Creating a Report for the conversion (openMetadataInitiative#50)

* create_report

* typo

* making report one object

* missing state

* adjusting report

* forgotten +1

* Experimental approaches

* returning the report

* dealing with list

bids2openminds/converter.py

@@ -1,19 +1,25 @@
-from warnings import warn
+import warnings
 from bids import BIDSLayout, BIDSValidator
 from openminds import Collection
 import os
 import click
 from . import main
 from . import utility
+from . import report
 
 
-def convert(input_path, save_output=False, output_path=None, multiple_files=False, include_empty_properties=False):
+def convert(input_path,  save_output=False, output_path=None, multiple_files=False, include_empty_properties=False, quiet=False):
     if not (os.path.isdir(input_path)):
         raise NotADirectoryError(
             f"The input directory is not valid, you have specified {input_path} which is not a directory."
         )
+    # TODO use BIDSValidator to check if input directory is a valid BIDS directory
     # if not(BIDSValidator().is_bids(input_path)):
     #  raise NotADirectoryError(f"The input directory is not valid, you have specified {input_path} which is not a BIDS directory.")
+
+    if quiet:
+        warnings.filterwarnings('ignore')
+
     collection = Collection()
     bids_layout = BIDSLayout(input_path)
 
@@ -53,12 +59,15 @@ def convert(input_path, save_output=False, output_path=None, multiple_files=Fals
 
         collection.save(output_path, individual_files=multiple_files,
                         include_empty_properties=include_empty_properties)
-        print(
-            f"Conversion was successful, the openMINDS file is in {output_path}")
-        return collection
+
+    if not quiet:
+        print(report.create_report(dataset, dataset_version, collection,
+                                   dataset_description, input_path, output_path))
+
     else:
         print("Conversion was successful")
-        return collection
+
+    return collection
 
 
 @click.command()
@@ -67,9 +76,10 @@ def convert(input_path, save_output=False, output_path=None, multiple_files=Fals
 @click.option("--single-file", "multiple_files", flag_value=False, default=False, help="Save the entire collection into a single file (default).")
 @click.option("--multiple-files", "multiple_files", flag_value=True, help="Each node is saved into a separate file within the specified directory. 'output-path' if specified, must be a directory.")
 @click.option("-e", "--include-empty-properties", is_flag=True, default=False, help="Whether to include empty properties in the final file.")
-def convert_click(input_path, output_path, multiple_files, include_empty_properties):
+@click.option("-q", "--quiet", is_flag=True, default=False, help="Not generate the final report and no warning.")
+def convert_click(input_path, output_path, multiple_files, include_empty_properties, quiet):
     convert(input_path, save_output=True, output_path=output_path,
-            multiple_files=multiple_files, include_empty_properties=include_empty_properties)
+            multiple_files=multiple_files, include_empty_properties=include_empty_properties, quiet=quiet)
 
 
 if __name__ == "__main__":

bids2openminds/report.py

@@ -0,0 +1,116 @@
+import os
+
+
+def create_report(dataset, dataset_version, collection, dataset_description, input_path, output_path):
+    subject_number = 0
+    subject_state_numbers = []
+    file_bundle_number = 0
+    files_number = 0
+    behavioral_protocols_numbers = 0
+
+    for item in collection:
+        if item.type_ == "https://openminds.ebrains.eu/core/Subject":
+
+            subject_number += 1
+            subject_state_numbers.append(len(item.studied_states))
+
+        if item.type_ == "https://openminds.ebrains.eu/core/File":
+
+            files_number += 1
+
+        if item.type_ == "https://openminds.ebrains.eu/core/FileBundle":
+
+            file_bundle_number += 1
+
+        if item.type_ == "https://openminds.ebrains.eu/core/BehavioralProtocol":
+
+            behavioral_protocols_numbers += 1
+
+    experimental_approaches_list = ""
+    if dataset_version.experimental_approaches is not None:
+        for approache in dataset_version.experimental_approaches:
+            experimental_approaches_list += f"{approache.name}\n"
+
+    data_types_list = ""
+    if dataset_version.data_types is not None:
+        if isinstance(dataset_version.data_types, list):
+            for data_type in dataset_version.data_types:
+                data_types_list += f"{data_type.name}\n"
+        else:
+            data_types_list = f"{dataset_version.data_types.name}\n"
+
+    author_list = ""
+    i = 1
+    if dataset_version.authors is not None:
+        for author in dataset_version.authors:
+            if author.family_name is not None:
+                author_list += f"  {i}. {author.family_name}, {author.given_name}\n"
+                i += 1
+            else:
+                author_list += f"  {i}. ___, {author.given_name}\n"
+                i += 1
+
+    min_subject_state_numbers = min(subject_state_numbers)
+    max_subject_state_numbers = max(subject_state_numbers)
+    if min_subject_state_numbers == max_subject_state_numbers:
+        text_subject_state_numbers = str(min_subject_state_numbers)
+    else:
+        text_subject_state_numbers = f"min={min_subject_state_numbers}, max={max_subject_state_numbers}"
+
+    report = f"""
+Conversion Report
+=================  
+Conversion was successful, the openMINDS file is in {output_path}
+
+Dataset title : {dataset.full_name}
+
+
+Experimental approaches detected:
+------------------------------------------ 
+{experimental_approaches_list}
+
+Detected data types:
+------------------------------------------
+{data_types_list}
+
+The following elements were converted:  
+------------------------------------------   
++ number of authors : {len(dataset_version.authors or [])}
++ number of converted subjects: {subject_number}  
++ number of states per subject: {text_subject_state_numbers}
++ number of files: {files_number} 
++ number of file bundles: {file_bundle_number}
++ number of techniques: {len(dataset_version.techniques or [])}
++ number of behavioral protocols: {behavioral_protocols_numbers}
+
+
+
+**Important Notes**
+------------------------------------------ 
+
+Authors:
+    The conversion of authors is not reliable due to missing source convention.
+    The converter may fail in detecting family vs given name.
+    The converter will fail in detecting organizations.
+    The following persons (family name, given name) were converted, : 
+{author_list}
+
+Subject States:
+    There are as many subject states as sessions for each subject.
+    Please modify to your needs (divide into more or merge into fewer subject states).
+
+Behavioral protocols:
+    The conversion of behavioral protocols is incomplete.
+    Only the task-label is extracted as name and internal identifier of a behavioral protocol.
+    Please adjust to your needs.
+ 
+"""
+    if "GeneratedBy" in dataset_description:
+        report = report+"+Dataset is derivative, derivative data are ignored for now\n"
+
+    derivatives_path = os.path.join(
+        input_path, "derivatives")
+    if os.path.isdir(derivatives_path):
+        report = report+"+ Dataset contains derivative, derivative data are ignored for now\n"
+
+    return report