def _get_data_rows(self):
rows = []
for obj in self.queryset:
ser = obj.get_json(json_encode=False)
row = []
row.extend(
Study.flat_complete_data_row(ser['study_population']['study']))
row.extend(
models.StudyPopulation.flat_complete_data_row(
ser['study_population']))
row.extend(models.Outcome.flat_complete_data_row(ser))
for res in ser['results']:
row_copy = list(row)
row_copy.extend(
models.Exposure.flat_complete_data_row(
res["comparison_set"]["exposure"]))
row_copy.extend(
models.ComparisonSet.flat_complete_data_row(
res["comparison_set"]))
row_copy.extend(models.Result.flat_complete_data_row(res))
for rg in res['results']:
row_copy2 = list(row_copy)
row_copy2.extend(
models.Group.flat_complete_data_row(rg["group"]))
row_copy2.extend(
models.GroupResult.flat_complete_data_row(rg))
rows.append(row_copy2)
return rows
def _get_data_rows(self):
rows = []
for obj in self.queryset:
ser = obj.get_json(json_encode=False)
row = []
row.extend(
Study.flat_complete_data_row(
ser['animal_group']['experiment']['study']))
row.extend(
models.Experiment.flat_complete_data_row(
ser['animal_group']['experiment']))
row.extend(
models.AnimalGroup.flat_complete_data_row(ser['animal_group']))
row.extend(
models.DosingRegime.flat_complete_data_row(
ser['animal_group']['dosing_regime']))
row.extend(models.Endpoint.flat_complete_data_row(ser))
for i, eg in enumerate(ser['endpoint_group']):
row_copy = copy(row)
row_copy.extend(
models.DoseGroup.flat_complete_data_row(
ser['animal_group']['dosing_regime']['doses'],
self.doses, i))
row_copy.extend(
models.EndpointGroup.flat_complete_data_row(eg, ser))
rows.append(row_copy)
return rows
def _get_data_rows(self):
rows = []
for obj in self.queryset:
ser = obj.get_json(json_encode=False)
row = []
row.extend(Study.flat_complete_data_row(ser['exposure']['study_population']['study']))
row.extend(models.StudyPopulation.flat_complete_data_row(ser['exposure']['study_population']))
row.extend(models.Exposure.flat_complete_data_row(ser['exposure']))
row.extend(models.AssessedOutcome.flat_complete_data_row(ser))
# build a row for each aog
for aog in ser['groups']:
row_copy = list(row) # clone
row_copy.extend(models.AssessedOutcomeGroup.flat_complete_data_row(aog))
rows.append(row_copy)
return rows
def _get_data_rows(self):
rows = []
for obj in self.queryset:
ser = obj.get_json(json_encode=False)
row = []
row.extend(Study.flat_complete_data_row(ser))
for rob in ser.get('riskofbiases', []):
rob_data = models.RiskOfBias.flat_complete_data_row(rob)
for score in rob['scores']:
row_copy = list(row)
row_copy.extend(
models.RiskOfBiasScore.flat_complete_data_row(score))
row_copy.extend(rob_data)
rows.append(row_copy)
return rows
def _get_data_rows(self):
rows = []
for obj in self.queryset:
ser = obj.get_json(json_encode=False)
row = []
row.extend(Study.flat_complete_data_row(ser['animal_group']['experiment']['study']))
row.extend(models.Experiment.flat_complete_data_row(ser['animal_group']['experiment']))
row.extend(models.AnimalGroup.flat_complete_data_row(ser['animal_group']))
row.extend(models.DosingRegime.flat_complete_data_row(ser['animal_group']['dosing_regime']))
row.extend(models.Endpoint.flat_complete_data_row(ser))
for i, eg in enumerate(ser['groups']):
row_copy = copy(row)
row_copy.extend(models.DoseGroup.flat_complete_data_row(
ser['animal_group']['dosing_regime']['doses'],
self.doses, i))
row_copy.extend(models.EndpointGroup.flat_complete_data_row(eg, ser))
rows.append(row_copy)
return rows
def _get_data_rows(self):
rows = []
for obj in self.queryset:
ser = obj.get_json(json_encode=False)
row = []
row.extend(Study.flat_complete_data_row(ser['protocol']['study']))
row.extend(models.MetaProtocol.flat_complete_data_row(ser['protocol']))
row.extend(models.MetaResult.flat_complete_data_row(ser))
if len(ser['single_results'])==0:
# print one-row with no single-results
rows.append(row)
else:
# print each single-result as a new row
for sr in ser['single_results']:
row_copy = list(row) # clone
row_copy.extend(models.SingleResult.flat_complete_data_row(sr))
rows.append(row_copy)
return rows
def _get_data_rows(self):
rows = []
for obj in self.queryset:
ser = obj.get_json(json_encode=False)
row = []
row.extend(Study.flat_complete_data_row(ser['study_population']['study']))
row.extend(models.StudyPopulation.flat_complete_data_row(ser['study_population']))
row.extend(models.Outcome.flat_complete_data_row(ser))
for res in ser['results']:
row_copy = list(row)
row_copy.extend(models.Exposure.flat_complete_data_row(res["comparison_set"]["exposure"]))
row_copy.extend(models.ComparisonSet.flat_complete_data_row(res["comparison_set"]))
row_copy.extend(models.Result.flat_complete_data_row(res))
for rg in res['results']:
row_copy2 = list(row_copy)
row_copy2.extend(models.Group.flat_complete_data_row(rg["group"]))
row_copy2.extend(models.GroupResult.flat_complete_data_row(rg))
rows.append(row_copy2)
return rows
def _get_data_rows(self):
rows = []
for obj in self.queryset:
ser = obj.get_json(json_encode=False)
row = []
row.extend(
Study.flat_complete_data_row(
ser['exposure']['study_population']['study']))
row.extend(
models.StudyPopulation.flat_complete_data_row(
ser['exposure']['study_population']))
row.extend(models.Exposure.flat_complete_data_row(ser['exposure']))
row.extend(models.AssessedOutcome.flat_complete_data_row(ser))
# build a row for each aog
for aog in ser['groups']:
row_copy = list(row) # clone
row_copy.extend(
models.AssessedOutcomeGroup.flat_complete_data_row(aog))
rows.append(row_copy)
return rows
def _get_data_rows(self):
rows = []
for obj in self.queryset:
ser = obj.get_json(json_encode=False)
row = []
row.extend(Study.flat_complete_data_row(ser['protocol']['study']))
row.extend(
models.MetaProtocol.flat_complete_data_row(ser['protocol']))
row.extend(models.MetaResult.flat_complete_data_row(ser))
if len(ser['single_results']) == 0:
# print one-row with no single-results
rows.append(row)
else:
# print each single-result as a new row
for sr in ser['single_results']:
row_copy = list(row) # clone
row_copy.extend(
models.SingleResult.flat_complete_data_row(sr))
rows.append(row_copy)
return rows
def _get_data_rows(self):
rows = []
for obj in self.queryset:
ser = obj.get_json(json_encode=False)
row = []
row.extend(Study.flat_complete_data_row(ser))
try:
scores = [
rob['scores'] for rob in ser.get('riskofbiases', [])
if rob['final'] and rob['active']
][0]
except IndexError:
scores = []
for score in scores:
row_copy = list(row) # clone
row_copy.extend(
models.RiskOfBiasScore.flat_complete_data_row(score))
rows.append(row_copy)
return rows
