add start of brain extraction script

fcest/features/brain_states.py

@@ -0,0 +1,59 @@
+import logging
+import os
+import sys
+
+from fcest.helpers.data import to_3d_format
+import math
+from nilearn import connectome
+import numpy as np
+import pandas as pd
+from scipy import cluster
+from sklearn.cluster import KMeans
+
+from helpers.array_operations import reconstruct_symmetric_matrix_from_tril
+from helpers.brain_states import compute_basis_state, extract_number_of_brain_state_switches
+from helpers.icc import compute_icc_scores_pingouin
+
+
+class BrainStatesExtractor:
+
+    def __init__(
+        self,
+        connectivity_metric: str,
+        num_time_series: int,
+        tvfc_estimates: np.array,
+    ) -> None:
+        """
+        Class for extracting brain states from TVFC estimates.
+
+        Parameters
+        ----------
+        connectivity_metric : str, default='correlation'
+        tvfc_estimates : np.array
+            Array of shape (num_subjects, num_time_steps, num_features).
+        """
+        logging.info("Initializing BrainStatesExtractor...")
+
+        self.connectivity_metric = connectivity_metric
+        self.num_time_steps = tvfc_estimates.shape[1]
+        self.num_time_series = num_time_series
+
+        self.tvfc_estimates_tril = tvfc_estimates.reshape(-1, tvfc_estimates.shape[-1])
+
+    def extract_brain_states(
+        self,
+        num_brain_states: int,
+    ):
+        """
+        Extract brain states from TVFC estimates.
+
+        Parameters
+        ----------
+        num_brain_states : int
+        """
+        return self.compute_basis_state(
+            all_subjects_tril_tvfc=self.tvfc_estimates_tril,
+            num_basis_states=num_brain_states,
+            num_time_series=self.num_time_series,
+            num_time_steps=self.num_time_steps,
+        )