comparison consecutive_peaks.py @ 1:f3ca59e53b73 draft default tip

planemo upload for repository https://github.com/bardin-lab/damid_galaxy_tools commit c753dd4f3e1863aae7ba45dcc7efdf6937b03542-dirty

0:7f827a8e4ec5

    """Finds the two lowest consecutives peaks for a group and reports"""
    df = pd.read_csv(input_file, sep='\t', header=None)
    grouped = df.groupby(groupby_column, sort=False)
    if add_number_of_peaks:
        df[PEAKS_PER_GROUP] = grouped[groupby_column].transform(np.size)
    df[SHIFTED_PADJ_COLUMN] = grouped[8].shift()
    df[CONSECUTIVE_MAX] = df[[padj_column, SHIFTED_PADJ_COLUMN]].max(axis=1)
    grouped = df.groupby(groupby_column, sort=False)
    idx = grouped[CONSECUTIVE_MAX].transform(min)  # index of groupwise consecutive minimum
    new_df = df[df[CONSECUTIVE_MAX] == idx]
    new_df.sort_values(by=CONSECUTIVE_MAX)
    new_df[padj_column].replace(new_df[CONSECUTIVE_MAX])
    new_df = new_df.drop(labels=[CONSECUTIVE_MAX, SHIFTED_PADJ_COLUMN], axis=1)
    new_df.to_csv(output_file, sep='\t', header=None, na_rep="NaN")

1:f3ca59e53b73

    """Finds the two lowest consecutives peaks for a group and reports"""
    df = pd.read_csv(input_file, sep='\t', header=None)
    grouped = df.groupby(groupby_column, sort=False)
    if add_number_of_peaks:
        df[PEAKS_PER_GROUP] = grouped[groupby_column].transform(np.size)
    df[SHIFTED_PADJ_COLUMN] = grouped[padj_column].shift()
    df[CONSECUTIVE_MAX] = df[[padj_column, SHIFTED_PADJ_COLUMN]].max(axis=1)
    grouped = df.groupby(groupby_column, sort=False)
    idx = grouped[CONSECUTIVE_MAX].idxmin()  # index of groupwise consecutive minimum
    new_df = df.loc[idx]
    new_df.sort_values(by=CONSECUTIVE_MAX)
    new_df[padj_column].replace(new_df[CONSECUTIVE_MAX])
    new_df = new_df.drop(labels=[CONSECUTIVE_MAX, SHIFTED_PADJ_COLUMN], axis=1)
    new_df.to_csv(output_file, sep='\t', header=None, na_rep="NaN")