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Merged
merged 11 commits into from
Dec 7, 2023
Merged

Shared Basis Rotate test #1057

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1d96987
Add simple rotation test across bases
garrettwrong Nov 27, 2023
b774f92
Convert basis rotation test to use Gaussian blob
garrettwrong Nov 27, 2023
9cf2a6e
Update rot test params to run doubles in long running
garrettwrong Nov 28, 2023
d91552b
Remove old FFB and FLE specific rotation tests
garrettwrong Nov 28, 2023
f0ae0a5
move new steerable rotate tests out of test_rotation
garrettwrong Nov 28, 2023
bb42122
Add a shared steerable reflection test.
garrettwrong Nov 28, 2023
0b2a530
Touch up tests
garrettwrong Nov 28, 2023
f32f023
normalize the images in steerable tests
garrettwrong Nov 29, 2023
aff1131
Tighten up steerable rotate tol after normalization
garrettwrong Nov 30, 2023
fcbd397
Merge branch 'develop' into basis_rot
garrettwrong Dec 6, 2023
e69a388
Merge branch 'develop' into basis_rot
garrettwrong Dec 6, 2023
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91 changes: 0 additions & 91 deletions tests/test_FFBbasis2D.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,6 @@
from scipy.special import jv

from aspire.basis import Coef, FFBBasis2D
from aspire.image import Image
from aspire.source import Simulation
from aspire.utils.misc import grid_2d
from aspire.volume import Volume
Expand Down Expand Up @@ -81,96 +80,6 @@ def testElements(self, basis):
for ell, k, sgn in zip(ells, ks, sgns):
self._testElement(basis, ell, k, sgn)

def testRotate(self, basis):
# Now low res (8x8) had problems;
# better with odd (7x7), but still not good.
# We'll use a higher res test image.
# fh = np.load(os.path.join(DATA_DIR, 'ffbbasis2d_xcoef_in_8_8.npy'))[:7,:7]
# Use a real data volume to generate a clean test image.
v = Volume(
np.load(os.path.join(DATA_DIR, "clean70SRibosome_vol.npy")).astype(
basis.dtype
)
)
src = Simulation(L=v.resolution, n=1, vols=v, dtype=v.dtype)
# Extract, this is the original image to transform.
x1 = src.images[0]

# Rotate 90 degrees CCW in cartesian coordinates.
x2 = Image(np.rot90(x1.asnumpy(), axes=(1, 2)))

# Express in an FB basis
basis = FFBBasis2D(x1.resolution, dtype=x1.dtype)
v1 = basis.evaluate_t(x1)
v2 = basis.evaluate_t(x2)

# Reflect in the FB basis space
v4 = basis.rotate(v1, 0, refl=[True])

# Rotate in the FB basis space
v3 = basis.rotate(v1, 2 * np.pi)
v1 = basis.rotate(v1, np.pi / 2)

# Evaluate back into cartesian
y1 = basis.evaluate(v1).asnumpy()
y2 = basis.evaluate(v2).asnumpy()
y3 = basis.evaluate(v3).asnumpy()
y4 = basis.evaluate(v4).asnumpy()

# Rotate 90
assert np.allclose(y1[0], y2[0], atol=1e-5)

# 2*pi Identity
assert np.allclose(x1[0], y3[0], atol=1e-5)

# Refl (flipped using flipud)
assert np.allclose(np.flipud(x1.asnumpy()[0]), y4[0], atol=1e-5)

def testRotateComplex(self, basis):
# Now low res (8x8) had problems;
# better with odd (7x7), but still not good.
# We'll use a higher res test image.
# fh = np.load(os.path.join(DATA_DIR, 'ffbbasis2d_xcoef_in_8_8.npy'))[:7,:7]
# Use a real data volume to generate a clean test image.
v = Volume(
np.load(os.path.join(DATA_DIR, "clean70SRibosome_vol.npy")).astype(
basis.dtype
)
)
src = Simulation(L=v.resolution, n=1, vols=v, dtype=v.dtype)
# Extract, this is the original image to transform.
x1 = src.images[0]

# Rotate 90 degrees CCW in cartesian coordinates.
x2 = Image(np.rot90(x1.asnumpy(), axes=(1, 2)))

# Express in an FB basis
basis = FFBBasis2D(x1.resolution, dtype=x1.dtype)
v1 = basis.evaluate_t(x1)
v2 = basis.evaluate_t(x2)

# Reflect in the FB basis space
v4 = basis.to_real(basis.complex_rotate(basis.to_complex(v1), 0, refl=[True]))

# Complex Rotate in the FB basis space
v3 = basis.to_real(basis.complex_rotate(basis.to_complex(v1), 2 * np.pi))
v1 = basis.to_real(basis.complex_rotate(basis.to_complex(v1), np.pi / 2))

# Evaluate back into cartesian
y1 = basis.evaluate(v1).asnumpy()
y2 = basis.evaluate(v2).asnumpy()
y3 = basis.evaluate(v3).asnumpy()
y4 = basis.evaluate(v4).asnumpy()

# Rotate 90
assert np.allclose(y1[0], y2[0], atol=1e-5)

# 2*pi Identity
assert np.allclose(x1[0].asnumpy(), y3[0], atol=1e-5)

# Refl (flipped using flipud)
assert np.allclose(np.flipud(x1.asnumpy()[0]), y4[0], atol=1e-5)

def testShift(self, basis):
"""
Compare shifting using Image with shifting provided by the Basis.
Expand Down
75 changes: 1 addition & 74 deletions tests/test_FLEbasis2D.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,12 +4,11 @@
import numpy as np
import pytest

from aspire.basis import Coef, FBBasis2D, FFBBasis2D, FLEBasis2D
from aspire.basis import Coef, FBBasis2D, FLEBasis2D
from aspire.image import Image
from aspire.nufft import backend_available
from aspire.numeric import fft
from aspire.source import Simulation
from aspire.utils import utest_tolerance
from aspire.volume import Volume

from ._basis_util import UniversalBasisMixin
Expand Down Expand Up @@ -228,78 +227,6 @@ def testLowPass():
_ = basis.lowpass(coefs[0, :], L)


def testRotate():
# test ability to accurately rotate images via
# FLE coefficients

L = 128
basis = FLEBasis2D(L, match_fb=False)

# sample image
ims = create_images(L, 1)
# rotate 90 degrees in cartesian coordinates
ims_90 = Image(np.rot90(ims.asnumpy(), axes=(1, 2)))

# get FLE coefficients
coefs = basis.evaluate_t(ims)
coefs_cart_rot = basis.evaluate_t(ims_90)

# rotate original image in FLE space using Steerable rotate method
coefs_fle_rot = basis.rotate(coefs, np.pi / 2)

# back to cartesian
ims_cart_rot = basis.evaluate(coefs_cart_rot)
ims_fle_rot = basis.evaluate(coefs_fle_rot)

# test rot90 close
assert np.allclose(ims_cart_rot[0], ims_fle_rot[0], atol=1e-4)

# 2Pi identity in FLE space (rotate by 2Pi)
coefs_fle_2pi = basis.rotate(coefs, 2 * np.pi)
ims_fle_2pi = basis.evaluate(coefs_fle_2pi)

# test 2Pi identity
assert np.allclose(ims[0], ims_fle_2pi[0], atol=utest_tolerance(basis.dtype))

# Reflect in FLE space (rotate by Pi)
coefs_fle_pi = basis.rotate(coefs, np.pi)
ims_fle_pi = basis.evaluate(coefs_fle_pi)

# test reflection
assert np.allclose(np.fliplr(np.flipud(ims.asnumpy()[0])), ims_fle_pi[0], atol=1e-4)

# make sure you can pass in a 1-D array if you want
_ = basis.lowpass(Coef(basis, np.zeros((basis.count,))), np.pi)


def testRotate45():
# test ability to accurately rotate images via
# FLE coefficients
dtype = np.float64

L = 128
fb_basis = FFBBasis2D(L, dtype=dtype)
basis = FLEBasis2D(L, match_fb=True, dtype=dtype)

# sample image
ims = create_images(L, 1)

# get FLE coefficients
fb_coefs = fb_basis.evaluate_t(ims)
coefs = basis.evaluate_t(ims)

# rotate original image in FLE space using Steerable rotate method
fb_coefs_rot = fb_basis.rotate(fb_coefs, np.pi / 4)
coefs_rot = basis.rotate(coefs, np.pi / 4)

# back to cartesian
fb_ims_rot = fb_basis.evaluate(fb_coefs_rot)
ims_rot = basis.evaluate(coefs_rot)

# test close
assert np.allclose(ims_rot[0], fb_ims_rot[0], atol=1e-4)


def testRadialConvolution():
# test ability to accurately convolve with a radial
# (e.g. CTF) function via FLE coefficients
Expand Down
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