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pylance standardization

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tyler
2026-07-21 00:54:51 -07:00
parent 2b019c1bc0
commit 8b017005c5
20 changed files with 608 additions and 277 deletions
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src/analysis/intergroupbrainimage.py
+55 -24
View File
@@ -1,20 +1,29 @@
"""
Filename: intergroupbrainimage.py
Description: Logic for the Inter-Group Brain & Image analysis window
Note: Compliant with pylance strict type checking
Author: Tyler de Zeeuw
License: GPL-3.0
"""
# Built-in Imports
from pathlib import Path
from typing import Any, cast
# External library imports
import pandas as pd
from pandas import DataFrame
from mne import Annotations
from mne.io.base import BaseRaw
from flares import aggregate_fnirs_group_geometry, plot_fir_model_results, brain_3d_visualization
from src.shared.flaresbasewidget import InterGroupUIMixin, FlaresBaseWidget
from src.shared.shareddata import APP_NAME
from mne.io import BaseRaw
PARAMETERIZED_INDEXES = {
PARAMETERIZED_INDEXES: dict[int, list[dict[str, Any]]] = {
0: [
{
"key": "lower_bound",
@@ -74,15 +83,24 @@ PARAMETERIZED_INDEXES = {
class InterGroupBrainImageWidget(InterGroupUIMixin, FlaresBaseWidget):
def __init__(self, haemo_dict, cha, df_ind, design_matrix, contrast_results, group):
def __init__(
self,
haemo_dict: dict[str | Path, BaseRaw],
cha_dict: dict[str, DataFrame],
df_ind_dict: dict[str, DataFrame],
design_matrix_dict: dict[str, DataFrame],
contrast_results_dict: dict[str, dict[str, Any]],
group_dict: dict[str, str]
) -> None:
super().__init__("InterGroupBrainImage")
self.setWindowTitle(f"Inter-Group Brain & Image Viewer - {APP_NAME.upper()}")
self.haemo_dict = haemo_dict
self.cha = cha
self.df_ind = df_ind
self.design_matrix = design_matrix
self.contrast_results = contrast_results
self.group = group
self.cha_dict = cha_dict
self.df_ind_dict = df_ind_dict
self.design_matrix_dict = design_matrix_dict
self.contrast_results_dict = contrast_results_dict
# self.group_dict = group_dict
self.setup_inter_group_ui(["0 (GLM Results)", "1 (Significance)", "2 (Brain Activity Visualization)",])
@@ -92,35 +110,45 @@ class InterGroupBrainImageWidget(InterGroupUIMixin, FlaresBaseWidget):
if request is None:
return
(selected_event, selected_file_paths, selected_indexes, param_values,) = request
(selected_event, selected_file_paths, selected_indexes, raw_params) = request
param_values = cast(dict[int | str, dict[str, Any]], raw_params)
all_cha = pd.DataFrame()
for file_path in selected_file_paths:
haemo_obj = self.haemo_dict.get(file_path)
if haemo_obj is None:
continue
if selected_event:
participant_events = set(haemo_obj.annotations.description)
raw_annotations = getattr(haemo_obj, "annotations", None)
if raw_annotations is not None:
annotations = cast(Annotations, raw_annotations)
descriptions = cast(list[str], list(annotations.description))
participant_events: set[str] = set(descriptions)
else:
participant_events: set[str] = set()
if selected_event not in participant_events:
print(f"Skipping {self.participant_map[file_path]}: Event '{selected_event}' not found.")
continue
if haemo_obj is None:
continue
cha_df = self.cha.get(file_path)
cha_df = self.cha_dict.get(file_path)
if cha_df is not None:
all_cha = pd.concat([all_cha, cha_df], ignore_index=True)
# Pass the necessary arguments to each method
file_path = selected_file_paths[0]
p_haemo = self.haemo_dict.get(file_path)
p_design_matrix = self.design_matrix.get(file_path)
p_design_matrix = self.design_matrix_dict.get(file_path)
df_group = pd.DataFrame()
if selected_file_paths:
for file_path in selected_file_paths:
df = self.df_ind.get(file_path)
df = self.df_ind_dict.get(file_path)
if df is not None:
df_group = pd.concat([df_group, df], ignore_index=True)
@@ -147,9 +175,9 @@ class InterGroupBrainImageWidget(InterGroupUIMixin, FlaresBaseWidget):
print(f"Missing parameters for index {idx}, skipping.")
continue
all_contrasts = []
all_contrasts: list[DataFrame] = []
for fp in selected_file_paths:
condition_dfs = self.contrast_results.get(fp, {})
condition_dfs = self.contrast_results_dict.get(fp, {})
if selected_event in condition_dfs:
df = condition_dfs[selected_event].copy()
df["ID"] = fp
@@ -159,7 +187,8 @@ class InterGroupBrainImageWidget(InterGroupUIMixin, FlaresBaseWidget):
print("No contrast data found for selected participants and event.")
return
df_contrasts = pd.concat(all_contrasts, ignore_index=True)
# TODO: look at intergroupstats and figure out what to do
_ = pd.concat(all_contrasts, ignore_index=True)
#flares.run_second_level_analysis(df_contrasts, p_haemo, p_val, graph_bounds)
elif idx == 2:
@@ -173,13 +202,15 @@ class InterGroupBrainImageWidget(InterGroupUIMixin, FlaresBaseWidget):
print(f"Missing parameters for index {idx}, skipping.")
continue
raw_list = [self.haemo_dict.get(fp) for fp in selected_file_paths]
all_raw_objs = [self.haemo_dict.get(fp) for fp in selected_file_paths if self.haemo_dict.get(fp)]
if len(selected_file_paths) > 1:
print(f"Aggregating geometry for {len(selected_file_paths)} participants...")
processed_raw = aggregate_fnirs_group_geometry(raw_list)
if len(all_raw_objs) > 1:
processed_raw = aggregate_fnirs_group_geometry(all_raw_objs)
elif len(all_raw_objs) == 1 and all_raw_objs[0] is not None:
processed_raw = all_raw_objs[0].copy()
processed_raw.pick(picks="hbo") # type: ignore
else:
processed_raw = raw_list[0].copy().pick(picks="hbo")
processed_raw = None
brain_3d_visualization(processed_raw, all_cha, selected_event, t_or_theta=t_or_theta, show_optodes=show_optodes, show_text=show_text, brain_bounds=brain_bounds)