interpolation.py 文件源码

 复制代码def __call__(self, *args, **kwargs):
        # TODO: Should be more defensive about this
        if len(args) == 1:
            # We have a dataframe
            df = args[0]
        else:
            # We have parameters for a single invocation
            df = pd.DataFrame(kwargs)

        if self.key_columns:
            sub_tables = df.groupby(self.key_columns)
        else:
            sub_tables = [(None, df)]

        result = pd.DataFrame(index=df.index)
        for key, sub_table in sub_tables:
            if sub_table.empty:
                continue
            funcs = self.interpolations[key]
            parameters = tuple(sub_table[k] for k in self.parameter_columns)
            for value_column, func in funcs.items():
                out = func(*parameters)
                # This reshape is necessary because RectBivariateSpline and InterpolatedUnivariateSpline return results
                # in slightly different shapes and we need them to be consistent
                if out.shape:
                    result.loc[sub_table.index, value_column] = out.reshape((out.shape[0],))
                else:
                    result.loc[sub_table.index, value_column] = out

        if self.func:
            return self.func(result)

        if len(result.columns) == 1:
            return result[result.columns[0]]

        return result