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ploting denoised img #1798

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imanusita opened this issue Mar 28, 2019 · 2 comments

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@imanusita
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commented Mar 28, 2019

before = data[:, :, axial_middle].T
after = den[:, :, axial_middle].T

difference = np.abs(after.astype('f8') - before.astype('f8'))
difference[~mask[:, :, axial_middle].T] = 0
what does the last line do ?
and what is tht f8 ?

@skoudoro

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commented Mar 28, 2019

Hi @imanusita,

what is tht f8 ?

convert your array/data to 64-bit floating-point. Equivalent to np.float64. more information here.

what does the last line do?

Invert the brain mask in order to put the background to 0. But I agree, there is a less "geeky" way to do that. We should update this part of the tutorial

@imanusita

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commented Mar 28, 2019

thnk u skoudoro
i hv tried it with nifti file and it worked
wanted to to the same between 2 fa_map images or 2 rgb images , is it possible cz it can be difficult to notice the difference i wanted to do tht with tht method , i tried it and i hv error tellin that -packages\matplotlib\image.py", line 638, in set_data
raise TypeError("Invalid dimensions for image data")
TypeError: Invalid dimensions for image data

@skoudoro skoudoro closed this May 3, 2019

@skoudoro skoudoro reopened this May 3, 2019

@skoudoro skoudoro added this to the 1.0 milestone May 3, 2019

@skoudoro skoudoro closed this Aug 5, 2019

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