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Merge pull request #153 from VisLab/develop
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Minor test and doc updates
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@VisLab
VisLab committed Feb 2, 2024
2 parents 6991ff6 + 1556262 commit 13b8843
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Showing 3 changed files with 70 additions and 53 deletions.
5 changes: 2 additions & 3 deletions hedweb/process_events.py
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Original file line number Diff line number Diff line change
Expand Up @@ -79,7 +79,7 @@ def process(self):
"""
if not self.command:
raise HedFileError('MissingCommand', 'Command is missing', '')
elif self.command == base_constants.COMMAND_GENERATE_SIDECAR:
elif self.command == base_constants.COMMAND_GENERATE_SIDECAR or self.command == base_constants.COMMAND_REMODEL:
pass
elif not self.schema or not \
isinstance(self.schema, (hedschema.hed_schema.HedSchema, hedschema.hed_schema_group.HedSchemaGroup)):
Expand Down Expand Up @@ -126,8 +126,7 @@ def assemble(self):
'definitions': DefinitionDict.get_as_strings(definitions),
'schema_version': self.schema.get_formatted_version(),
'msg_category': 'success', 'msg': 'Events file successfully expanded'}



def _assemble(self):
eligible_columns, missing_columns = separate_values(list(self.events.dataframe.columns), self.columns_included)
if self.expand_defs:
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118 changes: 68 additions & 50 deletions tests/test_events.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
import os
import json
from io import StringIO
import pandas as pd
import unittest
from werkzeug.test import create_environ
from werkzeug.wrappers import Request
Expand All @@ -14,16 +15,16 @@

class Test(TestWebBase):
cache_schemas = True

def get_event_proc(self, events_file, sidecar_file, schema_file):
events_proc = ProcessEvents()
events_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), events_file)
schema_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), schema_file)
events_proc.schema = load_schema(schema_path)
if schema_file:
schema_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), schema_file)
events_proc.schema = load_schema(schema_path)
if sidecar_file:
events_proc.sidecar = Sidecar(files=os.path.join(os.path.dirname(os.path.abspath(__file__)), sidecar_file))
if events_path:
events_proc.events = TabularInput(file=os.path.join(os.path.dirname(os.path.abspath(__file__)),
if events_file:
events_proc.events = TabularInput(file=os.path.join(os.path.dirname(os.path.abspath(__file__)),
events_file), sidecar=events_proc.sidecar)
events_proc.expand_defs = True
events_proc.columns_included = None
Expand Down Expand Up @@ -153,49 +154,66 @@ def test_events_validate_valid(self):
self.assertFalse(results['data'], 'should not have a data key when no validation errors')
self.assertEqual('success', results['msg_category'], 'should be success when no errors')

# def test_events_remodel_valid_no_hed(self):
# events_proc = self.get_event_proc('data/sub-002_task-FacePerception_run-1_events.tsv', None, None)
# events_proc.command = base_constants.COMMAND_REMODEL
#
# remodel_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
# 'data/simple_reorder_rmdl.json')
# df = events_proc.events.dataframe
# df_rows = len(df)
# df_cols = len(df.columns)
# with open(remodel_path, 'r') as fp:
# remodel_json = json.load(fp)
# remodeler = {'name': "simple_reorder_rmdl.json", 'operations': remodel_json}
# hed_schema = None
# sidecar = None
#
# with self.app.app_context():
# results = remodel(hed_schema, events, sidecar, remodeler)
# self.assertTrue(results['data'], 'remodel results should have a data key when successful')
# self.assertEqual('success', results['msg_category'], 'remodel msg_category should be success when no errors')
# # TODO: Test the rows and columns of result.

# def test_events_remodel_invalid_no_hed(self):
# # events_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
# 'data/sub-002_task-FacePerception_run-1_events.tsv')
# remodel_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
# 'data/simple_reorder_rmdl.json')
# events = TabularInput(file=events_path, name='wh_events')
# with open(remodel_path, 'r') as fp:
# remodeler = json.load(fp)
# hed_schema = None
# sidecar = None
# operation_0 = {'badoperation': 'remove_columns', 'description': 'bad structure',
# 'parameters': {'ignore_missing': True}}
# operation_1 = {'operation': 'unknown_command', 'description': 'bad command',
# 'parameters': {'ignore_missing': True}}
# operation_2 = {'command': 'remove_columns', 'description': 'bad parameters',
# 'parameters': {'ignore_missing': True}}
# operation_bad = [operation_0, remodeler[0], operation_1, remodeler[1], operation_2]
# remodel_bad = {'name': 'remodel_bad.json', 'operations': operation_bad}
# with self.app.app_context():
# results = remodel(hed_schema, events, sidecar, remodel_bad)
# self.assertTrue(results['data'], 'remodel results should have a data key when unsuccessful')
# self.assertEqual('warning', results['msg_category'], 'remodel msg_category should be success when no errors')
def test_events_remodel_valid_no_hed(self):
rmdl1 = [{
"operation": "remove_columns",
"description": "Remove unwanted columns prior to analysis",
"parameters": {
"column_names": ["value", "sample", "junk"],
"ignore_missing": True
}
}]
events_proc = self.get_event_proc('data/sub-002_task-FacePerception_run-1_events.tsv', None, None)
events_proc.command = base_constants.COMMAND_REMODEL
events_proc.remodel_operations = {'name': 'test', 'operations': rmdl1}
cols_orig = events_proc.events.columns
rows_orig = len(events_proc.events.dataframe)
with self.app.app_context():
results = events_proc.process()
self.assertTrue(results['data'], 'remodel results should have a data key when successful')
self.assertEqual('success', results['msg_category'], 'remodel msg_category should be success when no errors')
df = pd.read_csv(StringIO(results['data']), sep='\t')
self.assertEqual(len(df.columns), len(cols_orig) - 2),
self.assertEqual(len(df), rows_orig)

def test_events_remodel_invalid_no_hed(self):
rmdl1 = [{
"operation": "remove_columns",
"description": "Remove unwanted columns prior to analysis",
"parameters": {
"column_names": ["value", "sample", "junk"],
"ignore_missing": False
}
}]
events_proc = self.get_event_proc('data/sub-002_task-FacePerception_run-1_events.tsv', None, None)
events_proc.command = base_constants.COMMAND_REMODEL
events_proc.remodel_operations = {'name': 'test', 'operations': rmdl1}
with self.app.app_context():
with self.assertRaises(KeyError) as ex:
events_proc.process()
self.assertEqual(ex.exception.args[0], 'MissingColumnCannotBeRemoved')

def test_events_remodel_valid_with_hed(self):
rmdl1 = [{
"operation": "factor_hed_type",
"description": "Factor condition variables.",
"parameters": {
"type_tag": "Condition-variable"
}
}]
events_proc = self.get_event_proc('data/sub-002_task-FacePerception_run-1_events.tsv',
'data/task-facePerception_events.json', 'data/HED8.2.0.xml')
events_proc.command = base_constants.COMMAND_REMODEL
cols_orig = events_proc.events.columns
rows_orig = len(events_proc.events.dataframe)
events_proc.remodel_operations = {'name': 'test', 'operations': rmdl1}
with self.app.app_context():
results = events_proc.process()
self.assertTrue(results['data'], 'remodel results should have a data key when successful')
self.assertEqual('success', results['msg_category'], 'remodel msg_category should be success when no errors')
df = pd.read_csv(StringIO(results['data']), sep='\t')
self.assertEqual(len(df.columns), len(cols_orig) + 7),
self.assertEqual(len(df), rows_orig)


if __name__ == '__main__':
Expand Down

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