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919 lines (830 loc) · 30.4 KB
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"""Test the inputs module."""
import pathlib
import pickle
from itertools import chain
from unittest import mock
import numpy as np
import pytest
import RATapi
import RATapi.wrappers
from RATapi.inputs import check_indices, make_cells, make_controls, make_input, make_problem
from RATapi.rat_core import Cells, Checks, Control, Limits, Priors, ProblemDefinition
from RATapi.utils.enums import (
BoundHandling,
Calculations,
Display,
Geometries,
LayerModels,
Parallel,
Procedures,
TypeOptions,
)
from tests.utils import dummy_function
@pytest.fixture
def standard_layers_project():
"""Add parameters to the default project for a non polarised calculation."""
test_project = RATapi.Project(
data=RATapi.ClassList([RATapi.models.Data(name="Test Data", data=np.array([[1.0, 1.0, 1.0]]))]),
)
test_project.parameters.append(name="Test Thickness")
test_project.parameters.append(name="Test SLD")
test_project.parameters.append(name="Test Roughness")
test_project.custom_files.append(
name="Test Custom File",
filename="python_test.py",
function_name="dummy_function",
language="python",
)
test_project.layers.append(
name="Test Layer",
thickness="Test Thickness",
SLD="Test SLD",
roughness="Test Roughness",
)
test_project.contrasts.append(
name="Test Contrast",
data="Test Data",
background="Background 1",
bulk_in="SLD Air",
bulk_out="SLD D2O",
scalefactor="Scalefactor 1",
resolution="Resolution 1",
model=["Test Layer"],
)
return test_project
@pytest.fixture
def domains_project():
"""Add parameters to the default project for a domains calculation."""
test_project = RATapi.Project(
calculation=Calculations.Domains,
data=RATapi.ClassList([RATapi.models.Data(name="Test Data", data=np.array([[1.0, 1.0, 1.0]]))]),
)
test_project.parameters.append(name="Test Thickness")
test_project.parameters.append(name="Test SLD")
test_project.parameters.append(name="Test Roughness")
test_project.custom_files.append(name="Test Custom File", filename="matlab_test.m", language="matlab")
test_project.layers.append(
name="Test Layer",
thickness="Test Thickness",
SLD="Test SLD",
roughness="Test Roughness",
)
test_project.domain_contrasts.append(name="up", model=["Test Layer"])
test_project.domain_contrasts.append(name="down", model=["Test Layer"])
test_project.contrasts.append(
name="Test Contrast",
data="Test Data",
background="Background 1",
bulk_in="SLD Air",
bulk_out="SLD D2O",
scalefactor="Scalefactor 1",
resolution="Resolution 1",
domain_ratio="Domain Ratio 1",
model=["down", "up"],
)
return test_project
@pytest.fixture
def custom_xy_project():
"""Add parameters to the default project for a non polarised calculation and use the custom xy model."""
test_project = RATapi.Project(model=LayerModels.CustomXY)
test_project.parameters.append(name="Test Thickness")
test_project.parameters.append(name="Test SLD")
test_project.parameters.append(name="Test Roughness")
test_project.custom_files.append(name="Test Custom File", filename="cpp_test.dll", language="cpp")
test_project.contrasts.append(
name="Test Contrast",
data="Simulation",
background="Background 1",
bulk_in="SLD Air",
bulk_out="SLD D2O",
scalefactor="Scalefactor 1",
resolution="Resolution 1",
model=["Test Custom File"],
)
return test_project
@pytest.fixture
def standard_layers_problem():
"""The expected problem object from "standard_layers_project"."""
problem = ProblemDefinition()
problem.TF = Calculations.NonPolarised
problem.modelType = LayerModels.StandardLayers
problem.geometry = Geometries.AirSubstrate
problem.useImaginary = False
problem.params = [3.0, 0.0, 0.0, 0.0]
problem.bulkIn = [0.0]
problem.bulkOut = [6.35e-06]
problem.qzshifts = []
problem.scalefactors = [0.23]
problem.domainRatio = []
problem.backgroundParams = [1e-06]
problem.resolutionParams = [0.03]
problem.contrastBulkIns = [1]
problem.contrastBulkOuts = [1]
problem.contrastQzshifts = []
problem.contrastScalefactors = [1]
problem.contrastBackgroundParams = [1]
problem.contrastBackgroundActions = [1]
problem.contrastResolutionParams = [1]
problem.contrastCustomFiles = [float("NaN")]
problem.contrastDomainRatios = [0]
problem.resample = [False]
problem.dataPresent = [1]
problem.oilChiDataPresent = [0]
problem.numberOfContrasts = 1
problem.numberOfLayers = 1
problem.numberOfDomainContrasts = 0
problem.fitParams = [3.0]
problem.otherParams = [0.0, 0.0, 0.0, 1e-06, 0.23, 0.0, 6.35e-06, 0.03]
problem.fitLimits = [[1.0, 5.0]]
problem.otherLimits = [
[0.0, 0.0],
[0.0, 0.0],
[0.0, 0.0],
[1e-07, 1e-05],
[0.02, 0.25],
[0.0, 0.0],
[6.2e-06, 6.35e-06],
[0.01, 0.05],
]
return problem
@pytest.fixture
def domains_problem():
"""The expected problem object from "standard_layers_project"."""
problem = ProblemDefinition()
problem.TF = Calculations.Domains
problem.modelType = LayerModels.StandardLayers
problem.geometry = Geometries.AirSubstrate
problem.useImaginary = False
problem.params = [3.0, 0.0, 0.0, 0.0]
problem.bulkIn = [0.0]
problem.bulkOut = [6.35e-06]
problem.qzshifts = []
problem.scalefactors = [0.23]
problem.domainRatio = [0.5]
problem.backgroundParams = [1e-06]
problem.resolutionParams = [0.03]
problem.contrastBulkIns = [1]
problem.contrastBulkOuts = [1]
problem.contrastQzshifts = []
problem.contrastScalefactors = [1]
problem.contrastBackgroundParams = [1]
problem.contrastBackgroundActions = [1]
problem.contrastResolutionParams = [1]
problem.contrastCustomFiles = [float("NaN")]
problem.contrastDomainRatios = [1]
problem.resample = [False]
problem.dataPresent = [1]
problem.oilChiDataPresent = [0]
problem.numberOfContrasts = 1
problem.numberOfLayers = 1
problem.numberOfDomainContrasts = 2
problem.fitParams = [3.0]
problem.otherParams = [0.0, 0.0, 0.0, 1e-06, 0.23, 0.0, 6.35e-06, 0.03, 0.5]
problem.fitLimits = [[1.0, 5.0]]
problem.otherLimits = [
[0.0, 0.0],
[0.0, 0.0],
[0.0, 0.0],
[1e-07, 1e-05],
[0.02, 0.25],
[0.0, 0.0],
[6.2e-06, 6.35e-06],
[0.01, 0.05],
[0.4, 0.6],
]
return problem
@pytest.fixture
def custom_xy_problem():
"""The expected problem object from "custom_xy_project"."""
problem = ProblemDefinition()
problem.TF = Calculations.NonPolarised
problem.modelType = LayerModels.CustomXY
problem.geometry = Geometries.AirSubstrate
problem.useImaginary = False
problem.params = [3.0, 0.0, 0.0, 0.0]
problem.bulkIn = [0.0]
problem.bulkOut = [6.35e-06]
problem.qzshifts = []
problem.scalefactors = [0.23]
problem.domainRatio = []
problem.backgroundParams = [1e-06]
problem.resolutionParams = [0.03]
problem.contrastBulkIns = [1]
problem.contrastBulkOuts = [1]
problem.contrastQzshifts = []
problem.contrastScalefactors = [1]
problem.contrastBackgroundParams = [1]
problem.contrastBackgroundActions = [1]
problem.contrastResolutionParams = [1]
problem.contrastCustomFiles = [1]
problem.contrastDomainRatios = [0]
problem.resample = [False]
problem.dataPresent = [0]
problem.oilChiDataPresent = [0]
problem.numberOfContrasts = 1
problem.numberOfLayers = 0
problem.numberOfDomainContrasts = 0
problem.fitParams = [3.0]
problem.otherParams = [0.0, 0.0, 0.0, 1e-06, 0.23, 0.0, 6.35e-06, 0.03]
problem.fitLimits = [[1.0, 5.0]]
problem.otherLimits = [
[0.0, 0.0],
[0.0, 0.0],
[0.0, 0.0],
[1e-07, 1e-05],
[0.02, 0.25],
[0.0, 0.0],
[6.2e-06, 6.35e-06],
[0.01, 0.05],
]
return problem
@pytest.fixture
def standard_layers_cells():
"""The expected cells object from "standard_layers_project"."""
cells = Cells()
cells.f1 = [[0, 1]]
cells.f2 = [np.array([[1.0, 1.0, 1.0]])]
cells.f3 = [[1.0, 1.0]]
cells.f4 = [[1.0, 1.0]]
cells.f5 = [[1]]
cells.f6 = [[2, 3, 4, float("nan"), 2]]
cells.f7 = ["Substrate Roughness", "Test Thickness", "Test SLD", "Test Roughness"]
cells.f8 = ["Background Param 1"]
cells.f9 = ["Scalefactor 1"]
cells.f10 = []
cells.f11 = ["SLD Air"]
cells.f12 = ["SLD D2O"]
cells.f13 = ["Resolution Param 1"]
cells.f14 = [dummy_function]
cells.f15 = [TypeOptions.Constant]
cells.f16 = [TypeOptions.Constant]
cells.f17 = [[[]]]
cells.f18 = []
cells.f19 = []
cells.f20 = []
cells.f21 = ["D2O"]
return cells
@pytest.fixture
def domains_cells():
"""The expected cells object from "domains_project"."""
cells = Cells()
cells.f1 = [[0, 1]]
cells.f2 = [np.array([[1.0, 1.0, 1.0]])]
cells.f3 = [[1.0, 1.0]]
cells.f4 = [[1.0, 1.0]]
cells.f5 = [[2, 1]]
cells.f6 = [[2, 3, 4, float("nan"), 2]]
cells.f7 = ["Substrate Roughness", "Test Thickness", "Test SLD", "Test Roughness"]
cells.f8 = ["Background Param 1"]
cells.f9 = ["Scalefactor 1"]
cells.f10 = []
cells.f11 = ["SLD Air"]
cells.f12 = ["SLD D2O"]
cells.f13 = ["Resolution Param 1"]
cells.f14 = [dummy_function]
cells.f15 = [TypeOptions.Constant]
cells.f16 = [TypeOptions.Constant]
cells.f17 = [[[]]]
cells.f18 = [[0, 1], [0, 1]]
cells.f19 = [[1], [1]]
cells.f20 = ["Domain Ratio 1"]
cells.f21 = ["D2O"]
return cells
@pytest.fixture
def custom_xy_cells():
"""The expected cells object from "custom_xy_project"."""
cells = Cells()
cells.f1 = [[0, 1]]
cells.f2 = [np.empty([0, 3])]
cells.f3 = [[0.0, 0.0]]
cells.f4 = [[0.005, 0.7]]
cells.f5 = [[]]
cells.f6 = []
cells.f7 = ["Substrate Roughness", "Test Thickness", "Test SLD", "Test Roughness"]
cells.f8 = ["Background Param 1"]
cells.f9 = ["Scalefactor 1"]
cells.f10 = []
cells.f11 = ["SLD Air"]
cells.f12 = ["SLD D2O"]
cells.f13 = ["Resolution Param 1"]
cells.f14 = [dummy_function]
cells.f15 = [TypeOptions.Constant]
cells.f16 = [TypeOptions.Constant]
cells.f17 = [[[]]]
cells.f18 = []
cells.f19 = []
cells.f20 = []
cells.f21 = ["D2O"]
return cells
@pytest.fixture
def non_polarised_limits():
"""The expected limits object from "standard_layers_project" and "custom_xy_project"."""
limits = Limits()
limits.param = [[1.0, 5.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
limits.backgroundParam = [[1e-7, 1e-5]]
limits.qzshift = []
limits.scalefactor = [[0.02, 0.25]]
limits.bulkIn = [[0.0, 0.0]]
limits.bulkOut = [[6.2e-6, 6.35e-6]]
limits.resolutionParam = [[0.01, 0.05]]
limits.domainRatio = []
return limits
@pytest.fixture
def domains_limits():
"""The expected limits object from "domains_project"."""
limits = Limits()
limits.param = [[1.0, 5.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0]]
limits.backgroundParam = [[1e-7, 1e-5]]
limits.qzshift = []
limits.scalefactor = [[0.02, 0.25]]
limits.bulkIn = [[0.0, 0.0]]
limits.bulkOut = [[6.2e-6, 6.35e-6]]
limits.resolutionParam = [[0.01, 0.05]]
limits.domainRatio = [[0.4, 0.6]]
return limits
@pytest.fixture
def non_polarised_priors():
"""The expected priors object from "standard_layers_project" and "custom_xy_project"."""
priors = Priors()
priors.param = [
["Substrate Roughness", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf],
["Test Thickness", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf],
["Test SLD", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf],
["Test Roughness", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf],
]
priors.backgroundParam = [["Background Param 1", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf]]
priors.qzshift = []
priors.scalefactor = [["Scalefactor 1", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf]]
priors.bulkIn = [["SLD Air", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf]]
priors.bulkOut = [["SLD D2O", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf]]
priors.resolutionParam = [["Resolution Param 1", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf]]
priors.domainRatio = []
priors.priorNames = [
"Substrate Roughness",
"Test Thickness",
"Test SLD",
"Test Roughness",
"Background Param 1",
"Scalefactor 1",
"SLD Air",
"SLD D2O",
"Resolution Param 1",
]
priors.priorValues = [
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
]
return priors
@pytest.fixture
def domains_priors():
"""The expected priors object from "domains_project"."""
priors = Priors()
priors.param = [
["Substrate Roughness", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf],
["Test Thickness", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf],
["Test SLD", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf],
["Test Roughness", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf],
]
priors.backgroundParam = [["Background Param 1", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf]]
priors.qzshift = []
priors.scalefactor = [["Scalefactor 1", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf]]
priors.bulkIn = [["SLD Air", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf]]
priors.bulkOut = [["SLD D2O", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf]]
priors.resolutionParam = [["Resolution Param 1", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf]]
priors.domainRatio = [["Domain Ratio 1", RATapi.utils.enums.Priors.Uniform, 0.0, np.inf]]
priors.priorNames = [
"Substrate Roughness",
"Test Thickness",
"Test SLD",
"Test Roughness",
"Background Param 1",
"Scalefactor 1",
"SLD Air",
"SLD D2O",
"Resolution Param 1",
"Domain Ratio 1",
]
priors.priorValues = [
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
[1, 0.0, np.inf],
]
return priors
@pytest.fixture
def standard_layers_controls():
"""The expected controls object for input to the compiled RAT code given the default inputs and
"standard_layers_project".
"""
controls = Control()
controls.procedure = Procedures.Calculate
controls.parallel = Parallel.Single
controls.calcSldDuringFit = False
controls.resampleMinAngle = 0.9
controls.resampleNPoints = 50.0
controls.display = Display.Iter
controls.xTolerance = 1.0e-6
controls.funcTolerance = 1.0e-6
controls.maxFuncEvals = 10000
controls.maxIterations = 1000
controls.updateFreq = 1
controls.updatePlotFreq = 20
controls.populationSize = 20
controls.fWeight = 0.5
controls.crossoverProbability = 0.8
controls.strategy = 4
controls.targetValue = 1.0
controls.numGenerations = 500
controls.nLive = 150
controls.nMCMC = 0.0
controls.propScale = 0.1
controls.nsTolerance = 0.1
controls.nSamples = 20000
controls.nChains = 10
controls.jumpProbability = 0.5
controls.pUnitGamma = 0.2
controls.boundHandling = BoundHandling.Reflect
controls.adaptPCR = True
controls.checks.fitParam = [1, 0, 0, 0]
controls.checks.fitBackgroundParam = [0]
controls.checks.fitQzshift = []
controls.checks.fitScalefactor = [0]
controls.checks.fitBulkIn = [0]
controls.checks.fitBulkOut = [0]
controls.checks.fitResolutionParam = [0]
controls.checks.fitDomainRatio = []
return controls
@pytest.fixture
def custom_xy_controls():
"""The expected controls object for input to the compiled RAT code given the default inputs and
"custom_xy_project".
"""
controls = Control()
controls.procedure = Procedures.Calculate
controls.parallel = Parallel.Single
controls.calcSldDuringFit = True
controls.resampleMinAngle = 0.9
controls.resampleNPoints = 50.0
controls.display = Display.Iter
controls.xTolerance = 1.0e-6
controls.funcTolerance = 1.0e-6
controls.maxFuncEvals = 10000
controls.maxIterations = 1000
controls.updateFreq = 1
controls.updatePlotFreq = 20
controls.populationSize = 20
controls.fWeight = 0.5
controls.crossoverProbability = 0.8
controls.strategy = 4
controls.targetValue = 1.0
controls.numGenerations = 500
controls.nLive = 150
controls.nMCMC = 0.0
controls.propScale = 0.1
controls.nsTolerance = 0.1
controls.nSamples = 20000
controls.nChains = 10
controls.jumpProbability = 0.5
controls.pUnitGamma = 0.2
controls.boundHandling = BoundHandling.Reflect
controls.adaptPCR = True
controls.checks.fitParam = [1, 0, 0, 0]
controls.checks.fitBackgroundParam = [0]
controls.checks.fitQzshift = []
controls.checks.fitScalefactor = [0]
controls.checks.fitBulkIn = [0]
controls.checks.fitBulkOut = [0]
controls.checks.fitResolutionParam = [0]
controls.checks.fitDomainRatio = []
return controls
@pytest.fixture
def test_checks():
"""The expected checks object from "standard_layers_project", "domains_project" and "custom_xy_project"."""
checks = Checks()
checks.fitParam = [1, 0, 0, 0]
checks.fitBackgroundParam = [0]
checks.fitQzshift = []
checks.fitScalefactor = [0]
checks.fitBulkIn = [0]
checks.fitBulkOut = [0]
checks.fitResolutionParam = [0]
checks.fitDomainRatio = []
return checks
@pytest.mark.parametrize(
["test_project", "test_problem", "test_cells", "test_limits", "test_priors", "test_controls"],
[
(
"standard_layers_project",
"standard_layers_problem",
"standard_layers_cells",
"non_polarised_limits",
"non_polarised_priors",
"standard_layers_controls",
),
(
"custom_xy_project",
"custom_xy_problem",
"custom_xy_cells",
"non_polarised_limits",
"non_polarised_priors",
"custom_xy_controls",
),
(
"domains_project",
"domains_problem",
"domains_cells",
"domains_limits",
"domains_priors",
"standard_layers_controls",
),
],
)
def test_make_input(test_project, test_problem, test_cells, test_limits, test_priors, test_controls, request) -> None:
"""When converting the "project" and "controls", we should obtain the five input objects required for the compiled
RAT code.
"""
test_project = request.getfixturevalue(test_project)
test_problem = request.getfixturevalue(test_problem)
test_cells = request.getfixturevalue(test_cells)
test_limits = request.getfixturevalue(test_limits)
test_priors = request.getfixturevalue(test_priors)
test_controls = request.getfixturevalue(test_controls)
parameter_fields = [
"param",
"backgroundParam",
"scalefactor",
"qzshift",
"bulkIn",
"bulkOut",
"resolutionParam",
"domainRatio",
]
mocked_matlab_future = mock.MagicMock()
mocked_engine = mock.MagicMock()
mocked_matlab_future.result.return_value = mocked_engine
with mock.patch.object(
RATapi.wrappers.MatlabWrapper,
"loader",
mocked_matlab_future,
), mock.patch.object(RATapi.rat_core, "DylibEngine", mock.MagicMock()), mock.patch.object(
RATapi.inputs,
"get_python_handle",
mock.MagicMock(return_value=dummy_function),
), mock.patch.object(
RATapi.wrappers.MatlabWrapper,
"getHandle",
mock.MagicMock(return_value=dummy_function),
), mock.patch.object(RATapi.wrappers.DylibWrapper, "getHandle", mock.MagicMock(return_value=dummy_function)):
problem, cells, limits, priors, controls = make_input(test_project, RATapi.Controls())
problem = pickle.loads(pickle.dumps(problem))
check_problem_equal(problem, test_problem)
cells = pickle.loads(pickle.dumps(cells))
check_cells_equal(cells, test_cells)
limits = pickle.loads(pickle.dumps(limits))
for limit_field in parameter_fields:
assert (getattr(limits, limit_field) == getattr(test_limits, limit_field)).all()
priors = pickle.loads(pickle.dumps(priors))
for prior_field in parameter_fields:
assert getattr(priors, prior_field) == getattr(test_priors, prior_field)
assert priors.priorNames == test_priors.priorNames
assert (priors.priorValues == test_priors.priorValues).all()
controls = pickle.loads(pickle.dumps(controls))
check_controls_equal(controls, test_controls)
@pytest.mark.parametrize(
["test_project", "test_problem"],
[
("standard_layers_project", "standard_layers_problem"),
("custom_xy_project", "custom_xy_problem"),
("domains_project", "domains_problem"),
],
)
def test_make_problem(test_project, test_problem, request) -> None:
"""The problem object should contain the relevant parameters defined in the input project object."""
test_project = request.getfixturevalue(test_project)
test_problem = request.getfixturevalue(test_problem)
problem = make_problem(test_project)
check_problem_equal(problem, test_problem)
@pytest.mark.parametrize(
"test_problem",
[
"standard_layers_problem",
"custom_xy_problem",
"domains_problem",
],
)
def test_check_indices(test_problem, request) -> None:
"""The check_indices routine should not raise errors for a properly defined ProblemDefinition object."""
test_problem = request.getfixturevalue(test_problem)
check_indices(test_problem)
@pytest.mark.parametrize(
["test_problem", "index_list", "bad_value"],
[
("standard_layers_problem", "contrastBulkIns", [0.0]),
("standard_layers_problem", "contrastBulkIns", [2.0]),
("standard_layers_problem", "contrastBulkOuts", [0.0]),
("standard_layers_problem", "contrastBulkOuts", [2.0]),
("standard_layers_problem", "contrastScalefactors", [0.0]),
("standard_layers_problem", "contrastScalefactors", [2.0]),
("standard_layers_problem", "contrastBackgroundParams", [0.0]),
("standard_layers_problem", "contrastBackgroundParams", [2.0]),
("standard_layers_problem", "contrastResolutionParams", [0.0]),
("standard_layers_problem", "contrastResolutionParams", [2.0]),
("custom_xy_problem", "contrastBulkIns", [0.0]),
("custom_xy_problem", "contrastBulkIns", [2.0]),
("custom_xy_problem", "contrastBulkOuts", [0.0]),
("custom_xy_problem", "contrastBulkOuts", [2.0]),
("custom_xy_problem", "contrastScalefactors", [0.0]),
("custom_xy_problem", "contrastScalefactors", [2.0]),
("custom_xy_problem", "contrastBackgroundParams", [0.0]),
("custom_xy_problem", "contrastBackgroundParams", [2.0]),
("custom_xy_problem", "contrastResolutionParams", [0.0]),
("custom_xy_problem", "contrastResolutionParams", [2.0]),
("domains_problem", "contrastBulkIns", [0.0]),
("domains_problem", "contrastBulkIns", [2.0]),
("domains_problem", "contrastBulkOuts", [0.0]),
("domains_problem", "contrastBulkOuts", [2.0]),
("domains_problem", "contrastScalefactors", [0.0]),
("domains_problem", "contrastScalefactors", [2.0]),
("domains_problem", "contrastDomainRatios", [0.0]),
("domains_problem", "contrastDomainRatios", [2.0]),
("domains_problem", "contrastBackgroundParams", [0.0]),
("domains_problem", "contrastBackgroundParams", [2.0]),
("domains_problem", "contrastResolutionParams", [0.0]),
("domains_problem", "contrastResolutionParams", [2.0]),
],
)
def test_check_indices_error(test_problem, index_list, bad_value, request) -> None:
"""The check_indices routine should raise an IndexError if a contrast list contains an index that is out of the
range of the corresponding parameter list in a ProblemDefinition object.
"""
param_list = {
"contrastBulkIns": "bulkIn",
"contrastBulkOuts": "bulkOut",
"contrastScalefactors": "scalefactors",
"contrastDomainRatios": "domainRatio",
"contrastBackgroundParams": "backgroundParams",
"contrastResolutionParams": "resolutionParams",
}
test_problem = request.getfixturevalue(test_problem)
setattr(test_problem, index_list, bad_value)
with pytest.raises(
IndexError,
match=f'The problem field "{index_list}" contains: {bad_value[0]}, which lie '
f'outside of the range of "{param_list[index_list]}"',
):
check_indices(test_problem)
@pytest.mark.parametrize(
["test_project", "test_cells"],
[
("standard_layers_project", "standard_layers_cells"),
("custom_xy_project", "custom_xy_cells"),
("domains_project", "domains_cells"),
],
)
def test_make_cells(test_project, test_cells, request) -> None:
"""The cells object should be populated according to the input project object."""
test_project = request.getfixturevalue(test_project)
test_cells = request.getfixturevalue(test_cells)
mocked_matlab_future = mock.MagicMock()
mocked_engine = mock.MagicMock()
mocked_matlab_future.result.return_value = mocked_engine
with mock.patch.object(
RATapi.wrappers.MatlabWrapper,
"loader",
mocked_matlab_future,
), mock.patch.object(RATapi.rat_core, "DylibEngine", mock.MagicMock()), mock.patch.object(
RATapi.inputs,
"get_python_handle",
mock.MagicMock(return_value=dummy_function),
), mock.patch.object(
RATapi.wrappers.MatlabWrapper,
"getHandle",
mock.MagicMock(return_value=dummy_function),
), mock.patch.object(RATapi.wrappers.DylibWrapper, "getHandle", mock.MagicMock(return_value=dummy_function)):
cells = make_cells(test_project)
check_cells_equal(cells, test_cells)
def test_get_python_handle():
path = pathlib.Path(__file__).parent.resolve()
assert RATapi.inputs.get_python_handle("utils.py", "dummy_function", path).__code__ == dummy_function.__code__
def test_make_controls(standard_layers_controls, test_checks) -> None:
"""The controls object should contain the full set of controls parameters, with the appropriate set defined by the
input controls.
"""
controls = make_controls(RATapi.Controls(), test_checks)
check_controls_equal(controls, standard_layers_controls)
def check_problem_equal(actual_problem, expected_problem) -> None:
"""Compare two instances of the "problem" object for equality."""
scalar_fields = [
"TF",
"modelType",
"geometry",
"useImaginary",
"numberOfContrasts",
"numberOfLayers",
"numberOfDomainContrasts",
]
array_fields = [
"params",
"backgroundParams",
"qzshifts",
"scalefactors",
"bulkIn",
"bulkOut",
"resolutionParams",
"domainRatio",
"contrastBackgroundParams",
"contrastBackgroundActions",
"contrastQzshifts",
"contrastScalefactors",
"contrastBulkIns",
"contrastBulkOuts",
"contrastResolutionParams",
"contrastDomainRatios",
"resample",
"dataPresent",
"oilChiDataPresent",
"fitParams",
"otherParams",
"fitLimits",
"otherLimits",
]
for scalar_field in scalar_fields:
assert getattr(actual_problem, scalar_field) == getattr(expected_problem, scalar_field)
for array_field in array_fields:
assert (getattr(actual_problem, array_field) == getattr(expected_problem, array_field)).all()
# Need to account for "NaN" entries in contrastCustomFiles field
assert (actual_problem.contrastCustomFiles == expected_problem.contrastCustomFiles).all() or [
"NaN" if np.isnan(el) else el for el in actual_problem.contrastCustomFiles
] == ["NaN" if np.isnan(el) else el for el in expected_problem.contrastCustomFiles]
def check_cells_equal(actual_cells, expected_cells) -> None:
"""Compare two instances of the "cells" object for equality."""
assert actual_cells.f1 == expected_cells.f1
# Need to test equality of the numpy arrays separately
for a, b in zip(actual_cells.f2, expected_cells.f2):
assert (a == b).all()
# f6 may contain "NaN" values, so consider separately
assert actual_cells.f6 == expected_cells.f6 or [
"NaN" if np.isnan(el) else el for entry in actual_cells.f6 for el in entry
] == ["NaN" if np.isnan(el) else el for entry in expected_cells.f6 for el in entry]
for index in chain(range(3, 6), range(7, 21)):
field = f"f{index}"
assert getattr(actual_cells, field) == getattr(expected_cells, field)
def check_controls_equal(actual_controls, expected_controls) -> None:
"""Compare two instances of the "controls" object used as input for the compiled RAT code for equality."""
controls_fields = [
"procedure",
"parallel",
"calcSldDuringFit",
"resampleMinAngle",
"resampleNPoints",
"display",
"xTolerance",
"funcTolerance",
"maxFuncEvals",
"maxIterations",
"updateFreq",
"updatePlotFreq",
"populationSize",
"fWeight",
"crossoverProbability",
"strategy",
"targetValue",
"numGenerations",
"nLive",
"nMCMC",
"propScale",
"nsTolerance",
"nSamples",
"nChains",
"jumpProbability",
"pUnitGamma",
"boundHandling",
"adaptPCR",
]
checks_fields = [
"fitParam",
"fitBackgroundParam",
"fitQzshift",
"fitScalefactor",
"fitBulkIn",
"fitBulkOut",
"fitResolutionParam",
"fitDomainRatio",
]
for field in controls_fields:
assert getattr(actual_controls, field) == getattr(expected_controls, field)
for field in checks_fields:
assert (getattr(actual_controls.checks, field) == getattr(expected_controls.checks, field)).all()