本文整理汇总了Python中dipper.models.Model.Model.addPerson方法的典型用法代码示例。如果您正苦于以下问题：Python Model.addPerson方法的具体用法？Python Model.addPerson怎么用？Python Model.addPerson使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类dipper.models.Model.Model的用法示例。
在下文中一共展示了Model.addPerson方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _parse_patient_phenotypes
# 需要导入模块: from dipper.models.Model import Model [as 别名]
# 或者: from dipper.models.Model.Model import addPerson [as 别名]
def _parse_patient_phenotypes(self, file, limit=None):
"""
:param file: file handler
:param limit: limit rows processed
:return:
"""
model = Model(self.graph)
line_counter = 0
reader = csv.reader(file, delimiter="\t")
for row in reader:
(patient_id, hpo_curie, present) = row
patient_curie = ':{0}'.format(patient_id)
if patient_id == 'Patient': # skip header
line_counter += 1
continue
model.addPerson(patient_curie, patient_id)
self.graph.addTriple(
patient_curie, self.globaltt['has phenotype'], self.globaltt['disease'])
if present == 'yes':
self.graph.addTriple(
patient_curie, self.globaltt['has phenotype'], hpo_curie)
line_counter += 1
if not self.test_mode and limit is not None \
and line_counter >= limit:
break示例2: _process_data
# 需要导入模块: from dipper.models.Model import Model [as 别名]
# 或者: from dipper.models.Model.Model import addPerson [as 别名]
#.........这里部分代码省略.........
# in the source data; so add them
model.addIndividualToGraph(
equiv_cell_line, None, cell_line_reagent_id)
model.addSameIndividual(cell_line_id, equiv_cell_line)
# Cell line derives from patient
geno.addDerivesFrom(cell_line_id, patient_id)
geno.addDerivesFrom(cell_line_id, cell_type)
# Cell line a member of repository
family.addMember(repository, cell_line_id)
cat_remark = row[col.index('cat_remark')].strip()
if cat_remark != '':
model.addDescription(cell_line_id, cat_remark)
# Cell age_at_sampling
# TODO add the age nodes when modeled properly in #78
# if (age != ''):
# this would give a BNode that is an instance of Age.
# but i don't know how to connect
# the age node to the cell line? we need to ask @mbrush
# age_id = '_'+re.sub('\s+','_',age)
# gu.addIndividualToGraph(
# graph,age_id,age,self.globaltt['age'])
# gu.addTriple(
# graph,age_id,self.globaltt['has measurement value'],age,
# True)
# ############# BUILD THE PATIENT #############
# Add the patient ID as an individual.
model.addPerson(patient_id, patient_label)
# TODO map relationship to proband as a class
# (what ontology?)
# Add race of patient
# FIXME: Adjust for subcategories based on ethnicity field
# EDIT: There are 743 different entries for ethnicity...
# Too many to map?
# Add ethnicity as literal in addition to the mapped race?
# Adjust the ethnicity txt (if using)
# to initial capitalization to remove ALLCAPS
# TODO race should go into the individual's background
# and abstracted out to the Genotype class punting for now.
# if race != '':
# mapped_race = self.resolve(race)
# if mapped_race is not None:
# gu.addTriple(
# g,patient_id,self.globaltt['race'], mapped_race)
# model.addSubClass(
# mapped_race,self.globaltt['ethnic_group'])
# ############# BUILD THE FAMILY #############
# Add triples for family_id, if present.
if fam_id != '':
family_comp_id = 'CoriellFamily:' + fam_id
family_label = ' '.join(('Family of proband with', short_desc))
# Add the family ID as a named individual
model.addIndividualToGraph(
family_comp_id, family_label, self.globaltt['family'])