TypeError:使用imshow()绘制数组时图像数据的维度无效

Question

对于以下代码

# Numerical operation
SN_map_final = (new_SN_map - mean_SN) / sigma_SN  

# Plot figure
fig12 = plt.figure(12)
fig_SN_final = plt.imshow(SN_map_final, interpolation='nearest')
plt.colorbar()

fig12 = plt.savefig(outname12)

与new_SN_map作为一维数组,mean_SN并sigma_SN为常数,我碰到下面的错误.

Traceback (most recent call last):
  File "c:\Users\Valentin\Desktop\Stage M2\density_map_simple.py", line 546, in <module>
    fig_SN_final = plt.imshow(SN_map_final, interpolation='nearest')
  File "c:\users\valentin\appdata\local\enthought\canopy\user\lib\site-packages\matplotlib\pyplot.py", line 3022, in imshow
    **kwargs)
  File "c:\users\valentin\appdata\local\enthought\canopy\user\lib\site-packages\matplotlib\__init__.py", line 1812, in inner
    return func(ax, *args, **kwargs)
  File "c:\users\valentin\appdata\local\enthought\canopy\user\lib\site-packages\matplotlib\axes\_axes.py", line 4947, in imshow
    im.set_data(X)
  File "c:\users\valentin\appdata\local\enthought\canopy\user\lib\site-packages\matplotlib\image.py", line 453, in set_data
    raise TypeError("Invalid dimensions for image data")
TypeError: Invalid dimensions for image data

这个错误的来源是什么？我以为我的数字操作是允许的.

Answer 1

StackOverflow上有一个(有点)相关的问题:

• 用pylab.imshow()显示图像

这里的问题是形状(nx,ny,1)的数组仍然被认为是3D数组,并且必须被squeezed或切成2D数组.

更一般地说,异常的原因

TypeError:图像数据的维度无效

如下所示:matplotlib.pyplot.imshow()需要2D阵列,或者第三维的形状为3或4的3D阵列!

您可以轻松地检查这些(这些检查是通过完成的imshow,此功能仅用于在不是有效输入的情况下提供更具体的消息):

from __future__ import print_function
import numpy as np

def valid_imshow_data(data):
    data = np.asarray(data)
    if data.ndim == 2:
        return True
    elif data.ndim == 3:
        if 3 <= data.shape[2] <= 4:
            return True
        else:
            print('The "data" has 3 dimensions but the last dimension '
                  'must have a length of 3 (RGB) or 4 (RGBA), not "{}".'
                  ''.format(data.shape[2]))
            return False
    else:
        print('To visualize an image the data must be 2 dimensional or '
              '3 dimensional, not "{}".'
              ''.format(data.ndim))
        return False

在你的情况下:

>>> new_SN_map = np.array([1,2,3])
>>> valid_imshow_data(new_SN_map)
To visualize an image the data must be 2 dimensional or 3 dimensional, not "1".
False

这np.asarray是内部完成的,matplotlib.pyplot.imshow所以通常你最好也这样做.如果你有一个numpy数组它已经过时但如果没有(例如a list)它是必要的.

在您的特定情况下,您有一个1D数组,因此您需要添加维度 np.expand_dims()

import matplotlib.pyplot as plt
a = np.array([1,2,3,4,5])
a = np.expand_dims(a, axis=0)  # or axis=1
plt.imshow(a)
plt.show()

或者只使用接受一维数组的东西,例如plot:

a = np.array([1,2,3,4,5])
plt.plot(a)
plt.show()