Matplotlib:使用imshow显示数组值 [英] Matplotlib : display array values with imshow

问题描述

我正在尝试使用imshow之类的matplotlib函数创建网格.
在此数组中:

I'm trying to create a grid using a matplotlib function like imshow.
From this array:

[[ 1  8 13 29 17 26 10  4],
[16 25 31  5 21 30 19 15]]

我想将值绘制为颜色，并将文本值本身(1,2，...)绘制在同一网格上.这就是我目前拥有的(我只能绘制与每个值关联的颜色):

I would like to plot the value as a color AND the text value itself (1,2, ...) on the same grid. This is what I have for the moment (I can only plot the color associated to each value):

from matplotlib import pyplot
import numpy as np

grid = np.array([[1,8,13,29,17,26,10,4],[16,25,31,5,21,30,19,15]])
print 'Here is the array'
print grid

fig1, (ax1, ax2)= pyplot.subplots(2, sharex = True, sharey = False)
ax1.imshow(grid, interpolation ='none', aspect = 'auto')
ax2.imshow(grid, interpolation ='bicubic', aspect = 'auto')
pyplot.show()   

推荐答案

如果出于任何原因，您必须使用与imshow自然提供的范围不同的不同范围，请使用以下方法(即使更人为)也可以完成这项工作:

If for any reason you have to use a different extent from the one that is provided naturally by imshow the following method (even if more contrived) does the job:

size = 4
data = np.arange(size * size).reshape((size, size))

# Limits for the extent
x_start = 3.0
x_end = 9.0
y_start = 6.0
y_end = 12.0

extent = [x_start, x_end, y_start, y_end]

# The normal figure
fig = plt.figure(figsize=(16, 12))
ax = fig.add_subplot(111)
im = ax.imshow(data, extent=extent, origin='lower', interpolation='None', cmap='viridis')

# Add the text
jump_x = (x_end - x_start) / (2.0 * size)
jump_y = (y_end - y_start) / (2.0 * size)
x_positions = np.linspace(start=x_start, stop=x_end, num=size, endpoint=False)
y_positions = np.linspace(start=y_start, stop=y_end, num=size, endpoint=False)

for y_index, y in enumerate(y_positions):
    for x_index, x in enumerate(x_positions):
        label = data[y_index, x_index]
        text_x = x + jump_x
        text_y = y + jump_y
        ax.text(text_x, text_y, label, color='black', ha='center', va='center')

fig.colorbar(im)
plt.show()

如果要放置其他类型的数据，而不必放置用于图像的值，则可以按以下方式修改上面的脚本(在数据后添加值):

If you want to put other type of data and not necessarily the values that you used for the image you can modify the script above in the following way (added values after data):

size = 4
data = np.arange(size * size).reshape((size, size))
values = np.random.rand(size, size)

# Limits for the extent
x_start = 3.0
x_end = 9.0
y_start = 6.0
y_end = 12.0

extent = [x_start, x_end, y_start, y_end]

# The normal figure
fig = plt.figure(figsize=(16, 12))
ax = fig.add_subplot(111)
im = ax.imshow(data, extent=extent, origin='lower', interpolation='None', cmap='viridis')

# Add the text
jump_x = (x_end - x_start) / (2.0 * size)
jump_y = (y_end - y_start) / (2.0 * size)
x_positions = np.linspace(start=x_start, stop=x_end, num=size, endpoint=False)
y_positions = np.linspace(start=y_start, stop=y_end, num=size, endpoint=False)

for y_index, y in enumerate(y_positions):
    for x_index, x in enumerate(x_positions):
        label = values[y_index, x_index]
        text_x = x + jump_x
        text_y = y + jump_y
        ax.text(text_x, text_y, label, color='black', ha='center', va='center')

fig.colorbar(im)
plt.show()

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