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tools_test.py
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# SPDX-License-Identifier: BSD-3-Clause
# Copyright (c) 2023 Scipp contributors (https://github.com/scipp)
import pytest
import scipp as sc
from scipp.testing import assert_allclose
from ess.reflectometry.tools import combine_curves, scale_reflectivity_curves_to_overlap
def curve(d, qmin, qmax):
return sc.DataArray(data=d, coords={'Q': sc.linspace('Q', qmin, qmax, len(d) + 1)})
def test_reflectivity_curve_scaling():
data = sc.concat(
(
sc.ones(dims=['Q'], shape=[10], with_variances=True),
0.5 * sc.ones(dims=['Q'], shape=[15], with_variances=True),
),
dim='Q',
)
data.variances[:] = 0.1
curves = scale_reflectivity_curves_to_overlap(
(curve(data, 0, 0.3), curve(0.8 * data, 0.2, 0.7), curve(0.1 * data, 0.6, 1.0)),
)
assert_allclose(curves[0].data, data, rtol=sc.scalar(1e-5))
assert_allclose(curves[1].data, 0.5 * data, rtol=sc.scalar(1e-5))
assert_allclose(curves[2].data, 0.25 * data, rtol=sc.scalar(1e-5))
def test_reflectivity_curve_scaling_return_factors():
data = sc.concat(
(
sc.ones(dims=['Q'], shape=[10], with_variances=True),
0.5 * sc.ones(dims=['Q'], shape=[15], with_variances=True),
),
dim='Q',
)
data.variances[:] = 0.1
factors = scale_reflectivity_curves_to_overlap(
(curve(data, 0, 0.3), curve(0.8 * data, 0.2, 0.7), curve(0.1 * data, 0.6, 1.0)),
return_scaling_factors=True,
)
assert_allclose(factors[0], sc.scalar(1.0), rtol=sc.scalar(1e-5))
assert_allclose(factors[1], sc.scalar(0.5 / 0.8), rtol=sc.scalar(1e-5))
assert_allclose(factors[2], sc.scalar(0.25 / 0.1), rtol=sc.scalar(1e-5))
def test_combined_curves():
qgrid = sc.linspace('Q', 0, 1, 26)
data = sc.concat(
(
sc.ones(dims=['Q'], shape=[10], with_variances=True),
0.5 * sc.ones(dims=['Q'], shape=[15], with_variances=True),
),
dim='Q',
)
data.variances[:] = 0.1
curves = (
curve(data, 0, 0.3),
curve(0.5 * data, 0.2, 0.7),
curve(0.25 * data, 0.6, 1.0),
)
combined = combine_curves(curves, qgrid)
assert_allclose(
combined.data,
sc.array(
dims='Q',
values=[
1.0,
1,
1,
0.5,
0.5,
0.5,
0.5,
0.5,
0.5,
0.5,
0.25,
0.25,
0.25,
0.25,
0.25,
0.25,
0.25,
0.25,
0.25,
0.125,
0.125,
0.125,
0.125,
0.125,
0.125,
],
variances=[
0.1,
0.1,
0.1,
0.1,
0.1,
0.02,
0.02,
0.025,
0.025,
0.025,
0.025,
0.025,
0.025,
0.025,
0.025,
0.005,
0.005,
0.00625,
0.00625,
0.00625,
0.00625,
0.00625,
0.00625,
0.00625,
0.00625,
],
),
)
@pytest.mark.filterwarnings("ignore:invalid value encountered in divide")
def test_combined_curves_resolution():
qgrid = sc.linspace('Q', 0, 1, 26)
data = sc.concat(
(
sc.ones(dims=['Q'], shape=[10], with_variances=True),
0.5 * sc.ones(dims=['Q'], shape=[15], with_variances=True),
),
dim='Q',
)
data.variances[:] = 0.1
curves = (
curve(data, 0, 0.3),
curve(0.5 * data, 0.2, 0.7),
curve(0.25 * data, 0.6, 1.0),
)
curves[0].coords['Q_resolution'] = sc.midpoints(curves[0].coords['Q']) / 5
combined = combine_curves(curves, qgrid)
assert 'Q_resolution' in combined.coords
assert combined.coords['Q_resolution'][0] == curves[0].coords['Q_resolution'][1]
assert sc.isnan(combined.coords['Q_resolution'][-1])