def export_columns(cls, instances=[]):
# TODO: flip this to instead pass arguments to a factory on table.ColumnChoice
# only do ID and Name here, allow overrides to include e.g. metadata
return [
table.ColumnChoice(
cls, 'id', _('ID'), lambda x: x.id, heading=cls.__name__ + ' ID'),
table.ColumnChoice(
cls, 'name', _('Name'), lambda x: x.name, heading=cls.__name__ + ' Name'),
]
def export_columns(cls):
return [
table.ColumnChoice(
cls, 'type', _('Measurement Type'), lambda x: x.measurement_type.export_name()),
table.ColumnChoice(
cls, 'comp', _('Compartment'), lambda x: x.compartment_symbol),
table.ColumnChoice(
cls, 'mod', _('Measurement Updated'), lambda x: x.update_ref.mod_time),
table.ColumnChoice(
cls, 'x_units', _('X Units'),
lambda x: x.x_units.unit_name if x.x_units.display else ''),
table.ColumnChoice(
cls, 'y_units', _('Y Units'),
lambda x: x.y_units.unit_name if x.y_units.display else ''),
]
def get_column(self, **kwargs):
type_context = None
def lookup_format(instance, **kwargs):
return self.get_default() % self.get_format_dict(instance, **kwargs)
def lookup_meta(instance, **kwargs):
default = self.get_default() % kwargs
if instance:
return instance.metadata_get(self.meta_type, default=default)
return default
if self.meta_type:
type_context = self.meta_type.for_context
lookup = lookup_meta
else:
type_context = None
lookup = lookup_format
model = {
MetadataType.STUDY: Study,
MetadataType.LINE: Line,
MetadataType.ASSAY: Assay,
}.get(type_context, None)
return table.ColumnChoice(
model, "worklist_column_%s" % self.pk, str(self), lookup
)
def export_columns(cls, instances=[]):
return super(Study, cls).export_columns(instances) + [
table.ColumnChoice(cls,
'contact',
_('Contact'),
lambda x: x.get_contact(),
heading='Study Contact'),
]
def export_columns(cls, instances=[]):
types = MetadataType.all_types_on_instances(instances)
return super(Line, cls).export_columns(instances) + [
table.ColumnChoice(
cls, 'control', _('Control'), lambda x: 'T' if x.control else 'F'),
table.ColumnChoice(
# TODO export should handle multi-valued fields better than this
cls, 'strain', _('Strain'),
lambda x: '|'.join([s.name for s in x.strains.all()])),
table.ColumnChoice(
# TODO export should handle multi-valued fields better than this
cls, 'csource_name', _('Carbon Source'),
lambda x: '|'.join([c.name for c in x.carbon_source.all()])),
table.ColumnChoice(
# TODO export should handle multi-valued fields better than this
cls, 'csource_label', _('Carbon Labeling'),
lambda x: '|'.join([c.labeling for c in x.carbon_source.all()])),
table.ColumnChoice(
cls, 'experimenter', _('Experimenter'),
lambda x: x.experimenter.email if x.experimenter else '',
heading=_('Line Experimenter')),
table.ColumnChoice(
cls, 'contact', _('Contact'),
lambda x: x.contact.email if x.contact else '',
heading=_('Line Contact')),
] + [
table.ColumnChoice(
cls, 'meta.%s' % t.id, t.type_name,
lambda x: x.meta_store.get('%s' % t.id, ''))
for t in types
]
