fix several flaek8 errors

.flake8

@@ -31,14 +31,10 @@ ignore =
     E401,
     F401,
     F811,
-    F841,
     F821,
-    FS001
     W503,
-    W504,
-    W605,
-    F541,
-    E902
+
+
 # for compatibility with black
 # https://black.readthedocs.io/en/stable/guides/using_black_with_other_tools.html#flake8
 extend-ignore = E203

.pre-commit-config.yaml

@@ -56,5 +56,5 @@ repos:
     rev: 7.0.0
     hooks:
     -   id: flake8
-        args: [--config, .flake8, --verbose, pydfc, rest_dFC, task_dFC]
+        args: [--config, .flake8, --verbose, pydfc, HCP_resting_state_analysis, task_dFC]
         additional_dependencies: [flake8-use-fstring]

HCP_resting_state_analysis/functions/dFC_funcs.py

@@ -708,7 +708,7 @@ def visualize_conn_mat_dict(
         cb_ax = fig.add_axes([0.91, b, 0.007, h])
     else:
         cb_ax = fig.add_axes([0.91, b, 0.01, h])
-    cbar = fig.colorbar(im, cax=cb_ax, shrink=0.8)  # shrink=0.8??
+    fig.colorbar(im, cax=cb_ax, shrink=0.8)  # shrink=0.8??
 
     if save_image:
         folder = output_root[: output_root.rfind("/")]
@@ -880,12 +880,12 @@ def visualize_conn_mat_2D_dict(
     if not node_networks is None:
         fig.subplots_adjust(wspace=0.45, hspace=0.50)
 
-    l, b, w, h = axs[-1][-1].get_position().bounds
+    _, _, _, h = axs[-1][-1].get_position().bounds
     if node_networks is None:
         cb_ax = fig.add_axes([0.91, 0.5 - h / 2, 0.007, h])
     else:
         cb_ax = fig.add_axes([0.91, 0.5 - h / 2, 0.015, h])
-    cbar = fig.colorbar(im, cax=cb_ax, shrink=0.8)  # shrink=0.8??
+    fig.colorbar(im, cax=cb_ax, shrink=0.8)  # shrink=0.8??
 
     if save_image:
         folder = output_root[: output_root.rfind("/")]
@@ -1415,9 +1415,6 @@ def estimate_group_FCS(self, time_series_dict):
     def group_dFCM_assess(self, time_series_dict):
 
         # time_series_dict is a dict of time_series
-
-        SUBJ_s_dFCM_dict = {}
-
         SUBJECTs = common_subj_lst(time_series_dict)
 
         if self.params["n_jobs"] is None:
@@ -2103,7 +2100,7 @@ def visualize_TPM(self, normalize=True, save_image=False, output_root=None):
 
         plt.figure(figsize=(5, 5))
         plt.imshow(np.squeeze(C), interpolation="nearest", aspect="equal", cmap="jet")
-        cb = plt.colorbar(shrink=0.8)
+        plt.colorbar(shrink=0.8)
         plt.title(self.measure_name + " TPM")
 
         if save_image:

HCP_resting_state_analysis/functions/post_analysis_funcs.py

@@ -174,7 +174,7 @@ def plot_rois(node_networks, nodes_locs, save_image=False, output_root=None):
             axes=axes[i],
         )
 
-    title = f"Resting State Networks"
+    title = "Resting State Networks"
     # set subplot titles
     for i, network in enumerate(networks):
         axes[i].title.set_text(f"{network} network")
@@ -1123,7 +1123,7 @@ def plot_TSNE(
         ax = fig.add_subplot(projection="3d")
         sample_measure_array = np.array(sample_measure_lst)
         for measure in measures_lst:
-            scatter = ax.scatter(
+            ax.scatter(
                 X_embedded[sample_measure_array == measure, 0],
                 X_embedded[sample_measure_array == measure, 1],
                 X_embedded[sample_measure_array == measure, 2],

HCP_resting_state_analysis/post_analysis.py

@@ -41,7 +41,7 @@
 
 if not num_subj2include is None:
     ALL_RECORDS = ALL_RECORDS[:num_subj2include]
-    print("*** %d subjects were included." % (num_subj2include))
+    print(f"*** {num_subj2include} subjects were included.")
 
 FILTERS = [key for key in output]
 print(FILTERS)

pydfc/comparison/plotting.py

@@ -993,7 +993,7 @@ def plot_TSNE(
         ax = fig.add_subplot(projection="3d")
         sample_measure_array = np.array(sample_measure_lst)
         for measure in measures_lst:
-            scatter = ax.scatter(
+            ax.scatter(
                 X_embedded[sample_measure_array == measure, 0],
                 X_embedded[sample_measure_array == measure, 1],
                 X_embedded[sample_measure_array == measure, 2],

pydfc/dfc_utils.py

@@ -742,7 +742,7 @@ def visualize_conn_mat_dict(
         cb_ax = fig.add_axes([0.91, b, 0.007, h])
     else:
         cb_ax = fig.add_axes([0.91, b, 0.01, h])
-    cbar = fig.colorbar(im, cax=cb_ax, shrink=0.8)  # shrink=0.8??
+    fig.colorbar(im, cax=cb_ax, shrink=0.8)  # shrink=0.8??
 
     if save_image:
         folder = output_root[: output_root.rfind("/")]
@@ -919,7 +919,7 @@ def visualize_conn_mat_2D_dict(
         cb_ax = fig.add_axes([0.91, 0.5 - h / 2, 0.007, h])
     else:
         cb_ax = fig.add_axes([0.91, 0.5 - h / 2, 0.015, h])
-    cbar = fig.colorbar(im, cax=cb_ax, shrink=0.8)  # shrink=0.8??
+    fig.colorbar(im, cax=cb_ax, shrink=0.8)  # shrink=0.8??
 
     if save_image:
         folder = output_root[: output_root.rfind("/")]

pydfc/multi_analysis.py

@@ -205,9 +205,6 @@ def estimate_group_FCS(self, time_series_dict):
     def group_dFC_assess(self, time_series_dict):
 
         # time_series_dict is a dict of time_series
-
-        SUBJ_s_dFC_dict = {}
-
         SUBJECTs = common_subj_lst(time_series_dict)
 
         if self.params["n_jobs"] is None:

pydfc/task_utils.py

@@ -69,7 +69,7 @@ def plot_task_dFC(task_labels, dFC_lst, event_types, Fs_mri, TR_step=12):
     scale_task_plot = 20
 
     # plot task_data['event_labels']
-    fig = plt.figure(figsize=(50, 200))
+    plt.figure(figsize=(50, 200))
 
     ax = plt.gca()
 

tests/test_data_loader.py

@@ -25,7 +25,7 @@ def simulated_bold_data(tmp_path):
 
 
 def test_load(simulated_bold_data):
-    timeseries = nifti2timeseries(
+    nifti2timeseries(
         nifti_file=str(simulated_bold_data),
         n_rois=100,
         Fs=1 / 0.75,