def test_model_add_remove(self):
"""
Tests the outcome of adding and removing a model from the canonical graph.
"""
symbols = GraphTest.generate_canonical_symbols()
models = GraphTest.generate_canonical_models()
g = Graph(models=models, symbol_types=symbols, composite_models=dict())
g.remove_models({models['model6'].name: models['model6']})
self.assertTrue(models['model6'] not in g.get_models().values(),
"Model was unsuccessfully removed from the graph.")
for s in g._input_to_model.values():
self.assertTrue(models['model6'] not in s,
"Model was unsuccessfully removed from the graph.")
for s in g._output_to_model.values():
self.assertTrue(models['model6'] not in s,
"Model was unsuccessfully removed from the graph.")
m6 = models['model6']
del models['model6']
for m in models.values():
self.assertTrue(m in g.get_models().values(),
"Too many models were removed.")
g.update_models({'Model6': m6})
self.assertTrue(m6 in g.get_models().values(),
"Model was unsuccessfully added to the graph.")
self.assertTrue(m6 in g._input_to_model[symbols['D']],
"Model was unsuccessfully added to the graph.")
self.assertTrue(m6 in g._input_to_model[symbols['F']],
"Model was unsuccessfully added to the graph.")
self.assertTrue(m6 in g._output_to_model[symbols['A']],
"Model was unsuccessfully added to the graph.")
def process_item(self, item):
# Define quantities corresponding to materials doc fields
# Attach quantities to materials
item = MontyDecoder().process_decoded(item)
logger.info("Populating material for %s", item['task_id'])
material = Material()
for mkey, property_name in self.materials_symbol_map.items():
value = get(item, mkey)
if value:
material.add_quantity(Quantity(property_name, value))
# Add custom things, e. g. computed entry
computed_entry = get_entry(item)
material.add_quantity(Quantity("computed_entry", computed_entry))
material.add_quantity(
Quantity("external_identifier_mp", item['task_id']))
input_quantities = material.get_quantities()
# Use graph to generate expanded quantity pool
logger.info("Evaluating graph for %s", item['task_id'])
graph = Graph()
graph.remove_models({
"dimensionality_cheon":
DEFAULT_MODEL_DICT['dimensionality_cheon'],
"dimensionality_gorai":
DEFAULT_MODEL_DICT['dimensionality_gorai']
})
new_material = graph.evaluate(material)
# Format document and return
logger.info("Creating doc for %s", item['task_id'])
doc = {"inputs": [quantity.as_dict() for quantity in input_quantities]}
for symbol, quantity in new_material.get_aggregated_quantities().items(
):
all_qs = new_material._symbol_to_quantity[symbol]
# Only add new quantities
if len(all_qs) == 1 and list(all_qs)[0] in input_quantities:
continue
qs = [quantity.as_dict() for quantity in all_qs]
sub_doc = {
"quantities": qs,
"mean": unumpy.nominal_values(quantity.value).tolist(),
"std_dev": unumpy.std_devs(quantity.value).tolist(),
"units": qs[0]['units'],
"title": quantity._symbol_type.display_names[0]
}
doc[symbol.name] = sub_doc
doc.update({
"task_id": item["task_id"],
"pretty_formula": item["pretty_formula"]
})
return jsanitize(doc, strict=True)
def process_item(self, item):
# Define quantities corresponding to materials doc fields
# Attach quantities to materials
item = MontyDecoder().process_decoded(item)
logger.info("Populating material for %s", item['task_id'])
material = Material()
if 'created_at' in item.keys():
date_created = item['created_at']
else:
date_created = ""
provenance = ProvenanceElement(
source={
"source": self.source_name,
"source_key": item['task_id'],
"date_created": date_created
})
for mkey, property_name in self.materials_symbol_map.items():
value = get(item, mkey)
if value:
material.add_quantity(
QuantityFactory.create_quantity(property_name,
value,
provenance=provenance))
# Add custom things, e. g. computed entry
computed_entry = get_entry(item)
material.add_quantity(
QuantityFactory.create_quantity("computed_entry",
computed_entry,
provenance=provenance))
material.add_quantity(
QuantityFactory.create_quantity("external_identifier_mp",
item['task_id'],
provenance=provenance))
input_quantities = material.get_quantities()
# Use graph to generate expanded quantity pool
logger.info("Evaluating graph for %s", item['task_id'])
graph = Graph()
graph.remove_models({
"dimensionality_cheon":
DEFAULT_MODEL_DICT['dimensionality_cheon'],
"dimensionality_gorai":
DEFAULT_MODEL_DICT['dimensionality_gorai']
})
new_material = graph.evaluate(material)
# Format document and return
logger.info("Creating doc for %s", item['task_id'])
# Gives the initial inputs that were used to derive properties of a
# certain material.
doc = {
"inputs":
[StorageQuantity.from_quantity(q) for q in input_quantities]
}
for symbol, quantity in new_material.get_aggregated_quantities().items(
):
all_qs = new_material._symbol_to_quantity[symbol]
# Only add new quantities
# TODO: Condition insufficiently general.
# Can end up with initial quantities added as "new quantities"
if len(all_qs) == 1 and list(all_qs)[0] in input_quantities:
continue
# Write out all quantities as dicts including the
# internal ID for provenance tracing
qs = [StorageQuantity.from_quantity(q).as_dict() for q in all_qs]
# THE listing of all Quantities of a given symbol.
sub_doc = {
"quantities": qs,
"mean": unumpy.nominal_values(quantity.value).tolist(),
"std_dev": unumpy.std_devs(quantity.value).tolist(),
"units":
quantity.units.format_babel() if quantity.units else None,
"title": quantity._symbol_type.display_names[0]
}
# Symbol Name -> Sub_Document, listing all Quantities of that type.
doc[symbol.name] = sub_doc
doc.update({
"task_id": item["task_id"],
"pretty_formula": item["pretty_formula"]
})
return jsanitize(doc, strict=True)
