Matplotlib imshow/matshow在图上显示值

Question

我正在尝试使用Matplotlib中的任何一个imshow或matshow在Matplotlib中创建10x10网格.下面的函数将numpy数组作为输入,并绘制网格.但是,我希望数组中的值也显示在网格定义的单元格内.到目前为止,我找不到合适的方法来做到这一点.我可以plt.text用来将东西放在网格上,但这需要每个单元格的坐标,完全不方便.有没有更好的方法来做我想要完成的事情？

谢谢!

注意:下面的代码还没有从数组中获取值,我只是在玩plt.text.

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

board = np.zeros((10, 10))

def visBoard(board):
   cmap = colors.ListedColormap(['white', 'red'])
   bounds=[0,0.5,1]
   norm = colors.BoundaryNorm(bounds, cmap.N)
   plt.figure(figsize=(4,4))
   plt.matshow(board, cmap=cmap, norm=norm, interpolation='none', vmin=0, vmax=1)
   plt.xticks(np.arange(0.5,10.5), [])
   plt.yticks(np.arange(0.5,10.5), [])
   plt.text(-0.1, 0.2, 'x')
   plt.text(0.9, 0.2, 'o')
   plt.text(1.9, 0.2, 'x')
   plt.grid()

   visBoard(board)

输出:

Answer 1

你可以这样做:

import numpy as np
import matplotlib.pyplot as plt

fig, ax = plt.subplots()

min_val, max_val = 0, 10
ind_array = np.arange(min_val + 0.5, max_val + 0.5, 1.0)
x, y = np.meshgrid(ind_array, ind_array)

for i, (x_val, y_val) in enumerate(zip(x.flatten(), y.flatten())):
    c = 'x' if i%2 else 'o' 
    ax.text(x_val, y_val, c, va='center', ha='center')
#alternatively, you could do something like
#for x_val, y_val in zip(x.flatten(), y.flatten()):
#    c = 'x' if (x_val + y_val)%2 else 'o'

ax.set_xlim(min_val, max_val)
ax.set_ylim(min_val, max_val)
ax.set_xticks(np.arange(max_val))
ax.set_yticks(np.arange(max_val))
ax.grid()

编辑:

这是一个带imshow背景的更新示例.

import numpy as np
import matplotlib.pyplot as plt

fig, ax = plt.subplots()

min_val, max_val, diff = 0., 10., 1.

#imshow portion
N_points = (max_val - min_val) / diff
imshow_data = np.random.rand(N_points, N_points)
ax.imshow(imshow_data, interpolation='nearest')

#text portion
ind_array = np.arange(min_val, max_val, diff)
x, y = np.meshgrid(ind_array, ind_array)

for x_val, y_val in zip(x.flatten(), y.flatten()):
    c = 'x' if (x_val + y_val)%2 else 'o'
    ax.text(x_val, y_val, c, va='center', ha='center')

#set tick marks for grid
ax.set_xticks(np.arange(min_val-diff/2, max_val-diff/2))
ax.set_yticks(np.arange(min_val-diff/2, max_val-diff/2))
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_xlim(min_val-diff/2, max_val-diff/2)
ax.set_ylim(min_val-diff/2, max_val-diff/2)
ax.grid()
plt.show()