def get_reagent_columns(dataset_id):
col_field_info = {}
for fi in FieldInformation.objects.all().filter(
table__in=['smallmolecule','protein','cell','antibody','otherreagent',
'smallmoleculebatch','proteinbatch','cellbatch','antibodybatch','otherreagentbatch']):
col_field_info[fi.get_camel_case_dwg_name()] = {
'reagentType': fi.table,
'dwgName': fi.dwg_field_name,
'description': fi.description
}
data_columns = ( DataColumn.objects.filter(dataset_id=dataset_id)
.filter(data_type__in=[
'small_molecule','cell','protein','antibody','otherreagent']) )
reagent_fields = OrderedDict()
meta_field_info = get_listing(DataColumn(),['datacolumn'])
for dc in data_columns.order_by('display_order'):
specific_name = dc.name
field_schema = {}
for item in meta_field_info.items():
meta_fi_attr = item[0]
meta_fi = item[1]['fieldinformation']
field_schema[meta_fi.get_camel_case_dwg_name()] = (
getattr(dc,meta_fi_attr) )
reagent_fields[specific_name] = field_schema
reagent_fields[specific_name]['columns'] = {}
for dwg_name in DataSetDataResource2.datapoint_cols[dc.data_type]:
col_name = '%s_%s' % (specific_name,dwg_name)
reagent_fields[specific_name]['columns'][col_name] = col_field_info.get(dwg_name, {})
return reagent_fields
def get_datapoint_fields(dataset_id):
data_columns = ( DataColumn.objects.filter(dataset_id=dataset_id)
.exclude(data_type__in=[
'small_molecule','cell','protein','antibody','otherreagent',
'omero_image'])
.exclude(unit__in=['day','hour','minute','second']) )
datapoint_fields = OrderedDict()
meta_field_info = get_listing(DataColumn(),['datacolumn'])
for dc in data_columns.order_by('display_order'):
specific_name = dc.name
field_schema = {}
for item in meta_field_info.items():
meta_fi_attr = item[0]
meta_fi = item[1]['fieldinformation']
field_schema[meta_fi.get_camel_case_dwg_name()] = (
getattr(dc,meta_fi_attr) )
datapoint_fields[specific_name] = field_schema
return datapoint_fields
dataset = DataSet(**metadata)
logger.info('dataset to save %s' % dataset)
dataset.save()
logger.debug('read data columns...')
col_to_definitions = read_datacolumns(book)
small_molecule_col = None
col_to_dc_map = {}
for i, dc_definition in enumerate(col_to_definitions):
dc_definition['dataset'] = dataset
if (not 'display_order' in dc_definition
or dc_definition['display_order'] == None):
dc_definition['display_order'] = i
datacolumn = DataColumn(**dc_definition)
datacolumn.save()
if not small_molecule_col and datacolumn.data_type == 'small_molecule':
small_molecule_col = datacolumn
logger.debug('datacolumn created: %r' % datacolumn)
if datacolumn.worksheet_column:
col_to_dc_map[int_for_col(
datacolumn.worksheet_column)] = datacolumn
logger.debug('final data columns: %s' % col_to_dc_map)
logger.debug('read the Data sheet')
data_sheet = book.sheet_by_name('Data')
for i, label in enumerate(data_sheet.row_values(0)):
logger.debug('find datasheet label %r:%r' % (colname(i), label))
if label in meta_columns:
