def timeseries(inputs, period=None, extent=None, **kwds):
'''
Inputs is a variable or group of variables
If extent is larger than a single cell, variables
will be aggregated using their default method
'''
inputs = _sanitize_inputs(inputs)
if period is None:
period = inputs.source.period
else:
period = _sanitize_period(period, inputs.source.period.freq)
if extent is None:
extent = inputs.source.extent
vg_dict = _dd()
for v in inputs:
data = _spatial_aggregate(v, period, extent)
vg_dict.add_item(
_od(period=period,
_data=data,
units=v.units,
extent=extent,
method='mean',
variable=v.name,
source=v.source))
layout = _layout.SpatialAggregateLayout(**kwds)
gridview = layout.generate_view(vg_dict)
gridview.draw()
return gridview
def _plot_spatial_multi(var_group, period, extent=None, **kwds):
if not extent:
extent = var_group.source.extent
vg_dict = _dd()
for v in var_group:
aggregator = _sanitize_aggregate_method(v)
data = aggregator(v, period, extent)
vg_dict.add_query_item([ROW_FIELD, COLUMN_FIELD],
_od(period=period,
_data=data,
units=v.units,
extent=extent,
variable=v.name,
source=v.source))
layout = _layout.DefaultSpatialGridLayout(ROW_FIELD, COLUMN_FIELD, **kwds)
gridview = layout.generate_view(vg_dict)
gridview.draw()
return gridview