Unification ct scan voxel size by using interpolation in Python

Question

I have used interp2 in Matlab, such as the following code, that is part of @rayryeng\'s answer in: Three dimensional (3D) matrix interpolation in Matlab:

Answer 1

In MATLAB, interp2 has as arguments:

result = interp2(input_x, input_y, input_z, output_x, output_y)

You are using only the latter 3 arguments, the first two are assumed to be input_x = 1:size(input_z,2) and input_y = 1:size(input_z,1).

In Python, scipy.interpolate.interp2 is quite different: it takes the first 3 input arguments of the MATLAB function, and returns an object that you can call to get interpolated values:

f = scipy.interpolate.interp2(input_x, input_y, input_z)
result = f(output_x, output_y)

Following the example from the documentation, I get to something like this:

from scipy import interpolate
x = np.arange(0, volume_image.shape[2])
y = np.arange(0, volume_image.shape[1])
f = interpolate.interp2d(x, y, volume_image[ind, :, :])
xnew = np.arange(0, volume_image.shape[2], 1/scaleCoeff[0])
ynew = np.arange(0, volume_image.shape[1], 1/scaleCoeff[1])
M2D[ind, :, :] = f(xnew, ynew)

[Code not tested, please let me know if there are errors.]