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Fix QC incorrect column order #2

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Fix QC incorrect column order #2

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12 changes: 11 additions & 1 deletion code/data_processing/cc_qc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -86,7 +86,17 @@ def cc_qc(self, df, threshold, TS=False):
CATEGORY = 2
print(f"FOR TASK SWITCHING -> Average accuracy at or below 0.5 across conditions and CATEGORY set to 2")

problematic_conditions = QC_UTILS.cond_block_not_reported(raw, self.ACC_COLUMN_NAME, self.COND_COLUMN_NAME, self.INCORRECT_SYMBOL)
# Check for blocks/conditions where every response is either incorrect
# or not reported. The first argument expects the column that defines
# the blocks/conditions and the second is the accuracy column. The
# previous implementation mistakenly flipped these arguments which
# caused the check to operate on the wrong columns.
problematic_conditions = QC_UTILS.cond_block_not_reported(
raw,
self.COND_COLUMN_NAME,
self.ACC_COLUMN_NAME,
self.INCORRECT_SYMBOL,
)

if len(problematic_conditions) != 0:
CATEGORY = 3
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10 changes: 9 additions & 1 deletion code/data_processing/mem_qc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -68,7 +68,15 @@ def fn_sm_qc(self, df, threshold):
print(f"Condition/Block '{condition}' has accuracy == 0% and CATEGORY set to 3")
avg_acc /= len(accuracy)

problematic_conditions = QC_UTILS.cond_block_not_reported(raw, self.ACC_COLUMN_NAME, self.COND_COLUMN_NAME, self.INCORRECT_SYMBOL)
# Detect any blocks/conditions where all responses are incorrect or
# missing. The utility expects the condition column first followed by
# the accuracy column; previously these were reversed.
problematic_conditions = QC_UTILS.cond_block_not_reported(
raw,
self.COND_COLUMN_NAME,
self.ACC_COLUMN_NAME,
self.INCORRECT_SYMBOL,
)

if len(problematic_conditions) != 0:
CATEGORY = 3
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9 changes: 8 additions & 1 deletion code/data_processing/ps_qc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -90,7 +90,14 @@ def ps_qc(self, submission, threshold, DSST=False):
CATEGORY = 2
print(f"FOR DSST -> Average accuracy at or below 0.5 across conditions and CATEGORY set to 2")

problematic_conditions = QC_UTILS.cond_block_not_reported(raw, self.ACC_COLUMN_NAME, self.COND_COLUMN_NAME, self.INCORRECT_SYMBOL)
# Identify blocks/conditions with only incorrect or missing responses.
# Arguments were previously inverted, leading to incorrect detection.
problematic_conditions = QC_UTILS.cond_block_not_reported(
raw,
self.COND_COLUMN_NAME,
self.ACC_COLUMN_NAME,
self.INCORRECT_SYMBOL,
)

if len(problematic_conditions) != 0:
CATEGORY = 3
Expand Down