def test_gauss2D_sym(self):
"""Testing if the symmetrical case is a sub case of the full one"""
coefs_full = [12, 20, 70, 20, 20, 0, 2]
full_data = Gauss2D.gauss2D((self.xx, self.yy), *coefs_full)
coefs_sym = coefs_full[:4] + [coefs_full[-1]]
sym_data = Gauss2D.gauss2D_sym((self.xx, self.yy), *coefs_sym)
assert np.all(sym_data == full_data)
def test_gauss2D_norot(self):
"""Testing if the no rotation case is a sub case of the full one"""
coefs_full = [12, 20, 70, 20, 30, 0, 2]
full_data = Gauss2D.gauss2D((self.xx, self.yy), *coefs_full)
coefs_norot = coefs_full[:5] + [coefs_full[-1]]
norot_data = Gauss2D.gauss2D_norot((self.xx, self.yy), *coefs_norot)
assert np.all(norot_data == full_data)
def test_gauss2D_norot(self):
"""Testing if the no rotation case is a sub case of the full one"""
coefs_full = [12, 20, 70, 20, 30, 0, 2]
full_data = Gauss2D.gauss2D((self.xx, self.yy), *coefs_full)
coefs_norot = coefs_full[:5] + [coefs_full[-1]]
norot_data = Gauss2D.gauss2D_norot((self.xx, self.yy), *coefs_norot)
assert np.all(norot_data == full_data)
def test_gauss2D_sym(self):
"""Testing if the symmetrical case is a sub case of the full one"""
coefs_full = [12, 20, 70, 20, 20, 0, 2]
full_data = Gauss2D.gauss2D((self.xx, self.yy), *coefs_full)
coefs_sym = coefs_full[:4] + [coefs_full[-1]]
sym_data = Gauss2D.gauss2D_sym((self.xx, self.yy), *coefs_sym)
assert np.all(sym_data == full_data)
def test_unequal_range(self):
"""Making sure that a ValueError is thrown for unequal ranges"""
x = np.arange(64)
y = np.arange(64)
xx, yy = np.meshgrid(x, y)
coefs_full = [12, 20, 70, 20, 30, 0.5, 2]
with pytest.raises(RuntimeError):
Gauss2D.gauss2D((self.xx, yy), *coefs_full)
with pytest.raises(RuntimeError):
Gauss2D.gauss2D((xx, self.yy), *coefs_full)
def _test(self):
# pull proper data and coefs
coefs = self.coefs[modeltype]
data = self.data[modeltype]
# add noise
if snr:
if fittype == "ls":
amp = coefs[0]
noise_data = (amp / snr) * RNG.normal(size=data.shape)
noisy_data = data + noise_data
# this is a heuristic and should be replaced with a better
# reasone parameter
rtol = 1 / snr
elif fittype == "mle":
noisy_data = RNG.poisson(data)
rtol = 1 / coefs[0]
else:
noisy_data = data
rtol = 1e-7
# build object to test
test_g = Gauss2D(noisy_data)
# speficify guesses
if not guess:
guess_coefs = None
else:
guess_coefs = coefs.copy()
# grab optimized coefs
test_coefs = test_g.optimize_params(guess_params=guess_coefs,
modeltype=modeltype,
fittype=fittype)
# do the actual test
assert_allclose(test_coefs, coefs, rtol=rtol)
def setUp(self):
"""Set up testing fixtures, they'll be generated on the fly because
this is a small model"""
amp, x0, y0, sigma_x, sigma_y, rho, offset = self._make_coefs()
# make full
gt_coefs_full = np.array((amp, x0, y0, sigma_x, sigma_y, rho, offset))
gt_full = Gauss2D.model((self.xx, self.yy), *gt_coefs_full)
# make norot
gt_coefs_norot = np.array((amp, x0, y0, sigma_x, sigma_y, offset))
gt_norot = Gauss2D.model((self.xx, self.yy), *gt_coefs_norot)
# make sym
gt_coefs_sym = np.array((amp, x0, y0, sigma_x, offset))
gt_sym = Gauss2D.model((self.xx, self.yy), *gt_coefs_sym)
# make internal dictionaries for tests to use.
self.coefs = dict(sym=gt_coefs_sym, norot=gt_coefs_norot,
full=gt_coefs_full)
self.data = dict(sym=gt_sym, norot=gt_norot, full=gt_full)
def setUp(self):
"""Set up testing fixtures, they'll be generated on the fly because
this is a small model"""
amp, x0, y0, sigma_x, sigma_y, rho, offset = self._make_coefs()
# make full
gt_coefs_full = np.array((amp, x0, y0, sigma_x, sigma_y, rho, offset))
gt_full = Gauss2D.model((self.xx, self.yy), *gt_coefs_full)
# make norot
gt_coefs_norot = np.array((amp, x0, y0, sigma_x, sigma_y, offset))
gt_norot = Gauss2D.model((self.xx, self.yy), *gt_coefs_norot)
# make sym
gt_coefs_sym = np.array((amp, x0, y0, sigma_x, offset))
gt_sym = Gauss2D.model((self.xx, self.yy), *gt_coefs_sym)
# make internal dictionaries for tests to use.
self.coefs = dict(sym=gt_coefs_sym,
norot=gt_coefs_norot,
full=gt_coefs_full)
self.data = dict(sym=gt_sym, norot=gt_norot, full=gt_full)
def _test(self):
area = self.gauss.area()
model = self.gauss.fit_model
numeric_area = model.sum()
assert_allclose(area, numeric_area, err_msg="Failed with GT params")
assert_allclose(
Gauss2D(model).area(guess_params=self.gauss._popt),
numeric_area,
err_msg="Failed when optimizing params",
)
def test_model(self):
"""Test model classmethod in Gauss2D class"""
# first test acceptable values for goodness
funcs = (Gauss2D.gauss2D, Gauss2D.gauss2D_norot, Gauss2D.gauss2D_sym)
coefs = ([12, 20, 70, 20, 30, 0.5, 2], [12, 20, 70, 20, 30,
2], [12, 20, 70, 20, 2])
for func, coef in zip(funcs, coefs):
data = func((self.xx, self.yy), *coef)
model = Gauss2D.model((self.xx, self.yy), *coef)
assert np.all(model == data)
# now test edge cases
with pytest.raises(ValueError):
Gauss2D.model(1)
with pytest.raises(ValueError):
Gauss2D.model(*np.arange(10))
def test_gen_model(self):
"""Test model"""
params = np.array([1,
70,
25,
20,
10,
0.5,
1])
myg = Gauss2D.gen_model(self.noisy_data, *params)
assert_allclose(self.raw_data, myg)
def setUp(self):
# make x, y ranges
self.x = np.arange(64)
self.y = np.arange(128)
# make meshgrid
self.xx, self.yy = np.meshgrid(self.x, self.y)
self.noisy_data = tif.imread(
os.path.join(os.path.dirname(__file__), "..", "fixtures",
"noisy_data.tif"))
self.raw_data = tif.imread(
os.path.join(os.path.dirname(__file__), "..", "fixtures",
"raw_data.tif"))
self.myg = Gauss2D(self.noisy_data)
def test_model(self):
"""Test model classmethod in Gauss2D class"""
# first test acceptable values for goodness
funcs = (Gauss2D.gauss2D, Gauss2D.gauss2D_norot, Gauss2D.gauss2D_sym)
coefs = ([12, 20, 70, 20, 30, 0.5, 2],
[12, 20, 70, 20, 30, 2],
[12, 20, 70, 20, 2])
for func, coef in zip(funcs, coefs):
data = func((self.xx, self.yy), *coef)
model = Gauss2D.model((self.xx, self.yy), *coef)
assert np.all(model == data)
# now test edge cases
assert_raises(ValueError, Gauss2D.model, 1)
assert_raises(ValueError, Gauss2D.model, *np.arange(10))
def test_gen_model(self):
"""Test model"""
params = np.array([1, 70, 25, 20, 10, 0.5, 1])
myg = Gauss2D.gen_model(self.noisy_data, *params)
assert_allclose(self.raw_data, myg)
def setUp(self):
"""Basic set up"""
data = np.zeros((2001, 2001))
self.gauss = Gauss2D(data)
