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814 lines (723 loc) · 28.2 KB
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"""Test the inputs module."""
import pathlib
import pickle
import tempfile
from unittest.mock import patch
import numpy as np
import pytest
import ratapi
import ratapi.wrappers
from ratapi.inputs import FileHandles, check_indices, make_controls, make_input, make_problem
from ratapi.rat_core import Checks, Control, NameStore, ProblemDefinition
from ratapi.utils.enums import (
BackgroundActions,
BoundHandling,
Calculations,
Display,
Geometries,
LayerModels,
Parallel,
Procedures,
)
from tests.utils import dummy_function
@pytest.fixture
def standard_layers_project():
"""Add parameters to the default project for a normal 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 normal 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 test_names():
"""The expected NameStore object from "standard_layers_project", "domains_project" and "custom_xy_project"."""
names = NameStore()
names.params = ["Substrate Roughness", "Test Thickness", "Test SLD", "Test Roughness"]
names.backgroundParams = ["Background Param 1"]
names.scalefactors = ["Scalefactor 1"]
names.bulkIns = ["SLD Air"]
names.bulkOuts = ["SLD D2O"]
names.resolutionParams = ["Resolution Param 1"]
names.domainRatios = []
names.contrasts = ["Test Contrast"]
return names
@pytest.fixture
def test_checks():
"""The expected checks object from "standard_layers_project", "domains_project" and "custom_xy_project"."""
checks = Checks()
checks.params = np.array([1, 0, 0, 0])
checks.backgroundParams = np.array([0])
checks.scalefactors = np.array([0])
checks.bulkIns = np.array([0])
checks.bulkOuts = np.array([0])
checks.resolutionParams = np.array([0])
checks.domainRatios = np.array([])
return checks
@pytest.fixture
def standard_layers_problem(test_names, test_checks):
"""The expected problem object from "standard_layers_project"."""
problem = ProblemDefinition()
problem.TF = Calculations.Normal
problem.modelType = LayerModels.StandardLayers
problem.geometry = Geometries.AirSubstrate
problem.useImaginary = False
problem.params = [3.0, 0.0, 0.0, 0.0]
problem.bulkIns = [0.0]
problem.bulkOuts = [6.35e-06]
problem.scalefactors = [0.23]
problem.domainRatios = []
problem.backgroundParams = [1e-06]
problem.resolutionParams = [0.03]
problem.contrastBulkIns = [1]
problem.contrastBulkOuts = [1]
problem.contrastScalefactors = [1]
problem.contrastBackgroundParams = [[1]]
problem.contrastBackgroundActions = [BackgroundActions.Add]
problem.contrastBackgroundTypes = ["constant"]
problem.contrastResolutionParams = [[1]]
problem.contrastResolutionTypes = ["constant"]
problem.contrastCustomFiles = [float("NaN")]
problem.contrastDomainRatios = [0]
problem.resample = [False]
problem.dataPresent = [1]
problem.data = [np.array([[1.0, 1.0, 1.0, 0.0, 0.0, 0.0]])]
problem.dataLimits = [[1.0, 1.0]]
problem.simulationLimits = [[1.0, 1.0]]
problem.numberOfContrasts = 1
problem.numberOfLayers = 1
problem.repeatLayers = [1]
problem.layersDetails = [[2, 3, 4, float("NaN"), 1]]
problem.contrastLayers = [[1]]
problem.numberOfDomainContrasts = 0
problem.domainContrastLayers = []
problem.fitParams = [3.0]
problem.fitLimits = [[1.0, 5.0]]
problem.priorNames = [
"Substrate Roughness",
"Test Thickness",
"Test SLD",
"Test Roughness",
"Background Param 1",
"Scalefactor 1",
"SLD Air",
"SLD D2O",
"Resolution Param 1",
]
problem.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],
]
problem.customFiles = FileHandles([])
problem.names = test_names
problem.checks = test_checks
return problem
@pytest.fixture
def domains_problem(test_names, test_checks):
"""The expected problem object from "domains_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.bulkIns = [0.0]
problem.bulkOuts = [6.35e-06]
problem.scalefactors = [0.23]
problem.domainRatios = [0.5]
problem.backgroundParams = [1e-06]
problem.resolutionParams = [0.03]
problem.contrastBulkIns = [1]
problem.contrastBulkOuts = [1]
problem.contrastScalefactors = [1]
problem.contrastBackgroundParams = [[1]]
problem.contrastBackgroundActions = [BackgroundActions.Add]
problem.contrastBackgroundTypes = ["constant"]
problem.contrastResolutionParams = [[1]]
problem.contrastResolutionTypes = ["constant"]
problem.contrastCustomFiles = [float("NaN")]
problem.contrastDomainRatios = [1]
problem.resample = [False]
problem.dataPresent = [1]
problem.data = [np.array([[1.0, 1.0, 1.0, 0.0, 0.0, 0.0]])]
problem.dataLimits = [[1.0, 1.0]]
problem.simulationLimits = [[1.0, 1.0]]
problem.numberOfContrasts = 1
problem.numberOfLayers = 1
problem.repeatLayers = [1]
problem.layersDetails = [[2, 3, 4, float("NaN"), 1]]
problem.contrastLayers = [[2, 1]]
problem.numberOfDomainContrasts = 2
problem.domainContrastLayers = [[1], [1]]
problem.fitParams = [3.0]
problem.fitLimits = [[1.0, 5.0]]
problem.priorNames = [
"Substrate Roughness",
"Test Thickness",
"Test SLD",
"Test Roughness",
"Background Param 1",
"Scalefactor 1",
"SLD Air",
"SLD D2O",
"Resolution Param 1",
"Domain Ratio 1",
]
problem.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],
]
problem.customFiles = FileHandles([])
problem.names = test_names
problem.names.domainRatios = ["Domain Ratio 1"]
problem.checks = test_checks
return problem
@pytest.fixture
def custom_xy_problem(test_names, test_checks):
"""The expected problem object from "custom_xy_project"."""
problem = ProblemDefinition()
problem.TF = Calculations.Normal
problem.modelType = LayerModels.CustomXY
problem.geometry = Geometries.AirSubstrate
problem.useImaginary = False
problem.params = [3.0, 0.0, 0.0, 0.0]
problem.bulkIns = [0.0]
problem.bulkOuts = [6.35e-06]
problem.scalefactors = [0.23]
problem.domainRatios = []
problem.backgroundParams = [1e-06]
problem.resolutionParams = [0.03]
problem.contrastBulkIns = [1]
problem.contrastBulkOuts = [1]
problem.contrastScalefactors = [1]
problem.contrastBackgroundParams = [[1]]
problem.contrastBackgroundActions = [BackgroundActions.Add]
problem.contrastBackgroundTypes = ["constant"]
problem.contrastResolutionParams = [[1]]
problem.contrastResolutionTypes = ["constant"]
problem.contrastCustomFiles = [1]
problem.contrastDomainRatios = [0]
problem.resample = [True]
problem.dataPresent = [0]
problem.data = [np.empty([0, 6])]
problem.dataLimits = [[0.0, 0.0]]
problem.simulationLimits = [[0.005, 0.7]]
problem.repeatLayers = [1]
problem.layersDetails = []
problem.contrastLayers = [[]]
problem.numberOfContrasts = 1
problem.numberOfLayers = 0
problem.numberOfDomainContrasts = 0
problem.domainContrastLayers = []
problem.fitParams = [3.0]
problem.fitLimits = [[1.0, 5.0]]
problem.priorNames = [
"Substrate Roughness",
"Test Thickness",
"Test SLD",
"Test Roughness",
"Background Param 1",
"Scalefactor 1",
"SLD Air",
"SLD D2O",
"Resolution Param 1",
]
problem.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],
]
problem.customFiles = FileHandles(
[ratapi.models.CustomFile(name="Test Custom File", filename="cpp_test.dll", language="cpp")]
)
problem.names = test_names
problem.checks = test_checks
return problem
@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.numSimulationPoints = 500
controls.resampleMinAngle = 0.9
controls.resampleNPoints = 50
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
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.numSimulationPoints = 500
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
return controls
@pytest.mark.parametrize(
["test_project", "test_problem", "test_controls"],
[
(
"standard_layers_project",
"standard_layers_problem",
"standard_layers_controls",
),
(
"custom_xy_project",
"custom_xy_problem",
"custom_xy_controls",
),
(
"domains_project",
"domains_problem",
"standard_layers_controls",
),
],
)
def test_make_input(test_project, test_problem, test_controls, request) -> None:
"""When converting the "project" and "controls", we should obtain the two input objects required for the compiled
RAT code.
"""
test_project = request.getfixturevalue(test_project)
test_problem = request.getfixturevalue(test_problem)
test_controls = request.getfixturevalue(test_controls)
problem, controls = make_input(test_project, ratapi.Controls())
problem = pickle.loads(pickle.dumps(problem))
check_problem_equal(problem, test_problem)
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"])
class TestCheckIndices:
"""Tests for check_indices over a set of three test problems."""
def test_check_indices(self, 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(
"index_list",
[
"contrastBulkIns",
"contrastBulkOuts",
"contrastScalefactors",
"contrastDomainRatios",
],
)
@pytest.mark.parametrize("bad_value", ([0.0], [2.0]))
def test_check_indices_error(self, 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": "bulkIns",
"contrastBulkOuts": "bulkOuts",
"contrastScalefactors": "scalefactors",
"contrastDomainRatios": "domainRatios",
}
if (test_problem != "domains_problem") and (index_list == "contrastDomainRatios"):
# we expect this to not raise an error for non-domains problems as domainRatios is empty
pytest.xfail()
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 lies '
f'outside of the range of "{param_list[index_list]}"',
):
check_indices(test_problem)
@pytest.mark.parametrize("background_type", ["constant", "data", "function"])
@pytest.mark.parametrize("bad_value", ([[0.0]], [[2.0]]))
def test_background_params_source_indices(self, test_problem, background_type, bad_value, request):
"""check_indices should raise an IndexError for bad sources in the nested list contrastBackgroundParams."""
test_problem = request.getfixturevalue(test_problem)
test_problem.contrastBackgroundParams = bad_value
test_problem.contrastBackgroundTypes = [background_type]
source_param_lists = {
"constant": "backgroundParams",
"data": "data",
"function": "customFiles",
}
with pytest.raises(
IndexError,
match=f'Entry 0 of contrastBackgroundParams has type "{background_type}" '
f"and source index {bad_value[0][0]}, "
f'which is outside the range of "{source_param_lists[background_type]}".',
):
check_indices(test_problem)
@pytest.mark.parametrize(
"bad_value",
(
[[1.0, 0.0]],
[[1.0, 2.0]],
[[1.0, 1.0, 2.0]],
[[1.0], [1.0, 0.0]],
),
)
def test_background_params_value_indices(self, test_problem, bad_value, request):
"""check_indices should raise an IndexError for bad values in the nested list contrastBackgroundParams."""
test_problem = request.getfixturevalue(test_problem)
test_problem.contrastBackgroundParams = bad_value
if len(bad_value) > 1:
test_problem.contrastBackgroundTypes.append("constant")
with pytest.raises(
IndexError,
match=f"Entry {len(bad_value) - 1} of contrastBackgroundParams contains: {bad_value[-1][-1]}"
f', which lies outside of the range of "backgroundParams"',
):
check_indices(test_problem)
@pytest.mark.parametrize("test_project", ["standard_layers_project", "custom_xy_project", "domains_project"])
@pytest.mark.parametrize("field", ["data", "background", "bulk_in", "bulk_out", "scalefactor", "resolution"])
def test_undefined_contrast_fields(test_project, field, request):
"""If a field in a contrast is empty, we should raise an error."""
test_project = request.getfixturevalue(test_project)
setattr(test_project.contrasts[0], field, "")
with pytest.raises(
ValueError,
match=f'In the input project, the "{field}" field of contrast '
f'"{test_project.contrasts[0].name}" does not have a value defined. '
f"A value must be supplied before running the project.",
):
make_problem(test_project)
@pytest.mark.parametrize("test_project", ["standard_layers_project", "custom_xy_project", "domains_project"])
def test_undefined_background(test_project, request):
"""If the source field of a background defined in a contrast is empty, we should raise an error."""
test_project = request.getfixturevalue(test_project)
background = test_project.backgrounds[test_project.contrasts[0].background]
background.source = ""
with pytest.raises(
ValueError,
match=f"All backgrounds must have a source defined. For a {background.type} type "
f"background, the source must be defined in "
f'"{ratapi.project.values_defined_in[f"backgrounds.{background.type}.source"]}"',
):
make_problem(test_project)
@pytest.mark.parametrize("test_project", ["standard_layers_project", "custom_xy_project", "domains_project"])
def test_undefined_resolution(test_project, request):
"""If the source field of a resolution defined in a contrast is empty, we should raise an error."""
test_project = request.getfixturevalue(test_project)
resolution = test_project.resolutions[test_project.contrasts[0].resolution]
resolution.source = ""
with pytest.raises(
ValueError,
match=f"Constant resolutions must have a source defined. The source must be defined in "
f'"{ratapi.project.values_defined_in[f"resolutions.{resolution.type}.source"]}"',
):
make_problem(test_project)
@pytest.mark.parametrize("test_project", ["standard_layers_project", "domains_project"])
@pytest.mark.parametrize("field", ["thickness", "SLD", "roughness"])
def test_undefined_layers(test_project, field, request):
"""If the thickness, SLD, or roughness fields of a layer defined in the project are empty, we should raise an
error."""
test_project = request.getfixturevalue(test_project)
setattr(test_project.layers[0], field, "")
with pytest.raises(
ValueError,
match=f'In the input project, the "{field}" field of layer {test_project.layers[0].name} '
f"does not have a value defined. A value must be supplied before running the project.",
):
make_problem(test_project)
def test_append_data_background():
"""Test that background data is correctly added to contrast data."""
data = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
background = np.array([[1, 10, 11], [4, 12, 13], [7, 14, 15]])
result = ratapi.inputs.append_data_background(data, background)
np.testing.assert_allclose(result, np.array([[1, 2, 3, 0, 10, 11], [4, 5, 6, 0, 12, 13], [7, 8, 9, 0, 14, 15]]))
def test_append_data_background_res():
"""Test that background data is correctly added to contrast data when a resolution is in the data."""
data = np.array([[1, 2, 3, 4], [4, 5, 6, 6], [7, 8, 9, 72]])
background = np.array([[1, 10, 11], [4, 12, 13], [7, 14, 15]])
result = ratapi.inputs.append_data_background(data, background)
np.testing.assert_allclose(result, np.array([[1, 2, 3, 4, 10, 11], [4, 5, 6, 6, 12, 13], [7, 8, 9, 72, 14, 15]]))
def test_append_data_background_error():
"""Test that append_data_background raises an error if the q-values are not equal."""
data = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
background = np.array([[56, 10, 11], [41, 12, 13], [7, 14, 15]])
with pytest.raises(ValueError, match=("The q-values of the data and background must be equal.")):
ratapi.inputs.append_data_background(data, background)
def test_get_python_handle():
path = pathlib.Path(__file__).parent
assert ratapi.inputs.get_python_handle("utils.py", "dummy_function", path).__code__ == dummy_function.__code__
def test_make_controls(standard_layers_controls) -> 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())
check_controls_equal(controls, standard_layers_controls)
@patch("ratapi.wrappers.MatlabWrapper")
def test_file_handles(wrapper):
handle = FileHandles([ratapi.models.CustomFile(name="Test Custom File", filename="cpp_test.dll", language="cpp")])
with pytest.raises(FileNotFoundError, match="The custom file \\(Test Custom File\\) does not have a valid path."):
handle.get_handle(0)
with tempfile.NamedTemporaryFile("w", suffix=".dll") as f:
tmp_file = pathlib.Path(f.name)
handle.files[0]["path"] = tmp_file.parent
handle.files[0]["filename"] = tmp_file.name
handle.files[0]["function_name"] = ""
# No function name should throw exception
with pytest.raises(
ValueError, match="The custom file \\(Test Custom File\\) does not have a valid function name."
):
handle.get_handle(0)
# Matlab does not need function name
handle.files[0]["language"] = "matlab"
handle.get_handle(0)
wrapper.assert_called()
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",
"priorNames",
]
array_fields = [
"params",
"backgroundParams",
"scalefactors",
"bulkIns",
"bulkOuts",
"resolutionParams",
"domainRatios",
"contrastBackgroundParams",
"contrastBackgroundActions",
"contrastScalefactors",
"contrastBulkIns",
"contrastBulkOuts",
"contrastResolutionParams",
"contrastDomainRatios",
"resample",
"dataPresent",
"dataLimits",
"simulationLimits",
"repeatLayers",
"contrastLayers",
"domainContrastLayers",
"fitParams",
"fitLimits",
"priorValues",
]
checks_fields = [
"params",
"backgroundParams",
"scalefactors",
"bulkIns",
"bulkOuts",
"resolutionParams",
"domainRatios",
]
names_fields = [*checks_fields, "contrasts"]
for scalar_field in scalar_fields:
assert getattr(actual_problem, scalar_field) == getattr(expected_problem, scalar_field)
for array_field in array_fields:
assert np.all(getattr(actual_problem, array_field) == getattr(expected_problem, array_field))
for field in names_fields:
assert getattr(actual_problem.names, field) == getattr(expected_problem.names, field)
for field in checks_fields:
assert (getattr(actual_problem.checks, field) == getattr(expected_problem.checks, field)).all()
# Data field is a numpy array
assert [
actual_data == expected_data
for (actual_data, expected_data) in zip(actual_problem.data, expected_problem.data, strict=False)
]
# Need to account for "NaN" entries in layersDetails and contrastCustomFiles field
for actual_layer, expected_layer in zip(actual_problem.layersDetails, expected_problem.layersDetails, strict=False):
assert (actual_layer == expected_layer) or ["NaN" if np.isnan(el) else el for el in actual_layer] == [
"NaN" if np.isnan(el) else el for el in expected_layer
]
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_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",
"numSimulationPoints",
"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",
]
for field in controls_fields:
assert getattr(actual_controls, field) == getattr(expected_controls, field)