mirror of
https://github.com/cdtools-developers/cdtools.git
synced 2026-09-10 05:22:41 +02:00
93 lines
3.0 KiB
Python
93 lines
3.0 KiB
Python
from __future__ import division, print_function, absolute_import
|
|
|
|
|
|
import pytest
|
|
import numpy as np
|
|
import torch as t
|
|
|
|
from CDTools.tools import image_processing, cmath, initializers, interactions
|
|
from scipy import ndimage
|
|
|
|
|
|
def test_centroid():
|
|
# Test single im
|
|
im = t.rand((30,40))
|
|
sp_centroid = ndimage.measurements.center_of_mass(im.numpy())
|
|
centroid = image_processing.centroid(im)
|
|
assert t.allclose(centroid, t.Tensor(sp_centroid))
|
|
|
|
# Test stack o' ims
|
|
ims = t.rand((5,30,40))
|
|
sp_centroids = [ndimage.measurements.center_of_mass(im.numpy())
|
|
for im in ims]
|
|
centroids = image_processing.centroid(ims)
|
|
assert t.allclose(centroids, t.Tensor(sp_centroids))
|
|
|
|
|
|
def test_centroid_sq():
|
|
# Test single im
|
|
im = t.rand((30,40))
|
|
sp_centroid = ndimage.measurements.center_of_mass(im.numpy()**2)
|
|
centroid = image_processing.centroid_sq(im)
|
|
assert t.allclose(centroid, t.Tensor(sp_centroid))
|
|
|
|
# Test complex with multiple ims
|
|
ims = t.rand((5,30,40,2))
|
|
np_ims = cmath.torch_to_complex(ims)
|
|
sp_centroids = [ndimage.measurements.center_of_mass(np.abs(im)**2)
|
|
for im in np_ims]
|
|
centroids = image_processing.centroid_sq(ims, comp=True)
|
|
assert t.allclose(centroids, t.Tensor(np.array(sp_centroids)))
|
|
|
|
|
|
def test_find_pixel_shift():
|
|
|
|
# Test two real ims
|
|
big_im = t.rand((30,70))
|
|
im1 = big_im[3:,:-20]
|
|
im2 = big_im[:-3,20:]
|
|
assert t.all(image_processing.find_pixel_shift(im1,im2) == t.LongTensor([-3,20]))
|
|
|
|
# Test a real and complex im
|
|
big_im = t.rand((30,70))
|
|
im1 = t.stack((big_im[:-5,10:],t.zeros_like(big_im[:-5,10:])),dim=-1)
|
|
im2 = big_im[5:,:-10]
|
|
assert t.all(image_processing.find_pixel_shift(im1,im2) == t.LongTensor([5,-10]))
|
|
assert t.all(image_processing.find_pixel_shift(im2,im1) == t.LongTensor([-5,10]))
|
|
|
|
# Test two complex ims
|
|
big_im = t.rand((45,45,2))
|
|
im1 = big_im[:-5,:-4]
|
|
im2 = big_im[5:,4:]
|
|
assert t.all(image_processing.find_pixel_shift(im1,im2) == t.LongTensor([5,4]))
|
|
|
|
|
|
def test_find_subpixel_shift():
|
|
# We can do this by creating a test probe and a test object
|
|
test_probe = t.rand((70,70,2))
|
|
test_obj = t.ones((300,300,2))
|
|
|
|
shift = t.tensor((0.8,0.75))
|
|
|
|
im = interactions.ptycho_2D_sinc(test_probe, test_obj, shift)
|
|
|
|
retrieved_shift = image_processing.find_subpixel_shift(im, test_probe, search_around=(0,0), resolution=50)
|
|
# tolerance of 0.03 on this measurement
|
|
assert t.all(t.abs(shift - retrieved_shift) < 0.03)
|
|
|
|
|
|
def test_find_shift():
|
|
|
|
# We can do this by creating a test probe and a test object
|
|
test_probe = t.rand((200,200,2))
|
|
test_obj = t.ones((300,300,2))
|
|
|
|
shift = t.tensor((0.8,0.75))
|
|
|
|
im = interactions.ptycho_2D_sinc(test_probe, test_obj, shift)[:-40,:-6]
|
|
|
|
retrieved_shift = image_processing.find_shift(im, test_probe[40:,6:], resolution=50)
|
|
# tolerance of 0.03 on this measurement
|
|
assert t.all(t.abs(shift + t.Tensor((40,6)) - retrieved_shift) < 0.03)
|
|
|