af44192d3ae919e4cfadd6acfcdd3a1a16b4b5a9,plotnine/stats/stat_qq.py,stat_qq,compute_group,#Any#Any#Any#,52

Before Change

    @classmethod
    def compute_group(cls, data, scales, **params):
        theoretical, sample = probplot(data["sample"],
                                       dist=params["distribution"],
                                       sparams=params["dparams"],
                                       fit=False)

After Change

    @classmethod
    def compute_group(cls, data, scales, **params):
        sample = data["sample"].sort_values()
        alpha, beta = params["alpha_beta"]
        quantiles = params["quantiles"]

        if quantiles is None:
            quantiles = plotting_positions(sample, alpha, beta)
        elif len(quantiles) != len(sample):
            raise PlotnineError(
                "The number of quantile values is not the same as "
                "the number of sample values.")

        quantiles = np.asarray(quantiles)
        cdist = get_continuous_distribution(params["distribution"])
        theoretical = cdist.ppf(quantiles, *params["dparams"])
        return pd.DataFrame({"sample": sample,
                             "theoretical": theoretical})

Instances