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"""Test the run module using the example calculation from "DSPC_standard_layers.py".
We use the example for both a reflectivity calculation, and Bayesian analysis using the Dream algorithm.
"""
from unittest import mock
import numpy as np
import pytest
import RAT
import RAT.outputs
import RAT.rat_core
from RAT.utils.enums import Calculations, Geometries, LayerModels, Procedures
from tests.utils import check_results_equal
@pytest.fixture
def input_project():
"""A cut-down version of the input Project object for a reflectivity calculation set out in
"DSPC_standard_layers.py".
"""
project = RAT.Project(
name="original_dspc_bilayer",
calculation="non polarised",
model="standard layers",
geometry="substrate/liquid",
absorption=False,
)
# Set up the relevant parameters
project.parameters.append(
name="Oxide Thickness",
min=5.0,
value=19.54,
max=60.0,
fit=True,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="Oxide SLD",
min=3.39e-06,
value=3.39e-06,
max=3.41e-06,
fit=False,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="SAM Tails Thickness",
min=15.0,
value=22.66,
max=40.0,
fit=True,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="SAM Tails SLD",
min=-5e-07,
value=-4.01e-07,
max=-3e-07,
fit=False,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="SAM Tails Hydration",
min=1.0,
value=5.252,
max=50.0,
fit=True,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="SAM Roughness",
min=1.0,
value=5.64,
max=15.0,
fit=True,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="CW Thickness",
min=10.0,
value=17.12,
max=28.0,
fit=True,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="CW SLD",
min=0.0,
value=0.0,
max=1e-09,
fit=False,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="SAM Heads Thickness",
min=5.0,
value=8.56,
max=17.0,
fit=True,
prior_type="gaussian",
mu=10.0,
sigma=2.0,
)
project.parameters.append(
name="SAM Heads SLD",
min=1.0e-07,
value=1.75e-06,
max=2.0e-06,
fit=False,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="SAM Heads Hydration",
min=10.0,
value=45.45,
max=50.0,
fit=True,
prior_type="uniform",
mu=30.0,
sigma=3.0,
)
project.parameters.append(
name="Bilayer Heads Thickness",
min=7.0,
value=10.7,
max=17.0,
fit=True,
prior_type="gaussian",
mu=10.0,
sigma=2.0,
)
project.parameters.append(
name="Bilayer Heads SLD",
min=5.0e-07,
value=1.47e-06,
max=1.5e-06,
fit=False,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="Bilayer Roughness",
min=2.0,
value=6.014,
max=15.0,
fit=True,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="Bilayer Tails Thickness",
min=14.0,
value=17.82,
max=22.0,
fit=True,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="Bilayer Tails SLD",
min=-5.0e-07,
value=-4.61e-07,
max=0.0,
fit=False,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="Bilayer Tails Hydration",
min=10.0,
value=17.64,
max=50.0,
fit=True,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="Bilayer Heads Hydration",
min=10.0,
value=36.15,
max=50.0,
fit=True,
prior_type="gaussian",
mu=30.0,
sigma=3.0,
)
project.parameters.append(
name="CW Hydration",
min=99.9,
value=100.0,
max=100.0,
fit=False,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.append(
name="Oxide Hydration",
min=0.0,
value=23.61,
max=60.0,
fit=True,
prior_type="uniform",
mu=0.0,
sigma=np.inf,
)
project.parameters.set_fields(0, max=10)
del project.bulk_in[0]
project.bulk_in.append(name="Silicon", min=2.0e-06, value=2.073e-06, max=2.1e-06, fit=False)
del project.bulk_out[0]
project.bulk_out.append(name="D2O", min=5.50e-06, value=5.98e-06, max=6.4e-06, fit=True)
project.bulk_out.append(name="SMW", min=1.0e-06, value=2.21e-06, max=4.99e-06, fit=True)
del project.scalefactors[0]
project.scalefactors.append(name="Scalefactor 1", min=0.05, value=0.10, max=0.2, fit=False)
project.scalefactors.append(name="Scalefactor 2", min=0.05, value=0.15, max=0.2, fit=False)
del project.backgrounds[0]
del project.background_parameters[0]
project.background_parameters.append(
name="Background parameter D2O",
min=5.0e-10,
value=2.23e-06,
max=7.0e-06,
fit=True,
)
project.background_parameters.append(
name="Background parameter SMW",
min=1.0e-10,
value=3.38e-06,
max=4.99e-06,
fit=True,
)
return project
@pytest.fixture
def reflectivity_calculation_problem():
"""The output C++ ProblemDefinition object for a reflectivity calculation of the project set out in
"DSPC_standard_layers.py".
"""
problem = RAT.rat_core.ProblemDefinition()
problem.TF = Calculations.NonPolarised
problem.modelType = LayerModels.StandardLayers
problem.geometry = Geometries.SubstrateLiquid
problem.useImaginary = False
problem.params = np.array(
[
3.000e00,
1.954e01,
3.390e-06,
2.266e01,
-4.010e-07,
5.252e00,
5.640e00,
1.712e01,
0.000e00,
8.560e00,
1.750e-06,
4.545e01,
1.070e01,
1.470e-06,
6.014e00,
1.782e01,
-4.610e-07,
1.764e01,
3.615e01,
1.000e02,
2.361e01,
],
)
problem.bulkIn = np.array([2.073e-06])
problem.bulkOut = np.array([5.98e-06, 2.21e-06])
problem.qzshifts = np.array([0.0])
problem.scalefactors = np.array([0.1, 0.15])
problem.domainRatio = np.array([])
problem.backgroundParams = np.array([2.23e-06, 3.38e-06])
problem.resolutionParams = np.array([0.03])
problem.contrastBulkIns = np.array([1.0, 1.0])
problem.contrastBulkOuts = np.array([1.0, 2.0])
problem.contrastQzshifts = np.array([0.0, 0.0])
problem.contrastScalefactors = np.array([1.0, 2.0])
problem.contrastBackgroundParams = np.array([1.0, 2.0])
problem.contrastBackgroundActions = np.array([1.0, 1.0])
problem.contrastResolutionParams = np.array([1.0, 1.0])
problem.contrastCustomFiles = np.array([np.nan, np.nan])
problem.contrastDomainRatios = np.array([0.0, 0.0])
problem.resample = np.array([0.0, 0.0])
problem.dataPresent = np.array([1.0, 1.0])
problem.oilChiDataPresent = np.array([0.0, 0.0])
problem.numberOfContrasts = 2.0
problem.numberOfLayers = 6.0
problem.numberOfDomainContrasts = 0.0
problem.fitParams = np.array(
[
3.000e00,
1.954e01,
2.266e01,
5.252e00,
5.640e00,
1.712e01,
8.560e00,
4.545e01,
1.070e01,
6.014e00,
1.782e01,
1.764e01,
3.615e01,
2.361e01,
2.230e-06,
3.380e-06,
5.980e-06,
2.210e-06,
],
)
problem.otherParams = np.array(
[
3.390e-06,
-4.010e-07,
0.000e00,
1.750e-06,
1.470e-06,
-4.610e-07,
1.000e02,
1.000e-01,
1.500e-01,
2.073e-06,
3.000e-02,
],
)
problem.fitLimits = np.array(
[
[1.00e00, 1.00e01],
[5.00e00, 6.00e01],
[1.50e01, 3.50e01],
[1.00e00, 5.00e01],
[1.00e00, 1.50e01],
[1.00e01, 2.80e01],
[5.00e00, 1.70e01],
[1.00e01, 5.00e01],
[7.00e00, 1.70e01],
[2.00e00, 1.50e01],
[1.40e01, 2.20e01],
[1.00e01, 5.00e01],
[1.00e01, 5.00e01],
[0.00e00, 6.00e01],
[5.00e-10, 7.00e-06],
[1.00e-10, 4.99e-06],
[5.50e-06, 6.40e-06],
[1.00e-06, 4.99e-06],
],
)
problem.otherLimits = np.array(
[
[3.39e-06, 3.41e-06],
[-5.00e-07, -3.00e-07],
[0.00e00, 1.00e-09],
[1.00e-07, 2.00e-06],
[5.00e-07, 1.50e-06],
[-5.00e-07, 0.00e00],
[9.99e01, 1.00e02],
[5.00e-02, 2.00e-01],
[5.00e-02, 2.00e-01],
[2.00e-06, 2.10e-06],
[1.00e-02, 5.00e-02],
],
)
return problem
@pytest.fixture
def dream_problem():
"""The output C++ ProblemDefinition object for a Dream optimisation of the project set out in
"DSPC_standard_layers.py".
This optimisation used the parameters: nSamples=50000, nChains=10.
"""
problem = RAT.rat_core.ProblemDefinition()
problem.TF = Calculations.NonPolarised
problem.modelType = LayerModels.StandardLayers
problem.geometry = Geometries.SubstrateLiquid
problem.useImaginary = False
problem.params = np.array(
[
6.19503045e00,
1.84420960e01,
3.39000000e-06,
2.11039621e01,
-4.01000000e-07,
8.75538121e00,
3.72292994e00,
1.84624551e01,
0.00000000e00,
1.02316734e01,
1.75000000e-06,
2.31156093e01,
1.09906265e01,
1.47000000e-06,
5.71005361e00,
1.67933822e01,
-4.61000000e-07,
1.72009856e01,
3.00260126e01,
1.00000000e02,
2.94448999e01,
],
)
problem.bulkIn = np.array([2.073e-06])
problem.bulkOut = np.array([6.01489149e-06, 1.59371685e-06])
problem.qzshifts = np.array([0.0])
problem.scalefactors = np.array([0.1, 0.15])
problem.domainRatio = np.array([])
problem.backgroundParams = np.array([2.37113128e-06, 1.99006694e-06])
problem.resolutionParams = np.array([0.03])
problem.contrastBulkIns = np.array([1.0, 1.0])
problem.contrastBulkOuts = np.array([1.0, 2.0])
problem.contrastQzshifts = np.array([0.0, 0.0])
problem.contrastScalefactors = np.array([1.0, 2.0])
problem.contrastBackgroundParams = np.array([1.0, 2.0])
problem.contrastBackgroundActions = np.array([1.0, 1.0])
problem.contrastResolutionParams = np.array([1.0, 1.0])
problem.contrastCustomFiles = np.array([np.nan, np.nan])
problem.contrastDomainRatios = np.array([0.0, 0.0])
problem.resample = np.array([0.0, 0.0])
problem.dataPresent = np.array([1.0, 1.0])
problem.oilChiDataPresent = np.array([0.0, 0.0])
problem.numberOfContrasts = 2.0
problem.numberOfLayers = 6.0
problem.numberOfDomainContrasts = 0.0
problem.fitParams = np.array(
[
6.19503045e00,
1.84420960e01,
2.11039621e01,
8.75538121e00,
3.72292994e00,
1.84624551e01,
1.02316734e01,
2.31156093e01,
1.09906265e01,
5.71005361e00,
1.67933822e01,
1.72009856e01,
3.00260126e01,
2.94448999e01,
2.37113128e-06,
1.99006694e-06,
6.01489149e-06,
1.59371685e-06,
],
)
problem.otherParams = np.array(
[
3.390e-06,
-4.010e-07,
0.000e00,
1.750e-06,
1.470e-06,
-4.610e-07,
1.000e02,
1.000e-01,
1.500e-01,
2.073e-06,
3.000e-02,
0.000e00,
],
)
problem.fitLimits = np.array(
[
[1.00e00, 1.00e01],
[5.00e00, 6.00e01],
[1.50e01, 3.50e01],
[1.00e00, 5.00e01],
[1.00e00, 1.50e01],
[1.00e01, 2.80e01],
[5.00e00, 1.70e01],
[1.00e01, 5.00e01],
[7.00e00, 1.70e01],
[2.00e00, 1.50e01],
[1.40e01, 2.20e01],
[1.00e01, 5.00e01],
[1.00e01, 5.00e01],
[0.00e00, 6.00e01],
[5.00e-10, 7.00e-06],
[1.00e-10, 4.99e-06],
[5.50e-06, 6.40e-06],
[1.00e-06, 4.99e-06],
],
)
problem.otherLimits = np.array(
[
[3.39e-06, 3.41e-06],
[-5.00e-07, -3.00e-07],
[0.00e00, 1.00e-09],
[1.00e-07, 2.00e-06],
[5.00e-07, 1.50e-06],
[-5.00e-07, 0.00e00],
[9.99e01, 1.00e02],
[5.00e-02, 2.00e-01],
[5.00e-02, 2.00e-01],
[2.00e-06, 2.10e-06],
[1.00e-02, 5.00e-02],
[0.00e00, 0.00e00],
],
)
return problem
@pytest.mark.parametrize(
["test_procedure", "test_output_problem", "test_output_results", "test_bayes", "test_results"],
[
(
Procedures.Calculate,
"reflectivity_calculation_problem",
"reflectivity_calculation_output_results",
None,
"reflectivity_calculation_results",
),
(Procedures.Dream, "dream_problem", "dream_output_results", "dream_bayes", "dream_results"),
],
)
def test_run(test_procedure, test_output_problem, test_output_results, test_bayes, test_results, request) -> None:
input_project = request.getfixturevalue("input_project")
test_output_problem = request.getfixturevalue(test_output_problem)
test_output_results = request.getfixturevalue(test_output_results)
if test_bayes:
test_bayes = request.getfixturevalue(test_bayes)
test_results = request.getfixturevalue(test_results)
with mock.patch.object(
RAT.rat_core,
"RATMain",
mock.MagicMock(return_value=(test_output_problem, test_output_results, test_bayes)),
):
# Use default project as we patch RATMain to give the desired outputs
project, results = RAT.run(input_project, RAT.set_controls(procedure=test_procedure))
check_results_equal(test_results, results)