def dump_gender_check(self, ofile):
dt = DependencyTree(self.kb)
data_samples, ds_to_do = self.pre_load_data()
fnames = 'individual_id gender path mimetype size sha1'.split()
tsv = csv.DictWriter(ofile,
fnames,
delimiter='\t',
lineterminator=os.linesep)
tsv.writeheader()
for ds in data_samples:
v = dt.get_connected(ds)
i = filter(lambda x: type(x) == self.kb.Individual, v)[0]
if ds_to_do.has_key(ds.id):
for do in ds_to_do[ds.id]:
r = {
'individual_id': i.id,
'gender': self.gender_str(i.gender),
'path': do.path,
'mimetype': do.mimetype,
'size': do.size,
'sha1': do.sha1,
}
tsv.writerow(r)
else:
self.logger.warn('there is no DataObject for %s[%s]' %
(ds.label, ds.id))
def dump(self, study_label, ofile):
if study_label is None:
individuals = self.kb.get_objects(self.kb.Individual)
study_label = "_ALL_"
else:
study = self.kb.get_study(study_label)
if not study:
msg = 'study %s does not exist' % study_label
self.logger.critical(msg)
raise ValueError(msg)
individuals = [e.individual for e in self.kb.get_enrolled(study)]
dt = DependencyTree(self.kb)
self.dump_individuals(dt, study_label, individuals, ofile)
def dump(self, args):
self.ots = None
self._field_names = []
self.logger.info('start loading dependency tree')
dt = DependencyTree(self.kb)
self.logger.info('done loading dependency tree')
def writeheader(*field_names):
self._field_names = field_names
self.ots = csv.DictWriter(args.ofile,
self._field_names,
delimiter='\t')
self.ots.writeheader()
def writerow(*field_values):
d = dict(zip(self._field_names, field_values))
self.ots.writerow(d)
def Individuals(group):
return self.kb.get_individuals(group)
def DataSamples(individual, data_sample_klass_name='DataSample'):
klass = getattr(self.kb, data_sample_klass_name)
return dt.get_connected(individual, aklass=klass)
def DataObjects(data_sample):
q = """select o from DataObject as o join fetch o.sample as s
where s.id = :sid"""
return self.kb.find_all_by_query(q, {'sid': data_sample.omero_id})
def enum_label(x):
if isinstance(x, self.kb.Gender):
if x == self.kb.Gender.MALE:
return 'MALE'
if x == self.kb.Gender.FEMALE:
return 'FEMALE'
code = args.code_file.read()
group = self.kb.get_study(args.group)
ccode = compile(code, '<string>', 'exec')
exec ccode in locals()
def dump_call_gt(self, ofile):
if not self.data_collection:
raise ValueError('data_collection %s is not known to KB' %
self.data_collection)
dt = DependencyTree(self.kb)
data_samples, ds_to_do = self.pre_load_data()
fnames = [
'dc_id', 'item_id', 'data_sample_label', 'path', 'gender',
'mimetype', 'size', 'sha1'
]
tsv = csv.DictWriter(ofile,
fnames,
delimiter='\t',
lineterminator=os.linesep)
tsv.writeheader()
dc_id = self.data_collection.id
for ds in data_samples:
v = dt.get_connected(ds, self.kb.Individual)
assert len(v) == 1
i = v[0]
if ds_to_do.has_key(ds.id):
for do in ds_to_do[ds.id]:
r = {
'dc_id': dc_id,
'data_sample_label': do.sample.label,
'item_id': do.sample.id,
'gender': self.gender_str(i.gender),
'path': do.path,
'mimetype': do.mimetype,
'size': do.size,
'sha1': do.sha1,
}
tsv.writerow(r)
else:
self.logger.warn('there is no DataObject for %s[%s]' %
(ds.label, ds.id))
def dump(self, args, ots):
if args.seed is None:
random.seed()
else:
random.seed(args.seed)
if args.study is None:
individuals = self.kb.get_objects(self.kb.Individual)
else:
study = self.kb.get_study(args.study)
if not study:
self.__critical('study %s does not exist' % args.study)
individuals = [e.individual for e in self.kb.get_enrolled(study)]
if args.required_datasample:
tech = getattr(self.kb, args.required_datasample)
self.logger.info('start loading dependency tree')
dt = DependencyTree(self.kb)
self.logger.info('done loading dependency tree')
else:
tech = None
atype_control = 'openEHR-EHR-EVALUATION.exclusion-problem_diagnosis.v1'
atype_diagnosis = 'openEHR-EHR-EVALUATION.problem-diagnosis.v1'
field = 'at0002.1'
male_controls = []
male_affected = []
female_controls = []
female_affected = []
self.logger.debug('reference_disease: %s' % args.reference_disease)
for i in individuals:
if tech:
v = dt.get_connected(i, tech)
if not v:
continue
ehr = self.kb.get_ehr(i)
self.logger.debug('ehr: %s' % ehr.recs)
if ehr.matches(atype_control):
if i.gender == self.kb.Gender.MALE:
male_controls.append(i)
else:
female_controls.append(i)
elif ehr.matches(atype_diagnosis, field, args.reference_disease):
if i.gender == self.kb.Gender.MALE:
male_affected.append(i)
else:
female_affected.append(i)
# TODO add checks for round-off effects
total_affected = int((1.0 - args.control_fraction) * args.total_number)
total_male_affected = int(total_affected * args.male_fraction)
total_female_affected = int(total_affected *
(1.0 - args.male_fraction))
total_controls = int(args.control_fraction * args.total_number)
total_male_controls = int(total_controls * args.male_fraction)
total_female_controls = int(total_controls *
(1.0 - args.male_fraction))
if total_male_affected > len(male_affected):
self.__critical('Requested %d affected males out of %d' %
(total_male_affected, len(male_affected)))
if total_female_affected > len(female_affected):
self.__critical('Requested %d affected females out of %d' %
(total_female_affected, len(female_affected)))
if total_male_controls > len(male_controls):
self.__critical('Requested %d controls males out of %d' %
(total_male_controls, len(male_controls)))
if total_female_controls > len(female_controls):
self.__critical('Requested %d controls females out of %d' %
(total_female_controls, len(female_controls)))
s_male_controls = random.sample(male_controls, total_male_controls)
self.logger.info('selected %d male controls out of %d' %
(len(s_male_controls), len(male_controls)))
s_female_controls = random.sample(female_controls,
total_female_controls)
self.logger.info('selected %d female controls out of %d' %
(len(s_female_controls), len(female_controls)))
s_male_affected = random.sample(male_affected, total_male_affected)
self.logger.info('selected %d male affected out of %d' %
(len(s_male_affected), len(male_affected)))
s_female_affected = random.sample(female_affected,
total_female_affected)
self.logger.info('selected %d female affected out of %d' %
(len(s_female_affected), len(female_affected)))
all_individuals = (s_male_controls + s_female_controls +
s_male_affected + s_female_affected)
for i, indy in enumerate(all_individuals):
ots.writerow({
'group': args.group_label,
'group_code': 'I%04d' % i,
'individual': indy.id,
})
def update_dependency_tree(self):
self.dt = DependencyTree(self)
