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GUI.py
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GUI.py
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import tkinter.filedialog
from tkinter import (Tk, Label, Frame, Button, LabelFrame,INSERT, OptionMenu,
Radiobutton, IntVar,StringVar, Text, END, Entry, Toplevel, Checkbutton,
DISABLED, NORMAL, Listbox, LEFT, BOTH, simpledialog, messagebox)
from tkinter import filedialog as fd
from tkcalendar import Calendar
import tomlkit
import matplotlib.pyplot as plt
import numpy as np
import tkinter as tk
from matplotlib.backends.backend_tkagg import (
FigureCanvasTkAgg)
import webbrowser
class TDarts_GUI():
def __init__(self):
self.window = Tk()
# self.window.resizable(False, False)
width = 1650
height = 1000
self.window.geometry(str(width) + "x" + str(height))
self.window.title("Welcome to DARTS")
self.frame = Frame(self.window)
self.frame.pack()
########################################################################
# create config frame to place our grid
self.input_output_frame = LabelFrame(self.frame, text="Input/Output:", labelanchor="n")
self.input_output_frame.grid(row=0, column=0, sticky="news", padx=20, pady=20)
# batch or single processing
self.label_batch = Label(self.input_output_frame, text="Batch or single processing")
self.label_batch.grid(column=0, row=0, sticky="W")
self.select_mode = StringVar(value="file")
self.choose_single = Radiobutton(self.input_output_frame, text="Select File", variable=self.select_mode,
value="file")
self.choose_single.grid(column=0, row=1, sticky="W")
self.choose_dir = Radiobutton(self.input_output_frame, text="Select Directory", variable=self.select_mode,
value="dir")
self.choose_dir.grid(column=1, row=1, sticky="W")
self.label_path = Label(self.input_output_frame, text="path to input", anchor="e")
self.label_path.grid(row=2, column=0, sticky="E")
self.text_path = Text(self.input_output_frame, height=1, width=20)
self.text_path.grid(row=2, column=1, sticky="W")
self.selection_button = Button(self.input_output_frame, text="Choose files or directory",
command=self.select_files_or_directory)
self.selection_button.grid(row=3, column=0, sticky="W")
self.empty_label_fd = Label(self.input_output_frame, text="")
self.empty_label_fd.grid(row=4, column=0, sticky="W")
# image config: "single" or "two in one"
self.label_image_configuration = Label(self.input_output_frame, text="Image configuration")
self.label_image_configuration.grid(column=0, row=5, sticky="W")
self.label_image_configuration.config(bg='lightgray')
self.empty_label_cf = Label(self.input_output_frame, text="")
self.empty_label_cf.grid(row=6, column=0, sticky="W")
self.selected_image_configuration = IntVar(value=2)
self.image_config_radiobutton_1 = Radiobutton(self.input_output_frame, text='one file per channel', value=1,
variable=self.selected_image_configuration)
self.image_config_radiobutton_1.grid(row=7, column=0, sticky="W")
self.label_config1 = Label(self.input_output_frame, text="each channel is a separate file")
self.label_config1.grid(column=1, row=7, sticky="W")
self.image_config_radiobutton_2 = Radiobutton(self.input_output_frame, text='both channels in one file',
value=2,
variable=self.selected_image_configuration)
self.image_config_radiobutton_2.grid(row=8, column=0, sticky="W")
self.label_config2 = Label(self.input_output_frame, text="channels are side-by-side in the same frame or "
+ "\n" + "in the channel dimension of bioformats")
self.label_config2.grid(column=1, row=8, sticky="W")
self.empty_label_3 = Label(self.input_output_frame, text="")
self.empty_label_3.grid(row=9, column=0, sticky="W")
# path to result folder
self.label_results_directory = Label(self.input_output_frame, text="results directory")
self.label_results_directory.grid(row=10, column=0, sticky="W")
self.label_results_directory.config(bg='lightgray')
self.text_results_directory = Text(self.input_output_frame, height=1, width=20)
self.text_results_directory.grid(row=11, column=0, sticky="W")
self.choose_results_directory_button = Button(self.input_output_frame, text="Choose a results directory",
command=self.choose_results_directory_clicked)
self.choose_results_directory_button.grid(row=12, column=0, sticky="W")
#####################################################################################
# create Properties of measurement frame to place our grid
self.properties_of_measurement_frame = LabelFrame(self.frame, text="Properties of measurement:",
labelanchor="n")
self.properties_of_measurement_frame.grid(row=1, column=0, sticky="news", padx=20, pady=20)
# microscope
self.label_microscope_name = Label(self.properties_of_measurement_frame, text="Used microscope: ")
self.label_microscope_name.grid(row=0, column=0, sticky="W")
self.text_microscope = Text(self.properties_of_measurement_frame, height=1, width=20)
self.text_microscope.grid(row=0, column=1, sticky="W")
# scale
self.label_scale = Label(self.properties_of_measurement_frame, text="Scale (Pixels per micron): ")
self.label_scale.grid(row=1, column=0, sticky="W")
self.text_scale = Text(self.properties_of_measurement_frame, height=1, width=20)
self.text_scale.insert(INSERT, "0")
self.text_scale.grid(row=1, column=1, sticky="W")
# fps
self.label_fps = Label(self.properties_of_measurement_frame, text="frame rate (fps): ")
self.label_fps.grid(row=2, column=0, sticky="W")
self.text_fps = Text(self.properties_of_measurement_frame, height=1, width=20)
self.text_fps.insert(INSERT, "3.0")
self.text_fps.grid(row=2, column=1, sticky="W")
# resolution
self.label_resolution = Label(self.properties_of_measurement_frame, text="Spatial resolution in pixels: ")
self.label_resolution.grid(row=3, column=0, sticky="W")
self.text_resolution = Text(self.properties_of_measurement_frame, height=1, width=20)
self.text_resolution.insert(INSERT, "3")
self.text_resolution.grid(row=3, column=1, sticky="W")
# cell types
self.label_cell_type = Label(self.properties_of_measurement_frame, text="Cell type: ")
self.label_cell_type.grid(row=4, column=0, sticky="W")
self.cell_types = [
"jurkat",
"primary",
"NK"
]
self.cell_type = StringVar(self.properties_of_measurement_frame)
self.cell_type.set(self.cell_types[0])
self.option_menu_cell_types = OptionMenu(self.properties_of_measurement_frame, self.cell_type, *self.cell_types)
self.option_menu_cell_types.grid(row=4, column=1, sticky="W")
self.manage_cell_types_button = Button(self.properties_of_measurement_frame, text="Manage cell types", command=self.manage_cell_types)
self.manage_cell_types_button.grid(row=4, column=2, sticky="W")
self.cell_type_manager = CellTypeManager(self.window, self.cell_types, self.option_menu_cell_types,
self.cell_type)
# time
self.label_time = Label(self.properties_of_measurement_frame, text="day of measurement : ")
self.label_time.grid(row=5, column=0, sticky="W")
self.entry_time = Entry(self.properties_of_measurement_frame, width=10)
self.entry_time.grid(row=5, column=1, sticky="W")
self.entry_time.insert(0, "yyyy-mm-dd")
self.entry_time.bind("<1>", self.pick_date)
# user
self.label_user = Label(self.properties_of_measurement_frame, text="User: ")
self.label_user.grid(column=0, row=6, sticky="W")
self.text_user = Text(self.properties_of_measurement_frame, height=1, width=20)
self.text_user.grid(column=1, row=6, sticky="W")
# name of experiment
self.label_experiment_name = Label(self.properties_of_measurement_frame, text="Name of experiment: ")
self.label_experiment_name.grid(column=0, row=7, sticky="W")
self.text_experiment_name = Text(self.properties_of_measurement_frame, height=1, width=20)
self.text_experiment_name.grid(column=1, row=7, sticky="W")
# global or local measurement
self.label_global_or_local = Label(self.properties_of_measurement_frame, text="Imaging intention")
self.label_global_or_local.grid(column=0, row=8, sticky="W")
self.local_or_global = StringVar(value="local")
self.choose_local = Radiobutton(self.properties_of_measurement_frame, text="local imaging (microdomains)", variable=self.local_or_global,
value="local", command=self.set_default_settings_for_local_imaging)
self.choose_local.grid(column=0, row=9, sticky="W")
self.choose_global = Radiobutton(self.properties_of_measurement_frame, text="global imaging (ratio)", variable=self.local_or_global,
value="global", command=self.set_default_settings_for_global_imaging)
self.choose_global.grid(column=1, row=9, sticky="W")
# Bead contacts involved
self.label_bead_contact_sites = Label(self.properties_of_measurement_frame, text="Bead contact: ")
self.label_bead_contact_sites.grid(column=0, row=10, sticky="W")
self.bead_contacts_in_pipeline = IntVar()
self.check_box_bead_contacts = Checkbutton(self.properties_of_measurement_frame,
variable=self.bead_contacts_in_pipeline,
onvalue=1,
offvalue=0,
command=self.update_bead_contact)
self.check_box_bead_contacts.grid(column=1, row=10, sticky="W")
self.check_box_bead_contacts.select()
# self.check_box_bead_contacts.config(state=DISABLED)
# duration of measurement before bead contact/starting point
self.label_duration_before = Label(self.properties_of_measurement_frame, text="Measured seconds before starting" + "\n" +"point, e.g. bead contact:")
self.label_duration_before.grid(column=0, row=11, sticky="W")
self.text_duration_before = Text(self.properties_of_measurement_frame, height=1, width=20)
self.text_duration_before.grid(column=1, row=11, sticky="W")
# duration of measurement after bead contact/starting point
self.label_duration_after = Label(self.properties_of_measurement_frame, text="Measured seconds after starting" + "\n" +"point, e.g. bead contact:")
self.label_duration_after.grid(column=0, row=12, sticky="W")
self.text_duration_after = Text(self.properties_of_measurement_frame, height=1, width=20)
self.text_duration_after.grid(column=1, row=12, sticky="W")
###################################################################################
# create Pipeline frame to place our grid
self.label_processing_pipeline = LabelFrame(self.frame, text="Processing pipeline:", labelanchor="n")
self.label_processing_pipeline.grid(row=0, column=1, sticky="news", padx=20, pady=20)
self.label_postprocessing = Label(self.label_processing_pipeline, text="Postprocessing")
self.label_postprocessing.grid(column=1, row=12, sticky="W")
self.label_postprocessing.config(bg='lightgray')
self.label_channel_alignment = Label(self.label_processing_pipeline, text="Channel alignment (SITK): ")
self.label_channel_alignment.grid(column=1, row=13, sticky="W")
self.channel_alignment_in_pipeline = IntVar(value=0)
self.check_box_channel_alignment = Checkbutton(self.label_processing_pipeline,
variable=self.channel_alignment_in_pipeline,
onvalue=1, offvalue=0, command=self.update_settings_for_registration)
self.check_box_channel_alignment.grid(column=2, row=13, sticky="W")
self.check_box_channel_alignment.select()
# self.check_box_channel_alignment.config(state=DISABLED)
self.label_frame_by_frame_registration = Label(self.label_processing_pipeline,
text="align each frame?: ")
self.label_frame_by_frame_registration.grid(column=3, row=13, sticky="W")
self.frame_by_frame_registration = IntVar()
self.check_box_frame_by_frame_registration = Checkbutton(self.label_processing_pipeline,
variable=self.frame_by_frame_registration,
onvalue=1, offvalue=0, )
self.check_box_frame_by_frame_registration.grid(column=4, row=13, sticky="W")
#
self.label_background_subtraction = Label(self.label_processing_pipeline, text="Background subtraction: ")
self.label_background_subtraction.grid(column=1, row=14, sticky="W")
self.background_subtraction_in_pipeline = IntVar()
self.check_box_background_subtraction_in_pipeline = Checkbutton(self.label_processing_pipeline,
variable=self.background_subtraction_in_pipeline,
onvalue=1,
offvalue=0,
command=None)
self.check_box_background_subtraction_in_pipeline.grid(column=2, row=14, sticky="W")
self.check_box_background_subtraction_in_pipeline.select()
# self.check_box_background_subtraction_in_pipeline.config(state=DISABLED)
#
self.label_segmentation_tracking = Label(self.label_processing_pipeline, text="Cell segmentation/Tracking: ")
self.label_segmentation_tracking.grid(column=1, row=15, sticky="W")
self.segmentation_tracking_in_pipeline = IntVar()
self.check_box_segmentation_tracking_in_pipeline = Checkbutton(self.label_processing_pipeline,
variable=self.segmentation_tracking_in_pipeline,
onvalue=1,
offvalue=0,
command=None)
self.check_box_segmentation_tracking_in_pipeline.grid(column=2, row=15, sticky="W")
self.check_box_segmentation_tracking_in_pipeline.select()
self.check_box_segmentation_tracking_in_pipeline.config(state=DISABLED)
#
self.label_deconvolution = Label(self.label_processing_pipeline, text="Deconvolution: ")
self.label_deconvolution.grid(column=1, row=16, sticky="W")
self.deconvolution_in_pipeline = IntVar()
self.check_box_deconvolution_in_pipeline = Checkbutton(self.label_processing_pipeline,
variable=self.deconvolution_in_pipeline,
onvalue=1,
offvalue=0,
command=self.update_deconvolution)
self.check_box_deconvolution_in_pipeline.grid(column=2, row=16, sticky="W")
self.check_box_deconvolution_in_pipeline.select()
# self.check_box_deconvolution_in_pipeline.config(state=DISABLED)
deconvolution_algorithms = [
"LR",
"TDE"
]
self.deconvolution_algorithm = StringVar(self.label_processing_pipeline)
self.deconvolution_algorithm.set(deconvolution_algorithms[0])
self.option_menu_deconvolution = OptionMenu(self.label_processing_pipeline, self.deconvolution_algorithm, *deconvolution_algorithms, command=self.decon_selection_changed)
# self.option_menu_deconvolution.config(state=DISABLED)
self.option_menu_deconvolution.grid(column=3, row=16, sticky="W")
self.deconvolution_text_boxes = []
self.label_TDE_lambda = Label(self.label_processing_pipeline, text="lambda (TDE)")
self.label_TDE_lambda.grid(column=3, row=17, sticky="W")
self.text_TDE_lambda = Text(self.label_processing_pipeline, height=1, width=10)
self.text_TDE_lambda.grid(column=4, row=17, sticky="W")
self.text_TDE_lambda.config(state=DISABLED)
self.deconvolution_text_boxes.append(self.text_TDE_lambda)
self.label_TDE_lambda_t = Label(self.label_processing_pipeline, text="lambda t (TDE)")
self.label_TDE_lambda_t.grid(column=5, row=17, sticky="W")
self.text_TDE_lambda_t = Text(self.label_processing_pipeline, height=1, width=10)
self.text_TDE_lambda_t.grid(column=6, row=17, sticky="W")
self.text_TDE_lambda_t.config(state=DISABLED)
self.deconvolution_text_boxes.append(self.text_TDE_lambda_t)
self.label_psf_type = Label(self.label_processing_pipeline, text="psf: type")
self.label_psf_type.grid(column=7, row=17, sticky="W")
self.text_psf_type = Text(self.label_processing_pipeline, height=1, width=10)
self.text_psf_type.grid(column=8, row=17, sticky="W")
self.deconvolution_text_boxes.append(self.text_psf_type)
self.label_psf_lambdaEx_ch1 = Label(self.label_processing_pipeline, text="psf: lambdaEx_ch1")
self.label_psf_lambdaEx_ch1.grid(column=3, row=18, sticky="W")
self.text_psf_lambdaEx_ch1 = Text(self.label_processing_pipeline, height=1, width=10)
self.text_psf_lambdaEx_ch1.grid(column=4, row=18, sticky="W")
self.deconvolution_text_boxes.append(self.text_psf_lambdaEx_ch1)
self.label_psf_lambdaEm_ch1 = Label(self.label_processing_pipeline, text="psf: lambdaEm_ch1")
self.label_psf_lambdaEm_ch1.grid(column=5, row=18, sticky="W")
self.text_psf_lambdaEm_ch1 = Text(self.label_processing_pipeline, height=1, width=10)
self.text_psf_lambdaEm_ch1.grid(column=6, row=18, sticky="W")
self.deconvolution_text_boxes.append(self.text_psf_lambdaEm_ch1)
self.label_psf_lambdaEx_ch2 = Label(self.label_processing_pipeline, text="psf: lambdaEx_ch2")
self.label_psf_lambdaEx_ch2.grid(column=7, row=18, sticky="W")
self.text_psf_lambdaEx_ch2 = Text(self.label_processing_pipeline, height=1, width=10)
self.text_psf_lambdaEx_ch2.grid(column=8, row=18, sticky="W")
self.deconvolution_text_boxes.append(self.text_psf_lambdaEx_ch2)
self.label_psf_lambdaEm_ch2 = Label(self.label_processing_pipeline, text="psf: lambdaEm_ch2")
self.label_psf_lambdaEm_ch2.grid(column=3, row=19, sticky="W")
self.text_psf_lambdaEm_ch2 = Text(self.label_processing_pipeline, height=1, width=10)
self.text_psf_lambdaEm_ch2.grid(column=4, row=19, sticky="W")
self.deconvolution_text_boxes.append(self.text_psf_lambdaEm_ch2)
self.label_psf_numAper = Label(self.label_processing_pipeline, text="psf: numAper")
self.label_psf_numAper.grid(column=5, row=19, sticky="W")
self.text_psf_numAper= Text(self.label_processing_pipeline, height=1, width=10)
self.text_psf_numAper.grid(column=6, row=19, sticky="W")
self.deconvolution_text_boxes.append(self.text_psf_numAper)
self.label_psf_magObj = Label(self.label_processing_pipeline, text="psf: magObj")
self.label_psf_magObj.grid(column=7, row=19, sticky="W")
self.text_psf_magObj = Text(self.label_processing_pipeline, height=1, width=10)
self.text_psf_magObj.grid(column=8, row=19, sticky="W")
self.deconvolution_text_boxes.append(self.text_psf_magObj)
self.label_psf_rindexObj = Label(self.label_processing_pipeline, text="psf: rindexObj")
self.label_psf_rindexObj.grid(column=3, row=20, sticky="W")
self.text_psf_rindexObj = Text(self.label_processing_pipeline, height=1, width=10)
self.text_psf_rindexObj.grid(column=4, row=20, sticky="W")
self.deconvolution_text_boxes.append(self.text_psf_rindexObj)
self.label_psf_rindexSp = Label(self.label_processing_pipeline, text="psf: rindexSp")
self.label_psf_rindexSp.grid(column=5, row=20, sticky="W")
self.text_psf_rindexSp = Text(self.label_processing_pipeline, height=1, width=10)
self.text_psf_rindexSp.grid(column=6, row=20, sticky="W")
self.deconvolution_text_boxes.append(self.text_psf_rindexSp)
self.label_psf_ccdSize = Label(self.label_processing_pipeline, text="psf: ccdSize")
self.label_psf_ccdSize.grid(column=7, row=20, sticky="W")
self.text_psf_ccdSize = Text(self.label_processing_pipeline, height=1, width=10)
self.text_psf_ccdSize.grid(column=8, row=20, sticky="W")
self.deconvolution_text_boxes.append(self.text_psf_ccdSize)
#
self.label_bleaching_correction = Label(self.label_processing_pipeline, text="Bleaching correction: ")
self.label_bleaching_correction.grid(column=1, row=21, sticky="W")
self.bleaching_correction_in_pipeline = IntVar()
self.check_box_bleaching_correction = Checkbutton(self.label_processing_pipeline,
variable=self.bleaching_correction_in_pipeline,
onvalue=1,
offvalue=0,
command=self.update_bleaching_correction)
self.check_box_bleaching_correction.grid(column=2, row=21, sticky="W")
self.check_box_bleaching_correction.select()
# self.check_box_bleaching_correction.config(state=DISABLED)
bleaching_correction_algorithms = [
"additiv no fit",
"multiplicative simple ratio",
"biexponential fit additiv"
]
self.bleaching_correction_algorithm = StringVar(self.label_processing_pipeline)
self.bleaching_correction_algorithm.set(bleaching_correction_algorithms[0])
self.option_menu_bleaching_correction = OptionMenu(self.label_processing_pipeline, self.bleaching_correction_algorithm,
*bleaching_correction_algorithms)
# self.option_menu_bleaching_correction.config(state=DISABLED)
self.option_menu_bleaching_correction.grid(column=3, row=21, sticky="W")
#
self.label_ratio_generation = Label(self.label_processing_pipeline, text="Ratio images: ")
self.label_ratio_generation.grid(column=1, row=22, sticky="W")
self.ratio_generation_in_pipeline = IntVar()
self.check_box_ratio_generation = Checkbutton(self.label_processing_pipeline,
variable=self.ratio_generation_in_pipeline,
onvalue=1,
offvalue=0,
command=None)
self.check_box_ratio_generation.grid(column=2, row=22, sticky="W")
self.check_box_ratio_generation.select()
self.check_box_ratio_generation.config(state=DISABLED)
self.empty_label = Label(self.label_processing_pipeline, text="")
self.empty_label.grid(column=1, row=23, sticky="W")
self.label_shape_normalization = Label(self.label_processing_pipeline, text="Shape Normalization")
self.label_shape_normalization.grid(column=1, row=24, sticky="W")
self.label_shape_normalization.config(bg='lightgray')
self.shape_normalization_in_pipeline = IntVar()
self.check_box_shape_normalization = Checkbutton(self.label_processing_pipeline,
variable=self.shape_normalization_in_pipeline,
onvalue=1,
offvalue=0,
command=self.update_settings_shape_normalization)
self.check_box_shape_normalization.grid(column=2, row=24, sticky="W")
self.check_box_shape_normalization.select()
# self.check_box_shape_normalization.config(state=DISABLED)
self.empty_label_2 = Label(self.label_processing_pipeline, text="")
self.empty_label_2.grid(column=1, row=25, sticky="W")
self.label_analysis = Label(self.label_processing_pipeline, text="Analysis")
self.label_analysis.grid(column=1, row=26, sticky="W")
self.label_analysis.config(bg='lightgray')
self.label_hotspot_detection = Label(self.label_processing_pipeline, text="Hotspot detection: ")
self.label_hotspot_detection.grid(column=1, row=27, sticky="W")
self.hotspot_detection_in_pipeline = IntVar()
self.check_box_hotspot_detection = Checkbutton(self.label_processing_pipeline,
variable=self.hotspot_detection_in_pipeline,
onvalue=1,
offvalue=0,
command=self.update_settings_for_analysis)
self.check_box_hotspot_detection.grid(column=2, row=27, sticky="W")
self.check_box_hotspot_detection.select()
# self.check_box_hotspot_detection.config(state=DISABLED)
self.label_dartboard_projection = Label(self.label_processing_pipeline, text="Dartboard projection: ")
self.label_dartboard_projection.grid(column=1, row=28, sticky="W")
self.dartboard_projection_in_pipeline = IntVar()
self.check_box_dartboard_projection = Checkbutton(self.label_processing_pipeline,
variable=self.dartboard_projection_in_pipeline,
onvalue=1,
offvalue=0,
command=None)
self.check_box_dartboard_projection.grid(column=2, row=28, sticky="W")
self.check_box_dartboard_projection.select()
# self.check_box_dartboard_projection.config(state=DISABLED)
self.empty_label_3 = Label(self.label_processing_pipeline, text="")
self.empty_label_3.grid(column=1, row=29, sticky="W")
self.set_default_settings_for_local_imaging()
# select all/default settings button
# self.default_settings_button = Button(self.label_processing_pipeline, text='Default settings', command=self.default_processing_settings)
# self.default_settings_button.grid(column=1, row=30, sticky="W")
##################################################################################
"""
# create Properties of measurement frame to place our grid
self.processing_mode_frame = LabelFrame(self.frame, text="Choose a processing mode:", labelanchor="n")
self.processing_mode_frame.grid(row=4, column=0, sticky="news", padx=20, pady=20)
self.processing_mode = IntVar()
self.processing_mode_radiobutton_1 = Radiobutton(self.processing_mode_frame, text='single measurement', value=1,
variable=self.processing_mode)
self.processing_mode_radiobutton_2 = Radiobutton(self.processing_mode_frame, text='batch processing', value=2,
variable=self.processing_mode)
self.processing_mode_radiobutton_1.grid(row=0, column=0, sticky="W")
self.processing_mode_radiobutton_2.grid(row=1, column=0, sticky="W")
"""
#################################################################################
# create Pipeline frame to place our grid
self.label_control_buttons = LabelFrame(self.frame, text="Control buttons:", labelanchor="n")
self.label_control_buttons.grid(row=1, column=1, sticky="news", padx=20, pady=20)
# settings from last run
self.save_settings_as_method_button = Button(self.label_control_buttons, text="Save settings on computer",
command=self.save_settings_as_method)
self.save_settings_as_method_button.grid(row=0, column=1, sticky="W")
self.load_settings_from_computer_button = Button(self.label_control_buttons, text="Load settings from computer",
command=self.load_settings_from_computer)
self.load_settings_from_computer_button.grid(row=1, column=1, sticky="W")
################################################################################
self.start_button = Button(self.label_control_buttons, text='Start', command=self.start_analysis)
self.start_button.grid(row=2, column=1, sticky="W")
# cancel button
self.cancel_button = Button(self.label_control_buttons, text='Cancel', command=self.cancel)
self.cancel_button.grid(row=3, column=1, sticky="W")
# About DARTS button
self.about_DARTS_button = Button(self.label_control_buttons, text='About DARTS', command=self.open_github_page)
self.about_DARTS_button.grid(row=4, column=1, sticky="W")
def pick_date(self, event):
global calendar, date_window
date_window = Toplevel()
date_window.grab_set()
date_window.title("Choose date of measurement")
date_window.geometry('270x220+590+370')
calendar = Calendar(date_window,
selectmode="day",
background="black",
foreground="gray",
normalbackground="black",
selectedbackground="gray",
date_pattern="y-mm-dd")
calendar.place(x=0, y=0)
submit_button = Button(date_window, text='submit', command=self.grab_date)
submit_button.place(x=80, y=190)
def open_github_page(self):
website = "https://github.com/IPMI-ICNS-UKE/DARTS"
webbrowser.open(website)
def get_parameters(self):
data = {
'input_output': {
'file_or_directory': self.select_mode.get(),
'image_conf': self.get_image_configuration(),
'path': self.text_path.get("1.0", "end-1c"),
# 'path_to_input_1': self.text_single_path_to_input_channel1.get("1.0", "end-1c"),
# 'path_to_input_2': self.text_single_path_to_input_channel2.get("1.0", "end-1c"),
# 'path_to_input_combined': self.text_path_to_input_combined.get("1.0", "end-1c"),
'results_dir': self.text_results_directory.get("1.0", "end-1c"),
'excel_filename_microdomain_data': "microdomain_data.xlsx"
},
'properties_of_measurement': {
'used_microscope': str(self.text_microscope.get("1.0", "end-1c")),
'scale': float(self.text_scale.get("1.0", END)),
'frame_rate': float(self.text_fps.get("1.0", END)),
'resolution': int(self.text_resolution.get("1.0", END)),
'cell_type': self.cell_type.get(),
'cell_types_options': self.cell_types,
'calibration_parameters_cell_types': self.cell_type_manager.parameters_dict,
'day_of_measurement': str(self.entry_time.get()),
'user': str(self.text_user.get("1.0", "end-1c")),
'experiment_name': str(self.text_experiment_name.get("1.0", "end-1c")),
'imaging_local_or_global': self.local_or_global.get(),
'bead_contact': self.bead_contacts_in_pipeline.get() == 1,
'duration_of_measurement': (float(self.text_duration_before.get("1.0", END)) + float(self.text_duration_after.get("1.0", END)))*float(self.text_fps.get("1.0", END)),
'wavelength_1': 488,
'wavelength_2': 561,
'time_of_measurement_before_starting_point': float(self.text_duration_before.get("1.0", END)),
'time_of_measurement_after_starting_point': float(self.text_duration_after.get("1.0", END))
},
'processing_pipeline': {
'postprocessing': {
'channel_alignment_in_pipeline': self.channel_alignment_in_pipeline.get() == 1,
'channel_alignment_each_frame': self.frame_by_frame_registration.get() == 1,
'registration_method': 'SITK',
'background_sub_in_pipeline': self.background_subtraction_in_pipeline.get() == 1,
'cell_segmentation_tracking_in_pipeline': self.segmentation_tracking_in_pipeline.get() == 1,
'deconvolution_in_pipeline': self.deconvolution_in_pipeline.get() == 1,
'deconvolution_algorithm': str(self.deconvolution_algorithm.get()),
'TDE_lambda': self.text_TDE_lambda.get("1.0", "end-1c"),
'TDE_lambda_t': self.text_TDE_lambda_t.get("1.0", "end-1c"),
'psf': {
'type': str(self.text_psf_type.get("1.0", "end-1c")), # accepted types: "confocal" and "widefield"
'lambdaEx_ch1': int(self.text_psf_lambdaEx_ch1.get("1.0", END)),
'lambdaEm_ch1': int(self.text_psf_lambdaEm_ch1.get("1.0", END)),
'lambdaEx_ch2': int(self.text_psf_lambdaEx_ch2.get("1.0", END)),
'lambdaEm_ch2': int(self.text_psf_lambdaEm_ch2.get("1.0", END)),
'numAper': float(self.text_psf_numAper.get("1.0", END)),
'magObj': int(self.text_psf_magObj.get("1.0", END)),
'rindexObj': float(self.text_psf_rindexObj.get("1.0", END)),
'ccdSize': int(self.text_psf_ccdSize.get("1.0", END)),
'dz': 0,
'nslices': 1,
'depth': 0,
'rindexSp': float(self.text_psf_rindexSp.get("1.0", END)),
'nor': 0,
'xysize': 150
},
'bleaching_correction_in_pipeline': self.bleaching_correction_in_pipeline.get() == 1,
'bleaching_correction_algorithm': self.bleaching_correction_algorithm.get(),
'ratio_images': self.ratio_generation_in_pipeline.get() == 1,
'median_filter_kernel': 3
},
'shape_normalization': {
'shape_normalization': self.shape_normalization_in_pipeline.get() == 1
},
'analysis': {
'hotspot_detection': self.hotspot_detection_in_pipeline.get() == 1,
'dartboard_projection': self.dartboard_projection_in_pipeline.get() == 1
}
}
}
return data
def save_settings_as_method(self):
data = self.get_parameters()
directory = tkinter.filedialog.askdirectory()
experiment_name = data['properties_of_measurement']['experiment_name']
user = data['properties_of_measurement']['user']
date = data['properties_of_measurement']['day_of_measurement']
file = open(directory + "/DARTS_settings_" + date + "_" + experiment_name + "_" + user + ".toml", "w")
tomlkit.dump(data, file)
file.close()
def load_settings_from_computer(self):
config_file_path = tkinter.filedialog.askopenfilename()
with open(config_file_path, mode="rt", encoding="utf-8") as fp:
config = tomlkit.load(fp)
# INPUT OUTPUT
self.select_mode.set(config["input_output"]["file_or_directory"])
image_config = self.convert_image_config_to_number(config['input_output']['image_conf'])
self.selected_image_configuration.set(image_config)
self.text_path.delete(1.0, END)
self.text_path.insert(1.0, config["input_output"]["path"])
self.text_results_directory.delete(1.0, END)
self.text_results_directory.insert(1.0, config["input_output"]["results_dir"])
self.excel_filename_microdomain_data = config["input_output"]["excel_filename_microdomain_data"]
# PROPERTIES OF MEASUREMENT
self.text_microscope.delete(1.0, END)
self.text_microscope.insert(1.0, config["properties_of_measurement"]["used_microscope"])
self.text_scale.delete(1.0, END)
self.text_scale.insert(1.0, config["properties_of_measurement"]["scale"])
self.text_fps.delete(1.0, END)
self.text_fps.insert(1.0, config["properties_of_measurement"]["frame_rate"])
self.text_resolution.delete(1.0, END)
self.text_resolution.insert(1.0, config["properties_of_measurement"]["resolution"])
self.cell_type.set(config["properties_of_measurement"]["cell_type"])
self.cell_types = list(config["properties_of_measurement"]["cell_types_options"])
# Clear current menu
self.option_menu_cell_types['menu'].delete(0, END)
# Update options in cell type option menu
for cell_type in self.cell_types:
self.option_menu_cell_types['menu'].add_command(label=cell_type,
command=tkinter._setit(self.cell_type,
cell_type))
self.cell_type_manager.cell_types = self.cell_types
# calibration parameters for cell type
self.cell_type_manager.parameters_dict = dict(config["properties_of_measurement"]["calibration_parameters_cell_types"])
self.entry_time.delete(0, END)
self.entry_time.insert(0, config["properties_of_measurement"]["day_of_measurement"])
self.text_user.delete(1.0, END)
self.text_user.insert(1.0, config["properties_of_measurement"]["user"])
self.text_experiment_name.delete(1.0, END)
self.text_experiment_name.insert(1.0, config["properties_of_measurement"]["experiment_name"])
self.local_or_global.set(config["properties_of_measurement"]["imaging_local_or_global"])
if config["properties_of_measurement"]["bead_contact"]:
self.check_box_bead_contacts.select()
else:
self.check_box_bead_contacts.deselect()
self.duration_of_measurement = config["properties_of_measurement"]["duration_of_measurement"]
self.wavelength_1 = config["properties_of_measurement"]["wavelength_1"]
self.wavelength_2 = config["properties_of_measurement"]["wavelength_2"]
self.text_duration_before.delete(1.0, END)
self.text_duration_before.insert(1.0, config["properties_of_measurement"]["time_of_measurement_before_starting_point"])
self.text_duration_after.delete(1.0, END)
self.text_duration_after.insert(1.0, config["properties_of_measurement"]["time_of_measurement_after_starting_point"])
# PROCESSING PIPELINE
## POSTPROCESSING
if config["processing_pipeline"]["postprocessing"]["channel_alignment_in_pipeline"]:
self.check_box_channel_alignment.select()
else:
self.check_box_channel_alignment.deselect()
if config["processing_pipeline"]["postprocessing"]["channel_alignment_each_frame"]:
self.check_box_frame_by_frame_registration.select()
else:
self.check_box_frame_by_frame_registration.deselect()
self.registration_method = config["processing_pipeline"]["postprocessing"]["registration_method"]
if config["processing_pipeline"]["postprocessing"]["background_sub_in_pipeline"]:
self.check_box_background_subtraction_in_pipeline.select()
else:
self.check_box_background_subtraction_in_pipeline.deselect()
if config["processing_pipeline"]["postprocessing"]["cell_segmentation_tracking_in_pipeline"]:
self.check_box_segmentation_tracking_in_pipeline.select()
else:
self.check_box_segmentation_tracking_in_pipeline.deselect()
if config["processing_pipeline"]["postprocessing"]["deconvolution_in_pipeline"]:
self.check_box_deconvolution_in_pipeline.select()
self.deconvolution_algorithm.set(config["processing_pipeline"]["postprocessing"]["deconvolution_algorithm"])
self.option_menu_deconvolution.config(state=NORMAL)
if self.deconvolution_algorithm.get() == "TDE":
self.text_TDE_lambda.config(state=NORMAL)
self.text_TDE_lambda_t.config(state=NORMAL)
self.text_TDE_lambda.delete(1.0, END)
self.text_TDE_lambda.insert(1.0, config["processing_pipeline"]["postprocessing"]["TDE_lambda"])
self.text_TDE_lambda_t.delete(1.0, END)
self.text_TDE_lambda_t.insert(1.0, config["processing_pipeline"]["postprocessing"]["TDE_lambda_t"])
self.text_psf_type.delete(1.0, END)
self.text_psf_type.insert(1.0, config["processing_pipeline"]["postprocessing"]["psf"]["type"])
self.text_psf_lambdaEx_ch1.delete(1.0, END)
self.text_psf_lambdaEx_ch1.insert(1.0, config["processing_pipeline"]["postprocessing"]["psf"]["lambdaEx_ch1"])
self.text_psf_lambdaEm_ch1.delete(1.0, END)
self.text_psf_lambdaEm_ch1.insert(1.0, config["processing_pipeline"]["postprocessing"]["psf"]["lambdaEm_ch1"])
self.text_psf_lambdaEx_ch2.delete(1.0, END)
self.text_psf_lambdaEx_ch2.insert(1.0, config["processing_pipeline"]["postprocessing"]["psf"]["lambdaEx_ch2"])
self.text_psf_lambdaEm_ch2.delete(1.0, END)
self.text_psf_lambdaEm_ch2.insert(1.0, config["processing_pipeline"]["postprocessing"]["psf"]["lambdaEm_ch2"])
self.text_psf_numAper.delete(1.0, END)
self.text_psf_numAper.insert(1.0, config["processing_pipeline"]["postprocessing"]["psf"]["numAper"])
self.text_psf_magObj.delete(1.0, END)
self.text_psf_magObj.insert(1.0, config["processing_pipeline"]["postprocessing"]["psf"]["magObj"])
self.text_psf_rindexObj.delete(1.0, END)
self.text_psf_rindexObj.insert(1.0, config["processing_pipeline"]["postprocessing"]["psf"]["rindexObj"])
self.text_psf_rindexSp.delete(1.0, END)
self.text_psf_rindexSp.insert(1.0, config["processing_pipeline"]["postprocessing"]["psf"]["rindexSp"])
self.text_psf_ccdSize.delete(1.0, END)
self.text_psf_ccdSize.insert(1.0, config["processing_pipeline"]["postprocessing"]["psf"]["ccdSize"])
else:
self.check_box_deconvolution_in_pipeline.deselect()
self.option_menu_deconvolution.config(state=DISABLED)
if config["processing_pipeline"]["postprocessing"]["bleaching_correction_in_pipeline"]:
self.check_box_bleaching_correction.select()
self.bleaching_correction_algorithm.set(config["processing_pipeline"]["postprocessing"]["bleaching_correction_algorithm"])
self.option_menu_bleaching_correction.config(state=NORMAL)
else:
self.check_box_bleaching_correction.deselect()
self.option_menu_bleaching_correction.config(state=DISABLED)
if config["processing_pipeline"]["postprocessing"]["ratio_images"]:
self.check_box_ratio_generation.select()
else:
self.check_box_ratio_generation.deselect()
self.median_filter_kernel = config["processing_pipeline"]["postprocessing"]["median_filter_kernel"]
## SHAPE NORMALIZATION
if config["processing_pipeline"]["shape_normalization"]["shape_normalization"]:
self.check_box_shape_normalization.config(state=NORMAL)
self.check_box_shape_normalization.select()
else:
self.check_box_shape_normalization.deselect()
## ANALYSIS
if config["processing_pipeline"]["analysis"]["hotspot_detection"]:
self.check_box_hotspot_detection.select()
self.check_box_hotspot_detection.config(state=NORMAL)
else:
self.check_box_hotspot_detection.deselect()
if config["processing_pipeline"]["analysis"]["dartboard_projection"]:
self.check_box_dartboard_projection.select()
self.check_box_dartboard_projection.config(state=NORMAL)
else:
self.check_box_dartboard_projection.deselect()
def grab_date(self):
self.entry_time.delete(0, END)
self.entry_time.insert(0, calendar.get_date())
date_window.destroy()
def start_analysis(self):
self.write_input_to_config_file()
self.close_window()
def cancel(self):
self.window.destroy()
quit()
def update_settings_for_registration(self):
if self.channel_alignment_in_pipeline.get() == 0:
self.frame_by_frame_registration.set(0)
self.check_box_frame_by_frame_registration.config(state=DISABLED)
elif self.channel_alignment_in_pipeline.get() == 1:
self.check_box_frame_by_frame_registration.config(state=NORMAL)
def update_settings_for_analysis(self):
if self.hotspot_detection_in_pipeline.get() == 0:
self.dartboard_projection_in_pipeline.set(0)
self.check_box_dartboard_projection.config(state=DISABLED)
elif self.hotspot_detection_in_pipeline.get() == 1 and self.shape_normalization_in_pipeline.get() == 1 and self.bead_contacts_in_pipeline.get()==1:
self.check_box_dartboard_projection.config(state=NORMAL)
self.dartboard_projection_in_pipeline.set(1)
def update_settings_shape_normalization(self):
if self.shape_normalization_in_pipeline.get() == 0:
# self.hotspot_detection_in_pipeline.set(0)
# self.check_box_hotspot_detection.config(state=DISABLED)
self.dartboard_projection_in_pipeline.set(0)
self.check_box_dartboard_projection.config(state=DISABLED)
elif self.shape_normalization_in_pipeline.get() == 1 and self.bead_contacts_in_pipeline.get() == 1:
self.hotspot_detection_in_pipeline.set(1)
self.check_box_hotspot_detection.config(state=NORMAL)
self.dartboard_projection_in_pipeline.set(1)
self.check_box_dartboard_projection.config(state=NORMAL)
def update_deconvolution(self):
if self.deconvolution_in_pipeline.get() == 0:
self.option_menu_deconvolution.config(state=DISABLED)
for textbox in self.deconvolution_text_boxes:
textbox.config(state=DISABLED)
elif self.deconvolution_in_pipeline.get() == 1:
self.option_menu_deconvolution.config(state=NORMAL)
for textbox in self.deconvolution_text_boxes:
textbox.config(state=NORMAL)
def update_bleaching_correction(self):
if self.bleaching_correction_in_pipeline.get() == 0:
self.option_menu_bleaching_correction.config(state=DISABLED)
elif self.bleaching_correction_in_pipeline.get() == 1:
self.option_menu_bleaching_correction.config(state=NORMAL)
def update_bead_contact(self):
if self.bead_contacts_in_pipeline.get() == 0:
self.dartboard_projection_in_pipeline.set(0)
self.check_box_dartboard_projection.config(state=DISABLED)
elif self.bead_contacts_in_pipeline.get():
if self.shape_normalization_in_pipeline.get() == 1 and self.hotspot_detection_in_pipeline.get() == 1:
self.dartboard_projection_in_pipeline.set(1)
self.check_box_dartboard_projection.config(state=NORMAL)
def get_image_configuration(self):
if self.selected_image_configuration.get() == 1:
return "single"
if self.selected_image_configuration.get() == 2:
return "two-in-one"
else:
return "no configuration chosen"
def convert_image_config_to_number(self, image_config):
if image_config == "single":
return 1
elif image_config == "two-in-one":
return 2
else:
return None
def decon_selection_changed(self, event):
chosen_decon_algorithm = self.deconvolution_algorithm.get()
if chosen_decon_algorithm == "TDE":
self.text_TDE_lambda.config(state=NORMAL)
self.text_TDE_lambda_t.config(state=NORMAL)
elif chosen_decon_algorithm =="LR":
self.text_TDE_lambda.delete(1.0, END)
self.text_TDE_lambda.config(state=DISABLED)
self.text_TDE_lambda_t.delete(1.0, END)
self.text_TDE_lambda_t.config(state=DISABLED)
#def select_directory(self):
# chosen_image_configuration = self.get_image_configuration()
# if (chosen_image_configuration == "single"):
# #filename_channel1 = fd.askdirectory()
# filename_channel1 = fd.askopenfilename(title="Select a File or Directory",
# filetypes=[("All files and directories", "*.*")])
# #self.text_single_path_to_input_channel1.delete('1.0', END)
# self.text_single_path_to_input_channel1.insert(1.0, filename_channel1)
# filename_channel2 = fd.askopenfilename(title="Select a File or Directory",
# filetypes=[("All files and directories", "*.*")])
# #self.text_single_path_to_input_channel2.delete('1.0', END)
# self.text_single_path_to_input_channel2.insert(1.0, filename_channel2)
# #self.text_path_to_input_combined.delete('1.0', END)
# elif (chosen_image_configuration == "two-in-one"):
# #filename_combined = fd.askopenfilename(title="Select a File or Directory",
# # filetypes=[("All files and directories", "*.*")])
# filename_combined = fd.askopenfilenames()
# #filename_combined = fd.askdirectory()
# self.text_path_to_input_combined.delete('1.0', END)
# self.text_path_to_input_combined.insert(1.0, filename_combined)
# self.text_single_path_to_input_channel1.delete('1.0', END)
# self.text_single_path_to_input_channel2.delete('1.0', END)
def select_files_or_directory(self):
if self.select_mode.get() == "file":
paths = fd.askopenfilename(title="Select File")
else:
paths = fd.askdirectory(title="Select Directory")
self.text_path.delete('1.0', END)
self.text_path.insert(1.0, paths)
#def enable_text_boxes(self):
# self.text_path_to_input_combined['state'] = 'normal'
# self.text_single_path_to_input_channel1['state'] = 'normal'
# self.text_single_path_to_input_channel2['state'] = 'normal'
#def disable_text_boxes(self):
# self.text_path_to_input_combined['state'] = 'disabled'
# self.text_single_path_to_input_channel1['state'] = 'disabled'
# self.text_single_path_to_input_channel2['state'] = 'disabled'
def manage_cell_types(self):
self.cell_type_manager.open_manage_window()
def set_default_settings_for_global_imaging(self):
self.check_box_channel_alignment.select()
self.check_box_frame_by_frame_registration.deselect()
self.check_box_background_subtraction_in_pipeline.deselect()
self.check_box_deconvolution_in_pipeline.deselect()
self.update_deconvolution()
# self.option_menu_deconvolution.config(state=DISABLED)
self.check_box_bleaching_correction.deselect()
self.update_bleaching_correction()
# self.option_menu_bleaching_correction.config(state=DISABLED)
self.check_box_shape_normalization.deselect()
self.update_settings_shape_normalization()
self.check_box_hotspot_detection.deselect()
self.check_box_dartboard_projection.deselect()
def set_default_settings_for_local_imaging(self):
self.check_box_channel_alignment.select()
self.check_box_frame_by_frame_registration.deselect()
self.check_box_background_subtraction_in_pipeline.select()
self.set_default_decon_parameters()
self.check_box_bleaching_correction.select()
self.option_menu_bleaching_correction.config(state=NORMAL)
self.bleaching_correction_algorithm.set('additiv no fit')
self.check_box_shape_normalization.select()
self.update_settings_shape_normalization()
self.check_box_hotspot_detection.select()
self.check_box_dartboard_projection.select()
self.check_box_bead_contacts.select()
self.update_bead_contact()
def set_default_decon_parameters(self):
self.check_box_deconvolution_in_pipeline.select()
self.option_menu_deconvolution.config(state=NORMAL)
self.deconvolution_algorithm.set('LR')
self.text_psf_type.delete(1.0, END)
self.text_psf_type.insert(1.0, "confocal")
self.text_psf_lambdaEx_ch1.delete(1.0, END)
self.text_psf_lambdaEx_ch1.insert(1.0, "488")
self.text_psf_lambdaEm_ch1.delete(1.0, END)
self.text_psf_lambdaEm_ch1.insert(1.0, "520")
self.text_psf_lambdaEx_ch2.delete(1.0, END)
self.text_psf_lambdaEx_ch2.insert(1.0, "488")
self.text_psf_lambdaEm_ch2.delete(1.0, END)
self.text_psf_lambdaEm_ch2.insert(1.0, "600")
self.text_psf_numAper.delete(1.0, END)
self.text_psf_numAper.insert(1.0, "1.4")
self.text_psf_magObj.delete(1.0, END)
self.text_psf_magObj.insert(1.0, "100")
self.text_psf_rindexObj.delete(1.0, END)
self.text_psf_rindexObj.insert(1.0, "1.518")
self.text_psf_rindexSp.delete(1.0, END)
self.text_psf_rindexSp.insert(1.0, "1.518")
self.text_psf_ccdSize.delete(1.0, END)
self.text_psf_ccdSize.insert(1.0, "6450")
def choose_results_directory_clicked(self):
self.select_results_directory()
def select_results_directory(self):
results_directory = fd.askdirectory()
self.text_results_directory.delete('1.0', END)
self.text_results_directory.insert(1.0, results_directory)
def write_input_to_config_file(self):
file = open("config.toml", "w")
data = self.get_parameters()
tomlkit.dump(data, file)
file.close()
def add_cell_type_clicked(self):
pass
def run_main_loop(self):
self.window.mainloop()
def close_window(self):
self.window.destroy()
class CellTypeManager:
def __init__(self, root, cell_types, option_menu_cell_types, selected_cell_type):
self.root = root
self.cell_types = cell_types
self.option_menu_cell_types = option_menu_cell_types
self.selected_cell_type = selected_cell_type
self.parameters_dict = {"jurkat": {},
"NK": {},
"primary": {}}
def open_manage_window(self):
manage_window = Toplevel(self.root)
manage_window.title("Manage Cell Types")
self.listbox = Listbox(manage_window, width=30)
self.listbox.pack(padx=10, pady=10, side=LEFT, fill=BOTH)
for cell_type in self.cell_types:
self.listbox.insert(END, cell_type)
add_button = Button(manage_window, text="Add Cell Type", command=self.add_cell_type)
add_button.pack(pady=5)