PySDM_examples.Pyrcel.simulation

  1import numpy as np
  2from PySDM_examples.utils import BasicSimulation
  3
  4from PySDM import Builder
  5from PySDM.backends import CPU
  6from PySDM.backends.impl_numba.test_helpers import scipy_ode_condensation_solver
  7from PySDM.dynamics import AmbientThermodynamics, Condensation
  8from PySDM.environments import Parcel
  9from PySDM.initialisation.hygroscopic_equilibrium import equilibrate_wet_radii
 10from PySDM.initialisation.sampling.spectral_sampling import ConstantMultiplicity
 11from PySDM.physics import si
 12
 13
 14class Simulation(BasicSimulation):
 15    def __init__(
 16        self,
 17        settings,
 18        *,
 19        products=None,
 20        scipy_solver=False,
 21        rtol_thd=1e-10,
 22        rtol_x=1e-10,
 23        mass_of_dry_air=44 * si.kg,
 24        additional_attributes=None,
 25    ):
 26        n_sd = sum(settings.n_sd_per_mode)
 27        builder = Builder(
 28            n_sd=n_sd,
 29            backend=CPU(
 30                formulae=settings.formulae, override_jit_flags={"parallel": False}
 31            ),
 32            environment=Parcel(
 33                dt=settings.timestep,
 34                p0=settings.initial_pressure,
 35                initial_water_vapour_mixing_ratio=settings.initial_vapour_mixing_ratio,
 36                T0=settings.initial_temperature,
 37                w=settings.vertical_velocity,
 38                mass_of_dry_air=mass_of_dry_air,
 39            ),
 40            dynamics=(
 41                AmbientThermodynamics(),
 42                Condensation(rtol_thd=rtol_thd, rtol_x=rtol_x),
 43            ),
 44        )
 45        if additional_attributes is not None:
 46            for attribute in additional_attributes:
 47                builder.request_attribute(attribute)
 48
 49        volume = (
 50            builder.particulator.environment.mass_of_dry_air
 51            / settings.initial_air_density
 52        )
 53        attributes = {
 54            k: np.empty(0)
 55            for k in ("dry volume", "kappa times dry volume", "multiplicity")
 56        }
 57        for i, (kappa, spectrum) in enumerate(settings.aerosol_modes_by_kappa.items()):
 58            sampling = ConstantMultiplicity(spectrum)
 59            r_dry, n_per_volume = sampling.sample_deterministic(
 60                settings.n_sd_per_mode[i]
 61            )
 62            v_dry = settings.formulae.trivia.volume(radius=r_dry)
 63            attributes["multiplicity"] = np.append(
 64                attributes["multiplicity"], n_per_volume * volume
 65            )
 66            attributes["dry volume"] = np.append(attributes["dry volume"], v_dry)
 67            attributes["kappa times dry volume"] = np.append(
 68                attributes["kappa times dry volume"], v_dry * kappa
 69            )
 70        r_wet = equilibrate_wet_radii(
 71            r_dry=settings.formulae.trivia.radius(volume=attributes["dry volume"]),
 72            environment=builder.particulator.environment,
 73            kappa_times_dry_volume=attributes["kappa times dry volume"],
 74        )
 75        attributes["volume"] = settings.formulae.trivia.volume(radius=r_wet)
 76
 77        super().__init__(
 78            particulator=builder.build(attributes=attributes, products=products)
 79        )
 80        if scipy_solver:
 81            scipy_ode_condensation_solver.patch_particulator(self.particulator)
 82
 83        self.output_attributes = {
 84            attr: tuple([] for _ in range(self.particulator.n_sd))
 85            for attr in ["volume"]
 86            + (list(additional_attributes) if additional_attributes is not None else [])
 87        }
 88        self.settings = settings
 89
 90        self.__sanity_checks(attributes, volume)
 91
 92    def __sanity_checks(self, attributes, volume):
 93        for attribute in attributes.values():
 94            assert attribute.shape[0] == self.particulator.n_sd
 95        np.testing.assert_approx_equal(
 96            sum(attributes["multiplicity"]) / volume,
 97            sum(
 98                mode.norm_factor
 99                for mode in self.settings.aerosol_modes_by_kappa.values()
100            ),
101            significant=4,
102        )
103
104    def _save(self, output):
105        for key, attr in self.output_attributes.items():
106            attr_data = self.particulator.attributes[key].to_ndarray()
107            for drop_id in range(self.particulator.n_sd):
108                attr[drop_id].append(attr_data[drop_id])
109        super()._save(output)
110
111    def run(self, observers=()):
112        for observer in observers:
113            self.particulator.observers.append(observer)
114        output_products = super()._run(
115            self.settings.nt, self.settings.steps_per_output_interval
116        )
117        return {"products": output_products, "attributes": self.output_attributes}