def test_absolute_ratio_benchmark():
# Mostly sanity to check that Analytical functions don't have typos
# or syntax errors
n = 501
r_max = 50
for symmetric in [True, False]:
for Backend, options in [(StepAnalytical,
dict(A0=10.0,
r1=6.0,
r2=14.0,
ratio_valid_step=1.0)),
(GaussianAnalytical, dict(sigma=2))]:
ref = Backend(n, r_max, symmetric=symmetric, **options)
ratio = absolute_ratio_benchmark(ref, ref.func)
backend_name = type(ref).__name__
assert_allclose_msg(
ratio.mean(), 1.0,
"Sanity test, sym={}: {}: ratio == 1.0".format(
symmetric, backend_name))
assert_allclose_msg(
ratio.std(), 0.0, "Sanity test, sym={}: {}: std == 0.0".format(
symmetric, backend_name))
def test_fabel_hansenlaw_transform_gaussian():
"""Check fabel_hansenlaw with a Gaussian function"""
n = 1001
r_max = 501 # more points better fit
ref = GaussianAnalytical(n, r_max, symmetric=False, sigma=200)
recon = fabel_hansenlaw_transform(ref.func, ref.dr)
ratio = absolute_ratio_benchmark(ref, recon, kind='direct')
assert_allclose(ratio, 1.0, rtol=7e-2, atol=0)
def test_fabel_hansenlaw_transform_gaussian():
"""Check fabel_hansenlaw with a Gaussian function"""
n = 1001
r_max = 501 # more points better fit
ref = GaussianAnalytical(n, r_max, symmetric=False, sigma=200)
recon = fabel_hansenlaw_transform(ref.func, ref.dr)
ratio = absolute_ratio_benchmark(ref, recon, kind='direct')
assert_allclose(ratio, 1.0, rtol=7e-2, atol=0)
def test_iabel_hansenlaw_gaussian():
"""Check iabel_hansenlaw with a Gaussian function"""
n = 1001 # better with a larger number of points
r_max = 501
ref = GaussianAnalytical(n, r_max, symmetric=True, sigma=200)
tr = np.tile(ref.abel[None, :], (n, 1)) # make a 2D array from 1D
recon = iabel_hansenlaw(tr, ref.dr)
recon1d = recon[n // 2 + n % 2] # centre row
ratio = absolute_ratio_benchmark(ref, recon1d)
assert_allclose(ratio, 1.0, rtol=1e-1, atol=0)
def test_forward_direct_gaussian():
"""Check fabel_direct with a Gaussian"""
if not cython_ext:
raise SkipTest
n = 51
r_max = 25
ref = GaussianAnalytical(n, r_max, symmetric=False, sigma=10)
recon = fabel_direct(ref.func, dr=ref.dr)
ratio = absolute_ratio_benchmark(ref, recon, kind='direct')
assert_allclose(ratio, 1.0, rtol=7e-2, atol=0)
def test_iabel_hansenlaw_gaussian():
"""Check iabel_hansenlaw with a Gaussian function"""
n = 1001 # better with a larger number of points
r_max = 501
ref = GaussianAnalytical(n, r_max, symmetric=True, sigma=200)
tr = np.tile(ref.abel[None, :], (n, 1)) # make a 2D array from 1D
recon = iabel_hansenlaw(tr, ref.dr)
recon1d = recon[n//2 + n%2] # centre row
ratio = absolute_ratio_benchmark(ref, recon1d)
assert_allclose(ratio, 1.0, rtol=1e-1, atol=0)
def test_forward_direct_gaussian():
"""Check fabel_direct with a Gaussian"""
if not cython_ext:
raise SkipTest
n = 51
r_max = 25
ref = GaussianAnalytical(n, r_max, symmetric=False, sigma=10)
recon = fabel_direct(ref.func, dr=ref.dr)
ratio = absolute_ratio_benchmark(ref, recon, kind='direct')
assert_allclose(ratio, 1.0, rtol=7e-2, atol=0)
def test_three_point_step_ratio():
"""Check a gaussian solution for three_point"""
n = 51
r_max = 25
ref = GaussianAnalytical(n, r_max, symmetric=True, sigma=10)
tr = np.tile(ref.abel[None, :], (n, 1)) # make a 2D array from 1D
recon = iabel_three_point(tr, 25, basis_dir=None, verbose=False)
recon1d = recon[n // 2 + n % 2]
ratio = absolute_ratio_benchmark(ref, recon1d)
assert_allclose(ratio, 1.0, rtol=3e-2, atol=0)
def test_basex_step_ratio_asym():
"""Check a gaussian solution for asymmetric BASEX"""
n = 51
r_max = 25
ref = GaussianAnalytical(n, r_max, symmetric=True, sigma=10)
tr = np.tile(ref.abel[None, :], (n, 1)) # make a 2D array from 1D
bs = get_bs_basex_cached_asym(n, n, basis_dir=None, verbose=False)
recon = basex_transform_asym(tr, *bs)
recon1d = recon[n // 2 + n % 2]
ratio = absolute_ratio_benchmark(ref, recon1d)
assert_allclose(ratio, 1.0, rtol=3e-2, atol=0)
def test_basex_step_ratio_asym():
"""Check a gaussian solution for asymmetric BASEX"""
n = 51
r_max = 25
ref = GaussianAnalytical(n, r_max, symmetric=True, sigma=10)
tr = np.tile(ref.abel[None, :], (n, 1)) # make a 2D array from 1D
bs = get_bs_basex_cached_asym(n, n, basis_dir=None, verbose=False)
recon = basex_transform_asym(tr, *bs)
recon1d = recon[n // 2 + n % 2]
ratio = absolute_ratio_benchmark(ref, recon1d)
assert_allclose(ratio, 1.0, rtol=3e-2, atol=0)
def test_hansenlaw_gaussian():
"""Check a gaussian solution for HansenLaw"""
n = 51
r_max = 25
ref = GaussianAnalytical(n, r_max, symmetric=True, sigma=10)
tr = np.tile(ref.abel[None, :], (n, 1)) # make a 2D array from 1D
recon = iabel_hansenlaw(tr, calc_speeds=False, verbose=False)
recon1d = recon[n // 2 + n % 2]
ratio = absolute_ratio_benchmark(ref, recon1d)
# this only passes with a relative tolerance of 0.35, someone would
# need to look into it.
assert_allclose(ratio, 1.0, rtol=0.35, atol=0)
def test_three_point_step_ratio():
"""Check a gaussian solution for three_point"""
n = 51
r_max = 25
ref = abel.tools.analytical.GaussianAnalytical(n, r_max, symmetric=True, sigma=10)
tr = np.tile(ref.abel[None, :], (n, 1)) # make a 2D array from 1D
recon = abel.three_point.three_point(tr, 25, basis_dir=None,
direction='inverse',verbose=False)
recon1d = recon[n//2 + n%2]
ratio = absolute_ratio_benchmark(ref, recon1d)
assert_allclose( ratio , 1.0, rtol=3e-2, atol=0)
def test_absolute_ratio_benchmark():
# Mostly sanity to check that Analytical functions don't have typos
# or syntax errors
n = 501
r_max = 50
for symmetric in [True, False]:
for Backend, options in [(StepAnalytical, dict(A0=10.0, r1=6.0,
r2=14.0, ratio_valid_step=1.0)),
(GaussianAnalytical, dict(sigma=2))]:
ref = Backend(n, r_max, symmetric=symmetric, **options)
ratio = absolute_ratio_benchmark(ref, ref.func)
backend_name = type(ref).__name__
assert_allclose_msg(ratio.mean(), 1.0,
"Sanity test, sym={}: {}: ratio == 1.0".format(symmetric, backend_name))
assert_allclose_msg(ratio.std(), 0.0,
"Sanity test, sym={}: {}: std == 0.0".format(symmetric, backend_name))
