TypeError: Invalid dimensions for image data when plotting array with imshow()

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For the following code

# 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')

fig12 = plt.savefig(outname12)

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
  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
  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

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

There is a (somewhat) related question on StackOverflow:

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.

More generally, the reason for the Exception

TypeError: Invalid dimensions for image data

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

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
            print('The "data" has 3 dimensions but the last dimension '
                  'must have a length of 3 (RGB) or 4 (RGBA), not "{}".'
            return False
        print('To visualize an image the data must be 2 dimensional or '
              '3 dimensional, not "{}".'
        return False

In your case:

>>> 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".

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.

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

enter image description here

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

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

enter image description here

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