Setting correct limits with imshow if image data shape changes

I have a 3D array, of which the first two dimensions are spatial, so say (x,y). The third dimension contains point-specific information.

print H.shape  # --> (200, 480, 640)  spatial extents (200,480)

Now, by selecting a certain plane in the third dimension, I can display an image with

imdat = H[:,:,100]    # shape (200, 480)
img = ax.imshow(imdat, cmap='jet',vmin=imdat.min(),vmax=imdat.max(), animated=True, aspect='equal')

I want to now rotate the cube, so that I switch from (x,y) to (y,x).

    H = np.rot90(H)          # could also use H.swapaxes(0,1) or H.transpose((1,0,2)) 
    print H.shape    # --> (480, 200, 640)

Now, when I call:

imdat = H[:,:,100]   # shape (480,200)
img.set_data(imdat)
ax.relim()
ax.autoscale_view(tight=True)

I get weird behavior. The image along the rows displays the data till 200th row, and then it is black until the end of the y-axis (480). The x-axis extends from 0 to 200 and shows the rotated data. Now on, another rotation by 90-degrees, the image displays correctly (just rotated 180 degrees of course)

It seems to me like after rotating the data, the axis limits, (or image extents?) or something is not refres开发者_JAVA百科hing correctly. Can somebody help?

PS: to indulge in bad hacking, I also tried to regenerate a new image (by calling ax.imshow) after each rotation, but I still get the same behavior.

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Below I include a solution to your problem. The method resetExtent uses the data and the image to explicitly set the extent to the desired values. Hopefully I correctly emulated the intended outcome.

import matplotlib.pyplot as plt
import numpy as np

def resetExtent(data,im):
    """
    Using the data and axes from an AxesImage, im, force the extent and 
    axis values to match shape of data.
    """
    ax = im.get_axes()
    dataShape = data.shape

    if im.origin == 'upper':
        im.set_extent((-0.5,dataShape[0]-.5,dataShape[1]-.5,-.5))
        ax.set_xlim((-0.5,dataShape[0]-.5))
        ax.set_ylim((dataShape[1]-.5,-.5))
    else:
        im.set_extent((-0.5,dataShape[0]-.5,-.5,dataShape[1]-.5))
        ax.set_xlim((-0.5,dataShape[0]-.5))
        ax.set_ylim((-.5,dataShape[1]-.5))

def main():
    fig = plt.gcf()
    ax = fig.gca()

    H = np.zeros((200,480,10))
    # make distinguishing corner of data
    H[100:,...] = 1
    H[100:,240:,:] = 2

    imdat = H[:,:,5]
    datShape = imdat.shape

    im = ax.imshow(imdat,cmap='jet',vmin=imdat.min(),
                    vmax=imdat.max(),animated=True,
                    aspect='equal',
                    #                origin='lower'
                    )

    resetExtent(imdat,im)

    fig.savefig("img1.png")

    H = np.rot90(H)

    imdat = H[:,:,0]
    im.set_data(imdat)
    resetExtent(imdat,im)

    fig.savefig("img2.png")

if __name__ == '__main__':
  main()

This script produces two images: First un-rotated:

Then rotated:

I thought just explicitly calling set_extent would do everything resetExtent does, because it should adjust the axes limits if 'autoscle' is True. But for some unknown reason, calling set_extent alone does not do the job.