Correcting the call to the misc module

connectomicslab · Mar 7, 2024 · ac6d210 · ac6d210
1 parent 61cb144
commit ac6d210
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Showing 2 changed files with 6 additions and 6 deletions.
diff --git a/clabtoolkit/dicomtools.py b/clabtoolkit/dicomtools.py
@@ -1,4 +1,4 @@
-import clabtoolkit as clt
+import clabtoolkit.misctools as cltmisc
 import os
 from glob import glob
 import subprocess
@@ -41,7 +41,7 @@ def _uncompress_dicom_session(dic_dir: str, subj_ids = None):
     for i, subj_id in enumerate(subj_ids):  # Loop along the IDs
         subj_dir = os.path.join(dic_dir, subj_id)
 
-        clt._printprogressbar(
+        cltmisc._printprogressbar(
             i + 1,
             nsubj,
             "Processing subject "
@@ -116,7 +116,7 @@ def _compress_dicom_session(dic_dir: str, subj_ids = None):
     for i, subj_id in enumerate(subj_ids):  # Loop along the IDs
         subj_dir = os.path.join(dic_dir, subj_id)
 
-        clt._printprogressbar(
+        cltmisc._printprogressbar(
             i + 1,
             nsubj,
             "Processing subject "

diff --git a/clabtoolkit/parcellationtools.py b/clabtoolkit/parcellationtools.py
@@ -1,6 +1,6 @@
 import numpy as np
 import pandas as pd
-import clabtoolkit as clt
+import clabtoolkit.misctools as cltmisc
 
 
 def _parc_tsv_table(codes, names, colors, tsv_filename):
@@ -30,7 +30,7 @@ def _parc_tsv_table(codes, names, colors, tsv_filename):
     seg_hexcol = []
     nrows, ncols = colors.shape
     for i in np.arange(0, nrows):
-        seg_hexcol.append(clt.rgb2hex(colors[i, 0], colors[i, 1], colors[i, 2]))
+        seg_hexcol.append(cltmisc.rgb2hex(colors[i, 0], colors[i, 1], colors[i, 2]))
 
     tsv_df = pd.DataFrame(
         {
@@ -74,7 +74,7 @@ def tissue_seg_table(tsv_filename):
     seg_hexcol = []
     nrows, ncols = seg_rgbcol.shape
     for i in np.arange(0, nrows):
-        seg_hexcol.append(clt.rgb2hex(seg_rgbcol[i, 0], seg_rgbcol[i, 1], seg_rgbcol[i, 2]))
+        seg_hexcol.append(cltmisc.rgb2hex(seg_rgbcol[i, 0], seg_rgbcol[i, 1], seg_rgbcol[i, 2]))
 
     seg_df = pd.DataFrame(
         {