pylance standardization

src/analysis/intergroupstats.py

@@ -1,20 +1,29 @@
 """
 Filename: intergroupstats.py
 Description: Logic for the Inter-Group Stats 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 run_roi_paired_contrast_analysis, run_roi_second_level_analysis, aggregate_channel_contrasts_to_roi
 from src.shared.flaresbasewidget import InterGroupUIMixin, FlaresBaseWidget
 from src.shared.shareddata import APP_NAME
 
 
-PARAMETERIZED_INDEXES = {
+PARAMETERIZED_INDEXES: dict[int, list[dict[str, Any]]] = {
     0: [
         {
             "key": "p_threshold",
@@ -148,40 +157,64 @@ DESCRIPTION = """0. ROI vs. Zero (run_roi_second_level_analysis)
 
 
 class InterGroupStatsWidget(InterGroupUIMixin, FlaresBaseWidget):
-    def __init__(self, haemo_dict, cha, df_ind, design_matrix, contrast_results, group, json_location):
+    
+    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],
+        json_location: str | Path
+    ) -> None:
+        
         super().__init__("InterGroupStats")
         self.setWindowTitle(f"Inter-Group Stats 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.json_location = json_location
 
         self.setup_inter_group_ui(["0 (ROI vs. Zero)", "1 (Paired ROI Contrast)", "2 (Joint Contrast, ROI-Aggregated)"], placeholder_text=DESCRIPTION)
 
+
     def process_request(self):
-        request = self.get_common_request_data(PARAMETERIZED_INDEXES, self.json_location, self.contrast_results)
+        request = self.get_common_request_data(PARAMETERIZED_INDEXES, self.json_location, self.contrast_results_dict)
         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     
 
-        all_cha = pd.DataFrame()
+        param_values = cast(dict[int | str, dict[str, Any]], raw_params)
+
+        all_cha = 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)
 
@@ -189,10 +222,10 @@ class InterGroupStatsWidget(InterGroupUIMixin, FlaresBaseWidget):
         p_haemo = self.haemo_dict.get(file_path)
 
         # Concatenate individual ROI stats (df_ind) for all chosen subjects
-        df_group = pd.DataFrame()
+        df_group = 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)
 
@@ -226,7 +259,7 @@ class InterGroupStatsWidget(InterGroupUIMixin, FlaresBaseWidget):
                     print(f"No ROI data matches the condition '{selected_event}'.")
                     continue
 
-                all_cha_filtered = pd.DataFrame()
+                all_cha_filtered = DataFrame()
                 if not all_cha.empty:
                     if selected_event and 'Condition' in all_cha.columns:
                         all_cha_filtered = all_cha[all_cha['Condition'] == selected_event]
@@ -304,9 +337,9 @@ class InterGroupStatsWidget(InterGroupUIMixin, FlaresBaseWidget):
                     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 condition_dfs is None:
                         print(f"   [MISSING] '{fp}' not found in contrast_results.")
                         continue