def test_product_serialization(valid_product_design_space_data):
"""Ensure that a serialized ProductDesignSpace looks sane."""
design_space = ProductDesignSpace.build(valid_product_design_space_data)
serialized = design_space.dump()
serialized['id'] = valid_product_design_space_data['id']
assert serialized == valid_serialization_output(
valid_product_design_space_data)
def test_simple_product_deserialization(valid_product_data):
"""Ensure that a deserialized ProductDesignSpace looks sane."""
design_space: ProductDesignSpace = ProductDesignSpace.build(
valid_product_data)
assert design_space.name == 'my design space'
assert design_space.description == 'does some things'
assert type(design_space.dimensions[0]) == ContinuousDimension
assert design_space.dimensions[0].lower_bound == 6.0
assert type(design_space.dimensions[1]) == EnumeratedDimension
assert design_space.dimensions[1].values == ['red']
def product_design_space() -> ProductDesignSpace:
"""Build a ProductDesignSpace for testing."""
alpha = RealDescriptor('alpha', 0, 100)
beta = RealDescriptor('beta', 0, 100)
gamma = CategoricalDescriptor('gamma', ['a', 'b', 'c'])
dimensions = [
ContinuousDimension(alpha, 0, 10),
ContinuousDimension(beta, 0, 10),
EnumeratedDimension(gamma, ['a', 'c'])
]
return ProductDesignSpace('my design space', 'does some things',
dimensions)
def test_old_product_serialization(old_valid_product_design_space_data):
"""Ensure that the old version of the product design space can be (de)serialized.
The previous version had no `subspaces` field and had type `Univariate`.
Some on-platform assets are saved this way, and should be converted seamlessly
into ProductDesignSpaces.
"""
design_space = ProductDesignSpace.build(
old_valid_product_design_space_data)
assert design_space.subspaces == []
assert design_space.typ == 'ProductDesignSpace'
serialized = design_space.dump()
serialized['id'] = old_valid_product_design_space_data['id']
serialized['config']['type'] = 'Univariate'
del serialized['config']['subspaces']
assert serialized == valid_serialization_output(
old_valid_product_design_space_data)
def test_product_serialization(valid_product_design_space_data):
"""Ensure that a serialized ProductDesignSpace looks sane."""
original_data = deepcopy(valid_product_design_space_data)
design_space = ProductDesignSpace.build(valid_product_design_space_data)
serialized = design_space.dump()
serialized['id'] = valid_product_design_space_data['id']
assert serialized['config']['subspaces'][0] == original_data['config'][
'subspaces'][0]['id']
assert serialized['config']['subspaces'][1] == original_data['config'][
'subspaces'][1]['instance']
# Replace one of the subspaces with its uid, and check that the serialized result is the same.
design_space.subspaces[0] = design_space.subspaces[0].uid
serialized_with_uid = design_space.dump()
serialized_with_uid['id'] = valid_product_design_space_data['id']
assert serialized_with_uid == serialized
import pytest
from citrine.informatics.constraints import ScalarRangeConstraint, CategoricalConstraint
from citrine.informatics.design_spaces import ProductDesignSpace, EnumeratedDesignSpace
from citrine.informatics.objectives import ScalarMaxObjective, ScalarMinObjective
from citrine.informatics.processors import GridProcessor, EnumeratedProcessor
from citrine.informatics.scores import LIScore, EIScore
from citrine.informatics.reports import ModelSummary, FeatureImportanceReport
informatics_string_data = [
(ScalarRangeConstraint('z'), "<ScalarRangeConstraint 'z'>"),
(CategoricalConstraint('x', []), "<CategoricalConstraint 'x'>"),
(ProductDesignSpace('my design space', 'does some things',
[]), "<ProductDesignSpace 'my design space'>"),
(EnumeratedDesignSpace('enumerated', 'desc', [],
[]), "<EnumeratedDesignSpace 'enumerated'>"),
(ScalarMaxObjective('z', 1.0, 10.0), "<ScalarMaxObjective 'z'>"),
(ScalarMinObjective('z', 1.0, 10.0), "<ScalarMinObjective 'z'>"),
(GridProcessor('my thing', 'does a thing',
dict(x=1)), "<GridProcessor 'my thing'>"),
(EnumeratedProcessor('my enumerated thing', 'enumerates',
10), "<EnumeratedProcessor 'my enumerated thing'>"),
(LIScore("LI(z)", "score for z", [], []), "<LIScore 'LI(z)'>"),
(EIScore("EI(x)", "score for x", [], [], []), "<EIScore 'EI(x)'>"),
(FeatureImportanceReport("reflectivity",
{}), "<FeatureImportanceReport 'reflectivity'>"),
(ModelSummary("my model", "ML Model", [], [], {}, [],
"predictor name"), "<ModelSummary 'my model'>"),
]
informatics_string_data = [
(IngredientCountConstraint(
formulation_descriptor=FormulationDescriptor('x'), min=0,
max=1), "<IngredientCountConstraint 'x'>"),
(IngredientFractionConstraint(
formulation_descriptor=FormulationDescriptor('x'),
ingredient='y',
min=0,
max=1), "<IngredientFractionConstraint 'x'::'y'>"),
(LabelFractionConstraint(formulation_descriptor=FormulationDescriptor('x'),
label='y',
min=0,
max=1), "<LabelFractionConstraint 'x'::'y'>"),
(ScalarRangeConstraint('z'), "<ScalarRangeConstraint 'z'>"),
(CategoricalConstraint('x', []), "<CategoricalConstraint 'x'>"),
(ProductDesignSpace(name='my design space',
description='does some things'),
"<ProductDesignSpace 'my design space'>"),
(EnumeratedDesignSpace('enumerated', 'desc', [],
[]), "<EnumeratedDesignSpace 'enumerated'>"),
(FormulationDesignSpace(name='formulation',
description='desc',
formulation_descriptor=FormulationDescriptor('x'),
ingredients={'y'},
constraints=set(),
labels={}),
"<FormulationDesignSpace 'formulation'>"),
(ScalarMaxObjective('z'), "<ScalarMaxObjective 'z'>"),
(ScalarMinObjective('z'), "<ScalarMinObjective 'z'>"),
(GridProcessor('my thing', 'does a thing',
dict(x=1)), "<GridProcessor 'my thing'>"),
(EnumeratedProcessor('my enumerated thing', 'enumerates',