Merge pull request #34 from AdebayoBraimah/dev5

Dev5
AdebayoBraimah · Jun 10, 2021 · 2ea4d2a · 2ea4d2a
2 parents b053eaa + de65b0a
commit 2ea4d2a
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diff --git a/CHANGES.rst b/CHANGES.rst
@@ -1,6 +1,18 @@
 CHANGES
 =========
 
+0.2.0a6
+---------
+
+This version is an alpha release that contains several bug fixes.
+
+* BUG FIX: Removed the ``metadata`` fields ``EffectiveEchoSpacing`` and ``TotalReadoutTime`` as these fields were computed incorrectly, and thus failing BIDS validation.
+* BUG FIX: Fixed issue in which zero and non-zero b-values were included in the ``acq`` tag for ``dwis``, instead of either one or the other.
+* BUG FIX: The ``participants.tsv`` is correctly written to file.
+* BUG FIX: Added functionality to obtain the acqusition date and time for source data.
+* BUG FIX: Dropped unfilled BIDS metadata fields to avoid validation errors.
+* BUG FIX: Fixed output ``scans.tsv`` files to include all the necessary information to pass BIDS validation.
+
 0.2.0a5
 ---------
 

diff --git a/convert_source/batch_convert.py b/convert_source/batch_convert.py
@@ -320,20 +320,55 @@ def batch_proc(study_img_dir: str,
                         desc="Writing scan files",
                         position=0,
                         leave=True):
-            df: pd.DataFrame = export_bids_scans_dataframe(database=database,
-                                                        sub_id=sub,
-                                                        search_dict=search_dict,
-                                                        gzipped=gzip)
-            if len(df) == 0:
-                pass
+            try:
+                ses_list: List[str] = list_dir_files(pathname=os.path.join(out_dir,f"sub-{sub}"),
+                                                pattern="ses-*",
+                                                file_name_only=True)
+                ses_list: List[str] = [ x.replace('ses-','') for x in ses_list ]
+            except FileNotFoundError:
+                ses_list: List = []
+
+            if len(ses_list) == 0:
+                df: pd.DataFrame = export_bids_scans_dataframe(database=database,
+                                                            sub_id=sub,
+                                                            search_dict=search_dict,
+                                                            gzipped=gzip)
+
+                if len(df) == 0:
+                    continue
+                else:
+                    out_name: str = os.path.join(out_dir,f'sub-{sub}',f'sub-{sub}' + '_scans.tsv')
+
+                    if os.path.exists(out_name):
+                        os.remove(out_name)
+
+                    df.to_csv(out_name,
+                            sep='\t',
+                            na_rep='n/a',
+                            index=False,
+                            mode="a",
+                            encoding='utf-8')
             else:
-                out_name: str = os.path.join(out_dir,f'sub-{sub}',f'sub-{sub}' + '_scans.tsv')
-                df.to_csv(out_name,
-                        sep='\t',
-                        na_rep='',
-                        index=False,
-                        mode="w",
-                        encoding='utf-8')
+                for ses in ses_list:
+                    df: pd.DataFrame = export_bids_scans_dataframe(database=database,
+                                                            sub_id=sub,
+                                                            search_dict=search_dict,
+                                                            gzipped=gzip,
+                                                            ses_id=ses)
+                    if len(df) == 0:
+                        continue
+                    else:
+                        out_name: str = os.path.join(out_dir,f'sub-{sub}',f'ses-{ses}',f'sub-{sub}_ses-{ses}' + '_scans.tsv')
+
+                        if os.path.exists(out_name):
+                            os.remove(out_name)
+
+                        df.to_csv(out_name,
+                                sep='\t',
+                                na_rep='n/a',
+                                index=False,
+                                mode="a",
+                                encoding='utf-8')
 
     return (bids_imgs,
             bids_jsons,
@@ -941,11 +976,12 @@ def source_to_bids(sub_data: SubDataInfo,
 
                         if (modality_type.lower() == 'dwi' or modality_label.lower() == 'dwi') and append_dwi_info:
                             bvals: List[int] = get_bvals(img_data.bvals[i])
-                            echo_time: Union[int,str] = bids_dict["EchoTime"]
+                            echo_time: Union[int,str] = bids_dict.get("EchoTime",'')
                             _label: str = ""
                             for bval in bvals:
-                                if bval != 0:
-                                    _label += f"b{bval}"
+                                _label += f"b{bval}"
+                            if int(bvals[0]) == 0:
+                                modality_label: str = "sbref"
                             if echo_time:
                                 echo_time: float = float(echo_time) * 1000
                                 _label += f"TE{int(echo_time)}"
@@ -1310,11 +1346,12 @@ def nifti_to_bids(sub_data: SubDataInfo,
 
             if (modality_type.lower() == 'dwi' or modality_label.lower() == 'dwi') and append_dwi_info:
                 bvals: List[int] = get_bvals(img_data.bvals[0])
-                echo_time: Union[int,str] = bids_dict["EchoTime"]
+                echo_time: Union[int,str] = bids_dict.get("EchoTime",'')
                 _label: str = ""
                 for bval in bvals:
-                    if bval != 0:
-                        _label += f"b{bval}"
+                    _label += f"b{bval}"
+                if int(bvals[0]) == 0:
+                    modality_label: str = "sbref"
                 if echo_time:
                     echo_time: float = float(echo_time) * 1000
                     _label += f"TE{int(echo_time)}"
@@ -1839,7 +1876,7 @@ def create_participant_tsv(out_dir: str) -> Tuple[str,str]:
                             inplace=True)
         df_new.to_csv(participant_tsv,
                         sep='\t',
-                        na_rep='',
+                        na_rep='n/a',
                         index=False,
                         mode='w',
                         encoding='utf-8')
@@ -1857,7 +1894,7 @@ def create_participant_tsv(out_dir: str) -> Tuple[str,str]:
         df['participant_id'] = subs_list
         df.to_csv(participant_tsv,
                     sep='\t',
-                    na_rep='',
+                    na_rep='n/a',
                     index=False,
                     mode="w",
                     encoding='utf-8')

diff --git a/convert_source/cs_utils/bids_info.py b/convert_source/cs_utils/bids_info.py
@@ -137,10 +137,19 @@ def construct_bids_dict(meta_dict: Optional[Dict] = None,
     bids_dict: Dict = dict_multi_update(dictionary=bids_dict, **meta_dict)
     bids_dict: Dict = dict_multi_update(dictionary=bids_dict, **json_dict)
 
-    # Create ordered BIDS dictionary
+    # Create ordered BIDS dictionary and drop unfilled metadata fields from ordered BIDS dictionary
     ordered_bids_dict: OrderedDict = OrderedDict()
     for key in ordered_list:
-        ordered_bids_dict[key] = bids_dict[key]
+        val = bids_dict.get(key,'')
+        if (val == "") or (val is None):
+            continue
+        elif (key == "EffectiveEchoSpacing") or (key == "TotalReadoutTime"):
+            # NOTE: These two keys are being excluded entirely, as the current
+            #   calculations fail BIDS validation.
+            # TODO: Accurately compute 'EffectiveEchoSpacing' and 'TotalReadoutTime'
+            continue
+        else:
+            ordered_bids_dict[key] = bids_dict[key]
 
     return ordered_bids_dict
 

diff --git a/convert_source/cs_utils/const.py b/convert_source/cs_utils/const.py
@@ -54,72 +54,72 @@
 BIDS_INFO: Dict = {
     # Common metadata
     ## Scanner Hardware
-    "Manufacturer":"",
-    "ManufacturersModelName":"",
-    "DeviceSerialNumber":"",
-    "StationName":"",
-    "SoftwareVersions":"",
-    "HardcopyDeviceSoftwareVersion":"",
-    "MagneticFieldStrength":"",
-    "ReceiveCoilName":"",
-    "ReceiveCoilActiveElements":"",
-    "GradientSetType":"",
-    "MRTransmitCoilSequence":"",
-    "MatrixCoilMode":"",
-    "CoilCombinationMethod":"",
+    "Manufacturer":None,
+    "ManufacturersModelName":None,
+    "DeviceSerialNumber":None,
+    "StationName":None,
+    "SoftwareVersions":None,
+    "HardcopyDeviceSoftwareVersion":None,
+    "MagneticFieldStrength":None,
+    "ReceiveCoilName":None,
+    "ReceiveCoilActiveElements":None,
+    "GradientSetType":None,
+    "MRTransmitCoilSequence":None,
+    "MatrixCoilMode":None,
+    "CoilCombinationMethod":None,
     ## Sequence Specifics
-    "PulseSequenceType":"",
-    "ScanningSequence":"",
-    "SequenceVariant":"",
-    "ScanOptions":"",
-    "SequenceName":"",
-    "PulseSequenceDetails":"",
-    "NonlinearGradientCorrection":"",
+    "PulseSequenceType":None,
+    "ScanningSequence":None,
+    "SequenceVariant":None,
+    "ScanOptions":None,
+    "SequenceName":None,
+    "PulseSequenceDetails":None,
+    "NonlinearGradientCorrection":None,
     ## In-Plane Spatial Encoding
-    "NumberShots":"",
-    "ParallelReductionFactorInPlane":"",
-    "ParallelAcquisitionTechnique":"",
-    "PartialFourier":"",
-    "PartialFourierDirection":"",
-    "PhaseEncodingDirection":"",
-    "EffectiveEchoSpacing":"",
-    "TotalReadoutTime":"",
+    "NumberShots":None,
+    "ParallelReductionFactorInPlane":None,
+    "ParallelAcquisitionTechnique":None,
+    "PartialFourier":None,
+    "PartialFourierDirection":None,
+    "PhaseEncodingDirection":None,
+    "EffectiveEchoSpacing":None,
+    "TotalReadoutTime":None,
     ## Timing Parameters
-    "EchoTime":"",
-    "InversionTime":"",
-    "SliceTiming":"",
-    "SliceEncodingDirection":"",
-    "DwellTime":"",
+    "EchoTime":None,
+    "InversionTime":None,
+    "SliceTiming":None,
+    "SliceEncodingDirection":None,
+    "DwellTime":None,
     ## RF & Contrast
-    "FlipAngle":"",
-    "NegativeContrast":"",
+    "FlipAngle":None,
+    "NegativeContrast":None,
     ## Slice Acceleration
-    "MultibandAccelerationFactor":"",
+    "MultibandAccelerationFactor":None,
     ## Anatomical landmarks
-    "AnatomicalLandmarkCoordinates":"",
+    "AnatomicalLandmarkCoordinates":None,
     ## Institution information
-    "InstitutionName":"",
-    "InstitutionAddress":"",
-    "InstitutionalDepartmentName":"",
+    "InstitutionName":None,
+    "InstitutionAddress":None,
+    "InstitutionalDepartmentName":None,
     # Anat
-    "ContrastBolusIngredient":"",
+    "ContrastBolusIngredient":None,
     # Func
-    "RepetitionTime":"",
-    "TaskName":"",
-    "NumberOfVolumesDiscardedByScanner":"",
-    "NumberOfVolumesDiscardedByUser":"",
-    "DelayTime":"",
-    "AcquisitionDuration":"",
-    "DelayAfterTrigger":"",
-    "Instructions":"",
-    "TaskDescription":"",
-    "CogAtlasID":"",
-    "CogPOID":"",
+    "RepetitionTime":None,
+    "TaskName":None,
+    "NumberOfVolumesDiscardedByScanner":None,
+    "NumberOfVolumesDiscardedByUser":None,
+    "DelayTime":None,
+    "AcquisitionDuration":None,
+    "DelayAfterTrigger":None,
+    "Instructions":None,
+    "TaskDescription":None,
+    "CogAtlasID":None,
+    "CogPOID":None,
     # Fmap
-    "Units":"",
-    "IntendedFor":"",
+    "Units":None,
+    "IntendedFor":None,
     # Custom BIDS fields
-    "SourceDataFormat":"",
+    "SourceDataFormat":None,
     "BIDSVersion":DEFAULT_BIDS_VERSION,
     "ConvertSourceVersion": CS_VERSION
 }