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Descriptor files #89

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2 changes: 1 addition & 1 deletion VERSION
Original file line number Diff line number Diff line change
@@ -1 +1 @@
0.0.2
0.0.3-a.1
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Yes, this change should not be part of this PR.

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Updating from the latest master should fix this.

8 changes: 7 additions & 1 deletion redcap_bridge/tests/test_utils.py
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
from redcap_bridge.utils import compress_record
from redcap_bridge.utils import compress_record, conversion_to_odml_table_descriptor
from diglab_utils.test_utils import test_directory, initialize_test_dir


Expand All @@ -13,3 +13,9 @@ def test_compressedCSV(initialize_test_dir):
exp = exp_file.read()
assert res == exp


def test_conversion_to_odml_table_descriptor(initialize_test_dir):
test_dir = test_directory / 'testfiles_redcap' / 'descriptors'

conversion_to_odml_table_descriptor(test_dir / 'Vision4Action_DATA_2023-04-13_1110.csv', session_number=5)
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this test is only checking if the code runs into an error so far. Could you extend this and also test the content of the converted file? Maybe you will need to add an odmltables reference test file to compare against.

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Yes, will change the test in priority


24 changes: 24 additions & 0 deletions redcap_bridge/utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -81,3 +81,27 @@ def remove_columns(csv_file, compressed_file=None):
def exportCSVtoXLS(csv_file, compressed_file=None):
read_file = pd.read_csv(csv_file, na_filter=False, dtype='str')
read_file.to_excel(r'Path', index=None, header=True)

def conversion_to_odml_table_descriptor(full_elabbook_csv, session_number):
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Can you add a keyword argument to automatically save this to a csv file if a filename is provided?

"""
Create odml descriptor file base on the full elabbook csv file
Args:
full_elabbook_csv: path to the full csv file
session_number: number of the session you want to create descriptor csv file
Returns:
descriptor_elabbook_csv: csv descriptor file of the specific session given
"""

df = pd.read_csv(full_elabbook_csv)

df_ses = df.loc[df['ses_number'] == session_number]

cols_to_melt = df_ses.columns[df_ses.columns.get_loc('ethical_protocol_id'):]

print(cols_to_melt)

df_melted = df_ses.melt(id_vars='record_id', value_vars=cols_to_melt)

df_melted = df_melted.rename(columns={'variable': 'Property name'})

print(df_melted.to_string())
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There is a set of mandatory columns for odmltables csv files. Can you check that all of them are present after the conversion and have values that are accepted by odmltables? E.g. the data type colum can only contain specific values that are understood by odmltables...