TypeError:使用imshow()绘制数组时，图像数据的尺寸无效

问题描述

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)

new_SN_map是一维数组，而mean_SN和sigma_SN是常量，则出现以下错误.

with new_SN_map being a 1D array and mean_SN and sigma_SN being constants, I get the following error.

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

此错误的根源是什么?我以为可以进行数值运算.

What is the source of this error? I thought my numerical operations were allowed.

推荐答案

StackOverflow上有一个(有点)相关的问题:

There is a (somewhat) related question on StackOverflow:

• 使用pylab.imshow()显示图像

这里的问题是形状(nx，ny，1)的数组仍被认为是3D数组，必须被squeeze d或切成2D数组.

Here the problem was that an array of shape (nx,ny,1) is still considered a 3D array, and must be squeezed or sliced into a 2D array.

更一般地说，发生异常的原因

More generally, the reason for the Exception

显示在此处: matplotlib.pyplot.imshow() 需要2D数组，或三维尺寸为3或4的3D阵列！

is shown here: matplotlib.pyplot.imshow() needs a 2D array, or a 3D array with the third dimension being of shape 3 or 4!

您可以轻松地通过以下方式进行检查(这些检查由imshow完成，该功能仅是为了在输入无效内容时给出更具体的消息):

You can easily check this with (these checks are done by imshow, this function is only meant to give a more specific message in case it's not a valid input):

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

在您的情况下:

>>> 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

np.asarray是matplotlib.pyplot.imshow在内部完成的，因此通常最好也这样做.如果您有一个numpy数组，则该数组已过时，但如果不是(例如list)，则有必要.

The np.asarray is what is done internally by matplotlib.pyplot.imshow so it's generally best you do it too. If you have a numpy array it's obsolete but if not (for example a list) it's necessary.

在您的特定情况下，您获得了一维数组，因此您需要使用 np.expand_dims()

In your specific case you got a 1D array, so you need to add a dimension with 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()

或仅使用接受一维数组的内容，例如plot:

or just use something that accepts 1D arrays like plot:

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

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