def test_init_with_single_treatment(self):
treatment = Treatment(
treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=self.agent, value='crack'),
FactorValue(factor_name=self.intensity,
value='low'),
FactorValue(factor_name=self.duration,
value='short')))
new_sequence = TreatmentSequence(ranked_treatments=treatment)
self.assertTrue((treatment, 1) in new_sequence.ranked_treatments)
def setUp(self):
self.maxDiff = None
self.treatment = Treatment(
factor_values=(FactorValue(factor_name=BASE_FACTORS[0][NAME],
value=FACTORS_0_VALUE),
FactorValue(factor_name=BASE_FACTORS[1][NAME],
value=FACTORS_1_VALUE,
unit=FACTORS_1_UNIT),
FactorValue(factor_name=BASE_FACTORS[2][NAME],
value=FACTORS_2_VALUE,
unit=FACTORS_2_UNIT)))
def test_eq(self):
same_treatment = Treatment(
factor_values=(FactorValue(factor_name=BASE_FACTORS[0][NAME],
value=FACTORS_0_VALUE),
FactorValue(factor_name=BASE_FACTORS[1][NAME],
value=FACTORS_1_VALUE,
unit=FACTORS_1_UNIT),
FactorValue(factor_name=BASE_FACTORS[2][NAME],
value=FACTORS_2_VALUE,
unit=FACTORS_2_UNIT)))
self.assertEqual(self.treatment, same_treatment)
self.assertEqual(hash(self.treatment), hash(same_treatment))
def test_ne(self):
other_treatment = Treatment(
factor_values=(FactorValue(factor_name=BASE_FACTORS[0][NAME],
value=FACTORS_0_VALUE),
FactorValue(factor_name=BASE_FACTORS[1][NAME],
value=FACTORS_1_VALUE,
unit=FACTORS_1_UNIT),
FactorValue(factor_name=BASE_FACTORS[2][NAME],
value=FACTORS_2_VALUE_ALT,
unit=FACTORS_2_UNIT)))
self.assertNotEqual(self.treatment, other_treatment)
self.assertNotEqual(hash(self.treatment), hash(other_treatment))
def setUp(self):
self.maxDiff = None
self.sequence = TreatmentSequence()
self.agent = StudyFactor(name=BASE_FACTORS[0]['name'],
factor_type=BASE_FACTORS[0]['type'])
self.intensity = StudyFactor(name=BASE_FACTORS[1]['name'],
factor_type=BASE_FACTORS[1]['type'])
self.duration = StudyFactor(name=BASE_FACTORS[2]['name'],
factor_type=BASE_FACTORS[2]['type'])
self.test_treatment = Treatment(
treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=self.agent, value='crack'),
FactorValue(factor_name=self.intensity,
value='low'),
FactorValue(factor_name=self.duration,
value='short')))
def setUp(self):
self.design = InterventionStudyDesign()
self.agent = StudyFactor(name=BASE_FACTORS[0]['name'],
factor_type=BASE_FACTORS[0]['type'])
self.intensity = StudyFactor(name=BASE_FACTORS[1]['name'],
factor_type=BASE_FACTORS[1]['type'])
self.duration = StudyFactor(name=BASE_FACTORS[2]['name'],
factor_type=BASE_FACTORS[2]['type'])
self.first_treatment = Treatment(
treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=self.agent, value='crack'),
FactorValue(factor_name=self.intensity,
value='low'),
FactorValue(factor_name=self.duration,
value='medium')))
self.second_treatment = Treatment(
treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=self.agent, value='crack'),
FactorValue(factor_name=self.intensity,
value='high'),
FactorValue(factor_name=self.duration,
value='medium')))
self.test_sequence = TreatmentSequence(
ranked_treatments=[(self.first_treatment,
1), (self.second_treatment, 2)])
self.sample_plan = SampleAssayPlan(group_size=10,
sample_plan={},
assay_plan=None)
def unserialize_factor_value(json_obj):
factor_name = StudyFactor()
if 'factorName' in json_obj and json_obj['factorName'] is not None:
factor_name = unserialize_study_factor(json_obj['factorName'])
value = OntologyAnnotation()
if 'value' in json_obj and json_obj['value'] is not None:
value = unserialize_ontology_annotation(json_obj['value'])
unit = OntologyAnnotation()
if 'unit' in json_obj and json_obj['unit'] is not None:
unit = unserialize_ontology_annotation(json_obj['value'])
comments = list()
if 'comments' in json_obj and json_obj['comments'] is not None:
for comment in json_obj['comments']:
comments.append(unserialize_comment(comment))
return FactorValue(factor_name=factor_name,
value=value,
unit=unit,
comments=comments)
def test_repr(self):
treatments = [
(Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=self.agent,
value='crack'),
FactorValue(factor_name=self.intensity,
value='low'),
FactorValue(factor_name=self.duration,
value='short'))), 1),
(Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=self.agent,
value='crack'),
FactorValue(factor_name=self.intensity,
value='low'),
FactorValue(factor_name=self.duration,
value='long'))), 2)
]
new_sequence = TreatmentSequence(ranked_treatments=treatments)
self.assertEqual(
'TreatmentSequence([(Treatment(factor_type=chemical '
'intervention, factor_values=(FactorValue(factor_name='
'StudyFactor(name="AGENT", factor_type='
'OntologyAnnotation(term="perturbation agent", '
'term_source=None, term_accession="", comments=[]), '
'comments=[]), value=crack, unit=None), FactorValue('
'factor_name=StudyFactor(name="INTENSITY", '
'factor_type=OntologyAnnotation(term="intensity", '
'term_source=None, term_accession="", comments=[]), '
'comments=[]), value=low, unit=None), FactorValue('
'factor_name=StudyFactor(name="DURATION", '
'factor_type=OntologyAnnotation(term="time", '
'term_source=None, term_accession="", comments=[]), '
'comments=[]), value=short, unit=None))), 1), ('
'Treatment(factor_type=chemical intervention, '
'factor_values=(FactorValue(factor_name=StudyFactor('
'name="AGENT", factor_type=OntologyAnnotation('
'term="perturbation agent", term_source=None, '
'term_accession="", comments=[]), comments=[]), '
'value=crack, unit=None), FactorValue(factor_name='
'StudyFactor(name="INTENSITY", factor_type='
'OntologyAnnotation(term="intensity", '
'term_source=None, term_accession="", comments=[]), '
'comments=[]), value=low, unit=None), FactorValue('
'factor_name=StudyFactor(name="DURATION", '
'factor_type=OntologyAnnotation(term="time", '
'term_source=None, term_accession="", comments=[]), '
'comments=[]), value=long, unit=None))), 2)])', repr(new_sequence))
def test_init_with_treatments_list_no_rank(self):
treatments = [
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=self.agent,
value='crack'),
FactorValue(factor_name=self.intensity,
value='low'),
FactorValue(factor_name=self.duration,
value='short'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=self.agent,
value='crack'),
FactorValue(factor_name=self.intensity,
value='low'),
FactorValue(factor_name=self.duration,
value='long')))
]
new_sequence = TreatmentSequence(ranked_treatments=treatments)
self.assertTrue((treatments[0], 1) in new_sequence.ranked_treatments)
self.assertTrue((treatments[1], 1) in new_sequence.ranked_treatments)
def test_ranked_treatments_setter(self):
treatments = [
(Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=self.agent,
value='crack'),
FactorValue(factor_name=self.intensity,
value='low'),
FactorValue(factor_name=self.duration,
value='short'))), 2),
(Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=self.agent,
value='crack'),
FactorValue(factor_name=self.intensity,
value='low'),
FactorValue(factor_name=self.duration,
value='long'))), 1)
]
self.sequence.ranked_treatments = treatments
self.assertTrue(isinstance(self.sequence.ranked_treatments, set))
self.assertTrue(treatments[0] in self.sequence.ranked_treatments)
self.assertTrue(treatments[1] in self.sequence.ranked_treatments)
def test_eq(self):
treatments = [
(Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=self.agent,
value='crack'),
FactorValue(factor_name=self.intensity,
value='low'),
FactorValue(factor_name=self.duration,
value='short'))), 1),
(Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=self.agent,
value='crack'),
FactorValue(factor_name=self.intensity,
value='low'),
FactorValue(factor_name=self.duration,
value='long'))), 2)
]
first_sequence = TreatmentSequence(treatments)
second_sequence = TreatmentSequence(reversed(treatments))
self.assertEqual(first_sequence, second_sequence)
self.assertEqual(hash(first_sequence), hash(second_sequence))
characteristics=characteristics)
# print(source)
study.sources.append(source)
sample = Sample(name=ou["observationUnitDbId"])
if 'treatments' in ou.keys():
for element in ou['treatments']:
for key in element.keys():
f = StudyFactor(name=key,
factor_type=OntologyAnnotation(term=key))
if f not in study.factors:
study.factors.append(f)
fv = FactorValue(factor_name=f,
value=OntologyAnnotation(term=str(
element[key]),
term_source="",
term_accession=""))
sample.factor_values.append(fv)
print(sample)
if 'observations' in ou.keys():
for ob in ou['observations']:
phenotyping_process = Process(
executes_protocol=phenotyping_protocol)
phenotyping_process.name = "assay-name-{}".format(counter)
phenotyping_process.inputs.append(sample)
# print(ob['observations'])
if 'season' in ou['observations'][0].keys():
# if 'season' in phenotyping_protocol.parameter_list:
# pass
def create_study_sample_and_assay(client, brapi_study_id, isa_study, sample_collection_protocol, phenotyping_protocol):
obsunit_to_isasample_mapping_dictionary = {
"X": "X",
"Y": "Y",
"blockNumber": "Block Number",
"plotNumber": "Plot Number",
"plantNumber": "Plant Number",
"observationLevel": "Observation unit type"
}
obsunit_to_isaassay_mapping_dictionary = {
"X": "X",
"Y": "Y",
"blockNumber": "Block Number",
"plotNumber": "Plot Number",
"plantNumber": "Plant Number",
"observationLevel": "Observation unit type"
}
allready_converted_obs_unit = [] # Allow to handle multiyear observation units
for obs_unit in client.get_study_observation_units(brapi_study_id):
# Getting the relevant germplasm used for that observation event:
# ---------------------------------------------------------------
this_source = isa_study.get_source(obs_unit['germplasmName'])
#logger.debug("testing for the source reference: ", str(this_source))
# TODO Assumed one assay by study. Will need to move to one assay by level/datalink
this_assay = isa_study.assays[0]
# Sample == Observation Unit
if this_source is not None and obs_unit['observationUnitName'] not in allready_converted_obs_unit:
#The observationUnitName is the buisness ID of the Observation unit (ie plot number) while the ID is the PK
this_isa_sample = Sample(
name= obs_unit['observationUnitName'],
#name=obs_unit['observationUnitDbId'] + "_" + obs_unit['observationUnitName'],
derives_from=[this_source])
allready_converted_obs_unit.append(obs_unit['observationUnitName'])
for key in obs_unit.keys():
if key in obsunit_to_isasample_mapping_dictionary.keys():
if isinstance(obsunit_to_isasample_mapping_dictionary[key], str) and str(obs_unit[key]) is not None :
c = Characteristic(category=OntologyAnnotation(term=obsunit_to_isasample_mapping_dictionary[key]),
value=OntologyAnnotation(term=str(obs_unit[key]),
term_source="",
term_accession=""))
this_isa_sample.characteristics.append(c)
# else:
#no defult behaviour, it is maped or ignored
# c = Characteristic(category=OntologyAnnotation(term=key),
# value=OntologyAnnotation(term=str(obs_unit[key]),
# term_source="",
# term_accession=""))
# this_isa_sample.characteristics.append(c)
if key in obsunit_to_isaassay_mapping_dictionary.keys():
if isinstance(obsunit_to_isaassay_mapping_dictionary[key], str):
c = Characteristic(category=OntologyAnnotation(term=obsunit_to_isaassay_mapping_dictionary[key]),
value=OntologyAnnotation(term=str(obs_unit[key]),
term_source="",
term_accession=""))
#TODO: quick workaround used to store observation units characteristics
this_assay.comments.append(c)
# if 'observationLevel' in obs_unit.keys():
# # TODO: if absent, a warning should be logged as this is a MIAPPE requirement
# Looking for treatment in BRAPI and mapping to ISA Study Factor Value
# --------------------------------------------------------------------
if 'treatments' in obs_unit.keys():
for element in obs_unit['treatments']:
for key in element.keys():
f = StudyFactor(name=key, factor_type=OntologyAnnotation(term=key))
if f not in isa_study.factors:
isa_study.factors.append(f)
fv = FactorValue(factor_name=f,
value=OntologyAnnotation(term=str(element[key]),
term_source="",
term_accession=""))
this_isa_sample.factor_values.append(fv)
isa_study.samples.append(this_isa_sample)
# print("counting observations: ", i, "before: ", this_source.name)
# TODO: Add Comment[Factor Values] : iterate through BRAPI treatments to obtain all possible values for a given Factor
# Creating the corresponding ISA sample entity for structure the document:
# ------------------------------------------------------------------------
sample_collection_process = Process(executes_protocol=sample_collection_protocol)
sample_collection_process.performer = "n.a."
sample_collection_process.date = datetime.datetime.today().isoformat()
sample_collection_process.inputs.append(this_source)
sample_collection_process.outputs.append(this_isa_sample)
isa_study.process_sequence.append(sample_collection_process)
#logger.debug(str(this_assay))
# Creating the relevant ISA protocol application / Assay from BRAPI Observation Events:
# -------------------------------------------------------------------------------------
create_data_file(obs_unit, this_assay, sample_collection_process, this_isa_sample, phenotyping_protocol)
def test_compute_full_factorial_design(self):
agent = StudyFactor(name=BASE_FACTORS[0]['name'],
factor_type=BASE_FACTORS[0]['type'])
intensity = StudyFactor(name=BASE_FACTORS[1]['name'],
factor_type=BASE_FACTORS[1]['type'])
duration = StudyFactor(name=BASE_FACTORS[2]['name'],
factor_type=BASE_FACTORS[2]['type'])
self.factory.add_factor_value(agent, {'cocaine', 'crack', 'aether'})
self.factory.add_factor_value(intensity, {'low', 'medium', 'high'})
self.factory.add_factor_value(duration, {'short', 'long'})
full_factorial = self.factory.compute_full_factorial_design()
self.assertEqual(
full_factorial, {
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='cocaine'),
FactorValue(factor_name=intensity,
value='high'),
FactorValue(factor_name=duration,
value='long'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='cocaine'),
FactorValue(factor_name=intensity,
value='high'),
FactorValue(factor_name=duration,
value='short'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='cocaine'),
FactorValue(factor_name=intensity,
value='low'),
FactorValue(factor_name=duration,
value='long'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='cocaine'),
FactorValue(factor_name=intensity,
value='low'),
FactorValue(factor_name=duration,
value='short'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='cocaine'),
FactorValue(factor_name=intensity,
value='medium'),
FactorValue(factor_name=duration,
value='long'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='cocaine'),
FactorValue(factor_name=intensity,
value='medium'),
FactorValue(factor_name=duration,
value='short'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='crack'),
FactorValue(factor_name=intensity,
value='high'),
FactorValue(factor_name=duration,
value='long'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='crack'),
FactorValue(factor_name=intensity,
value='high'),
FactorValue(factor_name=duration,
value='short'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='crack'),
FactorValue(factor_name=intensity,
value='low'),
FactorValue(factor_name=duration,
value='long'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='crack'),
FactorValue(factor_name=intensity,
value='low'),
FactorValue(factor_name=duration,
value='short'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='crack'),
FactorValue(factor_name=intensity,
value='medium'),
FactorValue(factor_name=duration,
value='long'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='crack'),
FactorValue(factor_name=intensity,
value='medium'),
FactorValue(factor_name=duration,
value='short'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='aether'),
FactorValue(factor_name=intensity,
value='high'),
FactorValue(factor_name=duration,
value='long'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='aether'),
FactorValue(factor_name=intensity,
value='high'),
FactorValue(factor_name=duration,
value='short'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='aether'),
FactorValue(factor_name=intensity,
value='low'),
FactorValue(factor_name=duration,
value='long'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='aether'),
FactorValue(factor_name=intensity,
value='low'),
FactorValue(factor_name=duration,
value='short'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='aether'),
FactorValue(factor_name=intensity,
value='medium'),
FactorValue(factor_name=duration,
value='long'))),
Treatment(treatment_type=INTERVENTIONS['CHEMICAL'],
factor_values=(FactorValue(factor_name=agent,
value='aether'),
FactorValue(factor_name=intensity,
value='medium'),
FactorValue(factor_name=duration,
value='short')))
})