python - matplotlib 颜色条和具有共享轴的直方图

Question

我想用 imshow 显示 2D np.array 以及相应的颜色条，该颜色条应与 np.array< 的直方图共享其轴。不过，这是一次没有共享轴的尝试。

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.axes_grid1 import make_axes_locatable

fig, ax = plt.subplots(figsize=(7,10))

data = np.random.normal(0, 0.2, size=(100,100))
cax = ax.imshow(data, interpolation='nearest', cmap=cm.jet)

divider = make_axes_locatable(plt.gca())
axBar = divider.append_axes("bottom", '5%', pad='7%')
axHist = divider.append_axes("bottom", '30%', pad='7%')

cbar = plt.colorbar(cax, cax=axBar, orientation='horizontal')
axHist.hist(np.ndarray.flatten(data), bins=50)

plt.show()

我尝试将 axHist 中的 sharex 参数与 axHist =divider.append_axes("bottom", '30%', pad='7% 一起使用', sharex=axBar) 但这会以某种方式改变直方图数据:

除了共享轴 x 之外，如何修改直方图以采用与颜色图相同的颜色，类似于 here ？

Answer 1

您可以按 bin 值对直方图的每个 block 进行着色，而无需使用 sharex:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.axes_grid1 import make_axes_locatable
from matplotlib.colors import Normalize

fig, ax = plt.subplots(figsize=(7,10))

data = np.random.normal(0, 0.2, size=(100,100))
cax = ax.imshow(data, interpolation='nearest', cmap=cm.jet)

divider = make_axes_locatable(plt.gca())
axBar = divider.append_axes("bottom", '5%', pad='7%')
axHist = divider.append_axes("bottom", '30%', pad='7%')

cbar = plt.colorbar(cax, cax=axBar, orientation='horizontal')

# get hist data
N, bins, patches = axHist.hist(np.ndarray.flatten(data), bins=50)

norm = Normalize(bins.min(), bins.max())
# set a color for every bar (patch) according 
# to bin value from normalized min-max interval
for bin, patch in zip(bins, patches):
    color = cm.jet(norm(bin))
    patch.set_facecolor(color)

plt.show()

有关更多信息，请查找手册页:https://matplotlib.org/xkcd/examples/pylab_examples/hist_colormapped.html