def test_crop_bkg_kwargs(self):
"""
Test crop and bkg sub with kwargs
"""
file_name = path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat")
r = refl_data.Scan(file_name, io.i07_dat_parser)
p0 = [
5,
5,
1,
1,
1,
1000,
]
r.crop(
cropping.crop_around_peak_2d,
kwargs={"x_size": 20},
)
r.bkg_sub(
background.fit_gaussian_2d,
kwargs={"p0": p0},
)
a2 = np.zeros((3))
np.any(np.not_equal(unp.nominal_values(r.R), a2))
np.any(np.not_equal(unp.std_devs(r.R), a2))
np.any(np.not_equal(r.n_pixels, a2))
def test_init_d(self):
"""
Test init with wrong file path
"""
with self.assertRaises(FileNotFoundError):
file_name = path.join(path.dirname(islatu.__file__),
"tests/test_files/test_d.dat")
r = refl_data.Scan(file_name, io.i07_dat_parser)
def test_init_e(self):
"""
Test init with correct file path but q_axis as none
"""
file_name = path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat")
r = refl_data.Scan(file_name, io.i07_dat_parser, q_axis_name=None)
assert_equal(len(r.data["file"]), 3)
assert_almost_equal(unp.nominal_values(r.q), r.data["qdcd"], decimal=5)
def test_concatenate(self):
"""
Test concatenation
"""
y1 = np.ones(10) * 10
dy1 = np.ones(10)
y2 = np.ones(10) * 5
dy2 = np.ones(10) * 0.5
x1 = np.arange(1, 11, 1)
dx1 = np.copy(x1) * 0.05
x2 = np.arange(8, 18, 1)
dx2 = np.copy(x2) * 0.05
scan1 = refl_data.Scan(
path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat"),
io.i07_dat_parser,
)
scan2 = refl_data.Scan(
path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat"),
io.i07_dat_parser,
)
scan1.q = unumpy.uarray(x1, dx1)
scan1.R = unumpy.uarray(y1, dy1)
scan2.q = unumpy.uarray(x2, dx2)
scan2.R = unumpy.uarray(y2, dy2)
scan_list = [scan1, scan2]
exp_y1 = unumpy.uarray(np.append(y1, y2), np.append(dy1, dy2))
exp_x1 = unumpy.uarray(np.append(x1, x2), np.append(dx1, dx2))
q, r = stitching.concatenate(scan_list)
assert_almost_equal(unumpy.nominal_values(r),
unumpy.nominal_values(exp_y1))
assert_almost_equal(unumpy.std_devs(r), unumpy.std_devs(exp_y1))
assert_almost_equal(unumpy.nominal_values(q),
unumpy.nominal_values(exp_x1))
assert_almost_equal(unumpy.std_devs(q), unumpy.std_devs(exp_x1))
def test_correct_attentuation(self):
"""
Test correction of attenutation
"""
y1 = np.ones(10) * 10
dy1 = np.ones(10)
y2 = np.ones(10) * 5
dy2 = np.ones(10) * 0.5
x1 = np.arange(1, 11, 1)
dx1 = np.copy(x1) * 0.05
x2 = np.arange(8, 18, 1)
dx2 = np.copy(x2) * 0.05
scan1 = refl_data.Scan(
path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat"),
io.i07_dat_parser,
)
scan2 = refl_data.Scan(
path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat"),
io.i07_dat_parser,
)
scan1.q = unumpy.uarray(x1, dx1)
scan1.R = unumpy.uarray(y1, dy1)
scan2.q = unumpy.uarray(x2, dx2)
scan2.R = unumpy.uarray(y2, dy2)
scan_list = [scan1, scan2]
exp_y1 = np.ones(10) * 10
exp_dy1 = np.ones(10)
exp_y2 = np.ones(10) * 10
exp_dy2 = np.append(np.ones(3) * 0.8164966, np.ones(7) * 1.1547005)
scan_list = stitching.correct_attentuation(scan_list)
assert_almost_equal(unumpy.nominal_values(scan_list[0].R), exp_y1)
assert_almost_equal(unumpy.std_devs(scan_list[0].R), exp_dy1)
assert_almost_equal(unumpy.nominal_values(scan_list[1].R), exp_y2)
assert_almost_equal(unumpy.std_devs(scan_list[1].R), exp_dy2)
def test_repr(self):
"""
Test string output
"""
file_name = path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat")
r = refl_data.Scan(file_name, io.i07_dat_parser, q_axis_name=None)
assert_equal(
r.__repr__(),
"The file: {} contains 3 images from q = 0.0100 to q = 0.0110.".
format(file_name),
)
def test_resolution_function(self):
"""
Test resolution_function from pixel
"""
file_name = path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat")
r = refl_data.Scan(file_name, io.i07_dat_parser)
r.crop(cropping.crop_around_peak_2d)
r.bkg_sub(background.fit_gaussian_2d)
q_store = unp.nominal_values(r.q)
r.resolution_function(1)
assert_equal(unp.nominal_values(r.q), q_store)
np.any(np.not_equal(unp.std_devs(r.q), np.zeros((3))))
def test_transmission(self):
"""
Test transmission correction
"""
file_name = path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat")
r = refl_data.Scan(file_name, io.i07_dat_parser)
r.crop(cropping.crop_around_peak_2d)
r.bkg_sub(background.fit_gaussian_2d)
r_store = r.R
r.transmission_normalisation()
np.any(
np.not_equal(unp.nominal_values(r.R), unp.nominal_values(r_store)))
def test_footprint(self):
"""
Test footprint corrections
"""
file_name = path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat")
r = refl_data.Scan(file_name, io.i07_dat_parser)
r.crop(cropping.crop_around_peak_2d)
r.bkg_sub(background.fit_gaussian_2d)
r_store = r.R
r.footprint_correction(100e-6, 100e-3)
np.any(
np.not_equal(unp.nominal_values(r.R), unp.nominal_values(r_store)))
def test_crop_bkg(self):
"""
Test crop and bkg sub
"""
file_name = path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat")
r = refl_data.Scan(file_name, io.i07_dat_parser)
r.crop(cropping.crop_around_peak_2d)
r.bkg_sub(background.fit_gaussian_2d)
a2 = np.zeros((3))
np.any(np.not_equal(unp.nominal_values(r.R), a2))
np.any(np.not_equal(unp.std_devs(r.R), a2))
np.any(np.not_equal(r.n_pixels, a2))
def test_init_a(self):
"""
Test init with correct file path
"""
file_name = path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat")
r = refl_data.Scan(file_name, io.i07_dat_parser)
assert_equal(len(r.data["file"]), 3)
assert_equal(r.data["file"][0],
"islatu/tests/test_files/location/pilatus1/tiff_a.tif")
assert_equal(r.data["file"][1],
"islatu/tests/test_files/location/pilatus1/tiff_b.tif")
assert_equal(r.data["file"][2],
"islatu/tests/test_files/location/pilatus1/tiff_c.tif")
def test_qdcd_normalisation(self):
"""
Test qdcd normalisation
"""
file_name = path.join(path.dirname(islatu.__file__),
"tests/test_files/qdcd_norm.dat")
normalisation_metadata, normalisation_data = io.i07_dat_parser(
file_name)
itp = splrep(normalisation_data["qdcd_"], normalisation_data["adc2"])
file_name = path.join(path.dirname(islatu.__file__),
"tests/test_files/test_a.dat")
r = refl_data.Scan(file_name, io.i07_dat_parser)
r.crop(cropping.crop_around_peak_2d)
r.bkg_sub(background.fit_gaussian_2d)
r_store = r.R
r.qdcd_normalisation(itp)
np.any(
np.not_equal(unp.nominal_values(r.R), unp.nominal_values(r_store)))
