Re: Using ndimage.gaussian_filter for 3d array

A 3D gaussian filter is smoothing across all axes, so in abc[k, :, :] you are getting some of abc[k-1, :, :] and abc[k+1, :, :], and so on, according to the kernel weights in 3D. To smooth in 2D across all slices of a 3D array, specify a different sigma per axis, like so:

abc = ndimage.gaussian_filter(abc * 1e2, sigma=(0, 2, 2), output=abc, order=0)

Note that you don't need the [:, :, :]: using output=array is how to ensure that the array is modified in-place (if you are trying to avoid an extra allocation).

Juan.

On Tue, 26 Oct 2021, at 4:59 AM, ashwin .D wrote:
> Hello,
>              I am wanting to use ndimage.gaussian_filter for a 3d array in order to smooth the data .
> 
> When I do this - 
> 
> abc[:,:,:] = ndimage.gaussian_filter(abc[:,:,:]*1e2,sigma=2,order=0) I get unreal values.
> 
> However the function call when done within a loop like this 
> 
> for k in range(0,N):
>      abc[k,:,:] = ndimage.gaussian_filter(abc[k,:,:]*1e2,sigma=2,order=0) gives reasonable smoothed values.
> 
> From the docs - https://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.gaussian_filter.html
> 
> the input array does not seem to have any restriction on the dimensionality . So where am I going wrong ?
> 
> Best regards,
> Ashwin. 
> 
> _______________________________________________
> SciPy-User mailing list -- [email protected]
> To unsubscribe send an email to [email protected]
> https://mail.python.org/mailman3/lists/scipy-user.python.org/
> Member address: [email protected]
>

_______________________________________________
SciPy-User mailing list -- [email protected]
To unsubscribe send an email to [email protected]
https://mail.python.org/mailman3/lists/scipy-user.python.org/
Member address: [email protected]