add space to fname, fix tau computation

Author: 62442katieb

.gitignore

@@ -62,3 +62,6 @@ var/
 **.pyc
 **.egg*
 **/__pycache__/**
+idconn/connectivity/__pycache__/__init__.cpython-37.pyc
+__pycache__/versioneer.cpython-37.pyc
+idconn/__pycache__/_version.cpython-37.pyc

idconn/connectivity/build_networks.py

@@ -113,7 +113,7 @@ def task_connectivity(layout, subject, session, task, atlas, confounds, connecti
         ex_bold = image.index_img(bold_file[0], 2)
         display = plotting.plot_epi(ex_bold)
         display.add_contours(atlas)
-        display.savefig(join(deriv_dir,  f'sub-{subject}', f'ses-{session}', 'func', f'sub-{subject}_ses-{session}_task-{task}_run-{run}_desc-{atlas_name}_overlay.png'))
+        display.savefig(join(deriv_dir,  f'sub-{subject}', f'ses-{session}', 'func', f'sub-{subject}_ses-{session}_task-{task}_run-{run}_space-MNI152NLin2009cAsym_space-{atlas_name}_overlay.png'))
 
         print(f'BOLD file located at {bold_file}\nTR = {tr}s')
 
@@ -156,7 +156,7 @@ def task_connectivity(layout, subject, session, task, atlas, confounds, connecti
         corrmat_df = pd.DataFrame(index=np.arange(1, avg_corrmat.shape[0]+1), columns=np.arange(1, avg_corrmat.shape[0]+1),data=avg_corrmat)
         avg_corrmats[condition] = corrmat_df
         corrmat_file = join(deriv_dir,  
-                            f'sub-{subject}', f'ses-{session}', 'func', f'sub-{subject}_ses-{session}_task-{task}_condition-{condition}_desc-{atlas_name}_corrmat.tsv')
+                            f'sub-{subject}', f'ses-{session}', 'func', f'sub-{subject}_ses-{session}_task-{task}_desc-{condition}_space-MNI152NLin2009cAsym_atlas-{atlas_name}_corrmat.tsv')
         try:
             corrmat_df.to_csv(corrmat_file, sep='\t')
             files.append(corrmat_file)

idconn/connectivity/estimate_thresh.py

@@ -47,7 +47,7 @@ def connected_tau(corrmat, proportional=True):
     tau : float
         Highest vaue of tau (threshold) at which network becomes node-connected.
     '''
-    tau = 1
+    tau = 0.01
     connected = False
     while connected == False:
         if proportional:
@@ -56,5 +56,5 @@ def connected_tau(corrmat, proportional=True):
             w = bct.threshold_absolute(corrmat, tau)
         w_nx = nx.convert_matrix.from_numpy_array(w)
         connected = nx.algorithms.components.is_connected(w_nx)
-        tau -= 0.01
+        tau += 0.01
     return tau