def create(self, name, point_dataset_id, coverage_dataset_ids,
user_id, unit_of_time, random_group, model_variable,
data_type, model_id, analysis_description,input_hash,
time_indicies):
"""Creates a new analysis object
Params:
name - Friendly name for the analysis
point_dataset_id - Id of dataset containing point data
coverage_dataset_ids - List of coverage dataset ids, which should be
in the format <id>_<column_name>
user_id - Who is creating this analysis?
unit_of_time - unit of time selected
random_group - additional input into the model
model_variable - the variable that is being modelled
data_type - data type of the variable
model_id - id of the model to be used to generate the results
analysis_description - a short string describing the analysis
input_hash - used to quickly identify a duplicate analysis in terms of inputs
time_indicies - if any columns in coverage datasets need time slicing, the index (i.e. the time slice)
to take will be stored against each relevant column in here
Returns:
ID of newly-inserted analysis
"""
with self.transaction_scope() as session:
analysis = Analysis()
analysis.name = name
analysis.run_by = user_id
analysis.viewable_by = user_id
analysis.point_data_dataset_id = int(point_dataset_id)
analysis.deleted = False
analysis.model_id = model_id
analysis.description = analysis_description
# Hook up the coverage datasets
for id in coverage_dataset_ids:
coverage_ds = AnalysisCoverageDataset()
# The coverage dataset 'ID' is actually a
# composite in the form <id>_<column-name>
ds_id, column_name = id.split('_')
id_as_int = int(ds_id)
coverage_ds.dataset_id = id_as_int
col = AnalysisCoverageDatasetColumn()
# Check to see if we need to record a time index against
# this column, will be used for time-slicing later
if id in time_indicies:
col.time_index = time_indicies[id]
col.column = column_name
coverage_ds.columns.append(col)
analysis.coverage_datasets.append(coverage_ds)
# Parameters that are used in the analysis
analysis.unit_of_time = unit_of_time
analysis.random_group = random_group
analysis.model_variable = model_variable
analysis.data_type = data_type
# Hash of input values for future comparison
analysis.input_hash = input_hash
session.add(analysis)
# Flush and refresh to give us the generated ID for this new analysis
session.flush([analysis])
session.refresh(analysis)
return analysis.id
