You could, before plotting, sum the different image arrays? Depending on
whether you are plotting RGB(A) images or greyscale images, you could take
the sum of the color channels, or take a weighted average.
The method you use here depends strongly on the image type, but it will
reduce memory consumption.
Just a thought.
2013/8/27 Štěpán Turek <stepan.tu...@seznam.cz>
> Hi,
>
> I would like to plot multiple overlayed 4096x4096 images in one axes. If I
> run this code the plot takes 300 MB of memory:
>
> import numpy as np
> import matplotlib.pyplot as plt
>
> if __name__ == '__main__':
> img = np.zeros((4096, 4096))
> img[100: 300, 100:1500] = 200
> imgplot = plt.imshow(img)
>
> plt.show()
>
> And it takes additional 300 MB for every image with this size added into
> plot. Is there any way to reduce memory consumption without need of data
> resampling?
>
> My configuration:
> Matplotlib 1.2.1
> Numpy 1.7.1
> Ubuntu 13.04 64 bit
>
> Best
> Stepan
>
>
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