[ITK-users] simpleitk + python + vector type in sitk.mirrorpad args?

[Lowekamp, Bradley (NIH/NLM/LHC) [C]]

Hello,

It looks like there is rightfully so no implicit conversion from numpy.int32 to “unsigned int” for value in tuples.


The following worked for me:

 padim=sitk.MirrorPad(medim,padextra.astype(int),padtop.astype(int))

and so does the following:

padim=sitk.MirrorPad(medim,padextra.astype(np.int),padtop.astype(np.int))

Here is an example for manual padding for FFTs:
https://github.com/SimpleITK/SimpleITK/blob/master/Examples/Python/FFTConvolution.py


HTH,
Brad

> On Nov 28, 2016, at 8:46 AM, Robert.Atwood at diamond.ac.uk wrote:
> 
> Hi,
> I just can't get this to work, I've tried any permutation I can think of. 
> I want to pad an array up to a calculated value on all dimensions. The calculation is easy to do in vectors with numpy , but whatever I try to do the mirrorpad function will not accept the data type. 
> 
> 
> Fsize is the array size and padsize is the  desired size in all dimensions. The calculation produces initially a floating point number 
> The line in comment # works, but I can't find a simple way to get the calculated output into a type that the function accepts. 
> So my question :
> 
>  1. is there a more integrated  way to make the image fit the requirements of the FFT filter, because that's what all this is in aid of.
>  2. if this is the best way to do it, how do I make the function accept the dimension vector??
> 
> 
> Thanks! 
> 
> The error is as follows: 
> 
> _____________________________
> 
> Traceback (most recent call last):
>  File "/home/kny48981/progs/segment_sitk/trysitkmask.py", line 92, in <module>
>    padim=sitk.MirrorPad(medim,padextratup,padtoptup)
>  File "/home/kny48981/.local/lib/python2.7/site-packages/SimpleITK/SimpleITK.py", line 35916, in MirrorPad
>    return _SimpleITK.MirrorPad(*args, **kwargs)
> TypeError: in method 'MirrorPad', argument 2 of type 'std::vector< unsigned int,std::allocator< unsigned int > > const &'
> 
> _____________________
> 
> 
> Complete reproducer with dummy image: (full output below) 
> 
> 
> reproducer.py 
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> 
> import SimpleITK as sitk
> import numpy as np
> 
> 
> 
> medim=sitk.Image(120,122,135,sitk.sitkFloat32)
> 
> fsize=np.array(medim.GetSize())
> fctr=fsize/2.0
> 
> padsize=(256,256,256)
> 
> padextra=(((padsize-fsize)/2.0)).astype(np.int32)
> 
> print "fsize=",fsize
> print "padsize=",padsize
> print"padextra=", padextra
> print type(padextra)
> padfix = padsize - fsize - padextra - padextra
> print "padfix",padfix
> padtop=(padextra + padfix).astype(np.int32)
> 
> 
> padextratup=tuple(padextra)
> padtoptup=tuple(padtop)
> 
> #padextratup=(125,125,100)
> 
> print type(padtoptup)
> print padtoptup
> print type(padtoptup[0])
> print type(padtoptup[1])
> print type(padtoptup[2])
> 
> print type(padextratup)
> print padextratup
> print type(padextratup[0])
> print type(padextratup[1])
> print type(padextratup[2])
> 
> 
> padim=sitk.MirrorPad(medim,padextratup,padtoptup)
> <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
> Output: 
> 
> python ./reproducer.py 
> fsize= [120 122 135]
> padsize= (256, 256, 256)
> padextra= [68 67 60]
> <type 'numpy.ndarray'>
> padfix [0 0 1]
> <type 'tuple'>
> (68, 67, 61)
> <type 'numpy.int32'>
> <type 'numpy.int32'>
> <type 'numpy.int32'>
> <type 'tuple'>
> (68, 67, 60)
> <type 'numpy.int32'>
> <type 'numpy.int32'>
> <type 'numpy.int32'>
> Traceback (most recent call last):
>  File "./reproducer.py", line 42, in <module>
>    padim=sitk.MirrorPad(medim,padextratup,padtoptup)
>  File "/home/kny48981/.local/lib/python2.7/site-packages/SimpleITK/SimpleITK.py", line 35916, in MirrorPad
>    return _SimpleITK.MirrorPad(*args, **kwargs)
> TypeError: in method 'MirrorPad', argument 2 of type 'std::vector< unsigned int,std::allocator< unsigned int > > const &'
> [kny48981 at i12-ws011 testseg_sitk]$
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