add dps

dwi_ml/data/hdf5/hdf5_creation.py

@@ -136,6 +136,7 @@ class HDF5Creator:
     def __init__(self, root_folder: Path, out_hdf_filename: Path,
                  training_subjs: List[str], validation_subjs: List[str],
                  testing_subjs: List[str], groups_config: dict,
+                 dps_keys: List[str] = [],
                  step_size: float = None,
                  nb_points: int = None,
                  compress: float = None,
@@ -157,6 +158,8 @@ def __init__(self, root_folder: Path, out_hdf_filename: Path,
             List of subject names for each data set.
         groups_config: dict
             Information from json file loaded as a dict.
+        dps_keys: List[str]
+            List of keys to keep in data_per_streamline. Default: None.
         step_size: float
             Step size to resample streamlines. Default: None.
         nb_points: int
@@ -181,6 +184,7 @@ def __init__(self, root_folder: Path, out_hdf_filename: Path,
         self.validation_subjs = validation_subjs
         self.testing_subjs = testing_subjs
         self.groups_config = groups_config
+        self.dps_keys = dps_keys
         self.step_size = step_size
         self.nb_points = nb_points
         self.compress = compress
@@ -609,9 +613,11 @@ def _create_streamline_groups(self, ref, subj_input_dir, subj_id,
 
             if len(sft.data_per_point) > 0:
                 logging.debug('sft contained data_per_point. Data not kept.')
-            if len(sft.data_per_streamline) > 0:
-                logging.debug('sft contained data_per_streamlines. Data not '
-                              'kept.')
+
+            for dps_key in self.dps_keys:
+                logging.debug("    Include dps \"{}\" in the HDF5.".format(dps_key))
+                streamlines_group.create_dataset('dps_' + dps_key,
+                                                 data=sft.data_per_streamline[dps_key])
 
             # Accessing private Dipy values, but necessary.
             # We need to deconstruct the streamlines into arrays with

dwi_ml/data/hdf5/utils.py

@@ -78,6 +78,9 @@ def add_hdf5_creation_args(p: ArgumentParser):
                         "(Final concatenated standardized volumes and \n"
                         "final concatenated resampled/compressed "
                         "streamlines.)")
+    p.add_argument('--dps_keys', type=str, nargs='+', default=[],
+                   help="List of keys to keep in data_per_streamline. "
+                        "Default: Empty.")
 
 
 def add_streamline_processing_args(p: ArgumentParser):

scripts_python/dwiml_create_hdf5_dataset.py

@@ -87,7 +87,9 @@ def prepare_hdf5_creator(args):
     # Instantiate a creator and perform checks
     creator = HDF5Creator(Path(args.dwi_ml_ready_folder), args.out_hdf5_file,
                           training_subjs, validation_subjs, testing_subjs,
-                          groups_config, args.step_size,
+                          groups_config,
+                          args.dps_keys,
+                          args.step_size,
                           args.nb_points,
                           args.compress_th,
                           args.remove_invalid,