONE_HOUR,max_interval:12*m.ONE_HOUR,num_minor_ticks:0}),new r.DaysTicker({days:t.range(1,32)}),new r.DaysTicker({days:t.range(1,31,3)}),new r.DaysTicker({days:[1,8,15,22]}),new r.DaysTicker({days:[1,15]}),new c.MonthsTicker({months:t.range(0,12,1)}),new c.MonthsTicker({months:t.range(0,12,2)}),new c.MonthsTicker({months:t.range(0,12,4)}),new c.MonthsTicker({months:t.range(0,12,6)}),new _.YearsTicker({})]})}}n.DatetimeTicker=k,k.__name__=\"DatetimeTicker\",k.init_DatetimeTicker()},\n", - " function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});const r=t(1),s=t(128),n=r.__importStar(t(18)),_=t(9);class a extends s.ContinuousTicker{constructor(t){super(t)}static init_CompositeTicker(){this.define({tickers:[n.Array,[]]})}get min_intervals(){return this.tickers.map(t=>t.get_min_interval())}get max_intervals(){return this.tickers.map(t=>t.get_max_interval())}get min_interval(){return this.min_intervals[0]}get max_interval(){return this.max_intervals[0]}get_best_ticker(t,e,i){const r=e-t,s=this.get_ideal_interval(t,e,i),n=[_.sorted_index(this.min_intervals,s)-1,_.sorted_index(this.max_intervals,s)],a=[this.min_intervals[n[0]],this.max_intervals[n[1]]].map(t=>Math.abs(i-r/t));let c;if(_.is_empty(a.filter(t=>!isNaN(t))))c=this.tickers[0];else{const t=n[_.argmin(a)];c=this.tickers[t]}return c}get_interval(t,e,i){return this.get_best_ticker(t,e,i).get_interval(t,e,i)}get_ticks_no_defaults(t,e,i,r){return this.get_best_ticker(t,e,r).get_ticks_no_defaults(t,e,i,r)}}i.CompositeTicker=a,a.__name__=\"CompositeTicker\",a.init_CompositeTicker()},\n", - " function _(t,e,n){Object.defineProperty(n,\"__esModule\",{value:!0});const i=t(1),s=t(193),a=t(194),o=i.__importStar(t(18)),r=t(9);class _ extends s.SingleIntervalTicker{constructor(t){super(t)}static init_DaysTicker(){this.define({days:[o.Array,[]]}),this.override({num_minor_ticks:0})}initialize(){super.initialize();const t=this.days;t.length>1?this.interval=(t[1]-t[0])*a.ONE_DAY:this.interval=31*a.ONE_DAY}get_ticks_no_defaults(t,e,n,i){const s=function(t,e){const n=a.last_month_no_later_than(new Date(t)),i=a.last_month_no_later_than(new Date(e));i.setUTCMonth(i.getUTCMonth()+1);const s=[],o=n;for(;s.push(a.copy_date(o)),o.setUTCMonth(o.getUTCMonth()+1),!(o>i););return s}(t,e),o=this.days,_=this.interval;return{major:r.concat(s.map(t=>((t,e)=>{const n=t.getUTCMonth(),i=[];for(const s of o){const o=a.copy_date(t);o.setUTCDate(s);new Date(o.getTime()+e/2).getUTCMonth()==n&&i.push(o)}return i})(t,_))).map(t=>t.getTime()).filter(n=>t<=n&&n<=e),minor:[]}}}n.DaysTicker=_,_.__name__=\"DaysTicker\",_.init_DaysTicker()},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=e(1),r=e(128),l=n.__importStar(e(18));class a extends r.ContinuousTicker{constructor(e){super(e)}static init_SingleIntervalTicker(){this.define({interval:[l.Number]})}get_interval(e,t,i){return this.interval}get min_interval(){return this.interval}get max_interval(){return this.interval}}i.SingleIntervalTicker=a,a.__name__=\"SingleIntervalTicker\",a.init_SingleIntervalTicker()},\n", - " function _(t,e,n){function _(t){return new Date(t.getTime())}function O(t){const e=_(t);return e.setUTCDate(1),e.setUTCHours(0),e.setUTCMinutes(0),e.setUTCSeconds(0),e.setUTCMilliseconds(0),e}Object.defineProperty(n,\"__esModule\",{value:!0}),n.ONE_MILLI=1,n.ONE_SECOND=1e3,n.ONE_MINUTE=60*n.ONE_SECOND,n.ONE_HOUR=60*n.ONE_MINUTE,n.ONE_DAY=24*n.ONE_HOUR,n.ONE_MONTH=30*n.ONE_DAY,n.ONE_YEAR=365*n.ONE_DAY,n.copy_date=_,n.last_month_no_later_than=O,n.last_year_no_later_than=function(t){const e=O(t);return e.setUTCMonth(0),e}},\n", - " function _(t,e,n){Object.defineProperty(n,\"__esModule\",{value:!0});const r=t(1),i=t(193),s=t(194),a=r.__importStar(t(18)),o=t(9);class _ extends i.SingleIntervalTicker{constructor(t){super(t)}static init_MonthsTicker(){this.define({months:[a.Array,[]]})}initialize(){super.initialize();const t=this.months;t.length>1?this.interval=(t[1]-t[0])*s.ONE_MONTH:this.interval=12*s.ONE_MONTH}get_ticks_no_defaults(t,e,n,r){const i=function(t,e){const n=s.last_year_no_later_than(new Date(t)),r=s.last_year_no_later_than(new Date(e));r.setUTCFullYear(r.getUTCFullYear()+1);const i=[],a=n;for(;i.push(s.copy_date(a)),a.setUTCFullYear(a.getUTCFullYear()+1),!(a>r););return i}(t,e),a=this.months;return{major:o.concat(i.map(t=>a.map(e=>{const n=s.copy_date(t);return n.setUTCMonth(e),n}))).map(t=>t.getTime()).filter(n=>t<=n&&n<=e),minor:[]}}}n.MonthsTicker=_,_.__name__=\"MonthsTicker\",_.init_MonthsTicker()},\n", - " function _(e,t,a){Object.defineProperty(a,\"__esModule\",{value:!0});const i=e(126),r=e(193),n=e(194);class _ extends r.SingleIntervalTicker{constructor(e){super(e)}initialize(){super.initialize(),this.interval=n.ONE_YEAR,this.basic_ticker=new i.BasicTicker({num_minor_ticks:0})}get_ticks_no_defaults(e,t,a,i){const r=n.last_year_no_later_than(new Date(e)).getUTCFullYear(),_=n.last_year_no_later_than(new Date(t)).getUTCFullYear();return{major:this.basic_ticker.get_ticks_no_defaults(r,_,a,i).major.map(e=>Date.UTC(e,0,1)).filter(a=>e<=a&&a<=t),minor:[]}}}a.YearsTicker=_,_.__name__=\"YearsTicker\"},\n", - " function _(e,i,t){Object.defineProperty(t,\"__esModule\",{value:!0});const s=e(177),o=e(182),n=e(198),r=e(199);class _ extends s.AxisView{}t.LogAxisView=_,_.__name__=\"LogAxisView\";class c extends o.ContinuousAxis{constructor(e){super(e)}static init_LogAxis(){this.prototype.default_view=_,this.override({ticker:()=>new r.LogTicker,formatter:()=>new n.LogTickFormatter})}}t.LogAxis=c,c.__name__=\"LogAxis\",c.init_LogAxis()},\n", - " function _(t,e,r){Object.defineProperty(r,\"__esModule\",{value:!0});const i=t(1),o=t(131),a=t(130),n=i.__importStar(t(18));class c extends o.TickFormatter{constructor(t){super(t)}static init_LogTickFormatter(){this.define({ticker:[n.Instance,null]})}initialize(){super.initialize(),this.basic_formatter=new a.BasicTickFormatter}doFormat(t,e){if(0==t.length)return[];const r=null!=this.ticker?this.ticker.base:10;let i=!1;const o=new Array(t.length);for(let e=0,a=t.length;e0&&o[e]==o[e-1]){i=!0;break}return i?this.basic_formatter.doFormat(t,e):o}}r.LogTickFormatter=c,c.__name__=\"LogTickFormatter\",c.init_LogTickFormatter()},\n", - " function _(t,o,e){Object.defineProperty(e,\"__esModule\",{value:!0});const i=t(127),s=t(9);class n extends i.AdaptiveTicker{constructor(t){super(t)}static init_LogTicker(){this.override({mantissas:[1,5]})}get_ticks_no_defaults(t,o,e,i){const n=this.num_minor_ticks,r=[],c=this.base,a=Math.log(t)/Math.log(c),f=Math.log(o)/Math.log(c),l=f-a;let h;if(isFinite(l))if(l<2){const e=this.get_interval(t,o,i),c=Math.floor(t/e),a=Math.ceil(o/e);if(h=s.range(c,a+1).filter(t=>0!=t).map(t=>t*e).filter(e=>t<=e&&e<=o),n>0&&h.length>0){const t=e/n,o=s.range(0,n).map(o=>o*t);for(const t of o.slice(1))r.push(h[0]-t);for(const t of h)for(const e of o)r.push(t+e)}}else{const t=Math.ceil(.999999*a),o=Math.floor(1.000001*f),e=Math.ceil((o-t)/9);if(h=s.range(t-1,o+1,e).map(t=>c**t),n>0&&h.length>0){const t=c**e/n,o=s.range(1,n+1).map(o=>o*t);for(const t of o)r.push(h[0]/t);r.push(h[0]);for(const t of h)for(const e of o)r.push(t*e)}}else h=[];return{major:h.filter(e=>t<=e&&e<=o),minor:r.filter(e=>t<=e&&e<=o)}}}e.LogTicker=n,n.__name__=\"LogTicker\",n.init_LogTicker()},\n", - " function _(e,t,r){Object.defineProperty(r,\"__esModule\",{value:!0});const i=e(177),s=e(184),o=e(201),a=e(202);class c extends i.AxisView{}r.MercatorAxisView=c,c.__name__=\"MercatorAxisView\";class n extends s.LinearAxis{constructor(e){super(e)}static init_MercatorAxis(){this.prototype.default_view=c,this.override({ticker:()=>new a.MercatorTicker({dimension:\"lat\"}),formatter:()=>new o.MercatorTickFormatter({dimension:\"lat\"})})}}r.MercatorAxis=n,n.__name__=\"MercatorAxis\",n.init_MercatorAxis()},\n", - " function _(r,t,e){Object.defineProperty(e,\"__esModule\",{value:!0});const o=r(1),n=r(130),i=o.__importStar(r(18)),c=r(37);class a extends n.BasicTickFormatter{constructor(r){super(r)}static init_MercatorTickFormatter(){this.define({dimension:[i.LatLon]})}doFormat(r,t){if(null==this.dimension)throw new Error(\"MercatorTickFormatter.dimension not configured\");if(0==r.length)return[];const e=r.length,o=new Array(e);if(\"lon\"==this.dimension)for(let n=0;n{const n=s.replace_placeholders(this.url,t,e);if(!r.isString(n))throw new Error(\"HTML output is not supported in this context\");this.same_tab?window.location.href=n:window.open(n)},{selected:o}=t;for(const e of o.indices)n(e);for(const e of o.line_indices)n(e)}}n.OpenURL=a,a.__name__=\"OpenURL\",a.init_OpenURL()},\n", - " function _(a,e,r){Object.defineProperty(r,\"__esModule\",{value:!0});var n=a(77);r.Canvas=n.Canvas;var s=a(208);r.CartesianFrame=s.CartesianFrame},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const a=e(209),_=e(146),n=e(157),r=e(158),i=e(210),g=e(98),c=e(212),o=e(13),l=e(11);class h extends c.LayoutItem{constructor(e,t,s,a,_={},n={}){super(),this.in_x_scale=e,this.in_y_scale=t,this.x_range=s,this.y_range=a,this.extra_x_ranges=_,this.extra_y_ranges=n,l.assert(null==e.source_range&&null==e.target_range),l.assert(null==t.source_range&&null==t.target_range),this._configure_scales()}_get_ranges(e,t){return new Map(o.entries(Object.assign(Object.assign({},t),{default:e})))}_get_scales(e,t,s){const c=new Map;for(const[o,l]of t){if((l instanceof i.DataRange1d||l instanceof r.Range1d)&&!(e instanceof _.ContinuousScale))throw new Error(`Range ${l.type} is incompatible is Scale ${e.type}`);if(l instanceof g.FactorRange&&!(e instanceof a.CategoricalScale))throw new Error(`Range ${l.type} is incompatible is Scale ${e.type}`);e instanceof n.LogScale&&l instanceof i.DataRange1d&&(l.scale_hint=\"log\");const t=e.clone();t.setv({source_range:l,target_range:s}),c.set(o,t)}return c}_configure_frame_ranges(){const{bbox:e}=this;this._x_target=new r.Range1d({start:e.left,end:e.right}),this._y_target=new r.Range1d({start:e.bottom,end:e.top})}_configure_scales(){this._configure_frame_ranges(),this._x_ranges=this._get_ranges(this.x_range,this.extra_x_ranges),this._y_ranges=this._get_ranges(this.y_range,this.extra_y_ranges),this._x_scales=this._get_scales(this.in_x_scale,this._x_ranges,this._x_target),this._y_scales=this._get_scales(this.in_y_scale,this._y_ranges,this._y_target)}_update_scales(){this._configure_frame_ranges();for(const[,e]of this._x_scales)e.target_range=this._x_target;for(const[,e]of this._y_scales)e.target_range=this._y_target}_set_geometry(e,t){super._set_geometry(e,t),this._update_scales()}get x_ranges(){return this._x_ranges}get y_ranges(){return this._y_ranges}get x_scales(){return this._x_scales}get y_scales(){return this._y_scales}get x_scale(){return this._x_scales.get(\"default\")}get y_scale(){return this._y_scales.get(\"default\")}get xscales(){return o.to_object(this.x_scales)}get yscales(){return o.to_object(this.y_scales)}}s.CartesianFrame=h,h.__name__=\"CartesianFrame\"},\n", - " function _(e,r,t){Object.defineProperty(t,\"__esModule\",{value:!0});const n=e(147);class _ extends n.Scale{constructor(e){super(e)}compute(e){return super._linear_compute(this.source_range.synthetic(e))}v_compute(e){return super._linear_v_compute(this.source_range.v_synthetic(e))}invert(e){return this._linear_invert(e)}v_invert(e){return this._linear_v_invert(e)}}t.CategoricalScale=_,_.__name__=\"CategoricalScale\"},\n", - " function _(t,i,n){Object.defineProperty(n,\"__esModule\",{value:!0});const e=t(1),a=t(211),s=t(90),l=t(19),_=e.__importStar(t(18)),o=e.__importStar(t(79)),r=t(9);class h extends a.DataRange{constructor(t){super(t),this.have_updated_interactively=!1}static init_DataRange1d(){this.define({start:[_.Number],end:[_.Number],range_padding:[_.Number,.1],range_padding_units:[_.PaddingUnits,\"percent\"],flipped:[_.Boolean,!1],follow:[_.StartEnd],follow_interval:[_.Number],default_span:[_.Number,2],only_visible:[_.Boolean,!1]}),this.internal({scale_hint:[_.String,\"auto\"]})}initialize(){super.initialize(),this._initial_start=this.start,this._initial_end=this.end,this._initial_range_padding=this.range_padding,this._initial_range_padding_units=this.range_padding_units,this._initial_follow=this.follow,this._initial_follow_interval=this.follow_interval,this._initial_default_span=this.default_span,this._plot_bounds=new Map}get min(){return Math.min(this.start,this.end)}get max(){return Math.max(this.start,this.end)}computed_renderers(){const t=this.names;let i=this.renderers;if(0==i.length)for(const t of this.plots){const n=t.renderers.filter(t=>t instanceof s.GlyphRenderer);i=i.concat(n)}t.length>0&&(i=i.filter(i=>r.includes(t,i.name))),l.logger.debug(`computed ${i.length} renderers for ${this}`);for(const t of i)l.logger.trace(\" - \"+t);return i}_compute_plot_bounds(t,i){let n=o.empty();for(const e of t){const t=i.get(e);null==t||!e.visible&&this.only_visible||(n=o.union(n,t))}return n}adjust_bounds_for_aspect(t,i){const n=o.empty();let e=t.x1-t.x0;e<=0&&(e=1);let a=t.y1-t.y0;a<=0&&(a=1);const s=.5*(t.x1+t.x0),l=.5*(t.y1+t.y0);return e_&&(\"start\"==this.follow?a=e+s*_:\"end\"==this.follow&&(e=a-s*_)),[e,a]}update(t,i,n,e){if(this.have_updated_interactively)return;const a=this.computed_renderers();let s=this._compute_plot_bounds(a,t);null!=e&&(s=this.adjust_bounds_for_aspect(s,e)),this._plot_bounds.set(n,s);const[l,_]=this._compute_min_max(this._plot_bounds.values(),i);let[o,r]=this._compute_range(l,_);null!=this._initial_start&&(\"log\"==this.scale_hint?this._initial_start>0&&(o=this._initial_start):o=this._initial_start),null!=this._initial_end&&(\"log\"==this.scale_hint?this._initial_end>0&&(r=this._initial_end):r=this._initial_end);const[h,d]=[this.start,this.end];if(o!=h||r!=d){const t={};o!=h&&(t.start=o),r!=d&&(t.end=r),this.setv(t)}\"auto\"==this.bounds&&this.setv({bounds:[o,r]},{silent:!0}),this.change.emit()}reset(){this.have_updated_interactively=!1,this.setv({range_padding:this._initial_range_padding,range_padding_units:this._initial_range_padding_units,follow:this._initial_follow,follow_interval:this._initial_follow_interval,default_span:this._initial_default_span},{silent:!0}),this.change.emit()}}n.DataRange1d=h,h.__name__=\"DataRange1d\",h.init_DataRange1d()},\n", - " function _(e,a,t){Object.defineProperty(t,\"__esModule\",{value:!0});const n=e(1),r=e(99),s=n.__importStar(e(18));class _ extends r.Range{constructor(e){super(e)}static init_DataRange(){this.define({names:[s.Array,[]],renderers:[s.Array,[]]})}}t.DataRange=_,_.__name__=\"DataRange\",_.init_DataRange()},\n", - " function _(a,o,t){Object.defineProperty(t,\"__esModule\",{value:!0});var e=a(213);t.Sizeable=e.Sizeable,t.SizingPolicy=e.SizingPolicy;var i=a(214);t.Layoutable=i.Layoutable,t.LayoutItem=i.LayoutItem;var n=a(215);t.HStack=n.HStack,t.VStack=n.VStack,t.AnchorLayout=n.AnchorLayout;var r=a(216);t.Grid=r.Grid,t.Row=r.Row,t.Column=r.Column;var c=a(217);t.ContentBox=c.ContentBox,t.VariadicBox=c.VariadicBox},\n", - " function _(t,h,i){Object.defineProperty(i,\"__esModule\",{value:!0});const e=t(21),{min:d,max:n}=Math;class w{constructor(t={}){this.width=null!=t.width?t.width:0,this.height=null!=t.height?t.height:0}bounded_to({width:t,height:h}){return new w({width:this.width==1/0&&null!=t?t:this.width,height:this.height==1/0&&null!=h?h:this.height})}expanded_to({width:t,height:h}){return new w({width:t!=1/0?n(this.width,t):this.width,height:h!=1/0?n(this.height,h):this.height})}expand_to({width:t,height:h}){this.width=n(this.width,t),this.height=n(this.height,h)}narrowed_to({width:t,height:h}){return new w({width:d(this.width,t),height:d(this.height,h)})}narrow_to({width:t,height:h}){this.width=d(this.width,t),this.height=d(this.height,h)}grow_by({left:t,right:h,top:i,bottom:e}){const d=this.width+t+h,n=this.height+i+e;return new w({width:d,height:n})}shrink_by({left:t,right:h,top:i,bottom:e}){const d=n(this.width-t-h,0),s=n(this.height-i-e,0);return new w({width:d,height:s})}map(t,h){return new w({width:t(this.width),height:(null!=h?h:t)(this.height)})}}i.Sizeable=w,w.__name__=\"Sizeable\",i.SizingPolicy=e.Enum(\"fixed\",\"fit\",\"min\",\"max\")},\n", - " function _(i,t,h){Object.defineProperty(h,\"__esModule\",{value:!0});const e=i(213),s=i(79),{min:n,max:g,round:a}=Math;class l{constructor(){this._bbox=new s.BBox,this._inner_bbox=new s.BBox}get bbox(){return this._bbox}get inner_bbox(){return this._inner_bbox}get sizing(){return this._sizing}set_sizing(i){const t=i.width_policy||\"fit\",h=i.width,e=null!=i.min_width?i.min_width:0,s=null!=i.max_width?i.max_width:1/0,n=i.height_policy||\"fit\",g=i.height,a=null!=i.min_height?i.min_height:0,l=null!=i.max_height?i.max_height:1/0,_=i.aspect,d=i.margin||{top:0,right:0,bottom:0,left:0},r=!1!==i.visible,w=i.halign||\"start\",o=i.valign||\"start\";this._sizing={width_policy:t,min_width:e,width:h,max_width:s,height_policy:n,min_height:a,height:g,max_height:l,aspect:_,margin:d,visible:r,halign:w,valign:o,size:{width:h,height:g},min_size:{width:e,height:a},max_size:{width:s,height:l}},this._init()}_init(){}_set_geometry(i,t){this._bbox=i,this._inner_bbox=t}set_geometry(i,t){this._set_geometry(i,t||i)}is_width_expanding(){return\"max\"==this.sizing.width_policy}is_height_expanding(){return\"max\"==this.sizing.height_policy}apply_aspect(i,{width:t,height:h}){const{aspect:e}=this.sizing;if(null!=e){const{width_policy:s,height_policy:n}=this.sizing,g=(i,t)=>{const h={max:4,fit:3,min:2,fixed:1};return h[i]>h[t]};if(\"fixed\"!=s&&\"fixed\"!=n)if(s==n){const s=t,n=a(t/e),g=a(h*e),l=h;Math.abs(i.width-s)+Math.abs(i.height-n)<=Math.abs(i.width-g)+Math.abs(i.height-l)?(t=s,h=n):(t=g,h=l)}else g(s,n)?h=a(t/e):t=a(h*e);else\"fixed\"==s?h=a(t/e):\"fixed\"==n&&(t=a(h*e))}return{width:t,height:h}}measure(i){if(!this.sizing.visible)return{width:0,height:0};const t=i=>\"fixed\"==this.sizing.width_policy&&null!=this.sizing.width?this.sizing.width:i,h=i=>\"fixed\"==this.sizing.height_policy&&null!=this.sizing.height?this.sizing.height:i,s=new e.Sizeable(i).shrink_by(this.sizing.margin).map(t,h),n=this._measure(s),g=this.clip_size(n),a=t(g.width),l=h(g.height),_=this.apply_aspect(s,{width:a,height:l});return Object.assign(Object.assign({},n),_)}compute(i={}){const t=this.measure({width:null!=i.width&&this.is_width_expanding()?i.width:1/0,height:null!=i.height&&this.is_height_expanding()?i.height:1/0}),{width:h,height:e}=t,n=new s.BBox({left:0,top:0,width:h,height:e});let g=void 0;if(null!=t.inner){const{left:i,top:n,right:a,bottom:l}=t.inner;g=new s.BBox({left:i,top:n,right:h-a,bottom:e-l})}this.set_geometry(n,g)}get xview(){return this.bbox.xview}get yview(){return this.bbox.yview}clip_width(i){return g(this.sizing.min_width,n(i,this.sizing.max_width))}clip_height(i){return g(this.sizing.min_height,n(i,this.sizing.max_height))}clip_size({width:i,height:t}){return{width:this.clip_width(i),height:this.clip_height(t)}}}h.Layoutable=l,l.__name__=\"Layoutable\";class _ extends l{_measure(i){const{width_policy:t,height_policy:h}=this.sizing;let e,s;if(i.width==1/0)e=null!=this.sizing.width?this.sizing.width:0;else switch(t){case\"fixed\":e=null!=this.sizing.width?this.sizing.width:0;break;case\"min\":e=null!=this.sizing.width?n(i.width,this.sizing.width):0;break;case\"fit\":e=null!=this.sizing.width?n(i.width,this.sizing.width):i.width;break;case\"max\":e=null!=this.sizing.width?g(i.width,this.sizing.width):i.width}if(i.height==1/0)s=null!=this.sizing.height?this.sizing.height:0;else switch(h){case\"fixed\":s=null!=this.sizing.height?this.sizing.height:0;break;case\"min\":s=null!=this.sizing.height?n(i.height,this.sizing.height):0;break;case\"fit\":s=null!=this.sizing.height?n(i.height,this.sizing.height):i.height;break;case\"max\":s=null!=this.sizing.height?g(i.height,this.sizing.height):i.height}return{width:e,height:s}}}h.LayoutItem=_,_.__name__=\"LayoutItem\";class d extends l{_measure(i){const t=this._content_size(),h=i.bounded_to(this.sizing.size).bounded_to(t);return{width:(()=>{switch(this.sizing.width_policy){case\"fixed\":return null!=this.sizing.width?this.sizing.width:t.width;case\"min\":return t.width;case\"fit\":return h.width;case\"max\":return Math.max(t.width,h.width)}})(),height:(()=>{switch(this.sizing.height_policy){case\"fixed\":return null!=this.sizing.height?this.sizing.height:t.height;case\"min\":return t.height;case\"fit\":return h.height;case\"max\":return Math.max(t.height,h.height)}})()}}}h.ContentLayoutable=d,d.__name__=\"ContentLayoutable\"},\n", - " function _(t,e,h){Object.defineProperty(h,\"__esModule\",{value:!0});const o=t(214),r=t(79);class i extends o.Layoutable{constructor(){super(...arguments),this.children=[]}}h.Stack=i,i.__name__=\"Stack\";class s extends i{_measure(t){let e=0,h=0;for(const t of this.children){const o=t.measure({width:0,height:0});e+=o.width,h=Math.max(h,o.height)}return{width:e,height:h}}_set_geometry(t,e){super._set_geometry(t,e);const{top:h,bottom:o}=t;let{left:i}=t;for(const t of this.children){const{width:e}=t.measure({width:0,height:0});t.set_geometry(new r.BBox({left:i,width:e,top:h,bottom:o})),i+=e}}}h.HStack=s,s.__name__=\"HStack\";class n extends i{_measure(t){let e=0,h=0;for(const t of this.children){const o=t.measure({width:0,height:0});e=Math.max(e,o.width),h+=o.height}return{width:e,height:h}}_set_geometry(t,e){super._set_geometry(t,e);const{left:h,right:o}=t;let{top:i}=t;for(const t of this.children){const{height:e}=t.measure({width:0,height:0});t.set_geometry(new r.BBox({top:i,height:e,left:h,right:o})),i+=e}}}h.VStack=n,n.__name__=\"VStack\";class c extends o.Layoutable{constructor(){super(...arguments),this.children=[]}_measure(t){let e=0,h=0;for(const{layout:o}of this.children){const r=o.measure(t);e=Math.max(e,r.width),h=Math.max(h,r.height)}return{width:e,height:h}}_set_geometry(t,e){super._set_geometry(t,e);for(const{layout:e,anchor:h,margin:o}of this.children){const{left:i,right:s,top:n,bottom:c,hcenter:a,vcenter:_}=t,{width:g,height:d}=e.measure(t);let m;switch(h){case\"top_left\":m=new r.BBox({left:i+o,top:n+o,width:g,height:d});break;case\"top_center\":m=new r.BBox({hcenter:a,top:n+o,width:g,height:d});break;case\"top_right\":m=new r.BBox({right:s-o,top:n+o,width:g,height:d});break;case\"bottom_right\":m=new r.BBox({right:s-o,bottom:c-o,width:g,height:d});break;case\"bottom_center\":m=new r.BBox({hcenter:a,bottom:c-o,width:g,height:d});break;case\"bottom_left\":m=new r.BBox({left:i+o,bottom:c-o,width:g,height:d});break;case\"center_left\":m=new r.BBox({left:i+o,vcenter:_,width:g,height:d});break;case\"center\":m=new r.BBox({hcenter:a,vcenter:_,width:g,height:d});break;case\"center_right\":m=new r.BBox({right:s-o,vcenter:_,width:g,height:d})}e.set_geometry(m)}}}h.AnchorLayout=c,c.__name__=\"AnchorLayout\"},\n", - " function _(t,i,s){Object.defineProperty(s,\"__esModule\",{value:!0});const e=t(213),o=t(214),n=t(8),r=t(79),h=t(9),{max:l,round:c}=Math;class a{constructor(t){this.def=t,this._map=new Map}get(t){let i=this._map.get(t);return void 0===i&&(i=this.def(),this._map.set(t,i)),i}apply(t,i){const s=this.get(t);this._map.set(t,i(s))}}a.__name__=\"DefaultMap\";class g{constructor(){this._items=[],this._nrows=0,this._ncols=0}get nrows(){return this._nrows}get ncols(){return this._ncols}add(t,i){const{r1:s,c1:e}=t;this._nrows=l(this._nrows,s+1),this._ncols=l(this._ncols,e+1),this._items.push({span:t,data:i})}at(t,i){return this._items.filter(({span:s})=>s.r0<=t&&t<=s.r1&&s.c0<=i&&i<=s.c1).map(({data:t})=>t)}row(t){return this._items.filter(({span:i})=>i.r0<=t&&t<=i.r1).map(({data:t})=>t)}col(t){return this._items.filter(({span:i})=>i.c0<=t&&t<=i.c1).map(({data:t})=>t)}foreach(t){for(const{span:i,data:s}of this._items)t(i,s)}map(t){const i=new g;for(const{span:s,data:e}of this._items)i.add(s,t(s,e));return i}}g.__name__=\"Container\";class p extends o.Layoutable{constructor(t=[]){super(),this.items=t,this.rows=\"auto\",this.cols=\"auto\",this.spacing=0,this.absolute=!1}is_width_expanding(){if(super.is_width_expanding())return!0;if(\"fixed\"==this.sizing.width_policy)return!1;const{cols:t}=this._state;return h.some(t,t=>\"max\"==t.policy)}is_height_expanding(){if(super.is_height_expanding())return!0;if(\"fixed\"==this.sizing.height_policy)return!1;const{rows:t}=this._state;return h.some(t,t=>\"max\"==t.policy)}_init(){super._init();const t=new g;for(const{layout:i,row:s,col:e,row_span:o,col_span:n}of this.items)if(i.sizing.visible){const r=s,h=e,l=s+(null!=o?o:1)-1,c=e+(null!=n?n:1)-1;t.add({r0:r,c0:h,r1:l,c1:c},i)}const{nrows:i,ncols:s}=t,e=new Array(i);for(let s=0;s{const t=n.isPlainObject(this.rows)?this.rows[s]||this.rows[\"*\"]:this.rows;return null==t?{policy:\"auto\"}:n.isNumber(t)?{policy:\"fixed\",height:t}:n.isString(t)?{policy:t}:t})(),o=i.align||\"auto\";if(\"fixed\"==i.policy)e[s]={policy:\"fixed\",height:i.height,align:o};else if(\"min\"==i.policy)e[s]={policy:\"min\",align:o};else if(\"fit\"==i.policy||\"max\"==i.policy)e[s]={policy:i.policy,flex:i.flex||1,align:o};else{if(\"auto\"!=i.policy)throw new Error(\"unrechable\");h.some(t.row(s),t=>t.is_height_expanding())?e[s]={policy:\"max\",flex:1,align:o}:e[s]={policy:\"min\",align:o}}}const o=new Array(s);for(let i=0;i{const t=n.isPlainObject(this.cols)?this.cols[i]||this.cols[\"*\"]:this.cols;return null==t?{policy:\"auto\"}:n.isNumber(t)?{policy:\"fixed\",width:t}:n.isString(t)?{policy:t}:t})(),e=s.align||\"auto\";if(\"fixed\"==s.policy)o[i]={policy:\"fixed\",width:s.width,align:e};else if(\"min\"==s.policy)o[i]={policy:\"min\",align:e};else if(\"fit\"==s.policy||\"max\"==s.policy)o[i]={policy:s.policy,flex:s.flex||1,align:e};else{if(\"auto\"!=s.policy)throw new Error(\"unrechable\");h.some(t.col(i),t=>t.is_width_expanding())?o[i]={policy:\"max\",flex:1,align:e}:o[i]={policy:\"min\",align:e}}}const[r,l]=n.isNumber(this.spacing)?[this.spacing,this.spacing]:this.spacing;this._state={items:t,nrows:i,ncols:s,rows:e,cols:o,rspacing:r,cspacing:l}}_measure_totals(t,i){const{nrows:s,ncols:e,rspacing:o,cspacing:n}=this._state;return{height:h.sum(t)+(s-1)*o,width:h.sum(i)+(e-1)*n}}_measure_cells(t){const{items:i,nrows:s,ncols:o,rows:n,cols:r,rspacing:h,cspacing:a}=this._state,p=new Array(s);for(let t=0;t{const{r0:o,c0:g,r1:d,c1:w}=i,u=(d-o)*h,m=(w-g)*a;let y=0;for(let i=o;i<=d;i++)y+=t(i,g).height;y+=u;let x=0;for(let i=g;i<=w;i++)x+=t(o,i).width;x+=m;const b=s.measure({width:x,height:y});f.add(i,{layout:s,size_hint:b});const z=new e.Sizeable(b).grow_by(s.sizing.margin);z.height-=u,z.width-=m;const j=[];for(let t=o;t<=d;t++){const i=n[t];\"fixed\"==i.policy?z.height-=i.height:j.push(t)}if(z.height>0){const t=c(z.height/j.length);for(const i of j)p[i]=l(p[i],t)}const O=[];for(let t=g;t<=w;t++){const i=r[t];\"fixed\"==i.policy?z.width-=i.width:O.push(t)}if(z.width>0){const t=c(z.width/O.length);for(const i of O)_[i]=l(_[i],t)}});return{size:this._measure_totals(p,_),row_heights:p,col_widths:_,size_hints:f}}_measure_grid(t){const{nrows:i,ncols:s,rows:e,cols:o,rspacing:n,cspacing:r}=this._state,h=this._measure_cells((t,i)=>{const s=e[t],n=o[i];return{width:\"fixed\"==n.policy?n.width:1/0,height:\"fixed\"==s.policy?s.height:1/0}});let a;a=\"fixed\"==this.sizing.height_policy&&null!=this.sizing.height?this.sizing.height:t.height!=1/0&&this.is_height_expanding()?t.height:h.size.height;let g,p=0;for(let t=0;t0)for(let t=0;ti?i:e,t--}}}g=\"fixed\"==this.sizing.width_policy&&null!=this.sizing.width?this.sizing.width:t.width!=1/0&&this.is_width_expanding()?t.width:h.size.width;let _=0;for(let t=0;t0)for(let t=0;ts?s:o,t--}}}const{row_heights:f,col_widths:d,size_hints:w}=this._measure_cells((t,i)=>({width:h.col_widths[i],height:h.row_heights[t]}));return{size:this._measure_totals(f,d),row_heights:f,col_widths:d,size_hints:w}}_measure(t){const{size:i}=this._measure_grid(t);return i}_set_geometry(t,i){super._set_geometry(t,i);const{nrows:s,ncols:e,rspacing:o,cspacing:n}=this._state,{row_heights:h,col_widths:g,size_hints:p}=this._measure_grid(t),_=this._state.rows.map((t,i)=>Object.assign(Object.assign({},t),{top:0,height:h[i],get bottom(){return this.top+this.height}})),f=this._state.cols.map((t,i)=>Object.assign(Object.assign({},t),{left:0,width:g[i],get right(){return this.left+this.width}})),d=p.map((t,i)=>Object.assign(Object.assign({},i),{outer:new r.BBox,inner:new r.BBox}));for(let i=0,e=this.absolute?t.top:0;i{const{layout:l,size_hint:a}=h,{sizing:g}=l,{width:p,height:d}=a,w=function(t,i){let s=(i-t)*n;for(let e=t;e<=i;e++)s+=f[e].width;return s}(i,e),u=function(t,i){let s=(i-t)*o;for(let e=t;e<=i;e++)s+=_[e].height;return s}(t,s),m=i==e&&\"auto\"!=f[i].align?f[i].align:g.halign,y=t==s&&\"auto\"!=_[t].align?_[t].align:g.valign;let x=f[i].left;\"start\"==m?x+=g.margin.left:\"center\"==m?x+=c((w-p)/2):\"end\"==m&&(x+=w-g.margin.right-p);let b=_[t].top;\"start\"==y?b+=g.margin.top:\"center\"==y?b+=c((u-d)/2):\"end\"==y&&(b+=u-g.margin.bottom-d),h.outer=new r.BBox({left:x,top:b,width:p,height:d})});const w=_.map(()=>({start:new a(()=>0),end:new a(()=>0)})),u=f.map(()=>({start:new a(()=>0),end:new a(()=>0)}));d.foreach(({r0:t,c0:i,r1:s,c1:e},{size_hint:o,outer:n})=>{const{inner:r}=o;null!=r&&(w[t].start.apply(n.top,t=>l(t,r.top)),w[s].end.apply(_[s].bottom-n.bottom,t=>l(t,r.bottom)),u[i].start.apply(n.left,t=>l(t,r.left)),u[e].end.apply(f[e].right-n.right,t=>l(t,r.right)))}),d.foreach(({r0:t,c0:i,r1:s,c1:e},o)=>{const{size_hint:n,outer:h}=o;function l({left:t,right:i,top:s,bottom:e}){const o=h.width-t-i,n=h.height-s-e;return new r.BBox({left:t,top:s,width:o,height:n})}if(null!=n.inner){let r=l(n.inner);if(!1!==n.align){const o=w[t].start.get(h.top),n=w[s].end.get(_[s].bottom-h.bottom),c=u[i].start.get(h.left),a=u[e].end.get(f[e].right-h.right);try{r=l({top:o,bottom:n,left:c,right:a})}catch(t){}}o.inner=r}else o.inner=h}),d.foreach((t,{layout:i,outer:s,inner:e})=>{i.set_geometry(s,e)})}}s.Grid=p,p.__name__=\"Grid\";class _ extends p{constructor(t){super(),this.items=t.map((t,i)=>({layout:t,row:0,col:i})),this.rows=\"fit\"}}s.Row=_,_.__name__=\"Row\";class f extends p{constructor(t){super(),this.items=t.map((t,i)=>({layout:t,row:i,col:0})),this.cols=\"fit\"}}s.Column=f,f.__name__=\"Column\"},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const n=e(214),i=e(213),a=e(72);class c extends n.ContentLayoutable{constructor(e){super(),this.content_size=a.unsized(e,()=>new i.Sizeable(a.size(e)))}_content_size(){return this.content_size}}s.ContentBox=c,c.__name__=\"ContentBox\";class o extends n.Layoutable{constructor(e){super(),this.el=e}_measure(e){const t=new i.Sizeable(e).bounded_to(this.sizing.size);return a.sized(this.el,t,()=>{const e=new i.Sizeable(a.content_size(this.el)),{border:t,padding:s}=a.extents(this.el);return e.grow_by(t).grow_by(s).map(Math.ceil)})}}s.VariadicBox=o,o.__name__=\"VariadicBox\";class r extends o{constructor(e){super(e),this._cache=new Map}_measure(e){const{width:t,height:s}=e,n=`${t},${s}`;let i=this._cache.get(n);return null==i&&(i=super._measure(e),this._cache.set(n,i)),i}invalidate_cache(){this._cache.clear()}}s.CachedVariadicBox=r,r.__name__=\"CachedVariadicBox\"},\n", - " function _(e,r,u){Object.defineProperty(u,\"__esModule\",{value:!0});var a=e(219);u.Expression=a.Expression;var n=e(220);u.Stack=n.Stack;var o=e(221);u.CumSum=o.CumSum},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const n=e(81);class i extends n.Model{constructor(e){super(e)}initialize(){super.initialize(),this._connected=new Set,this._result=new Map}v_compute(e){this._connected.has(e)||(this.connect(e.change,()=>this._result.delete(e)),this.connect(e.patching,()=>this._result.delete(e)),this.connect(e.streaming,()=>this._result.delete(e)),this._connected.add(e));let t=this._result.get(e);return null==t&&(t=this._v_compute(e),this._result.set(e,t)),t}}s.Expression=i,i.__name__=\"Expression\"},\n", - " function _(t,e,n){Object.defineProperty(n,\"__esModule\",{value:!0});const r=t(1),i=t(219),s=t(24),o=r.__importStar(t(18));class a extends i.Expression{constructor(t){super(t)}static init_Stack(){this.define({fields:[o.Array,[]]})}_v_compute(t){var e;const n=null!==(e=t.get_length())&&void 0!==e?e:0,r=new s.NumberArray(n);for(const e of this.fields){const i=t.data[e];if(null!=i)for(let t=0,e=Math.min(n,i.length);tn(t,e,r,...this.values))}}n.FuncTickFormatter=u,u.__name__=\"FuncTickFormatter\",u.init_FuncTickFormatter()},\n", - " function _(r,t,n){Object.defineProperty(n,\"__esModule\",{value:!0});const e=r(1),o=e.__importStar(r(188)),a=r(131),i=e.__importStar(r(18));class u extends a.TickFormatter{constructor(r){super(r)}static init_NumeralTickFormatter(){this.define({format:[i.String,\"0,0\"],language:[i.String,\"en\"],rounding:[i.RoundingFunction,\"round\"]})}get _rounding_fn(){switch(this.rounding){case\"round\":case\"nearest\":return Math.round;case\"floor\":case\"rounddown\":return Math.floor;case\"ceil\":case\"roundup\":return Math.ceil}}doFormat(r,t){const{format:n,language:e,_rounding_fn:a}=this;return r.map(r=>o.format(r,n,e,a))}}n.NumeralTickFormatter=u,u.__name__=\"NumeralTickFormatter\",u.init_NumeralTickFormatter()},\n", - " function _(t,r,i){Object.defineProperty(i,\"__esModule\",{value:!0});const e=t(1),n=t(131),o=t(187),a=e.__importStar(t(18));class c extends n.TickFormatter{constructor(t){super(t)}static init_PrintfTickFormatter(){this.define({format:[a.String,\"%s\"]})}doFormat(t,r){return t.map(t=>o.sprintf(this.format,t))}}i.PrintfTickFormatter=c,c.__name__=\"PrintfTickFormatter\",c.init_PrintfTickFormatter()},\n", - " function _(a,e,r){Object.defineProperty(r,\"__esModule\",{value:!0});var v=a(233);r.AnnularWedge=v.AnnularWedge;var l=a(234);r.Annulus=l.Annulus;var t=a(235);r.Arc=t.Arc;var i=a(236);r.Bezier=i.Bezier;var n=a(237);r.Circle=n.Circle;var u=a(241);r.CenterRotatable=u.CenterRotatable;var c=a(242);r.Ellipse=c.Ellipse;var g=a(243);r.EllipseOval=g.EllipseOval;var A=a(94);r.Glyph=A.Glyph;var p=a(111);r.HArea=p.HArea;var s=a(244);r.HBar=s.HBar;var d=a(246);r.HexTile=d.HexTile;var R=a(247);r.Image=R.Image;var o=a(249);r.ImageRGBA=o.ImageRGBA;var y=a(250);r.ImageURL=y.ImageURL;var h=a(92);r.Line=h.Line;var m=a(252);r.MultiLine=m.MultiLine;var B=a(253);r.MultiPolygons=B.MultiPolygons;var P=a(254);r.Oval=P.Oval;var G=a(110);r.Patch=G.Patch;var H=a(255);r.Patches=H.Patches;var I=a(256);r.Quad=I.Quad;var L=a(257);r.Quadratic=L.Quadratic;var M=a(258);r.Ray=M.Ray;var O=a(259);r.Rect=O.Rect;var x=a(260);r.Segment=x.Segment;var C=a(261);r.Step=C.Step;var E=a(262);r.Text=E.Text;var Q=a(113);r.VArea=Q.VArea;var S=a(263);r.VBar=S.VBar;var T=a(264);r.Wedge=T.Wedge;var V=a(93);r.XYGlyph=V.XYGlyph},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=e(1),r=e(93),n=e(100),a=e(28),_=e(24),o=i.__importStar(e(18)),d=e(10),h=e(88);class u extends r.XYGlyphView{_map_data(){\"data\"==this.model.properties.inner_radius.units?this.sinner_radius=this.sdist(this.renderer.xscale,this._x,this._inner_radius):this.sinner_radius=this._inner_radius,\"data\"==this.model.properties.outer_radius.units?this.souter_radius=this.sdist(this.renderer.xscale,this._x,this._outer_radius):this.souter_radius=this._outer_radius,this._angle=new _.NumberArray(this._start_angle.length);for(let e=0,t=this._start_angle.length;e=s&&u.push(e)}const l=this.model.properties.direction.value(),c=[];for(const e of u){const i=Math.atan2(s-this.sy[e],t-this.sx[e]);d.angle_between(-i,-this._start_angle[e],-this._end_angle[e],l)&&c.push(e)}return new h.Selection({indices:c})}draw_legend_for_index(e,t,s){n.generic_area_legend(this.visuals,e,t,s)}scenterxy(e){const t=(this.sinner_radius[e]+this.souter_radius[e])/2,s=(this._start_angle[e]+this._end_angle[e])/2;return[this.sx[e]+t*Math.cos(s),this.sy[e]+t*Math.sin(s)]}}s.AnnularWedgeView=u,u.__name__=\"AnnularWedgeView\";class l extends r.XYGlyph{constructor(e){super(e)}static init_AnnularWedge(){this.prototype.default_view=u,this.mixins([a.LineVector,a.FillVector]),this.define({direction:[o.Direction,\"anticlock\"],inner_radius:[o.DistanceSpec],outer_radius:[o.DistanceSpec],start_angle:[o.AngleSpec],end_angle:[o.AngleSpec]})}}s.AnnularWedge=l,l.__name__=\"AnnularWedge\",l.init_AnnularWedge()},\n", - " function _(s,i,e){Object.defineProperty(e,\"__esModule\",{value:!0});const t=s(1),r=s(93),n=s(28),a=t.__importStar(s(18)),_=s(32),u=s(88);class o extends r.XYGlyphView{_map_data(){\"data\"==this.model.properties.inner_radius.units?this.sinner_radius=this.sdist(this.renderer.xscale,this._x,this._inner_radius):this.sinner_radius=this._inner_radius,\"data\"==this.model.properties.outer_radius.units?this.souter_radius=this.sdist(this.renderer.xscale,this._x,this._outer_radius):this.souter_radius=this._outer_radius}_render(s,i,{sx:e,sy:t,sinner_radius:r,souter_radius:n}){for(const a of i)if(!isNaN(e[a]+t[a]+r[a]+n[a])){if(this.visuals.fill.doit){if(this.visuals.fill.set_vectorize(s,a),s.beginPath(),_.is_ie)for(const i of[!1,!0])s.arc(e[a],t[a],r[a],0,Math.PI,i),s.arc(e[a],t[a],n[a],Math.PI,0,!i);else s.arc(e[a],t[a],r[a],0,2*Math.PI,!0),s.arc(e[a],t[a],n[a],2*Math.PI,0,!1);s.fill()}this.visuals.line.doit&&(this.visuals.line.set_vectorize(s,a),s.beginPath(),s.arc(e[a],t[a],r[a],0,2*Math.PI),s.moveTo(e[a]+n[a],t[a]),s.arc(e[a],t[a],n[a],0,2*Math.PI),s.stroke())}}_hit_point(s){const{sx:i,sy:e}=s,t=this.renderer.xscale.invert(i),r=this.renderer.yscale.invert(e);let n,a,_,o;if(\"data\"==this.model.properties.outer_radius.units)n=t-this.max_outer_radius,_=t+this.max_outer_radius,a=r-this.max_outer_radius,o=r+this.max_outer_radius;else{const s=i-this.max_outer_radius,t=i+this.max_outer_radius;[n,_]=this.renderer.xscale.r_invert(s,t);const r=e-this.max_outer_radius,u=e+this.max_outer_radius;[a,o]=this.renderer.yscale.r_invert(r,u)}const d=[];for(const s of this.index.indices({x0:n,x1:_,y0:a,y1:o})){const i=this.souter_radius[s]**2,e=this.sinner_radius[s]**2,[n,a]=this.renderer.xscale.r_compute(t,this._x[s]),[_,u]=this.renderer.yscale.r_compute(r,this._y[s]),o=(n-a)**2+(_-u)**2;o<=i&&o>=e&&d.push(s)}return new u.Selection({indices:d})}draw_legend_for_index(s,{x0:i,y0:e,x1:t,y1:r},n){const a=n+1,_=new Array(a);_[n]=(i+t)/2;const u=new Array(a);u[n]=(e+r)/2;const o=.5*Math.min(Math.abs(t-i),Math.abs(r-e)),d=new Array(a);d[n]=.4*o;const h=new Array(a);h[n]=.8*o,this._render(s,[n],{sx:_,sy:u,sinner_radius:d,souter_radius:h})}}e.AnnulusView=o,o.__name__=\"AnnulusView\";class d extends r.XYGlyph{constructor(s){super(s)}static init_Annulus(){this.prototype.default_view=o,this.mixins([n.LineVector,n.FillVector]),this.define({inner_radius:[a.DistanceSpec],outer_radius:[a.DistanceSpec]})}}e.Annulus=d,d.__name__=\"Annulus\",d.init_Annulus()},\n", - " function _(e,i,s){Object.defineProperty(s,\"__esModule\",{value:!0});const t=e(1),r=e(93),n=e(100),a=e(28),_=t.__importStar(e(18));class c extends r.XYGlyphView{_map_data(){\"data\"==this.model.properties.radius.units?this.sradius=this.sdist(this.renderer.xscale,this._x,this._radius):this.sradius=this._radius}_render(e,i,{sx:s,sy:t,sradius:r,_start_angle:n,_end_angle:a}){if(this.visuals.line.doit){const _=this.model.properties.direction.value();for(const c of i)isNaN(s[c]+t[c]+r[c]+n[c]+a[c])||(e.beginPath(),e.arc(s[c],t[c],r[c],n[c],a[c],_),this.visuals.line.set_vectorize(e,c),e.stroke())}}draw_legend_for_index(e,i,s){n.generic_line_legend(this.visuals,e,i,s)}}s.ArcView=c,c.__name__=\"ArcView\";class d extends r.XYGlyph{constructor(e){super(e)}static init_Arc(){this.prototype.default_view=c,this.mixins(a.LineVector),this.define({direction:[_.Direction,\"anticlock\"],radius:[_.DistanceSpec],start_angle:[_.AngleSpec],end_angle:[_.AngleSpec]})}}s.Arc=d,d.__name__=\"Arc\",d.init_Arc()},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=e(1),n=e(28),c=e(94),o=e(100),_=e(37),r=s.__importStar(e(18));function a(e,t,i,s,n,c,o,_){const r=[],a=[[],[]];for(let a=0;a<=2;a++){let h,d,x;if(0===a?(d=6*e-12*i+6*n,h=-3*e+9*i-9*n+3*o,x=3*i-3*e):(d=6*t-12*s+6*c,h=-3*t+9*s-9*c+3*_,x=3*s-3*t),Math.abs(h)<1e-12){if(Math.abs(d)<1e-12)continue;const e=-x/d;0Math.max(s,i[e]));break}case\"min\":{const s=this.sdist(this.renderer.xscale,this._x,this._radius),i=this.sdist(this.renderer.yscale,this._y,this._radius);this.sradius=_.map(s,(s,e)=>Math.min(s,i[e]));break}}else this.sradius=this._radius,this.max_size=2*this.max_radius;else this.sradius=_.map(this._size,s=>s/2)}_mask_data(){const[s,i]=this.renderer.plot_view.frame.bbox.ranges;let e,t,r,a;if(null!=this._radius&&\"data\"==this.model.properties.radius.units){const n=s.start,h=s.end;[e,r]=this.renderer.xscale.r_invert(n,h),e-=this.max_radius,r+=this.max_radius;const d=i.start,l=i.end;[t,a]=this.renderer.yscale.r_invert(d,l),t-=this.max_radius,a+=this.max_radius}else{const n=s.start-this.max_size,h=s.end+this.max_size;[e,r]=this.renderer.xscale.r_invert(n,h);const d=i.start-this.max_size,l=i.end+this.max_size;[t,a]=this.renderer.yscale.r_invert(d,l)}return this.index.indices({x0:e,x1:r,y0:t,y1:a})}_render(s,i,{sx:e,sy:t,sradius:r}){for(const a of i)isNaN(e[a]+t[a]+r[a])||(s.beginPath(),s.arc(e[a],t[a],r[a],0,2*Math.PI,!1),this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(s,a),s.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(s,a),s.stroke()))}_hit_point(s){const{sx:i,sy:e}=s,t=this.renderer.xscale.invert(i),r=this.renderer.yscale.invert(e);let a,n,h,d;if(null!=this._radius&&\"data\"==this.model.properties.radius.units)a=t-this.max_radius,n=t+this.max_radius,h=r-this.max_radius,d=r+this.max_radius;else{const s=i-this.max_size,t=i+this.max_size;[a,n]=this.renderer.xscale.r_invert(s,t);const r=e-this.max_size,l=e+this.max_size;[h,d]=this.renderer.yscale.r_invert(r,l)}const l=this.index.indices({x0:a,x1:n,y0:h,y1:d}),_=[];if(null!=this._radius&&\"data\"==this.model.properties.radius.units)for(const s of l){const i=this.sradius[s]**2,[e,a]=this.renderer.xscale.r_compute(t,this._x[s]),[n,h]=this.renderer.yscale.r_compute(r,this._y[s]);(e-a)**2+(n-h)**2<=i&&_.push(s)}else for(const s of l){const t=this.sradius[s]**2;(this.sx[s]-i)**2+(this.sy[s]-e)**2<=t&&_.push(s)}return new c.Selection({indices:_})}_hit_span(s){const{sx:i,sy:e}=s,t=this.bounds();let r,a,n,h;if(\"h\"==s.direction){let s,e;if(n=t.y0,h=t.y1,null!=this._radius&&\"data\"==this.model.properties.radius.units)s=i-this.max_radius,e=i+this.max_radius,[r,a]=this.renderer.xscale.r_invert(s,e);else{const t=this.max_size/2;s=i-t,e=i+t,[r,a]=this.renderer.xscale.r_invert(s,e)}}else{let s,i;if(r=t.x0,a=t.x1,null!=this._radius&&\"data\"==this.model.properties.radius.units)s=e-this.max_radius,i=e+this.max_radius,[n,h]=this.renderer.yscale.r_invert(s,i);else{const t=this.max_size/2;s=e-t,i=e+t,[n,h]=this.renderer.yscale.r_invert(s,i)}}const d=[...this.index.indices({x0:r,x1:a,y0:n,y1:h})];return new c.Selection({indices:d})}_hit_rect(s){const{sx0:i,sx1:e,sy0:t,sy1:r}=s,[a,n]=this.renderer.xscale.r_invert(i,e),[h,d]=this.renderer.yscale.r_invert(t,r),l=[...this.index.indices({x0:a,x1:n,y0:h,y1:d})];return new c.Selection({indices:l})}_hit_poly(s){const{sx:i,sy:e}=s,t=l.range(0,this.sx.length),r=[];for(let s=0,a=t.length;s2*t)),i.data_changed=!1),this.visuals_changed&&(this._set_visuals(a),this.visuals_changed=!1),this.prog.set_uniform(\"u_pixel_ratio\",\"float\",[s.pixel_ratio]),this.prog.set_uniform(\"u_canvas_size\",\"vec2\",[s.width,s.height]),this.prog.set_attribute(\"a_sx\",\"float\",i.vbo_sx),this.prog.set_attribute(\"a_sy\",\"float\",i.vbo_sy),this.prog.set_attribute(\"a_size\",\"float\",i.vbo_s),this.prog.set_attribute(\"a_angle\",\"float\",i.vbo_a),0!=t.length)if(t.length===a)this.prog.draw(this.gl.POINTS,[0,a]);else if(a<65535){const e=window.navigator.userAgent;e.indexOf(\"MSIE \")+e.indexOf(\"Trident/\")+e.indexOf(\"Edge/\")>0&&n.logger.warn(\"WebGL warning: IE is known to produce 1px sprites whith selections.\"),this.index_buffer.set_size(2*t.length),this.index_buffer.set_data(0,new Uint16Array(t)),this.prog.draw(this.gl.POINTS,this.index_buffer)}else{const e=64e3,s=[];for(let t=0,i=Math.ceil(a/e);t2*t)):this.vbo_s.set_data(0,new Float32Array(this.glyph._size))}_set_visuals(t){u(this.prog,this.vbo_linewidth,\"a_linewidth\",t,this.glyph.visuals.line,\"line_width\"),f(this.prog,this.vbo_fg_color,\"a_fg_color\",t,this.glyph.visuals.line,\"line\"),f(this.prog,this.vbo_bg_color,\"a_bg_color\",t,this.glyph.visuals.fill,\"fill\"),this.prog.set_uniform(\"u_antialias\",\"float\",[.8])}}function b(t){return class extends d{get _marker_code(){return t}}}s.MarkerGL=d,d.__name__=\"MarkerGL\";const c=i.__importStar(t(240));s.AsteriskGL=b(c.asterisk),s.CircleGL=b(c.circle),s.CircleCrossGL=b(c.circlecross),s.CircleXGL=b(c.circlex),s.CrossGL=b(c.cross),s.DiamondGL=b(c.diamond),s.DiamondCrossGL=b(c.diamondcross),s.HexGL=b(c.hex),s.InvertedTriangleGL=b(c.invertedtriangle),s.SquareGL=b(c.square),s.SquareCrossGL=b(c.squarecross),s.SquareXGL=b(c.squarex),s.TriangleGL=b(c.triangle),s.XGL=b(c.x)},\n", - " function _(n,i,a){Object.defineProperty(a,\"__esModule\",{value:!0}),a.vertex_shader=\"\\nprecision mediump float;\\nconst float SQRT_2 = 1.4142135623730951;\\n//\\nuniform float u_pixel_ratio;\\nuniform vec2 u_canvas_size;\\nuniform vec2 u_offset;\\nuniform vec2 u_scale;\\nuniform float u_antialias;\\n//\\nattribute float a_sx;\\nattribute float a_sy;\\nattribute float a_size;\\nattribute float a_angle; // in radians\\nattribute float a_linewidth;\\nattribute vec4 a_fg_color;\\nattribute vec4 a_bg_color;\\n//\\nvarying float v_linewidth;\\nvarying float v_size;\\nvarying vec4 v_fg_color;\\nvarying vec4 v_bg_color;\\nvarying vec2 v_rotation;\\n\\nvoid main (void)\\n{\\n v_size = a_size * u_pixel_ratio;\\n v_linewidth = a_linewidth * u_pixel_ratio;\\n v_fg_color = a_fg_color;\\n v_bg_color = a_bg_color;\\n v_rotation = vec2(cos(-a_angle), sin(-a_angle));\\n vec2 pos = vec2(a_sx, a_sy); // in pixels\\n pos += 0.5; // make up for Bokeh's offset\\n pos /= u_canvas_size / u_pixel_ratio; // in 0..1\\n gl_Position = vec4(pos*2.0-1.0, 0.0, 1.0);\\n gl_Position.y *= -1.0;\\n gl_PointSize = SQRT_2 * v_size + 2.0 * (v_linewidth + 1.5*u_antialias);\\n}\\n\"},\n", - " function _(a,n,s){Object.defineProperty(s,\"__esModule\",{value:!0}),s.fragment_shader=a=>`\\nprecision mediump float;\\nconst float SQRT_2 = 1.4142135623730951;\\nconst float PI = 3.14159265358979323846264;\\n//\\nuniform float u_antialias;\\n//\\nvarying vec4 v_fg_color;\\nvarying vec4 v_bg_color;\\nvarying float v_linewidth;\\nvarying float v_size;\\nvarying vec2 v_rotation;\\n\\n${a}\\n\\nvec4 outline(float distance, float linewidth, float antialias, vec4 fg_color, vec4 bg_color)\\n{\\n vec4 frag_color;\\n float t = linewidth/2.0 - antialias;\\n float signed_distance = distance;\\n float border_distance = abs(signed_distance) - t;\\n float alpha = border_distance/antialias;\\n alpha = exp(-alpha*alpha);\\n\\n // If fg alpha is zero, it probably means no outline. To avoid a dark outline\\n // shining through due to aa, we set the fg color to the bg color. Avoid if (i.e. branching).\\n float select = float(bool(fg_color.a));\\n fg_color.rgb = select * fg_color.rgb + (1.0 - select) * bg_color.rgb;\\n // Similarly, if we want a transparent bg\\n select = float(bool(bg_color.a));\\n bg_color.rgb = select * bg_color.rgb + (1.0 - select) * fg_color.rgb;\\n\\n if( border_distance < 0.0)\\n frag_color = fg_color;\\n else if( signed_distance < 0.0 ) {\\n frag_color = mix(bg_color, fg_color, sqrt(alpha));\\n } else {\\n if( abs(signed_distance) < (linewidth/2.0 + antialias) ) {\\n frag_color = vec4(fg_color.rgb, fg_color.a * alpha);\\n } else {\\n discard;\\n }\\n }\\n return frag_color;\\n}\\n\\nvoid main()\\n{\\n vec2 P = gl_PointCoord.xy - vec2(0.5, 0.5);\\n P = vec2(v_rotation.x*P.x - v_rotation.y*P.y,\\n v_rotation.y*P.x + v_rotation.x*P.y);\\n float point_size = SQRT_2*v_size + 2.0 * (v_linewidth + 1.5*u_antialias);\\n float distance = marker(P*point_size, v_size);\\n gl_FragColor = outline(distance, v_linewidth, u_antialias, v_fg_color, v_bg_color);\\n}\\n`,s.circle=\"\\nfloat marker(vec2 P, float size)\\n{\\n return length(P) - size/2.0;\\n}\\n\",s.square=\"\\nfloat marker(vec2 P, float size)\\n{\\n return max(abs(P.x), abs(P.y)) - size/2.0;\\n}\\n\",s.diamond=\"\\nfloat marker(vec2 P, float size)\\n{\\n float x = SQRT_2 / 2.0 * (P.x * 1.5 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.5 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / (2.0 * SQRT_2);\\n return r1 / SQRT_2;\\n}\\n\",s.hex=\"\\nfloat marker(vec2 P, float size)\\n{\\n vec2 q = abs(P);\\n return max(q.y * 0.57735 + q.x - 1.0 * size/2.0, q.y - 0.866 * size/2.0);\\n}\\n\",s.triangle=\"\\nfloat marker(vec2 P, float size)\\n{\\n P.y -= size * 0.3;\\n float x = SQRT_2 / 2.0 * (P.x * 1.7 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.7 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / 1.6;\\n float r2 = P.y;\\n return max(r1 / SQRT_2, r2); // Intersect diamond with rectangle\\n}\\n\",s.invertedtriangle=\"\\nfloat marker(vec2 P, float size)\\n{\\n P.y += size * 0.3;\\n float x = SQRT_2 / 2.0 * (P.x * 1.7 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.7 + P.y);\\n float r1 = max(abs(x), abs(y)) - size / 1.6;\\n float r2 = - P.y;\\n return max(r1 / SQRT_2, r2); // Intersect diamond with rectangle\\n}\\n\",s.cross='\\nfloat marker(vec2 P, float size)\\n{\\n float square = max(abs(P.x), abs(P.y)) - size / 2.5; // 2.5 is a tweak\\n float cross = min(abs(P.x), abs(P.y)) - size / 100.0; // bit of \"width\" for aa\\n return max(square, cross);\\n}\\n',s.circlecross=\"\\nfloat marker(vec2 P, float size)\\n{\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(P.x - qs), abs(P.y - qs)) - qs;\\n float s2 = max(abs(P.x + qs), abs(P.y - qs)) - qs;\\n float s3 = max(abs(P.x - qs), abs(P.y + qs)) - qs;\\n float s4 = max(abs(P.x + qs), abs(P.y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float circle = length(P) - size/2.0;\\n float c1 = max(circle, s1);\\n float c2 = max(circle, s2);\\n float c3 = max(circle, s3);\\n float c4 = max(circle, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n\",s.squarecross=\"\\nfloat marker(vec2 P, float size)\\n{\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(P.x - qs), abs(P.y - qs)) - qs;\\n float s2 = max(abs(P.x + qs), abs(P.y - qs)) - qs;\\n float s3 = max(abs(P.x - qs), abs(P.y + qs)) - qs;\\n float s4 = max(abs(P.x + qs), abs(P.y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float square = max(abs(P.x), abs(P.y)) - size/2.0;\\n float c1 = max(square, s1);\\n float c2 = max(square, s2);\\n float c3 = max(square, s3);\\n float c4 = max(square, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n\",s.diamondcross=\"\\nfloat marker(vec2 P, float size)\\n{\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(P.x - qs), abs(P.y - qs)) - qs;\\n float s2 = max(abs(P.x + qs), abs(P.y - qs)) - qs;\\n float s3 = max(abs(P.x - qs), abs(P.y + qs)) - qs;\\n float s4 = max(abs(P.x + qs), abs(P.y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float x = SQRT_2 / 2.0 * (P.x * 1.5 - P.y);\\n float y = SQRT_2 / 2.0 * (P.x * 1.5 + P.y);\\n float diamond = max(abs(x), abs(y)) - size / (2.0 * SQRT_2);\\n diamond /= SQRT_2;\\n float c1 = max(diamond, s1);\\n float c2 = max(diamond, s2);\\n float c3 = max(diamond, s3);\\n float c4 = max(diamond, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n\",s.x='\\nfloat marker(vec2 P, float size)\\n{\\n float circle = length(P) - size / 1.6;\\n float X = min(abs(P.x - P.y), abs(P.x + P.y)) - size / 100.0; // bit of \"width\" for aa\\n return max(circle, X);\\n}\\n',s.circlex='\\nfloat marker(vec2 P, float size)\\n{\\n float x = P.x - P.y;\\n float y = P.x + P.y;\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(x - qs), abs(y - qs)) - qs;\\n float s2 = max(abs(x + qs), abs(y - qs)) - qs;\\n float s3 = max(abs(x - qs), abs(y + qs)) - qs;\\n float s4 = max(abs(x + qs), abs(y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float circle = length(P) - size/2.0;\\n float c1 = max(circle, s1);\\n float c2 = max(circle, s2);\\n float c3 = max(circle, s3);\\n float c4 = max(circle, s4);\\n // Union\\n float almost = min(min(min(c1, c2), c3), c4);\\n // In this case, the X is also outside of the main shape\\n float Xmask = length(P) - size / 1.6; // a circle\\n float X = min(abs(P.x - P.y), abs(P.x + P.y)) - size / 100.0; // bit of \"width\" for aa\\n return min(max(X, Xmask), almost);\\n}\\n',s.squarex=\"\\nfloat marker(vec2 P, float size)\\n{\\n float x = P.x - P.y;\\n float y = P.x + P.y;\\n // Define quadrants\\n float qs = size / 2.0; // quadrant size\\n float s1 = max(abs(x - qs), abs(y - qs)) - qs;\\n float s2 = max(abs(x + qs), abs(y - qs)) - qs;\\n float s3 = max(abs(x - qs), abs(y + qs)) - qs;\\n float s4 = max(abs(x + qs), abs(y + qs)) - qs;\\n // Intersect main shape with quadrants (to form cross)\\n float square = max(abs(P.x), abs(P.y)) - size/2.0;\\n float c1 = max(square, s1);\\n float c2 = max(square, s2);\\n float c3 = max(square, s3);\\n float c4 = max(square, s4);\\n // Union\\n return min(min(min(c1, c2), c3), c4);\\n}\\n\",s.asterisk='\\nfloat marker(vec2 P, float size)\\n{\\n // Masks\\n float diamond = max(abs(SQRT_2 / 2.0 * (P.x - P.y)), abs(SQRT_2 / 2.0 * (P.x + P.y))) - size / (2.0 * SQRT_2);\\n float square = max(abs(P.x), abs(P.y)) - size / (2.0 * SQRT_2);\\n // Shapes\\n float X = min(abs(P.x - P.y), abs(P.x + P.y)) - size / 100.0; // bit of \"width\" for aa\\n float cross = min(abs(P.x), abs(P.y)) - size / 100.0; // bit of \"width\" for aa\\n // Result is union of masked shapes\\n return min(max(X, diamond), max(cross, square));\\n}\\n'},\n", - " function _(e,t,n){Object.defineProperty(n,\"__esModule\",{value:!0});const a=e(1),i=e(93),l=e(28),s=a.__importStar(e(18));class c extends i.XYGlyphView{}n.CenterRotatableView=c,c.__name__=\"CenterRotatableView\";class o extends i.XYGlyph{constructor(e){super(e)}static init_CenterRotatable(){this.mixins([l.LineVector,l.FillVector]),this.define({angle:[s.AngleSpec,0],width:[s.DistanceSpec],height:[s.DistanceSpec]})}}n.CenterRotatable=o,o.__name__=\"CenterRotatable\",o.init_CenterRotatable()},\n", - " function _(e,l,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=e(243);class t extends s.EllipseOvalView{}i.EllipseView=t,t.__name__=\"EllipseView\";class _ extends s.EllipseOval{constructor(e){super(e)}static init_Ellipse(){this.prototype.default_view=t}}i.Ellipse=_,_.__name__=\"Ellipse\",_.init_Ellipse()},\n", - " function _(t,s,i){Object.defineProperty(i,\"__esModule\",{value:!0});const e=t(1),h=t(241),a=e.__importStar(t(101)),r=t(88);class n extends h.CenterRotatableView{_set_data(){this.max_w2=0,\"data\"==this.model.properties.width.units&&(this.max_w2=this.max_width/2),this.max_h2=0,\"data\"==this.model.properties.height.units&&(this.max_h2=this.max_height/2)}_map_data(){\"data\"==this.model.properties.width.units?this.sw=this.sdist(this.renderer.xscale,this._x,this._width,\"center\"):this.sw=this._width,\"data\"==this.model.properties.height.units?this.sh=this.sdist(this.renderer.yscale,this._y,this._height,\"center\"):this.sh=this._height}_render(t,s,{sx:i,sy:e,sw:h,sh:a,_angle:r}){for(const n of s)isNaN(i[n]+e[n]+h[n]+a[n]+r[n])||(t.beginPath(),t.ellipse(i[n],e[n],h[n]/2,a[n]/2,r[n],0,2*Math.PI),this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(t,n),t.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(t,n),t.stroke()))}_hit_point(t){let s,i,e,h,n,_,l,d,o;const{sx:x,sy:m}=t,w=this.renderer.xscale.invert(x),c=this.renderer.yscale.invert(m);\"data\"==this.model.properties.width.units?(s=w-this.max_width,i=w+this.max_width):(_=x-this.max_width,l=x+this.max_width,[s,i]=this.renderer.xscale.r_invert(_,l)),\"data\"==this.model.properties.height.units?(e=c-this.max_height,h=c+this.max_height):(d=m-this.max_height,o=m+this.max_height,[e,h]=this.renderer.yscale.r_invert(d,o));const p=this.index.indices({x0:s,x1:i,y0:e,y1:h}),y=[];for(const t of p)n=a.point_in_ellipse(x,m,this._angle[t],this.sh[t]/2,this.sw[t]/2,this.sx[t],this.sy[t]),n&&y.push(t);return new r.Selection({indices:y})}draw_legend_for_index(t,{x0:s,y0:i,x1:e,y1:h},a){const r=a+1,n=new Array(r);n[a]=(s+e)/2;const _=new Array(r);_[a]=(i+h)/2;const l=this.sw[a]/this.sh[a],d=.8*Math.min(Math.abs(e-s),Math.abs(h-i)),o=new Array(r),x=new Array(r);l>1?(o[a]=d,x[a]=d/l):(o[a]=d*l,x[a]=d),this._render(t,[a],{sx:n,sy:_,sw:o,sh:x,_angle:[0]})}_bounds({x0:t,x1:s,y0:i,y1:e}){return{x0:t-this.max_w2,x1:s+this.max_w2,y0:i-this.max_h2,y1:e+this.max_h2}}}i.EllipseOvalView=n,n.__name__=\"EllipseOvalView\";class _ extends h.CenterRotatable{constructor(t){super(t)}}i.EllipseOval=_,_.__name__=\"EllipseOval\"},\n", - " function _(t,e,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=t(1),h=t(245),r=t(24),_=i.__importStar(t(18));class a extends h.BoxView{scenterxy(t){return[(this.sleft[t]+this.sright[t])/2,this.sy[t]]}_lrtb(t){return[Math.min(this._left[t],this._right[t]),Math.max(this._left[t],this._right[t]),this._y[t]+.5*this._height[t],this._y[t]-.5*this._height[t]]}_map_data(){this.sy=this.renderer.yscale.v_compute(this._y),this.sh=this.sdist(this.renderer.yscale,this._y,this._height,\"center\"),this.sleft=this.renderer.xscale.v_compute(this._left),this.sright=this.renderer.xscale.v_compute(this._right);const t=this.sy.length;this.stop=new r.NumberArray(t),this.sbottom=new r.NumberArray(t);for(let e=0;e{t.beginPath(),t.rect(i[a],r[a],s[a]-i[a],n[a]-r[a]),t.fill()},()=>this.renderer.request_render()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(t,a),t.beginPath(),t.rect(i[a],r[a],s[a]-i[a],n[a]-r[a]),t.stroke()))}_clamp_viewport(){const t=this.renderer.plot_view.frame.bbox.h_range,e=this.renderer.plot_view.frame.bbox.v_range,i=this.stop.length;for(let s=0;sthis._update_image())}_update_image(){null!=this.image_data&&(this._set_data(null),this.renderer.plot_view.request_render())}_flat_img_to_buf8(e){return this.model.color_mapper.rgba_mapper.v_compute(e)}}a.ImageView=r,r.__name__=\"ImageView\";class o extends i.ImageBase{constructor(e){super(e)}static init_Image(){this.prototype.default_view=r,this.define({color_mapper:[s.Instance,()=>new n.LinearColorMapper({palette:[\"#000000\",\"#252525\",\"#525252\",\"#737373\",\"#969696\",\"#bdbdbd\",\"#d9d9d9\",\"#f0f0f0\",\"#ffffff\"]})]})}}a.Image=o,o.__name__=\"Image\",o.init_Image()},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=e(1),a=e(93),h=e(24),_=i.__importStar(e(18)),n=e(88),r=e(9),d=e(30),l=e(11);class g extends a.XYGlyphView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.global_alpha.change,()=>this.renderer.request_render())}_render(e,t,{image_data:s,sx:i,sy:a,sw:h,sh:_}){const n=e.getImageSmoothingEnabled();e.setImageSmoothingEnabled(!1),e.globalAlpha=this.model.global_alpha;for(const n of t){if(null==s[n]||isNaN(i[n]+a[n]+h[n]+_[n]))continue;const t=a[n];e.translate(0,t),e.scale(1,-1),e.translate(0,-t),e.drawImage(s[n],0|i[n],0|a[n],h[n],_[n]),e.translate(0,t),e.scale(1,-1),e.translate(0,-t)}e.setImageSmoothingEnabled(n)}_set_data(e){this._set_width_heigh_data();for(let t=0,s=this._image.length;tthis.renderer.request_render())}_index_data(e){const{data_size:t}=this;for(let s=0;snull));const{retry_attempts:e,retry_timeout:t}=this.model;for(let s=0,r=this._url.length;s{this.image[s]=e,this.renderer.request_render()},attempts:e+1,timeout:t})}const s=\"data\"==this.model.properties.w.units,r=\"data\"==this.model.properties.h.units,i=this._x.length,n=new a.NumberArray(s?2*i:i),_=new a.NumberArray(r?2*i:i),{anchor:c}=this.model;function l(e,t){switch(c){case\"top_left\":case\"bottom_left\":case\"center_left\":return[e,e+t];case\"top_center\":case\"bottom_center\":case\"center\":return[e-t/2,e+t/2];case\"top_right\":case\"bottom_right\":case\"center_right\":return[e-t,e]}}function d(e,t){switch(c){case\"top_left\":case\"top_center\":case\"top_right\":return[e,e-t];case\"bottom_left\":case\"bottom_center\":case\"bottom_right\":return[e+t,e];case\"center_left\":case\"center\":case\"center_right\":return[e+t/2,e-t/2]}}if(s)for(let e=0;eNaN),t=null!=this.model.h?this._h:h.map(this._x,()=>NaN);switch(this.model.properties.w.units){case\"data\":this.sw=this.sdist(this.renderer.xscale,this._x,e,\"edge\",this.model.dilate);break;case\"screen\":this.sw=e}switch(this.model.properties.h.units){case\"data\":this.sh=this.sdist(this.renderer.yscale,this._y,t,\"edge\",this.model.dilate);break;case\"screen\":this.sh=t}}_render(e,t,{image:s,sx:r,sy:i,sw:a,sh:n,_angle:h}){const{frame:o}=this.renderer.plot_view;e.rect(o.bbox.left+1,o.bbox.top+1,o.bbox.width-2,o.bbox.height-2),e.clip();let _=!0;for(const o of t){if(isNaN(r[o]+i[o]+h[o]))continue;const t=s[o];null!=t?this._render_image(e,o,t,r,i,a,n,h):_=!1}_&&!this._images_rendered&&(this._images_rendered=!0,this.notify_finished())}_final_sx_sy(e,t,s,r,i){switch(e){case\"top_left\":return[t,s];case\"top_center\":return[t-r/2,s];case\"top_right\":return[t-r,s];case\"center_right\":return[t-r,s-i/2];case\"bottom_right\":return[t-r,s-i];case\"bottom_center\":return[t-r/2,s-i];case\"bottom_left\":return[t,s-i];case\"center_left\":return[t,s-i/2];case\"center\":return[t-r/2,s-i/2]}}_render_image(e,t,s,r,i,a,n,h){isNaN(a[t])&&(a[t]=s.width),isNaN(n[t])&&(n[t]=s.height);const{anchor:o}=this.model,[_,c]=this._final_sx_sy(o,r[t],i[t],a[t],n[t]);e.save(),e.globalAlpha=this.model.global_alpha;const l=a[t]/2,d=n[t]/2;h[t]?(e.translate(_,c),e.translate(l,d),e.rotate(h[t]),e.translate(-l,-d),e.drawImage(s,0,0,a[t],n[t]),e.translate(l,d),e.rotate(-h[t]),e.translate(-l,-d),e.translate(-_,-c)):e.drawImage(s,_,c,a[t],n[t]),e.restore()}bounds(){return this._bounds_rect}}s.ImageURLView=_,_.__name__=\"ImageURLView\";class c extends i.XYGlyph{constructor(e){super(e)}static init_ImageURL(){this.prototype.default_view=_,this.define({url:[n.StringSpec],anchor:[n.Anchor,\"top_left\"],global_alpha:[n.Number,1],angle:[n.AngleSpec,0],w:[n.DistanceSpec],h:[n.DistanceSpec],dilate:[n.Boolean,!1],retry_attempts:[n.Number,0],retry_timeout:[n.Number,0]})}}s.ImageURL=c,c.__name__=\"ImageURL\",c.init_ImageURL()},\n", - " function _(i,e,t){Object.defineProperty(t,\"__esModule\",{value:!0});const s=i(19);class a{constructor(i,e={}){this._image=new Image,this._finished=!1;const{attempts:t=1,timeout:a=1}=e;this.promise=new Promise((o,n)=>{this._image.crossOrigin=\"anonymous\";let r=0;this._image.onerror=()=>{if(++r==t){const a=`unable to load ${i} image after ${t} attempts`;if(s.logger.warn(a),null==this._image.crossOrigin)return void(null!=e.failed&&e.failed());s.logger.warn(`attempting to load ${i} without a cross origin policy`),this._image.crossOrigin=null,r=0}setTimeout(()=>this._image.src=i,a)},this._image.onload=()=>{this._finished=!0,null!=e.loaded&&e.loaded(this._image),o(this._image)},this._image.src=i})}get finished(){return this._finished}get image(){return this._image}}t.ImageLoader=a,a.__name__=\"ImageLoader\"},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=e(1),n=e(37),o=e(28),l=s.__importStar(e(101)),r=s.__importStar(e(18)),_=e(12),c=e(13),a=e(94),h=e(100),d=e(88);class y extends a.GlyphView{_project_data(){n.inplace.project_xy(this._xs.array,this._ys.array)}_index_data(e){const{data_size:t}=this;for(let i=0;i0&&o.set(e,i)}return new d.Selection({indices:[...o.keys()],multiline_indices:c.to_object(o)})}get_interpolation_hit(e,t,i){const s=this._xs.get(e),n=this._ys.get(e),o=s[t],l=n[t],r=s[t+1],_=n[t+1];return h.line_interpolation(this.renderer,i,o,l,r,_)}draw_legend_for_index(e,t,i){h.generic_line_legend(this.visuals,e,t,i)}scenterxy(){throw new Error(this+\".scenterxy() is not implemented\")}}i.MultiLineView=y,y.__name__=\"MultiLineView\";class x extends a.Glyph{constructor(e){super(e)}static init_MultiLine(){this.prototype.default_view=y,this.define({xs:[r.XCoordinateSeqSpec,{field:\"xs\"}],ys:[r.YCoordinateSeqSpec,{field:\"ys\"}]}),this.mixins(o.LineVector)}}i.MultiLine=x,x.__name__=\"MultiLine\",x.init_MultiLine()},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=e(1),n=e(95),o=e(94),r=e(100),l=e(12),h=e(12),_=e(28),a=i.__importStar(e(101)),d=i.__importStar(e(18)),c=e(88),x=e(11);class y extends o.GlyphView{_project_data(){}_index_data(e){const{min:t,max:s}=Math,{data_size:i}=this;for(let n=0;n1&&d.length>1)for(let s=1,i=n.length;s{this._inner_loop(e,t,o),e.fill(\"evenodd\")},()=>this.renderer.request_render()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,n),this._inner_loop(e,t,o),e.stroke())}}_hit_rect(e){const{sx0:t,sx1:s,sy0:i,sy1:n}=e,o=[t,s,s,t],r=[i,i,n,n],[l,h]=this.renderer.xscale.r_invert(t,s),[_,d]=this.renderer.yscale.r_invert(i,n),x=this.index.indices({x0:l,x1:h,y0:_,y1:d}),y=[];for(const e of x){const t=this.sxs[e],s=this.sys[e];let i=!0;for(let e=0,n=t.length;e1){let r=!1;for(let e=1;ethis._inner_loop(e,t,r,e.fill),()=>this.renderer.request_render()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,n),this._inner_loop(e,t,r,e.stroke))}}_hit_rect(e){const{sx0:t,sx1:s,sy0:i,sy1:n}=e,r=[t,s,s,t],o=[i,i,n,n],[a,c]=this.renderer.xscale.r_invert(t,s),[h,d]=this.renderer.yscale.r_invert(i,n),y=this.index.indices({x0:a,x1:c,y0:h,y1:d}),p=[];for(const e of y){const t=this.sxs.get(e),s=this.sys.get(e);let i=!0;for(let e=0,n=t.length;e1&&(e.stroke(),s=!1)}s?(e.lineTo(t,a),e.lineTo(l,_)):(e.beginPath(),e.moveTo(i[r],n[r]),s=!0),o=r}e.lineTo(i[r-1],n[r-1]),e.stroke()}}draw_legend_for_index(e,t,i){o.generic_line_legend(this.visuals,e,t,i)}}i.StepView=a,a.__name__=\"StepView\";class _ extends s.XYGlyph{constructor(e){super(e)}static init_Step(){this.prototype.default_view=a,this.mixins(r.LineVector),this.define({mode:[l.StepMode,\"before\"]})}}i.Step=_,_.__name__=\"Step\",_.init_Step()},\n", - " function _(t,s,e){Object.defineProperty(e,\"__esModule\",{value:!0});const i=t(1),n=t(93),_=t(28),o=i.__importStar(t(101)),h=i.__importStar(t(18)),l=t(159),a=t(11),r=t(88);class c extends n.XYGlyphView{_rotate_point(t,s,e,i,n){return[(t-e)*Math.cos(n)-(s-i)*Math.sin(n)+e,(t-e)*Math.sin(n)+(s-i)*Math.cos(n)+i]}_text_bounds(t,s,e,i){return[[t,t+e,t+e,t,t],[s,s,s-i,s-i,s]]}_render(t,s,{sx:e,sy:i,_x_offset:n,_y_offset:_,_angle:o,_text:h}){this._sys=[],this._sxs=[];for(const a of s)if(this._sxs[a]=[],this._sys[a]=[],!isNaN(e[a]+i[a]+n[a]+_[a]+o[a])&&null!=h[a]&&this.visuals.text.doit){const s=\"\"+h[a];t.save(),t.translate(e[a]+n[a],i[a]+_[a]),t.rotate(o[a]),this.visuals.text.set_vectorize(t,a);const r=this.visuals.text.cache_select(\"font\",a),{height:c}=l.measure_font(r),x=this.visuals.text.text_line_height.value()*c;if(-1==s.indexOf(\"\\n\")){t.fillText(s,0,0);const o=e[a]+n[a],h=i[a]+_[a],l=t.measureText(s).width,[r,c]=this._text_bounds(o,h,l,x);this._sxs[a].push(r),this._sys[a].push(c)}else{const o=s.split(\"\\n\"),h=x*o.length,l=this.visuals.text.cache_select(\"text_baseline\",a);let r;switch(l){case\"top\":r=0;break;case\"middle\":r=-h/2+x/2;break;case\"bottom\":r=-h+x;break;default:r=0,console.warn(`'${l}' baseline not supported with multi line text`)}for(const s of o){t.fillText(s,0,r);const o=e[a]+n[a],h=r+i[a]+_[a],l=t.measureText(s).width,[c,u]=this._text_bounds(o,h,l,x);this._sxs[a].push(c),this._sys[a].push(u),r+=x}}t.restore()}}_hit_point(t){const{sx:s,sy:e}=t,i=[];for(let t=0;tthis.request_render())}_draw_regions(i){if(!this.visuals.band_fill.doit&&!this.visuals.band_hatch.doit)return;this.visuals.band_fill.set_value(i);const[e,t]=this.grid_coords(\"major\",!1);for(let s=0;s{i.fillRect(n[0],r[0],o[1]-n[0],d[1]-r[0])},()=>this.request_render())}}_draw_grids(i){if(!this.visuals.grid_line.doit)return;const[e,t]=this.grid_coords(\"major\");this._draw_grid_helper(i,this.visuals.grid_line,e,t)}_draw_minor_grids(i){if(!this.visuals.minor_grid_line.doit)return;const[e,t]=this.grid_coords(\"minor\");this._draw_grid_helper(i,this.visuals.minor_grid_line,e,t)}_draw_grid_helper(i,e,t,s){e.set_value(i),i.beginPath();for(let e=0;et[1]&&(n=t[1]);else{[s,n]=t;for(const i of this.plot_view.axis_views)i.dimension==this.model.dimension&&i.model.x_range_name==this.model.x_range_name&&i.model.y_range_name==this.model.y_range_name&&([s,n]=i.computed_bounds)}return[s,n]}grid_coords(i,e=!0){const t=this.model.dimension,s=(t+1)%2,[n,r]=this.ranges();let[o,d]=this.computed_bounds();[o,d]=[Math.min(o,d),Math.max(o,d)];const _=[[],[]],a=this.model.get_ticker();if(null==a)return _;const l=a.get_ticks(o,d,n,r.min,{})[i],h=n.min,c=n.max,u=r.min,m=r.max;e||(l[0]!=h&&l.splice(0,0,h),l[l.length-1]!=c&&l.push(c));for(let i=0;ithis.rebuild())}get child_models(){return this.model.children}}i.BoxView=c,c.__name__=\"BoxView\";class r extends s.LayoutDOM{constructor(e){super(e)}static init_Box(){this.define({children:[o.Array,[]],spacing:[o.Number,0]})}}i.Box=r,r.__name__=\"Box\",r.init_Box()},\n", - " function _(i,t,e){Object.defineProperty(e,\"__esModule\",{value:!0});const s=i(81),o=i(20),l=i(72),n=i(19),h=i(8),a=i(115),r=i(78),_=i(212),d=i(273),c=i(77);class u extends r.DOMView{constructor(){super(...arguments),this._idle_notified=!1,this._offset_parent=null,this._viewport={}}initialize(){super.initialize(),this.el.style.position=this.is_root?\"relative\":\"absolute\",this._child_views=new Map}async lazy_initialize(){await this.build_child_views()}remove(){for(const i of this.child_views)i.remove();this._child_views.clear(),super.remove()}connect_signals(){super.connect_signals(),this.is_root&&(this._on_resize=()=>this.resize_layout(),window.addEventListener(\"resize\",this._on_resize),this._parent_observer=setInterval(()=>{const i=this.el.offsetParent;this._offset_parent!=i&&(this._offset_parent=i,null!=i&&(this.compute_viewport(),this.invalidate_layout()))},250));const i=this.model.properties;this.on_change([i.width,i.height,i.min_width,i.min_height,i.max_width,i.max_height,i.margin,i.width_policy,i.height_policy,i.sizing_mode,i.aspect_ratio,i.visible],()=>this.invalidate_layout()),this.on_change([i.background,i.css_classes],()=>this.invalidate_render())}disconnect_signals(){null!=this._parent_observer&&clearTimeout(this._parent_observer),null!=this._on_resize&&window.removeEventListener(\"resize\",this._on_resize),super.disconnect_signals()}css_classes(){return super.css_classes().concat(this.model.css_classes)}get child_views(){return this.child_models.map(i=>this._child_views.get(i))}async build_child_views(){await a.build_views(this._child_views,this.child_models,{parent:this})}render(){super.render(),l.empty(this.el);const{background:i}=this.model;this.el.style.backgroundColor=null!=i?i:\"\",l.classes(this.el).clear().add(...this.css_classes());for(const i of this.child_views)this.el.appendChild(i.el),i.render()}update_layout(){for(const i of this.child_views)i.update_layout();this._update_layout()}update_position(){this.el.style.display=this.model.visible?\"block\":\"none\";const i=this.is_root?this.layout.sizing.margin:void 0;l.position(this.el,this.layout.bbox,i);for(const i of this.child_views)i.update_position()}after_layout(){for(const i of this.child_views)i.after_layout();this._has_finished=!0}compute_viewport(){this._viewport=this._viewport_size()}renderTo(i){i.appendChild(this.el),this._offset_parent=this.el.offsetParent,this.compute_viewport(),this.build()}build(){return this.assert_root(),this.render(),this.update_layout(),this.compute_layout(),this}async rebuild(){await this.build_child_views(),this.invalidate_render()}compute_layout(){const i=Date.now();this.layout.compute(this._viewport),this.update_position(),this.after_layout(),n.logger.debug(`layout computed in ${Date.now()-i} ms`),this.notify_finished()}resize_layout(){this.root.compute_viewport(),this.root.compute_layout()}invalidate_layout(){this.root.update_layout(),this.root.compute_layout()}invalidate_render(){this.render(),this.invalidate_layout()}has_finished(){if(!super.has_finished())return!1;for(const i of this.child_views)if(!i.has_finished())return!1;return!0}notify_finished(){this.is_root?!this._idle_notified&&this.has_finished()&&null!=this.model.document&&(this._idle_notified=!0,this.model.document.notify_idle(this.model)):this.root.notify_finished()}_width_policy(){return null!=this.model.width?\"fixed\":\"fit\"}_height_policy(){return null!=this.model.height?\"fixed\":\"fit\"}box_sizing(){let{width_policy:i,height_policy:t,aspect_ratio:e}=this.model;\"auto\"==i&&(i=this._width_policy()),\"auto\"==t&&(t=this._height_policy());const{sizing_mode:s}=this.model;if(null!=s)if(\"fixed\"==s)i=t=\"fixed\";else if(\"stretch_both\"==s)i=t=\"max\";else if(\"stretch_width\"==s)i=\"max\";else if(\"stretch_height\"==s)t=\"max\";else switch(null==e&&(e=\"auto\"),s){case\"scale_width\":i=\"max\",t=\"min\";break;case\"scale_height\":i=\"min\",t=\"max\";break;case\"scale_both\":i=\"max\",t=\"max\"}const o={width_policy:i,height_policy:t},{min_width:l,min_height:n}=this.model;null!=l&&(o.min_width=l),null!=n&&(o.min_height=n);const{width:a,height:r}=this.model;null!=a&&(o.width=a),null!=r&&(o.height=r);const{max_width:_,max_height:d}=this.model;null!=_&&(o.max_width=_),null!=d&&(o.max_height=d),\"auto\"==e&&null!=a&&null!=r?o.aspect=a/r:h.isNumber(e)&&(o.aspect=e);const{margin:c}=this.model;if(null!=c)if(h.isNumber(c))o.margin={top:c,right:c,bottom:c,left:c};else if(2==c.length){const[i,t]=c;o.margin={top:i,right:t,bottom:i,left:t}}else{const[i,t,e,s]=c;o.margin={top:i,right:t,bottom:e,left:s}}o.visible=this.model.visible;const{align:u}=this.model;return h.isArray(u)?[o.halign,o.valign]=u:o.halign=o.valign=u,o}_viewport_size(){return l.undisplayed(this.el,()=>{let i=this.el;for(;i=i.parentElement;){if(i.classList.contains(d.bk_root))continue;if(i==document.body){const{margin:{left:i,right:t,top:e,bottom:s}}=l.extents(document.body);return{width:Math.ceil(document.documentElement.clientWidth-i-t),height:Math.ceil(document.documentElement.clientHeight-e-s)}}const{padding:{left:t,right:e,top:s,bottom:o}}=l.extents(i),{width:n,height:h}=i.getBoundingClientRect(),a=Math.ceil(n-t-e),r=Math.ceil(h-s-o);if(a>0||r>0)return{width:a>0?a:void 0,height:r>0?r:void 0}}return{}})}export(i,t=!0){const e=\"png\"==i?\"canvas\":\"svg\",s=new c.CanvasLayer(e,t),{width:o,height:l}=this.layout.bbox;s.resize(o,l);for(const e of this.child_views){const o=e.export(i,t),{x:l,y:n}=e.layout.bbox;s.ctx.drawImage(o.canvas,l,n)}return s}serializable_state(){return Object.assign(Object.assign({},super.serializable_state()),{bbox:this.layout.bbox.box,children:this.child_views.map(i=>i.serializable_state())})}}e.LayoutDOMView=u,u.__name__=\"LayoutDOMView\";class m extends s.Model{constructor(i){super(i)}static init_LayoutDOM(){this.define(i=>{const{Boolean:t,Number:e,String:s,Null:l,Auto:n,Color:h,Array:a,Tuple:r,Or:d}=i,c=r(e,e),u=r(e,e,e,e);return{width:[d(e,l),null],height:[d(e,l),null],min_width:[d(e,l),null],min_height:[d(e,l),null],max_width:[d(e,l),null],max_height:[d(e,l),null],margin:[d(e,c,u),[0,0,0,0]],width_policy:[d(_.SizingPolicy,n),\"auto\"],height_policy:[d(_.SizingPolicy,n),\"auto\"],aspect_ratio:[d(e,n,l),null],sizing_mode:[d(o.SizingMode,l),null],visible:[t,!0],disabled:[t,!1],align:[d(o.Align,r(o.Align,o.Align)),\"start\"],background:[d(h,l),null],css_classes:[a(s),[]]}})}}e.LayoutDOM=m,m.__name__=\"LayoutDOM\",m.init_LayoutDOM()},\n", - " function _(e,o,t){Object.defineProperty(t,\"__esModule\",{value:!0}),t.bk_root=\"bk-root\"},\n", - " function _(t,o,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=t(1),e=t(271),n=t(216),l=s.__importStar(t(18));class u extends e.BoxView{_update_layout(){const t=this.child_views.map(t=>t.layout);this.layout=new n.Column(t),this.layout.rows=this.model.rows,this.layout.spacing=[this.model.spacing,0],this.layout.set_sizing(this.box_sizing())}}i.ColumnView=u,u.__name__=\"ColumnView\";class _ extends e.Box{constructor(t){super(t)}static init_Column(){this.prototype.default_view=u,this.define({rows:[l.Any,\"auto\"]})}}i.Column=_,_.__name__=\"Column\",_.init_Column()},\n", - " function _(t,i,s){Object.defineProperty(s,\"__esModule\",{value:!0});const o=t(1),e=t(272),n=t(216),l=o.__importStar(t(18));class r extends e.LayoutDOMView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.children.change,()=>this.rebuild())}get child_models(){return this.model.children.map(([t])=>t)}_update_layout(){this.layout=new n.Grid,this.layout.rows=this.model.rows,this.layout.cols=this.model.cols,this.layout.spacing=this.model.spacing;for(const[t,i,s,o,e]of this.model.children){const n=this._child_views.get(t);this.layout.items.push({layout:n.layout,row:i,col:s,row_span:o,col_span:e})}this.layout.set_sizing(this.box_sizing())}}s.GridBoxView=r,r.__name__=\"GridBoxView\";class a extends e.LayoutDOM{constructor(t){super(t)}static init_GridBox(){this.prototype.default_view=r,this.define({children:[l.Array,[]],rows:[l.Any,\"auto\"],cols:[l.Any,\"auto\"],spacing:[l.Any,0]})}}s.GridBox=a,a.__name__=\"GridBox\",a.init_GridBox()},\n", - " function _(e,t,o){Object.defineProperty(o,\"__esModule\",{value:!0});const s=e(272),_=e(212);class n extends s.LayoutDOMView{get child_models(){return[]}_update_layout(){this.layout=new _.ContentBox(this.el),this.layout.set_sizing(this.box_sizing())}}o.HTMLBoxView=n,n.__name__=\"HTMLBoxView\";class i extends s.LayoutDOM{constructor(e){super(e)}}o.HTMLBox=i,i.__name__=\"HTMLBox\"},\n", - " function _(t,o,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=t(1),e=t(271),_=t(216),a=s.__importStar(t(18));class n extends e.BoxView{_update_layout(){const t=this.child_views.map(t=>t.layout);this.layout=new _.Row(t),this.layout.cols=this.model.cols,this.layout.spacing=[0,this.model.spacing],this.layout.set_sizing(this.box_sizing())}}i.RowView=n,n.__name__=\"RowView\";class l extends e.Box{constructor(t){super(t)}static init_Row(){this.prototype.default_view=n,this.define({cols:[a.Any,\"auto\"]})}}i.Row=l,l.__name__=\"Row\",l.init_Row()},\n", - " function _(e,t,a){Object.defineProperty(a,\"__esModule\",{value:!0});const i=e(272),s=e(212);class _ extends i.LayoutDOMView{get child_models(){return[]}_update_layout(){this.layout=new s.LayoutItem,this.layout.set_sizing(this.box_sizing())}}a.SpacerView=_,_.__name__=\"SpacerView\";class o extends i.LayoutDOM{constructor(e){super(e)}static init_Spacer(){this.prototype.default_view=_}}a.Spacer=o,o.__name__=\"Spacer\",o.init_Spacer()},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=e(1),a=e(212),l=e(72),h=e(9),o=i.__importStar(e(18)),c=e(272),d=e(81),r=e(173),n=e(280),_=e(281),b=e(282),p=i.__importDefault(e(283)),u=i.__importDefault(e(284)),m=i.__importDefault(e(285));class v extends c.LayoutDOMView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.tabs.change,()=>this.rebuild()),this.connect(this.model.properties.active.change,()=>this.on_active_change())}styles(){return[...super.styles(),p.default,u.default,m.default]}get child_models(){return this.model.tabs.map(e=>e.child)}_update_layout(){const e=this.model.tabs_location,t=\"above\"==e||\"below\"==e,{scroll_el:s,headers_el:i}=this;this.header=new class extends a.ContentBox{_measure(e){const a=l.size(s),o=l.children(i).slice(0,3).map(e=>l.size(e)),{width:c,height:d}=super._measure(e);if(t){const t=a.width+h.sum(o.map(e=>e.width));return{width:e.width!=1/0?e.width:t,height:d}}{const t=a.height+h.sum(o.map(e=>e.height));return{width:c,height:e.height!=1/0?e.height:t}}}}(this.header_el),t?this.header.set_sizing({width_policy:\"fit\",height_policy:\"fixed\"}):this.header.set_sizing({width_policy:\"fixed\",height_policy:\"fit\"});let o=1,c=1;switch(e){case\"above\":o-=1;break;case\"below\":o+=1;break;case\"left\":c-=1;break;case\"right\":c+=1}const d={layout:this.header,row:o,col:c},r=this.child_views.map(e=>({layout:e.layout,row:1,col:1}));this.layout=new a.Grid([d,...r]),this.layout.set_sizing(this.box_sizing())}update_position(){super.update_position(),this.header_el.style.position=\"absolute\",l.position(this.header_el,this.header.bbox);const e=this.model.tabs_location,t=\"above\"==e||\"below\"==e,s=l.size(this.scroll_el),i=l.scroll_size(this.headers_el);if(t){const{width:e}=this.header.bbox;i.width>e?(this.wrapper_el.style.maxWidth=e-s.width+\"px\",l.display(this.scroll_el)):(this.wrapper_el.style.maxWidth=\"\",l.undisplay(this.scroll_el))}else{const{height:e}=this.header.bbox;i.height>e?(this.wrapper_el.style.maxHeight=e-s.height+\"px\",l.display(this.scroll_el)):(this.wrapper_el.style.maxHeight=\"\",l.undisplay(this.scroll_el))}const{child_views:a}=this;for(const e of a)l.hide(e.el);const h=a[this.model.active];null!=h&&l.show(h.el)}render(){super.render();const{active:e}=this.model,t=this.model.tabs_location,s=\"above\"==t||\"below\"==t,i=this.model.tabs.map((t,s)=>{const i=l.div({class:[n.bk_tab,s==e?r.bk_active:null]},t.title);if(i.addEventListener(\"click\",e=>{e.target==e.currentTarget&&this.change_active(s)}),t.closable){const e=l.div({class:n.bk_close});e.addEventListener(\"click\",e=>{if(e.target==e.currentTarget){this.model.tabs=h.remove_at(this.model.tabs,s);const e=this.model.tabs.length;this.model.active>e-1&&(this.model.active=e-1)}}),i.appendChild(e)}return i});this.headers_el=l.div({class:[n.bk_headers]},i),this.wrapper_el=l.div({class:n.bk_headers_wrapper},this.headers_el);const a=l.div({class:[_.bk_btn,_.bk_btn_default],disabled:\"\"},l.div({class:[b.bk_caret,r.bk_left]})),o=l.div({class:[_.bk_btn,_.bk_btn_default]},l.div({class:[b.bk_caret,r.bk_right]}));let c=0;const d=e=>()=>{const t=this.model.tabs.length;c=\"left\"==e?Math.max(c-1,0):Math.min(c+1,t-1),0==c?a.setAttribute(\"disabled\",\"\"):a.removeAttribute(\"disabled\"),c==t-1?o.setAttribute(\"disabled\",\"\"):o.removeAttribute(\"disabled\");const i=l.children(this.headers_el).slice(0,c).map(e=>e.getBoundingClientRect());if(s){const e=-h.sum(i.map(e=>e.width));this.headers_el.style.left=e+\"px\"}else{const e=-h.sum(i.map(e=>e.height));this.headers_el.style.top=e+\"px\"}};a.addEventListener(\"click\",d(\"left\")),o.addEventListener(\"click\",d(\"right\")),this.scroll_el=l.div({class:_.bk_btn_group},a,o),this.header_el=l.div({class:[n.bk_tabs_header,r.bk_side(t)]},this.scroll_el,this.wrapper_el),this.el.appendChild(this.header_el)}change_active(e){e!=this.model.active&&(this.model.active=e)}on_active_change(){const e=this.model.active,t=l.children(this.headers_el);for(const e of t)e.classList.remove(r.bk_active);t[e].classList.add(r.bk_active);const{child_views:s}=this;for(const e of s)l.hide(e.el);l.show(s[e].el)}}s.TabsView=v,v.__name__=\"TabsView\";class g extends c.LayoutDOM{constructor(e){super(e)}static init_Tabs(){this.prototype.default_view=v,this.define({tabs:[o.Array,[]],tabs_location:[o.Location,\"above\"],active:[o.Number,0]})}}s.Tabs=g,g.__name__=\"Tabs\",g.init_Tabs();class w extends d.Model{constructor(e){super(e)}static init_Panel(){this.define({title:[o.String,\"\"],child:[o.Instance],closable:[o.Boolean,!1]})}}s.Panel=w,w.__name__=\"Panel\",w.init_Panel()},\n", - " function _(e,b,a){Object.defineProperty(a,\"__esModule\",{value:!0}),a.bk_tabs_header=\"bk-tabs-header\",a.bk_headers_wrapper=\"bk-headers-wrapper\",a.bk_headers=\"bk-headers\",a.bk_tab=\"bk-tab\",a.bk_close=\"bk-close\"},\n", - " function _(n,b,t){Object.defineProperty(t,\"__esModule\",{value:!0}),t.bk_btn=\"bk-btn\",t.bk_btn_group=\"bk-btn-group\",t.bk_btn_default=\"bk-btn-default\",t.bk_btn_primary=\"bk-btn-primary\",t.bk_btn_success=\"bk-btn-success\",t.bk_btn_warning=\"bk-btn-warning\",t.bk_btn_danger=\"bk-btn-danger\",t.bk_btn_type=function(n){switch(n){case\"default\":return t.bk_btn_default;case\"primary\":return t.bk_btn_primary;case\"success\":return t.bk_btn_success;case\"warning\":return t.bk_btn_warning;case\"danger\":return t.bk_btn_danger}},t.bk_dropdown_toggle=\"bk-dropdown-toggle\"},\n", - " function _(e,b,d){Object.defineProperty(d,\"__esModule\",{value:!0}),d.bk_menu=\"bk-menu\",d.bk_caret=\"bk-caret\",d.bk_divider=\"bk-divider\"},\n", - " function _(n,o,b){Object.defineProperty(b,\"__esModule\",{value:!0});b.default=\"\\n.bk-root .bk-btn {\\n height: 100%;\\n display: inline-block;\\n text-align: center;\\n vertical-align: middle;\\n white-space: nowrap;\\n cursor: pointer;\\n padding: 6px 12px;\\n font-size: 12px;\\n border: 1px solid transparent;\\n border-radius: 4px;\\n outline: 0;\\n user-select: none;\\n -ms-user-select: none;\\n -moz-user-select: none;\\n -webkit-user-select: none;\\n}\\n.bk-root .bk-btn:hover,\\n.bk-root .bk-btn:focus {\\n text-decoration: none;\\n}\\n.bk-root .bk-btn:active,\\n.bk-root .bk-btn.bk-active {\\n background-image: none;\\n box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);\\n}\\n.bk-root .bk-btn[disabled] {\\n cursor: not-allowed;\\n pointer-events: none;\\n opacity: 0.65;\\n box-shadow: none;\\n}\\n.bk-root .bk-btn-default {\\n color: #333;\\n background-color: #fff;\\n border-color: #ccc;\\n}\\n.bk-root .bk-btn-default:hover {\\n background-color: #f5f5f5;\\n border-color: #b8b8b8;\\n}\\n.bk-root .bk-btn-default.bk-active {\\n background-color: #ebebeb;\\n border-color: #adadad;\\n}\\n.bk-root .bk-btn-default[disabled],\\n.bk-root .bk-btn-default[disabled]:hover,\\n.bk-root .bk-btn-default[disabled]:focus,\\n.bk-root .bk-btn-default[disabled]:active,\\n.bk-root .bk-btn-default[disabled].bk-active {\\n background-color: #e6e6e6;\\n border-color: #ccc;\\n}\\n.bk-root .bk-btn-primary {\\n color: #fff;\\n background-color: #428bca;\\n border-color: #357ebd;\\n}\\n.bk-root .bk-btn-primary:hover {\\n background-color: #3681c1;\\n border-color: #2c699e;\\n}\\n.bk-root .bk-btn-primary.bk-active {\\n background-color: #3276b1;\\n border-color: #285e8e;\\n}\\n.bk-root .bk-btn-primary[disabled],\\n.bk-root .bk-btn-primary[disabled]:hover,\\n.bk-root .bk-btn-primary[disabled]:focus,\\n.bk-root .bk-btn-primary[disabled]:active,\\n.bk-root .bk-btn-primary[disabled].bk-active {\\n background-color: #506f89;\\n border-color: #357ebd;\\n}\\n.bk-root .bk-btn-success {\\n color: #fff;\\n background-color: #5cb85c;\\n border-color: #4cae4c;\\n}\\n.bk-root .bk-btn-success:hover {\\n background-color: #4eb24e;\\n border-color: #409240;\\n}\\n.bk-root .bk-btn-success.bk-active {\\n background-color: #47a447;\\n border-color: #398439;\\n}\\n.bk-root .bk-btn-success[disabled],\\n.bk-root .bk-btn-success[disabled]:hover,\\n.bk-root .bk-btn-success[disabled]:focus,\\n.bk-root .bk-btn-success[disabled]:active,\\n.bk-root .bk-btn-success[disabled].bk-active {\\n background-color: #667b66;\\n border-color: #4cae4c;\\n}\\n.bk-root .bk-btn-warning {\\n color: #fff;\\n background-color: #f0ad4e;\\n border-color: #eea236;\\n}\\n.bk-root .bk-btn-warning:hover {\\n background-color: #eea43b;\\n border-color: #e89014;\\n}\\n.bk-root .bk-btn-warning.bk-active {\\n background-color: #ed9c28;\\n border-color: #d58512;\\n}\\n.bk-root .bk-btn-warning[disabled],\\n.bk-root .bk-btn-warning[disabled]:hover,\\n.bk-root .bk-btn-warning[disabled]:focus,\\n.bk-root .bk-btn-warning[disabled]:active,\\n.bk-root .bk-btn-warning[disabled].bk-active {\\n background-color: #c89143;\\n border-color: #eea236;\\n}\\n.bk-root .bk-btn-danger {\\n color: #fff;\\n background-color: #d9534f;\\n border-color: #d43f3a;\\n}\\n.bk-root .bk-btn-danger:hover {\\n background-color: #d5433e;\\n border-color: #bd2d29;\\n}\\n.bk-root .bk-btn-danger.bk-active {\\n background-color: #d2322d;\\n border-color: #ac2925;\\n}\\n.bk-root .bk-btn-danger[disabled],\\n.bk-root .bk-btn-danger[disabled]:hover,\\n.bk-root .bk-btn-danger[disabled]:focus,\\n.bk-root .bk-btn-danger[disabled]:active,\\n.bk-root .bk-btn-danger[disabled].bk-active {\\n background-color: #a55350;\\n border-color: #d43f3a;\\n}\\n.bk-root .bk-btn-group {\\n height: 100%;\\n display: flex;\\n display: -webkit-flex;\\n flex-wrap: nowrap;\\n -webkit-flex-wrap: nowrap;\\n align-items: center;\\n -webkit-align-items: center;\\n flex-direction: row;\\n -webkit-flex-direction: row;\\n}\\n.bk-root .bk-btn-group > .bk-btn {\\n flex-grow: 1;\\n -webkit-flex-grow: 1;\\n}\\n.bk-root .bk-btn-group > .bk-btn + .bk-btn {\\n margin-left: -1px;\\n}\\n.bk-root .bk-btn-group > .bk-btn:first-child:not(:last-child) {\\n border-bottom-right-radius: 0;\\n border-top-right-radius: 0;\\n}\\n.bk-root .bk-btn-group > .bk-btn:not(:first-child):last-child {\\n border-bottom-left-radius: 0;\\n border-top-left-radius: 0;\\n}\\n.bk-root .bk-btn-group > .bk-btn:not(:first-child):not(:last-child) {\\n border-radius: 0;\\n}\\n.bk-root .bk-btn-group .bk-dropdown-toggle {\\n flex: 0 0 0;\\n -webkit-flex: 0 0 0;\\n padding: 6px 6px;\\n}\\n\"},\n", - " function _(n,o,r){Object.defineProperty(r,\"__esModule\",{value:!0});r.default=\"\\n.bk-root .bk-menu-icon {\\n width: 28px;\\n height: 28px;\\n background-size: 60%;\\n background-color: transparent;\\n background-repeat: no-repeat;\\n background-position: center center;\\n}\\n.bk-root .bk-context-menu {\\n position: absolute;\\n display: inline-flex;\\n display: -webkit-inline-flex;\\n flex-wrap: nowrap;\\n -webkit-flex-wrap: nowrap;\\n user-select: none;\\n -ms-user-select: none;\\n -moz-user-select: none;\\n -webkit-user-select: none;\\n width: auto;\\n height: auto;\\n z-index: 100;\\n cursor: pointer;\\n font-size: 12px;\\n background-color: #fff;\\n border: 1px solid #ccc;\\n border-radius: 4px;\\n box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);\\n}\\n.bk-root .bk-context-menu.bk-horizontal {\\n flex-direction: row;\\n -webkit-flex-direction: row;\\n}\\n.bk-root .bk-context-menu.bk-vertical {\\n flex-direction: column;\\n -webkit-flex-direction: column;\\n}\\n.bk-root .bk-context-menu > .bk-divider {\\n cursor: default;\\n overflow: hidden;\\n background-color: #e5e5e5;\\n}\\n.bk-root .bk-context-menu.bk-horizontal > .bk-divider {\\n width: 1px;\\n margin: 5px 0;\\n}\\n.bk-root .bk-context-menu.bk-vertical > .bk-divider {\\n height: 1px;\\n margin: 0 5px;\\n}\\n.bk-root .bk-context-menu > :not(.bk-divider) {\\n border: 1px solid transparent;\\n}\\n.bk-root .bk-context-menu > :not(.bk-divider).bk-active {\\n border-color: #26aae1;\\n}\\n.bk-root .bk-context-menu > :not(.bk-divider):hover {\\n background-color: #f9f9f9;\\n}\\n.bk-root .bk-context-menu.bk-horizontal > :not(.bk-divider):first-child {\\n border-top-left-radius: 4px;\\n border-bottom-left-radius: 4px;\\n}\\n.bk-root .bk-context-menu.bk-horizontal > :not(.bk-divider):last-child {\\n border-top-right-radius: 4px;\\n border-bottom-right-radius: 4px;\\n}\\n.bk-root .bk-context-menu.bk-vertical > :not(.bk-divider):first-child {\\n border-top-left-radius: 4px;\\n border-top-right-radius: 4px;\\n}\\n.bk-root .bk-context-menu.bk-vertical > :not(.bk-divider):last-child {\\n border-bottom-left-radius: 4px;\\n border-bottom-right-radius: 4px;\\n}\\n.bk-root .bk-menu {\\n position: absolute;\\n left: 0;\\n width: 100%;\\n z-index: 100;\\n cursor: pointer;\\n font-size: 12px;\\n background-color: #fff;\\n border: 1px solid #ccc;\\n border-radius: 4px;\\n box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);\\n}\\n.bk-root .bk-menu.bk-above {\\n bottom: 100%;\\n}\\n.bk-root .bk-menu.bk-below {\\n top: 100%;\\n}\\n.bk-root .bk-menu > .bk-divider {\\n height: 1px;\\n margin: 7.5px 0;\\n overflow: hidden;\\n background-color: #e5e5e5;\\n}\\n.bk-root .bk-menu > :not(.bk-divider) {\\n padding: 6px 12px;\\n}\\n.bk-root .bk-menu > :not(.bk-divider):hover,\\n.bk-root .bk-menu > :not(.bk-divider).bk-active {\\n background-color: #e6e6e6;\\n}\\n.bk-root .bk-caret {\\n display: inline-block;\\n vertical-align: middle;\\n width: 0;\\n height: 0;\\n margin: 0 5px;\\n}\\n.bk-root .bk-caret.bk-down {\\n border-top: 4px solid;\\n}\\n.bk-root .bk-caret.bk-up {\\n border-bottom: 4px solid;\\n}\\n.bk-root .bk-caret.bk-down,\\n.bk-root .bk-caret.bk-up {\\n border-right: 4px solid transparent;\\n border-left: 4px solid transparent;\\n}\\n.bk-root .bk-caret.bk-left {\\n border-right: 4px solid;\\n}\\n.bk-root .bk-caret.bk-right {\\n border-left: 4px solid;\\n}\\n.bk-root .bk-caret.bk-left,\\n.bk-root .bk-caret.bk-right {\\n border-top: 4px solid transparent;\\n border-bottom: 4px solid transparent;\\n}\\n\"},\n", - " function _(e,r,n){Object.defineProperty(n,\"__esModule\",{value:!0});n.default='\\n.bk-root .bk-tabs-header {\\n display: flex;\\n display: -webkit-flex;\\n flex-wrap: nowrap;\\n -webkit-flex-wrap: nowrap;\\n align-items: center;\\n -webkit-align-items: center;\\n overflow: hidden;\\n user-select: none;\\n -ms-user-select: none;\\n -moz-user-select: none;\\n -webkit-user-select: none;\\n}\\n.bk-root .bk-tabs-header .bk-btn-group {\\n height: auto;\\n margin-right: 5px;\\n}\\n.bk-root .bk-tabs-header .bk-btn-group > .bk-btn {\\n flex-grow: 0;\\n -webkit-flex-grow: 0;\\n height: auto;\\n padding: 4px 4px;\\n}\\n.bk-root .bk-tabs-header .bk-headers-wrapper {\\n flex-grow: 1;\\n -webkit-flex-grow: 1;\\n overflow: hidden;\\n color: #666666;\\n}\\n.bk-root .bk-tabs-header.bk-above .bk-headers-wrapper {\\n border-bottom: 1px solid #e6e6e6;\\n}\\n.bk-root .bk-tabs-header.bk-right .bk-headers-wrapper {\\n border-left: 1px solid #e6e6e6;\\n}\\n.bk-root .bk-tabs-header.bk-below .bk-headers-wrapper {\\n border-top: 1px solid #e6e6e6;\\n}\\n.bk-root .bk-tabs-header.bk-left .bk-headers-wrapper {\\n border-right: 1px solid #e6e6e6;\\n}\\n.bk-root .bk-tabs-header.bk-above,\\n.bk-root .bk-tabs-header.bk-below {\\n flex-direction: row;\\n -webkit-flex-direction: row;\\n}\\n.bk-root .bk-tabs-header.bk-above .bk-headers,\\n.bk-root .bk-tabs-header.bk-below .bk-headers {\\n flex-direction: row;\\n -webkit-flex-direction: row;\\n}\\n.bk-root .bk-tabs-header.bk-left,\\n.bk-root .bk-tabs-header.bk-right {\\n flex-direction: column;\\n -webkit-flex-direction: column;\\n}\\n.bk-root .bk-tabs-header.bk-left .bk-headers,\\n.bk-root .bk-tabs-header.bk-right .bk-headers {\\n flex-direction: column;\\n -webkit-flex-direction: column;\\n}\\n.bk-root .bk-tabs-header .bk-headers {\\n position: relative;\\n display: flex;\\n display: -webkit-flex;\\n flex-wrap: nowrap;\\n -webkit-flex-wrap: nowrap;\\n align-items: center;\\n -webkit-align-items: center;\\n}\\n.bk-root .bk-tabs-header .bk-tab {\\n padding: 4px 8px;\\n border: solid transparent;\\n white-space: nowrap;\\n cursor: pointer;\\n}\\n.bk-root .bk-tabs-header .bk-tab:hover {\\n background-color: #f2f2f2;\\n}\\n.bk-root .bk-tabs-header .bk-tab.bk-active {\\n color: #4d4d4d;\\n background-color: white;\\n border-color: #e6e6e6;\\n}\\n.bk-root .bk-tabs-header .bk-tab .bk-close {\\n margin-left: 10px;\\n}\\n.bk-root .bk-tabs-header.bk-above .bk-tab {\\n border-width: 3px 1px 0px 1px;\\n border-radius: 4px 4px 0 0;\\n}\\n.bk-root .bk-tabs-header.bk-right .bk-tab {\\n border-width: 1px 3px 1px 0px;\\n border-radius: 0 4px 4px 0;\\n}\\n.bk-root .bk-tabs-header.bk-below .bk-tab {\\n border-width: 0px 1px 3px 1px;\\n border-radius: 0 0 4px 4px;\\n}\\n.bk-root .bk-tabs-header.bk-left .bk-tab {\\n border-width: 1px 0px 1px 3px;\\n border-radius: 4px 0 0 4px;\\n}\\n.bk-root .bk-close {\\n display: inline-block;\\n width: 10px;\\n height: 10px;\\n vertical-align: middle;\\n background-image: url(\\'data:image/svg+xml;utf8, \\');\\n}\\n.bk-root .bk-close:hover {\\n background-image: url(\\'data:image/svg+xml;utf8, \\');\\n}\\n'},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const o=e(274);class _ extends o.ColumnView{}i.WidgetBoxView=_,_.__name__=\"WidgetBoxView\";class n extends o.Column{constructor(e){super(e)}static init_WidgetBox(){this.prototype.default_view=_}}i.WidgetBox=n,n.__name__=\"WidgetBox\",n.init_WidgetBox()},\n", - " function _(e,r,t){Object.defineProperty(t,\"__esModule\",{value:!0});e(1).__exportStar(e(288),t);var a=e(289);t.Marker=a.Marker;var _=e(290);t.Scatter=_.Scatter},\n", - " function 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this.index.indices({x0:t,x1:n,y0:h,y1:l})}_hit_point(e){const{sx:s,sy:i}=e,t=s-this.max_size,n=s+this.max_size,[r,a]=this.renderer.xscale.r_invert(t,n),_=i-this.max_size,h=i+this.max_size,[c,o]=this.renderer.yscale.r_invert(_,h),x=this.index.indices({x0:r,x1:a,y0:c,y1:o}),d=[];for(const e of x){const t=this._size[e]/2;Math.abs(this.sx[e]-s)<=t&&Math.abs(this.sy[e]-i)<=t&&d.push(e)}return new l.Selection({indices:d})}_hit_span(e){const{sx:s,sy:i}=e,t=this.bounds(),n=this.max_size/2;let r,a,_,h;if(\"h\"==e.direction){_=t.y0,h=t.y1;const e=s-n,i=s+n;[r,a]=this.renderer.xscale.r_invert(e,i)}else{r=t.x0,a=t.x1;const e=i-n,s=i+n;[_,h]=this.renderer.yscale.r_invert(e,s)}const c=[...this.index.indices({x0:r,x1:a,y0:_,y1:h})];return new l.Selection({indices:c})}_hit_rect(e){const{sx0:s,sx1:i,sy0:t,sy1:n}=e,[r,a]=this.renderer.xscale.r_invert(s,i),[_,h]=this.renderer.yscale.r_invert(t,n),c=[...this.index.indices({x0:r,x1:a,y0:_,y1:h})];return new l.Selection({indices:c})}_hit_poly(e){const{sx:s,sy:i}=e,t=h.range(0,this.sx.length),n=[];for(let e=0,r=t.length;enew r.Range1d,y_range:()=>new r.Range1d})}initialize(){super.initialize(),this.use_map=!0,this.api_key||n.logger.error(\"api_key is required. 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" function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=t(1).__importStar(t(18)),c=t(8),o=t(9),n=t(13),a=t(295),l=t(305),r=t=>{switch(t){case\"tap\":return\"active_tap\";case\"pan\":return\"active_drag\";case\"pinch\":case\"scroll\":return\"active_scroll\";case\"multi\":return\"active_multi\"}return null},_=t=>\"tap\"==t||\"pan\"==t;class h extends l.ToolbarBase{constructor(t){super(t)}static init_Toolbar(){this.prototype.default_view=l.ToolbarBaseView,this.define({active_drag:[s.Any,\"auto\"],active_inspect:[s.Any,\"auto\"],active_scroll:[s.Any,\"auto\"],active_tap:[s.Any,\"auto\"],active_multi:[s.Any,null]})}connect_signals(){super.connect_signals();const{tools:t,active_drag:e,active_inspect:i,active_scroll:s,active_tap:c,active_multi:o}=this.properties;this.on_change([t,e,i,s,c,o],()=>this._init_tools())}_init_tools(){if(super._init_tools(),\"auto\"==this.active_inspect);else if(this.active_inspect instanceof a.InspectTool){let t=!1;for(const e of this.inspectors)e!=this.active_inspect?e.active=!1:t=!0;t||(this.active_inspect=null)}else if(c.isArray(this.active_inspect)){const t=o.intersection(this.active_inspect,this.inspectors);t.length!=this.active_inspect.length&&(this.active_inspect=t);for(const t of this.inspectors)o.includes(this.active_inspect,t)||(t.active=!1)}else if(null==this.active_inspect)for(const t of this.inspectors)t.active=!1;const t=t=>{t.active?this._active_change(t):t.active=!0};for(const t of n.values(this.gestures)){t.tools=o.sort_by(t.tools,t=>t.default_order);for(const e of t.tools)this.connect(e.properties.active.change,()=>this._active_change(e))}for(const[e,i]of n.entries(this.gestures)){const s=r(e);if(s){const c=this[s];\"auto\"==c?0!=i.tools.length&&_(e)&&t(i.tools[0]):null!=c&&(o.includes(this.tools,c)?t(c):this[s]=null)}}}}i.Toolbar=h,h.__name__=\"Toolbar\",h.init_Toolbar()},\n", - 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i(n){e.manager.emit(n,t)}n<8&&i(e.options.event+ft(n)),i(e.options.event),t.additionalEvent&&i(t.additionalEvent),n>=8&&i(e.options.event+ft(n))},tryEmit:function(t){if(this.canEmit())return this.emit(t);this.state=32},canEmit:function(){for(var t=0;te.threshold&&r&e.direction},attrTest:function(t){return mt.prototype.attrTest.call(this,t)&&(2&this.state||!(2&this.state)&&this.directionTest(t))},emit:function(t){this.pX=t.deltaX,this.pY=t.deltaY;var e=vt(t.direction);e&&(t.additionalEvent=this.options.event+e),this._super.emit.call(this,t)}}),g(yt,mt,{defaults:{event:\"pinch\",threshold:0,pointers:2},getTouchAction:function(){return[\"none\"]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.scale-1)>this.options.threshold||2&this.state)},emit:function(t){if(1!==t.scale){var e=t.scale<1?\"in\":\"out\";t.additionalEvent=this.options.event+e}this._super.emit.call(this,t)}}),g(Tt,pt,{defaults:{event:\"press\",pointers:1,time:251,threshold:9},getTouchAction:function(){return[\"auto\"]},process:function(t){var e=this.options,n=t.pointers.length===e.pointers,i=t.distancee.time;if(this._input=t,!i||!n||12&t.eventType&&!r)this.reset();else if(1&t.eventType)this.reset(),this._timer=l((function(){this.state=8,this.tryEmit()}),e.time,this);else if(4&t.eventType)return 8;return 32},reset:function(){clearTimeout(this._timer)},emit:function(t){8===this.state&&(t&&4&t.eventType?this.manager.emit(this.options.event+\"up\",t):(this._input.timeStamp=c(),this.manager.emit(this.options.event,this._input)))}}),g(Et,mt,{defaults:{event:\"rotate\",threshold:0,pointers:2},getTouchAction:function(){return[\"none\"]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.rotation)>this.options.threshold||2&this.state)}}),g(It,mt,{defaults:{event:\"swipe\",threshold:10,velocity:.3,direction:30,pointers:1},getTouchAction:function(){return gt.prototype.getTouchAction.call(this)},attrTest:function(t){var e,n=this.options.direction;return 30&n?e=t.overallVelocity:6&n?e=t.overallVelocityX:24&n&&(e=t.overallVelocityY),this._super.attrTest.call(this,t)&&n&t.offsetDirection&&t.distance>this.options.threshold&&t.maxPointers==this.options.pointers&&u(e)>this.options.velocity&&4&t.eventType},emit:function(t){var e=vt(t.offsetDirection);e&&this.manager.emit(this.options.event+e,t),this.manager.emit(this.options.event,t)}}),g(At,pt,{defaults:{event:\"tap\",pointers:1,taps:1,interval:300,time:250,threshold:9,posThreshold:10},getTouchAction:function(){return[\"manipulation\"]},process:function(t){var e=this.options,n=t.pointers.length===e.pointers,i=t.distance{this.model.active?this.activate():this.deactivate()})}activate(){}deactivate(){}}i.ToolView=r,r.__name__=\"ToolView\";class _ extends a.Model{constructor(t){super(t)}static init_Tool(){this.prototype._known_aliases=new Map,this.internal({active:[n.Boolean,!1]})}get synthetic_renderers(){return[]}_get_dim_tooltip(t,e){switch(e){case\"width\":return t+\" (x-axis)\";case\"height\":return t+\" (y-axis)\";case\"both\":return t}}_get_dim_limits([t,e],[i,n],o,a){const r=o.bbox.h_range;let _;\"width\"==a||\"both\"==a?(_=[s.min([t,i]),s.max([t,i])],_=[s.max([_[0],r.start]),s.min([_[1],r.end])]):_=[r.start,r.end];const l=o.bbox.v_range;let c;return\"height\"==a||\"both\"==a?(c=[s.min([e,n]),s.max([e,n])],c=[s.max([c[0],l.start]),s.min([c[1],l.end])]):c=[l.start,l.end],[_,c]}static register_alias(t,e){this.prototype._known_aliases.set(t,e)}static from_string(t){const e=this.prototype._known_aliases.get(t);if(null!=e)return e();{const e=[...this.prototype._known_aliases.keys()];throw new Error(`unexpected tool name '${t}', possible tools are ${e.join(\", \")}`)}}}i.Tool=_,_.__name__=\"Tool\",_.init_Tool()},\n", - " function _(o,b,t){Object.defineProperty(t,\"__esModule\",{value:!0}),t.bk_toolbar=\"bk-toolbar\",t.bk_toolbar_hidden=\"bk-toolbar-hidden\",t.bk_toolbar_button=\"bk-toolbar-button\",t.bk_button_bar=\"bk-button-bar\",t.bk_toolbar_button_custom_action=\"bk-toolbar-button-custom-action\"},\n", - " function _(o,b,t){Object.defineProperty(t,\"__esModule\",{value:!0});t.default='\\n.bk-root .bk-toolbar-hidden {\\n visibility: hidden;\\n opacity: 0;\\n transition: visibility 0.3s linear, opacity 0.3s linear;\\n}\\n.bk-root .bk-toolbar,\\n.bk-root .bk-button-bar {\\n display: flex;\\n display: -webkit-flex;\\n flex-wrap: nowrap;\\n -webkit-flex-wrap: nowrap;\\n align-items: center;\\n -webkit-align-items: center;\\n user-select: none;\\n -ms-user-select: none;\\n -moz-user-select: none;\\n -webkit-user-select: none;\\n}\\n.bk-root .bk-toolbar .bk-logo {\\n flex-shrink: 0;\\n -webkit-flex-shrink: 0;\\n}\\n.bk-root .bk-toolbar.bk-above,\\n.bk-root .bk-toolbar.bk-below {\\n flex-direction: row;\\n -webkit-flex-direction: row;\\n justify-content: flex-end;\\n -webkit-justify-content: flex-end;\\n}\\n.bk-root .bk-toolbar.bk-above .bk-button-bar,\\n.bk-root .bk-toolbar.bk-below .bk-button-bar {\\n display: flex;\\n display: -webkit-flex;\\n flex-direction: row;\\n -webkit-flex-direction: row;\\n}\\n.bk-root .bk-toolbar.bk-above .bk-logo,\\n.bk-root .bk-toolbar.bk-below .bk-logo {\\n order: 1;\\n -webkit-order: 1;\\n margin-left: 5px;\\n margin-right: 0px;\\n}\\n.bk-root .bk-toolbar.bk-left,\\n.bk-root .bk-toolbar.bk-right {\\n flex-direction: column;\\n -webkit-flex-direction: column;\\n justify-content: flex-start;\\n -webkit-justify-content: flex-start;\\n}\\n.bk-root .bk-toolbar.bk-left .bk-button-bar,\\n.bk-root .bk-toolbar.bk-right .bk-button-bar {\\n display: flex;\\n display: -webkit-flex;\\n flex-direction: column;\\n -webkit-flex-direction: column;\\n}\\n.bk-root .bk-toolbar.bk-left .bk-logo,\\n.bk-root .bk-toolbar.bk-right .bk-logo {\\n order: 0;\\n -webkit-order: 0;\\n margin-bottom: 5px;\\n margin-top: 0px;\\n}\\n.bk-root .bk-toolbar-button {\\n width: 30px;\\n height: 30px;\\n cursor: pointer;\\n background-size: 60% 60%;\\n background-origin: border-box;\\n background-color: transparent;\\n background-repeat: no-repeat;\\n background-position: center center;\\n}\\n.bk-root .bk-toolbar-button:hover {\\n background-color: rgba(192, 192, 192, 0.15);\\n}\\n.bk-root .bk-toolbar-button:focus {\\n outline: none;\\n}\\n.bk-root .bk-toolbar-button::-moz-focus-inner {\\n border: 0;\\n}\\n.bk-root .bk-toolbar.bk-above .bk-toolbar-button {\\n border-bottom: 2px solid transparent;\\n}\\n.bk-root .bk-toolbar.bk-above .bk-toolbar-button.bk-active {\\n border-bottom-color: #26aae1;\\n}\\n.bk-root .bk-toolbar.bk-below .bk-toolbar-button {\\n border-top: 2px solid transparent;\\n}\\n.bk-root .bk-toolbar.bk-below .bk-toolbar-button.bk-active {\\n border-top-color: #26aae1;\\n}\\n.bk-root .bk-toolbar.bk-right .bk-toolbar-button {\\n border-left: 2px solid transparent;\\n}\\n.bk-root .bk-toolbar.bk-right .bk-toolbar-button.bk-active {\\n border-left-color: #26aae1;\\n}\\n.bk-root .bk-toolbar.bk-left .bk-toolbar-button {\\n border-right: 2px solid transparent;\\n}\\n.bk-root .bk-toolbar.bk-left .bk-toolbar-button.bk-active {\\n border-right-color: #26aae1;\\n}\\n.bk-root .bk-button-bar + .bk-button-bar:before {\\n content: \" \";\\n display: inline-block;\\n background-color: lightgray;\\n}\\n.bk-root .bk-toolbar.bk-above .bk-button-bar + .bk-button-bar:before,\\n.bk-root .bk-toolbar.bk-below .bk-button-bar + .bk-button-bar:before {\\n height: 10px;\\n width: 1px;\\n}\\n.bk-root .bk-toolbar.bk-left .bk-button-bar + .bk-button-bar:before,\\n.bk-root .bk-toolbar.bk-right .bk-button-bar + .bk-button-bar:before {\\n height: 1px;\\n width: 10px;\\n}\\n'},\n", - " function _(A,g,C){Object.defineProperty(C,\"__esModule\",{value:!0});C.default='\\n.bk-root .bk-tool-icon-copy-to-clipboard {\\n background-image: url(\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAABmJLR0QA/wD/AP+gvaeTAAAACXBIWXMAAAsTAAALEwEAmpwYAAAAB3RJTUUH5AUSDBoBvcHQeQAAAG9JREFUWMNjXLhsJcNAAiaGAQYwB/xHwh/Q+ITEkfHQCwEWND4jmeb8H/JpgBwfI6cNBhLSEkqaGXRpgFRAcZoZsmlg1AGjDhh1wKgDRh0w6gCaVcf/R2wIkNqw+D9s0wADvUNiyIYA47BJAwPuAAAj/Cjd0TCN6wAAAABJRU5ErkJggg==\");\\n}\\n.bk-root .bk-tool-icon-replace-mode {\\n background-image: url(\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAABmJLR0QA/wD/AP+gvaeTAAAACXBIWXMAAAsTAAALEwEAmpwYAAAAB3RJTUUH5AUFFxokK3gniQAAAHpJREFUWMNjXLhsJcNAAiaGAQajDhhwB7DgEP+PxmeksvjgDwFcLmYkUh2hkBj8IcBIZXsYh1w2/I8v3sgAOM0bLYhGc8GgrwuICgldfQO88pcvXvg/aOuCUQeM5oLRuoCFCJcTbOMh5XOiW0JDNhdQS3y0IBp1ABwAAF8KGrhC1Eg6AAAAAElFTkSuQmCC\");\\n}\\n.bk-root .bk-tool-icon-append-mode {\\n background-image: url(\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAABmJLR0QA/wD/AP+gvaeTAAAACXBIWXMAAAsTAAALEwEAmpwYAAAAB3RJTUUH5AUFFxkZWD04WwAAAB1pVFh0Q29tbWVudAAAAAAAQ3JlYXRlZCB3aXRoIEdJTVBkLmUHAAAAoUlEQVRYw+1WQQ6AIAwrhO8Y/bIXEz9jIMSDr8ETCUEPQzA4pMeFLKNbu4l5WR0CDOMEALBGIzMuQIBEZQjPgP9JLjwTfBjY9sO9lZsFA9IafZng3BlIyVefgd8XQFZBAWe8jfNxwsDhir6rzoCiPiy1K+J8/FRQemv2XfAdFcQ9znU4Viqg9ta1qYJ+D1BnAIBrkgGVOrXNqUA9rbyZm/AEzFh4jEeY/soAAAAASUVORK5CYII=\");\\n}\\n.bk-root .bk-tool-icon-intersect-mode {\\n background-image: url(\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAABmJLR0QA/wD/AP+gvaeTAAAACXBIWXMAAAsTAAALEwEAmpwYAAAAB3RJTUUH5AUFFxkrkOpp2wAAAPhJREFUWMPtV1EKwjAMTUavI3oawR/vtn5srJdREfzwMvHHQlcT2mpdMzFfWxiP5r2+JMN+mAiCOB72CABgR1cln4oOGocJnuMTSxWk8jMm7OggYkYXA9gPE3uyd8NXHONJ+eYMdE/NqCJmEZ5ZqlJJ4sUksKN7cYSaPoCZFWR1QI+Xm1fBACU63Cw22x0AAJxudwrffVwvZ+JmQdAHZkw0d4EpAMCw8k87pMdbnwtizQumJYv3nwV6XOA1qbUT/oQLUJgFRbsiNwFVucBIlyR3p0tdMp+XmFjfLKi1LatyAXtCRjPWBdL3Ke3VuACJKFfDr/xFN2fgAR/Go0qaLlmEAAAAAElFTkSuQmCC\");\\n}\\n.bk-root .bk-tool-icon-subtract-mode {\\n background-image: url(\"data:image/png;base64,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\");\\n}\\n.bk-root .bk-tool-icon-clear-selection {\\n background-image: url(\"data:image/png;base64,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\");\\n}\\n.bk-root .bk-tool-icon-box-select {\\n background-image: url(\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAABmJLR0QA/wD/AP+gvaeTAAAACXBIWXMAAAsTAAALEwEAmpwYAAAAB3RJTUUH4gEMEg0kduFrowAAAIdJREFUWMPtVtEKwCAI9KL//4e9DPZ3+wP3KgOjNZouFYI4C8q7s7DtB1lGIeMoRMRinCLXg/ML3EcFqpjjloOyZxRntxpwQ8HsgHYARKFAtSFrCg3TCdMFCE1BuuALEXJLjC4qENsFVXCESZw38/kWLOkC/K4PcOc/Hj03WkoDT3EaWW9egQul6CUbq90JTwAAAABJRU5ErkJggg==\");\\n}\\n.bk-root .bk-tool-icon-box-zoom {\\n background-image: 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background-image: 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url(\"data:image/png;base64,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\");\\n}\\n'},\n", - " function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=t(1),s=t(72),o=t(303),l=n.__importStar(t(282));class h{constructor(t,e={}){this.items=t,this.options=e,this.el=s.div(),this._open=!1,this._item_click=t=>{var e;null===(e=this.items[t])||void 0===e||e.handler(),this.hide()},this._on_mousedown=t=>{var e,i;const{target:n}=t;n instanceof Node&&this.el.contains(n)||(null===(i=(e=this.options).prevent_hide)||void 0===i?void 0:i.call(e,t))||this.hide()},this._on_keydown=t=>{t.keyCode==s.Keys.Esc&&this.hide()},this._on_blur=()=>{this.hide()},s.undisplay(this.el)}get is_open(){return this._open}get can_open(){return 0!=this.items.length}remove(){s.remove(this.el),this._unlisten()}_listen(){document.addEventListener(\"mousedown\",this._on_mousedown),document.addEventListener(\"keydown\",this._on_keydown),window.addEventListener(\"blur\",this._on_blur)}_unlisten(){document.removeEventListener(\"mousedown\",this._on_mousedown),document.removeEventListener(\"keydown\",this._on_keydown),window.removeEventListener(\"blur\",this._on_blur)}_position(t){const e=this.el.parentElement;if(null!=e){const i=e.getBoundingClientRect();this.el.style.left=null!=t.left?t.left-i.left+\"px\":\"\",this.el.style.top=null!=t.top?t.top-i.top+\"px\":\"\",this.el.style.right=null!=t.right?i.right-t.right+\"px\":\"\",this.el.style.bottom=null!=t.bottom?i.bottom-t.bottom+\"px\":\"\"}}render(){var t,e;s.empty(this.el,!0);const i=null!==(t=this.options.orientation)&&void 0!==t?t:\"vertical\";s.classes(this.el).add(\"bk-context-menu\",\"bk-\"+i);for(const[t,i]of o.enumerate(this.items)){let n;if(null==t)n=s.div({class:l.bk_divider});else{if(null!=t.if&&!t.if())continue;{const i=null!=t.icon?s.div({class:[\"bk-menu-icon\",t.icon]}):null;n=s.div({class:(null===(e=t.active)||void 0===e?void 0:e.call(t))?\"bk-active\":null,title:t.tooltip},i,t.label)}}n.addEventListener(\"click\",()=>this._item_click(i)),this.el.appendChild(n)}}show(t){if(0!=this.items.length&&!this._open){if(this.render(),0==this.el.children.length)return;this._position(null!=t?t:{left:0,top:0}),s.display(this.el),this._listen(),this._open=!0}}hide(){this._open&&(this._open=!1,this._unlisten(),s.undisplay(this.el))}toggle(t){this._open?this.hide():this.show(t)}}i.ContextMenu=h,h.__name__=\"ContextMenu\"},\n", - " function _(e,n,o){Object.defineProperty(o,\"__esModule\",{value:!0});const t=e(9);function*r(e,n){const o=e.length;if(n>o)return;const r=t.range(n);for(yield r.map(n=>e[n]);;){let f;for(const e of t.reversed(t.range(n)))if(r[e]!=e+o-n){f=e;break}if(null==f)return;r[f]+=1;for(const e of t.range(f+1,n))r[e]=r[e-1]+1;yield r.map(n=>e[n])}}o.enumerate=function*(e){let n=0;for(const o of e)yield[o,n++]},o.combinations=r,o.subsets=function*(e){for(const n of t.range(e.length+1))yield*r(e,n)}},\n", - " function _(e,t,n){Object.defineProperty(n,\"__esModule\",{value:!0});const o=e(296),i=e(173),s=e(72);class c extends o.ButtonToolButtonView{render(){super.render(),s.classes(this.el).toggle(i.bk_active,this.model.active)}_clicked(){const{active:e}=this.model;this.model.active=!e}}n.OnOffButtonView=c,c.__name__=\"OnOffButtonView\"},\n", - " function _(t,o,e){Object.defineProperty(e,\"__esModule\",{value:!0});const i=t(1),s=t(19),l=t(72),n=t(115),a=i.__importStar(t(18)),r=t(78),_=t(9),c=t(13),h=t(8),u=t(81),v=t(306),d=t(307),b=t(308),p=t(295),g=t(299),f=t(310),m=t(173),w=i.__importDefault(t(300)),y=i.__importDefault(t(311));class T extends u.Model{constructor(t){super(t)}static init_ToolbarViewModel(){this.define({_visible:[a.Any,null],autohide:[a.Boolean,!1]})}get visible(){return!this.autohide||null!=this._visible&&this._visible}}e.ToolbarViewModel=T,T.__name__=\"ToolbarViewModel\",T.init_ToolbarViewModel();class k extends r.DOMView{initialize(){super.initialize(),this._tool_button_views=new Map,this._toolbar_view_model=new T({autohide:this.model.autohide})}async lazy_initialize(){await this._build_tool_button_views()}connect_signals(){super.connect_signals(),this.connect(this.model.properties.tools.change,async()=>{await this._build_tool_button_views(),this.render()}),this.connect(this.model.properties.autohide.change,()=>{this._toolbar_view_model.autohide=this.model.autohide,this._on_visible_change()}),this.connect(this._toolbar_view_model.properties._visible.change,()=>this._on_visible_change())}styles(){return[...super.styles(),w.default,y.default]}remove(){n.remove_views(this._tool_button_views),super.remove()}async _build_tool_button_views(){const t=null!=this.model._proxied_tools?this.model._proxied_tools:this.model.tools;await n.build_views(this._tool_button_views,t,{parent:this},t=>t.button_view)}set_visibility(t){t!=this._toolbar_view_model._visible&&(this._toolbar_view_model._visible=t)}_on_visible_change(){const t=this._toolbar_view_model.visible,o=g.bk_toolbar_hidden;this.el.classList.contains(o)&&t?this.el.classList.remove(o):t||this.el.classList.add(o)}render(){if(l.empty(this.el),this.el.classList.add(g.bk_toolbar),this.el.classList.add(m.bk_side(this.model.toolbar_location)),this._toolbar_view_model.autohide=this.model.autohide,this._on_visible_change(),null!=this.model.logo){const t=\"grey\"===this.model.logo?f.bk_grey:null,o=l.a({href:\"https://bokeh.org/\",target:\"_blank\",class:[f.bk_logo,f.bk_logo_small,t]});this.el.appendChild(o)}for(const[,t]of this._tool_button_views)t.render();const t=[],o=t=>this._tool_button_views.get(t).el,{gestures:e}=this.model;for(const i of c.values(e))t.push(i.tools.map(o));t.push(this.model.actions.map(o)),t.push(this.model.inspectors.filter(t=>t.toggleable).map(o));for(const o of t)if(0!==o.length){const t=l.div({class:g.bk_button_bar},o);this.el.appendChild(t)}}update_layout(){}update_position(){}after_layout(){this._has_finished=!0}}function M(){return{pan:{tools:[],active:null},scroll:{tools:[],active:null},pinch:{tools:[],active:null},tap:{tools:[],active:null},doubletap:{tools:[],active:null},press:{tools:[],active:null},pressup:{tools:[],active:null},rotate:{tools:[],active:null},move:{tools:[],active:null},multi:{tools:[],active:null}}}e.ToolbarBaseView=k,k.__name__=\"ToolbarBaseView\";class B extends u.Model{constructor(t){super(t)}static init_ToolbarBase(){this.prototype.default_view=k,this.define({tools:[a.Array,[]],logo:[a.Logo,\"normal\"],autohide:[a.Boolean,!1]}),this.internal({gestures:[a.Any,M],actions:[a.Array,[]],inspectors:[a.Array,[]],help:[a.Array,[]],toolbar_location:[a.Location,\"right\"]})}initialize(){super.initialize(),this._init_tools()}_init_tools(){const t=function(t,o){if(t.length!=o.length)return!0;const e=new Set(o.map(t=>t.id));return _.some(t,t=>!e.has(t.id))},o=this.tools.filter(t=>t instanceof p.InspectTool);t(this.inspectors,o)&&(this.inspectors=o);const e=this.tools.filter(t=>t instanceof b.HelpTool);t(this.help,e)&&(this.help=e);const i=this.tools.filter(t=>t instanceof d.ActionTool);t(this.actions,i)&&(this.actions=i);const l=(t,o)=>{t in this.gestures||s.logger.warn(`Toolbar: unknown event type '${t}' for tool: ${o}`)},n={pan:{tools:[],active:null},scroll:{tools:[],active:null},pinch:{tools:[],active:null},tap:{tools:[],active:null},doubletap:{tools:[],active:null},press:{tools:[],active:null},pressup:{tools:[],active:null},rotate:{tools:[],active:null},move:{tools:[],active:null},multi:{tools:[],active:null}};for(const t of this.tools)if(t instanceof v.GestureTool&&t.event_type)if(h.isString(t.event_type))n[t.event_type].tools.push(t),l(t.event_type,t);else{n.multi.tools.push(t);for(const o of t.event_type)l(o,t)}for(const o of Object.keys(n)){const e=this.gestures[o];t(e.tools,n[o].tools)&&(e.tools=n[o].tools),e.active&&_.every(e.tools,t=>t.id!=e.active.id)&&(e.active=null)}}get horizontal(){return\"above\"===this.toolbar_location||\"below\"===this.toolbar_location}get vertical(){return\"left\"===this.toolbar_location||\"right\"===this.toolbar_location}_active_change(t){const{event_type:o}=t;if(null==o)return;const e=h.isString(o)?[o]:o;for(const o of e)if(t.active){const e=this.gestures[o].active;null!=e&&t!=e&&(s.logger.debug(`Toolbar: deactivating tool: ${e} for event type '${o}'`),e.active=!1),this.gestures[o].active=t,s.logger.debug(`Toolbar: activating tool: ${t} for event type '${o}'`)}else this.gestures[o].active=null}}e.ToolbarBase=B,B.__name__=\"ToolbarBase\",B.init_ToolbarBase()},\n", - " function _(e,o,t){Object.defineProperty(t,\"__esModule\",{value:!0});const s=e(296),n=e(304);class u extends s.ButtonToolView{}t.GestureToolView=u,u.__name__=\"GestureToolView\";class _ extends s.ButtonTool{constructor(e){super(e),this.button_view=n.OnOffButtonView}}t.GestureTool=_,_.__name__=\"GestureTool\"},\n", - " function _(o,t,n){Object.defineProperty(n,\"__esModule\",{value:!0});const e=o(296),i=o(15);class s extends e.ButtonToolButtonView{_clicked(){this.model.do.emit(void 0)}}n.ActionToolButtonView=s,s.__name__=\"ActionToolButtonView\";class c extends e.ButtonToolView{connect_signals(){super.connect_signals(),this.connect(this.model.do,o=>this.doit(o))}}n.ActionToolView=c,c.__name__=\"ActionToolView\";class l extends e.ButtonTool{constructor(o){super(o),this.button_view=s,this.do=new i.Signal(this,\"do\")}}n.ActionTool=l,l.__name__=\"ActionTool\"},\n", - " function _(o,e,t){Object.defineProperty(t,\"__esModule\",{value:!0});const i=o(1),l=o(307),s=i.__importStar(o(18)),n=o(309);class _ extends l.ActionToolView{doit(){window.open(this.model.redirect)}}t.HelpToolView=_,_.__name__=\"HelpToolView\";class r extends l.ActionTool{constructor(o){super(o),this.tool_name=\"Help\",this.icon=n.bk_tool_icon_help}static init_HelpTool(){this.prototype.default_view=_,this.define({help_tooltip:[s.String,\"Click the question mark to learn more about Bokeh plot tools.\"],redirect:[s.String,\"https://docs.bokeh.org/en/latest/docs/user_guide/tools.html\"]}),this.register_alias(\"help\",()=>new r)}get tooltip(){return this.help_tooltip}}t.HelpTool=r,r.__name__=\"HelpTool\",r.init_HelpTool()},\n", - " function _(o,_,l){Object.defineProperty(l,\"__esModule\",{value:!0}),l.bk_tool_icon_box_select=\"bk-tool-icon-box-select\",l.bk_tool_icon_box_zoom=\"bk-tool-icon-box-zoom\",l.bk_tool_icon_zoom_in=\"bk-tool-icon-zoom-in\",l.bk_tool_icon_zoom_out=\"bk-tool-icon-zoom-out\",l.bk_tool_icon_help=\"bk-tool-icon-help\",l.bk_tool_icon_hover=\"bk-tool-icon-hover\",l.bk_tool_icon_crosshair=\"bk-tool-icon-crosshair\",l.bk_tool_icon_lasso_select=\"bk-tool-icon-lasso-select\",l.bk_tool_icon_pan=\"bk-tool-icon-pan\",l.bk_tool_icon_xpan=\"bk-tool-icon-xpan\",l.bk_tool_icon_ypan=\"bk-tool-icon-ypan\",l.bk_tool_icon_range=\"bk-tool-icon-range\",l.bk_tool_icon_polygon_select=\"bk-tool-icon-polygon-select\",l.bk_tool_icon_redo=\"bk-tool-icon-redo\",l.bk_tool_icon_reset=\"bk-tool-icon-reset\",l.bk_tool_icon_save=\"bk-tool-icon-save\",l.bk_tool_icon_tap_select=\"bk-tool-icon-tap-select\",l.bk_tool_icon_undo=\"bk-tool-icon-undo\",l.bk_tool_icon_wheel_pan=\"bk-tool-icon-wheel-pan\",l.bk_tool_icon_wheel_zoom=\"bk-tool-icon-wheel-zoom\",l.bk_tool_icon_box_edit=\"bk-tool-icon-box-edit\",l.bk_tool_icon_freehand_draw=\"bk-tool-icon-freehand-draw\",l.bk_tool_icon_poly_draw=\"bk-tool-icon-poly-draw\",l.bk_tool_icon_point_draw=\"bk-tool-icon-point-draw\",l.bk_tool_icon_poly_edit=\"bk-tool-icon-poly-edit\",l.bk_tool_icon_line_edit=\"bk-tool-icon-line-edit\"},\n", - " function _(o,l,b){Object.defineProperty(b,\"__esModule\",{value:!0}),b.bk_logo=\"bk-logo\",b.bk_logo_notebook=\"bk-logo-notebook\",b.bk_logo_small=\"bk-logo-small\",b.bk_grey=\"bk-grey\"},\n", - " function _(l,n,o){Object.defineProperty(o,\"__esModule\",{value:!0});o.default=\"\\n.bk-root .bk-logo {\\n margin: 5px;\\n position: relative;\\n display: block;\\n background-repeat: no-repeat;\\n}\\n.bk-root .bk-logo.bk-grey {\\n filter: url(\\\"data:image/svg+xml;utf8,#grayscale\\\");\\n /* Firefox 10+, Firefox on Android */\\n filter: gray;\\n /* IE6-9 */\\n -webkit-filter: grayscale(100%);\\n /* Chrome 19+, Safari 6+, Safari 6+ iOS */\\n}\\n.bk-root .bk-logo-small {\\n width: 20px;\\n height: 20px;\\n background-image: url(data:image/png;base64,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);\\n}\\n.bk-root .bk-logo-notebook {\\n display: inline-block;\\n vertical-align: middle;\\n margin-right: 5px;\\n}\\n\"},\n", - " function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});var s=this&&this.__rest||function(t,e){var i={};for(var s in t)Object.prototype.hasOwnProperty.call(t,s)&&e.indexOf(s)<0&&(i[s]=t[s]);if(null!=t&&\"function\"==typeof Object.getOwnPropertySymbols){var n=0;for(s=Object.getOwnPropertySymbols(t);nt)}}request_layout(){this._needs_layout=!0,this.request_paint()}reset(){\"standard\"==this.model.reset_policy&&(this.clear_state(),this.reset_range(),this.reset_selection()),this.model.trigger_event(new c.Reset)}remove(){this.ui_event_bus.destroy(),p.remove_views(this.renderer_views),p.remove_views(this.tool_views),this.canvas_view.remove(),super.remove()}render(){super.render(),this.el.appendChild(this.canvas_view.el),this.canvas_view.render()}initialize(){this.pause(),super.initialize(),this.state_changed=new u.Signal0(this,\"state_changed\"),this.lod_started=!1,this.visuals=new b.Visuals(this.model),this._initial_state_info={selection:new Map,dimensions:{width:0,height:0}},this.visibility_callbacks=[],this.state={history:[],index:-1};const{hidpi:t,output_backend:e}=this.model;this.canvas=new a.Canvas({hidpi:t,output_backend:e}),this.frame=new n.CartesianFrame(this.model.x_scale,this.model.y_scale,this.model.x_range,this.model.y_range,this.model.extra_x_ranges,this.model.extra_y_ranges),this.throttled_paint=m.throttle(()=>this.repaint(),1e3/60);const{title_location:i,title:s}=this.model;null!=i&&null!=s&&(this._title=s instanceof h.Title?s:new h.Title({text:s}));const{toolbar_location:o,toolbar:l}=this.model;null!=o&&null!=l&&(this._toolbar=new d.ToolbarPanel({toolbar:l}),l.toolbar_location=o),this.renderer_views=new Map,this.tool_views=new Map}async lazy_initialize(){this.canvas_view=await p.build_view(this.canvas,{parent:this}),this.ui_event_bus=new f.UIEvents(this,this.model.toolbar,this.canvas_view.events_el),await this.build_renderer_views(),await this.build_tool_views(),this.update_dataranges(),this.unpause(!0),g.logger.debug(\"PlotView initialized\")}_width_policy(){return null==this.model.frame_width?super._width_policy():\"min\"}_height_policy(){return null==this.model.frame_height?super._height_policy():\"min\"}_update_layout(){this.layout=new x.BorderLayout,this.layout.set_sizing(this.box_sizing());const{frame_width:t,frame_height:e}=this.model;this.layout.center_panel=this.frame,this.layout.center_panel.set_sizing(Object.assign(Object.assign({},null!=t?{width_policy:\"fixed\",width:t}:{width_policy:\"fit\"}),null!=e?{height_policy:\"fixed\",height:e}:{height_policy:\"fit\"}));const i=w.copy(this.model.above),s=w.copy(this.model.below),n=w.copy(this.model.left),a=w.copy(this.model.right),o=t=>{switch(t){case\"above\":return i;case\"below\":return s;case\"left\":return n;case\"right\":return a}},{title_location:l,title:r}=this.model;null!=l&&null!=r&&o(l).push(this._title);const{toolbar_location:_,toolbar:c}=this.model;if(null!=_&&null!=c){const t=o(_);let e=!0;if(this.model.toolbar_sticky)for(let i=0;i{const i=this.renderer_views.get(e);return i.layout=new z.SidePanel(t,i)},p=(t,e)=>{const i=\"above\"==t||\"below\"==t,s=[];for(const n of e)if(v.isArray(n)){const e=n.map(e=>{const s=u(t,e);if(e instanceof d.ToolbarPanel){const t=i?\"width_policy\":\"height_policy\";s.set_sizing(Object.assign(Object.assign({},s.sizing),{[t]:\"min\"}))}return s});let a;i?(a=new M.Row(e),a.set_sizing({width_policy:\"max\",height_policy:\"min\"})):(a=new M.Column(e),a.set_sizing({width_policy:\"min\",height_policy:\"max\"})),a.absolute=!0,s.push(a)}else s.push(u(t,n));return s},f=null!=this.model.min_border?this.model.min_border:0;this.layout.min_border={left:null!=this.model.min_border_left?this.model.min_border_left:f,top:null!=this.model.min_border_top?this.model.min_border_top:f,right:null!=this.model.min_border_right?this.model.min_border_right:f,bottom:null!=this.model.min_border_bottom?this.model.min_border_bottom:f};const b=new y.VStack,g=new y.VStack,m=new y.HStack,O=new y.HStack;b.children=w.reversed(p(\"above\",i)),g.children=p(\"below\",s),m.children=w.reversed(p(\"left\",n)),O.children=p(\"right\",a),b.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),g.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),m.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),O.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),this.layout.top_panel=b,this.layout.bottom_panel=g,this.layout.left_panel=m,this.layout.right_panel=O}get axis_views(){const t=[];for(const[,e]of this.renderer_views)e instanceof _.AxisView&&t.push(e);return t}set_cursor(t=\"default\"){this.canvas_view.el.style.cursor=t}set_toolbar_visibility(t){for(const e of this.visibility_callbacks)e(t)}update_dataranges(){const t=new Map,e=new Map;let i=!1;for(const[,t]of this.frame.x_ranges)t instanceof o.DataRange1d&&\"log\"==t.scale_hint&&(i=!0);for(const[,t]of this.frame.y_ranges)t instanceof o.DataRange1d&&\"log\"==t.scale_hint&&(i=!0);for(const[s,n]of this.renderer_views)if(n instanceof l.GlyphRendererView){const a=n.glyph.bounds();if(null!=a&&t.set(s,a),i){const t=n.glyph.log_bounds();null!=t&&e.set(s,t)}}let s=!1,n=!1;const{width:a,height:r}=this.frame.bbox;let h;!1!==this.model.match_aspect&&0!=a&&0!=r&&(h=1/this.model.aspect_scale*(a/r));for(const[,i]of this.frame.x_ranges){if(i instanceof o.DataRange1d){const n=\"log\"==i.scale_hint?e:t;i.update(n,0,this.model,h),i.follow&&(s=!0)}null!=i.bounds&&(n=!0)}for(const[,i]of this.frame.y_ranges){if(i instanceof o.DataRange1d){const n=\"log\"==i.scale_hint?e:t;i.update(n,1,this.model,h),i.follow&&(s=!0)}null!=i.bounds&&(n=!0)}if(s&&n){g.logger.warn(\"Follow enabled so bounds are unset.\");for(const[,t]of this.frame.x_ranges)t.bounds=null;for(const[,t]of this.frame.y_ranges)t.bounds=null}this.range_update_timestamp=Date.now()}push_state(t,e){const{history:i,index:s}=this.state,n=null!=i[s]?i[s].info:{},a=Object.assign(Object.assign(Object.assign({},this._initial_state_info),n),e);this.state.history=this.state.history.slice(0,this.state.index+1),this.state.history.push({type:t,info:a}),this.state.index=this.state.history.length-1,this.state_changed.emit()}clear_state(){this.state={history:[],index:-1},this.state_changed.emit()}can_undo(){return this.state.index>=0}can_redo(){return this.state.index=a.end&&(n=!0,a.end=t,(e||i)&&(a.start=t+l)),null!=o&&o<=a.start&&(n=!0,a.start=o,(e||i)&&(a.end=o-l))):(null!=t&&t>=a.start&&(n=!0,a.start=t,(e||i)&&(a.end=t+l)),null!=o&&o<=a.end&&(n=!0,a.end=o,(e||i)&&(a.start=o-l)))}}if(!(i&&n&&s))for(const[e,i]of t)e.have_updated_interactively=!0,e.start==i.start&&e.end==i.end||e.setv(i)}_get_weight_to_constrain_interval(t,e){const{min_interval:i}=t;let{max_interval:s}=t;if(null!=t.bounds&&\"auto\"!=t.bounds){const[e,i]=t.bounds;if(null!=e&&null!=i){const t=Math.abs(i-e);s=null!=s?Math.min(s,t):t}}let n=1;if(null!=i||null!=s){const a=Math.abs(t.end-t.start),o=Math.abs(e.end-e.start);i>0&&o0&&o>s&&(n=(s-a)/(o-a)),n=Math.max(0,Math.min(1,n))}return n}update_range(t,e=!1,i=!1,s=!0){this.pause();const{x_ranges:n,y_ranges:a}=this.frame;if(null==t){for(const[,t]of n)t.reset();for(const[,t]of a)t.reset();this.update_dataranges()}else{const o=[];for(const[e,i]of n)o.push([i,t.xrs.get(e)]);for(const[e,i]of a)o.push([i,t.yrs.get(e)]);i&&this._update_ranges_together(o),this._update_ranges_individually(o,e,i,s)}this.unpause()}reset_range(){this.update_range(null)}_invalidate_layout(){(()=>{for(const t of this.model.side_panels){if(this.renderer_views.get(t).layout.has_size_changed())return!0}return!1})()&&this.root.compute_layout()}get_renderer_views(){return this.computed_renderers.map(t=>this.renderer_views.get(t))}async build_renderer_views(){this.computed_renderers=[];const{above:t,below:e,left:i,right:s,center:n,renderers:a}=this.model;this.computed_renderers.push(...t,...e,...i,...s,...n,...a),null!=this._title&&this.computed_renderers.push(this._title),null!=this._toolbar&&this.computed_renderers.push(this._toolbar);for(const t of this.model.toolbar.tools)null!=t.overlay&&this.computed_renderers.push(t.overlay),this.computed_renderers.push(...t.synthetic_renderers);await p.build_views(this.renderer_views,this.computed_renderers,{parent:this})}async build_tool_views(){const t=this.model.toolbar.tools;(await p.build_views(this.tool_views,t,{parent:this})).map(t=>this.ui_event_bus.register_tool(t))}connect_signals(){super.connect_signals();const{x_ranges:t,y_ranges:e}=this.frame;for(const[,e]of t)this.connect(e.change,()=>{this._needs_layout=!0,this.request_paint()});for(const[,t]of e)this.connect(t.change,()=>{this._needs_layout=!0,this.request_paint()});const{plot_width:i,plot_height:s}=this.model.properties;this.on_change([i,s],()=>this.invalidate_layout());const{above:n,below:a,left:o,right:l,center:r,renderers:h}=this.model.properties;this.on_change([n,a,o,l,r,h],async()=>await this.build_renderer_views()),this.connect(this.model.toolbar.properties.tools.change,async()=>{await this.build_renderer_views(),await this.build_tool_views()}),this.connect(this.model.change,()=>this.request_paint()),this.connect(this.model.reset,()=>this.reset())}set_initial_range(){let t=!0;const{x_ranges:e,y_ranges:i}=this.frame,s=new Map,n=new Map;for(const[i,n]of e){const{start:e,end:a}=n;if(null==e||null==a||isNaN(e+a)){t=!1;break}s.set(i,{start:e,end:a})}if(t)for(const[e,s]of i){const{start:i,end:a}=s;if(null==i||null==a||isNaN(i+a)){t=!1;break}n.set(e,{start:i,end:a})}t?(this._initial_state_info.range={xrs:s,yrs:n},g.logger.debug(\"initial ranges set\")):g.logger.warn(\"could not set initial ranges\")}has_finished(){if(!super.has_finished())return!1;if(this.model.visible)for(const[,t]of this.renderer_views)if(!t.has_finished())return!1;return!0}after_layout(){if(super.after_layout(),this._needs_layout=!1,this.model.setv({inner_width:Math.round(this.frame.bbox.width),inner_height:Math.round(this.frame.bbox.height),outer_width:Math.round(this.layout.bbox.width),outer_height:Math.round(this.layout.bbox.height)},{no_change:!0}),!1!==this.model.match_aspect&&(this.pause(),this.update_dataranges(),this.unpause(!0)),!this._outer_bbox.equals(this.layout.bbox)){const{width:t,height:e}=this.layout.bbox;this.canvas_view.resize(t,e),this._outer_bbox=this.layout.bbox,this._invalidate_all=!0,this._needs_paint=!0}this._inner_bbox.equals(this.frame.inner_bbox)||(this._inner_bbox=this.layout.inner_bbox,this._needs_paint=!0),this._needs_paint&&this.paint()}repaint(){this._needs_layout&&this._invalidate_layout(),this.paint()}paint(){if(this.is_paused||!this.model.visible)return;g.logger.trace(\"PlotView.paint() for \"+this.model.id);const{document:t}=this.model;if(null!=t){const e=t.interactive_duration();e>=0&&e{t.interactive_duration()>this.model.lod_timeout&&t.interactive_stop(),this.request_paint()},this.model.lod_timeout):t.interactive_stop()}for(const[,t]of this.renderer_views)if(null==this.range_update_timestamp||t instanceof l.GlyphRendererView&&t.set_data_timestamp>this.range_update_timestamp){this.update_dataranges();break}let e=!1,i=!1;if(this._invalidate_all)e=!0,i=!0;else for(const t of this._invalidated_painters){const{level:s}=t.model;if(\"overlay\"!=s?e=!0:i=!0,e&&i)break}this._invalidated_painters.clear(),this._invalidate_all=!1;const s=[this.frame.bbox.left,this.frame.bbox.top,this.frame.bbox.width,this.frame.bbox.height],{primary:n,overlays:a}=this.canvas_view;e&&(n.prepare(),this.canvas_view.prepare_webgl(s),this.canvas_view.clear_webgl(),this._map_hook(n.ctx,s),this._paint_empty(n.ctx,s),this._paint_outline(n.ctx,s),this._paint_levels(n.ctx,\"image\",s,!0),this._paint_levels(n.ctx,\"underlay\",s,!0),this._paint_levels(n.ctx,\"glyph\",s,!0),this._paint_levels(n.ctx,\"guide\",s,!1),this._paint_levels(n.ctx,\"annotation\",s,!1),n.finish()),i&&(a.prepare(),this._paint_levels(a.ctx,\"overlay\",s,!1),a.finish()),null==this._initial_state_info.range&&this.set_initial_range(),this._needs_paint=!1}_paint_levels(t,e,i,s){for(const n of this.computed_renderers){if(n.level!=e)continue;const a=this.renderer_views.get(n);t.save(),(s||a.needs_clip)&&(t.beginPath(),t.rect(...i),t.clip()),a.render(),t.restore(),a.has_webgl&&a.needs_webgl_blit&&(this.canvas_view.blit_webgl(t),this.canvas_view.clear_webgl())}}_map_hook(t,e){}_paint_empty(t,e){const[i,s,n,a]=[0,0,this.layout.bbox.width,this.layout.bbox.height],[o,l,r,h]=e;this.visuals.border_fill.doit&&(this.visuals.border_fill.set_value(t),t.fillRect(i,s,n,a),t.clearRect(o,l,r,h)),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(t),t.fillRect(o,l,r,h))}_paint_outline(t,e){if(this.visuals.outline_line.doit){t.save(),this.visuals.outline_line.set_value(t);let[i,s,n,a]=e;i+n==this.layout.bbox.width&&(n-=1),s+a==this.layout.bbox.height&&(a-=1),t.strokeRect(i,s,n,a),t.restore()}}to_blob(){return this.canvas_view.to_blob()}export(t,e=!0){const i=\"png\"==t?\"canvas\":\"svg\",s=new a.CanvasLayer(i,e),{width:n,height:o}=this.layout.bbox;s.resize(n,o);const{canvas:l}=this.canvas_view.compose();return s.ctx.drawImage(l,0,0),s}serializable_state(){const t=super.serializable_state(),{children:e}=t,i=s(t,[\"children\"]),n=this.get_renderer_views().map(t=>t.serializable_state()).filter(t=>\"bbox\"in t);return Object.assign(Object.assign({},i),{children:[...e,...n]})}}i.PlotView=k,k.__name__=\"PlotView\"},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});var n=this&&this.__decorate||function(e,t,s,n){var _,a=arguments.length,o=a<3?t:null===n?n=Object.getOwnPropertyDescriptor(t,s):n;if(\"object\"==typeof Reflect&&\"function\"==typeof Reflect.decorate)o=Reflect.decorate(e,t,s,n);else for(var r=e.length-1;r>=0;r--)(_=e[r])&&(o=(a<3?_(o):a>3?_(t,s,o):_(t,s))||o);return a>3&&o&&Object.defineProperty(t,s,o),o};function _(e){return function(t){t.prototype.event_name=e}}class a{to_json(){const{event_name:e}=this;return{event_name:e,event_values:this._to_json()}}}s.BokehEvent=a,a.__name__=\"BokehEvent\";class o extends a{constructor(){super(...arguments),this.origin=null}_to_json(){return{model:this.origin}}}s.ModelEvent=o,o.__name__=\"ModelEvent\";let r=class extends a{_to_json(){return{}}};s.DocumentReady=r,r.__name__=\"DocumentReady\",s.DocumentReady=r=n([_(\"document_ready\")],r);let c=class extends o{};s.ButtonClick=c,c.__name__=\"ButtonClick\",s.ButtonClick=c=n([_(\"button_click\")],c);let l=class extends o{constructor(e){super(),this.item=e}_to_json(){const{item:e}=this;return Object.assign(Object.assign({},super._to_json()),{item:e})}};s.MenuItemClick=l,l.__name__=\"MenuItemClick\",s.MenuItemClick=l=n([_(\"menu_item_click\")],l);class i extends o{}s.UIEvent=i,i.__name__=\"UIEvent\";let u=class extends i{};s.LODStart=u,u.__name__=\"LODStart\",s.LODStart=u=n([_(\"lodstart\")],u);let d=class extends i{};s.LODEnd=d,d.__name__=\"LODEnd\",s.LODEnd=d=n([_(\"lodend\")],d);let h=class extends i{constructor(e,t){super(),this.geometry=e,this.final=t}_to_json(){const{geometry:e,final:t}=this;return Object.assign(Object.assign({},super._to_json()),{geometry:e,final:t})}};s.SelectionGeometry=h,h.__name__=\"SelectionGeometry\",s.SelectionGeometry=h=n([_(\"selectiongeometry\")],h);let m=class extends i{};s.Reset=m,m.__name__=\"Reset\",s.Reset=m=n([_(\"reset\")],m);class x extends i{constructor(e,t,s,n){super(),this.sx=e,this.sy=t,this.x=s,this.y=n}_to_json(){const{sx:e,sy:t,x:s,y:n}=this;return Object.assign(Object.assign({},super._to_json()),{sx:e,sy:t,x:s,y:n})}}s.PointEvent=x,x.__name__=\"PointEvent\";let p=class extends x{constructor(e,t,s,n,_,a){super(e,t,s,n),this.sx=e,this.sy=t,this.x=s,this.y=n,this.delta_x=_,this.delta_y=a}_to_json(){const{delta_x:e,delta_y:t}=this;return Object.assign(Object.assign({},super._to_json()),{delta_x:e,delta_y:t})}};s.Pan=p,p.__name__=\"Pan\",s.Pan=p=n([_(\"pan\")],p);let j=class extends x{constructor(e,t,s,n,_){super(e,t,s,n),this.sx=e,this.sy=t,this.x=s,this.y=n,this.scale=_}_to_json(){const{scale:e}=this;return Object.assign(Object.assign({},super._to_json()),{scale:e})}};s.Pinch=j,j.__name__=\"Pinch\",s.Pinch=j=n([_(\"pinch\")],j);let y=class extends x{constructor(e,t,s,n,_){super(e,t,s,n),this.sx=e,this.sy=t,this.x=s,this.y=n,this.rotation=_}_to_json(){const{rotation:e}=this;return Object.assign(Object.assign({},super._to_json()),{rotation:e})}};s.Rotate=y,y.__name__=\"Rotate\",s.Rotate=y=n([_(\"rotate\")],y);let P=class extends x{constructor(e,t,s,n,_){super(e,t,s,n),this.sx=e,this.sy=t,this.x=s,this.y=n,this.delta=_}_to_json(){const{delta:e}=this;return Object.assign(Object.assign({},super._to_json()),{delta:e})}};s.MouseWheel=P,P.__name__=\"MouseWheel\",s.MouseWheel=P=n([_(\"wheel\")],P);let v=class extends x{};s.MouseMove=v,v.__name__=\"MouseMove\",s.MouseMove=v=n([_(\"mousemove\")],v);let O=class extends x{};s.MouseEnter=O,O.__name__=\"MouseEnter\",s.MouseEnter=O=n([_(\"mouseenter\")],O);let b=class extends x{};s.MouseLeave=b,b.__name__=\"MouseLeave\",s.MouseLeave=b=n([_(\"mouseleave\")],b);let g=class extends x{};s.Tap=g,g.__name__=\"Tap\",s.Tap=g=n([_(\"tap\")],g);let E=class extends x{};s.DoubleTap=E,E.__name__=\"DoubleTap\",s.DoubleTap=E=n([_(\"doubletap\")],E);let M=class extends x{};s.Press=M,M.__name__=\"Press\",s.Press=M=n([_(\"press\")],M);let R=class extends x{};s.PressUp=R,R.__name__=\"PressUp\",s.PressUp=R=n([_(\"pressup\")],R);let f=class extends x{};s.PanStart=f,f.__name__=\"PanStart\",s.PanStart=f=n([_(\"panstart\")],f);let S=class extends x{};s.PanEnd=S,S.__name__=\"PanEnd\",s.PanEnd=S=n([_(\"panend\")],S);let D=class extends x{};s.PinchStart=D,D.__name__=\"PinchStart\",s.PinchStart=D=n([_(\"pinchstart\")],D);let k=class extends x{};s.PinchEnd=k,k.__name__=\"PinchEnd\",s.PinchEnd=k=n([_(\"pinchend\")],k);let L=class extends x{};s.RotateStart=L,L.__name__=\"RotateStart\",s.RotateStart=L=n([_(\"rotatestart\")],L);let C=class extends x{};s.RotateEnd=C,C.__name__=\"RotateEnd\",s.RotateEnd=C=n([_(\"rotateend\")],C)},\n", - " function _(t,e,s){Object.defineProperty(s,\"__esModule\",{value:!0});const n=t(1),i=n.__importDefault(t(297)),r=t(15),a=t(19),h=t(72),_=n.__importStar(t(313)),o=t(315),c=t(9),l=t(8),p=t(32),u=t(302);class d{constructor(t,e,s){this.plot_view=t,this.toolbar=e,this.hit_area=s,this.pan_start=new r.Signal(this,\"pan:start\"),this.pan=new r.Signal(this,\"pan\"),this.pan_end=new r.Signal(this,\"pan:end\"),this.pinch_start=new r.Signal(this,\"pinch:start\"),this.pinch=new r.Signal(this,\"pinch\"),this.pinch_end=new r.Signal(this,\"pinch:end\"),this.rotate_start=new r.Signal(this,\"rotate:start\"),this.rotate=new r.Signal(this,\"rotate\"),this.rotate_end=new r.Signal(this,\"rotate:end\"),this.tap=new r.Signal(this,\"tap\"),this.doubletap=new r.Signal(this,\"doubletap\"),this.press=new r.Signal(this,\"press\"),this.pressup=new r.Signal(this,\"pressup\"),this.move_enter=new r.Signal(this,\"move:enter\"),this.move=new r.Signal(this,\"move\"),this.move_exit=new r.Signal(this,\"move:exit\"),this.scroll=new r.Signal(this,\"scroll\"),this.keydown=new r.Signal(this,\"keydown\"),this.keyup=new r.Signal(this,\"keyup\"),this.hammer=new i.default(this.hit_area,{touchAction:\"auto\",inputClass:i.default.TouchMouseInput}),this._configure_hammerjs(),this.hit_area.addEventListener(\"mousemove\",t=>this._mouse_move(t)),this.hit_area.addEventListener(\"mouseenter\",t=>this._mouse_enter(t)),this.hit_area.addEventListener(\"mouseleave\",t=>this._mouse_exit(t)),this.hit_area.addEventListener(\"contextmenu\",t=>this._context_menu(t)),this.hit_area.addEventListener(\"wheel\",t=>this._mouse_wheel(t)),document.addEventListener(\"keydown\",this),document.addEventListener(\"keyup\",this),this.menu=new u.ContextMenu([],{prevent_hide:t=>2==t.button&&t.target==this.hit_area}),this.hit_area.appendChild(this.menu.el)}destroy(){this.menu.remove(),this.hammer.destroy(),document.removeEventListener(\"keydown\",this),document.removeEventListener(\"keyup\",this)}handleEvent(t){\"keydown\"==t.type?this._key_down(t):\"keyup\"==t.type&&this._key_up(t)}_configure_hammerjs(){this.hammer.get(\"doubletap\").recognizeWith(\"tap\"),this.hammer.get(\"tap\").requireFailure(\"doubletap\"),this.hammer.get(\"doubletap\").dropRequireFailure(\"tap\"),this.hammer.on(\"doubletap\",t=>this._doubletap(t)),this.hammer.on(\"tap\",t=>this._tap(t)),this.hammer.on(\"press\",t=>this._press(t)),this.hammer.on(\"pressup\",t=>this._pressup(t)),this.hammer.get(\"pan\").set({direction:i.default.DIRECTION_ALL}),this.hammer.on(\"panstart\",t=>this._pan_start(t)),this.hammer.on(\"pan\",t=>this._pan(t)),this.hammer.on(\"panend\",t=>this._pan_end(t)),this.hammer.get(\"pinch\").set({enable:!0}),this.hammer.on(\"pinchstart\",t=>this._pinch_start(t)),this.hammer.on(\"pinch\",t=>this._pinch(t)),this.hammer.on(\"pinchend\",t=>this._pinch_end(t)),this.hammer.get(\"rotate\").set({enable:!0}),this.hammer.on(\"rotatestart\",t=>this._rotate_start(t)),this.hammer.on(\"rotate\",t=>this._rotate(t)),this.hammer.on(\"rotateend\",t=>this._rotate_end(t))}register_tool(t){const e=t.model.event_type;null!=e&&(l.isString(e)?this._register_tool(t,e):e.forEach((e,s)=>this._register_tool(t,e,s<1)))}_register_tool(t,e,s=!0){const n=t,{id:i}=n.model,r=t=>e=>{e.id==i&&t(e.e)},h=t=>e=>{t(e.e)};switch(e){case\"pan\":null!=n._pan_start&&n.connect(this.pan_start,r(n._pan_start.bind(n))),null!=n._pan&&n.connect(this.pan,r(n._pan.bind(n))),null!=n._pan_end&&n.connect(this.pan_end,r(n._pan_end.bind(n)));break;case\"pinch\":null!=n._pinch_start&&n.connect(this.pinch_start,r(n._pinch_start.bind(n))),null!=n._pinch&&n.connect(this.pinch,r(n._pinch.bind(n))),null!=n._pinch_end&&n.connect(this.pinch_end,r(n._pinch_end.bind(n)));break;case\"rotate\":null!=n._rotate_start&&n.connect(this.rotate_start,r(n._rotate_start.bind(n))),null!=n._rotate&&n.connect(this.rotate,r(n._rotate.bind(n))),null!=n._rotate_end&&n.connect(this.rotate_end,r(n._rotate_end.bind(n)));break;case\"move\":null!=n._move_enter&&n.connect(this.move_enter,r(n._move_enter.bind(n))),null!=n._move&&n.connect(this.move,r(n._move.bind(n))),null!=n._move_exit&&n.connect(this.move_exit,r(n._move_exit.bind(n)));break;case\"tap\":null!=n._tap&&n.connect(this.tap,r(n._tap.bind(n)));break;case\"press\":null!=n._press&&n.connect(this.press,r(n._press.bind(n))),null!=n._pressup&&n.connect(this.pressup,r(n._pressup.bind(n)));break;case\"scroll\":null!=n._scroll&&n.connect(this.scroll,r(n._scroll.bind(n)));break;default:throw new Error(\"unsupported event_type: \"+e)}s&&(null!=n._doubletap&&n.connect(this.doubletap,h(n._doubletap.bind(n))),null!=n._keydown&&n.connect(this.keydown,h(n._keydown.bind(n))),null!=n._keyup&&n.connect(this.keyup,h(n._keyup.bind(n))),p.is_mobile&&null!=n._scroll&&\"pinch\"==e&&(a.logger.debug(\"Registering scroll on touch screen\"),n.connect(this.scroll,r(n._scroll.bind(n)))))}_hit_test_renderers(t,e){const s=this.plot_view.get_renderer_views();for(const n of c.reversed(s)){const{level:s}=n.model;if((\"annotation\"==s||\"overlay\"==s)&&null!=n.interactive_hit&&n.interactive_hit(t,e))return n}return null}_hit_test_frame(t,e){return this.plot_view.frame.bbox.contains(t,e)}_hit_test_canvas(t,e){return this.plot_view.layout.bbox.contains(t,e)}_trigger(t,e,s){const n=this.toolbar.gestures,i=t.name.split(\":\")[0],r=this._hit_test_renderers(e.sx,e.sy),a=this._hit_test_canvas(e.sx,e.sy);switch(i){case\"move\":{const s=n[i].active;null!=s&&this.trigger(t,e,s.id);const h=this.toolbar.inspectors.filter(t=>t.active);let _=\"default\";null!=r?(_=r.cursor(e.sx,e.sy)||_,c.is_empty(h)||(t=this.move_exit)):this._hit_test_frame(e.sx,e.sy)&&(c.is_empty(h)||(_=\"crosshair\")),this.plot_view.set_cursor(_),this.plot_view.set_toolbar_visibility(a),h.map(s=>this.trigger(t,e,s.id));break}case\"tap\":{const{target:a}=s;if(null!=a&&a!=this.hit_area)return;null!=r&&null!=r.on_hit&&r.on_hit(e.sx,e.sy);const h=n[i].active;null!=h&&this.trigger(t,e,h.id);break}case\"scroll\":{const i=n[p.is_mobile?\"pinch\":\"scroll\"].active;null!=i&&(s.preventDefault(),s.stopPropagation(),this.trigger(t,e,i.id));break}case\"pan\":{const r=n[i].active;null!=r&&(s.preventDefault(),this.trigger(t,e,r.id));break}default:{const s=n[i].active;null!=s&&this.trigger(t,e,s.id)}}this._trigger_bokeh_event(e)}trigger(t,e,s=null){t.emit({id:s,e})}_trigger_bokeh_event(t){const e=(()=>{const{sx:e,sy:s}=t,n=this.plot_view.frame.x_scale.invert(e),i=this.plot_view.frame.y_scale.invert(s);switch(t.type){case\"wheel\":return new _.MouseWheel(e,s,n,i,t.delta);case\"mousemove\":return new _.MouseMove(e,s,n,i);case\"mouseenter\":return new _.MouseEnter(e,s,n,i);case\"mouseleave\":return new _.MouseLeave(e,s,n,i);case\"tap\":return new _.Tap(e,s,n,i);case\"doubletap\":return new _.DoubleTap(e,s,n,i);case\"press\":return new _.Press(e,s,n,i);case\"pressup\":return new _.PressUp(e,s,n,i);case\"pan\":return new _.Pan(e,s,n,i,t.deltaX,t.deltaY);case\"panstart\":return new _.PanStart(e,s,n,i);case\"panend\":return new _.PanEnd(e,s,n,i);case\"pinch\":return new _.Pinch(e,s,n,i,t.scale);case\"pinchstart\":return new _.PinchStart(e,s,n,i);case\"pinchend\":return new _.PinchEnd(e,s,n,i);case\"rotate\":return new _.Rotate(e,s,n,i,t.rotation);case\"rotatestart\":return new _.RotateStart(e,s,n,i);case\"rotateend\":return new _.RotateEnd(e,s,n,i);default:return}})();null!=e&&this.plot_view.model.trigger_event(e)}_get_sxy(t){const{pageX:e,pageY:s}=function(t){return\"undefined\"!=typeof TouchEvent&&t instanceof TouchEvent}(t)?(0!=t.touches.length?t.touches:t.changedTouches)[0]:t,{left:n,top:i}=h.offset(this.hit_area);return{sx:e-n,sy:s-i}}_pan_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{deltaX:t.deltaX,deltaY:t.deltaY,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_pinch_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{scale:t.scale,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_rotate_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{rotation:t.rotation,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_tap_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_move_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t)),{shiftKey:t.shiftKey,ctrlKey:t.ctrlKey})}_scroll_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t)),{delta:o.getDeltaY(t),shiftKey:t.shiftKey,ctrlKey:t.ctrlKey})}_key_event(t){return{type:t.type,keyCode:t.keyCode}}_pan_start(t){const e=this._pan_event(t);e.sx-=t.deltaX,e.sy-=t.deltaY,this._trigger(this.pan_start,e,t.srcEvent)}_pan(t){this._trigger(this.pan,this._pan_event(t),t.srcEvent)}_pan_end(t){this._trigger(this.pan_end,this._pan_event(t),t.srcEvent)}_pinch_start(t){this._trigger(this.pinch_start,this._pinch_event(t),t.srcEvent)}_pinch(t){this._trigger(this.pinch,this._pinch_event(t),t.srcEvent)}_pinch_end(t){this._trigger(this.pinch_end,this._pinch_event(t),t.srcEvent)}_rotate_start(t){this._trigger(this.rotate_start,this._rotate_event(t),t.srcEvent)}_rotate(t){this._trigger(this.rotate,this._rotate_event(t),t.srcEvent)}_rotate_end(t){this._trigger(this.rotate_end,this._rotate_event(t),t.srcEvent)}_tap(t){this._trigger(this.tap,this._tap_event(t),t.srcEvent)}_doubletap(t){const e=this._tap_event(t);this._trigger_bokeh_event(e),this.trigger(this.doubletap,e)}_press(t){this._trigger(this.press,this._tap_event(t),t.srcEvent)}_pressup(t){this._trigger(this.pressup,this._tap_event(t),t.srcEvent)}_mouse_enter(t){this._trigger(this.move_enter,this._move_event(t),t)}_mouse_move(t){this._trigger(this.move,this._move_event(t),t)}_mouse_exit(t){this._trigger(this.move_exit,this._move_event(t),t)}_mouse_wheel(t){this._trigger(this.scroll,this._scroll_event(t),t)}_context_menu(t){!this.menu.is_open&&this.menu.can_open&&t.preventDefault();const{sx:e,sy:s}=this._get_sxy(t);this.menu.toggle({left:e,top:s})}_key_down(t){this.trigger(this.keydown,this._key_event(t))}_key_up(t){this.trigger(this.keyup,this._key_event(t))}}s.UIEvents=d,d.__name__=\"UIEvents\"},\n", - " function _(e,t,n){\n", - " /*!\n", - " * jQuery Mousewheel 3.1.13\n", - " *\n", - " * Copyright jQuery Foundation and other contributors\n", - " * Released under the MIT license\n", - " * http://jquery.org/license\n", - " */\n", - " function r(e){const t=getComputedStyle(e).fontSize;return null!=t?parseInt(t,10):null}Object.defineProperty(n,\"__esModule\",{value:!0}),n.getDeltaY=function(e){let t=-e.deltaY;if(e.target instanceof HTMLElement)switch(e.deltaMode){case e.DOM_DELTA_LINE:t*=r((n=e.target).offsetParent||document.body)||r(n)||16;break;case e.DOM_DELTA_PAGE:t*=function(e){return e.clientHeight}(e.target)}var n;return t}},\n", - " function _(n,e,o){Object.defineProperty(o,\"__esModule\",{value:!0});const t=(\"undefined\"!=typeof window?window.requestAnimationFrame:void 0)||(\"undefined\"!=typeof window?window.webkitRequestAnimationFrame:void 0)||(\"undefined\"!=typeof window?window.mozRequestAnimationFrame:void 0)||(\"undefined\"!=typeof window?window.msRequestAnimationFrame:void 0)||function(n){return n(Date.now()),-1};o.throttle=function(n,e){let o=null,i=0,u=!1;return function(){return new Promise((d,w)=>{const 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i.Sizeable(t).shrink_by({left:h,right:r,top:n,bottom:g}),m=this.center_panel.measure(_);return{width:h+m.width+r,height:n+m.height+g,inner:{left:h,right:r,top:n,bottom:g},align:(()=>{const{width_policy:t,height_policy:e}=this.center_panel.sizing;return\"fixed\"!=t&&\"fixed\"!=e})()}}_set_geometry(t,e){super._set_geometry(t,e),this.center_panel.set_geometry(e);const h=this.left_panel.measure({width:0,height:t.height}),i=this.right_panel.measure({width:0,height:t.height}),o=this.top_panel.measure({width:t.width,height:0}),s=this.bottom_panel.measure({width:t.width,height:0}),{left:n,top:a,right:g,bottom:_}=e;this.top_panel.set_geometry(new r.BBox({left:n,right:g,bottom:a,height:o.height})),this.bottom_panel.set_geometry(new r.BBox({left:n,right:g,top:_,height:s.height})),this.left_panel.set_geometry(new r.BBox({top:a,bottom:_,right:n,width:h.width})),this.right_panel.set_geometry(new r.BBox({top:a,bottom:_,left:g,width:i.width}))}}h.BorderLayout=s,s.__name__=\"BorderLayout\"},\n", - " function _(i,t,e){Object.defineProperty(e,\"__esModule\",{value:!0});const l=i(213),a=i(214),r=i(8),o=Math.PI/2,h=\"left\",s=\"center\",n={above:{parallel:0,normal:-o,horizontal:0,vertical:-o},below:{parallel:0,normal:o,horizontal:0,vertical:o},left:{parallel:-o,normal:0,horizontal:0,vertical:-o},right:{parallel:o,normal:0,horizontal:0,vertical:o}},d={above:{justified:\"top\",parallel:\"alphabetic\",normal:\"middle\",horizontal:\"alphabetic\",vertical:\"middle\"},below:{justified:\"bottom\",parallel:\"hanging\",normal:\"middle\",horizontal:\"hanging\",vertical:\"middle\"},left:{justified:\"top\",parallel:\"alphabetic\",normal:\"middle\",horizontal:\"middle\",vertical:\"alphabetic\"},right:{justified:\"top\",parallel:\"alphabetic\",normal:\"middle\",horizontal:\"middle\",vertical:\"alphabetic\"}},_={above:{justified:s,parallel:s,normal:h,horizontal:s,vertical:h},below:{justified:s,parallel:s,normal:h,horizontal:s,vertical:h},left:{justified:s,parallel:s,normal:\"right\",horizontal:\"right\",vertical:s},right:{justified:s,parallel:s,normal:h,horizontal:h,vertical:s}},c={above:\"right\",below:h,left:\"right\",right:h},m={above:h,below:\"right\",left:\"right\",right:h};class g extends a.ContentLayoutable{constructor(i,t){switch(super(),this.side=i,this.obj=t,this.side){case\"above\":this._dim=0,this._normals=[0,-1];break;case\"below\":this._dim=0,this._normals=[0,1];break;case\"left\":this._dim=1,this._normals=[-1,0];break;case\"right\":this._dim=1,this._normals=[1,0]}this.is_horizontal?this.set_sizing({width_policy:\"max\",height_policy:\"fixed\"}):this.set_sizing({width_policy:\"fixed\",height_policy:\"max\"})}_content_size(){return new l.Sizeable(this.get_oriented_size())}get_oriented_size(){const{width:i,height:t}=this.obj.get_size();return!this.obj.rotate||this.is_horizontal?{width:i,height:t}:{width:t,height:i}}has_size_changed(){const{width:i,height:t}=this.get_oriented_size();return this.is_horizontal?this.bbox.height!=t:this.bbox.width!=i}get dimension(){return this._dim}get normals(){return this._normals}get is_horizontal(){return 0==this._dim}get is_vertical(){return 1==this._dim}apply_label_text_heuristics(i,t){const e=this.side;let l,a;r.isString(t)?(l=d[e][t],a=_[e][t]):t<0?(l=\"middle\",a=c[e]):(l=\"middle\",a=m[e]),i.textBaseline=l,i.textAlign=a}get_label_angle_heuristic(i){return n[this.side][i]}}e.SidePanel=g,g.__name__=\"SidePanel\"},\n", - " function _(t,e,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=t(15),o=t(72),a=t(37),n=t(312),p=new i.Signal0({},\"gmaps_ready\");class l extends n.PlotView{initialize(){this.pause(),super.initialize(),this._tiles_loaded=!1,this.zoom_count=0;const{zoom:t,lat:e,lng:s}=this.model.map_options;if(this.initial_zoom=t,this.initial_lat=e,this.initial_lng=s,\"undefined\"==typeof google||null==google.maps){if(void 0===window._bokeh_gmaps_callback){!function(t){window._bokeh_gmaps_callback=()=>p.emit();const e=document.createElement(\"script\");e.type=\"text/javascript\",e.src=`https://maps.googleapis.com/maps/api/js?v=3.36&key=${t}&callback=_bokeh_gmaps_callback`,document.body.appendChild(e)}(atob(this.model.api_key))}p.connect(()=>this.request_render())}this.unpause()}remove(){o.remove(this.map_el),super.remove()}update_range(t){if(null==t)this.map.setCenter({lat:this.initial_lat,lng:this.initial_lng}),this.map.setOptions({zoom:this.initial_zoom}),super.update_range(null);else if(null!=t.sdx||null!=t.sdy)this.map.panBy(t.sdx||0,t.sdy||0),super.update_range(t);else if(null!=t.factor){if(10!==this.zoom_count)return void(this.zoom_count+=1);this.zoom_count=0,this.pause(),super.update_range(t);const e=t.factor<0?-1:1,s=this.map.getZoom(),i=s+e;if(i>=2){this.map.setZoom(i);const[t,e,,]=this._get_projected_bounds();e-t<0&&this.map.setZoom(s)}this.unpause()}this._set_bokeh_ranges()}_build_map(){const{maps:t}=google;this.map_types={satellite:t.MapTypeId.SATELLITE,terrain:t.MapTypeId.TERRAIN,roadmap:t.MapTypeId.ROADMAP,hybrid:t.MapTypeId.HYBRID};const e=this.model.map_options,s={center:new t.LatLng(e.lat,e.lng),zoom:e.zoom,disableDefaultUI:!0,mapTypeId:this.map_types[e.map_type],scaleControl:e.scale_control,tilt:e.tilt};null!=e.styles&&(s.styles=JSON.parse(e.styles)),this.map_el=o.div({style:{position:\"absolute\"}}),this.canvas_view.add_underlay(this.map_el),this.map=new t.Map(this.map_el,s),t.event.addListener(this.map,\"idle\",()=>this._set_bokeh_ranges()),t.event.addListener(this.map,\"bounds_changed\",()=>this._set_bokeh_ranges()),t.event.addListenerOnce(this.map,\"tilesloaded\",()=>this._render_finished()),this.connect(this.model.properties.map_options.change,()=>this._update_options()),this.connect(this.model.map_options.properties.styles.change,()=>this._update_styles()),this.connect(this.model.map_options.properties.lat.change,()=>this._update_center(\"lat\")),this.connect(this.model.map_options.properties.lng.change,()=>this._update_center(\"lng\")),this.connect(this.model.map_options.properties.zoom.change,()=>this._update_zoom()),this.connect(this.model.map_options.properties.map_type.change,()=>this._update_map_type()),this.connect(this.model.map_options.properties.scale_control.change,()=>this._update_scale_control()),this.connect(this.model.map_options.properties.tilt.change,()=>this._update_tilt())}_render_finished(){this._tiles_loaded=!0,this.notify_finished()}has_finished(){return super.has_finished()&&!0===this._tiles_loaded}_get_latlon_bounds(){const t=this.map.getBounds(),e=t.getNorthEast(),s=t.getSouthWest();return[s.lng(),e.lng(),s.lat(),e.lat()]}_get_projected_bounds(){const[t,e,s,i]=this._get_latlon_bounds(),[o,n]=a.wgs84_mercator.compute(t,s),[p,l]=a.wgs84_mercator.compute(e,i);return[o,p,n,l]}_set_bokeh_ranges(){const[t,e,s,i]=this._get_projected_bounds();this.frame.x_range.setv({start:t,end:e}),this.frame.y_range.setv({start:s,end:i})}_update_center(t){const e=this.map.getCenter().toJSON();e[t]=this.model.map_options[t],this.map.setCenter(e),this._set_bokeh_ranges()}_update_map_type(){this.map.setOptions({mapTypeId:this.map_types[this.model.map_options.map_type]})}_update_scale_control(){this.map.setOptions({scaleControl:this.model.map_options.scale_control})}_update_tilt(){this.map.setOptions({tilt:this.model.map_options.tilt})}_update_options(){this._update_styles(),this._update_center(\"lat\"),this._update_center(\"lng\"),this._update_zoom(),this._update_map_type()}_update_styles(){this.map.setOptions({styles:JSON.parse(this.model.map_options.styles)})}_update_zoom(){this.map.setOptions({zoom:this.model.map_options.zoom}),this._set_bokeh_ranges()}_map_hook(t,e){if(null==this.map&&\"undefined\"!=typeof google&&null!=google.maps&&this._build_map(),null!=this.map_el){const[t,s,i,o]=e;this.map_el.style.top=s+\"px\",this.map_el.style.left=t+\"px\",this.map_el.style.width=i+\"px\",this.map_el.style.height=o+\"px\"}}_paint_empty(t,e){const s=this.layout.bbox.width,i=this.layout.bbox.height,[o,a,n,p]=e;t.clearRect(0,0,s,i),t.beginPath(),t.moveTo(0,0),t.lineTo(0,i),t.lineTo(s,i),t.lineTo(s,0),t.lineTo(0,0),t.moveTo(o,a),t.lineTo(o+n,a),t.lineTo(o+n,a+p),t.lineTo(o,a+p),t.lineTo(o,a),t.closePath(),null!=this.model.border_fill_color&&(t.fillStyle=this.model.border_fill_color,t.fill())}}s.GMapPlotView=l,l.__name__=\"GMapPlotView\"},\n", - " function _(a,e,n){Object.defineProperty(n,\"__esModule\",{value:!0});var g=a(211);n.DataRange=g.DataRange;var R=a(210);n.DataRange1d=R.DataRange1d;var r=a(98);n.FactorRange=r.FactorRange;var t=a(99);n.Range=t.Range;var d=a(158);n.Range1d=d.Range1d},\n", - " function _(e,r,d){Object.defineProperty(d,\"__esModule\",{value:!0});var n=e(90);d.GlyphRenderer=n.GlyphRenderer;var R=e(116);d.GraphRenderer=R.GraphRenderer;var a=e(178);d.GuideRenderer=a.GuideRenderer;var G=e(70);d.Renderer=G.Renderer},\n", - " function _(a,e,l){Object.defineProperty(l,\"__esModule\",{value:!0});var c=a(209);l.CategoricalScale=c.CategoricalScale;var r=a(146);l.ContinuousScale=r.ContinuousScale;var n=a(145);l.LinearScale=n.LinearScale;var o=a(156);l.LinearInterpolationScale=o.LinearInterpolationScale;var i=a(157);l.LogScale=i.LogScale;var S=a(147);l.Scale=S.Scale},\n", - " function _(e,t,o){Object.defineProperty(o,\"__esModule\",{value:!0});e(1).__exportStar(e(118),o);var n=e(88);o.Selection=n.Selection},\n", - " function _(a,e,r){Object.defineProperty(r,\"__esModule\",{value:!0});var o=a(325);r.ServerSentDataSource=o.ServerSentDataSource;var S=a(327);r.AjaxDataSource=S.AjaxDataSource;var u=a(85);r.ColumnDataSource=u.ColumnDataSource;var t=a(86);r.ColumnarDataSource=t.ColumnarDataSource;var c=a(114);r.CDSView=c.CDSView;var D=a(87);r.DataSource=D.DataSource;var v=a(328);r.GeoJSONDataSource=v.GeoJSONDataSource;var n=a(326);r.WebDataSource=n.WebDataSource},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const a=e(326);class s extends a.WebDataSource{constructor(e){super(e),this.initialized=!1}destroy(){super.destroy()}setup(){if(!this.initialized){this.initialized=!0;new EventSource(this.data_url).onmessage=e=>{this.load_data(JSON.parse(e.data),this.mode,this.max_size)}}}}i.ServerSentDataSource=s,s.__name__=\"ServerSentDataSource\"},\n", - " function _(e,t,a){Object.defineProperty(a,\"__esModule\",{value:!0});const r=e(1),s=e(85),i=r.__importStar(e(18));class n extends s.ColumnDataSource{constructor(e){super(e)}get_column(e){const t=this.data[e];return null!=t?t:[]}initialize(){super.initialize(),this.setup()}load_data(e,t,a){const{adapter:r}=this;let s;switch(s=null!=r?r.execute(this,{response:e}):e,t){case\"replace\":this.data=s;break;case\"append\":{const e=this.data;for(const t of this.columns()){const r=Array.from(e[t]),i=Array.from(s[t]);s[t]=r.concat(i).slice(-a)}this.data=s;break}}}static init_WebDataSource(){this.define({mode:[i.UpdateMode,\"replace\"],max_size:[i.Number],adapter:[i.Any,null],data_url:[i.String]})}}a.WebDataSource=n,n.__name__=\"WebDataSource\",n.init_WebDataSource()},\n", - " function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=t(1),a=t(326),r=t(19),o=s.__importStar(t(18)),n=t(13);class d extends a.WebDataSource{constructor(t){super(t),this.initialized=!1}static init_AjaxDataSource(){this.define({polling_interval:[o.Number],content_type:[o.String,\"application/json\"],http_headers:[o.Any,{}],method:[o.HTTPMethod,\"POST\"],if_modified:[o.Boolean,!1]})}destroy(){null!=this.interval&&clearInterval(this.interval),super.destroy()}setup(){if(!this.initialized&&(this.initialized=!0,this.get_data(this.mode),this.polling_interval)){const t=()=>this.get_data(this.mode,this.max_size,this.if_modified);this.interval=setInterval(t,this.polling_interval)}}get_data(t,e=0,i=!1){const s=this.prepare_request();s.addEventListener(\"load\",()=>this.do_load(s,t,e)),s.addEventListener(\"error\",()=>this.do_error(s)),s.send()}prepare_request(){const t=new XMLHttpRequest;t.open(this.method,this.data_url,!0),t.withCredentials=!1,t.setRequestHeader(\"Content-Type\",this.content_type);const e=this.http_headers;for(const[i,s]of n.entries(e))t.setRequestHeader(i,s);return t}do_load(t,e,i){if(200===t.status){const s=JSON.parse(t.responseText);this.load_data(s,e,i)}}do_error(t){r.logger.error(`Failed to fetch JSON from ${this.data_url} with code ${t.status}`)}}i.AjaxDataSource=d,d.__name__=\"AjaxDataSource\",d.init_AjaxDataSource()},\n", - " function _(e,t,o){Object.defineProperty(o,\"__esModule\",{value:!0});const r=e(1),n=e(86),s=e(19),a=r.__importStar(e(18)),i=e(9),l=e(13);function c(e){return null!=e?e:NaN}class _ extends n.ColumnarDataSource{constructor(e){super(e)}static init_GeoJSONDataSource(){this.define({geojson:[a.Any]}),this.internal({data:[a.Any,{}]})}initialize(){super.initialize(),this._update_data()}connect_signals(){super.connect_signals(),this.connect(this.properties.geojson.change,()=>this._update_data())}_update_data(){this.data=this.geojson_to_column_data()}_get_new_list_array(e){return i.range(0,e).map(e=>[])}_get_new_nan_array(e){return i.range(0,e).map(e=>NaN)}_add_properties(e,t,o,r){var n;const s=null!==(n=e.properties)&&void 0!==n?n:{};for(const[e,n]of l.entries(s))t.hasOwnProperty(e)||(t[e]=this._get_new_nan_array(r)),t[e][o]=c(n)}_add_geometry(e,t,o){function r(e,t){return e.concat([[NaN,NaN,NaN]]).concat(t)}switch(e.type){case\"Point\":{const[r,n,s]=e.coordinates;t.x[o]=r,t.y[o]=n,t.z[o]=c(s);break}case\"LineString\":{const{coordinates:r}=e;for(let e=0;e1&&s.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\");const r=e.coordinates[0];for(let e=0;e1&&s.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\"),n.push(t[0]);const a=n.reduce(r);for(let e=0;ethis.get_resolution(t))}_computed_initial_resolution(){return null!=this.initial_resolution?this.initial_resolution:2*Math.PI*6378137/this.tile_size}is_valid_tile(t,e,i){return!(!this.wrap_around&&(t<0||t>=2**i))&&!(e<0||e>=2**i)}parent_by_tile_xyz(t,e,i){const _=this.tile_xyz_to_quadkey(t,e,i),s=_.substring(0,_.length-1);return this.quadkey_to_tile_xyz(s)}get_resolution(t){return this._computed_initial_resolution()/2**t}get_resolution_by_extent(t,e,i){return[(t[2]-t[0])/i,(t[3]-t[1])/e]}get_level_by_extent(t,e,i){const _=(t[2]-t[0])/i,s=(t[3]-t[1])/e,r=Math.max(_,s);let o=0;for(const t of this._resolutions){if(r>t){if(0==o)return 0;if(o>0)return o-1}o+=1}return o-1}get_closest_level_by_extent(t,e,i){const _=(t[2]-t[0])/i,s=(t[3]-t[1])/e,r=Math.max(_,s),o=this._resolutions.reduce((function(t,e){return Math.abs(e-r)e?(u=o-s,a*=t):(u*=e,a=n-r)}const h=(u-(o-s))/2,c=(a-(n-r))/2;return[s-h,r-c,o+h,n+c]}tms_to_wmts(t,e,i){return[t,2**i-1-e,i]}wmts_to_tms(t,e,i){return[t,2**i-1-e,i]}pixels_to_meters(t,e,i){const _=this.get_resolution(i);return[t*_-this.x_origin_offset,e*_-this.y_origin_offset]}meters_to_pixels(t,e,i){const _=this.get_resolution(i);return[(t+this.x_origin_offset)/_,(e+this.y_origin_offset)/_]}pixels_to_tile(t,e){let i=Math.ceil(t/this.tile_size);i=0===i?i:i-1;return[i,Math.max(Math.ceil(e/this.tile_size)-1,0)]}pixels_to_raster(t,e,i){return[t,(this.tile_size<=l;t--)for(let i=n;i<=u;i++)this.is_valid_tile(i,t,e)&&h.push([i,t,e,this.get_tile_meter_bounds(i,t,e)]);return this.sort_tiles_from_center(h,[n,l,u,a]),h}quadkey_to_tile_xyz(t){let e=0,i=0;const _=t.length;for(let s=_;s>0;s--){const r=1<0;s--){const i=1<0;)if(s=s.substring(0,s.length-1),[t,e,i]=this.quadkey_to_tile_xyz(s),[t,e,i]=this.denormalize_xyz(t,e,i,_),this.tiles.has(this.tile_xyz_to_key(t,e,i)))return[t,e,i];return[0,0,0]}normalize_xyz(t,e,i){if(this.wrap_around){const _=2**i;return[(t%_+_)%_,e,i]}return[t,e,i]}denormalize_xyz(t,e,i,_){return[t+_*2**i,e,i]}denormalize_meters(t,e,i,_){return[t+2*_*Math.PI*6378137,e]}calculate_world_x_by_tile_xyz(t,e,i){return Math.floor(t/2**i)}}i.MercatorTileSource=l,l.__name__=\"MercatorTileSource\",l.init_MercatorTileSource()},\n", - " function _(e,t,r){Object.defineProperty(r,\"__esModule\",{value:!0});const i=e(1),n=e(81),s=e(13),l=i.__importStar(e(18));class a extends n.Model{constructor(e){super(e)}static init_TileSource(){this.define({url:[l.String,\"\"],tile_size:[l.Number,256],max_zoom:[l.Number,30],min_zoom:[l.Number,0],extra_url_vars:[l.Any,{}],attribution:[l.String,\"\"],x_origin_offset:[l.Number],y_origin_offset:[l.Number],initial_resolution:[l.Number]})}initialize(){super.initialize(),this.tiles=new Map,this._normalize_case()}connect_signals(){super.connect_signals(),this.connect(this.change,()=>this._clear_cache())}string_lookup_replace(e,t){let r=e;for(const[e,i]of s.entries(t))r=r.replace(`{${e}}`,i);return r}_normalize_case(){const e=this.url.replace(\"{x}\",\"{X}\").replace(\"{y}\",\"{Y}\").replace(\"{z}\",\"{Z}\").replace(\"{q}\",\"{Q}\").replace(\"{xmin}\",\"{XMIN}\").replace(\"{ymin}\",\"{YMIN}\").replace(\"{xmax}\",\"{XMAX}\").replace(\"{ymax}\",\"{YMAX}\");this.url=e}_clear_cache(){this.tiles=new Map}tile_xyz_to_key(e,t,r){return`${e}:${t}:${r}`}key_to_tile_xyz(e){const[t,r,i]=e.split(\":\").map(e=>parseInt(e));return[t,r,i]}sort_tiles_from_center(e,t){const[r,i,n,s]=t,l=(n-r)/2+r,a=(s-i)/2+i;e.sort((function(e,t){return Math.sqrt((l-e[0])**2+(a-e[1])**2)-Math.sqrt((l-t[0])**2+(a-t[1])**2)}))}get_image_url(e,t,r){return this.string_lookup_replace(this.url,this.extra_url_vars).replace(\"{X}\",e.toString()).replace(\"{Y}\",t.toString()).replace(\"{Z}\",r.toString())}}r.TileSource=a,a.__name__=\"TileSource\",a.init_TileSource()},\n", - " function _(e,t,r){Object.defineProperty(r,\"__esModule\",{value:!0});const n=e(37);function o(e,t){return n.wgs84_mercator.compute(e,t)}function c(e,t){return n.wgs84_mercator.invert(e,t)}r.geographic_to_meters=o,r.meters_to_geographic=c,r.geographic_extent_to_meters=function(e){const[t,r,n,c]=e,[_,u]=o(t,r),[i,g]=o(n,c);return[_,u,i,g]},r.meters_extent_to_geographic=function(e){const[t,r,n,o]=e,[_,u]=c(t,r),[i,g]=c(n,o);return[_,u,i,g]}},\n", - " function _(e,t,r){Object.defineProperty(r,\"__esModule\",{value:!0});const _=e(333);class s extends _.MercatorTileSource{constructor(e){super(e)}get_image_url(e,t,r){const _=this.string_lookup_replace(this.url,this.extra_url_vars),[s,o,u]=this.tms_to_wmts(e,t,r),c=this.tile_xyz_to_quadkey(s,o,u);return _.replace(\"{Q}\",c)}}r.QUADKEYTileSource=s,s.__name__=\"QUADKEYTileSource\"},\n", - " function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=t(1),_=t(338),n=t(91),a=t(158),r=t(72),o=s.__importStar(t(18)),h=t(251),l=t(9),d=t(8),m=t(89),c=t(85),g=t(339),p=s.__importDefault(t(340));class u extends n.DataRendererView{initialize(){this._tiles=[],super.initialize()}connect_signals(){super.connect_signals(),this.connect(this.model.change,()=>this.request_render()),this.connect(this.model.tile_source.change,()=>this.request_render())}styles(){return[...super.styles(),p.default]}get_extent(){return[this.x_range.start,this.y_range.start,this.x_range.end,this.y_range.end]}get map_plot(){return this.plot_model}get map_canvas(){return this.layer.ctx}get map_frame(){return this.plot_view.frame}get x_range(){return this.map_plot.x_range}get y_range(){return this.map_plot.y_range}_set_data(){this.extent=this.get_extent(),this._last_height=void 0,this._last_width=void 0}_update_attribution(){null!=this.attribution_el&&r.removeElement(this.attribution_el);const{attribution:t}=this.model.tile_source;if(d.isString(t)&&t.length>0){const{layout:e,frame:i}=this.plot_view,s=e.bbox.width-i.bbox.right,_=e.bbox.height-i.bbox.bottom,n=i.bbox.width;this.attribution_el=r.div({class:g.bk_tile_attribution,style:{position:\"absolute\",right:s+\"px\",bottom:_+\"px\",\"max-width\":n-4+\"px\",padding:\"2px\",\"background-color\":\"rgba(255,255,255,0.5)\",\"font-size\":\"9px\",\"line-height\":\"1.05\",\"white-space\":\"nowrap\",overflow:\"hidden\",\"text-overflow\":\"ellipsis\"}}),this.plot_view.canvas_view.add_event(this.attribution_el),this.attribution_el.innerHTML=t,this.attribution_el.title=this.attribution_el.textContent.replace(/\\s*\\n\\s*/g,\" \")}}_map_data(){this.initial_extent=this.get_extent();const t=this.model.tile_source.get_level_by_extent(this.initial_extent,this.map_frame.bbox.height,this.map_frame.bbox.width),e=this.model.tile_source.snap_to_zoom_level(this.initial_extent,this.map_frame.bbox.height,this.map_frame.bbox.width,t);this.x_range.start=e[0],this.y_range.start=e[1],this.x_range.end=e[2],this.y_range.end=e[3],this.x_range instanceof a.Range1d&&(this.x_range.reset_start=e[0],this.x_range.reset_end=e[2]),this.y_range instanceof a.Range1d&&(this.y_range.reset_start=e[1],this.y_range.reset_end=e[3]),this._update_attribution()}_create_tile(t,e,i,s,_=!1){const[n,a,r]=this.model.tile_source.normalize_xyz(t,e,i),o={img:void 0,tile_coords:[t,e,i],normalized_coords:[n,a,r],quadkey:this.model.tile_source.tile_xyz_to_quadkey(t,e,i),cache_key:this.model.tile_source.tile_xyz_to_key(t,e,i),bounds:s,loaded:!1,finished:!1,x_coord:s[0],y_coord:s[3]},l=this.model.tile_source.get_image_url(n,a,r);new h.ImageLoader(l,{loaded:t=>{Object.assign(o,{img:t,loaded:!0}),_?(o.finished=!0,this.notify_finished()):this.request_render()},failed(){o.finished=!0}}),this.model.tile_source.tiles.set(o.cache_key,o),this._tiles.push(o)}_enforce_aspect_ratio(){if(this._last_height!==this.map_frame.bbox.height||this._last_width!==this.map_frame.bbox.width){const t=this.get_extent(),e=this.model.tile_source.get_level_by_extent(t,this.map_frame.bbox.height,this.map_frame.bbox.width),i=this.model.tile_source.snap_to_zoom_level(t,this.map_frame.bbox.height,this.map_frame.bbox.width,e);this.x_range.setv({start:i[0],end:i[2]}),this.y_range.setv({start:i[1],end:i[3]}),this.extent=i,this._last_height=this.map_frame.bbox.height,this._last_width=this.map_frame.bbox.width}}has_finished(){if(!super.has_finished())return!1;if(0===this._tiles.length)return!1;for(const t of this._tiles)if(!t.finished)return!1;return!0}_render(){null==this.map_initialized&&(this._set_data(),this._map_data(),this.map_initialized=!0),this._enforce_aspect_ratio(),this._update(),null!=this.prefetch_timer&&clearTimeout(this.prefetch_timer),this.prefetch_timer=setTimeout(this._prefetch_tiles.bind(this),500),this.has_finished()&&this.notify_finished()}_draw_tile(t){const e=this.model.tile_source.tiles.get(t);if(null!=e&&e.loaded){const[[t],[i]]=this.coordinates.map_to_screen([e.bounds[0]],[e.bounds[3]]),[[s],[_]]=this.coordinates.map_to_screen([e.bounds[2]],[e.bounds[1]]),n=s-t,a=_-i,r=t,o=i,h=this.map_canvas.getImageSmoothingEnabled();this.map_canvas.setImageSmoothingEnabled(this.model.smoothing),this.map_canvas.drawImage(e.img,r,o,n,a),this.map_canvas.setImageSmoothingEnabled(h),e.finished=!0}}_set_rect(){const t=this.plot_model.properties.outline_line_width.value(),e=this.map_frame.bbox.left+t/2,i=this.map_frame.bbox.top+t/2,s=this.map_frame.bbox.width-t,_=this.map_frame.bbox.height-t;this.map_canvas.rect(e,i,s,_),this.map_canvas.clip()}_render_tiles(t){this.map_canvas.save(),this._set_rect(),this.map_canvas.globalAlpha=this.model.alpha;for(const e of t)this._draw_tile(e);this.map_canvas.restore()}_prefetch_tiles(){const{tile_source:t}=this.model,e=this.get_extent(),i=this.map_frame.bbox.height,s=this.map_frame.bbox.width,_=this.model.tile_source.get_level_by_extent(e,i,s),n=this.model.tile_source.get_tiles_by_extent(e,_);for(let e=0,i=Math.min(10,n.length);ei&&(s=this.extent,r=i,o=!0),o&&(this.x_range.setv({x_range:{start:s[0],end:s[2]}}),this.y_range.setv({start:s[1],end:s[3]})),this.extent=s;const h=t.get_tiles_by_extent(s,r),d=[],m=[],c=[],g=[];for(const e of h){const[i,s,n]=e,a=t.tile_xyz_to_key(i,s,n),r=t.tiles.get(a);if(null!=r&&r.loaded)m.push(a);else if(this.model.render_parents){const[e,a,r]=t.get_closest_parent_by_tile_xyz(i,s,n),o=t.tile_xyz_to_key(e,a,r),h=t.tiles.get(o);if(null!=h&&h.loaded&&!l.includes(c,o)&&c.push(o),_){const e=t.children_by_tile_xyz(i,s,n);for(const[i,s,_]of e){const e=t.tile_xyz_to_key(i,s,_);t.tiles.has(e)&&g.push(e)}}}null==r&&d.push(e)}this._render_tiles(c),this._render_tiles(g),this._render_tiles(m),null!=this.render_timer&&clearTimeout(this.render_timer),this.render_timer=setTimeout(()=>this._fetch_tiles(d),65)}}i.TileRendererView=u,u.__name__=\"TileRendererView\";class b extends n.DataRenderer{constructor(t){super(t),this._selection_manager=new m.SelectionManager({source:new c.ColumnDataSource})}static init_TileRenderer(){this.prototype.default_view=u,this.define({alpha:[o.Number,1],smoothing:[o.Boolean,!0],tile_source:[o.Instance,()=>new _.WMTSTileSource],render_parents:[o.Boolean,!0]})}get_selection_manager(){return this._selection_manager}}i.TileRenderer=b,b.__name__=\"TileRenderer\",b.init_TileRenderer()},\n", - " function _(e,t,r){Object.defineProperty(r,\"__esModule\",{value:!0});const o=e(333);class s extends o.MercatorTileSource{constructor(e){super(e)}get_image_url(e,t,r){const o=this.string_lookup_replace(this.url,this.extra_url_vars),[s,c,_]=this.tms_to_wmts(e,t,r);return o.replace(\"{X}\",s.toString()).replace(\"{Y}\",c.toString()).replace(\"{Z}\",_.toString())}}r.WMTSTileSource=s,s.__name__=\"WMTSTileSource\"},\n", - " function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0}),i.bk_tile_attribution=\"bk-tile-attribution\"},\n", - " function _(e,t,n){Object.defineProperty(n,\"__esModule\",{value:!0});n.default=\"\\n.bk-root .bk-tile-attribution a {\\n color: black;\\n}\\n\"},\n", - " function _(e,r,t){Object.defineProperty(t,\"__esModule\",{value:!0});const o=e(333);class c extends o.MercatorTileSource{constructor(e){super(e)}get_image_url(e,r,t){return this.string_lookup_replace(this.url,this.extra_url_vars).replace(\"{X}\",e.toString()).replace(\"{Y}\",r.toString()).replace(\"{Z}\",t.toString())}}t.TMSTileSource=c,c.__name__=\"TMSTileSource\"},\n", - " function _(e,r,a){Object.defineProperty(a,\"__esModule\",{value:!0});var t=e(343);a.CanvasTexture=t.CanvasTexture;var u=e(345);a.ImageURLTexture=u.ImageURLTexture;var v=e(344);a.Texture=v.Texture},\n", - " function _(t,e,n){Object.defineProperty(n,\"__esModule\",{value:!0});const r=t(1),c=t(344),s=r.__importStar(t(18)),i=t(29);class a extends c.Texture{constructor(t){super(t)}static init_CanvasTexture(){this.define({code:[s.String]})}get func(){const t=i.use_strict(this.code);return new Function(\"ctx\",\"color\",\"scale\",\"weight\",t)}get_pattern(t,e,n){return r=>{const c=document.createElement(\"canvas\");c.width=e,c.height=e;const s=c.getContext(\"2d\");return this.func.call(this,s,t,e,n),r.createPattern(c,this.repetition)}}}n.CanvasTexture=a,a.__name__=\"CanvasTexture\",a.init_CanvasTexture()},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const r=e(1),n=e(81),o=r.__importStar(e(18));class _ extends n.Model{constructor(e){super(e)}static init_Texture(){this.define({repetition:[o.TextureRepetition,\"repeat\"]})}onload(e){e()}}i.Texture=_,_.__name__=\"Texture\",_.init_Texture()},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const r=e(1),a=e(344),n=r.__importStar(e(18)),s=e(251);class o extends a.Texture{constructor(e){super(e)}static init_ImageURLTexture(){this.define({url:[n.String]})}initialize(){super.initialize(),this._loader=new s.ImageLoader(this.url)}get_pattern(e,t,i){return e=>this._loader.finished?e.createPattern(this._loader.image,this.repetition):null}onload(e){this._loader.promise.then(()=>e())}}i.ImageURLTexture=o,o.__name__=\"ImageURLTexture\",o.init_ImageURLTexture()},\n", - " function _(o,l,T){Object.defineProperty(T,\"__esModule\",{value:!0});var a=o(307);T.ActionTool=a.ActionTool;var r=o(347);T.CustomAction=r.CustomAction;var e=o(308);T.HelpTool=e.HelpTool;var v=o(348);T.RedoTool=v.RedoTool;var t=o(349);T.ResetTool=t.ResetTool;var n=o(350);T.SaveTool=n.SaveTool;var s=o(351);T.UndoTool=s.UndoTool;var i=o(352);T.ZoomInTool=i.ZoomInTool;var P=o(355);T.ZoomOutTool=P.ZoomOutTool;var c=o(296);T.ButtonTool=c.ButtonTool;var d=o(356);T.EditTool=d.EditTool;var u=o(357);T.BoxEditTool=u.BoxEditTool;var y=o(358);T.FreehandDrawTool=y.FreehandDrawTool;var m=o(359);T.PointDrawTool=m.PointDrawTool;var x=o(360);T.PolyDrawTool=x.PolyDrawTool;var B=o(361);T.PolyTool=B.PolyTool;var S=o(362);T.PolyEditTool=S.PolyEditTool;var b=o(363);T.BoxSelectTool=b.BoxSelectTool;var h=o(366);T.BoxZoomTool=h.BoxZoomTool;var E=o(306);T.GestureTool=E.GestureTool;var Z=o(367);T.LassoSelectTool=Z.LassoSelectTool;var p=o(369);T.LineEditTool=p.LineEditTool;var w=o(371);T.PanTool=w.PanTool;var C=o(368);T.PolySelectTool=C.PolySelectTool;var D=o(372);T.RangeTool=D.RangeTool;var H=o(364);T.SelectTool=H.SelectTool;var R=o(373);T.TapTool=R.TapTool;var A=o(374);T.WheelPanTool=A.WheelPanTool;var I=o(375);T.WheelZoomTool=I.WheelZoomTool;var L=o(376);T.CrosshairTool=L.CrosshairTool;var W=o(377);T.CustomJSHover=W.CustomJSHover;var O=o(378);T.HoverTool=O.HoverTool;var _=o(295);T.InspectTool=_.InspectTool;var f=o(298);T.Tool=f.Tool;var g=o(379);T.ToolProxy=g.ToolProxy;var F=o(294);T.Toolbar=F.Toolbar;var G=o(305);T.ToolbarBase=G.ToolbarBase;var J=o(380);T.ProxyToolbar=J.ProxyToolbar;var U=o(380);T.ToolbarBox=U.ToolbarBox},\n", - " function _(t,o,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=t(1),s=t(307),e=n.__importStar(t(18)),c=t(299);class _ extends s.ActionToolButtonView{css_classes(){return super.css_classes().concat(c.bk_toolbar_button_custom_action)}}i.CustomActionButtonView=_,_.__name__=\"CustomActionButtonView\";class l extends s.ActionToolView{doit(){null!=this.model.callback&&this.model.callback.execute(this.model)}}i.CustomActionView=l,l.__name__=\"CustomActionView\";class u extends s.ActionTool{constructor(t){super(t),this.tool_name=\"Custom Action\",this.button_view=_}static init_CustomAction(){this.prototype.default_view=l,this.define({action_tooltip:[e.String,\"Perform a Custom Action\"],callback:[e.Any],icon:[e.String]})}get tooltip(){return this.action_tooltip}}i.CustomAction=u,u.__name__=\"CustomAction\",u.init_CustomAction()},\n", - " function _(o,e,t){Object.defineProperty(t,\"__esModule\",{value:!0});const i=o(307),s=o(309);class n extends i.ActionToolView{connect_signals(){super.connect_signals(),this.connect(this.plot_view.state_changed,()=>this.model.disabled=!this.plot_view.can_redo())}doit(){this.plot_view.redo()}}t.RedoToolView=n,n.__name__=\"RedoToolView\";class _ extends i.ActionTool{constructor(o){super(o),this.tool_name=\"Redo\",this.icon=s.bk_tool_icon_redo}static init_RedoTool(){this.prototype.default_view=n,this.override({disabled:!0}),this.register_alias(\"redo\",()=>new _)}}t.RedoTool=_,_.__name__=\"RedoTool\",_.init_RedoTool()},\n", - " function _(e,t,o){Object.defineProperty(o,\"__esModule\",{value:!0});const s=e(307),i=e(309);class _ extends s.ActionToolView{doit(){this.plot_view.reset()}}o.ResetToolView=_,_.__name__=\"ResetToolView\";class l extends s.ActionTool{constructor(e){super(e),this.tool_name=\"Reset\",this.icon=i.bk_tool_icon_reset}static init_ResetTool(){this.prototype.default_view=_,this.register_alias(\"reset\",()=>new l)}}o.ResetTool=l,l.__name__=\"ResetTool\",l.init_ResetTool()},\n", - " function _(e,o,t){Object.defineProperty(t,\"__esModule\",{value:!0});const a=e(307),i=e(309);class n extends a.ActionToolView{async copy(){const e=await this.plot_view.to_blob(),o=new ClipboardItem({[e.type]:e});await navigator.clipboard.write([o])}async save(e){const o=await this.plot_view.to_blob(),t=document.createElement(\"a\");t.href=URL.createObjectURL(o),t.download=e,t.target=\"_blank\",t.dispatchEvent(new MouseEvent(\"click\"))}doit(e=\"save\"){switch(e){case\"save\":this.save(\"bokeh_plot\");break;case\"copy\":this.copy()}}}t.SaveToolView=n,n.__name__=\"SaveToolView\";class s extends a.ActionTool{constructor(e){super(e),this.tool_name=\"Save\",this.icon=i.bk_tool_icon_save}static init_SaveTool(){this.prototype.default_view=n,this.register_alias(\"save\",()=>new s)}get menu(){return[{icon:\"bk-tool-icon-copy-to-clipboard\",tooltip:\"Copy image to clipboard\",if:()=>\"undefined\"!=typeof ClipboardItem,handler:()=>{this.do.emit(\"copy\")}}]}}t.SaveTool=s,s.__name__=\"SaveTool\",s.init_SaveTool()},\n", - " function _(o,t,e){Object.defineProperty(e,\"__esModule\",{value:!0});const n=o(307),i=o(309);class s extends n.ActionToolView{connect_signals(){super.connect_signals(),this.connect(this.plot_view.state_changed,()=>this.model.disabled=!this.plot_view.can_undo())}doit(){this.plot_view.undo()}}e.UndoToolView=s,s.__name__=\"UndoToolView\";class _ extends n.ActionTool{constructor(o){super(o),this.tool_name=\"Undo\",this.icon=i.bk_tool_icon_undo}static init_UndoTool(){this.prototype.default_view=s,this.override({disabled:!0}),this.register_alias(\"undo\",()=>new _)}}e.UndoTool=_,_.__name__=\"UndoTool\",_.init_UndoTool()},\n", - " function _(o,i,e){Object.defineProperty(e,\"__esModule\",{value:!0});const n=o(353),s=o(309);class t extends n.ZoomBaseTool{constructor(o){super(o),this.sign=1,this.tool_name=\"Zoom In\",this.icon=s.bk_tool_icon_zoom_in}static init_ZoomInTool(){this.prototype.default_view=n.ZoomBaseToolView,this.register_alias(\"zoom_in\",()=>new t({dimensions:\"both\"})),this.register_alias(\"xzoom_in\",()=>new t({dimensions:\"width\"})),this.register_alias(\"yzoom_in\",()=>new t({dimensions:\"height\"}))}}e.ZoomInTool=t,t.__name__=\"ZoomInTool\",t.init_ZoomInTool()},\n", - " function _(o,t,e){Object.defineProperty(e,\"__esModule\",{value:!0});const i=o(1),s=o(307),n=o(354),_=i.__importStar(o(18));class l extends s.ActionToolView{doit(){const o=this.plot_view.frame,t=this.model.dimensions,e=\"width\"==t||\"both\"==t,i=\"height\"==t||\"both\"==t,s=n.scale_range(o,this.model.sign*this.model.factor,e,i);this.plot_view.push_state(\"zoom_out\",{range:s}),this.plot_view.update_range(s,!1,!0),this.model.document&&this.model.document.interactive_start(this.plot_model)}}e.ZoomBaseToolView=l,l.__name__=\"ZoomBaseToolView\";class a extends s.ActionTool{constructor(o){super(o)}static init_ZoomBaseTool(){this.prototype.default_view=l,this.define({factor:[_.Percent,.1],dimensions:[_.Dimensions,\"both\"]})}get tooltip(){return this._get_dim_tooltip(this.tool_name,this.dimensions)}}e.ZoomBaseTool=a,a.__name__=\"ZoomBaseTool\",a.init_ZoomBaseTool()},\n", - " function _(n,e,t){Object.defineProperty(t,\"__esModule\",{value:!0});const o=n(10);function r(n,e,t){const[o,r]=[n.start,n.end],s=null!=t?t:(r+o)/2;return[o-(o-s)*e,r-(r-s)*e]}function s(n,[e,t]){const o=new Map;for(const[r,s]of n){const[n,c]=s.r_invert(e,t);o.set(r,{start:n,end:c})}return o}t.scale_highlow=r,t.get_info=s,t.scale_range=function(n,e,t=!0,c=!0,l){e=o.clamp(e,-.9,.9);const a=t?e:0,[u,_]=r(n.bbox.h_range,a,null!=l?l.x:void 0),i=s(n.x_scales,[u,_]),f=c?e:0,[d,b]=r(n.bbox.v_range,f,null!=l?l.y:void 0);return{xrs:i,yrs:s(n.y_scales,[d,b]),factor:e}}},\n", - " function _(o,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const e=o(353),s=o(309);class n extends e.ZoomBaseTool{constructor(o){super(o),this.sign=-1,this.tool_name=\"Zoom Out\",this.icon=s.bk_tool_icon_zoom_out}static init_ZoomOutTool(){this.prototype.default_view=e.ZoomBaseToolView,this.register_alias(\"zoom_out\",()=>new n({dimensions:\"both\"})),this.register_alias(\"xzoom_out\",()=>new n({dimensions:\"width\"})),this.register_alias(\"yzoom_out\",()=>new n({dimensions:\"height\"}))}}i.ZoomOutTool=n,n.__name__=\"ZoomOutTool\",n.init_ZoomOutTool()},\n", - " function _(e,t,o){Object.defineProperty(o,\"__esModule\",{value:!0});const s=e(1).__importStar(e(18)),i=e(9),n=e(8),r=e(11),_=e(306);class c extends _.GestureToolView{constructor(){super(...arguments),this._mouse_in_frame=!0}_select_mode(e){const{shiftKey:t,ctrlKey:o}=e;return t||o?t&&!o?\"append\":!t&&o?\"intersect\":t&&o?\"subtract\":void r.unreachable():\"replace\"}_move_enter(e){this._mouse_in_frame=!0}_move_exit(e){this._mouse_in_frame=!1}_map_drag(e,t,o){if(!this.plot_view.frame.bbox.contains(e,t))return null;const s=this.plot_view.renderer_views.get(o);return[s.coordinates.x_scale.invert(e),s.coordinates.y_scale.invert(t)]}_delete_selected(e){const t=e.data_source,o=t.selected.indices;o.sort();for(const e of t.columns()){const s=t.get_array(e);for(let e=0;ethis._show_vertices())}this._initialized=!0}}deactivate(){this._drawing&&(this._remove(),this._drawing=!1),this.model.vertex_renderer&&this._hide_vertices()}}s.PolyDrawToolView=d,d.__name__=\"PolyDrawToolView\";class l extends n.PolyTool{constructor(e){super(e),this.tool_name=\"Polygon Draw Tool\",this.icon=_.bk_tool_icon_poly_draw,this.event_type=[\"pan\",\"tap\",\"move\"],this.default_order=3}static init_PolyDrawTool(){this.prototype.default_view=d,this.define({drag:[a.Boolean,!0],num_objects:[a.Int,0]})}}s.PolyDrawTool=l,l.__name__=\"PolyDrawTool\",l.init_PolyDrawTool()},\n", - " function _(e,t,r){Object.defineProperty(r,\"__esModule\",{value:!0});const o=e(1).__importStar(e(18)),i=e(8),s=e(356);class _ extends s.EditToolView{_set_vertices(e,t){const r=this.model.vertex_renderer.glyph,o=this.model.vertex_renderer.data_source,[s,_]=[r.x.field,r.y.field];s&&(i.isArray(e)?o.data[s]=e:r.x={value:e}),_&&(i.isArray(t)?o.data[_]=t:r.y={value:t}),this._emit_cds_changes(o,!0,!0,!1)}_hide_vertices(){this._set_vertices([],[])}_snap_to_vertex(e,t,r){if(this.model.vertex_renderer){const o=this._select_event(e,\"replace\",[this.model.vertex_renderer]),i=this.model.vertex_renderer.data_source,s=this.model.vertex_renderer.glyph,[_,l]=[s.x.field,s.y.field];if(o.length){const e=i.selected.indices[0];_&&(t=i.data[_][e]),l&&(r=i.data[l][e]),i.selection_manager.clear()}}return[t,r]}}r.PolyToolView=_,_.__name__=\"PolyToolView\";class l extends s.EditTool{constructor(e){super(e)}static init_PolyTool(){this.prototype.default_view=_,this.define({vertex_renderer:[o.Instance]})}}r.PolyTool=l,l.__name__=\"PolyTool\",l.init_PolyTool()},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const r=e(72),i=e(8),_=e(361),d=e(309);class n extends _.PolyToolView{constructor(){super(...arguments),this._drawing=!1}_doubletap(e){if(!this.model.active)return;const t=this._map_drag(e.sx,e.sy,this.model.vertex_renderer);if(null==t)return;const[s,r]=t,i=this._select_event(e,\"replace\",[this.model.vertex_renderer]),_=this.model.vertex_renderer.data_source,d=this.model.vertex_renderer.glyph,[n,l]=[d.x.field,d.y.field];if(i.length&&null!=this._selected_renderer){const e=_.selected.indices[0];this._drawing?(this._drawing=!1,_.selection_manager.clear()):(_.selected.indices=[e+1],n&&_.get_array(n).splice(e+1,0,s),l&&_.get_array(l).splice(e+1,0,r),this._drawing=!0),_.change.emit(),this._emit_cds_changes(this._selected_renderer.data_source)}else this._show_vertices(e)}_show_vertices(e){if(!this.model.active)return;const t=this._select_event(e,\"replace\",this.model.renderers);if(!t.length)return this._set_vertices([],[]),this._selected_renderer=null,void(this._drawing=!1);const s=t[0],r=s.glyph,_=s.data_source,d=_.selected.indices[0],[n,l]=[r.xs.field,r.ys.field];let a,c;n?(a=_.data[n][d],i.isArray(a)||(_.data[n][d]=a=Array.from(a))):a=r.xs.value,l?(c=_.data[l][d],i.isArray(c)||(_.data[l][d]=c=Array.from(c))):c=r.ys.value,this._selected_renderer=s,this._set_vertices(a,c)}_move(e){if(this._drawing&&null!=this._selected_renderer){const t=this.model.vertex_renderer,s=t.data_source,r=t.glyph,i=this._map_drag(e.sx,e.sy,t);if(null==i)return;let[_,d]=i;const n=s.selected.indices;[_,d]=this._snap_to_vertex(e,_,d),s.selected.indices=n;const[l,a]=[r.x.field,r.y.field],c=n[0];l&&(s.data[l][c]=_),a&&(s.data[a][c]=d),s.change.emit(),this._selected_renderer.data_source.change.emit()}}_tap(e){const t=this.model.vertex_renderer,s=this._map_drag(e.sx,e.sy,t);if(null==s)return;if(this._drawing&&this._selected_renderer){let[r,i]=s;const _=t.data_source,d=t.glyph,[n,l]=[d.x.field,d.y.field],a=_.selected.indices;[r,i]=this._snap_to_vertex(e,r,i);const c=a[0];if(_.selected.indices=[c+1],n){const e=_.get_array(n),t=e[c];e[c]=r,e.splice(c+1,0,t)}if(l){const e=_.get_array(l),t=e[c];e[c]=i,e.splice(c+1,0,t)}return _.change.emit(),void this._emit_cds_changes(this._selected_renderer.data_source,!0,!1,!0)}const r=this._select_mode(e);this._select_event(e,r,[t]),this._select_event(e,r,this.model.renderers)}_remove_vertex(){if(!this._drawing||!this._selected_renderer)return;const e=this.model.vertex_renderer,t=e.data_source,s=e.glyph,r=t.selected.indices[0],[i,_]=[s.x.field,s.y.field];i&&t.get_array(i).splice(r,1),_&&t.get_array(_).splice(r,1),t.change.emit(),this._emit_cds_changes(this._selected_renderer.data_source)}_pan_start(e){this._select_event(e,\"append\",[this.model.vertex_renderer]),this._basepoint=[e.sx,e.sy]}_pan(e){null!=this._basepoint&&(this._drag_points(e,[this.model.vertex_renderer]),this._selected_renderer&&this._selected_renderer.data_source.change.emit())}_pan_end(e){null!=this._basepoint&&(this._drag_points(e,[this.model.vertex_renderer]),this._emit_cds_changes(this.model.vertex_renderer.data_source,!1,!0,!0),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source),this._basepoint=null)}_keyup(e){if(!this.model.active||!this._mouse_in_frame)return;let t;t=this._selected_renderer?[this.model.vertex_renderer]:this.model.renderers;for(const s of t)e.keyCode===r.Keys.Backspace?(this._delete_selected(s),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source)):e.keyCode==r.Keys.Esc&&(this._drawing?(this._remove_vertex(),this._drawing=!1):this._selected_renderer&&this._hide_vertices(),s.data_source.selection_manager.clear())}deactivate(){this._selected_renderer&&(this._drawing&&(this._remove_vertex(),this._drawing=!1),this._hide_vertices())}}s.PolyEditToolView=n,n.__name__=\"PolyEditToolView\";class l extends _.PolyTool{constructor(e){super(e),this.tool_name=\"Poly Edit Tool\",this.icon=d.bk_tool_icon_poly_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=4}static init_PolyEditTool(){this.prototype.default_view=n}}s.PolyEditTool=l,l.__name__=\"PolyEditTool\",l.init_PolyEditTool()},\n", - " function _(e,t,o){Object.defineProperty(o,\"__esModule\",{value:!0});const s=e(1),i=e(364),l=e(124),_=s.__importStar(e(18)),n=e(309);class c extends i.SelectToolView{_compute_limits(e){const t=this.plot_view.frame,o=this.model.dimensions;let s=this._base_point;if(\"center\"==this.model.origin){const[t,o]=s,[i,l]=e;s=[t-(i-t),o-(l-o)]}return this.model._get_dim_limits(s,e,t,o)}_pan_start(e){const{sx:t,sy:o}=e;this._base_point=[t,o]}_pan(e){const{sx:t,sy:o}=e,s=[t,o],[i,l]=this._compute_limits(s);this.model.overlay.update({left:i[0],right:i[1],top:l[0],bottom:l[1]}),this.model.select_every_mousemove&&this._do_select(i,l,!1,this._select_mode(e))}_pan_end(e){const{sx:t,sy:o}=e,s=[t,o],[i,l]=this._compute_limits(s);this._do_select(i,l,!0,this._select_mode(e)),this.model.overlay.update({left:null,right:null,top:null,bottom:null}),this._base_point=null,this.plot_view.push_state(\"box_select\",{selection:this.plot_view.get_selection()})}_do_select([e,t],[o,s],i,l=\"replace\"){const _={type:\"rect\",sx0:e,sx1:t,sy0:o,sy1:s};this._select(_,i,l)}}o.BoxSelectToolView=c,c.__name__=\"BoxSelectToolView\";const r=()=>new l.BoxAnnotation({level:\"overlay\",top_units:\"screen\",left_units:\"screen\",bottom_units:\"screen\",right_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class h extends i.SelectTool{constructor(e){super(e),this.tool_name=\"Box Select\",this.icon=n.bk_tool_icon_box_select,this.event_type=\"pan\",this.default_order=30}static init_BoxSelectTool(){this.prototype.default_view=c,this.define({dimensions:[_.Dimensions,\"both\"],select_every_mousemove:[_.Boolean,!1],overlay:[_.Instance,r],origin:[_.BoxOrigin,\"corner\"]}),this.register_alias(\"box_select\",()=>new h),this.register_alias(\"xbox_select\",()=>new h({dimensions:\"width\"})),this.register_alias(\"ybox_select\",()=>new h({dimensions:\"height\"}))}get tooltip(){return this._get_dim_tooltip(this.tool_name,this.dimensions)}}o.BoxSelectTool=h,h.__name__=\"BoxSelectTool\",h.init_BoxSelectTool()},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const n=e(1),o=e(306),r=e(90),c=e(116),i=e(365),l=n.__importStar(e(18)),a=e(72),_=e(313),d=e(15),h=e(11);class p extends o.GestureToolView{connect_signals(){super.connect_signals(),this.model.clear.connect(()=>this._clear())}get computed_renderers(){const e=this.model.renderers,t=this.plot_model.renderers,s=this.model.names;return i.compute_renderers(e,t,s)}_computed_renderers_by_data_source(){var e;const t=new Map;for(const s of this.computed_renderers){let n;if(s instanceof r.GlyphRenderer)n=s.data_source;else{if(!(s instanceof c.GraphRenderer))continue;n=s.node_renderer.data_source}const o=null!==(e=t.get(n))&&void 0!==e?e:[];t.set(n,[...o,s])}return t}_select_mode(e){const{shiftKey:t,ctrlKey:s}=e;return t||s?t&&!s?\"append\":!t&&s?\"intersect\":t&&s?\"subtract\":void h.unreachable():this.model.mode}_keyup(e){e.keyCode==a.Keys.Esc&&this._clear()}_clear(){for(const e of this.computed_renderers)e.get_selection_manager().clear();this.plot_view.request_render()}_select(e,t,s){const n=this._computed_renderers_by_data_source();for(const[,o]of n){const n=o[0].get_selection_manager(),r=[];for(const e of o){const t=this.plot_view.renderer_views.get(e);null!=t&&r.push(t)}n.select(r,e,t,s)}null!=this.model.callback&&this._emit_callback(e),this._emit_selection_event(e,t)}_emit_selection_event(e,t=!0){const{x_scale:s,y_scale:n}=this.plot_view.frame;let o;switch(e.type){case\"point\":{const{sx:t,sy:r}=e,c=s.invert(t),i=n.invert(r);o=Object.assign(Object.assign({},e),{x:c,y:i});break}case\"span\":{const{sx:t,sy:r}=e,c=s.invert(t),i=n.invert(r);o=Object.assign(Object.assign({},e),{x:c,y:i});break}case\"rect\":{const{sx0:t,sx1:r,sy0:c,sy1:i}=e,[l,a]=s.r_invert(t,r),[_,d]=n.r_invert(c,i);o=Object.assign(Object.assign({},e),{x0:l,y0:_,x1:a,y1:d});break}case\"poly\":{const{sx:t,sy:r}=e,c=s.v_invert(t),i=n.v_invert(r);o=Object.assign(Object.assign({},e),{x:c,y:i});break}}this.plot_model.trigger_event(new _.SelectionGeometry(o,t))}}s.SelectToolView=p,p.__name__=\"SelectToolView\";class u extends o.GestureTool{constructor(e){super(e)}initialize(){super.initialize(),this.clear=new d.Signal0(this,\"clear\")}static init_SelectTool(){this.define({renderers:[l.Any,\"auto\"],names:[l.Array,[]],mode:[l.Any,\"replace\"]})}get menu(){return[{icon:\"bk-tool-icon-replace-mode\",tooltip:\"Replace the current selection\",active:()=>\"replace\"==this.mode,handler:()=>{this.mode=\"replace\",this.active=!0}},{icon:\"bk-tool-icon-append-mode\",tooltip:\"Append to the current selection (Shift)\",active:()=>\"append\"==this.mode,handler:()=>{this.mode=\"append\",this.active=!0}},{icon:\"bk-tool-icon-intersect-mode\",tooltip:\"Intersect with the current selection (Ctrl)\",active:()=>\"intersect\"==this.mode,handler:()=>{this.mode=\"intersect\",this.active=!0}},{icon:\"bk-tool-icon-subtract-mode\",tooltip:\"Subtract from the current selection (Shift+Ctrl)\",active:()=>\"subtract\"==this.mode,handler:()=>{this.mode=\"subtract\",this.active=!0}},null,{icon:\"bk-tool-icon-clear-selection\",tooltip:\"Clear the current selection (Esc)\",handler:()=>{this.clear.emit()}}]}}s.SelectTool=u,u.__name__=\"SelectTool\",u.init_SelectTool()},\n", - " function _(e,n,t){Object.defineProperty(t,\"__esModule\",{value:!0});const r=e(9);t.compute_renderers=function(e,n,t){if(null==e)return[];let u=\"auto\"==e?n:e;return t.length>0&&(u=u.filter(e=>r.includes(t,e.name))),u}},\n", - " function _(t,o,e){Object.defineProperty(e,\"__esModule\",{value:!0});const s=t(1),i=t(306),n=t(124),_=s.__importStar(t(18)),a=t(309);class l extends i.GestureToolView{_match_aspect(t,o,e){const s=e.bbox.aspect,i=e.bbox.h_range.end,n=e.bbox.h_range.start,_=e.bbox.v_range.end,a=e.bbox.v_range.start;let l=Math.abs(t[0]-o[0]),r=Math.abs(t[1]-o[1]);const h=0==r?0:l/r,[c]=h>=s?[1,h/s]:[s/h,1];let m,p,d,b;return t[0]<=o[0]?(m=t[0],p=t[0]+l*c,p>i&&(p=i)):(p=t[0],m=t[0]-l*c,m_&&(d=_)):(d=t[1],b=t[1]-l/s,bnew n.BoxAnnotation({level:\"overlay\",top_units:\"screen\",left_units:\"screen\",bottom_units:\"screen\",right_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class h extends i.GestureTool{constructor(t){super(t),this.tool_name=\"Box Zoom\",this.icon=a.bk_tool_icon_box_zoom,this.event_type=\"pan\",this.default_order=20}static init_BoxZoomTool(){this.prototype.default_view=l,this.define({dimensions:[_.Dimensions,\"both\"],overlay:[_.Instance,r],match_aspect:[_.Boolean,!1],origin:[_.BoxOrigin,\"corner\"]}),this.register_alias(\"box_zoom\",()=>new h({dimensions:\"both\"})),this.register_alias(\"xbox_zoom\",()=>new h({dimensions:\"width\"})),this.register_alias(\"ybox_zoom\",()=>new h({dimensions:\"height\"}))}get tooltip(){return this._get_dim_tooltip(this.tool_name,this.dimensions)}}e.BoxZoomTool=h,h.__name__=\"BoxZoomTool\",h.init_BoxZoomTool()},\n", - " function _(e,s,t){Object.defineProperty(t,\"__esModule\",{value:!0});const o=e(1),a=e(364),i=e(368),l=e(72),_=o.__importStar(e(18)),c=e(309);class n extends a.SelectToolView{initialize(){super.initialize(),this.data=null}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,()=>this._active_change())}_active_change(){this.model.active||this._clear_overlay()}_keyup(e){e.keyCode==l.Keys.Enter&&this._clear_overlay()}_pan_start(e){const{sx:s,sy:t}=e;this.data={sx:[s],sy:[t]}}_pan(e){const{sx:s,sy:t}=e,[o,a]=this.plot_view.frame.bbox.clip(s,t);this.data.sx.push(o),this.data.sy.push(a);this.model.overlay.update({xs:this.data.sx,ys:this.data.sy}),this.model.select_every_mousemove&&this._do_select(this.data.sx,this.data.sy,!1,this._select_mode(e))}_pan_end(e){this._clear_overlay(),this._do_select(this.data.sx,this.data.sy,!0,this._select_mode(e)),this.plot_view.push_state(\"lasso_select\",{selection:this.plot_view.get_selection()})}_clear_overlay(){this.model.overlay.update({xs:[],ys:[]})}_do_select(e,s,t,o){const a={type:\"poly\",sx:e,sy:s};this._select(a,t,o)}}t.LassoSelectToolView=n,n.__name__=\"LassoSelectToolView\";class h extends a.SelectTool{constructor(e){super(e),this.tool_name=\"Lasso Select\",this.icon=c.bk_tool_icon_lasso_select,this.event_type=\"pan\",this.default_order=12}static init_LassoSelectTool(){this.prototype.default_view=n,this.define({select_every_mousemove:[_.Boolean,!0],overlay:[_.Instance,i.DEFAULT_POLY_OVERLAY]}),this.register_alias(\"lasso_select\",()=>new h)}}t.LassoSelectTool=h,h.__name__=\"LassoSelectTool\",h.init_LassoSelectTool()},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const l=e(1),i=e(364),o=e(166),a=e(72),_=l.__importStar(e(18)),c=e(9),n=e(309);class h extends i.SelectToolView{initialize(){super.initialize(),this.data={sx:[],sy:[]}}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,()=>this._active_change())}_active_change(){this.model.active||this._clear_data()}_keyup(e){e.keyCode==a.Keys.Enter&&this._clear_data()}_doubletap(e){this._do_select(this.data.sx,this.data.sy,!0,this._select_mode(e)),this.plot_view.push_state(\"poly_select\",{selection:this.plot_view.get_selection()}),this._clear_data()}_clear_data(){this.data={sx:[],sy:[]},this.model.overlay.update({xs:[],ys:[]})}_tap(e){const{sx:t,sy:s}=e;this.plot_view.frame.bbox.contains(t,s)&&(this.data.sx.push(t),this.data.sy.push(s),this.model.overlay.update({xs:c.copy(this.data.sx),ys:c.copy(this.data.sy)}))}_do_select(e,t,s,l){const i={type:\"poly\",sx:e,sy:t};this._select(i,s,l)}}s.PolySelectToolView=h,h.__name__=\"PolySelectToolView\",s.DEFAULT_POLY_OVERLAY=()=>new o.PolyAnnotation({level:\"overlay\",xs_units:\"screen\",ys_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class y extends i.SelectTool{constructor(e){super(e),this.tool_name=\"Poly Select\",this.icon=n.bk_tool_icon_polygon_select,this.event_type=\"tap\",this.default_order=11}static init_PolySelectTool(){this.prototype.default_view=h,this.define({overlay:[_.Instance,s.DEFAULT_POLY_OVERLAY]}),this.register_alias(\"poly_select\",()=>new y)}}s.PolySelectTool=y,y.__name__=\"PolySelectTool\",y.init_PolySelectTool()},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=e(1),n=e(370),r=s.__importStar(e(18)),_=e(309);class d extends n.LineToolView{constructor(){super(...arguments),this._drawing=!1}_doubletap(e){if(!this.model.active)return;const t=this.model.renderers;for(const i of t){1==this._select_event(e,\"replace\",[i]).length&&(this._selected_renderer=i)}this._show_intersections(),this._update_line_cds()}_show_intersections(){if(!this.model.active)return;if(null==this._selected_renderer)return;if(!this.model.renderers.length)return this._set_intersection([],[]),this._selected_renderer=null,void(this._drawing=!1);const e=this._selected_renderer.data_source,t=this._selected_renderer.glyph,[i,s]=[t.x.field,t.y.field],n=e.get_array(i),r=e.get_array(s);this._set_intersection(n,r)}_tap(e){const t=this.model.intersection_renderer;if(null==this._map_drag(e.sx,e.sy,t))return;if(this._drawing&&this._selected_renderer){const i=this._select_mode(e);if(0==this._select_event(e,i,[t]).length)return}const i=this._select_mode(e);this._select_event(e,i,[t]),this._select_event(e,i,this.model.renderers)}_update_line_cds(){if(null==this._selected_renderer)return;const e=this.model.intersection_renderer.glyph,t=this.model.intersection_renderer.data_source,[i,s]=[e.x.field,e.y.field];if(i&&s){const e=t.data[i],n=t.data[s];this._selected_renderer.data_source.data[i]=e,this._selected_renderer.data_source.data[s]=n}this._emit_cds_changes(this._selected_renderer.data_source,!0,!0,!1)}_pan_start(e){this._select_event(e,\"append\",[this.model.intersection_renderer]),this._basepoint=[e.sx,e.sy]}_pan(e){null!=this._basepoint&&(this._drag_points(e,[this.model.intersection_renderer],this.model.dimensions),this._selected_renderer&&this._selected_renderer.data_source.change.emit())}_pan_end(e){null!=this._basepoint&&(this._drag_points(e,[this.model.intersection_renderer]),this._emit_cds_changes(this.model.intersection_renderer.data_source,!1,!0,!0),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source),this._basepoint=null)}activate(){this._drawing=!0}deactivate(){this._selected_renderer&&(this._drawing&&(this._drawing=!1),this._hide_intersections())}}i.LineEditToolView=d,d.__name__=\"LineEditToolView\";class o extends n.LineTool{constructor(e){super(e),this.tool_name=\"Line Edit Tool\",this.icon=_.bk_tool_icon_line_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=4}static init_LineEditTool(){this.prototype.default_view=d,this.define({dimensions:[r.Dimensions,\"both\"]})}get tooltip(){return this._get_dim_tooltip(this.tool_name,this.dimensions)}}i.LineEditTool=o,o.__name__=\"LineEditTool\",o.init_LineEditTool()},\n", - " function _(e,i,t){Object.defineProperty(t,\"__esModule\",{value:!0});const n=e(1).__importStar(e(18)),o=e(8),s=e(356);class _ extends s.EditToolView{_set_intersection(e,i){const t=this.model.intersection_renderer.glyph,n=this.model.intersection_renderer.data_source,[s,_]=[t.x.field,t.y.field];s&&(o.isArray(e)?n.data[s]=e:t.x={value:e}),_&&(o.isArray(i)?n.data[_]=i:t.y={value:i}),this._emit_cds_changes(n,!0,!0,!1)}_hide_intersections(){this._set_intersection([],[])}}t.LineToolView=_,_.__name__=\"LineToolView\";class r extends s.EditTool{constructor(e){super(e)}static init_LineTool(){this.prototype.default_view=_,this.define({intersection_renderer:[n.Instance]})}}t.LineTool=r,r.__name__=\"LineTool\",r.init_LineTool()},\n", - " function _(t,s,e){Object.defineProperty(e,\"__esModule\",{value:!0});const n=t(1),i=t(306),o=n.__importStar(t(18)),a=t(309);function _(t,s,e){const n=new Map;for(const[i,o]of t){const[t,a]=o.r_invert(s,e);n.set(i,{start:t,end:a})}return n}e.update_ranges=_;class h extends i.GestureToolView{_pan_start(t){this.last_dx=0,this.last_dy=0;const{sx:s,sy:e}=t,n=this.plot_view.frame.bbox;if(!n.contains(s,e)){const t=n.h_range,i=n.v_range;(st.end)&&(this.v_axis_only=!0),(ei.end)&&(this.h_axis_only=!0)}null!=this.model.document&&this.model.document.interactive_start(this.plot_model)}_pan(t){this._update(t.deltaX,t.deltaY),null!=this.model.document&&this.model.document.interactive_start(this.plot_model)}_pan_end(t){this.h_axis_only=!1,this.v_axis_only=!1,null!=this.pan_info&&this.plot_view.push_state(\"pan\",{range:this.pan_info})}_update(t,s){const e=this.plot_view.frame,n=t-this.last_dx,i=s-this.last_dy,o=e.bbox.h_range,a=o.start-n,h=o.end-n,l=e.bbox.v_range,r=l.start-i,d=l.end-i,p=this.model.dimensions;let c,u,m,x,y,g;\"width\"!=p&&\"both\"!=p||this.v_axis_only?(c=o.start,u=o.end,m=0):(c=a,u=h,m=-n),\"height\"!=p&&\"both\"!=p||this.h_axis_only?(x=l.start,y=l.end,g=0):(x=r,y=d,g=-i),this.last_dx=t,this.last_dy=s;const{x_scales:w,y_scales:b}=e,f=_(w,c,u),v=_(b,x,y);this.pan_info={xrs:f,yrs:v,sdx:m,sdy:g},this.plot_view.update_range(this.pan_info,!0)}}e.PanToolView=h,h.__name__=\"PanToolView\";class l extends i.GestureTool{constructor(t){super(t),this.tool_name=\"Pan\",this.event_type=\"pan\",this.default_order=10}static init_PanTool(){this.prototype.default_view=h,this.define({dimensions:[o.Dimensions,\"both\"]}),this.register_alias(\"pan\",()=>new l({dimensions:\"both\"})),this.register_alias(\"xpan\",()=>new l({dimensions:\"width\"})),this.register_alias(\"ypan\",()=>new l({dimensions:\"height\"}))}get tooltip(){return this._get_dim_tooltip(\"Pan\",this.dimensions)}get icon(){switch(this.dimensions){case\"both\":return a.bk_tool_icon_pan;case\"width\":return a.bk_tool_icon_xpan;case\"height\":return a.bk_tool_icon_ypan}}}e.PanTool=l,l.__name__=\"PanTool\",l.init_PanTool()},\n", - " function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=e(1),n=e(124),l=e(19),a=s.__importStar(e(18)),r=e(306),o=e(309);function _(e){switch(e){case 1:return 2;case 2:return 1;case 4:return 5;case 5:return 4;default:return e}}function h(e,t,i,s){if(null==t)return!1;const n=i.compute(t);return Math.abs(e-n)n.right)&&(l=!1)}if(null!=n.bottom&&null!=n.top){const e=s.invert(t);(en.top)&&(l=!1)}return l}function u(e,t,i){let s=0;return e>=i.start&&e<=i.end&&(s+=1),t>=i.start&&t<=i.end&&(s+=1),s}function c(e,t,i,s){const n=t.compute(e),l=t.invert(n+i);return l>=s.start&&l<=s.end?l:e}function g(e,t,i){return e>t.start?(t.end=e,i):(t.end=t.start,t.start=e,_(i))}function y(e,t,i){return e=o&&(e.start=a,e.end=r)}i.flip_side=_,i.is_near=h,i.is_inside=d,i.sides_inside=u,i.compute_value=c,i.update_range_end_side=g,i.update_range_start_side=y,i.update_range=f;class p extends r.GestureToolView{initialize(){super.initialize(),this.side=0,this.model.update_overlay_from_ranges()}connect_signals(){super.connect_signals(),null!=this.model.x_range&&this.connect(this.model.x_range.change,()=>this.model.update_overlay_from_ranges()),null!=this.model.y_range&&this.connect(this.model.y_range.change,()=>this.model.update_overlay_from_ranges())}_pan_start(e){this.last_dx=0,this.last_dy=0;const t=this.model.x_range,i=this.model.y_range,{frame:s}=this.plot_view,l=s.x_scale,a=s.y_scale,r=this.model.overlay,{left:o,right:_,top:u,bottom:c}=r,g=this.model.overlay.properties.line_width.value()+n.EDGE_TOLERANCE;null!=t&&this.model.x_interaction&&(h(e.sx,o,l,g)?this.side=1:h(e.sx,_,l,g)?this.side=2:d(e.sx,e.sy,l,a,r)&&(this.side=3)),null!=i&&this.model.y_interaction&&(0==this.side&&h(e.sy,c,a,g)&&(this.side=4),0==this.side&&h(e.sy,u,a,g)?this.side=5:d(e.sx,e.sy,l,a,this.model.overlay)&&(3==this.side?this.side=7:this.side=6))}_pan(e){const t=this.plot_view.frame,i=e.deltaX-this.last_dx,s=e.deltaY-this.last_dy,n=this.model.x_range,l=this.model.y_range,a=t.x_scale,r=t.y_scale;if(null!=n)if(3==this.side||7==this.side)f(n,a,i,t.x_range);else if(1==this.side){const e=c(n.start,a,i,t.x_range);this.side=y(e,n,this.side)}else if(2==this.side){const e=c(n.end,a,i,t.x_range);this.side=g(e,n,this.side)}if(null!=l)if(6==this.side||7==this.side)f(l,r,s,t.y_range);else if(4==this.side){const e=c(l.start,r,s,t.y_range);this.side=y(e,l,this.side)}else if(5==this.side){const e=c(l.end,r,s,t.y_range);this.side=g(e,l,this.side)}this.last_dx=e.deltaX,this.last_dy=e.deltaY}_pan_end(e){this.side=0}}i.RangeToolView=p,p.__name__=\"RangeToolView\";const m=()=>new n.BoxAnnotation({level:\"overlay\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:.5,line_dash:[2,2]});class v extends r.GestureTool{constructor(e){super(e),this.tool_name=\"Range Tool\",this.icon=o.bk_tool_icon_range,this.event_type=\"pan\",this.default_order=1}static init_RangeTool(){this.prototype.default_view=p,this.define({x_range:[a.Instance,null],x_interaction:[a.Boolean,!0],y_range:[a.Instance,null],y_interaction:[a.Boolean,!0],overlay:[a.Instance,m]})}initialize(){super.initialize(),this.overlay.in_cursor=\"grab\",this.overlay.ew_cursor=null!=this.x_range&&this.x_interaction?\"ew-resize\":null,this.overlay.ns_cursor=null!=this.y_range&&this.y_interaction?\"ns-resize\":null}update_overlay_from_ranges(){null==this.x_range&&null==this.y_range&&(this.overlay.left=null,this.overlay.right=null,this.overlay.bottom=null,this.overlay.top=null,l.logger.warn(\"RangeTool not configured with any Ranges.\")),null==this.x_range?(this.overlay.left=null,this.overlay.right=null):(this.overlay.left=this.x_range.start,this.overlay.right=this.x_range.end),null==this.y_range?(this.overlay.bottom=null,this.overlay.top=null):(this.overlay.bottom=this.y_range.start,this.overlay.top=this.y_range.end)}}i.RangeTool=v,v.__name__=\"RangeTool\",v.init_RangeTool()},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const o=e(1),i=e(364),c=o.__importStar(e(18)),n=e(309);class a extends i.SelectToolView{_tap(e){const{sx:t,sy:s}=e,o={type:\"point\",sx:t,sy:s};this._select(o,!0,this._select_mode(e))}_select(e,t,s){const o=this.model.callback;if(\"select\"==this.model.behavior){const i=this._computed_renderers_by_data_source();for(const[,c]of i){const i=c[0].get_selection_manager(),n=c.map(e=>this.plot_view.renderer_views.get(e));if(i.select(n,e,t,s)&&null!=o){const t=n[0].coordinates.x_scale.invert(e.sx),s=n[0].coordinates.y_scale.invert(e.sy),c={geometries:Object.assign(Object.assign({},e),{x:t,y:s}),source:i.source};o.execute(this.model,c)}}this._emit_selection_event(e),this.plot_view.push_state(\"tap\",{selection:this.plot_view.get_selection()})}else for(const t of this.computed_renderers){const s=this.plot_view.renderer_views.get(t),i=t.get_selection_manager();if(i.inspect(s,e)&&null!=o){const t=s.coordinates.x_scale.invert(e.sx),c=s.coordinates.y_scale.invert(e.sy),n={geometries:Object.assign(Object.assign({},e),{x:t,y:c}),source:i.source};o.execute(this.model,n)}}}}s.TapToolView=a,a.__name__=\"TapToolView\";class _ extends i.SelectTool{constructor(e){super(e),this.tool_name=\"Tap\",this.icon=n.bk_tool_icon_tap_select,this.event_type=\"tap\",this.default_order=10}static init_TapTool(){this.prototype.default_view=a,this.define({behavior:[c.TapBehavior,\"select\"],callback:[c.Any]}),this.register_alias(\"click\",()=>new _({behavior:\"inspect\"})),this.register_alias(\"tap\",()=>new _)}}s.TapTool=_,_.__name__=\"TapTool\",_.init_TapTool()},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=e(1),o=e(306),n=i.__importStar(e(18)),a=e(309),l=e(371);class _ extends o.GestureToolView{_scroll(e){let t=this.model.speed*e.delta;t>.9?t=.9:t<-.9&&(t=-.9),this._update_ranges(t)}_update_ranges(e){const{frame:t}=this.plot_view,s=t.bbox.h_range,i=t.bbox.v_range,[o,n]=[s.start,s.end],[a,_]=[i.start,i.end];let h,r,d,p;switch(this.model.dimension){case\"height\":{const t=Math.abs(_-a);h=o,r=n,d=a-t*e,p=_-t*e;break}case\"width\":{const t=Math.abs(n-o);h=o-t*e,r=n-t*e,d=a,p=_;break}default:throw new Error(\"this shouldn't have happened\")}const{x_scales:c,y_scales:u}=t,m={xrs:l.update_ranges(c,h,r),yrs:l.update_ranges(u,d,p),factor:e};this.plot_view.push_state(\"wheel_pan\",{range:m}),this.plot_view.update_range(m,!1,!0),null!=this.model.document&&this.model.document.interactive_start(this.plot_model)}}s.WheelPanToolView=_,_.__name__=\"WheelPanToolView\";class h extends o.GestureTool{constructor(e){super(e),this.tool_name=\"Wheel Pan\",this.icon=a.bk_tool_icon_wheel_pan,this.event_type=\"scroll\",this.default_order=12}static init_WheelPanTool(){this.prototype.default_view=_,this.define({dimension:[n.Dimension,\"width\"]}),this.internal({speed:[n.Number,.001]}),this.register_alias(\"xwheel_pan\",()=>new h({dimension:\"width\"})),this.register_alias(\"ywheel_pan\",()=>new h({dimension:\"height\"}))}get tooltip(){return this._get_dim_tooltip(this.tool_name,this.dimension)}}s.WheelPanTool=h,h.__name__=\"WheelPanTool\",h.init_WheelPanTool()},\n", - " function _(e,o,t){Object.defineProperty(t,\"__esModule\",{value:!0});const s=e(1),i=e(306),l=e(354),n=s.__importStar(e(18)),_=e(32),h=e(309);class a extends i.GestureToolView{_pinch(e){const{sx:o,sy:t,scale:s,ctrlKey:i,shiftKey:l}=e;let n;n=s>=1?20*(s-1):-20/s,this._scroll({type:\"wheel\",sx:o,sy:t,delta:n,ctrlKey:i,shiftKey:l})}_scroll(e){const{frame:o}=this.plot_view,t=o.bbox.h_range,s=o.bbox.v_range,{sx:i,sy:n}=e,_=this.model.dimensions,h=(\"width\"==_||\"both\"==_)&&t.startnew m({dimensions:\"both\"})),this.register_alias(\"xwheel_zoom\",()=>new m({dimensions:\"width\"})),this.register_alias(\"ywheel_zoom\",()=>new m({dimensions:\"height\"}))}get tooltip(){return this._get_dim_tooltip(this.tool_name,this.dimensions)}}t.WheelZoomTool=m,m.__name__=\"WheelZoomTool\",m.init_WheelZoomTool()},\n", - " function _(i,s,e){Object.defineProperty(e,\"__esModule\",{value:!0});const t=i(1),o=i(295),n=i(168),l=t.__importStar(i(18)),h=i(13),a=i(309);class r extends o.InspectToolView{_move(i){if(!this.model.active)return;const{sx:s,sy:e}=i;this.plot_view.frame.bbox.contains(s,e)?this._update_spans(s,e):this._update_spans(null,null)}_move_exit(i){this._update_spans(null,null)}_update_spans(i,s){const e=this.model.dimensions;\"width\"!=e&&\"both\"!=e||(this.model.spans.width.location=s),\"height\"!=e&&\"both\"!=e||(this.model.spans.height.location=i)}}e.CrosshairToolView=r,r.__name__=\"CrosshairToolView\";class _ extends o.InspectTool{constructor(i){super(i),this.tool_name=\"Crosshair\",this.icon=a.bk_tool_icon_crosshair}static init_CrosshairTool(){this.prototype.default_view=r,this.define({dimensions:[l.Dimensions,\"both\"],line_color:[l.Color,\"black\"],line_width:[l.Number,1],line_alpha:[l.Number,1]}),this.internal({spans:[l.Any]}),this.register_alias(\"crosshair\",()=>new _)}get tooltip(){return this._get_dim_tooltip(\"Crosshair\",this.dimensions)}get synthetic_renderers(){return h.values(this.spans)}initialize(){super.initialize(),this.spans={width:new n.Span({for_hover:!0,dimension:\"width\",location_units:\"screen\",level:\"overlay\",line_color:this.line_color,line_width:this.line_width,line_alpha:this.line_alpha}),height:new n.Span({for_hover:!0,dimension:\"height\",location_units:\"screen\",level:\"overlay\",line_color:this.line_color,line_width:this.line_width,line_alpha:this.line_alpha})}}}e.CrosshairTool=_,_.__name__=\"CrosshairTool\",_.init_CrosshairTool()},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const r=e(1),o=e(81),i=r.__importStar(e(18)),a=e(13),n=e(29);class u extends o.Model{constructor(e){super(e)}static init_CustomJSHover(){this.define({args:[i.Any,{}],code:[i.String,\"\"]})}get values(){return a.values(this.args)}_make_code(e,t,s,r){return new Function(...a.keys(this.args),e,t,s,n.use_strict(r))}format(e,t,s){return this._make_code(\"value\",\"format\",\"special_vars\",this.code)(...this.values,e,t,s)}}s.CustomJSHover=u,u.__name__=\"CustomJSHover\",u.init_CustomJSHover()},\n", - " function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const o=e(1),n=e(295),i=e(171),r=e(90),l=e(116),c=e(365),a=o.__importStar(e(101)),_=e(187),d=e(72),p=o.__importStar(e(18)),h=e(22),m=e(13),u=e(303),y=e(8),f=e(115),x=e(309),v=e(172);function w(e,t,s,o,n,i){const r={x:n[e],y:i[e]},l={x:n[e+1],y:i[e+1]};let c,_;if(\"span\"==t.type)\"h\"==t.direction?(c=Math.abs(r.x-s),_=Math.abs(l.x-s)):(c=Math.abs(r.y-o),_=Math.abs(l.y-o));else{const e={x:s,y:o};c=a.dist_2_pts(r,e),_=a.dist_2_pts(l,e)}return c<_?[[r.x,r.y],e]:[[l.x,l.y],e+1]}function g(e,t,s){return[[e[s],t[s]],s]}s._nearest_line_hit=w,s._line_hit=g;class b extends n.InspectToolView{initialize(){super.initialize(),this._ttmodels=null,this._ttviews=new Map;const{tooltips:e}=this.model;y.isArray(e)&&(this._template_el=this._create_template(e))}remove(){f.remove_views(this._ttviews),super.remove()}connect_signals(){super.connect_signals();for(const e of this.computed_renderers)e instanceof r.GlyphRenderer?this.connect(e.data_source.inspect,this._update):e instanceof l.GraphRenderer&&(this.connect(e.node_renderer.data_source.inspect,this._update),this.connect(e.edge_renderer.data_source.inspect,this._update));this.connect(this.model.properties.renderers.change,()=>this._computed_renderers=this._ttmodels=null),this.connect(this.model.properties.names.change,()=>this._computed_renderers=this._ttmodels=null),this.connect(this.model.properties.tooltips.change,()=>this._ttmodels=null)}_compute_ttmodels(){const e=new Map,t=this.model.tooltips;if(null!=t)for(const s of this.computed_renderers){const o=new i.Tooltip({custom:y.isString(t)||y.isFunction(t),attachment:this.model.attachment,show_arrow:this.model.show_arrow});s instanceof r.GlyphRenderer?e.set(s,o):s instanceof l.GraphRenderer&&(e.set(s.node_renderer,o),e.set(s.edge_renderer,o))}return(async()=>{const t=await f.build_views(this._ttviews,[...e.values()],{parent:this.plot_view});for(const e of t)e.render()})(),e}get computed_renderers(){if(null==this._computed_renderers){const e=this.model.renderers,t=this.plot_model.renderers,s=this.model.names;this._computed_renderers=c.compute_renderers(e,t,s)}return this._computed_renderers}get ttmodels(){return null==this._ttmodels&&(this._ttmodels=this._compute_ttmodels()),this._ttmodels}_clear(){this._inspect(1/0,1/0);for(const[,e]of this.ttmodels)e.clear()}_move(e){if(!this.model.active)return;const{sx:t,sy:s}=e;this.plot_view.frame.bbox.contains(t,s)?this._inspect(t,s):this._clear()}_move_exit(){this._clear()}_inspect(e,t){let s;if(\"mouse\"==this.model.mode)s={type:\"point\",sx:e,sy:t};else{s={type:\"span\",direction:\"vline\"==this.model.mode?\"h\":\"v\",sx:e,sy:t}}for(const e of this.computed_renderers){e.get_selection_manager().inspect(this.plot_view.renderer_views.get(e),s)}null!=this.model.callback&&this._emit_callback(s)}_update([e,{geometry:t}]){if(!this.model.active)return;if(!(e instanceof r.GlyphRendererView))return;const{model:s}=e;if(\"ignore\"==this.model.muted_policy&&s instanceof r.GlyphRenderer&&s.muted)return;const o=this.ttmodels.get(s);if(null==o)return;const n=s.get_selection_manager();let i=n.inspectors.get(s);if(s instanceof r.GlyphRenderer&&(i=s.view.convert_selection_to_subset(i)),i.is_empty())return void o.clear();const l=n.source,{sx:c,sy:a}=t,_=e.coordinates.x_scale,p=e.coordinates.y_scale,h=_.invert(c),u=p.invert(a),y=e.glyph,f=[];for(const s of i.line_indices){let o,n,r=y._x[s+1],d=y._y[s+1],m=s;switch(this.model.line_policy){case\"interp\":[r,d]=y.get_interpolation_hit(s,t),o=_.compute(r),n=p.compute(d);break;case\"prev\":[[o,n],m]=g(y.sx,y.sy,s);break;case\"next\":[[o,n],m]=g(y.sx,y.sy,s+1);break;case\"nearest\":[[o,n],m]=w(s,t,c,a,y.sx,y.sy),r=y._x[m],d=y._y[m];break;default:[o,n]=[c,a]}const x={index:m,x:h,y:u,sx:c,sy:a,data_x:r,data_y:d,rx:o,ry:n,indices:i.line_indices,name:e.model.name};f.push([o,n,this._render_tooltips(l,m,x)])}for(const t of i.image_indices){const s={index:t.index,x:h,y:u,sx:c,sy:a,name:e.model.name},o=this._render_tooltips(l,t,s);f.push([c,a,o])}for(const o of i.indices)if(m.isEmpty(i.multiline_indices)){const t=null!=y._x?y._x[o]:void 0,n=null!=y._y?y._y[o]:void 0;let _,d,p;if(\"snap_to_data\"==this.model.point_policy){let e=y.get_anchor_point(this.model.anchor,o,[c,a]);null==e&&(e=y.get_anchor_point(\"center\",o,[c,a])),_=e.x,d=e.y}else[_,d]=[c,a];p=s instanceof r.GlyphRenderer?s.view.convert_indices_from_subset([o])[0]:o;const m={index:p,x:h,y:u,sx:c,sy:a,data_x:t,data_y:n,indices:i.indices,name:e.model.name};f.push([_,d,this._render_tooltips(l,p,m)])}else for(const n of i.multiline_indices[o.toString()]){let d,m,x,v=y._xs[o][n],b=y._ys[o][n],k=n;switch(this.model.line_policy){case\"interp\":[v,b]=y.get_interpolation_hit(o,n,t),d=_.compute(v),m=p.compute(b);break;case\"prev\":[[d,m],k]=g(y.sxs[o],y.sys[o],n);break;case\"next\":[[d,m],k]=g(y.sxs[o],y.sys[o],n+1);break;case\"nearest\":[[d,m],k]=w(n,t,c,a,y.sxs[o],y.sys[o]),v=y._xs[o][k],b=y._ys[o][k];break;default:throw new Error(\"should't have happened\")}x=s instanceof r.GlyphRenderer?s.view.convert_indices_from_subset([o])[0]:o;const A={index:x,x:h,y:u,sx:c,sy:a,data_x:v,data_y:b,segment_index:k,indices:i.multiline_indices,name:e.model.name};f.push([d,m,this._render_tooltips(l,x,A)])}if(0==f.length)o.clear();else{const{content:e}=o;d.empty(o.content);for(const[,,t]of f)e.appendChild(t);const[t,s]=f[f.length-1];o.setv({position:[t,s]},{check_eq:!1})}}_emit_callback(e){for(const t of this.computed_renderers){const s=this.plot_view.renderer_views.get(t),o=s.coordinates.x_scale.invert(e.sx),n=s.coordinates.y_scale.invert(e.sy),i=t.data_source.inspected,r=Object.assign({x:o,y:n},e);this.model.callback.execute(this.model,{index:i,geometry:r,renderer:t})}}_create_template(e){const t=d.div({style:{display:\"table\",borderSpacing:\"2px\"}});for(const[s]of e){const e=d.div({style:{display:\"table-row\"}});t.appendChild(e);const o=d.div({style:{display:\"table-cell\"},class:v.bk_tooltip_row_label},0!=s.length?s+\": \":\"\");e.appendChild(o);const n=d.span();n.dataset.value=\"\";const i=d.span({class:v.bk_tooltip_color_block},\" \");i.dataset.swatch=\"\",d.undisplay(i);const r=d.div({style:{display:\"table-cell\"},class:v.bk_tooltip_row_value},n,i);e.appendChild(r)}return t}_render_template(e,t,s,o,n){const i=e.cloneNode(!0),r=i.querySelectorAll(\"[data-value]\"),l=i.querySelectorAll(\"[data-swatch]\"),c=/\\$color(\\[.*\\])?:(\\w*)/;for(const[[,e],i]of u.enumerate(t)){const t=e.match(c);if(null!=t){const[,e=\"\",n]=t,c=s.get_column(n);if(null==c){r[i].textContent=n+\" unknown\";continue}const a=e.indexOf(\"hex\")>=0,_=e.indexOf(\"swatch\")>=0;let p=y.isNumber(o)?c[o]:null;if(null==p){r[i].textContent=\"(null)\";continue}a&&(p=h.color2hex(p)),r[i].textContent=p,_&&(l[i].style.backgroundColor=p,d.display(l[i]))}else{const t=_.replace_placeholders(e.replace(\"$~\",\"$data_\"),s,o,this.model.formatters,n);if(y.isString(t))r[i].textContent=t;else for(const e of t)r[i].appendChild(e)}}return i}_render_tooltips(e,t,s){const o=this.model.tooltips;if(y.isString(o)){const n=_.replace_placeholders({html:o},e,t,this.model.formatters,s);return d.div({},n)}return y.isFunction(o)?o(e,s):this._render_template(this._template_el,o,e,t,s)}}s.HoverToolView=b,b.__name__=\"HoverToolView\";class k extends n.InspectTool{constructor(e){super(e),this.tool_name=\"Hover\",this.icon=x.bk_tool_icon_hover}static init_HoverTool(){this.prototype.default_view=b,this.define({tooltips:[p.Any,[[\"index\",\"$index\"],[\"data (x, y)\",\"($x, $y)\"],[\"screen (x, y)\",\"($sx, $sy)\"]]],formatters:[p.Any,{}],renderers:[p.Any,\"auto\"],names:[p.Array,[]],mode:[p.HoverMode,\"mouse\"],muted_policy:[p.MutedPolicy,\"show\"],point_policy:[p.PointPolicy,\"snap_to_data\"],line_policy:[p.LinePolicy,\"nearest\"],show_arrow:[p.Boolean,!0],anchor:[p.Anchor,\"center\"],attachment:[p.TooltipAttachment,\"horizontal\"],callback:[p.Any]}),this.register_alias(\"hover\",()=>new k)}}s.HoverTool=k,k.__name__=\"HoverTool\",k.init_HoverTool()},\n", - " function _(t,o,e){Object.defineProperty(e,\"__esModule\",{value:!0});const i=t(1).__importStar(t(18)),n=t(15),s=t(81),l=t(295),c=t(303);class r extends s.Model{constructor(t){super(t)}static init_ToolProxy(){this.define({tools:[i.Array,[]],active:[i.Boolean,!1],disabled:[i.Boolean,!1]})}get button_view(){return this.tools[0].button_view}get event_type(){return this.tools[0].event_type}get tooltip(){return this.tools[0].tooltip}get tool_name(){return this.tools[0].tool_name}get icon(){return this.tools[0].computed_icon}get computed_icon(){return this.icon}get toggleable(){const t=this.tools[0];return t instanceof l.InspectTool&&t.toggleable}initialize(){super.initialize(),this.do=new n.Signal0(this,\"do\")}connect_signals(){super.connect_signals(),this.connect(this.do,()=>this.doit()),this.connect(this.properties.active.change,()=>this.set_active());for(const t of this.tools)this.connect(t.properties.active.change,()=>{this.active=t.active})}doit(){for(const t of this.tools)t.do.emit()}set_active(){for(const t of this.tools)t.active=this.active}get menu(){const{menu:t}=this.tools[0];if(null==t)return null;const o=[];for(const[e,i]of c.enumerate(t))if(null==e)o.push(null);else{const t=()=>{var t,o;for(const e of this.tools)null===(o=null===(t=e.menu)||void 0===t?void 0:t[i])||void 0===o||o.handler()};o.push(Object.assign(Object.assign({},e),{handler:t}))}return o}}e.ToolProxy=r,r.__name__=\"ToolProxy\",r.init_ToolProxy()},\n", - " function _(o,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=o(1).__importStar(o(18)),e=o(9),n=o(13),r=o(305),l=o(379),c=o(272),h=o(212);class a extends r.ToolbarBase{constructor(o){super(o)}static init_ProxyToolbar(){this.define({toolbars:[i.Array,[]]})}initialize(){super.initialize(),this._merge_tools()}_merge_tools(){this._proxied_tools=[];const o={},t={},s={},i=[],r=[];for(const o of this.help)e.includes(r,o.redirect)||(i.push(o),r.push(o.redirect));this._proxied_tools.push(...i),this.help=i;for(const[o,t]of n.entries(this.gestures)){o in s||(s[o]={});for(const i of t.tools)i.type in s[o]||(s[o][i.type]=[]),s[o][i.type].push(i)}for(const t of this.inspectors)t.type in o||(o[t.type]=[]),o[t.type].push(t);for(const o of this.actions)o.type in t||(t[o.type]=[]),t[o.type].push(o);const c=(o,t=!1)=>{const s=new l.ToolProxy({tools:o,active:t});return this._proxied_tools.push(s),s};for(const o of n.keys(s)){const t=this.gestures[o];t.tools=[];for(const i of n.keys(s[o])){const e=s[o][i];if(e.length>0)if(\"multi\"==o)for(const o of e){const s=c([o]);t.tools.push(s),this.connect(s.properties.active.change,()=>this._active_change(s))}else{const o=c(e);t.tools.push(o),this.connect(o.properties.active.change,()=>this._active_change(o))}}}this.actions=[];for(const[o,s]of n.entries(t))if(\"CustomAction\"==o)for(const o of s)this.actions.push(c([o]));else s.length>0&&this.actions.push(c(s));this.inspectors=[];for(const t of n.values(o))t.length>0&&this.inspectors.push(c(t,!0));for(const[o,t]of n.entries(this.gestures))0!=t.tools.length&&(t.tools=e.sort_by(t.tools,o=>o.default_order),\"pinch\"!=o&&\"scroll\"!=o&&\"multi\"!=o&&(t.tools[0].active=!0))}}s.ProxyToolbar=a,a.__name__=\"ProxyToolbar\",a.init_ProxyToolbar();class _ extends c.LayoutDOMView{initialize(){this.model.toolbar.toolbar_location=this.model.toolbar_location,super.initialize()}get child_models(){return[this.model.toolbar]}_update_layout(){this.layout=new h.ContentBox(this.child_views[0].el);const{toolbar:o}=this.model;o.horizontal?this.layout.set_sizing({width_policy:\"fit\",min_width:100,height_policy:\"fixed\"}):this.layout.set_sizing({width_policy:\"fixed\",height_policy:\"fit\",min_height:100})}}s.ToolbarBoxView=_,_.__name__=\"ToolbarBoxView\";class p extends c.LayoutDOM{constructor(o){super(o)}static init_ToolbarBox(){this.prototype.default_view=_,this.define({toolbar:[i.Instance],toolbar_location:[i.Location,\"right\"]})}}s.ToolbarBox=p,p.__name__=\"ToolbarBox\",p.init_ToolbarBox()},\n", - " function _(e,n,t){Object.defineProperty(t,\"__esModule\",{value:!0});const o=e(5),i=e(78),d=e(115),c=e(72),l=e(382);t.index={},t.add_document_standalone=async function(e,n,s=[],a=!1){const u=new Map;async function r(o){let a;const r=e.roots().indexOf(o),f=s[r];null!=f?a=f:n.classList.contains(l.BOKEH_ROOT)?a=n:(a=c.div({class:l.BOKEH_ROOT}),n.appendChild(a));const v=await d.build_view(o,{parent:null});return v instanceof i.DOMView&&v.renderTo(a),u.set(o,v),t.index[o.id]=v,v}for(const n of e.roots())await r(n);return a&&(window.document.title=e.title()),e.on_change(e=>{e instanceof o.RootAddedEvent?r(e.model):e instanceof o.RootRemovedEvent?function(e){const n=u.get(e);null!=n&&(n.remove(),u.delete(e),delete t.index[e.id])}(e.model):a&&e instanceof o.TitleChangedEvent&&(window.document.title=e.title)}),[...u.values()]}},\n", - " function _(e,o,n){Object.defineProperty(n,\"__esModule\",{value:!0});const t=e(72),r=e(273);function l(e){let o=document.getElementById(e);if(null==o)throw new Error(`Error rendering Bokeh model: could not find #${e} HTML tag`);if(!document.body.contains(o))throw new Error(`Error rendering Bokeh model: element #${e} must be under `);if(\"SCRIPT\"==o.tagName){const e=t.div({class:n.BOKEH_ROOT});t.replaceWith(o,e),o=e}return o}n.BOKEH_ROOT=r.bk_root,n._resolve_element=function(e){const{elementid:o}=e;return null!=o?l(o):document.body},n._resolve_root_elements=function(e){const o=[];if(null!=e.root_ids&&null!=e.roots)for(const n of e.root_ids)o.push(l(e.roots[n]));return o}},\n", - " function _(n,o,t){Object.defineProperty(t,\"__esModule\",{value:!0});const e=n(384),s=n(19),c=n(381);t._get_ws_url=function(n,o){let t,e=\"ws:\";return\"https:\"==window.location.protocol&&(e=\"wss:\"),null!=o?(t=document.createElement(\"a\"),t.href=o):t=window.location,null!=n?\"/\"==n&&(n=\"\"):n=t.pathname.replace(/\\/+$/,\"\"),e+\"//\"+t.host+n+\"/ws\"};const r={};t.add_document_from_session=async function(n,o,t,a=[],i=!1){const l=window.location.search.substr(1);let d;try{d=await function(n,o,t){const s=e.parse_token(o).session_id;n in r||(r[n]={});const c=r[n];return s in c||(c[s]=e.pull_session(n,o,t)),c[s]}(n,o,l)}catch(n){const t=e.parse_token(o).session_id;throw s.logger.error(`Failed to load Bokeh session ${t}: ${n}`),n}return c.add_document_standalone(d.document,t,a,i)}},\n", - " function _(e,s,n){Object.defineProperty(n,\"__esModule\",{value:!0});const t=e(19),o=e(5),r=e(385),i=e(386),c=e(387);n.DEFAULT_SERVER_WEBSOCKET_URL=\"ws://localhost:5006/ws\",n.DEFAULT_TOKEN=\"eyJzZXNzaW9uX2lkIjogImRlZmF1bHQifQ\";let l=0;function _(e){let s=e.split(\".\")[0];const n=s.length%4;return 0!=n&&(s+=\"=\".repeat(4-n)),JSON.parse(atob(s.replace(/_/g,\"/\").replace(/-/g,\"+\")))}n.parse_token=_;class h{constructor(e=n.DEFAULT_SERVER_WEBSOCKET_URL,s=n.DEFAULT_TOKEN,o=null){this.url=e,this.token=s,this.args_string=o,this._number=l++,this.socket=null,this.session=null,this.closed_permanently=!1,this._current_handler=null,this._pending_replies=new Map,this._pending_messages=[],this._receiver=new i.Receiver,this.id=_(s).session_id.split(\".\")[0],t.logger.debug(`Creating websocket ${this._number} to '${this.url}' session '${this.id}'`)}async connect(){if(this.closed_permanently)throw new Error(\"Cannot connect() a closed ClientConnection\");if(null!=this.socket)throw new Error(\"Already connected\");this._current_handler=null,this._pending_replies.clear(),this._pending_messages=[];try{let e=\"\"+this.url;return null!=this.args_string&&this.args_string.length>0&&(e+=\"?\"+this.args_string),this.socket=new WebSocket(e,[\"bokeh\",this.token]),new Promise((e,s)=>{this.socket.binaryType=\"arraybuffer\",this.socket.onopen=()=>this._on_open(e,s),this.socket.onmessage=e=>this._on_message(e),this.socket.onclose=e=>this._on_close(e,s),this.socket.onerror=()=>this._on_error(s)})}catch(e){throw t.logger.error(\"websocket creation failed to url: \"+this.url),t.logger.error(\" - \"+e),e}}close(){this.closed_permanently||(t.logger.debug(\"Permanently closing websocket connection \"+this._number),this.closed_permanently=!0,null!=this.socket&&this.socket.close(1e3,\"close method called on ClientConnection \"+this._number),this.session._connection_closed())}_schedule_reconnect(e){setTimeout(()=>{this.closed_permanently||t.logger.info(`Websocket connection ${this._number} disconnected, will not attempt to reconnect`)},e)}send(e){if(null==this.socket)throw new Error(\"not connected so cannot send \"+e);e.send(this.socket)}async send_with_reply(e){const s=await new Promise((s,n)=>{this._pending_replies.set(e.msgid(),{resolve:s,reject:n}),this.send(e)});if(\"ERROR\"===s.msgtype())throw new Error(\"Error reply \"+s.content.text);return s}async _pull_doc_json(){const e=r.Message.create(\"PULL-DOC-REQ\",{}),s=await this.send_with_reply(e);if(!(\"doc\"in s.content))throw new Error(\"No 'doc' field in PULL-DOC-REPLY\");return s.content.doc}async _repull_session_doc(e,s){var n;t.logger.debug(this.session?\"Repulling session\":\"Pulling session for first time\");try{const n=await this._pull_doc_json();if(null==this.session)if(this.closed_permanently)t.logger.debug(\"Got new document after connection was already closed\"),s(new Error(\"The connection has been closed\"));else{const s=o.Document.from_json(n),i=o.Document._compute_patch_since_json(n,s);if(i.events.length>0){t.logger.debug(`Sending ${i.events.length} changes from model construction back to server`);const e=r.Message.create(\"PATCH-DOC\",{},i);this.send(e)}this.session=new c.ClientSession(this,s,this.id);for(const e of this._pending_messages)this.session.handle(e);this._pending_messages=[],t.logger.debug(\"Created a new session from new pulled doc\"),e(this.session)}else this.session.document.replace_with_json(n),t.logger.debug(\"Updated existing session with new pulled doc\")}catch(e){null===(n=console.trace)||void 0===n||n.call(console,e),t.logger.error(\"Failed to repull session \"+e),s(e)}}_on_open(e,s){t.logger.info(`Websocket connection ${this._number} is now open`),this._current_handler=n=>{this._awaiting_ack_handler(n,e,s)}}_on_message(e){null==this._current_handler&&t.logger.error(\"Got a message with no current handler set\");try{this._receiver.consume(e.data)}catch(e){this._close_bad_protocol(e.toString())}const s=this._receiver.message;if(null!=s){const e=s.problem();null!=e&&this._close_bad_protocol(e),this._current_handler(s)}}_on_close(e,s){t.logger.info(`Lost websocket ${this._number} connection, ${e.code} (${e.reason})`),this.socket=null,this._pending_replies.forEach(e=>e.reject(\"Disconnected\")),this._pending_replies.clear(),this.closed_permanently||this._schedule_reconnect(2e3),s(new Error(`Lost websocket connection, ${e.code} (${e.reason})`))}_on_error(e){t.logger.debug(\"Websocket error on socket \"+this._number);const s=\"Could not open websocket\";t.logger.error(\"Failed to connect to Bokeh server: \"+s),e(new Error(s))}_close_bad_protocol(e){t.logger.error(\"Closing connection: 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{});\n", - " })\n", - "\n", - "\n", - " /* END bokeh.min.js */\n", - " },\n", - " \n", - " function(Bokeh) {\n", - " /* BEGIN bokeh-widgets.min.js */\n", - " /*!\n", - " * Copyright (c) 2012 - 2020, Anaconda, Inc., and Bokeh Contributors\n", - " * All rights reserved.\n", - " * \n", - " * Redistribution and use in source and binary forms, with or without modification,\n", - " * are permitted provided that the following conditions are met:\n", - " * \n", - " * Redistributions of source code must retain the above copyright notice,\n", - " * this list of conditions and the following disclaimer.\n", - " * \n", - " * Redistributions in binary form must reproduce the above copyright notice,\n", - " * this list of conditions and the following disclaimer in the documentation\n", - " * and/or other materials provided with the distribution.\n", - " * \n", - " * Neither the name of Anaconda nor the names of any contributors\n", - " * may be used to endorse or promote products derived from this software\n", - " * without specific prior written permission.\n", - " * \n", - " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", - " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", - " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", - " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", - " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", - " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", - " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", - " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", - " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", - " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", - " * THE POSSIBILITY OF SUCH DAMAGE.\n", - " */\n", - " (function(root, factory) {\n", - " factory(root[\"Bokeh\"], \"2.2.3\");\n", - " })(this, function(Bokeh, version) {\n", - " var define;\n", - " return (function(modules, entry, aliases, externals) {\n", - " const bokeh = typeof Bokeh !== \"undefined\" && (version != null ? Bokeh[version] : Bokeh);\n", - " if (bokeh != null) {\n", - " return bokeh.register_plugin(modules, entry, aliases);\n", - " } else {\n", - " throw new Error(\"Cannot find Bokeh \" + version + \". You have to load it prior to loading plugins.\");\n", - " }\n", - " })\n", - " ({\n", - " 402: function _(e,t,o){Object.defineProperty(o,\"__esModule\",{value:!0});const r=e(1).__importStar(e(403));o.Widgets=r;e(7).register_models(r)},\n", - " 403: function _(r,e,t){Object.defineProperty(t,\"__esModule\",{value:!0});var a=r(404);t.AbstractButton=a.AbstractButton;var o=r(407);t.AbstractIcon=o.AbstractIcon;var u=r(408);t.AutocompleteInput=u.AutocompleteInput;var n=r(413);t.Button=n.Button;var i=r(414);t.CheckboxButtonGroup=i.CheckboxButtonGroup;var v=r(416);t.CheckboxGroup=v.CheckboxGroup;var p=r(418);t.ColorPicker=p.ColorPicker;var c=r(419);t.DatePicker=c.DatePicker;var l=r(422);t.DateRangeSlider=l.DateRangeSlider;var d=r(428);t.DateSlider=d.DateSlider;var I=r(429);t.Div=I.Div;var g=r(433);t.Dropdown=g.Dropdown;var S=r(434);t.FileInput=S.FileInput;var P=r(410);t.InputWidget=P.InputWidget;var k=r(430);t.Markup=k.Markup;var x=r(435);t.MultiSelect=x.MultiSelect;var D=r(436);t.Paragraph=D.Paragraph;var b=r(437);t.PasswordInput=b.PasswordInput;var s=r(438);t.MultiChoice=s.MultiChoice;var h=r(441);t.NumericInput=h.NumericInput;var A=r(444);t.PreText=A.PreText;var B=r(445);t.RadioButtonGroup=B.RadioButtonGroup;var C=r(446);t.RadioGroup=C.RadioGroup;var G=r(447);t.RangeSlider=G.RangeSlider;var R=r(448);t.Select=R.Select;var T=r(449);t.Slider=T.Slider;var M=r(450);t.Spinner=M.Spinner;var m=r(409);t.TextInput=m.TextInput;var w=r(451);t.TextAreaInput=w.TextAreaInput;var W=r(452);t.Toggle=W.Toggle;var _=r(472);t.Widget=_.Widget},\n", - " 404: function _(t,e,n){Object.defineProperty(n,\"__esModule\",{value:!0});const i=t(1),s=i.__importStar(t(18)),o=t(72),l=t(115),r=t(405),_=t(281),c=i.__importDefault(t(283));class u extends r.ControlView{*controls(){yield this.button_el}async lazy_initialize(){await super.lazy_initialize();const{icon:t}=this.model;null!=t&&(this.icon_view=await l.build_view(t,{parent:this}))}connect_signals(){super.connect_signals(),this.connect(this.model.change,()=>this.render())}remove(){null!=this.icon_view&&this.icon_view.remove(),super.remove()}styles(){return[...super.styles(),c.default]}_render_button(...t){return o.button({type:\"button\",disabled:this.model.disabled,class:[_.bk_btn,_.bk_btn_type(this.model.button_type)]},...t)}render(){super.render(),this.button_el=this._render_button(this.model.label),this.button_el.addEventListener(\"click\",()=>this.click()),null!=this.icon_view&&(o.prepend(this.button_el,this.icon_view.el,o.nbsp()),this.icon_view.render()),this.group_el=o.div({class:_.bk_btn_group},this.button_el),this.el.appendChild(this.group_el)}click(){}}n.AbstractButtonView=u,u.__name__=\"AbstractButtonView\";class a extends r.Control{constructor(t){super(t)}static init_AbstractButton(){this.define({label:[s.String,\"Button\"],icon:[s.Instance],button_type:[s.ButtonType,\"default\"]})}}n.AbstractButton=a,a.__name__=\"AbstractButton\",a.init_AbstractButton()},\n", - " 405: function _(e,t,o){Object.defineProperty(o,\"__esModule\",{value:!0});const s=e(472),n=e(72);class i extends s.WidgetView{connect_signals(){super.connect_signals();const e=this.model.properties;this.on_change(e.disabled,()=>{for(const e of this.controls())n.toggle_attribute(e,\"disabled\",this.model.disabled)})}}o.ControlView=i,i.__name__=\"ControlView\";class l extends s.Widget{constructor(e){super(e)}}o.Control=l,l.__name__=\"Control\"},\n", - " 472: function _(i,e,t){Object.defineProperty(t,\"__esModule\",{value:!0});const o=i(1),n=i(276),r=o.__importStar(i(18));class _ extends n.HTMLBoxView{_width_policy(){return\"horizontal\"==this.model.orientation?super._width_policy():\"fixed\"}_height_policy(){return\"horizontal\"==this.model.orientation?\"fixed\":super._height_policy()}box_sizing(){const i=super.box_sizing();return\"horizontal\"==this.model.orientation?null==i.width&&(i.width=this.model.default_size):null==i.height&&(i.height=this.model.default_size),i}}t.WidgetView=_,_.__name__=\"WidgetView\";class s extends n.HTMLBox{constructor(i){super(i)}static init_Widget(){this.define({orientation:[r.Orientation,\"horizontal\"],default_size:[r.Number,300]}),this.override({margin:[5,5,5,5]})}}t.Widget=s,s.__name__=\"Widget\",s.init_Widget()},\n", - " 407: function _(e,t,c){Object.defineProperty(c,\"__esModule\",{value:!0});const s=e(81),n=e(78);class o extends n.DOMView{}c.AbstractIconView=o,o.__name__=\"AbstractIconView\";class _ extends s.Model{constructor(e){super(e)}}c.AbstractIcon=_,_.__name__=\"AbstractIcon\"},\n", - " 408: function _(e,t,n){Object.defineProperty(n,\"__esModule\",{value:!0});const i=e(1),s=e(409),h=e(72),_=i.__importStar(e(18)),o=e(10),u=e(173),r=e(282),c=i.__importDefault(e(284));class l extends s.TextInputView{constructor(){super(...arguments),this._open=!1,this._last_value=\"\",this._hover_index=0}styles(){return[...super.styles(),c.default]}render(){super.render(),this.input_el.addEventListener(\"keydown\",e=>this._keydown(e)),this.input_el.addEventListener(\"keyup\",e=>this._keyup(e)),this.menu=h.div({class:[r.bk_menu,u.bk_below]}),this.menu.addEventListener(\"click\",e=>this._menu_click(e)),this.menu.addEventListener(\"mouseover\",e=>this._menu_hover(e)),this.el.appendChild(this.menu),h.undisplay(this.menu)}change_input(){this._open&&this.menu.children.length>0&&(this.model.value=this.menu.children[this._hover_index].textContent,this.input_el.focus(),this._hide_menu())}_update_completions(e){h.empty(this.menu);for(const t of e){const e=h.div({},t);this.menu.appendChild(e)}e.length>0&&this.menu.children[0].classList.add(u.bk_active)}_show_menu(){if(!this._open){this._open=!0,this._hover_index=0,this._last_value=this.model.value,h.display(this.menu);const e=t=>{const{target:n}=t;n instanceof HTMLElement&&!this.el.contains(n)&&(document.removeEventListener(\"click\",e),this._hide_menu())};document.addEventListener(\"click\",e)}}_hide_menu(){this._open&&(this._open=!1,h.undisplay(this.menu))}_menu_click(e){e.target!=e.currentTarget&&e.target instanceof Element&&(this.model.value=e.target.textContent,this.input_el.focus(),this._hide_menu())}_menu_hover(e){if(e.target!=e.currentTarget&&e.target instanceof Element){let t=0;for(t=0;t0&&(this.menu.children[this._hover_index].classList.remove(u.bk_active),this._hover_index=o.clamp(e,0,t-1),this.menu.children[this._hover_index].classList.add(u.bk_active))}_keydown(e){}_keyup(e){switch(e.keyCode){case h.Keys.Enter:this.change_input();break;case h.Keys.Esc:this._hide_menu();break;case h.Keys.Up:this._bump_hover(this._hover_index-1);break;case h.Keys.Down:this._bump_hover(this._hover_index+1);break;default:{const e=this.input_el.value;if(e.lengthe:e=>e.toLowerCase();for(const n of this.model.completions)i(n).startsWith(i(e))&&t.push(n);this._update_completions(t),0==t.length?this._hide_menu():this._show_menu()}}}}n.AutocompleteInputView=l,l.__name__=\"AutocompleteInputView\";class a extends s.TextInput{constructor(e){super(e)}static init_AutocompleteInput(){this.prototype.default_view=l,this.define({completions:[_.Array,[]],min_characters:[_.Int,2],case_sensitive:[_.Boolean,!0]})}}n.AutocompleteInput=a,a.__name__=\"AutocompleteInput\",a.init_AutocompleteInput()},\n", - " 409: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=e(1),s=e(410),l=e(72),p=n.__importStar(e(18)),u=e(412);class a extends s.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,()=>this.input_el.name=this.model.name||\"\"),this.connect(this.model.properties.value.change,()=>this.input_el.value=this.model.value),this.connect(this.model.properties.value_input.change,()=>this.input_el.value=this.model.value_input),this.connect(this.model.properties.disabled.change,()=>this.input_el.disabled=this.model.disabled),this.connect(this.model.properties.placeholder.change,()=>this.input_el.placeholder=this.model.placeholder)}render(){super.render(),this.input_el=l.input({type:\"text\",class:u.bk_input,name:this.model.name,value:this.model.value,disabled:this.model.disabled,placeholder:this.model.placeholder}),this.input_el.addEventListener(\"change\",()=>this.change_input()),this.input_el.addEventListener(\"input\",()=>this.change_input_oninput()),this.group_el.appendChild(this.input_el)}change_input(){this.model.value=this.input_el.value,super.change_input()}change_input_oninput(){this.model.value_input=this.input_el.value,super.change_input()}}i.TextInputView=a,a.__name__=\"TextInputView\";class h extends s.InputWidget{constructor(e){super(e)}static init_TextInput(){this.prototype.default_view=a,this.define({value:[p.String,\"\"],value_input:[p.String,\"\"],placeholder:[p.String,\"\"]})}}i.TextInput=h,h.__name__=\"TextInput\",h.init_TextInput()},\n", - " 410: function _(t,e,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=t(1),l=t(405),s=t(72),_=n.__importStar(t(18)),o=n.__importDefault(t(411)),r=t(412);class p extends l.ControlView{*controls(){yield this.input_el}connect_signals(){super.connect_signals(),this.connect(this.model.properties.title.change,()=>{this.label_el.textContent=this.model.title})}styles(){return[...super.styles(),o.default]}render(){super.render();const{title:t}=this.model;this.label_el=s.label({style:{display:0==t.length?\"none\":\"\"}},t),this.group_el=s.div({class:r.bk_input_group},this.label_el),this.el.appendChild(this.group_el)}change_input(){}}i.InputWidgetView=p,p.__name__=\"InputWidgetView\";class u extends l.Control{constructor(t){super(t)}static init_InputWidget(){this.define({title:[_.String,\"\"]})}}i.InputWidget=u,u.__name__=\"InputWidget\",u.init_InputWidget()},\n", - " 411: function _(n,o,t){Object.defineProperty(t,\"__esModule\",{value:!0});t.default='\\n.bk-root .bk-input {\\n display: inline-block;\\n width: 100%;\\n flex-grow: 1;\\n -webkit-flex-grow: 1;\\n min-height: 31px;\\n padding: 0 12px;\\n background-color: #fff;\\n border: 1px solid #ccc;\\n border-radius: 4px;\\n}\\n.bk-root .bk-input:focus {\\n border-color: #66afe9;\\n outline: 0;\\n box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 8px rgba(102, 175, 233, 0.6);\\n}\\n.bk-root .bk-input::placeholder,\\n.bk-root .bk-input:-ms-input-placeholder,\\n.bk-root .bk-input::-moz-placeholder,\\n.bk-root .bk-input::-webkit-input-placeholder {\\n color: #999;\\n opacity: 1;\\n}\\n.bk-root .bk-input[disabled] {\\n cursor: not-allowed;\\n background-color: #eee;\\n opacity: 1;\\n}\\n.bk-root select:not([multiple]).bk-input,\\n.bk-root select:not([size]).bk-input {\\n height: auto;\\n appearance: none;\\n -webkit-appearance: none;\\n background-image: url(\\'data:image/svg+xml;utf8,\\');\\n background-position: right 0.5em center;\\n background-size: 8px 6px;\\n background-repeat: no-repeat;\\n}\\n.bk-root select[multiple].bk-input,\\n.bk-root select[size].bk-input,\\n.bk-root textarea.bk-input {\\n height: auto;\\n}\\n.bk-root .bk-input-group {\\n width: 100%;\\n height: 100%;\\n display: inline-flex;\\n display: -webkit-inline-flex;\\n flex-wrap: nowrap;\\n -webkit-flex-wrap: nowrap;\\n align-items: start;\\n -webkit-align-items: start;\\n flex-direction: column;\\n -webkit-flex-direction: column;\\n white-space: nowrap;\\n}\\n.bk-root .bk-input-group.bk-inline {\\n flex-direction: row;\\n -webkit-flex-direction: row;\\n}\\n.bk-root .bk-input-group.bk-inline > *:not(:first-child) {\\n margin-left: 5px;\\n}\\n.bk-root .bk-input-group input[type=\"checkbox\"] + span,\\n.bk-root .bk-input-group input[type=\"radio\"] + span {\\n position: relative;\\n top: -2px;\\n margin-left: 3px;\\n}\\n.bk-root .bk-input-group > .bk-spin-wrapper {\\n display: inherit;\\n width: inherit;\\n height: inherit;\\n position: relative;\\n overflow: hidden;\\n padding: 0;\\n vertical-align: middle;\\n}\\n.bk-root .bk-input-group > .bk-spin-wrapper input {\\n padding-right: 20px;\\n}\\n.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn {\\n position: absolute;\\n display: block;\\n height: 50%;\\n min-height: 0;\\n min-width: 0;\\n width: 30px;\\n padding: 0;\\n margin: 0;\\n right: 0;\\n border: none;\\n background: none;\\n cursor: pointer;\\n}\\n.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn:before {\\n content: \"\";\\n display: inline-block;\\n transform: translateY(-50%);\\n border-left: 5px solid transparent;\\n border-right: 5px solid transparent;\\n}\\n.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up {\\n top: 0;\\n}\\n.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up:before {\\n border-bottom: 5px solid black;\\n}\\n.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up:disabled:before {\\n border-bottom-color: grey;\\n}\\n.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down {\\n bottom: 0;\\n}\\n.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down:before {\\n border-top: 5px solid black;\\n}\\n.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down:disabled:before {\\n border-top-color: grey;\\n}\\n'},\n", - " 412: function _(u,e,n){Object.defineProperty(n,\"__esModule\",{value:!0}),n.bk_input=\"bk-input\",n.bk_input_group=\"bk-input-group\"},\n", - " 413: function _(t,e,n){Object.defineProperty(n,\"__esModule\",{value:!0});const o=t(404),i=t(313);class s extends o.AbstractButtonView{click(){this.model.trigger_event(new i.ButtonClick),super.click()}}n.ButtonView=s,s.__name__=\"ButtonView\";class u extends o.AbstractButton{constructor(t){super(t)}static init_Button(){this.prototype.default_view=s,this.override({label:\"Button\"})}}n.Button=u,u.__name__=\"Button\",u.init_Button()},\n", - " 414: function _(t,e,o){Object.defineProperty(o,\"__esModule\",{value:!0});const i=t(1),c=t(415),s=t(72),n=i.__importStar(t(18)),a=t(173);class u extends c.ButtonGroupView{get active(){return new Set(this.model.active)}change_active(t){const{active:e}=this;e.has(t)?e.delete(t):e.add(t),this.model.active=[...e].sort()}_update_active(){const{active:t}=this;this._buttons.forEach((e,o)=>{s.classes(e).toggle(a.bk_active,t.has(o))})}}o.CheckboxButtonGroupView=u,u.__name__=\"CheckboxButtonGroupView\";class r extends c.ButtonGroup{constructor(t){super(t)}static init_CheckboxButtonGroup(){this.prototype.default_view=u,this.define({active:[n.Array,[]]})}}o.CheckboxButtonGroup=r,r.__name__=\"CheckboxButtonGroup\",r.init_CheckboxButtonGroup()},\n", - " 415: function _(t,e,s){Object.defineProperty(s,\"__esModule\",{value:!0});const n=t(1),o=t(405),i=t(72),r=n.__importStar(t(18)),_=t(281),u=n.__importDefault(t(283));class a extends o.ControlView{*controls(){yield*this._buttons}connect_signals(){super.connect_signals();const t=this.model.properties;this.on_change(t.button_type,()=>this.render()),this.on_change(t.labels,()=>this.render()),this.on_change(t.active,()=>this._update_active())}styles(){return[...super.styles(),u.default]}render(){super.render(),this._buttons=this.model.labels.map((t,e)=>{const s=i.div({class:[_.bk_btn,_.bk_btn_type(this.model.button_type)],disabled:this.model.disabled},t);return s.addEventListener(\"click\",()=>this.change_active(e)),s}),this._update_active();const t=i.div({class:_.bk_btn_group},this._buttons);this.el.appendChild(t)}}s.ButtonGroupView=a,a.__name__=\"ButtonGroupView\";class l extends o.Control{constructor(t){super(t)}static init_ButtonGroup(){this.define({labels:[r.Array,[]],button_type:[r.ButtonType,\"default\"]})}}s.ButtonGroup=l,l.__name__=\"ButtonGroup\",l.init_ButtonGroup()},\n", - " 416: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=e(1),s=e(417),o=e(72),c=e(9),a=n.__importStar(e(18)),l=e(173),d=e(412);class r extends s.InputGroupView{render(){super.render();const e=o.div({class:[d.bk_input_group,this.model.inline?l.bk_inline:null]});this.el.appendChild(e);const{active:t,labels:i}=this.model;this._inputs=[];for(let n=0;nthis.change_active(n)),this._inputs.push(s),this.model.disabled&&(s.disabled=!0),c.includes(t,n)&&(s.checked=!0);const a=o.label({},s,o.span({},i[n]));e.appendChild(a)}}change_active(e){const t=new Set(this.model.active);t.has(e)?t.delete(e):t.add(e),this.model.active=[...t].sort()}}i.CheckboxGroupView=r,r.__name__=\"CheckboxGroupView\";class p extends s.InputGroup{constructor(e){super(e)}static init_CheckboxGroup(){this.prototype.default_view=r,this.define({active:[a.Array,[]],labels:[a.Array,[]],inline:[a.Boolean,!1]})}}i.CheckboxGroup=p,p.__name__=\"CheckboxGroup\",p.init_CheckboxGroup()},\n", - " 417: function _(e,t,n){Object.defineProperty(n,\"__esModule\",{value:!0});const s=e(1),o=e(405),r=s.__importDefault(e(411));class u extends o.ControlView{*controls(){yield*this._inputs}connect_signals(){super.connect_signals(),this.connect(this.model.change,()=>this.render())}styles(){return[...super.styles(),r.default]}}n.InputGroupView=u,u.__name__=\"InputGroupView\";class _ extends o.Control{constructor(e){super(e)}}n.InputGroup=_,_.__name__=\"InputGroup\"},\n", - " 418: function _(e,i,t){Object.defineProperty(t,\"__esModule\",{value:!0});const n=e(1),o=e(410),s=e(72),l=n.__importStar(e(18)),r=e(412);class c extends o.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,()=>this.input_el.name=this.model.name||\"\"),this.connect(this.model.properties.color.change,()=>this.input_el.value=this.model.color),this.connect(this.model.properties.disabled.change,()=>this.input_el.disabled=this.model.disabled)}render(){super.render(),this.input_el=s.input({type:\"color\",class:r.bk_input,name:this.model.name,value:this.model.color,disabled:this.model.disabled}),this.input_el.addEventListener(\"change\",()=>this.change_input()),this.group_el.appendChild(this.input_el)}change_input(){this.model.color=this.input_el.value,super.change_input()}}t.ColorPickerView=c,c.__name__=\"ColorPickerView\";class d extends o.InputWidget{constructor(e){super(e)}static init_ColorPicker(){this.prototype.default_view=c,this.define({color:[l.Color,\"#000000\"]})}}t.ColorPicker=d,d.__name__=\"ColorPicker\",d.init_ColorPicker()},\n", - " 419: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=e(1),s=n.__importDefault(e(420)),a=e(410),l=e(72),o=n.__importStar(e(18)),r=e(8),d=e(412),c=n.__importDefault(e(421));function u(e){const t=[];for(const i of e)if(r.isString(i))t.push(i);else{const[e,n]=i;t.push({from:e,to:n})}return t}class _ extends a.InputWidgetView{connect_signals(){super.connect_signals();const{value:e,min_date:t,max_date:i,disabled_dates:n,enabled_dates:s,position:a,inline:l}=this.model.properties;this.connect(e.change,()=>{var t;return null===(t=this._picker)||void 0===t?void 0:t.setDate(e.value())}),this.connect(t.change,()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"minDate\",t.value())}),this.connect(i.change,()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"maxDate\",i.value())}),this.connect(n.change,()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"disable\",n.value())}),this.connect(s.change,()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"enable\",s.value())}),this.connect(a.change,()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"position\",a.value())}),this.connect(l.change,()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"inline\",l.value())})}remove(){var e;null===(e=this._picker)||void 0===e||e.destroy(),super.remove()}styles(){return[...super.styles(),c.default]}render(){null==this._picker&&(super.render(),this.input_el=l.input({type:\"text\",class:d.bk_input,disabled:this.model.disabled}),this.group_el.appendChild(this.input_el),this._picker=s.default(this.input_el,{defaultDate:this.model.value,minDate:this.model.min_date,maxDate:this.model.max_date,inline:this.model.inline,position:this.model.position,disable:u(this.model.disabled_dates),enable:u(this.model.enabled_dates),onChange:(e,t,i)=>this._on_change(e,t,i)}))}_on_change(e,t,i){this.model.value=t,this.change_input()}}i.DatePickerView=_,_.__name__=\"DatePickerView\";class h extends a.InputWidget{constructor(e){super(e)}static init_DatePicker(){this.prototype.default_view=_,this.define({value:[o.Any],min_date:[o.Any],max_date:[o.Any],disabled_dates:[o.Any,[]],enabled_dates:[o.Any,[]],position:[o.CalendarPosition,\"auto\"],inline:[o.Boolean,!1]})}}i.DatePicker=h,h.__name__=\"DatePicker\",h.init_DatePicker()},\n", - " 420: function _(e,t,n){\n", - " /* flatpickr v4.6.3, @license MIT */var a,i;a=this,i=function(){\"use strict\";\n", - " /*! *****************************************************************************\n", - " Copyright (c) Microsoft Corporation. All rights reserved.\n", - " Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use\n", - " this file except in compliance with the License. You may obtain a copy of the\n", - " License at http://www.apache.org/licenses/LICENSE-2.0\n", - " \n", - " THIS CODE IS PROVIDED ON AN *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\n", - " KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED\n", - " WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,\n", - " MERCHANTABLITY OR NON-INFRINGEMENT.\n", - " \n", - " See the Apache Version 2.0 License for specific language governing permissions\n", - " and limitations under the License.\n", - " ***************************************************************************** */var e=function(){return(e=Object.assign||function(e){for(var t,n=1,a=arguments.length;n\",noCalendar:!1,now:new Date,onChange:[],onClose:[],onDayCreate:[],onDestroy:[],onKeyDown:[],onMonthChange:[],onOpen:[],onParseConfig:[],onReady:[],onValueUpdate:[],onYearChange:[],onPreCalendarPosition:[],plugins:[],position:\"auto\",positionElement:void 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Date(t)},d:function(e,t){e.setDate(parseFloat(t))},h:function(e,t){e.setHours(parseFloat(t))},i:function(e,t){e.setMinutes(parseFloat(t))},j:function(e,t){e.setDate(parseFloat(t))},l:f,m:function(e,t){e.setMonth(parseFloat(t)-1)},n:function(e,t){e.setMonth(parseFloat(t)-1)},s:function(e,t){e.setSeconds(parseFloat(t))},u:function(e,t){return new Date(parseFloat(t))},w:f,y:function(e,t){e.setFullYear(2e3+parseFloat(t))}},p={D:\"(\\\\w+)\",F:\"(\\\\w+)\",G:\"(\\\\d\\\\d|\\\\d)\",H:\"(\\\\d\\\\d|\\\\d)\",J:\"(\\\\d\\\\d|\\\\d)\\\\w+\",K:\"\",M:\"(\\\\w+)\",S:\"(\\\\d\\\\d|\\\\d)\",U:\"(.+)\",W:\"(\\\\d\\\\d|\\\\d)\",Y:\"(\\\\d{4})\",Z:\"(.+)\",d:\"(\\\\d\\\\d|\\\\d)\",h:\"(\\\\d\\\\d|\\\\d)\",i:\"(\\\\d\\\\d|\\\\d)\",j:\"(\\\\d\\\\d|\\\\d)\",l:\"(\\\\w+)\",m:\"(\\\\d\\\\d|\\\\d)\",n:\"(\\\\d\\\\d|\\\\d)\",s:\"(\\\\d\\\\d|\\\\d)\",u:\"(.+)\",w:\"(\\\\d\\\\d|\\\\d)\",y:\"(\\\\d{2})\"},h={Z:function(e){return e.toISOString()},D:function(e,t,n){return 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K(){s(h.monthNav),h.monthNav.appendChild(h.prevMonthNav),h.config.showMonths&&(h.yearElements=[],h.monthElements=[]);for(var e=h.config.showMonths;e--;){var t=J();h.yearElements.push(t.yearElement),h.monthElements.push(t.monthElement),h.monthNav.appendChild(t.container)}h.monthNav.appendChild(h.nextMonthNav)}function U(){h.weekdayContainer?s(h.weekdayContainer):h.weekdayContainer=d(\"div\",\"flatpickr-weekdays\");for(var e=h.config.showMonths;e--;){var t=d(\"div\",\"flatpickr-weekdaycontainer\");h.weekdayContainer.appendChild(t)}return q(),h.weekdayContainer}function q(){if(h.weekdayContainer){var e=h.l10n.firstDayOfWeek,t=h.l10n.weekdays.shorthand.slice();e>0&&e\\n \"+t.join(\"\")+\"\\n \\n \"}}function $(e,t){void 0===t&&(t=!0);var n=t?e:e-h.currentMonth;n<0&&!0===h._hidePrevMonthArrow||n>0&&!0===h._hideNextMonthArrow||(h.currentMonth+=n,(h.currentMonth<0||h.currentMonth>11)&&(h.currentYear+=h.currentMonth>11?1:-1,h.currentMonth=(h.currentMonth+12)%12,fe(\"onYearChange\"),B()),R(),fe(\"onMonthChange\"),pe())}function z(e){return!(!h.config.appendTo||!h.config.appendTo.contains(e))||h.calendarContainer.contains(e)}function G(e){if(h.isOpen&&!h.config.inline){var t=\"function\"==typeof(r=e).composedPath?r.composedPath()[0]:r.target,n=z(t),a=t===h.input||t===h.altInput||h.element.contains(t)||e.path&&e.path.indexOf&&(~e.path.indexOf(h.input)||~e.path.indexOf(h.altInput)),i=\"blur\"===e.type?a&&e.relatedTarget&&!z(e.relatedTarget):!a&&!n&&!z(e.relatedTarget),o=!h.config.ignoredFocusElements.some((function(e){return e.contains(t)}));i&&o&&(void 0!==h.timeContainer&&void 0!==h.minuteElement&&void 0!==h.hourElement&&x(),h.close(),\"range\"===h.config.mode&&1===h.selectedDates.length&&(h.clear(!1),h.redraw()))}var 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0!==h.daysContainer&&-1===e.className.indexOf(\"hidden\")&&h.daysContainer.contains(e)}function X(e){var t=e.target===h._input,n=h.config.allowInput,a=h.isOpen&&(!n||!t),i=h.config.inline&&t&&!n;if(13===e.keyCode&&t){if(n)return h.setDate(h._input.value,!0,e.target===h.altInput?h.config.altFormat:h.config.dateFormat),e.target.blur();h.open()}else if(z(e.target)||a||i){var o=!!h.timeContainer&&h.timeContainer.contains(e.target);switch(e.keyCode){case 13:o?(e.preventDefault(),x(),le()):ce(e);break;case 27:e.preventDefault(),le();break;case 8:case 46:t&&!h.config.allowInput&&(e.preventDefault(),h.clear());break;case 37:case 39:if(o||t)h.hourElement&&h.hourElement.focus();else if(e.preventDefault(),void 0!==h.daysContainer&&(!1===n||document.activeElement&&Q(document.activeElement))){var r=39===e.keyCode?1:-1;e.ctrlKey?(e.stopPropagation(),$(r),L(H(1),0)):L(void 0,r)}break;case 38:case 40:e.preventDefault();var l=40===e.keyCode?1:-1;h.daysContainer&&void 0!==e.target.$i||e.target===h.input||e.target===h.altInput?e.ctrlKey?(e.stopPropagation(),V(h.currentYear-l),L(H(1),0)):o||L(void 0,7*l):e.target===h.currentYearElement?V(h.currentYear-l):h.config.enableTime&&(!o&&h.hourElement&&h.hourElement.focus(),x(e),h._debouncedChange());break;case 9:if(o){var c=[h.hourElement,h.minuteElement,h.secondElement,h.amPM].concat(h.pluginElements).filter((function(e){return e})),d=c.indexOf(e.target);if(-1!==d){var s=c[d+(e.shiftKey?-1:1)];e.preventDefault(),(s||h._input).focus()}}else!h.config.noCalendar&&h.daysContainer&&h.daysContainer.contains(e.target)&&e.shiftKey&&(e.preventDefault(),h._input.focus())}}if(void 0!==h.amPM&&e.target===h.amPM)switch(e.key){case h.l10n.amPM[0].charAt(0):case h.l10n.amPM[0].charAt(0).toLowerCase():h.amPM.textContent=h.l10n.amPM[0],E(),ve();break;case h.l10n.amPM[1].charAt(0):case h.l10n.amPM[1].charAt(0).toLowerCase():h.amPM.textContent=h.l10n.amPM[1],E(),ve()}(t||z(e.target))&&fe(\"onKeyDown\",e)}function ee(e){if(1===h.selectedDates.length&&(!e||e.classList.contains(\"flatpickr-day\")&&!e.classList.contains(\"flatpickr-disabled\"))){for(var t=e?e.dateObj.getTime():h.days.firstElementChild.dateObj.getTime(),n=h.parseDate(h.selectedDates[0],void 0,!0).getTime(),a=Math.min(t,h.selectedDates[0].getTime()),i=Math.max(t,h.selectedDates[0].getTime()),o=!1,r=0,l=0,c=a;ca&&cr)?r=c:c>n&&(!l||c0&&m0&&m>l;return g?(f.classList.add(\"notAllowed\"),[\"inRange\",\"startRange\",\"endRange\"].forEach((function(e){f.classList.remove(e)})),\"continue\"):o&&!g?\"continue\":([\"startRange\",\"inRange\",\"endRange\",\"notAllowed\"].forEach((function(e){f.classList.remove(e)})),void(void 0!==e&&(e.classList.add(t<=h.selectedDates[0].getTime()?\"startRange\":\"endRange\"),nt&&m===n&&f.classList.add(\"endRange\"),m>=r&&(0===l||m<=l)&&(d=n,u=t,(c=m)>Math.min(d,u)&&c0||n.getMinutes()>0||n.getSeconds()>0),h.selectedDates&&(h.selectedDates=h.selectedDates.filter((function(e){return Z(e)})),h.selectedDates.length||\"min\"!==e||T(n),ve()),h.daysContainer&&(re(),void 0!==n?h.currentYearElement[e]=n.getFullYear().toString():h.currentYearElement.removeAttribute(e),h.currentYearElement.disabled=!!a&&void 0!==n&&a.getFullYear()===n.getFullYear())}}function ie(){\"object\"!=typeof h.config.locale&&void 0===y.l10ns[h.config.locale]&&h.config.errorHandler(new Error(\"flatpickr: invalid locale \"+h.config.locale)),h.l10n=e({},y.l10ns.default,\"object\"==typeof h.config.locale?h.config.locale:\"default\"!==h.config.locale?y.l10ns[h.config.locale]:void 0),p.K=\"(\"+h.l10n.amPM[0]+\"|\"+h.l10n.amPM[1]+\"|\"+h.l10n.amPM[0].toLowerCase()+\"|\"+h.l10n.amPM[1].toLowerCase()+\")\",void 0===e({},g,JSON.parse(JSON.stringify(f.dataset||{}))).time_24hr&&void 0===y.defaultConfig.time_24hr&&(h.config.time_24hr=h.l10n.time_24hr),h.formatDate=v(h),h.parseDate=D({config:h.config,l10n:h.l10n})}function oe(e){if(void 0!==h.calendarContainer){fe(\"onPreCalendarPosition\");var t=e||h._positionElement,n=Array.prototype.reduce.call(h.calendarContainer.children,(function(e,t){return e+t.offsetHeight}),0),a=h.calendarContainer.offsetWidth,i=h.config.position.split(\" \"),o=i[0],r=i.length>1?i[1]:null,l=t.getBoundingClientRect(),d=window.innerHeight-l.bottom,s=\"above\"===o||\"below\"!==o&&dn,u=window.pageYOffset+l.top+(s?-n-2:t.offsetHeight+2);if(c(h.calendarContainer,\"arrowTop\",!s),c(h.calendarContainer,\"arrowBottom\",s),!h.config.inline){var f=window.pageXOffset+l.left-(null!=r&&\"center\"===r?(a-l.width)/2:0),m=window.document.body.offsetWidth-(window.pageXOffset+l.right),g=f+a>window.document.body.offsetWidth,p=m+a>window.document.body.offsetWidth;if(c(h.calendarContainer,\"rightMost\",g),!h.config.static)if(h.calendarContainer.style.top=u+\"px\",g)if(p){var v=document.styleSheets[0];if(void 0===v)return;var D=window.document.body.offsetWidth,w=Math.max(0,D/2-a/2),b=v.cssRules.length,C=\"{left:\"+l.left+\"px;right:auto;}\";c(h.calendarContainer,\"rightMost\",!1),c(h.calendarContainer,\"centerMost\",!0),v.insertRule(\".flatpickr-calendar.centerMost:before,.flatpickr-calendar.centerMost:after\"+C,b),h.calendarContainer.style.left=w+\"px\",h.calendarContainer.style.right=\"auto\"}else h.calendarContainer.style.left=\"auto\",h.calendarContainer.style.right=m+\"px\";else h.calendarContainer.style.left=f+\"px\",h.calendarContainer.style.right=\"auto\"}}}function re(){h.config.noCalendar||h.isMobile||(pe(),R())}function le(){h._input.focus(),-1!==window.navigator.userAgent.indexOf(\"MSIE\")||void 0!==navigator.msMaxTouchPoints?setTimeout(h.close,0):h.close()}function ce(e){e.preventDefault(),e.stopPropagation();var t=function e(t,n){return n(t)?t:t.parentNode?e(t.parentNode,n):void 0}(e.target,(function(e){return e.classList&&e.classList.contains(\"flatpickr-day\")&&!e.classList.contains(\"flatpickr-disabled\")&&!e.classList.contains(\"notAllowed\")}));if(void 0!==t){var n=t,a=h.latestSelectedDateObj=new Date(n.dateObj.getTime()),i=(a.getMonth()h.currentMonth+h.config.showMonths-1)&&\"range\"!==h.config.mode;if(h.selectedDateElem=n,\"single\"===h.config.mode)h.selectedDates=[a];else if(\"multiple\"===h.config.mode){var o=ge(a);o?h.selectedDates.splice(parseInt(o),1):h.selectedDates.push(a)}else\"range\"===h.config.mode&&(2===h.selectedDates.length&&h.clear(!1,!1),h.latestSelectedDateObj=a,h.selectedDates.push(a),0!==w(a,h.selectedDates[0],!0)&&h.selectedDates.sort((function(e,t){return e.getTime()-t.getTime()})));if(E(),i){var r=h.currentYear!==a.getFullYear();h.currentYear=a.getFullYear(),h.currentMonth=a.getMonth(),r&&(fe(\"onYearChange\"),B()),fe(\"onMonthChange\")}if(pe(),R(),ve(),h.config.enableTime&&setTimeout((function(){return h.showTimeInput=!0}),50),i||\"range\"===h.config.mode||1!==h.config.showMonths?void 0!==h.selectedDateElem&&void 0===h.hourElement&&h.selectedDateElem&&h.selectedDateElem.focus():j(n),void 0!==h.hourElement&&void 0!==h.hourElement&&h.hourElement.focus(),h.config.closeOnSelect){var l=\"single\"===h.config.mode&&!h.config.enableTime,c=\"range\"===h.config.mode&&2===h.selectedDates.length&&!h.config.enableTime;(l||c)&&le()}F()}}h.parseDate=D({config:h.config,l10n:h.l10n}),h._handlers=[],h.pluginElements=[],h.loadedPlugins=[],h._bind=O,h._setHoursFromDate=T,h._positionCalendar=oe,h.changeMonth=$,h.changeYear=V,h.clear=function(e,t){void 0===e&&(e=!0),void 0===t&&(t=!0),h.input.value=\"\",void 0!==h.altInput&&(h.altInput.value=\"\"),void 0!==h.mobileInput&&(h.mobileInput.value=\"\"),h.selectedDates=[],h.latestSelectedDateObj=void 0,!0===t&&(h.currentYear=h._initialDate.getFullYear(),h.currentMonth=h._initialDate.getMonth()),h.showTimeInput=!1,!0===h.config.enableTime&&k(),h.redraw(),e&&fe(\"onChange\")},h.close=function(){h.isOpen=!1,h.isMobile||(void 0!==h.calendarContainer&&h.calendarContainer.classList.remove(\"open\"),void 0!==h._input&&h._input.classList.remove(\"active\")),fe(\"onClose\")},h._createElement=d,h.destroy=function(){void 0!==h.config&&fe(\"onDestroy\");for(var e=h._handlers.length;e--;){var t=h._handlers[e];t.element.removeEventListener(t.event,t.handler,t.options)}if(h._handlers=[],h.mobileInput)h.mobileInput.parentNode&&h.mobileInput.parentNode.removeChild(h.mobileInput),h.mobileInput=void 0;else if(h.calendarContainer&&h.calendarContainer.parentNode)if(h.config.static&&h.calendarContainer.parentNode){var n=h.calendarContainer.parentNode;if(n.lastChild&&n.removeChild(n.lastChild),n.parentNode){for(;n.firstChild;)n.parentNode.insertBefore(n.firstChild,n);n.parentNode.removeChild(n)}}else h.calendarContainer.parentNode.removeChild(h.calendarContainer);h.altInput&&(h.input.type=\"text\",h.altInput.parentNode&&h.altInput.parentNode.removeChild(h.altInput),delete h.altInput),h.input&&(h.input.type=h.input._type,h.input.classList.remove(\"flatpickr-input\"),h.input.removeAttribute(\"readonly\"),h.input.value=\"\"),[\"_showTimeInput\",\"latestSelectedDateObj\",\"_hideNextMonthArrow\",\"_hidePrevMonthArrow\",\"__hideNextMonthArrow\",\"__hidePrevMonthArrow\",\"isMobile\",\"isOpen\",\"selectedDateElem\",\"minDateHasTime\",\"maxDateHasTime\",\"days\",\"daysContainer\",\"_input\",\"_positionElement\",\"innerContainer\",\"rContainer\",\"monthNav\",\"todayDateElem\",\"calendarContainer\",\"weekdayContainer\",\"prevMonthNav\",\"nextMonthNav\",\"monthsDropdownContainer\",\"currentMonthElement\",\"currentYearElement\",\"navigationCurrentMonth\",\"selectedDateElem\",\"config\"].forEach((function(e){try{delete h[e]}catch(e){}}))},h.isEnabled=Z,h.jumpToDate=N,h.open=function(e,t){if(void 0===t&&(t=h._positionElement),!0===h.isMobile)return e&&(e.preventDefault(),e.target&&e.target.blur()),void 0!==h.mobileInput&&(h.mobileInput.focus(),h.mobileInput.click()),void fe(\"onOpen\");if(!h._input.disabled&&!h.config.inline){var n=h.isOpen;h.isOpen=!0,n||(h.calendarContainer.classList.add(\"open\"),h._input.classList.add(\"active\"),fe(\"onOpen\"),oe(t)),!0===h.config.enableTime&&!0===h.config.noCalendar&&(0===h.selectedDates.length&&ne(),!1!==h.config.allowInput||void 0!==e&&h.timeContainer.contains(e.relatedTarget)||setTimeout((function(){return h.hourElement.select()}),50))}},h.redraw=re,h.set=function(e,n){if(null!==e&&\"object\"==typeof e)for(var a in Object.assign(h.config,e),e)void 0!==de[a]&&de[a].forEach((function(e){return e()}));else h.config[e]=n,void 0!==de[e]?de[e].forEach((function(e){return e()})):t.indexOf(e)>-1&&(h.config[e]=l(n));h.redraw(),ve(!1)},h.setDate=function(e,t,n){if(void 0===t&&(t=!1),void 0===n&&(n=h.config.dateFormat),0!==e&&!e||e instanceof 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Date&&Z(e,!1)})),\"range\"===h.config.mode&&h.selectedDates.sort((function(e,t){return e.getTime()-t.getTime()}))}function ue(e){return e.slice().map((function(e){return\"string\"==typeof e||\"number\"==typeof e||e instanceof Date?h.parseDate(e,void 0,!0):e&&\"object\"==typeof e&&e.from&&e.to?{from:h.parseDate(e.from,void 0),to:h.parseDate(e.to,void 0)}:e})).filter((function(e){return e}))}function fe(e,t){if(void 0!==h.config){var n=h.config[e];if(void 0!==n&&n.length>0)for(var a=0;n[a]&&a1||\"static\"===h.config.monthSelectorType?h.monthElements[t].textContent=m(n.getMonth(),h.config.shorthandCurrentMonth,h.l10n)+\" \":h.monthsDropdownContainer.value=n.getMonth().toString(),e.value=n.getFullYear().toString()})),h._hidePrevMonthArrow=void 0!==h.config.minDate&&(h.currentYear===h.config.minDate.getFullYear()?h.currentMonth<=h.config.minDate.getMonth():h.currentYearh.config.maxDate.getMonth():h.currentYear>h.config.maxDate.getFullYear()))}function he(e){return h.selectedDates.map((function(t){return h.formatDate(t,e)})).filter((function(e,t,n){return\"range\"!==h.config.mode||h.config.enableTime||n.indexOf(e)===t})).join(\"range\"!==h.config.mode?h.config.conjunction:h.l10n.rangeSeparator)}function ve(e){void 0===e&&(e=!0),void 0!==h.mobileInput&&h.mobileFormatStr&&(h.mobileInput.value=void 0!==h.latestSelectedDateObj?h.formatDate(h.latestSelectedDateObj,h.mobileFormatStr):\"\"),h.input.value=he(h.config.dateFormat),void 0!==h.altInput&&(h.altInput.value=he(h.config.altFormat)),!1!==e&&fe(\"onValueUpdate\")}function De(e){var t=h.prevMonthNav.contains(e.target),n=h.nextMonthNav.contains(e.target);t||n?$(t?-1:1):h.yearElements.indexOf(e.target)>=0?e.target.select():e.target.classList.contains(\"arrowUp\")?h.changeYear(h.currentYear+1):e.target.classList.contains(\"arrowDown\")&&h.changeYear(h.currentYear-1)}return function(){h.element=h.input=f,h.isOpen=!1,function(){var a=[\"wrap\",\"weekNumbers\",\"allowInput\",\"clickOpens\",\"time_24hr\",\"enableTime\",\"noCalendar\",\"altInput\",\"shorthandCurrentMonth\",\"inline\",\"static\",\"enableSeconds\",\"disableMobile\"],i=e({},g,JSON.parse(JSON.stringify(f.dataset||{}))),o={};h.config.parseDate=i.parseDate,h.config.formatDate=i.formatDate,Object.defineProperty(h.config,\"enable\",{get:function(){return h.config._enable},set:function(e){h.config._enable=ue(e)}}),Object.defineProperty(h.config,\"disable\",{get:function(){return h.config._disable},set:function(e){h.config._disable=ue(e)}});var r=\"time\"===i.mode;if(!i.dateFormat&&(i.enableTime||r)){var c=y.defaultConfig.dateFormat||n.dateFormat;o.dateFormat=i.noCalendar||r?\"H:i\"+(i.enableSeconds?\":S\":\"\"):c+\" H:i\"+(i.enableSeconds?\":S\":\"\")}if(i.altInput&&(i.enableTime||r)&&!i.altFormat){var d=y.defaultConfig.altFormat||n.altFormat;o.altFormat=i.noCalendar||r?\"h:i\"+(i.enableSeconds?\":S K\":\" K\"):d+\" h:i\"+(i.enableSeconds?\":S\":\"\")+\" K\"}i.altInputClass||(h.config.altInputClass=h.input.className+\" \"+h.config.altInputClass),Object.defineProperty(h.config,\"minDate\",{get:function(){return h.config._minDate},set:ae(\"min\")}),Object.defineProperty(h.config,\"maxDate\",{get:function(){return h.config._maxDate},set:ae(\"max\")});var s=function(e){return function(t){h.config[\"min\"===e?\"_minTime\":\"_maxTime\"]=h.parseDate(t,\"H:i:S\")}};Object.defineProperty(h.config,\"minTime\",{get:function(){return h.config._minTime},set:s(\"min\")}),Object.defineProperty(h.config,\"maxTime\",{get:function(){return h.config._maxTime},set:s(\"max\")}),\"time\"===i.mode&&(h.config.noCalendar=!0,h.config.enableTime=!0),Object.assign(h.config,o,i);for(var u=0;u-1?h.config[p]=l(m[p]).map(C).concat(h.config[p]):void 0===i[p]&&(h.config[p]=m[p])}fe(\"onParseConfig\")}(),ie(),h.input=h.config.wrap?f.querySelector(\"[data-input]\"):f,h.input?(h.input._type=h.input.type,h.input.type=\"text\",h.input.classList.add(\"flatpickr-input\"),h._input=h.input,h.config.altInput&&(h.altInput=d(h.input.nodeName,h.config.altInputClass),h._input=h.altInput,h.altInput.placeholder=h.input.placeholder,h.altInput.disabled=h.input.disabled,h.altInput.required=h.input.required,h.altInput.tabIndex=h.input.tabIndex,h.altInput.type=\"text\",h.input.setAttribute(\"type\",\"hidden\"),!h.config.static&&h.input.parentNode&&h.input.parentNode.insertBefore(h.altInput,h.input.nextSibling)),h.config.allowInput||h._input.setAttribute(\"readonly\",\"readonly\"),h._positionElement=h.config.positionElement||h._input):h.config.errorHandler(new Error(\"Invalid input element specified\")),function(){h.selectedDates=[],h.now=h.parseDate(h.config.now)||new Date;var e=h.config.defaultDate||(\"INPUT\"!==h.input.nodeName&&\"TEXTAREA\"!==h.input.nodeName||!h.input.placeholder||h.input.value!==h.input.placeholder?h.input.value:null);e&&se(e,h.config.dateFormat),h._initialDate=h.selectedDates.length>0?h.selectedDates[0]:h.config.minDate&&h.config.minDate.getTime()>h.now.getTime()?h.config.minDate:h.config.maxDate&&h.config.maxDate.getTime()0&&(h.latestSelectedDateObj=h.selectedDates[0]),void 0!==h.config.minTime&&(h.config.minTime=h.parseDate(h.config.minTime,\"H:i\")),void 0!==h.config.maxTime&&(h.config.maxTime=h.parseDate(h.config.maxTime,\"H:i\")),h.minDateHasTime=!!h.config.minDate&&(h.config.minDate.getHours()>0||h.config.minDate.getMinutes()>0||h.config.minDate.getSeconds()>0),h.maxDateHasTime=!!h.config.maxDate&&(h.config.maxDate.getHours()>0||h.config.maxDate.getMinutes()>0||h.config.maxDate.getSeconds()>0),Object.defineProperty(h,\"showTimeInput\",{get:function(){return h._showTimeInput},set:function(e){h._showTimeInput=e,h.calendarContainer&&c(h.calendarContainer,\"showTimeInput\",e),h.isOpen&&oe()}})}(),h.utils={getDaysInMonth:function(e,t){return void 0===e&&(e=h.currentMonth),void 0===t&&(t=h.currentYear),1===e&&(t%4==0&&t%100!=0||t%400==0)?29:h.l10n.daysInMonth[e]}},h.isMobile||function(){var e=window.document.createDocumentFragment();if(h.calendarContainer=d(\"div\",\"flatpickr-calendar\"),h.calendarContainer.tabIndex=-1,!h.config.noCalendar){if(e.appendChild((h.monthNav=d(\"div\",\"flatpickr-months\"),h.yearElements=[],h.monthElements=[],h.prevMonthNav=d(\"span\",\"flatpickr-prev-month\"),h.prevMonthNav.innerHTML=h.config.prevArrow,h.nextMonthNav=d(\"span\",\"flatpickr-next-month\"),h.nextMonthNav.innerHTML=h.config.nextArrow,K(),Object.defineProperty(h,\"_hidePrevMonthArrow\",{get:function(){return 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-5px;\\n}\\n.bk-root .noUi-vertical .noUi-handle {\\n width: 18px;\\n height: 14px;\\n right: -5px;\\n top: -7px;\\n}\\n.bk-root .noUi-target.noUi-horizontal {\\n margin: 5px 0px;\\n}\\n.bk-root .noUi-target.noUi-vertical {\\n margin: 0px 5px;\\n}\\n\"},\n", - " 427: function _(e,n,t){Object.defineProperty(t,\"__esModule\",{value:!0});t.default=\"\\n.bk-root .bk-slider-title {\\n white-space: nowrap;\\n}\\n.bk-root .bk-slider-value {\\n font-weight: 600;\\n}\\n\"},\n", - " 428: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const r=e(1).__importDefault(e(186)),a=e(423);class d extends a.AbstractSliderView{}i.DateSliderView=d,d.__name__=\"DateSliderView\";class s extends a.AbstractSlider{constructor(e){super(e),this.behaviour=\"tap\",this.connected=[!0,!1]}static init_DateSlider(){this.prototype.default_view=d,this.override({format:\"%d %b %Y\"})}_formatter(e,t){return r.default(e,t)}}i.DateSlider=s,s.__name__=\"DateSlider\",s.init_DateSlider()},\n", - " 429: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const r=e(1),_=e(430),n=r.__importStar(e(18));class s extends _.MarkupView{render(){super.render(),this.model.render_as_text?this.markup_el.textContent=this.model.text:this.markup_el.innerHTML=this.model.text}}i.DivView=s,s.__name__=\"DivView\";class a extends _.Markup{constructor(e){super(e)}static init_Div(){this.prototype.default_view=s,this.define({render_as_text:[n.Boolean,!1]})}}i.Div=a,a.__name__=\"Div\",a.init_Div()},\n", - " 430: function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const i=e(1),a=e(217),n=e(72),l=i.__importStar(e(18)),r=e(472),_=e(431),c=i.__importDefault(e(432));class u extends r.WidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.change,()=>{this.layout.invalidate_cache(),this.render(),this.root.compute_layout()})}styles(){return[...super.styles(),c.default]}_update_layout(){this.layout=new a.CachedVariadicBox(this.el),this.layout.set_sizing(this.box_sizing())}render(){super.render();const e=Object.assign(Object.assign({},this.model.style),{display:\"inline-block\"});this.markup_el=n.div({class:_.bk_clearfix,style:e}),this.el.appendChild(this.markup_el)}}s.MarkupView=u,u.__name__=\"MarkupView\";class o extends r.Widget{constructor(e){super(e)}static init_Markup(){this.define({text:[l.String,\"\"],style:[l.Any,{}]})}}s.Markup=o,o.__name__=\"Markup\",o.init_Markup()},\n", - " 431: function _(e,c,f){Object.defineProperty(f,\"__esModule\",{value:!0}),f.bk_clearfix=\"bk-clearfix\"},\n", - " 432: function _(e,n,t){Object.defineProperty(t,\"__esModule\",{value:!0});t.default='\\n.bk-root .bk-clearfix:before,\\n.bk-root .bk-clearfix:after {\\n content: \"\";\\n display: table;\\n}\\n.bk-root .bk-clearfix:after {\\n clear: both;\\n}\\n'},\n", - " 433: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=e(1),s=e(404),o=e(313),_=e(72),d=n.__importStar(e(18)),l=e(8),r=e(173),u=e(281),c=e(282),h=n.__importDefault(e(284));class p extends s.AbstractButtonView{constructor(){super(...arguments),this._open=!1}styles(){return[...super.styles(),h.default]}render(){super.render();const e=_.div({class:[c.bk_caret,r.bk_down]});if(this.model.is_split){const t=this._render_button(e);t.classList.add(u.bk_dropdown_toggle),t.addEventListener(\"click\",()=>this._toggle_menu()),this.group_el.appendChild(t)}else this.button_el.appendChild(e);const t=this.model.menu.map((e,t)=>{if(null==e)return _.div({class:c.bk_divider});{const i=l.isString(e)?e:e[0],n=_.div({},i);return n.addEventListener(\"click\",()=>this._item_click(t)),n}});this.menu=_.div({class:[c.bk_menu,r.bk_below]},t),this.el.appendChild(this.menu),_.undisplay(this.menu)}_show_menu(){if(!this._open){this._open=!0,_.display(this.menu);const e=t=>{const{target:i}=t;i instanceof HTMLElement&&!this.el.contains(i)&&(document.removeEventListener(\"click\",e),this._hide_menu())};document.addEventListener(\"click\",e)}}_hide_menu(){this._open&&(this._open=!1,_.undisplay(this.menu))}_toggle_menu(){this._open?this._hide_menu():this._show_menu()}click(){this.model.is_split?(this._hide_menu(),this.model.trigger_event(new o.ButtonClick),super.click()):this._toggle_menu()}_item_click(e){this._hide_menu();const t=this.model.menu[e];if(null!=t){const i=l.isString(t)?t:t[1];l.isString(i)?this.model.trigger_event(new o.MenuItemClick(i)):i.execute(this.model,{index:e})}}}i.DropdownView=p,p.__name__=\"DropdownView\";class m extends s.AbstractButton{constructor(e){super(e)}static init_Dropdown(){this.prototype.default_view=p,this.define({split:[d.Boolean,!1],menu:[d.Array,[]]}),this.override({label:\"Dropdown\"})}get is_split(){return this.split}}i.Dropdown=m,m.__name__=\"Dropdown\",m.init_Dropdown()},\n", - " 434: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const l=e(1).__importStar(e(18)),s=e(472);class n extends s.WidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.change,()=>this.render()),this.connect(this.model.properties.width.change,()=>this.render())}render(){null==this.dialogEl&&(this.dialogEl=document.createElement(\"input\"),this.dialogEl.type=\"file\",this.dialogEl.multiple=this.model.multiple,this.dialogEl.onchange=()=>{const{files:e}=this.dialogEl;null!=e&&this.load_files(e)},this.el.appendChild(this.dialogEl)),null!=this.model.accept&&\"\"!=this.model.accept&&(this.dialogEl.accept=this.model.accept),this.dialogEl.style.width=\"{this.model.width}px\",this.dialogEl.disabled=this.model.disabled}async load_files(e){const t=[],i=[],l=[];let s;for(s=0;s{const l=new FileReader;l.onload=()=>{var s;const{result:n}=l;null!=n?t(n):i(null!==(s=l.error)&&void 0!==s?s:new Error(`unable to read 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c.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.value.change,()=>this.render_selection()),this.connect(this.model.properties.options.change,()=>this.render()),this.connect(this.model.properties.name.change,()=>this.render()),this.connect(this.model.properties.title.change,()=>this.render()),this.connect(this.model.properties.size.change,()=>this.render()),this.connect(this.model.properties.disabled.change,()=>this.render())}render(){super.render();const e=this.model.options.map(e=>{let t,s;return l.isString(e)?t=s=e:[t,s]=e,n.option({value:t},s)});this.select_el=n.select({multiple:!0,class:r.bk_input,name:this.model.name,disabled:this.model.disabled},e),this.select_el.addEventListener(\"change\",()=>this.change_input()),this.group_el.appendChild(this.select_el),this.render_selection()}render_selection(){const e=new Set(this.model.value);for(const t of this.el.querySelectorAll(\"option\"))t.selected=e.has(t.value);this.select_el.size=this.model.size}change_input(){const e=null!=this.el.querySelector(\"select:focus\"),t=[];for(const e of this.el.querySelectorAll(\"option\"))e.selected&&t.push(e.value);this.model.value=t,super.change_input(),e&&this.select_el.focus()}}s.MultiSelectView=h,h.__name__=\"MultiSelectView\";class d extends c.InputWidget{constructor(e){super(e)}static init_MultiSelect(){this.prototype.default_view=h,this.define({value:[o.Array,[]],options:[o.Array,[]],size:[o.Number,4]})}}s.MultiSelect=d,d.__name__=\"MultiSelect\",d.init_MultiSelect()},\n", - " 436: function _(a,e,r){Object.defineProperty(r,\"__esModule\",{value:!0});const t=a(430),p=a(72);class s extends t.MarkupView{render(){super.render();const a=p.p({style:{margin:0}},this.model.text);this.markup_el.appendChild(a)}}r.ParagraphView=s,s.__name__=\"ParagraphView\";class i extends t.Markup{constructor(a){super(a)}static init_Paragraph(){this.prototype.default_view=s}}r.Paragraph=i,i.__name__=\"Paragraph\",i.init_Paragraph()},\n", - " 437: function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});const n=e(409);class r extends n.TextInputView{render(){super.render(),this.input_el.type=\"password\"}}s.PasswordInputView=r,r.__name__=\"PasswordInputView\";class p extends n.TextInput{constructor(e){super(e)}static init_PasswordInput(){this.prototype.default_view=r}}s.PasswordInput=p,p.__name__=\"PasswordInput\",p.init_PasswordInput()},\n", - " 438: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const l=e(1),s=l.__importDefault(e(439)),o=e(72),n=e(8),h=e(217),a=l.__importStar(e(18)),c=e(412),u=l.__importDefault(e(440)),d=e(410);class _ extends 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n=(e-i)/t,s=n>1?n:1;this.element.scrollTop=e-s},t._animateScroll=function(e,t){var i=this,n=this.element.scrollTop,s=!1;t>0?(this._scrollDown(n,4,e),ne&&(s=!0)),s&&requestAnimationFrame((function(){i._animateScroll(e,t)}))},e}();function le(e,t){for(var i=0;i0?\"treeitem\":\"option\"),Object.assign(g.dataset,{choice:\"\",id:l,value:h,selectText:i}),m?(g.classList.add(a),g.dataset.choiceDisabled=\"\",g.setAttribute(\"aria-disabled\",\"true\")):(g.classList.add(r),g.dataset.choiceSelectable=\"\"),g},input:function(e,t){var i=e.input,n=e.inputCloned,s=Object.assign(document.createElement(\"input\"),{type:\"text\",className:i+\" \"+n,autocomplete:\"off\",autocapitalize:\"off\",spellcheck:!1});return s.setAttribute(\"role\",\"textbox\"),s.setAttribute(\"aria-autocomplete\",\"list\"),s.setAttribute(\"aria-label\",t),s},dropdown:function(e){var t=e.list,i=e.listDropdown,n=document.createElement(\"div\");return n.classList.add(t,i),n.setAttribute(\"aria-expanded\",\"false\"),n},notice:function(e,t,i){var n=e.item,s=e.itemChoice,r=e.noResults,o=e.noChoices;void 0===i&&(i=\"\");var a=[n,s];return\"no-choices\"===i?a.push(o):\"no-results\"===i&&a.push(r),Object.assign(document.createElement(\"div\"),{innerHTML:t,className:a.join(\" \")})},option:function(e){var t=e.label,i=e.value,n=e.customProperties,s=e.active,r=e.disabled,o=new Option(t,i,!1,s);return n&&(o.dataset.customProperties=n),o.disabled=r,o}},ve=function(e){return void 0===e&&(e=!0),{type:q,active:e}},ge=function(e,t){return{type:$,id:e,highlighted:t}},_e=function(e){var t=e.value,i=e.id,n=e.active,s=e.disabled;return{type:z,value:t,id:i,active:n,disabled:s}},be=function(e){return{type:\"SET_IS_LOADING\",isLoading:e}};function ye(e,t){for(var i=0;i=0?this._store.getGroupById(s):null;return this._store.dispatch(ge(i,!0)),t&&this.passedElement.triggerEvent(H,{id:i,value:o,label:c,groupValue:l&&l.value?l.value:null}),this},r.unhighlightItem=function(e){if(!e)return this;var t=e.id,i=e.groupId,n=void 0===i?-1:i,s=e.value,r=void 0===s?\"\":s,o=e.label,a=void 0===o?\"\":o,c=n>=0?this._store.getGroupById(n):null;return this._store.dispatch(ge(t,!1)),this.passedElement.triggerEvent(H,{id:t,value:r,label:a,groupValue:c&&c.value?c.value:null}),this},r.highlightAll=function(){var e=this;return this._store.items.forEach((function(t){return e.highlightItem(t)})),this},r.unhighlightAll=function(){var e=this;return this._store.items.forEach((function(t){return e.unhighlightItem(t)})),this},r.removeActiveItemsByValue=function(e){var t=this;return this._store.activeItems.filter((function(t){return t.value===e})).forEach((function(e){return t._removeItem(e)})),this},r.removeActiveItems=function(e){var t=this;return this._store.activeItems.filter((function(t){return t.id!==e})).forEach((function(e){return t._removeItem(e)})),this},r.removeHighlightedItems=function(e){var t=this;return void 0===e&&(e=!1),this._store.highlightedActiveItems.forEach((function(i){t._removeItem(i),e&&t._triggerChange(i.value)})),this},r.showDropdown=function(e){var t=this;return this.dropdown.isActive||requestAnimationFrame((function(){t.dropdown.show(),t.containerOuter.open(t.dropdown.distanceFromTopWindow),!e&&t._canSearch&&t.input.focus(),t.passedElement.triggerEvent(D,{})})),this},r.hideDropdown=function(e){var t=this;return this.dropdown.isActive?(requestAnimationFrame((function(){t.dropdown.hide(),t.containerOuter.close(),!e&&t._canSearch&&(t.input.removeActiveDescendant(),t.input.blur()),t.passedElement.triggerEvent(M,{})})),this):this},r.getValue=function(e){void 0===e&&(e=!1);var t=this._store.activeItems.reduce((function(t,i){var n=e?i.value:i;return t.push(n),t}),[]);return this._isSelectOneElement?t[0]:t},r.setValue=function(e){var t=this;return this.initialised?(e.forEach((function(e){return t._setChoiceOrItem(e)})),this):this},r.setChoiceByValue=function(e){var t=this;return!this.initialised||this._isTextElement||(Array.isArray(e)?e:[e]).forEach((function(e){return t._findAndSelectChoiceByValue(e)})),this},r.setChoices=function(e,t,i,n){var s=this;if(void 0===e&&(e=[]),void 0===t&&(t=\"value\"),void 0===i&&(i=\"label\"),void 0===n&&(n=!1),!this.initialised)throw new ReferenceError(\"setChoices was called on a non-initialized instance of Choices\");if(!this._isSelectElement)throw new TypeError(\"setChoices can't be used with INPUT based Choices\");if(\"string\"!=typeof t||!t)throw new TypeError(\"value parameter must be a name of 'value' field in passed objects\");if(n&&this.clearChoices(),\"function\"==typeof e){var r=e(this);if(\"function\"==typeof Promise&&r instanceof Promise)return new Promise((function(e){return requestAnimationFrame(e)})).then((function(){return s._handleLoadingState(!0)})).then((function(){return r})).then((function(e){return s.setChoices(e,t,i,n)})).catch((function(e){s.config.silent||console.error(e)})).then((function(){return s._handleLoadingState(!1)})).then((function(){return s}));if(!Array.isArray(r))throw new TypeError(\".setChoices first argument function must return either array of choices or Promise, got: \"+typeof r);return this.setChoices(r,t,i,!1)}if(!Array.isArray(e))throw new TypeError(\".setChoices must be called either with array of choices with a function resulting into Promise of array of choices\");return this.containerOuter.removeLoadingState(),this._startLoading(),e.forEach((function(e){e.choices?s._addGroup({id:parseInt(e.id,10)||null,group:e,valueKey:t,labelKey:i}):s._addChoice({value:e[t],label:e[i],isSelected:e.selected,isDisabled:e.disabled,customProperties:e.customProperties,placeholder:e.placeholder})})),this._stopLoading(),this},r.clearChoices=function(){return this._store.dispatch({type:U}),this},r.clearStore=function(){return this._store.dispatch({type:\"CLEAR_ALL\"}),this},r.clearInput=function(){var e=!this._isSelectOneElement;return this.input.clear(e),!this._isTextElement&&this._canSearch&&(this._isSearching=!1,this._store.dispatch(ve(!0))),this},r._render=function(){if(!this._store.isLoading()){this._currentState=this._store.state;var e=this._currentState.choices!==this._prevState.choices||this._currentState.groups!==this._prevState.groups||this._currentState.items!==this._prevState.items,t=this._isSelectElement,i=this._currentState.items!==this._prevState.items;e&&(t&&this._renderChoices(),i&&this._renderItems(),this._prevState=this._currentState)}},r._renderChoices=function(){var e=this,t=this._store,i=t.activeGroups,n=t.activeChoices,s=document.createDocumentFragment();if(this.choiceList.clear(),this.config.resetScrollPosition&&requestAnimationFrame((function(){return e.choiceList.scrollToTop()})),i.length>=1&&!this._isSearching){var r=n.filter((function(e){return!0===e.placeholder&&-1===e.groupId}));r.length>=1&&(s=this._createChoicesFragment(r,s)),s=this._createGroupsFragment(i,n,s)}else n.length>=1&&(s=this._createChoicesFragment(n,s));if(s.childNodes&&s.childNodes.length>0){var o=this._store.activeItems,a=this._canAddItem(o,this.input.value);a.response?(this.choiceList.append(s),this._highlightChoice()):this.choiceList.append(this._getTemplate(\"notice\",a.notice))}else{var c,l;this._isSearching?(l=\"function\"==typeof this.config.noResultsText?this.config.noResultsText():this.config.noResultsText,c=this._getTemplate(\"notice\",l,\"no-results\")):(l=\"function\"==typeof this.config.noChoicesText?this.config.noChoicesText():this.config.noChoicesText,c=this._getTemplate(\"notice\",l,\"no-choices\")),this.choiceList.append(c)}},r._renderItems=function(){var e=this._store.activeItems||[];this.itemList.clear();var t=this._createItemsFragment(e);t.childNodes&&this.itemList.append(t)},r._createGroupsFragment=function(e,t,i){var n=this;return void 0===i&&(i=document.createDocumentFragment()),this.config.shouldSort&&e.sort(this.config.sorter),e.forEach((function(e){var s=function(e){return t.filter((function(t){return n._isSelectOneElement?t.groupId===e.id:t.groupId===e.id&&(\"always\"===n.config.renderSelectedChoices||!t.selected)}))}(e);if(s.length>=1){var r=n._getTemplate(\"choiceGroup\",e);i.appendChild(r),n._createChoicesFragment(s,i,!0)}})),i},r._createChoicesFragment=function(e,t,i){var n=this;void 0===t&&(t=document.createDocumentFragment()),void 0===i&&(i=!1);var s=this.config,r=s.renderSelectedChoices,o=s.searchResultLimit,a=s.renderChoiceLimit,c=this._isSearching?w:this.config.sorter,l=function(e){if(\"auto\"!==r||n._isSelectOneElement||!e.selected){var i=n._getTemplate(\"choice\",e,n.config.itemSelectText);t.appendChild(i)}},h=e;\"auto\"!==r||this._isSelectOneElement||(h=e.filter((function(e){return!e.selected})));var u=h.reduce((function(e,t){return t.placeholder?e.placeholderChoices.push(t):e.normalChoices.push(t),e}),{placeholderChoices:[],normalChoices:[]}),d=u.placeholderChoices,p=u.normalChoices;(this.config.shouldSort||this._isSearching)&&p.sort(c);var m=h.length,f=this._isSelectOneElement?[].concat(d,p):p;this._isSearching?m=o:a&&a>0&&!i&&(m=a);for(var v=0;v=n){var o=s?this._searchChoices(e):0;this.passedElement.triggerEvent(j,{value:e,resultCount:o})}else r&&(this._isSearching=!1,this._store.dispatch(ve(!0)))}},r._canAddItem=function(e,t){var i=!0,n=\"function\"==typeof this.config.addItemText?this.config.addItemText(t):this.config.addItemText;if(!this._isSelectOneElement){var s=function(e,t,i){return void 0===i&&(i=\"value\"),e.some((function(e){return\"string\"==typeof t?e[i]===t.trim():e[i]===t}))}(e,t);this.config.maxItemCount>0&&this.config.maxItemCount<=e.length&&(i=!1,n=\"function\"==typeof this.config.maxItemText?this.config.maxItemText(this.config.maxItemCount):this.config.maxItemText),!this.config.duplicateItemsAllowed&&s&&i&&(i=!1,n=\"function\"==typeof this.config.uniqueItemText?this.config.uniqueItemText(t):this.config.uniqueItemText),this._isTextElement&&this.config.addItems&&i&&\"function\"==typeof this.config.addItemFilter&&!this.config.addItemFilter(t)&&(i=!1,n=\"function\"==typeof this.config.customAddItemText?this.config.customAddItemText(t):this.config.customAddItemText)}return{response:i,notice:n}},r._searchChoices=function(e){var t=\"string\"==typeof e?e.trim():e,i=\"string\"==typeof this._currentValue?this._currentValue.trim():this._currentValue;if(t.length<1&&t===i+\" \")return 0;var n=this._store.searchableChoices,r=t,o=[].concat(this.config.searchFields),a=Object.assign(this.config.fuseOptions,{keys:o}),c=new s.a(n,a).search(r);return this._currentValue=t,this._highlightPosition=0,this._isSearching=!0,this._store.dispatch(function(e){return{type:G,results:e}}(c)),c.length},r._addEventListeners=function(){var e=document.documentElement;e.addEventListener(\"touchend\",this._onTouchEnd,!0),this.containerOuter.element.addEventListener(\"keydown\",this._onKeyDown,!0),this.containerOuter.element.addEventListener(\"mousedown\",this._onMouseDown,!0),e.addEventListener(\"click\",this._onClick,{passive:!0}),e.addEventListener(\"touchmove\",this._onTouchMove,{passive:!0}),this.dropdown.element.addEventListener(\"mouseover\",this._onMouseOver,{passive:!0}),this._isSelectOneElement&&(this.containerOuter.element.addEventListener(\"focus\",this._onFocus,{passive:!0}),this.containerOuter.element.addEventListener(\"blur\",this._onBlur,{passive:!0})),this.input.element.addEventListener(\"keyup\",this._onKeyUp,{passive:!0}),this.input.element.addEventListener(\"focus\",this._onFocus,{passive:!0}),this.input.element.addEventListener(\"blur\",this._onBlur,{passive:!0}),this.input.element.form&&this.input.element.form.addEventListener(\"reset\",this._onFormReset,{passive:!0}),this.input.addEventListeners()},r._removeEventListeners=function(){var e=document.documentElement;e.removeEventListener(\"touchend\",this._onTouchEnd,!0),this.containerOuter.element.removeEventListener(\"keydown\",this._onKeyDown,!0),this.containerOuter.element.removeEventListener(\"mousedown\",this._onMouseDown,!0),e.removeEventListener(\"click\",this._onClick),e.removeEventListener(\"touchmove\",this._onTouchMove),this.dropdown.element.removeEventListener(\"mouseover\",this._onMouseOver),this._isSelectOneElement&&(this.containerOuter.element.removeEventListener(\"focus\",this._onFocus),this.containerOuter.element.removeEventListener(\"blur\",this._onBlur)),this.input.element.removeEventListener(\"keyup\",this._onKeyUp),this.input.element.removeEventListener(\"focus\",this._onFocus),this.input.element.removeEventListener(\"blur\",this._onBlur),this.input.element.form&&this.input.element.form.removeEventListener(\"reset\",this._onFormReset),this.input.removeEventListeners()},r._onKeyDown=function(e){var t,i=e.target,n=e.keyCode,s=e.ctrlKey,r=e.metaKey,o=this._store.activeItems,a=this.input.isFocussed,c=this.dropdown.isActive,l=this.itemList.hasChildren(),h=String.fromCharCode(n),u=J,d=Y,p=Z,m=Q,f=ee,v=te,g=ie,_=ne,b=se,y=s||r;!this._isTextElement&&/[a-zA-Z0-9-_ ]/.test(h)&&this.showDropdown();var E=((t={})[m]=this._onAKey,t[p]=this._onEnterKey,t[f]=this._onEscapeKey,t[v]=this._onDirectionKey,t[_]=this._onDirectionKey,t[g]=this._onDirectionKey,t[b]=this._onDirectionKey,t[d]=this._onDeleteKey,t[u]=this._onDeleteKey,t);E[n]&&E[n]({event:e,target:i,keyCode:n,metaKey:r,activeItems:o,hasFocusedInput:a,hasActiveDropdown:c,hasItems:l,hasCtrlDownKeyPressed:y})},r._onKeyUp=function(e){var t=e.target,i=e.keyCode,n=this.input.value,s=this._store.activeItems,r=this._canAddItem(s,n),o=J,a=Y;if(this._isTextElement)if(r.notice&&n){var c=this._getTemplate(\"notice\",r.notice);this.dropdown.element.innerHTML=c.outerHTML,this.showDropdown(!0)}else this.hideDropdown(!0);else{var l=(i===o||i===a)&&!t.value,h=!this._isTextElement&&this._isSearching,u=this._canSearch&&r.response;l&&h?(this._isSearching=!1,this._store.dispatch(ve(!0))):u&&this._handleSearch(this.input.value)}this._canSearch=this.config.searchEnabled},r._onAKey=function(e){var t=e.hasItems;e.hasCtrlDownKeyPressed&&t&&(this._canSearch=!1,this.config.removeItems&&!this.input.value&&this.input.element===document.activeElement&&this.highlightAll())},r._onEnterKey=function(e){var t=e.event,i=e.target,n=e.activeItems,s=e.hasActiveDropdown,r=Z,o=i.hasAttribute(\"data-button\");if(this._isTextElement&&i.value){var a=this.input.value;this._canAddItem(n,a).response&&(this.hideDropdown(!0),this._addItem({value:a}),this._triggerChange(a),this.clearInput())}if(o&&(this._handleButtonAction(n,i),t.preventDefault()),s){var c=this.dropdown.getChild(\".\"+this.config.classNames.highlightedState);c&&(n[0]&&(n[0].keyCode=r),this._handleChoiceAction(n,c)),t.preventDefault()}else this._isSelectOneElement&&(this.showDropdown(),t.preventDefault())},r._onEscapeKey=function(e){e.hasActiveDropdown&&(this.hideDropdown(!0),this.containerOuter.focus())},r._onDirectionKey=function(e){var t,i,n,s=e.event,r=e.hasActiveDropdown,o=e.keyCode,a=e.metaKey,c=ie,l=ne,h=se;if(r||this._isSelectOneElement){this.showDropdown(),this._canSearch=!1;var u,d=o===c||o===h?1:-1;if(a||o===h||o===l)u=d>0?this.dropdown.element.querySelector(\"[data-choice-selectable]:last-of-type\"):this.dropdown.element.querySelector(\"[data-choice-selectable]\");else{var p=this.dropdown.element.querySelector(\".\"+this.config.classNames.highlightedState);u=p?function(e,t,i){if(void 0===i&&(i=1),e instanceof Element&&\"string\"==typeof t){for(var n=(i>0?\"next\":\"previous\")+\"ElementSibling\",s=e[n];s;){if(s.matches(t))return s;s=s[n]}return s}}(p,\"[data-choice-selectable]\",d):this.dropdown.element.querySelector(\"[data-choice-selectable]\")}u&&(t=u,i=this.choiceList.element,void 0===(n=d)&&(n=1),t&&(n>0?i.scrollTop+i.offsetHeight>=t.offsetTop+t.offsetHeight:t.offsetTop>=i.scrollTop)||this.choiceList.scrollToChildElement(u,d),this._highlightChoice(u)),s.preventDefault()}},r._onDeleteKey=function(e){var t=e.event,i=e.target,n=e.hasFocusedInput,s=e.activeItems;!n||i.value||this._isSelectOneElement||(this._handleBackspace(s),t.preventDefault())},r._onTouchMove=function(){this._wasTap&&(this._wasTap=!1)},r._onTouchEnd=function(e){var t=(e||e.touches[0]).target;this._wasTap&&this.containerOuter.element.contains(t)&&((t===this.containerOuter.element||t===this.containerInner.element)&&(this._isTextElement?this.input.focus():this._isSelectMultipleElement&&this.showDropdown()),e.stopPropagation()),this._wasTap=!0},r._onMouseDown=function(e){var t=e.target;if(t instanceof HTMLElement){if(Ee&&this.choiceList.element.contains(t)){var i=this.choiceList.element.firstElementChild,n=\"ltr\"===this._direction?e.offsetX>=i.offsetWidth:e.offsetX0&&this.unhighlightAll(),this.containerOuter.removeFocusState(),this.hideDropdown(!0))},r._onFocus=function(e){var t,i=this,n=e.target;this.containerOuter.element.contains(n)&&((t={}).text=function(){n===i.input.element&&i.containerOuter.addFocusState()},t[\"select-one\"]=function(){i.containerOuter.addFocusState(),n===i.input.element&&i.showDropdown(!0)},t[\"select-multiple\"]=function(){n===i.input.element&&(i.showDropdown(!0),i.containerOuter.addFocusState())},t)[this.passedElement.element.type]()},r._onBlur=function(e){var t=this,i=e.target;if(this.containerOuter.element.contains(i)&&!this._isScrollingOnIe){var n,s=this._store.activeItems.some((function(e){return e.highlighted}));((n={}).text=function(){i===t.input.element&&(t.containerOuter.removeFocusState(),s&&t.unhighlightAll(),t.hideDropdown(!0))},n[\"select-one\"]=function(){t.containerOuter.removeFocusState(),(i===t.input.element||i===t.containerOuter.element&&!t._canSearch)&&t.hideDropdown(!0)},n[\"select-multiple\"]=function(){i===t.input.element&&(t.containerOuter.removeFocusState(),t.hideDropdown(!0),s&&t.unhighlightAll())},n)[this.passedElement.element.type]()}else this._isScrollingOnIe=!1,this.input.element.focus()},r._onFormReset=function(){this._store.dispatch({type:\"RESET_TO\",state:this._initialState})},r._highlightChoice=function(e){var t=this;void 0===e&&(e=null);var i=Array.from(this.dropdown.element.querySelectorAll(\"[data-choice-selectable]\"));if(i.length){var n=e;Array.from(this.dropdown.element.querySelectorAll(\".\"+this.config.classNames.highlightedState)).forEach((function(e){e.classList.remove(t.config.classNames.highlightedState),e.setAttribute(\"aria-selected\",\"false\")})),n?this._highlightPosition=i.indexOf(n):(n=i.length>this._highlightPosition?i[this._highlightPosition]:i[i.length-1])||(n=i[0]),n.classList.add(this.config.classNames.highlightedState),n.setAttribute(\"aria-selected\",\"true\"),this.passedElement.triggerEvent(B,{el:n}),this.dropdown.isActive&&(this.input.setActiveDescendant(n.id),this.containerOuter.setActiveDescendant(n.id))}},r._addItem=function(e){var t=e.value,i=e.label,n=void 0===i?null:i,s=e.choiceId,r=void 0===s?-1:s,o=e.groupId,a=void 0===o?-1:o,c=e.customProperties,l=void 0===c?null:c,h=e.placeholder,u=void 0!==h&&h,d=e.keyCode,p=void 0===d?null:d,m=\"string\"==typeof t?t.trim():t,f=p,v=l,g=this._store.items,_=n||m,b=r||-1,y=a>=0?this._store.getGroupById(a):null,E=g?g.length+1:1;return this.config.prependValue&&(m=this.config.prependValue+m.toString()),this.config.appendValue&&(m+=this.config.appendValue.toString()),this._store.dispatch(function(e){var t=e.value,i=e.label,n=e.id,s=e.choiceId,r=e.groupId,o=e.customProperties,a=e.placeholder,c=e.keyCode;return{type:W,value:t,label:i,id:n,choiceId:s,groupId:r,customProperties:o,placeholder:a,keyCode:c}}({value:m,label:_,id:E,choiceId:b,groupId:a,customProperties:l,placeholder:u,keyCode:f})),this._isSelectOneElement&&this.removeActiveItems(E),this.passedElement.triggerEvent(K,{id:E,value:m,label:_,customProperties:v,groupValue:y&&y.value?y.value:void 0,keyCode:f}),this},r._removeItem=function(e){if(!e||!E(\"Object\",e))return this;var t=e.id,i=e.value,n=e.label,s=e.choiceId,r=e.groupId,o=r>=0?this._store.getGroupById(r):null;return this._store.dispatch(function(e,t){return{type:X,id:e,choiceId:t}}(t,s)),o&&o.value?this.passedElement.triggerEvent(R,{id:t,value:i,label:n,groupValue:o.value}):this.passedElement.triggerEvent(R,{id:t,value:i,label:n}),this},r._addChoice=function(e){var t=e.value,i=e.label,n=void 0===i?null:i,s=e.isSelected,r=void 0!==s&&s,o=e.isDisabled,a=void 0!==o&&o,c=e.groupId,l=void 0===c?-1:c,h=e.customProperties,u=void 0===h?null:h,d=e.placeholder,p=void 0!==d&&d,m=e.keyCode,f=void 0===m?null:m;if(null!=t){var v=this._store.choices,g=n||t,_=v?v.length+1:1,b=this._baseId+\"-\"+this._idNames.itemChoice+\"-\"+_;this._store.dispatch(function(e){var t=e.value,i=e.label,n=e.id,s=e.groupId,r=e.disabled,o=e.elementId,a=e.customProperties,c=e.placeholder,l=e.keyCode;return{type:V,value:t,label:i,id:n,groupId:s,disabled:r,elementId:o,customProperties:a,placeholder:c,keyCode:l}}({id:_,groupId:l,elementId:b,value:t,label:g,disabled:a,customProperties:u,placeholder:p,keyCode:f})),r&&this._addItem({value:t,label:g,choiceId:_,customProperties:u,placeholder:p,keyCode:f})}},r._addGroup=function(e){var t=this,i=e.group,n=e.id,s=e.valueKey,r=void 0===s?\"value\":s,o=e.labelKey,a=void 0===o?\"label\":o,c=E(\"Object\",i)?i.choices:Array.from(i.getElementsByTagName(\"OPTION\")),l=n||Math.floor((new Date).valueOf()*Math.random()),h=!!i.disabled&&i.disabled;c?(this._store.dispatch(_e({value:i.label,id:l,active:!0,disabled:h})),c.forEach((function(e){var i=e.disabled||e.parentNode&&e.parentNode.disabled;t._addChoice({value:e[r],label:E(\"Object\",e)?e[a]:e.innerHTML,isSelected:e.selected,isDisabled:i,groupId:l,customProperties:e.customProperties,placeholder:e.placeholder})}))):this._store.dispatch(_e({value:i.label,id:i.id,active:!1,disabled:i.disabled}))},r._getTemplate=function(e){var t;if(!e)return null;for(var i=this.config.classNames,n=arguments.length,s=new Array(n>1?n-1:0),r=1;rthis.input_el.name=this.model.name||\"\"),this.connect(this.model.properties.value.change,()=>{this.input_el.value=this.format_value,this.old_value=this.input_el.value}),this.connect(this.model.properties.low.change,()=>{const{value:e,low:t,high:l}=this.model;null!=t&&null!=l&&h.assert(t<=l,\"Invalid bounds, low must be inferior to high\"),null!=e&&null!=t&&(this.model.value=Math.max(e,t))}),this.connect(this.model.properties.high.change,()=>{const{value:e,low:t,high:l}=this.model;null!=t&&null!=l&&h.assert(l>=t,\"Invalid bounds, high must be superior to low\"),null!=e&&null!=l&&(this.model.value=Math.min(e,l))}),this.connect(this.model.properties.high.change,()=>this.input_el.placeholder=this.model.placeholder),this.connect(this.model.properties.disabled.change,()=>this.input_el.disabled=this.model.disabled),this.connect(this.model.properties.placeholder.change,()=>this.input_el.placeholder=this.model.placeholder)}get format_value(){return null!=this.model.value?this.model.pretty(this.model.value):\"\"}_set_input_filter(e){this.input_el.addEventListener(\"input\",()=>{const{selectionStart:t,selectionEnd:l}=this.input_el;if(e(this.input_el.value))this.old_value=this.input_el.value;else{const e=this.old_value.length-this.input_el.value.length;this.input_el.value=this.old_value,t&&l&&this.input_el.setSelectionRange(t-1,l+e)}})}render(){super.render(),this.input_el=u.input({type:\"text\",class:r.bk_input,name:this.model.name,value:this.format_value,disabled:this.model.disabled,placeholder:this.model.placeholder}),this.old_value=this.format_value,this.set_input_filter(),this.input_el.addEventListener(\"change\",()=>this.change_input()),this.input_el.addEventListener(\"focusout\",()=>this.input_el.value=this.format_value),this.group_el.appendChild(this.input_el)}set_input_filter(){\"int\"==this.model.mode?this._set_input_filter(e=>d.test(e)):\"float\"==this.model.mode&&this._set_input_filter(e=>p.test(e))}bound_value(e){let t=e;const{low:l,high:i}=this.model;return t=null!=l?Math.max(l,t):t,t=null!=i?Math.min(i,t):t,t}get value(){let e=\"\"!==this.input_el.value?Number(this.input_el.value):null;return null!=e&&(e=this.bound_value(e)),e}change_input(){null==this.value?this.model.value=null:Number.isNaN(this.value)||(this.model.value=this.value)}}l.NumericInputView=_,_.__name__=\"NumericInputView\";class m extends s.InputWidget{constructor(e){super(e)}static init_NumericInput(){this.prototype.default_view=_,this.define({value:[o.Number,null],placeholder:[o.String,\"\"],mode:[o.Any,\"int\"],format:[o.Any],low:[o.Number,null],high:[o.Number,null]})}_formatter(e,t){return a.isString(t)?n.format(e,t):t.doFormat([e],{loc:0})[0]}pretty(e){return null!=this.format?this._formatter(e,this.format):\"\"+e}}l.NumericInput=m,m.__name__=\"NumericInput\",m.init_NumericInput()},\n", - " 442: function _(t,_,r){Object.defineProperty(r,\"__esModule\",{value:!0});const e=t(1);e.__exportStar(t(13),r),e.__exportStar(t(9),r),e.__exportStar(t(29),r),e.__exportStar(t(443),r),e.__exportStar(t(8),r),e.__exportStar(t(25),r)},\n", - " 443: function _(e,t,s){Object.defineProperty(s,\"__esModule\",{value:!0});class n{constructor(e){this.seed=e%2147483647,this.seed<=0&&(this.seed+=2147483646)}integer(){return this.seed=48271*this.seed%2147483647,this.seed}float(){return(this.integer()-1)/2147483646}floats(e){const t=new Array(e);for(let s=0;s{n.classes(o).toggle(s.bk_active,t===e)})}}e.RadioButtonGroupView=_,_.__name__=\"RadioButtonGroupView\";class c extends a.ButtonGroup{constructor(t){super(t)}static init_RadioButtonGroup(){this.prototype.default_view=_,this.define({active:[u.Any,null]})}}e.RadioButtonGroup=c,c.__name__=\"RadioButtonGroup\",c.init_RadioButtonGroup()},\n", - " 446: function _(e,i,t){Object.defineProperty(t,\"__esModule\",{value:!0});const n=e(1),a=e(72),s=e(29),o=n.__importStar(e(18)),d=e(417),l=e(173),p=e(412);class r extends d.InputGroupView{render(){super.render();const e=a.div({class:[p.bk_input_group,this.model.inline?l.bk_inline:null]});this.el.appendChild(e);const i=s.uniqueId(),{active:t,labels:n}=this.model;this._inputs=[];for(let s=0;sthis.change_active(s)),this._inputs.push(o),this.model.disabled&&(o.disabled=!0),s==t&&(o.checked=!0);const d=a.label({},o,a.span({},n[s]));e.appendChild(d)}}change_active(e){this.model.active=e}}t.RadioGroupView=r,r.__name__=\"RadioGroupView\";class u extends d.InputGroup{constructor(e){super(e)}static init_RadioGroup(){this.prototype.default_view=r,this.define({active:[o.Number],labels:[o.Array,[]],inline:[o.Boolean,!1]})}}t.RadioGroup=u,u.__name__=\"RadioGroup\",u.init_RadioGroup()},\n", - " 447: function _(e,t,r){Object.defineProperty(r,\"__esModule\",{value:!0});const i=e(1).__importStar(e(188)),a=e(423),n=e(8);class o extends a.AbstractRangeSliderView{}r.RangeSliderView=o,o.__name__=\"RangeSliderView\";class s extends a.AbstractSlider{constructor(e){super(e),this.behaviour=\"drag\",this.connected=[!1,!0,!1]}static init_RangeSlider(){this.prototype.default_view=o,this.override({format:\"0[.]00\"})}_formatter(e,t){return n.isString(t)?i.format(e,t):t.doFormat([e],{loc:0})[0]}}r.RangeSlider=s,s.__name__=\"RangeSlider\",s.init_RangeSlider()},\n", - " 448: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=e(1),s=e(72),l=e(8),o=e(13),p=n.__importStar(e(18)),u=e(410),a=e(412);class _ extends u.InputWidgetView{connect_signals(){super.connect_signals();const{value:e,options:t}=this.model.properties;this.on_change(e,()=>{this._update_value()}),this.on_change(t,()=>{s.empty(this.input_el),s.append(this.input_el,...this.options_el())})}options_el(){function e(e){return e.map(e=>{let t,i;return l.isString(e)?t=i=e:[t,i]=e,s.option({value:t},i)})}const{options:t}=this.model;return l.isArray(t)?e(t):o.entries(t).map(([t,i])=>s.optgroup({label:t},e(i)))}render(){super.render(),this.input_el=s.select({class:a.bk_input,name:this.model.name,disabled:this.model.disabled},this.options_el()),this._update_value(),this.input_el.addEventListener(\"change\",()=>this.change_input()),this.group_el.appendChild(this.input_el)}change_input(){const e=this.input_el.value;this.model.value=e,super.change_input()}_update_value(){const{value:e}=this.model;null!=e&&0!=e.length&&(this.input_el.value=this.model.value)}}i.SelectView=_,_.__name__=\"SelectView\";class h extends u.InputWidget{constructor(e){super(e)}static init_Select(){this.prototype.default_view=_,this.define({value:[p.String,\"\"],options:[p.Any,[]]})}}i.Select=h,h.__name__=\"Select\",h.init_Select()},\n", - " 449: function _(e,t,r){Object.defineProperty(r,\"__esModule\",{value:!0});const i=e(1).__importStar(e(188)),o=e(423),s=e(8);class _ extends o.AbstractSliderView{}r.SliderView=_,_.__name__=\"SliderView\";class a extends o.AbstractSlider{constructor(e){super(e),this.behaviour=\"tap\",this.connected=[!0,!1]}static init_Slider(){this.prototype.default_view=_,this.override({format:\"0[.]00\"})}_formatter(e,t){return s.isString(t)?i.format(e,t):t.doFormat([e],{loc:0})[0]}}r.Slider=a,a.__name__=\"Slider\",a.init_Slider()},\n", - " 450: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const n=e(1),s=e(441),l=n.__importStar(e(18)),r=e(72),{min:o,max:_,floor:a,abs:h}=Math;function u(e){return a(e)!==e?e.toFixed(16).replace(/0+$/,\"\").split(\".\")[1].length:0}class p extends s.NumericInputView{*buttons(){yield this.btn_up_el,yield this.btn_down_el}initialize(){super.initialize(),this._interval=200}connect_signals(){super.connect_signals();const e=this.model.properties;this.on_change(e.disabled,()=>{for(const e of this.buttons())r.toggle_attribute(e,\"disabled\",this.model.disabled)})}render(){super.render(),this.wrapper_el=r.div({class:\"bk-spin-wrapper\"}),this.group_el.replaceChild(this.wrapper_el,this.input_el),this.btn_up_el=r.button({class:\"bk-spin-btn bk-spin-btn-up\"}),this.btn_down_el=r.button({class:\"bk-spin-btn bk-spin-btn-down\"}),this.wrapper_el.appendChild(this.input_el),this.wrapper_el.appendChild(this.btn_up_el),this.wrapper_el.appendChild(this.btn_down_el);for(const e of this.buttons())r.toggle_attribute(e,\"disabled\",this.model.disabled),e.addEventListener(\"mousedown\",e=>this._btn_mouse_down(e)),e.addEventListener(\"mouseup\",()=>this._btn_mouse_up()),e.addEventListener(\"mouseleave\",()=>this._btn_mouse_leave());this.input_el.addEventListener(\"keydown\",e=>this._input_key_down(e)),this.input_el.addEventListener(\"keyup\",()=>this.model.value_throttled=this.model.value),this.input_el.addEventListener(\"wheel\",e=>this._input_mouse_wheel(e)),this.input_el.addEventListener(\"wheel\",function(e,t,i=!1){let n;return function(...s){const l=this,r=i&&void 0===n;void 0!==n&&clearTimeout(n),n=setTimeout((function(){n=void 0,i||e.apply(l,s)}),t),r&&e.apply(l,s)}}(()=>{this.model.value_throttled=this.model.value},this.model.wheel_wait,!1))}get precision(){const{low:e,high:t,step:i}=this.model;return _(...[e,t,i].map(h).reduce((e,t)=>(null!=t&&e.push(t),e),[]).map(u))}_start_incrementation(e){clearInterval(this._interval_handle),this._counter=0;const{step:t}=this.model,i=e=>{if(this._counter+=1,this._counter%5==0){const t=Math.floor(this._counter/5);t<10?(clearInterval(this._interval_handle),this._interval_handle=setInterval(()=>i(e),this._interval/(t+1))):t>=10&&t<=13&&(clearInterval(this._interval_handle),this._interval_handle=setInterval(()=>i(2*e),this._interval/10))}this.increment(e)};this._interval_handle=setInterval(()=>i(e*t),this._interval)}_stop_incrementation(){clearInterval(this._interval_handle),this.model.value_throttled=this.model.value}_btn_mouse_down(e){e.preventDefault();const t=e.currentTarget===this.btn_up_el?1:-1;this.increment(t*this.model.step),this.input_el.focus(),this._start_incrementation(t)}_btn_mouse_up(){this._stop_incrementation()}_btn_mouse_leave(){this._stop_incrementation()}_input_mouse_wheel(e){if(document.activeElement===this.input_el){e.preventDefault();const t=e.deltaY>0?-1:1;this.increment(t*this.model.step)}}_input_key_down(e){switch(e.keyCode){case r.Keys.Up:return e.preventDefault(),this.increment(this.model.step);case r.Keys.Down:return e.preventDefault(),this.increment(-this.model.step);case r.Keys.PageUp:return e.preventDefault(),this.increment(this.model.page_step_multiplier*this.model.step);case r.Keys.PageDown:return e.preventDefault(),this.increment(-this.model.page_step_multiplier*this.model.step)}}adjust_to_precision(e){return this.bound_value(Number(e.toFixed(this.precision)))}increment(e){const{low:t,high:i}=this.model;null==this.model.value?e>0?this.model.value=null!=t?t:null!=i?o(0,i):0:e<0&&(this.model.value=null!=i?i:null!=t?_(t,0):0):this.model.value=this.adjust_to_precision(this.model.value+e)}change_input(){super.change_input(),this.model.value_throttled=this.model.value}}i.SpinnerView=p,p.__name__=\"SpinnerView\";class d extends s.NumericInput{constructor(e){super(e)}static init_Spinner(){this.prototype.default_view=p,this.define({value_throttled:[l.Number,null],step:[l.Number,1],page_step_multiplier:[l.Number,10],wheel_wait:[l.Number,100]}),this.override({mode:\"float\"})}}i.Spinner=d,d.__name__=\"Spinner\",d.init_Spinner()},\n", - " 451: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=e(1),n=e(410),l=e(72),h=s.__importStar(e(18)),o=e(412);class a extends n.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,()=>this.input_el.name=this.model.name||\"\"),this.connect(this.model.properties.value.change,()=>this.input_el.value=this.model.value),this.connect(this.model.properties.disabled.change,()=>this.input_el.disabled=this.model.disabled),this.connect(this.model.properties.placeholder.change,()=>this.input_el.placeholder=this.model.placeholder),this.connect(this.model.properties.rows.change,()=>this.input_el.rows=this.model.rows),this.connect(this.model.properties.cols.change,()=>this.input_el.cols=this.model.cols),this.connect(this.model.properties.max_length.change,()=>this.input_el.maxLength=this.model.max_length)}render(){super.render(),this.input_el=l.textarea({class:o.bk_input,name:this.model.name,disabled:this.model.disabled,placeholder:this.model.placeholder,cols:this.model.cols,rows:this.model.rows,maxLength:this.model.max_length}),this.input_el.textContent=this.model.value,this.input_el.addEventListener(\"change\",()=>this.change_input()),this.group_el.appendChild(this.input_el)}change_input(){this.model.value=this.input_el.value,super.change_input()}}i.TextAreaInputView=a,a.__name__=\"TextAreaInputView\";class p extends n.InputWidget{constructor(e){super(e)}static init_TextAreaInput(){this.prototype.default_view=a,this.define({value:[h.String,\"\"],value_input:[h.String,\"\"],placeholder:[h.String,\"\"],cols:[h.Number,20],rows:[h.Number,2],max_length:[h.Number,500]})}}i.TextAreaInput=p,p.__name__=\"TextAreaInput\",p.init_TextAreaInput()},\n", - " 452: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=e(1),c=e(404),o=e(72),a=s.__importStar(e(18)),n=e(173);class l extends c.AbstractButtonView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,()=>this._update_active())}render(){super.render(),this._update_active()}click(){this.model.active=!this.model.active,super.click()}_update_active(){o.classes(this.button_el).toggle(n.bk_active,this.model.active)}}i.ToggleView=l,l.__name__=\"ToggleView\";class _ extends c.AbstractButton{constructor(e){super(e)}static init_Toggle(){this.prototype.default_view=l,this.define({active:[a.Boolean,!1]}),this.override({label:\"Toggle\"})}}i.Toggle=_,_.__name__=\"Toggle\",_.init_Toggle()},\n", - " }, 402, {\"models/widgets/main\":402,\"models/widgets/index\":403,\"models/widgets/abstract_button\":404,\"models/widgets/control\":405,\"models/widgets/widget\":472,\"models/widgets/abstract_icon\":407,\"models/widgets/autocomplete_input\":408,\"models/widgets/text_input\":409,\"models/widgets/input_widget\":410,\"styles/widgets/inputs.css\":411,\"styles/widgets/inputs\":412,\"models/widgets/button\":413,\"models/widgets/checkbox_button_group\":414,\"models/widgets/button_group\":415,\"models/widgets/checkbox_group\":416,\"models/widgets/input_group\":417,\"models/widgets/color_picker\":418,\"models/widgets/date_picker\":419,\"styles/widgets/flatpickr.css\":421,\"models/widgets/date_range_slider\":422,\"models/widgets/abstract_slider\":423,\"styles/widgets/sliders\":425,\"styles/widgets/nouislider.css\":426,\"styles/widgets/sliders.css\":427,\"models/widgets/date_slider\":428,\"models/widgets/div\":429,\"models/widgets/markup\":430,\"styles/clearfix\":431,\"styles/clearfix.css\":432,\"models/widgets/dropdown\":433,\"models/widgets/file_input\":434,\"models/widgets/multiselect\":435,\"models/widgets/paragraph\":436,\"models/widgets/password_input\":437,\"models/widgets/multichoice\":438,\"styles/widgets/choices.css\":440,\"models/widgets/numeric_input\":441,\"api/linalg\":442,\"core/util/random\":443,\"models/widgets/pretext\":444,\"models/widgets/radio_button_group\":445,\"models/widgets/radio_group\":446,\"models/widgets/range_slider\":447,\"models/widgets/selectbox\":448,\"models/widgets/slider\":449,\"models/widgets/spinner\":450,\"models/widgets/textarea_input\":451,\"models/widgets/toggle\":452}, {});\n", - " })\n", - "\n", - "\n", - " /* END bokeh-widgets.min.js */\n", - " },\n", - " \n", - " function(Bokeh) {\n", - " /* BEGIN bokeh-tables.min.js */\n", - " /*!\n", - " * Copyright (c) 2012 - 2020, Anaconda, Inc., and Bokeh Contributors\n", - " * All rights reserved.\n", - " * \n", - " * Redistribution and use in source and binary forms, with or without modification,\n", - " * are permitted provided that the following conditions are met:\n", - " * \n", - " * Redistributions of source code must retain the above copyright notice,\n", - " * this list of conditions and the following disclaimer.\n", - " * \n", - " * Redistributions in binary form must reproduce the above copyright notice,\n", - " * this list of conditions and the following disclaimer in the documentation\n", - " * and/or other materials provided with the distribution.\n", - " * \n", - " * Neither the name of Anaconda nor the names of any contributors\n", - " * may be used to endorse or promote products derived from this software\n", - " * without specific prior written permission.\n", - " * \n", - " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", - " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", - " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", - " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", - " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", - " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", - " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", - " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", - " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", - " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", - " * THE POSSIBILITY OF SUCH DAMAGE.\n", - " */\n", - " (function(root, factory) {\n", - " factory(root[\"Bokeh\"], \"2.2.3\");\n", - " })(this, function(Bokeh, version) {\n", - " var define;\n", - " return (function(modules, entry, aliases, externals) {\n", - " const bokeh = typeof Bokeh !== \"undefined\" && (version != null ? Bokeh[version] : Bokeh);\n", - " if (bokeh != null) {\n", - " return bokeh.register_plugin(modules, entry, aliases);\n", - " } else {\n", - " throw new Error(\"Cannot find Bokeh \" + version + \". You have to load it prior to loading plugins.\");\n", - " }\n", - " })\n", - " ({\n", - " 453: function _(e,t,o){Object.defineProperty(o,\"__esModule\",{value:!0});const r=e(1).__importStar(e(454));o.Tables=r;e(7).register_models(r)},\n", - " 454: function _(a,g,r){Object.defineProperty(r,\"__esModule\",{value:!0});const e=a(1);e.__exportStar(a(455),r),e.__exportStar(a(475),r);var t=a(456);r.DataTable=t.DataTable;var o=a(474);r.TableColumn=o.TableColumn;var n=a(473);r.TableWidget=n.TableWidget;var u=a(481);r.AvgAggregator=u.AvgAggregator,r.MinAggregator=u.MinAggregator,r.MaxAggregator=u.MaxAggregator,r.SumAggregator=u.SumAggregator;var l=a(482);r.GroupingInfo=l.GroupingInfo,r.DataCube=l.DataCube},\n", - " 455: function _(e,t,i){Object.defineProperty(i,\"__esModule\",{value:!0});const s=e(1).__importStar(e(18)),r=e(72),a=e(78),n=e(81),l=e(456),u=e(478);class d extends a.DOMView{constructor(e){const{model:t,parent:i}=e.column;super(Object.assign({model:t,parent:i},e)),this.args=e,this.initialize(),this.render()}get emptyValue(){return null}initialize(){super.initialize(),this.inputEl=this._createInput(),this.defaultValue=null}async lazy_initialize(){throw new Error(\"unsupported\")}css_classes(){return super.css_classes().concat(u.bk_cell_editor)}render(){super.render(),this.args.container.append(this.el),this.el.appendChild(this.inputEl),this.renderEditor(),this.disableNavigation()}renderEditor(){}disableNavigation(){this.inputEl.addEventListener(\"keydown\",e=>{switch(e.keyCode){case r.Keys.Left:case r.Keys.Right:case r.Keys.Up:case r.Keys.Down:case r.Keys.PageUp:case r.Keys.PageDown:e.stopImmediatePropagation()}})}destroy(){this.remove()}focus(){this.inputEl.focus()}show(){}hide(){}position(){}getValue(){return this.inputEl.value}setValue(e){this.inputEl.value=e}serializeValue(){return this.getValue()}isValueChanged(){return!(\"\"==this.getValue()&&null==this.defaultValue)&&this.getValue()!==this.defaultValue}applyValue(e,t){const i=this.args.grid.getData(),s=i.index.indexOf(e[l.DTINDEX_NAME]);i.setField(s,this.args.column.field,t)}loadValue(e){const t=e[this.args.column.field];this.defaultValue=null!=t?t:this.emptyValue,this.setValue(this.defaultValue)}validateValue(e){if(this.args.column.validator){const t=this.args.column.validator(e);if(!t.valid)return t}return{valid:!0,msg:null}}validate(){return this.validateValue(this.getValue())}}i.CellEditorView=d,d.__name__=\"CellEditorView\";class o extends n.Model{}i.CellEditor=o,o.__name__=\"CellEditor\";class _ extends d{get emptyValue(){return\"\"}_createInput(){return r.input({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}}i.StringEditorView=_,_.__name__=\"StringEditorView\";class c extends o{static init_StringEditor(){this.prototype.default_view=_,this.define({completions:[s.Array,[]]})}}i.StringEditor=c,c.__name__=\"StringEditor\",c.init_StringEditor();class p extends d{_createInput(){return r.textarea()}renderEditor(){this.inputEl.focus(),this.inputEl.select()}}i.TextEditorView=p,p.__name__=\"TextEditorView\";class h extends o{static init_TextEditor(){this.prototype.default_view=p}}i.TextEditor=h,h.__name__=\"TextEditor\",h.init_TextEditor();class E extends d{_createInput(){return r.select()}renderEditor(){for(const e of this.model.options)this.inputEl.appendChild(r.option({value:e},e));this.focus()}}i.SelectEditorView=E,E.__name__=\"SelectEditorView\";class V extends o{static init_SelectEditor(){this.prototype.default_view=E,this.define({options:[s.Array,[]]})}}i.SelectEditor=V,V.__name__=\"SelectEditor\",V.init_SelectEditor();class m extends d{_createInput(){return r.input({type:\"text\"})}}i.PercentEditorView=m,m.__name__=\"PercentEditorView\";class f extends 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s=e(1),o=e(457),n=e(461),l=e(462),r=e(463),d=e(29),a=e(8),h=e(9),u=e(13),c=e(19),_=e(472),m=e(473),g=e(474),p=e(478),f=s.__importDefault(e(479)),b=s.__importDefault(e(480));i.DTINDEX_NAME=\"__bkdt_internal_index__\",i.AutosizeModes={fit_columns:\"FCV\",fit_viewport:\"FVC\",force_fit:\"LFF\",none:\"NOA\"};class w{constructor(e,t){this.init(e,t)}init(e,t){if(i.DTINDEX_NAME in e.data)throw new Error(`special name ${i.DTINDEX_NAME} cannot be used as a data table column`);this.source=e,this.view=t,this.index=[...this.view.indices]}getLength(){return this.index.length}getItem(e){const t={};for(const i of u.keys(this.source.data))t[i]=this.source.data[i][this.index[e]];return t[i.DTINDEX_NAME]=this.index[e],t}getField(e,t){return t==i.DTINDEX_NAME?this.index[e]:this.source.data[t][this.index[e]]}setField(e,t,i){const s=this.index[e];this.source.patch({[t]:[[s,i]]})}getRecords(){return h.range(0,this.getLength()).map(e=>this.getItem(e))}getItems(){return this.getRecords()}slice(e,t,i){return 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