diff --git a/examples/visualization/reference/satn_to_movie.ipynb b/examples/visualization/reference/satn_to_movie.ipynb index ed7cc6769..3544baadd 100644 --- a/examples/visualization/reference/satn_to_movie.ipynb +++ b/examples/visualization/reference/satn_to_movie.ipynb @@ -195218,1495 +195218,381545 @@ "text": [ " \r" ] - } - ], - "source": [ - "mov = ps.visualization.satn_to_movie(im=im, satn=satn, c_under='green')\n", - "image_based_ip_c_under = mov.to_jshtml()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "dc43465f", - "metadata": {}, - "outputs": [], - "source": [ - "HTML(image_based_ip_c_under)" - ] - }, - { - "cell_type": "markdown", - "id": "6edfdfc3", - "metadata": {}, - "source": [ - "## `c_over`" - ] - }, - { - "cell_type": "markdown", - "id": "ff9c2933", - "metadata": {}, - "source": [ - "Colormap to be assigned to the highest color bound (over color) in the color map. The voxeled colored by `c_overer` are the solid phase. The default over color is white." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "fb8cdf9d", - "metadata": { - "execution": { - "iopub.execute_input": "2022-04-25T05:21:37.509070Z", - "iopub.status.busy": "2022-04-25T05:21:37.508915Z", - "iopub.status.idle": "2022-04-25T05:21:59.751378Z", - "shell.execute_reply": "2022-04-25T05:21:59.750706Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "data": { - "image/svg+xml": [ - "\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " 2022-04-25T02:55:10.378412\n", - " image/svg+xml\n", - " \n", - " \n", - " Matplotlib v3.5.1, https://matplotlib.org/\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "\n" - ], - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "mov = ps.visualization.satn_to_movie(im=im, satn=satn, c_over='yellow')\n", - "image_based_ip_c_over = mov.to_jshtml()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8b8b82b7", - "metadata": {}, - "outputs": [], - "source": [ - "HTML(image_based_ip_c_over)" - ] - }, - { - "cell_type": "markdown", - "id": "964039c6", - "metadata": {}, - "source": [ - "## `v_under`" - ] - }, - { - "cell_type": "markdown", - "id": "9565edcb", - "metadata": {}, - "source": [ - "This is the lowest bound of `satn` data range that the colormap covers. By default, the `v_under` is 0.001." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "172fb4c7", - "metadata": { - "execution": { - "iopub.execute_input": "2022-04-25T05:21:59.755286Z", - "iopub.status.busy": "2022-04-25T05:21:59.754684Z", - "iopub.status.idle": "2022-04-25T05:22:22.409071Z", - "shell.execute_reply": "2022-04-25T05:22:22.408410Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \r" - ] }, { "data": { - "image/svg+xml": [ - "\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " 2022-04-25T02:55:33.719540\n", - " image/svg+xml\n", - " \n", - " \n", - " Matplotlib v3.5.1, https://matplotlib.org/\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "\n" - ], + "image/png": "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", "text/plain": [ - "
" + "
" ] }, "metadata": { - "needs_background": "light" + "image/png": { + "height": 464, + "width": 468 + } }, "output_type": "display_data" } ], "source": [ - "mov = ps.visualization.satn_to_movie(im=im, satn=satn, v_under=0.2)\n", - "image_based_ip_v_under = mov.to_jshtml()" + "mov = ps.visualization.satn_to_movie(im=im, satn=satn, c_under='green')\n", + "image_based_ip_c_under = mov.to_jshtml()" ] }, { "cell_type": "code", - "execution_count": null, - "id": "0fc1a26d", - "metadata": {}, - "outputs": [], - "source": [ - "HTML(image_based_ip_v_under)" - ] - }, - { - "cell_type": "markdown", - "id": "7fbdec6c", - "metadata": {}, - "source": [ - "## `v_over`" - ] - }, - { - "cell_type": "markdown", - "id": "96bd8912", + "execution_count": 28, + "id": "dc43465f", "metadata": {}, - "source": [ - "This is the highest bound of `satn` data range that the colormap covers. By default, the `v_over` is 1." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0dd48cdc", - "metadata": { - "execution": { - "iopub.execute_input": "2022-04-25T05:22:22.413488Z", - "iopub.status.busy": "2022-04-25T05:22:22.413192Z", - "iopub.status.idle": "2022-04-25T05:22:44.785435Z", - "shell.execute_reply": "2022-04-25T05:22:44.784573Z" - } - }, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " \r" - ] - }, { "data": { - "image/svg+xml": [ - "\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " 2022-04-25T02:55:56.884008\n", - " image/svg+xml\n", - " \n", - " \n", - " Matplotlib v3.5.1, https://matplotlib.org/\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "\n" - ], - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "mov = ps.visualization.satn_to_movie(im=im, satn=satn, v_over=0.5)\n", - "image_based_ip_v_over = mov.to_jshtml()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "24adff52", - "metadata": {}, - "outputs": [], + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n", + " \n", + "
\n", + " \n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
\n", + "\n", + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "HTML(image_based_ip_c_under)" + ] + }, + { + "cell_type": "markdown", + "id": "6edfdfc3", + "metadata": {}, + "source": [ + "## `c_over`" + ] + }, + { + "cell_type": "markdown", + "id": "ff9c2933", + "metadata": {}, + "source": [ + "Colormap to be assigned to the highest color bound (over color) in the color map. The voxeled colored by `c_overer` are the solid phase. The default over color is white." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "fb8cdf9d", + "metadata": { + "execution": { + "iopub.execute_input": "2022-04-25T05:21:37.509070Z", + "iopub.status.busy": "2022-04-25T05:21:37.508915Z", + "iopub.status.idle": "2022-04-25T05:21:59.751378Z", + "shell.execute_reply": "2022-04-25T05:21:59.750706Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \r" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 464, + "width": 468 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "mov = ps.visualization.satn_to_movie(im=im, satn=satn, c_over='yellow')\n", + "image_based_ip_c_over = mov.to_jshtml()" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "8b8b82b7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n", + " \n", + "
\n", + " \n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
\n", + "\n", + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "HTML(image_based_ip_c_over)" + ] + }, + { + "cell_type": "markdown", + "id": "964039c6", + "metadata": {}, + "source": [ + "## `v_under`" + ] + }, + { + "cell_type": "markdown", + "id": "9565edcb", + "metadata": {}, + "source": [ + "This is the lowest bound of `satn` data range that the colormap covers. By default, the `v_under` is 0.001." + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "172fb4c7", + "metadata": { + "execution": { + "iopub.execute_input": "2022-04-25T05:21:59.755286Z", + "iopub.status.busy": "2022-04-25T05:21:59.754684Z", + "iopub.status.idle": "2022-04-25T05:22:22.409071Z", + "shell.execute_reply": "2022-04-25T05:22:22.408410Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \r" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "image/png": { + "height": 464, + "width": 468 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "mov = ps.visualization.satn_to_movie(im=im, satn=satn, v_under=0.2)\n", + "image_based_ip_v_under = mov.to_jshtml()" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "0fc1a26d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n", + " \n", + "
\n", + " \n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
\n", + "\n", + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "HTML(image_based_ip_v_under)" + ] + }, + { + "cell_type": "markdown", + "id": "7fbdec6c", + "metadata": {}, + "source": [ + "## `v_over`" + ] + }, + { + "cell_type": "markdown", + "id": "96bd8912", + "metadata": {}, + "source": [ + "This is the highest bound of `satn` data range that the colormap covers. By default, the `v_over` is 1." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "0dd48cdc", + "metadata": { + "execution": { + "iopub.execute_input": "2022-04-25T05:22:22.413488Z", + "iopub.status.busy": "2022-04-25T05:22:22.413192Z", + "iopub.status.idle": "2022-04-25T05:22:44.785435Z", + "shell.execute_reply": "2022-04-25T05:22:44.784573Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 0%| | 0/390 [00:00" + ] + }, + "metadata": { + "image/png": { + "height": 464, + "width": 468 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "mov = ps.visualization.satn_to_movie(im=im, satn=satn, v_over=0.5)\n", + "image_based_ip_v_over = mov.to_jshtml()" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "24adff52", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n", + " \n", + "
\n", + " \n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
\n", + "\n", + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "HTML(image_based_ip_v_over)" ]