def result(self, boxkwargs=None, figsize=(12, 10), maxpoints=1000):

        if boxkwargs is None:
            boxkwargs = {}

        filtered = random.sample(list(self.df.index), maxpoints)
        sampled_df = self.df.ix[filtered]

        fig = mpl.figure.Figure(figsize=figsize, tight_layout=True)
        canvas = mbb.FigureCanvasAgg(fig)
        grid = gs.GridSpec(4, 3,
                           width_ratios=[4, 4, 1],
                           height_ratios=[2, 1, 2, 1])

        axm = fig.add_subplot(grid[0], label='axm')
        axmd = fig.add_subplot(grid[1], label='axmd')
        axtm = fig.add_subplot(grid[3], label='axtm', frameon=False,)
        axtmd = fig.add_subplot(grid[4], label='axtmd', frameon=False,)
        axs = fig.add_subplot(grid[6], label='axs')
        axsd = fig.add_subplot(grid[7], label='axsd')
        axts = fig.add_subplot(grid[9], label='axts', frameon=False,)
        axtsd = fig.add_subplot(grid[10], label='axtsd', frameon=False,)

        jp.boxplot('Group', 'Mean', sampled_df, axes=axm,
                   legend='Group', **boxkwargs)
        jp.boxplot('Group', 'Mean Delta', sampled_df, axes=axmd,
                   legend='Group', **boxkwargs)
        jp.boxplot('Group', 'Sigma', sampled_df, axes=axs,
                   legend='Group', **boxkwargs)
        jp.boxplot('Group', 'Sigma Delta', sampled_df, axes=axsd,
                   legend='Group', **boxkwargs)

        jp.components.datatable('Mean', self.df, axtm,
                                by='Group', probs='bayes')
        jp.components.datatable('Mean Delta', self.df, axtmd,
                                by='Group', probs='bayes')
        jp.components.datatable('Sigma', self.df, axts,
                                by='Group', probs='bayes')
        jp.components.datatable('Sigma Delta', self.df, axtsd,
                                by='Group', probs='bayes')

        for ax in axm, axmd, axtm, axtmd, axs, axsd, axts, axtsd:
            if not ax:
                continue

            ax.tick_params(top="off")
            ax.tick_params(bottom="off")
            ax.tick_params(right="off")
            ax.tick_params(left="off")

        fig.suptitle('')
        return canvas.figure
Method for storing the deposit receipts, and also for providing lookup dictionaries that
dataset/ETHPy150Open beltashazzer/jmpy/jmpy/bayes/oneway.py/JbResult.result--crossover with--dataset/ETHPy150Open swordapp/python-client-sword2/sword2/connection.py/Connection._cache_deposit_receipt