impact-calculations/generate/loadmodels.py at 8bcd1e128b1b43fd53acace9ef3689c53429bc3e · ClimateImpactLab/impact-calculations · GitHub

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import numpy as np
from . import weather
from adaptation import covariates

do_econ_model_only = None
do_econ_scenario_only = None #{'rcp45': ['SSP4', 'SSP1'], 'rcp85': ['SSP4', 'SSP3']}
do_clim_scenario_only = None

single_clim_model = 'CCSM4'
single_clim_scenario = 'rcp85'
single_econ_model = 'high'
single_econ_scenario = 'SSP3'

def single(bundle_iterator):
    allecons = []
    for econ_model, econ_scenario, economicmodel in covariates.iterate_econmodels():
        allecons.append((econ_scenario, econ_model, economicmodel))

    assert allecons, "Cannot find economic models."

    allclims = []
    for clim_scenario, clim_model, weatherbundle in bundle_iterator:
        allclims.append((clim_scenario, clim_model, weatherbundle))

    assert allclims, "Cannot find climate models."

    allexogenous = []
    for econ_scenario, econ_model, economicmodel in allecons:
        for clim_scenario, clim_model, weatherbundle in allclims:
            if clim_scenario != single_clim_scenario or clim_model != single_clim_model:
                continue
            if single_econ_scenario is not None:
                if econ_scenario[:4] == single_econ_scenario and econ_model == single_econ_model:
                    return clim_scenario, clim_model, weatherbundle, econ_scenario, econ_model, economicmodel
                continue

            if (do_econ_scenario_only is not None and econ_scenario[0:4] != do_econ_scenario_only[clim_scenario][0]) or (do_econ_model_only is not None and econ_model != do_econ_model_only[0]):
                continue

            return clim_scenario, clim_model, weatherbundle, econ_scenario, econ_model, economicmodel

    assert False, "Could not find an appropriate single model."

def random_order(bundle_iterator, config=None):
    if config is None:
        config = {}
    mydo_econ_scenario_only = config.get('ssp', config.get('only-ssp', do_econ_scenario_only))
    mydo_clim_scenario_only = config.get('rcp', config.get('only-rcp', do_clim_scenario_only))
    mydo_econ_model_only = config.get('iam', config.get('only-iam', do_econ_model_only))

    print("Loading models...")
    allecons = []
    for econ_model, econ_scenario, economicmodel in covariates.iterate_econmodels(config):
        allecons.append((econ_scenario, econ_model, economicmodel))

    allclims = []
    for clim_scenario, clim_model, weatherbundle in bundle_iterator:
        allclims.append((clim_scenario, clim_model, weatherbundle))

    allexogenous = []
    for econ_scenario, econ_model, economicmodel in allecons:
        for clim_scenario, clim_model, weatherbundle in allclims:
            # Drop PIK GDP-32 (it's USA-only)
            if econ_model == 'PIK GDP-32':
                continue
            if mydo_econ_model_only is not None and econ_model not in mydo_econ_model_only:
                continue
            if mydo_econ_scenario_only is not None and econ_scenario[0:4] not in mydo_econ_scenario_only:
                continue

            if mydo_clim_scenario_only is not None and clim_scenario not in mydo_clim_scenario_only:
                continue

            ## By default, we drop SSP1/RCP8.5 and all of SSP5 except SSP5/RCP8.5.
            ## These are allowed only if they are explicitly requested.
            # Drop SSP1 with RCP 8.5
            if econ_scenario[:4] == 'SSP1' and clim_scenario == 'rcp85':
                if mydo_econ_scenario_only != 'SSP1' or mydo_clim_scenario_only != 'rcp85': # Don't stop if requested
                    continue
            # Drop SSP5 except with RCP 8.5
            if econ_scenario[:4] == 'SSP5' and clim_scenario != 'rcp85':
                if mydo_econ_scenario_only != 'SSP5' or mydo_clim_scenario_only != clim_scenario: # Don't stop if requested
                    continue

            allexogen = (clim_scenario, clim_model, weatherbundle, econ_scenario, econ_model, economicmodel)
            allexogenous.append(allexogen)

    allexogenous = np.random.permutation(allexogenous)
    for clim_scenario, clim_model, weatherbundle, econ_scenario, econ_model, economicmodel in allexogenous:
        print(clim_scenario, clim_model, econ_scenario, econ_model)
        yield clim_scenario, clim_model, weatherbundle, econ_scenario, econ_model, economicmodel