Redirect nypipe crash output to logging directory.

clpipe/config_json_parser.py

@@ -89,8 +89,8 @@ def setup_project(self, project_title, project_dir, source_data):
         self.setup_intensity_normalization(os.path.join(self.config['FMRIPrepOptions']['OutputDirectory'], "fmriprep"),
                                             None,
                                             os.path.join(self.config['ProjectDirectory'], 'data_postproc', 'normalized'),
-                                            None,
-                                            None)
+                                            None, None,
+                                            os.path.join(self.config['ProjectDirectory'], "logs", "intensity_normalization_logs"))
         processing_streams = self.get_processing_stream_names()
         if processing_streams:
             for stream in processing_streams:
@@ -169,7 +169,7 @@ def setup_postproc(self, target_dir, target_suffix, output_dir, output_suffix, b
             self.config[target_output]['LogDirectory'] = os.path.join(self.config['ProjectDirectory'], 'logs', log_target)
         os.makedirs(self.config[target_output]['LogDirectory'], exist_ok=True)
 
-    def setup_intensity_normalization(self, target_dir, target_suffix, output_dir, output_suffix, method):
+    def setup_intensity_normalization(self, target_dir, target_suffix, output_dir, output_suffix, method, log_dir):
         target_output = 'IntensityNormalizationOptions'
 
         if target_dir is not None:
@@ -183,6 +183,9 @@ def setup_intensity_normalization(self, target_dir, target_suffix, output_dir, o
             self.config[target_output]['OutputSuffix'] = output_suffix
         if method is not None:
             self.config[target_output]['Method'] = method
+        if log_dir is not None:
+            self.config[target_output]['LogDirectory'] = os.path.abspath(log_dir)
+            os.makedirs(self.config[target_output]['LogDirectory'], exist_ok=True)
 
     def setup_heudiconv(self, dicom_directory, heuristic_file, output_directory):
         if dicom_directory is not None:

clpipe/data/defaultConfig.json

@@ -74,7 +74,8 @@
 		"TargetSuffix": "space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz",
 		"OutputDirectory": "",
 		"OutputSuffix": "",
-		"Method": "10000_globalmedian"
+		"Method": "10000_globalmedian",
+		"LogDirectory": ""
 	},
 	"BetaSeriesOptions": {
 		"TargetDirectory": "",

clpipe/intensity_normalization.py

@@ -88,7 +88,7 @@ def intensity_normalization(subjects:list=None, config_file:str=None, method:str
     # If provided, override project config with parameter config
     config.config_updater(config_file)
     # For those provided, replace intensity normalization config values with parameter values
-    config.setup_intensity_normalization(target_dir, target_suffix, output_dir, output_suffix, method)
+    config.setup_intensity_normalization(target_dir, target_suffix, output_dir, output_suffix, method, log_dir)
 
     target_dir = Path(config.config["IntensityNormalizationOptions"]["TargetDirectory"])
     target_suffix = config.config["IntensityNormalizationOptions"]["TargetSuffix"]
@@ -107,7 +107,7 @@ def intensity_normalization(subjects:list=None, config_file:str=None, method:str
         normalize_subject(config, f'sub-{subject}')
 
 def calculate_10000_global_median(in_path: os.PathLike, out_path:os.PathLike,
-        mask_path: os.PathLike=None, base_dir: os.PathLike=None):
+        mask_path: os.PathLike=None, base_dir: os.PathLike=None, crashdump_dir: os.PathLike=None):
     """Perform intensity normalization using the 10,000 global median method.
 
     Args:
@@ -127,11 +127,15 @@ def calculate_10000_global_median(in_path: os.PathLike, out_path:os.PathLike,
     div_median_node = pe.Node(BinaryMaths(operation="div", out_file=out_path), name="div_median")
 
     workflow = pe.Workflow(name='10000_global_median', base_dir=base_dir)
+    if crashdump_dir is not None:
+        workflow.config['execution']['crashdump_dir'] = crashdump_dir
+
     workflow.connect(mul_10000_node, "out_file", div_median_node, "in_file")
     workflow.connect(median_node, "out_stat", div_median_node, "operand_value")
     workflow.run()
 
-def calculate_100_voxel_mean(in_path: os.PathLike, out_path: os.PathLike, base_dir: os.PathLike=None):
+def calculate_100_voxel_mean(in_path: os.PathLike, out_path: os.PathLike, base_dir: os.PathLike=None,
+    crashdump_dir: os.PathLike=None):
     """Perform intensity normalization using the 100 voxel mean method.
 
     Args:
@@ -145,6 +149,8 @@ def calculate_100_voxel_mean(in_path: os.PathLike, out_path: os.PathLike, base_d
     div_mean_node = pe.Node(BinaryMaths(operation='div', out_file=out_path), name="div_mean") #operand_file=mean_path
 
     workflow = pe.Workflow(name='100_voxel_mean', base_dir=base_dir)
+    if crashdump_dir is not None:
+        workflow.config['execution']['crashdump_dir'] = crashdump_dir
 
     workflow.connect(mul100_node, "out_file", div_mean_node, "in_file")
     workflow.connect(mean_node, "out_file",  div_mean_node, "operand_file")

nipype.cfg

@@ -0,0 +1,6 @@
+[logging]
+workflow_level = DEBUG
+log_directory = ./logs
+
+[execution]
+crashfile_format = txt

tests/conftest.py

@@ -1,9 +1,11 @@
 import pytest
 import numpy as np
+import sys
 import nibabel as nib
 from pathlib import Path
 from click.testing import CliRunner
 
+sys.path.append('../clpipe')
 from clpipe.project_setup import project_setup
 from clpipe.config_json_parser import ClpipeConfigParser
 

tests/test_intensity_normalization.py

@@ -174,7 +174,8 @@ def test_calculate_10000_global_median(tmp_path, random_nii):
 
 def test_calculate_10000_global_median_masked(tmp_path, random_nii, random_nii_mask):
     out_path = tmp_path / "normalized.nii.gz"
-    calculate_10000_global_median(random_nii, out_path, mask_path=random_nii_mask, base_dir=tmp_path)
+    calculate_10000_global_median(random_nii, out_path, mask_path=random_nii_mask, base_dir=tmp_path,
+        crashdump_dir=tmp_path)
 
     # Load random nii data and a mask
     random_nii_data = nib.load(random_nii).get_fdata()
@@ -189,7 +190,7 @@ def test_calculate_10000_global_median_masked(tmp_path, random_nii, random_nii_m
 
 def test_calculate_100_voxel_mean(tmp_path, random_nii):
     out_path = tmp_path / "normalized.nii.gz"
-    calculate_100_voxel_mean(random_nii, out_path, base_dir=tmp_path)
+    calculate_100_voxel_mean(random_nii, out_path, base_dir=tmp_path, crashdump_dir=tmp_path)
 
     random_nii_data = nib.load(random_nii).get_fdata()
     normalized_data = nib.load(out_path).get_fdata()