def test_dict_serialization():
"""Test that a dictionary can be serialized and then deserialized as a taurus object."""
process = ProcessRun("A process")
mat = MaterialRun("A material", process=process)
meas = MeasurementRun("A measurement", material=mat)
copy = loads(dumps(meas.as_dict()))
assert copy == meas
def test_substitution_without_id():
"""Test that trying to substitute links if uids haven't been assigned throws an error."""
mat = MaterialRun("A material with no id")
meas = MeasurementRun("A measurement with no id", material=mat)
with pytest.raises(ValueError):
substitute_links(
meas
), "subbed = substitute_links should fail if objects don't have uids"
with pytest.raises(ValueError):
substitute_links([meas, mat]), \
"subbed = substitute_links should fail if objects don't have uids"
with pytest.raises(ValueError):
substitute_links(meas.as_dict()), \
"subbed = substitute_links should fail if objects don't have uids"
# Create a dictionary in which either the key or value is missing a uid
meas.add_uid('id', str(uuid4()))
with pytest.raises(ValueError):
substitute_links({mat: meas}), \
"subbed = substitute_links should fail if objects don't have uids"
with pytest.raises(ValueError):
substitute_links({meas: mat}), \
"subbed = substitute_links should fail if objects don't have uids"
def test_invalid_assignment():
"""Invalid assignments to `material` or `spec` throw a TypeError."""
with pytest.raises(TypeError):
MeasurementRun("name",
spec=Condition("value of pi",
value=NominalReal(3.14159, '')))
with pytest.raises(TypeError):
MeasurementRun("name", material=FileLink("filename", "url"))
def test_source():
"""Test that source can be set, serialized, and deserialized."""
source = PerformedSource(performed_by="Marie Curie",
performed_date="1898-07-01")
measurement = MeasurementRun(name="Polonium", source=source)
assert loads(dumps(measurement)).source.performed_by == "Marie Curie"
with pytest.raises(TypeError):
MeasurementRun(name="Polonium", source="Marie Curie on 1898-07-01")
def test_template_access():
"""A measurement run's template should be equal to its spec's template."""
template = MeasurementTemplate("measurement template",
uids={'id': str(uuid4())})
spec = MeasurementSpec("A spec",
uids={'id': str(uuid4())},
template=template)
meas = MeasurementRun("A run", uids={'id': str(uuid4())}, spec=spec)
assert meas.template == template
meas.spec = LinkByUID.from_entity(spec)
assert meas.template is None
def test_thin_dumps():
"""Test that thin_dumps turns pointers into links and doesn't work on non-BaseEntity."""
mat = MaterialRun("The actual material")
meas_spec = MeasurementSpec("measurement", uids={'my_scope': '324324'})
meas = MeasurementRun("The measurement", spec=meas_spec, material=mat)
thin_copy = MeasurementRun.build(json.loads(thin_dumps(meas)))
assert isinstance(thin_copy, MeasurementRun)
assert isinstance(thin_copy.material, LinkByUID)
assert isinstance(thin_copy.spec, LinkByUID)
assert thin_copy.spec.id == meas_spec.uids['my_scope']
with pytest.raises(TypeError):
thin_dumps(LinkByUID('scope', 'id'))
def test_material_soft_link():
"""Test that a measurement run can link to a material run, and that it survives serde."""
dye = MaterialRun("rhodamine",
file_links=FileLink(filename='a.csv', url='/a/path'))
assert dye.measurements == [], "default value of .measurements should be an empty list"
# The .measurements member should not be settable
with pytest.raises(AttributeError):
dye.measurements = [MeasurementRun()]
absorbance = MeasurementRun(name="Absorbance",
uids={'id': str(uuid4())},
properties=[
Property(name='Abs at 500 nm',
value=NominalReal(0.1, ''))
])
assert absorbance.material is None, "Measurements should have None as the material by default"
absorbance.material = dye
assert absorbance.material == dye, "Material not set correctly for measurement"
assert dye.measurements == [
absorbance
], "Soft-link from material to measurement not created"
fluorescence = MeasurementRun(name="Fluorescence",
uids={'id': str(uuid4())},
properties=[
Property(name='PL counts at 550 nm',
value=NominalReal(30000, ''))
],
material=dye)
assert fluorescence.material == dye, "Material not set correctly for measurement"
assert dye.measurements == [absorbance, fluorescence], \
"Soft-link from material to measurements not created"
assert loads(dumps(absorbance)) == absorbance, \
"Measurement should remain unchanged when serialized"
assert loads(dumps(fluorescence)) == fluorescence, \
"Measurement should remain unchanged when serialized"
# Serializing the material breaks the material-->measurement link.
assert loads(dumps(dye)).measurements == [], \
"Measurement information should be removed when material is serialized"
assert 'measurements' in repr(dye)
assert 'material' in repr(fluorescence)
assert 'material' in repr(absorbance)
substitute_links(dye.measurements)
assert 'measurements' in repr(dye)
def test_native_id_substitution():
"""Test that the native id gets serialized, when specified."""
native_id = 'id1'
# Create measurement and material with two ids
mat = MaterialRun("A material",
uids={
native_id: str(uuid4()),
"an_id": str(uuid4()),
"another_id": str(uuid4())
})
meas = MeasurementRun("A measurement",
material=mat,
uids={
"some_id": str(uuid4()),
native_id: str(uuid4()),
"an_id": str(uuid4())
})
# Turn the material pointer into a LinkByUID using native_id
subbed = substitute_links(meas, native_uid=native_id)
assert subbed.material == LinkByUID.from_entity(mat, name=native_id)
# Put the measurement into a list and convert that into a LinkByUID using native_id
measurements_list = [meas]
subbed = substitute_links(measurements_list, native_uid=native_id)
assert subbed == [LinkByUID.from_entity(meas, name=native_id)]
def make_flexural_test_measurement(my_id, deflection, extra_tags=frozenset()):
"""
Compute the stree, strain, and modulus.
According to https://en.wikipedia.org/wiki/Three-point_flexural_test
"""
stress = 3 * applied_force * span / (2 * thickness * thickness * width)
strain = 6 * deflection * thickness / (span * span)
modulus = stress / strain
measurement = MeasurementRun(
uids={"my_id": my_id},
tags=["3_pt_bend", "mechanical", "flex"] + list(extra_tags),
properties=[
Property(name="flexural stress",
value=NormalReal(stress, std=(0.01 * stress),
units="MPa"),
origin=Origin.MEASURED),
Property(name="flexural strain",
value=NormalReal(strain, std=(0.01 * strain), units=""),
origin=Origin.MEASURED),
Property(name="flexural modulus",
value=NormalReal(modulus,
std=(0.01 * modulus),
units="MPa"),
origin=Origin.MEASURED),
Property(name="deflection",
value=NominalReal(deflection, units="mm"),
origin=Origin.MEASURED)
])
return measurement
def ingest_table(material_run, table):
"""Ingest a material run into an existing table."""
for _, row in table.iterrows():
exp = MeasurementRun()
for prop_name in known_properties:
if prop_name in row:
exp.properties.append(
Property(name=prop_name,
value=NominalReal(row[prop_name], '')))
for cond_name in known_conditions:
if cond_name in row:
exp.conditions.append(
Condition(name=cond_name,
value=NominalReal(row[cond_name], '')))
exp.material = material_run
return material_run
def test_measurement_reassignment():
"""Check that a measurement run can be re-assigned to a new material run."""
sample1 = MaterialRun("Sample 1")
sample2 = MaterialRun("Sample 2")
mass = MeasurementRun("Mass of sample", material=sample1)
volume = MeasurementRun("Volume of sample", material=sample1)
assert mass.material == sample1
assert set(sample1.measurements) == {mass, volume}
assert sample2.measurements == []
mass.material = sample2
assert mass.material == sample2
assert sample1.measurements == [volume]
assert sample2.measurements == [mass]
mass.material = None
assert mass.material is None
assert sample2.measurements == []
def test_thin_dumps():
"""Test that thin_dumps turns pointers into links."""
mat = MaterialRun("The actual material")
meas_spec = MeasurementSpec("measurement", uids={'my_scope': '324324'})
meas = MeasurementRun("The measurement", spec=meas_spec, material=mat)
thin_copy = MeasurementRun.build(json.loads(TaurusJson().thin_dumps(meas)))
assert isinstance(thin_copy, MeasurementRun)
assert isinstance(thin_copy.material, LinkByUID)
assert isinstance(thin_copy.spec, LinkByUID)
assert thin_copy.spec.id == meas_spec.uids['my_scope']
# Check that LinkByUID objects are correctly converted their JSON equivalent
expected_json = '{"id": "my_id", "scope": "scope", "type": "link_by_uid"}'
assert TaurusJson().thin_dumps(LinkByUID('scope', 'my_id')) == expected_json
# Check that objects lacking .uid attributes will raise an exception when dumped
with pytest.raises(TypeError):
TaurusJson().thin_dumps({{'key': 'value'}})
def test_deserialize():
"""Round-trip serde should leave the object unchanged."""
condition = Condition(name="A condition", value=NominalReal(7, ''))
parameter = Parameter(name="A parameter", value=NormalReal(mean=17, std=1, units=''))
measurement = MeasurementRun(tags="A tag on a measurement", conditions=condition,
parameters=parameter)
copy_meas = copy(measurement)
assert(copy_meas.conditions[0].value == measurement.conditions[0].value)
assert(copy_meas.parameters[0].value == measurement.parameters[0].value)
assert(copy_meas.uids["auto"] == measurement.uids["auto"])
def test_attribute_serde():
"""An attribute with a link to an attribute template should be copy-able."""
prop_tmpl = PropertyTemplate(name='prop_tmpl',
bounds=RealBounds(0, 2, 'm')
)
prop = Property(name='prop',
template=prop_tmpl,
value=NominalReal(1, 'm')
)
meas_spec = MeasurementSpec("a spec")
meas = MeasurementRun("a measurement", spec=meas_spec, properties=[prop])
assert loads(dumps(prop)) == prop
assert loads(dumps(meas)) == meas
assert isinstance(prop.template, PropertyTemplate)
def test_measurement_spec():
"""Test the measurement spec/run connection survives ser/de."""
condition = Condition(name="Temp condition",
value=NominalReal(nominal=298, units='kelvin'))
parameter = Parameter(name="Important parameter")
spec = MeasurementSpec(name="Precise way to do a measurement",
parameters=parameter,
conditions=condition)
# Create a measurement run from this measurement spec
measurement = MeasurementRun(conditions=condition, spec=spec)
copy = loads(dumps(measurement))
assert dumps(copy.spec) == dumps(measurement.spec), \
"Measurement spec should be preserved if measurement run is serialized"
def test_recursive_foreach():
"""Test that recursive foreach will actually walk through a material history."""
mat_run = MaterialRun("foo")
process_run = ProcessRun("bar")
IngredientRun(process=process_run, material=mat_run)
output = MaterialRun(process=process_run)
# property templates are trickier than templates because they are referenced in attributes
template = PropertyTemplate("prop", bounds=RealBounds(0, 1, ""))
prop = Property("prop", value=NominalReal(1.0, ""), template=template)
MeasurementRun("check", material=output, properties=prop)
types = []
recursive_foreach(output, lambda x: types.append(x.typ))
expected = [
"ingredient_run", "material_run", "material_run", "process_run",
"measurement_run", "property_template"
]
assert sorted(types) == sorted(expected)
def test_serialize():
"""Serializing a nested object should be identical to individually serializing each piece."""
condition = Condition(name="A condition", value=NominalReal(7, ''))
parameter = Parameter(name="A parameter", value=NormalReal(mean=17, std=1, units=''))
input_material = MaterialRun(tags="input")
process = ProcessRun(tags="A tag on a process run")
ingredient = IngredientRun(material=input_material, process=process)
material = MaterialRun(tags=["A tag on a material"], process=process)
measurement = MeasurementRun(tags="A tag on a measurement", conditions=condition,
parameters=parameter, material=material)
# serialize the root of the tree
native_object = json.loads(dumps(measurement))
# ingredients don't get serialized on the process
assert(len(native_object[0]) == 3)
assert(native_object[1]["type"] == LinkByUID.typ)
# serialize all of the nodes
native_batch = json.loads(dumps([material, process, measurement, ingredient]))
assert(len(native_batch[0]) == 5)
assert(len(native_batch[1]) == 4)
assert(all(x["type"] == LinkByUID.typ for x in native_batch[1]))
def make_data_island(density, bulk_modulus, firing_temperature, binders, powders, tag=None):
"""Helper function to create a relatively involved data island."""
binder_specs = keymap(lambda x: MaterialSpec(name=x), binders)
powder_specs = keymap(lambda x: MaterialSpec(name=x), powders)
binder_runs = keymap(lambda x: MaterialRun(spec=x), binder_specs)
powder_runs = keymap(lambda x: MaterialRun(spec=x), powder_specs)
all_input_materials = keymap(lambda x: x.spec.name, merge(binder_runs, powder_runs))
mixing_composition = Condition(
name="composition",
value=NominalComposition(all_input_materials)
)
mixing_process = ProcessRun(
tags=["mixing"],
conditions=[mixing_composition]
)
binder_ingredients = []
for run in binder_runs:
binder_ingredients.append(
IngredientRun(
material=run,
process=mixing_process,
mass_fraction=NominalReal(binders[run.spec.name], ''),
)
)
powder_ingredients = []
for run in powder_runs:
powder_ingredients.append(
IngredientRun(
material=run,
process=mixing_process,
mass_fraction=NominalReal(powders[run.spec.name], ''),
)
)
green_sample = MaterialRun(process=mixing_process)
measured_firing_temperature = Condition(
name="Firing Temperature",
value=UniformReal(firing_temperature - 0.5, firing_temperature + 0.5, 'degC'),
template=firing_temperature_template
)
specified_firing_setting = Parameter(
name="Firing setting",
value=DiscreteCategorical("hot")
)
firing_spec = ProcessSpec(template=firing_template)
firing_process = ProcessRun(
conditions=[measured_firing_temperature],
parameters=[specified_firing_setting],
spec=firing_spec
)
IngredientRun(
green_sample,
process=firing_process,
mass_fraction=NormalReal(1.0, 0.0, ''),
volume_fraction=NormalReal(1.0, 0.0, ''),
number_fraction=NormalReal(1.0, 0.0, '')
)
measured_density = Property(
name="Density",
value=NominalReal(density, ''),
template=density_template
)
measured_modulus = Property(
name="Bulk modulus",
value=NormalReal(bulk_modulus, bulk_modulus / 100.0, '')
)
measurement_spec = MeasurementSpec(template=measurement_template)
measurement = MeasurementRun(
properties=[measured_density, measured_modulus],
spec=measurement_spec
)
tags = [tag] if tag else []
material_spec = MaterialSpec(template=material_template)
material_run = MaterialRun(process=firing_process, tags=tags, spec=material_spec)
measurement.material = material_run
return material_run
def ingest_material_run(data, material_spec=None, process_run=None):
"""Ingest material run with data, a material spec, and an originating process run."""
if isinstance(data, list):
return [ingest_material_run(x, material_spec) for x in data]
if not isinstance(data, dict):
raise ValueError("This ingester operates on dict, but got {}".format(type(data)))
material = MaterialRun()
sample_id = data.get("sample_id")
if sample_id:
material.add_uid("given_sample_id", sample_id)
tags = data.get("tags")
if tags:
material.tags = tags
for experiment in data.get("experiments", []):
measurement = MeasurementRun()
for name in set(known_properties.keys()).intersection(experiment.keys()):
prop = Property(
name=name,
template=known_properties[name],
value=_parse_value(experiment[name])
)
measurement.properties.append(prop)
for name in set(known_conditions.keys()).intersection(experiment.keys()):
cond = Condition(
name=name,
template=known_conditions[name],
value=_parse_value(experiment[name])
)
measurement.conditions.append(cond)
for name in set(known_parameters.keys()).intersection(experiment.keys()):
param = Parameter(
name=name,
template=known_parameters[name],
value=_parse_value(experiment[name])
)
measurement.parameters.append(param)
scan_id = experiment.get("scan_id")
if scan_id:
measurement.add_uid("given_scan_id", scan_id)
tags = experiment.get("tags")
if tags:
measurement.tags = tags
measurement.material = material
if material_spec:
material.material_spec = material_spec
if process_run:
material.process = process_run
return material
def test_material_id_link():
"""Check that a measurement can be linked to a material that is a LinkByUID."""
mat = LinkByUID('id', str(uuid4()))
meas = MeasurementRun(material=mat)
assert meas.material == mat
assert loads(dumps(meas)) == meas
def make_cake(seed=None, tmpl=None, cake_spec=None):
"""Define all objects that go into making a demo cake."""
import struct
import hashlib
if seed is not None:
random.seed(seed)
######################################################################
# Parent Objects
if tmpl is None:
tmpl = make_cake_templates()
if cake_spec is None:
cake_spec = make_cake_spec(tmpl)
######################################################################
# Objects
cake = make_instance(cake_spec)
operators = ['gwash', 'jadams', 'thomasj', 'jmadison', 'jmonroe']
cake.process.source = PerformedSource(
performed_by=random.choice(operators), performed_date='2015-03-14')
# Replace Abstract/In General
queue = [cake]
while queue:
item = queue.pop(0)
if item.spec.tags is not None:
item.tags = list(item.spec.tags)
if item.spec.notes: # None or empty string
item.notes = 'The spec says "{}"'.format(item.spec.notes)
if isinstance(item, MaterialRun):
item.name = item.name.replace('Abstract ', '')
queue.append(item.process)
elif isinstance(item, ProcessRun):
item.name = item.name.replace(', in General', '')
queue.extend(item.ingredients)
if item.template.name == "Procurement":
item.source = PerformedSource(performed_by='hamilton',
performed_date='2015-02-17')
else:
item.source = cake.process.source
elif isinstance(item, IngredientRun):
queue.append(item.material)
fuzz = 0.95 + 0.1 * random.random()
if item.spec.absolute_quantity is not None:
item.absolute_quantity = \
NormalReal(mean=fuzz * item.spec.absolute_quantity.nominal,
std=0.05 * item.spec.absolute_quantity.nominal,
units=item.spec.absolute_quantity.units)
if item.spec.volume_fraction is not None:
item.volume_fraction = \
NormalReal(mean=fuzz * item.spec.volume_fraction.nominal,
std=0.05 * item.spec.volume_fraction.nominal,
units=item.spec.volume_fraction.units)
if item.spec.mass_fraction is not None:
item.mass_fraction = \
UniformReal(lower_bound=(fuzz - 0.05) * item.spec.mass_fraction.nominal,
upper_bound=(fuzz + 0.05) * item.spec.mass_fraction.nominal,
units=item.spec.mass_fraction.units)
if item.spec.number_fraction is not None:
item.number_fraction = \
NormalReal(mean=fuzz * item.spec.number_fraction.nominal,
std=0.05 * item.spec.number_fraction.nominal,
units=item.spec.number_fraction.units)
else:
raise TypeError("Unexpected object in the queue")
frosting = \
next(x.material for x in cake.process.ingredients if 'rosting' in x.name)
baked = \
next(x.material for x in cake.process.ingredients if 'aked' in x.name)
def find_name(name, material):
# Recursively search for the right material
if name == material.name:
return material
for ingredient in material.process.ingredients:
result = find_name(name, ingredient.material)
if result:
return result
return
flour = find_name('Flour', cake)
salt = find_name('Salt', cake)
sugar = find_name('Sugar', cake)
# Add measurements
cake_taste = MeasurementRun(name='Final Taste', material=cake)
cake_appearance = MeasurementRun(name='Final Appearance', material=cake)
frosting_taste = MeasurementRun(name='Frosting Taste', material=frosting)
frosting_sweetness = MeasurementRun(name='Frosting Sweetness',
material=frosting)
baked_doneness = MeasurementRun(name='Baking doneness', material=baked)
flour_content = MeasurementRun(name='Flour nutritional analysis',
material=flour)
salt_content = MeasurementRun(name='Salt elemental analysis',
material=salt)
sugar_content = MeasurementRun(name='Sugar elemental analysis',
material=sugar)
# and spec out the measurements
cake_taste.spec = MeasurementSpec(name='Taste',
template=tmpl['Taste test'])
cake_appearance.spec = MeasurementSpec(name='Appearance')
frosting_taste.spec = cake_taste.spec # Taste
frosting_sweetness.spec = MeasurementSpec(name='Sweetness')
baked_doneness.spec = MeasurementSpec(name='Doneness',
template=tmpl["Doneness"])
flour_content.spec = MeasurementSpec(name='Nutritional analysis',
template=tmpl["Nutritional Analysis"])
salt_content.spec = MeasurementSpec(name='Elemental analysis',
template=tmpl["Elemental Analysis"])
sugar_content.spec = salt_content.spec
for msr in (cake_taste, cake_appearance, frosting_taste,
frosting_sweetness, baked_doneness, flour_content,
salt_content, sugar_content):
msr.spec.add_uid(DEMO_SCOPE, msr.spec.name)
######################################################################
# Let's add some attributes
baked.process.conditions.append(
Condition(name='Cooking time',
template=tmpl['Cooking time'],
origin=Origin.MEASURED,
value=NominalReal(nominal=48, units='min')))
baked.spec.process.conditions.append(
Condition(name='Cooking time',
template=tmpl['Cooking time'],
origin=Origin.SPECIFIED,
value=NormalReal(mean=50, std=5, units='min')))
baked.process.conditions.append(
Condition(name='Oven temperature',
origin="measured",
value=NominalReal(nominal=362, units='degF')))
baked.spec.process.parameters.append(
Parameter(name='Oven temperature setting',
template=tmpl['Oven temperature setting'],
origin="specified",
value=NominalReal(nominal=350, units='degF')))
cake_taste.properties.append(
Property(name='Tastiness',
origin=Origin.MEASURED,
template=tmpl['Tastiness'],
value=UniformInteger(4, 5)))
cake_appearance.properties.append(
Property(name='Visual Appeal',
origin=Origin.MEASURED,
value=NominalInteger(nominal=5)))
frosting_taste.properties.append(
Property(name='Tastiness',
origin=Origin.MEASURED,
template=tmpl['Tastiness'],
value=NominalInteger(nominal=4)))
frosting_sweetness.properties.append(
Property(name='Sweetness (Sucrose-basis)',
origin=Origin.MEASURED,
value=NominalReal(nominal=1.7, units='')))
baked_doneness.properties.append(
Property(name='Toothpick test',
origin="measured",
template=tmpl["Toothpick test"],
value=NominalCategorical("crumbs")))
baked_doneness.properties.append(
Property(name='Color',
origin="measured",
template=tmpl["Color"],
value=DiscreteCategorical({
"Pale": 0.05,
"Golden brown": 0.65,
"Deep brown": 0.3
})))
flour_content.properties.append(
Property(name='Nutritional Information',
value=NominalComposition({
"dietary-fiber":
1 * (0.99 + 0.02 * random.random()),
"sugars":
1 * (0.99 + 0.02 * random.random()),
"other-carbohydrate":
20 * (0.99 + 0.02 * random.random()),
"protein":
4 * (0.99 + 0.02 * random.random()),
"other":
4 * (0.99 + 0.02 * random.random())
}),
template=tmpl["Nutritional Information"],
origin="measured"))
flour_content.conditions.append(
Condition(name='Sample Mass',
value=NormalReal(mean=99 + 2 * random.random(),
std=1.5,
units='mg'),
template=tmpl["Sample Mass"],
origin="measured"))
flour_content.parameters.append(
Parameter(name='Expected Sample Mass',
value=NominalReal(nominal=0.1, units='g'),
template=tmpl["Expected Sample Mass"],
origin="specified"))
flour_content.spec.conditions.append(
Condition(name='Sample Mass',
value=NominalReal(nominal=100, units='mg'),
template=tmpl["Sample Mass"],
origin="specified"))
flour_content.spec.parameters.append(
Parameter(name='Expected Sample Mass',
value=NominalReal(nominal=0.1, units='g'),
template=tmpl["Expected Sample Mass"],
origin="specified"))
salt_content.properties.append(
Property(name="Composition",
value=EmpiricalFormula(
formula="NaClCa0.006Si0.006O0.018K0.000015I0.000015"),
template=tmpl["Chemical Formula"],
origin="measured"))
salt_content.conditions.append(
Condition(name='Sample Mass',
value=NormalReal(mean=99 + 2 * random.random(),
std=1.5,
units='mg'),
template=tmpl["Sample Mass"],
origin="measured"))
salt_content.parameters.append(
Parameter(name='Expected Sample Mass',
value=NominalReal(nominal=0.1, units='g'),
template=tmpl["Expected Sample Mass"],
origin="specified"))
salt_content.spec.conditions.append(
Condition(name='Sample Mass',
value=NominalReal(nominal=100, units='mg'),
template=tmpl["Sample Mass"],
origin="specified"))
sugar_content.properties.append(
Property(
name="Composition",
value=EmpiricalFormula(formula='C11.996H21.995O10.997S0.00015'),
template=tmpl["Chemical Formula"],
origin="measured"))
sugar_content.conditions.append(
Condition(name='Sample Mass',
value=NormalReal(mean=99 + 2 * random.random(),
std=1.5,
units='mg'),
template=tmpl["Sample Mass"],
origin="measured"))
sugar_content.spec.parameters.append(
Parameter(name='Expected Sample Mass',
value=NominalReal(nominal=0.1, units='g'),
template=tmpl["Expected Sample Mass"],
origin="specified"))
# Code to generate quasi-repeatable run annotations
# Note there are potential machine dependencies
md5 = hashlib.md5()
for x in random.getstate()[1]:
md5.update(struct.pack(">I", x))
run_key = md5.hexdigest()
# Crawl tree and annotate with uids; only add ids if there's nothing there
recursive_foreach(
cake,
lambda obj: obj.uids or obj.add_uid(DEMO_SCOPE, obj.name + run_key))
cake.notes = cake.notes + "; Très délicieux! 😀"
cake.file_links = [
FileLink(
filename="Photo",
url='https://www.landolakes.com/RecipeManagementSystem/media/'
'Recipe-Media-Files/Recipes/Retail/x17/16730-beckys-butter-cake-600x600.jpg?ext=.jpg'
)
]
return cake