使用matplotlib / python的平方根刻度

Question

我想使用Python绘制平方根比例的图：

但是，我不知道该怎么做。Matplotlib允许进行对数刻度，但是在这种情况下，我需要像幂函数刻度之类的东西。

Answer 1

您可以创建自己的ScaleBase课程来做。我已根据您的目的从此处修改了示例（该示例制作了正方形比例，而不是平方根比例）。另外，请参阅此处的文档。

请注意，要正确执行此操作，您可能还应该创建自己的自定义刻度定位器。我在这里还没有做到；我只是使用手动设置主要和次要刻度线ax.set_yticks()。

import matplotlib.scale as mscale
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
import matplotlib.ticker as ticker
import numpy as np

class SquareRootScale(mscale.ScaleBase):
    """
    ScaleBase class for generating square root scale.
    """

    name = 'squareroot'

    def __init__(self, axis, **kwargs):
        # note in older versions of matplotlib (<3.1), this worked fine.
        # mscale.ScaleBase.__init__(self)

        # In newer versions (>=3.1), you also need to pass in `axis` as an arg
        mscale.ScaleBase.__init__(self, axis)

    def set_default_locators_and_formatters(self, axis):
        axis.set_major_locator(ticker.AutoLocator())
        axis.set_major_formatter(ticker.ScalarFormatter())
        axis.set_minor_locator(ticker.NullLocator())
        axis.set_minor_formatter(ticker.NullFormatter())

    def limit_range_for_scale(self, vmin, vmax, minpos):
        return  max(0., vmin), vmax

    class SquareRootTransform(mtransforms.Transform):
        input_dims = 1
        output_dims = 1
        is_separable = True

        def transform_non_affine(self, a): 
            return np.array(a)**0.5

        def inverted(self):
            return SquareRootScale.InvertedSquareRootTransform()

    class InvertedSquareRootTransform(mtransforms.Transform):
        input_dims = 1
        output_dims = 1
        is_separable = True

        def transform(self, a):
            return np.array(a)**2

        def inverted(self):
            return SquareRootScale.SquareRootTransform()

    def get_transform(self):
        return self.SquareRootTransform()

mscale.register_scale(SquareRootScale)

fig, ax = plt.subplots(1)

ax.plot(np.arange(0, 9)**2, label='$y=x^2$')
ax.legend()

ax.set_yscale('squareroot')
ax.set_yticks(np.arange(0,9,2)**2)
ax.set_yticks(np.arange(0,8.5,0.5)**2, minor=True)

plt.show()