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I have a numpy array of shape (66,67,4). When I do np.mean(imarray) it calculates the array mean but takes all channels into consideration. I want to calculate the mean of only channel 1 and channel 3, separately.

I am doing this since I have a .tif file and it contains certain attributes in each band and they are essentially independent from each other so I need to calculate means separately

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  • numpy.org/doc/stable/reference/arrays.indexing.html Commented Sep 4, 2022 at 13:04
  • np.mean(im[...,1]) and np.mean(im[...,3]) Commented Sep 4, 2022 at 13:08
  • Please provide enough code so others can better understand or reproduce the problem. Commented Sep 4, 2022 at 16:11

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The mean of channel 1 - assuming you meant the first channel:

np.mean(array[:, :, 0])
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2 Comments

Thank you very much for this. And channel 3 would be np.mean(array[:,:,2])?
@AhmedTech Yes, again I'm assuming you're aware of zero-based indexing

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