from .base import _DatabaseCruncher
from .interpolation import Interpolation
[docs]class ScenarioAndModelSpecificInterpolate(_DatabaseCruncher):
"""
Database cruncher which pre-filters to only use data from specific scenarios, then
runs the interpolation cruncher to return values from that set of scenarios. See the
documentation of Interpolation for more details.
"""
[docs] def derive_relationship(
self,
variable_follower,
variable_leaders,
required_scenario="*",
required_model="*",
interpkind="linear",
):
"""
Derive the relationship between two variables from the database.
Parameters
----------
variable_follower : str
The variable for which we want to calculate timeseries (e.g.
``"Emissions|CH4"``).
variable_leaders : list[str]
The variable(s) we want to use in order to infer timeseries of
``variable_follower`` (e.g. ``["Emissions|CO2"]``).
required_scenario : str or list[str]
The string(s) which all relevant scenarios are required to match. This may
have *s to represent wild cards. It defaults to "*" to accept all scenarios.
required_model : str or list[str]
The string(s) which all relevant models are required to match. This may have
*s to represent wild cards. It defaults to "*" to accept all models.
interpkind : str
The style of interpolation. By default, linear, but can
also be any value accepted as the "kind" option in
scipy.interpolate.interp1d, or "PchipInterpolator", in which case
scipy.interpolate.PchipInterpolator is used. Care should be taken if using
non-default interp1d options, as they are either uneven or have "ringing"
Returns
-------
:obj:`func`
Function which takes a :obj:`pyam.IamDataFrame` containing
``variable_leaders`` timeseries and returns timeseries for
``variable_follower`` based on the derived relationship between the two.
Please see the source code for the exact definition (and docstring) of the
returned function.
Raises
------
ValueError
There is no data of the appropriate type in the database.
There may be a typo in the SSP option.
"""
use_db = self._db.filter(scenario=required_scenario, model=required_model)
if use_db.data.empty:
raise ValueError(
"There is no data of the appropriate type in the database."
" There may be a typo in the SSP option."
)
cruncher = Interpolation(use_db)
return cruncher.derive_relationship(
variable_follower, variable_leaders, interpkind=interpkind
)