def ensemble()

in cv.py [0:0]

• 41 lines of code
• 7 McCabe index (conditional complexity)

def ensemble(basedirs, cfg, module, prefix, outdir):
    def _path(x):
        return os.path.join(basedir, prefix + x)

    means = []
    stds = []
    mean_deltas = []
    kwargs = {"index_col": "date", "parse_dates": ["date"]}
    stdfile = "std_closed_form.csv"
    meanfile = "mean_closed_form.csv"
    for basedir in basedirs:
        if os.path.exists(_path(cfg["validation"]["output"])):
            means.append(pd.read_csv(_path(cfg["validation"]["output"]), **kwargs))
        if os.path.exists(_path(stdfile)):
            stds.append(pd.read_csv(_path(stdfile), **kwargs))
            mean_deltas.append(pd.read_csv(_path(meanfile), **kwargs))
    if len(stds) > 0:
        # Average the variance, and take square root
        std = pd.concat(stds).pow(2).groupby(level=0).mean().pow(0.5)
        std.to_csv(os.path.join(outdir, prefix + stdfile))
        mean_deltas = pd.concat(mean_deltas).groupby(level=0).mean()
        mean_deltas.to_csv(os.path.join(outdir, prefix + meanfile))

    assert len(means) > 0, "All ensemble jobs failed!!!!"

    mod = importlib.import_module("covid19_spread." + module).CV_CLS()

    if len(stds) > 0:
        pred_interval = cfg.get("prediction_interval", {})
        piv = mod.run_prediction_interval(
            os.path.join(outdir, prefix + meanfile),
            os.path.join(outdir, prefix + stdfile),
            pred_interval.get("intervals", [0.99, 0.95, 0.8]),
        )
        piv.to_csv(os.path.join(outdir, prefix + "piv.csv"), index=False)

    mean = pd.concat(means).groupby(level=0).median()
    outfile = os.path.join(outdir, prefix + cfg["validation"]["output"])
    mean.to_csv(outfile, index_label="date")

    # -- metrics --
    metric_args = cfg[module].get("metrics", {})
    df_val, json_val = mod.compute_metrics(
        cfg[module]["data"], outfile, None, metric_args
    )
    df_val.to_csv(os.path.join(outdir, prefix + "metrics.csv"))
    with open(os.path.join(outdir, prefix + "metrics.json"), "w") as fout:
        json.dump(json_val, fout)
    print(df_val)