matplotlib:在 hist2d 中记录转换计数

问题描述

在matplotlib中绘制二维直方图时，是否有一种简单的方法来获取对数转换后的计数?与 pyplot.hist 方法不同，pyplot.hist2d 方法似乎没有有一个log参数.

Is there a simple way to get log transformed counts when plotting a two dimensional histogram in matplotlib? Unlike the pyplot.hist method, the pyplot.hist2d method does not seem to have a log parameter.

当前我正在执行以下操作:

Currently I'm doing the following:

import numpy as np
import matplotlib as mpl
import matplotlib.pylab as plt

matrix, *opt = np.histogram2d(x, y)
img = plt.imshow(matrix, norm = mpl.colors.LogNorm(), cmap = mpl.cm.gray,
                 interpolation="None")

其中绘制了预期的直方图，但轴标签显示了bin的索引，因此没有预期的值.

Which plots the expected histogram, but the axis labels show the indices of the bins and thus not the expected value.

推荐答案

有点尴尬，不过我问题的答案其实在 docstring 的相应代码:

It's kind of embarrassing, but the answer to my question is actually in the docstring of the corresponding code:

Notes
-----
    Rendering the histogram with a logarithmic color scale is
    accomplished by passing a :class:`colors.LogNorm` instance to
    the *norm* keyword argument. Likewise, power-law normalization
    (similar in effect to gamma correction) can be accomplished with
    :class:`colors.PowerNorm`.

所以这是有效的:

import matplotlib as mpl
import matplotlib.pylab as plt
par = plt.hist2d(x, y, norm=mpl.colors.LogNorm(), cmap=mpl.cm.gray)

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