less crazy test values for T and S

open-atmos · claresinger · Nov 27, 2024 · Dec 19, 2024 · Dec 20, 2024 · Jan 6, 2025
commit 12b55dd3753d4b4c4d780c777510c46a87a1d0e8
diff --git a/tests/unit_tests/physics/test_homogeneous_liquid_nucleation.py b/tests/unit_tests/physics/test_homogeneous_liquid_nucleation.py
@@ -106,10 +106,10 @@ def test_units(formulae_factory, check):
             # act & assert
             if check == "j":
                 assert sut.j_liq_homo(
-                    T=1 * si.K, S=1 * si.dimensionless, e_s=1 * si.Pa
+                    T=300 * si.K, S=2 * si.dimensionless, e_s=600 * si.Pa
                 ).check("[frequency] / [volume]")
             elif check == "r":
-                assert sut.r_liq_homo(T=1 * si.K, S=1 * si.dimensionless).check(
+                assert sut.r_liq_homo(T=300 * si.K, S=2 * si.dimensionless).check(
                     "[length]"
                 )
             else:

diff --git a/PySDM/dynamics/homogeneous_liquid_nucleation.py b/PySDM/dynamics/homogeneous_liquid_nucleation.py
 @register_dynamic()
 class HomogeneousLiquidNucleation(SuperParticleSpawningDynamic):
    def __init__(self):
        self.particulator = None
        self.formulae = None
        self.index = None

    def register(self, builder):
        self.particulator = builder.particulator
        self.formulae = builder.formulae
        self.index = self.particulator.Index.identity_index(1)

    def __call__(self):
        env = {
            k: self.particulator.environment[k].to_ndarray()[0] for k in ("T", "RH")
        }  # TODO #1492: >0D

        if env["RH"] < 1:
            return

        e_s = self.formulae.saturation_vapour_pressure.pvs_water(env["T"])
        j = self.formulae.homogeneous_liquid_nucleation_rate.j_liq_homo(
            env["T"], env["RH"], e_s
        )

        # TODO #1492: take care of cases where round yields zero -> MC sampling?
        new_sd_multiplicity = round(
            j * self.particulator.environment.mesh.dv * self.particulator.dt
        )

        if new_sd_multiplicity > 0:
            r_wet = self.formulae.homogeneous_liquid_nucleation_rate.r_liq_homo(
                env["T"], env["RH"]
            )
            v_wet = self.formulae.trivia.volume(radius=r_wet)
            new_sd_extensive_attributes = {
                "water mass": (v_wet * self.formulae.constants.rho_w,),
                "dry volume": (0,),
                "kappa times dry volume": (0,),
            }

            # TODO #1492: to be done once, not every time we spawn
            self.check_extensive_attribute_keys(
                particulator_attributes=self.particulator.attributes,
                spawned_attributes=new_sd_extensive_attributes,
            )

            # TODO #1492: allocate once, reuse
            new_sd_extensive_attributes = self.particulator.IndexedStorage.from_ndarray(
                self.index,
                np.asarray(list(new_sd_extensive_attributes.values())),
            )
            # TODO #1492: ditto
            new_sd_multiplicity = self.particulator.IndexedStorage.from_ndarray(
                self.index,
                np.asarray((new_sd_multiplicity,), dtype=np.int64),
            )

            self.particulator.spawn(
                spawned_particle_index=self.index,
                number_of_super_particles_to_spawn=1,
                spawned_particle_multiplicity=new_sd_multiplicity,
diff --git a/PySDM/environments/expansion_chamber.py b/PySDM/environments/expansion_chamber.py
    def advance_moist_vars(self):
        """compute new values of dry density and thd, and write them to self._tmp and self["thd"]
        assuming water-vapour mixing ratio is not altered by the expansion"""
        dt = self.particulator.dt
        t_new = (self.particulator.n_steps + 1) * dt
        if t_new > self.delta_time:
            return

        formulae = self.particulator.formulae
        p_new = self["p"][0] + self.dp_dt * dt
        vapour_mixing_ratio = self["water_vapour_mixing_ratio"][0]
        gg = (
            1 - formulae.adiabatic_exponent.gamma(vapour_mixing_ratio)
        ) / formulae.adiabatic_exponent.gamma(vapour_mixing_ratio)
        T_new = self.initial_temperature * (self.initial_pressure / p_new) ** gg
        wvmr_new = self._tmp["water_vapour_mixing_ratio"][
            0
        ]  # TODO #1492 - should _tmp or self[] be used?
        pv_new = wvmr_new * p_new / (wvmr_new + formulae.constants.eps)
        pd_new = p_new - pv_new

        self._tmp["rhod"][:] = pd_new / T_new / formulae.constants.Rd
        self["thd"][:] = formulae.trivia.th_std(p=pd_new, T=T_new)

    def sync_moist_vars(self):
        for var in self.variables:
diff --git a/PySDM/environments/impl/moist_lagrangian.py b/PySDM/environments/impl/moist_lagrangian.py
        self.notify()

    def sync_moist_vars(self):
        raise NotImplementedError()

    def advance_moist_vars(self):
        raise NotImplementedError()
diff --git a/PySDM/physics/adiabatic_exponent/dry.py b/PySDM/physics/adiabatic_exponent/dry.py

    @staticmethod
    def gamma(const, qv):  # pylint: disable=unused-argument
        return 1 + const.Rd / const.c_vd
diff --git a/PySDM/physics/adiabatic_exponent/moist_leading_terms.py b/PySDM/physics/adiabatic_exponent/moist_leading_terms.py

 class MoistLeadingTerms:  # pylint: disable=too-few-public-methods
    def __init__(self, _):
        pass

    @staticmethod
    def gamma(const, vapour_mixing_ratio):
        return (
            1
            + const.Rd / const.c_vd
            + (const.Rv * vapour_mixing_ratio)
	@register_dynamic()
	class HomogeneousLiquidNucleation(SuperParticleSpawningDynamic):
	def __init__(self):
	self.particulator = None
	self.formulae = None
	self.index = None
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	def register(self, builder):
	self.particulator = builder.particulator
	self.formulae = builder.formulae
	self.index = self.particulator.Index.identity_index(1)
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	def __call__(self):
	env = {
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	k: self.particulator.environment[k].to_ndarray()[0] for k in ("T", "RH")
	} # TODO #1492: >0D

	if env["RH"] < 1:
	return
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	e_s = self.formulae.saturation_vapour_pressure.pvs_water(env["T"])
	j = self.formulae.homogeneous_liquid_nucleation_rate.j_liq_homo(
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	env["T"], env["RH"], e_s
	)

	# TODO #1492: take care of cases where round yields zero -> MC sampling?
	new_sd_multiplicity = round(
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	j * self.particulator.environment.mesh.dv * self.particulator.dt
	)

	if new_sd_multiplicity > 0:
	r_wet = self.formulae.homogeneous_liquid_nucleation_rate.r_liq_homo(
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	env["T"], env["RH"]
	)
	v_wet = self.formulae.trivia.volume(radius=r_wet)
	new_sd_extensive_attributes = {
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	"water mass": (v_wet * self.formulae.constants.rho_w,),
	"dry volume": (0,),
	"kappa times dry volume": (0,),
	}

	# TODO #1492: to be done once, not every time we spawn
	self.check_extensive_attribute_keys(
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	particulator_attributes=self.particulator.attributes,
	spawned_attributes=new_sd_extensive_attributes,
	)

	# TODO #1492: allocate once, reuse
	new_sd_extensive_attributes = self.particulator.IndexedStorage.from_ndarray(
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	self.index,
	np.asarray(list(new_sd_extensive_attributes.values())),
	)
	# TODO #1492: ditto
	new_sd_multiplicity = self.particulator.IndexedStorage.from_ndarray(
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	self.index,
	np.asarray((new_sd_multiplicity,), dtype=np.int64),
	)

	self.particulator.spawn(
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	spawned_particle_index=self.index,
	number_of_super_particles_to_spawn=1,
	spawned_particle_multiplicity=new_sd_multiplicity,
	def advance_moist_vars(self):
	"""compute new values of dry density and thd, and write them to self._tmp and self["thd"]
	assuming water-vapour mixing ratio is not altered by the expansion"""
	dt = self.particulator.dt
	t_new = (self.particulator.n_steps + 1) * dt
	if t_new > self.delta_time:
	return
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	formulae = self.particulator.formulae
	p_new = self["p"][0] + self.dp_dt * dt
	vapour_mixing_ratio = self["water_vapour_mixing_ratio"][0]
	gg = (
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	1 - formulae.adiabatic_exponent.gamma(vapour_mixing_ratio)
	) / formulae.adiabatic_exponent.gamma(vapour_mixing_ratio)
	T_new = self.initial_temperature * (self.initial_pressure / p_new) ** gg
	wvmr_new = self._tmp["water_vapour_mixing_ratio"][
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	0
	] # TODO #1492 - should _tmp or self[] be used?
	pv_new = wvmr_new * p_new / (wvmr_new + formulae.constants.eps)
	pd_new = p_new - pv_new
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	self._tmp["rhod"][:] = pd_new / T_new / formulae.constants.Rd
	self["thd"][:] = formulae.trivia.th_std(p=pd_new, T=T_new)
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	def sync_moist_vars(self):
	for var in self.variables:
	self.notify()

	def sync_moist_vars(self):
	raise NotImplementedError()
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	def advance_moist_vars(self):
	raise NotImplementedError()
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	@staticmethod
	def gamma(const, qv): # pylint: disable=unused-argument
	return 1 + const.Rd / const.c_vd
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	class MoistLeadingTerms: # pylint: disable=too-few-public-methods
	def __init__(self, _):
	pass
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	@staticmethod
	def gamma(const, vapour_mixing_ratio):
	return (
Check warning on line 12 in PySDM/physics/adiabatic_exponent/moist_leading_terms.py Codecov / codecov/patch PySDM/physics/adiabatic_exponent/moist_leading_terms.py#L12 `Added line #L12 was not covered by tests`
	1
	+ const.Rd / const.c_vd
	+ (const.Rv * vapour_mixing_ratio)