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Multiplex_Analysis_Web_Apps.py
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Multiplex_Analysis_Web_Apps.py
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import streamlit as st
import os
from streamlit_extras.app_logo import add_logo
import streamlit_session_state_management
import nidap_dashboard_lib as ndl # Useful functions for dashboards connected to NIDAP
import streamlit_utils
import numpy as np
import subprocess
import platform_io
import install_missing_packages
install_missing_packages.live_package_installation()
# Note if any of the following imports having " # slow" are not commented out, there is a delay in running the forking test
from pages2 import data_import_and_export
from pages2 import datafile_format_unifier
from pages2 import open_file
from pages2 import robust_scatter_plotter
from pages2 import multiaxial_gating
from pages2 import thresholded_phenotyping # slow due to things ultimately importing umap
from pages2 import adaptive_phenotyping
from pages2 import Pheno_Cluster_a # "slow" for forking test initialization
from pages2 import Pheno_Cluster_b # "slow" for forking test initialization
from pages2 import Tool_parameter_selection
from pages2 import Run_workflow
from pages2 import Display_individual_ROI_heatmaps
from pages2 import Display_average_heatmaps
from pages2 import Display_average_heatmaps_per_annotation
from pages2 import Display_ROI_P_values_overlaid_on_slides
from pages2 import Neighborhood_Profiles # slow due to things ultimately importing umap
from pages2 import UMAP_Analyzer # slow due to things ultimately importing umap
from pages2 import Clusters_Analyzer # slow due to things ultimately importing umap
from pages2 import memory_analyzer
from pages2 import radial_bins_plots
from pages2 import radial_profiles_analysis
from pages2 import preprocessing
from pages2 import results_transfer
# from pages2 import forking_test
def welcome_page():
# Markdown text
intro_markdown = ndl.read_markdown_file('markdown/MAWA_WelcomePage.md')
st.markdown(intro_markdown, unsafe_allow_html=True)
def platform_is_nidap():
'''
Check if the Streamlit application is operating on NIDAP
'''
return np.any(['nidap.nih.gov' in x for x in subprocess.run('conda config --show channels', shell=True, capture_output=True).stdout.decode().split('\n')[1:-1]])
def check_for_platform(session_state):
'''
Set the platform parameters based on the platform the Streamlit app is running on
'''
# Initialize the platform object
if 'platform' not in session_state:
session_state['platform'] = platform_io.Platform(platform=('nidap' if platform_is_nidap() else 'local'))
return session_state
def main():
st.set_page_config(layout="wide")
# Use the new st.naviation()/st.Page() API to create a multi-page app
pg = st.navigation({
'Home 🏠':
[
st.Page(welcome_page, title="Welcome", url_path='home')
],
'File Handling 🗄️':
[
st.Page(data_import_and_export.main, title="Data Import and Export", url_path='data_import_and_export'),
st.Page(datafile_format_unifier.main, title="Datafile Unification", url_path='datafile_unification'),
st.Page(open_file.main, title="Open File", url_path='open_file')
],
'Coordinate Scatter Plotter 🌟':
[
st.Page(robust_scatter_plotter.main, title="Coordinate Scatter Plotter", url_path='coordinate_scatter_plotter')
],
'Phenotyping 🧬':
[
st.Page(multiaxial_gating.main, title="Using Raw Intensities", url_path='using_raw_intensities'),
st.Page(thresholded_phenotyping.main, title="Using Thresholded Intensities", url_path='using_thresholded_intensities'),
st.Page(adaptive_phenotyping.main, title="Adaptive Phenotyping", url_path='adaptive_phenotyping')
],
'Phenotype Clustering Workflow ✨':
[
st.Page(Pheno_Cluster_a.main, title="Unsupervised Phenotype Clustering", url_path='unsupervised_phenotype_clustering'),
st.Page(Pheno_Cluster_b.main, title="Differential Intensity", url_path='differential_intensity')
],
'Spatial Interaction Tool 🗺️':
[
st.Page(Tool_parameter_selection.main, title="Tool Parameter Selection", url_path='tool_parameter_selection'),
st.Page(Run_workflow.main, title="Run SIT Workflow", url_path='run_sit_workflow'),
st.Page(Display_individual_ROI_heatmaps.main, title="Display Individual ROI Heatmaps", url_path='display_individual_roi_heatmaps'),
st.Page(Display_average_heatmaps.main, title="Display Average Heatmaps", url_path='display_average_heatmaps'),
st.Page(Display_average_heatmaps_per_annotation.main, title="Display Average Heatmaps per Annotation", url_path='display_average_heatmaps_per_annotation'),
st.Page(Display_ROI_P_values_overlaid_on_slides.main, title="Display ROI P Values Overlaid on Slides", url_path='display_roi_p_values_overlaid_on_slides')
],
'Neighborhood Profiles Workflow 🌳':
[
st.Page(Neighborhood_Profiles.main, title="Neighborhood Profiles", url_path='neighborhood_profiles'),
st.Page(UMAP_Analyzer.main, title="UMAP Differences Analyzer", url_path='umap_differences_analyzer'),
st.Page(Clusters_Analyzer.main, title="Clusters Analyzer", url_path='clusters_analyzer')
],
'Radial Profiles 🌀':
[
st.Page(radial_bins_plots.main, title="Radial Bins Plots", url_path='radial_bins_plots'),
st.Page(radial_profiles_analysis.main, title="Radial Profiles Analysis", url_path='radial_profiles_analysis')
],
'Utilities 🛠️':
[
st.Page(preprocessing.main, title="Preprocessing", url_path='preprocessing'),
st.Page(memory_analyzer.main, title="Memory Analyzer", url_path='memory_analyzer'),
st.Page(results_transfer.main, title="Results Transfer", url_path='results_transfer'),
# st.Page(forking_test.main, title="Forking Test", url_path='forking_test')
]
})
# Ensure the input/output directories exist
input_path = './input'
if not os.path.exists(input_path):
os.makedirs(input_path)
output_path = './output'
if not os.path.exists(output_path):
os.makedirs(output_path)
# For widget persistence, we need always copy the session state to itself, being careful with widgets that cannot be persisted, like st.data_editor() (where we use the "__do_not_persist" suffix to avoid persisting it)
for key in st.session_state.keys():
if (not key.endswith('__do_not_persist')) and (not key.startswith('FormSubmitter:')):
st.session_state[key] = st.session_state[key]
# This is needed for the st.dataframe_editor() class (https://github.com/andrew-weisman/streamlit-dataframe-editor) but is also useful for seeing where we are and where we've been
st.session_state['current_page_name'] = pg.url_path if pg.url_path != '' else 'Home'
if 'previous_page_name' not in st.session_state:
st.session_state['previous_page_name'] = st.session_state['current_page_name']
# Add logo to sidebar
add_logo('app_images/mawa_logo-width315.png', height=250)
# Determine whether this is the first time the app has been run
if 'app_has_been_run_at_least_once' not in st.session_state:
st.session_state['app_has_been_run_at_least_once'] = True
first_app_run = True
else:
first_app_run = False
# Run session state management in the sidebar
streamlit_session_state_management.execute(first_app_run)
# Initalize session_state values for streamlit processing
if 'init' not in st.session_state:
st.session_state = ndl.init_session_state(st.session_state)
# Sidebar organization
with st.sidebar:
st.write('**:book: [Documentation](https://ncats.github.io/multiplex-analysis-web-apps/)**')
with st.expander('Advanced:'):
benchmark_button = True
if benchmark_button:
st.button('Record Benchmarking', on_click = st.session_state.bc.save_run_to_csv)
if st.button('Calculate memory used by Python session'):
streamlit_utils.write_python_session_memory_usage()
# Check the platform
st.session_state = check_for_platform(st.session_state)
# Format tooltips
tooltip_style = """
<style>
div[data-baseweb="tooltip"] {
width: 250px;
}
</style>
"""
st.markdown(tooltip_style,unsafe_allow_html=True)
# On every page, display its title
st.title(pg.title)
# Render the select page
pg.run()
# Update the previous page location
st.session_state['previous_page_name'] = st.session_state['current_page_name']
# Needed for rendering pages which use multiprocessing (https://docs.python.org/3/library/multiprocessing.html#the-spawn-and-forkserver-start-methods)
if __name__ == '__main__':
main()