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目前我正在绘制如下直方图：

我只想用等间距的直方图重新组合数据，但使用新的比例。我需要指定宽度，但由于 xscale,yscale 重置轴的方式，我不知道如何定义它。即在每种情况下（线性对数、对数对数等），应该做什么

ax.set_xlim(min(bin_edges), max(bin_edges))
ax.set_ylim(min(hist), max(hist))

设置为？或者有没有办法自动设置它，所以直方图看起来很正确，这完全基于我将 xscale 和 yscale 设置为“线性”或“对数”的事实。我确信有一个更简单的解决方案。目前，当我进入日志空间时，条形重叠并且宽度不同。

        if self.xscale_hist == 'linear-linear':
            ax.set_xscale("linear")
            ax.set_yscale("linear")
            hist, bin_edges = np.histogram(self.tmphistdata, bins=self.numhistbins)
            width = (max(bin_edges)-min(bin_edges))/len(bin_edges)
            self._display_points = ax.bar(bin_edges[:-1], hist, width = width, facecolor='green')
        if self.xscale_hist == 'linear-log':
            ax.set_xscale("linear")
            ax.set_yscale("log")
            hist, bin_edges = np.histogram(self.tmphistdata, bins=self.numhistbins)
            hist = np.log10(hist)
            width = (max(bin_edges)-min(bin_edges))/len(bin_edges)
            self._display_points = ax.bar(bin_edges[:-1], hist, width = width, facecolor='green')
        if self.xscale_hist == 'log-linear':
            ax.set_xscale("log")
            ax.set_yscale("linear")
            hist, bin_edges = np.histogram(self.tmphistdata, bins=self.numhistbins)
            bin_edges = np.log10(bin_edges)
            width = (max(bin_edges)-min(bin_edges))/len(bin_edges)
            self._display_points = ax.bar(bin_edges[:-1], hist, width = width, facecolor='green')
        if self.xscale_hist == 'log-log':
            ax.set_xscale("log")
            ax.set_yscale("log")
            hist, bin_edges = np.histogram(self.tmphistdata, bins=self.numhistbins)
            bin_edges = np.log10(bin_edges)
            hist = np.log10(hist)
            width = (max(bin_edges)-min(bin_edges))/len(bin_edges)
            self._display_points = ax.bar(bin_edges[:-1], hist, width = width, facecolor='green')
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