diff --git a/csv_merge.py b/csv_merge.py index 1aef136..0d2cc40 100644 --- a/csv_merge.py +++ b/csv_merge.py @@ -24,10 +24,10 @@ def merge(mainDF:pd.DataFrame, candDF:pd.DataFrame, outname): mainDF.insert(colNum+1, "label", 0) #iterate over candidates - for name, probability, label in candDF.itertuples(index=False): + for props in candDF.itertuples(index=False): #get dm and snr via string parsing the cand name - dm = float(name.split("dm_")[1].split("_")[0].split(".h5")[0].strip("0")) - snr = float(name.split("snr_")[1].split("_")[0].split(".h5")[0].strip("0")) + dm = float(props.candidate.split("dm_")[1].split("_")[0].split(".h5")[0].strip("0")) + snr = float(props.candidate.split("snr_")[1].split("_")[0].split(".h5")[0].strip("0")) #use those values to index the main dataframe and replace values dmMatch = mainDF['dm'].map(lambda d: round(d, 2) == round(dm, 2)) @@ -39,8 +39,8 @@ def merge(mainDF:pd.DataFrame, candDF:pd.DataFrame, outname): logger.error(f"{outname}: No matches found for DM {dm} and SNR {snr}.") else: index = int(row.index[0]) - mainDF.loc[index, 'probability'] = probability - mainDF.loc[index, 'label'] = label + mainDF.loc[index, 'probability'] = props.probability + mainDF.loc[index, 'label'] = props.label mainDF.to_csv(outname) @@ -63,5 +63,5 @@ if __name__ == "__main__": dirname = os.path.basename(os.path.dirname(values.directory)) mainCSV = pd.read_csv(os.path.join(values.directory, f"{dirname}.csv")) candCSV = pd.read_csv(os.path.join(values.directory, "cands","results_a.csv")) - logger.info(f"Working with {os.path.join(values.directory, f"{dirname}.csv")} and {os.path.join(values.directory, "cands","results_a.csv")}") + logger.info(f"Working with {os.path.join(values.directory, f'{dirname}.csv')} and {os.path.join(values.directory, 'cands','results_a.csv')}") merge(mainCSV, candCSV, os.path.join(values.directory, f"{dirname}_merged.csv")) \ No newline at end of file