spaemis.scaling.timeseries

Proxy scaler

A proxy scaler uses a proxy (a 2d pattern) to disaggregate an emissions timeseries over a target area.

The proxy must cover the area of interest of the emissions timeseries

TimeseriesScaler

class TimeseriesScaler(proxy, proxy_region, source_timeseries, source_filters)

Bases: BaseScaler

Scale a spatial pattern using a timeseries

classmethod create_from_config(method)

Create Scaler from configuration

Return type:

spaemis.scaling.timeseries.TimeseriesScaler

get_timeseries_point

get_timeseries_point(timeseries, source, filters, target_year)

Extract a single value according to some filters

Parameters:

• timeseries (dict[str, scmdata.run.ScmRun]) – Collection of loaded timeseries

• source (str) – Timeseries name

• filters (list[dict[str, str]]) –

  Filter to apply to the selected timeseries

  These filters if applied must result in a single remaining timeseries otherwise a ValueError will be raised.

• target_year (int) –

  Year to extract

  Must be contained in the targeted timeseries

Raises:

ValueError – If the selected data cannot be retrieved

Returns:

scmdata.run.ScmRun – ScmRun with a containing a single timeseries and year.

This object will retain the metadata of the filtered timeseries

apply_amount

apply_amount(amount, unit, proxy)

Scale a known amount of emissions across a proxy

Parameters:

• amount (float) –

  Amount of stuff to allocate across the proxy

  The stuff is usually annual emissions of a given species and currently

• unit (str) –

  Unit of the stuff

  Must be able to be converted to a Pint unit with dimensions [X] * [mass] / [time] where X can be any dimension (typically CO2 or other species in the case of emissions)

• proxy (xarray.core.dataarray.DataArray) –

  Proxy array

  Can include nans and missing data

Returns:

xarray.core.dataarray.DataArray – DataArray with the same dimensions of proxy where the sum matches amount