def test_WildtypeFilter(self):
f = data_query.WildtypeFilter()
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(variation='')))
self.assertEqual(f.score(None, ov), 1)
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(variation='Delta gene-01')))
self.assertEqual(f.score(None, ov), -1)
def test(self):
genetics = data_model.Genetics(taxon='Mycoplasma pneumoniae',
variation='ΔMPN001')
self.assertFalse(genetics.is_wildtype())
self.assertTrue(genetics.is_variant())
genetics = data_model.Genetics(taxon='Mycoplasma pneumoniae',
variation='')
self.assertTrue(genetics.is_wildtype())
self.assertFalse(genetics.is_variant())
def test_TaxonomicDistanceFilter(self):
# example 1
f = data_query.TaxonomicDistanceFilter('Mycoplasma pneumoniae M129')
self.assertEqual(f.max, 8.)
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(taxon='Mycoplasma pneumoniae M129')))
self.assertEqual(f.score(None, ov), 1.)
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(taxon='Mycoplasma pneumoniae')))
self.assertEqual(f.scale, 8./5)
self.assertEqual(f.score(None, ov), math.exp(-1/f.scale))
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(taxon='Escherichia coli')))
self.assertEqual(f.score(None, ov), math.exp(-5))
# example 2
f = data_query.TaxonomicDistanceFilter('Mycoplasma pneumoniae M129', max=5)
self.assertEqual(f.max, 5.)
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(taxon='Mycoplasma pneumoniae M129')))
self.assertEqual(f.score(None, ov), 1.)
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(taxon='Mycoplasma pneumoniae')))
self.assertEqual(f.score(None, ov), math.exp(-1/f.scale))
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(taxon='Escherichia coli')))
self.assertEqual(f.score(None, ov), -1)
# example 3
f = data_query.TaxonomicDistanceFilter('Mycoplasma genitalium')
self.assertEqual(f.max, 7.)
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(taxon='Mycoplasma genitalium G37')))
self.assertEqual(f.score(None, ov), 1.)
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(taxon='Mycoplasma genitalium')))
self.assertEqual(f.score(None, ov), 1)
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(taxon='Mycoplasma')))
self.assertEqual(f.score(None, ov), math.exp(-1/f.scale))
def read_genetics(self, ws):
""" Read taxon from an Excel worksheet
Args:
ws (:obj:`openpyxl.Worksheet`): worksheet
Returns:
:obj:`data_model.Genetics`: taxon
"""
return data_model.Genetics(
taxon=ws.cell(row=2, column=1).value,
variation=ws.cell(row=2, column=2).value,
)
def test_OptionsFilter(self):
f = data_query.OptionsFilter(('metadata', 'genetics', 'variation', ), [''])
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(variation='')))
self.assertEqual(f.score(None, ov), 1)
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(variation='wildtype')))
self.assertEqual(f.score(None, ov), -1)
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(variation='Delta gene-01')))
self.assertEqual(f.score(None, ov), -1)
f = data_query.OptionsFilter(('metadata', 'genetics', 'variation', ), ['wildtype'])
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(variation='')))
self.assertEqual(f.score(None, ov), -1)
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(variation='wildtype')))
self.assertEqual(f.score(None, ov), 1)
ov = data_model.ObservedValue(
metadata=data_model.ObservedResultMetadata(genetics=data_model.Genetics(variation='Delta gene-01')))
self.assertEqual(f.score(None, ov), -1)
def metadata_dump(self, component):
""" Calculate a consensus statistical representation of the one or more observed values
Args:
component (:obj:`models.Observation`): model component dump data for
Returns:
:obj:`list` of :obj:`data_model.ObservedResultMetadata`: data model metadata object
"""
genetics = None
environment = None
cross_references = []
method = None
synonym = []
meta = component._metadata
taxon = meta.taxon[0].name if meta.taxon else None
variation = meta.cell_line[0].name if meta.cell_line else None
genetics = data_model.Genetics(taxon=taxon, variation=variation)
temperature = meta.conditions[
0].temperature if meta.conditions else None
ph = meta.conditions[0].ph if meta.conditions else None
media = meta.conditions[0].media if meta.conditions else None
growth_status = meta.conditions[
0].growth_status if meta.conditions else None
growth_system = meta.conditions[
0].growth_system if meta.conditions else None
environment = data_model.Environment(temperature=temperature,
ph=ph,
media=media,
growth_status=growth_status,
growth_system=growth_system)
name = meta.method[0].name if meta.method else None
description = meta.method[0].comments if meta.method else None
performer = meta.method[0].performer if meta.method else None
hardware = meta.method[0].hardware if meta.method else None
software = meta.method[0].software if meta.method else None
method = data_model.Method(name=name,
description=description,
performer=performer,
hardware=hardware,
software=software)
if meta.resource:
for item in meta.resource:
cross_references.append(
data_model.Resource(namespace=item.namespace, id=item._id))
else:
cross_references.append(
data_model.Resource(namespace=None, id=None))
if meta.synonym:
for item in meta.synonym:
synonym.append(data_model.Synonym(name=item.name))
else:
synonym.append(data_model.Synonym(name=None))
metadata_result = data_model.ObservedResultMetadata(
genetics=genetics,
environment=environment,
cross_references=cross_references,
method=method,
synonym=synonym)
return metadata_result
def test_ObservedResultMetadata(self):
o = data_model.ObservedResultMetadata()
o.genetics = data_model.Genetics(taxon='Mycoplasma pneumoniae',
variation='ΔMPN001')
o.environment = data_model.Environment(temperature=37,
ph=7.,
media='Hayflick')
o.reference = data_model.Reference(title='title',
author='author',
year=2017,
volume=1,
number=1,
pages='1-10')
o.method = data_model.ExperimentalMethod(
name='assay', description='description of assay')
observable = data_model.Observable(
interaction=data_model.Reaction(id='AtpSynthase'),
specie=data_model.Specie(id='ATP'),
compartment=data_model.Compartment(id='c'),
property='K_m',
)
ov = data_model.ObservedValue(
observable=observable,
value=1.0,
error=0.5,
units='U/mg',
)
o.observed_result.append(ov)
o.validate()
self.assertEqual(o.observed_result, [ov])
self.assertEqual(ov.metadata, o)
self.assertEqual(ov.observable.interaction.id, 'AtpSynthase')
self.assertEqual(ov.observable.specie.id, 'ATP')
self.assertEqual(ov.observable.compartment.id, 'c')
self.assertEqual(ov.observable.property, 'K_m')
self.assertEqual(ov.value, 1.0)
self.assertEqual(ov.error, 0.5)
self.assertEqual(ov.units, 'U/mg')
self.assertEqual(o.genetics.taxon, 'Mycoplasma pneumoniae')
self.assertEqual(o.genetics.variation, 'ΔMPN001')
self.assertEqual(o.environment.temperature, 37.)
self.assertEqual(o.environment.ph, 7.)
self.assertEqual(o.environment.media, 'Hayflick')
self.assertEqual(o.reference.title, 'title')
self.assertEqual(o.reference.author, 'author')
self.assertEqual(o.reference.year, 2017)
self.assertEqual(o.reference.volume, 1)
self.assertEqual(o.reference.number, 1)
self.assertEqual(o.reference.pages, '1-10')
self.assertEqual(o.method.name, 'assay')
self.assertEqual(o.method.description, 'description of assay')