确保 0 在 RdBu 颜色条中变白

Question

我使用以下代码片段创建了一个热图：

import numpy as np
import matplotlib.pyplot as plt
d = np.random.normal(.4,2,(10,10))
plt.imshow(d,cmap=plt.cm.RdBu)
plt.colorbar()
plt.show()

结果如下图：

现在，由于数据的中间点不为 0，因此颜色图值为 0 的单元格不是白色，而是有点偏红。

如何强制颜色图使 max=blue、min=red 和 0=white？

Answer 1

A previous SO post () wanted a solution for a more complicated situation, but one of the answers talked about the MidpointNormalize subclass in the matplotlib documentation. 这样，解决方案就变成了：

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

class MidpointNormalize(mpl.colors.Normalize):
    ## class from the mpl docs:
    # https://matplotlib.org/users/colormapnorms.html

    def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
        self.midpoint = midpoint
        super().__init__(vmin, vmax, clip)

    def __call__(self, value, clip=None):
        # I'm ignoring masked values and all kinds of edge cases to make a
        # simple example...
        x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
        return np.ma.masked_array(np.interp(value, x, y))

d = np.random.normal(.4,2,(10,10))
plt.imshow(d,cmap=plt.cm.RdBu,norm=MidpointNormalize(midpoint=0))
plt.colorbar()
plt.show()

感谢 Joe Kington 编写子类，感谢 Rutger Kassies 指出答案。

Answer 2

使用 DivergingNorm.

注：从matplotlib 3.2开始DivergingNorm重命名为TwoSlopeNorm

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors

d = np.random.normal(.4,2,(10,10))

norm = mcolors.DivergingNorm(vmin=d.min(), vmax = d.max(), vcenter=0)
plt.imshow(d, cmap=plt.cm.RdBu, norm=norm)

plt.colorbar()
plt.show()

确保 0 在 RdBu 颜色条中变白

Making sure 0 gets white in a RdBu colorbar

matplotlib

colormap