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Showing different trials to a returning participant

Today’s tip is a little different. With the help of ChatGPT, I have written a solution which would allow participants to press escape during a local experiment and then be shown different trials when they restart. This will only work locally, not online.

Put the following code into the Begin Experiment tab of a Python code component.

The code counts the number of rows in a conditions file and then looks for values of trials.thisIndex in data files starting the with current participant number, creating useRows as a list of indices that haven’t yet been seen.

import pandas as pd
from glob import glob

# Set variables
conditions_file = "conditions.xlsx"  # Can be .xlsx or .csv
loop_name = "trials"

# Determine file type and read data
if conditions_file.endswith('.xlsx'):
    df_conditions = pd.read_excel(conditions_file)
elif conditions_file.endswith('.csv'):
    df_conditions = pd.read_csv(conditions_file)
else:
    raise ValueError("Unsupported file format. Use .xlsx or .csv.")

# Get the total number of rows
total_rows = len(df_conditions)

# Get all CSV files starting with participant ID
csv_files = glob(os.path.join("data", f"{expInfo['participant']}*.csv"))

# Extract trials.thisIndex values
trial_indices = set()  # Using a set for fast lookup
for file in csv_files:
    try:
        df = pd.read_csv(file)
        if loop_name + '.thisIndex' in df.columns:
            trial_indices.update(df[loop_name + '.thisIndex'].dropna().astype(int))
    except Exception as e:
        print(f"Error reading {file}: {e}")

# Generate the full range of expected indices
all_indices = set(range(total_rows))

# Find missing indices
useRows = sorted(all_indices - trial_indices)

# Output results
print('useRows', useRows)

Then set the selected rows of the loop as $useRows.

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