def _micro_init(opts, state, info):
# sanity check
_stats(state, info)
if (state["RH"] > 1): raise Exception("Please supply initial T,p,r_v below supersaturation")
# using nested function to get access to opts
def lognormal(lnr):
from math import exp, log, sqrt, pi
return opts["n_tot"] * exp(
-(lnr - log(opts["mean_r"]))**2 / 2 / log(opts["gstdev"])**2
) / log(opts["gstdev"]) / sqrt(2*pi);
# lagrangian scheme options
opts_init = lgrngn.opts_init_t()
for opt in ["dt",]:
setattr(opts_init, opt, opts[opt])
opts_init.sd_conc = opts["sd_conc"]
opts_init.dry_distros = {opts["kappa"]:lognormal}
opts_init.kernel = lgrngn.kernel_t.geometric #TODO: will not be needed soon (libcloud PR #89)
opts_init.chem_rho = opts["chem_rho"]
# switch off sedimentation and collisions
opts_init.sedi_switch = False
opts_init.coal_switch = False
# switching on chemistry if either dissolving, dissociation or reactions are chosen
opts_init.chem_switch = False
if opts["chem_dsl"] or opts["chem_dsc"] or opts["chem_rct"]: opts_init.chem_switch = True
# initialisation
micro = lgrngn.factory(lgrngn.backend_t.serial, opts_init)
micro.init(state["th_d"], state["r_v"], state["rhod"])
return micro
def _micro_init(aerosol, opts, state, info):
# lagrangian scheme options
opts_init = lgrngn.opts_init_t()
for opt in ["dt", "sd_conc", "chem_rho", "sstp_cond"]:
setattr(opts_init, opt, opts[opt])
opts_init.n_sd_max = opts_init.sd_conc
# read in the initial aerosol size distribution
dry_distros = {}
for name, dct in aerosol.items(): # loop over kappas
lognormals = []
for i in range(len(dct["mean_r"])):
lognormals.append(
lognormal(dct["mean_r"][i], dct["gstdev"][i], dct["n_tot"][i]))
dry_distros[dct["kappa"]] = sum_of_lognormals(lognormals)
opts_init.dry_distros = dry_distros
# better resolution for the SD tail
if opts["large_tail"]:
opts_init.sd_conc_large_tail = 1
opts_init.n_sd_max = int(1e6) # some more space for the tail SDs
# switch off sedimentation and collisions
opts_init.sedi_switch = False
opts_init.coal_switch = False
# switching on chemistry if either dissolving, dissociation or reactions are chosen
opts_init.chem_switch = False
if opts["chem_dsl"] or opts["chem_dsc"] or opts["chem_rct"]:
opts_init.chem_switch = True
opts_init.sstp_chem = opts["sstp_chem"]
# initialisation
micro = lgrngn.factory(lgrngn.backend_t.serial, opts_init)
ambient_chem = {}
if micro.opts_init.chem_switch:
ambient_chem = dict((v, state[k]) for k, v in _Chem_g_id.items())
micro.init(state["th_d"],
state["r_v"],
state["rhod"],
ambient_chem=ambient_chem)
# sanity check
_stats(state, info)
if (state["RH"] > 1):
raise Exception("Please supply initial T,p,r_v below supersaturation")
return micro
def _micro_init(aerosol, opts, state, info):
# lagrangian scheme options
opts_init = lgrngn.opts_init_t()
for opt in ["dt", "sd_conc", "chem_rho", "sstp_cond"]:
setattr(opts_init, opt, opts[opt])
opts_init.n_sd_max = opts_init.sd_conc
# read in the initial aerosol size distribution
dry_distros = {}
for name, dct in aerosol.iteritems(): # loop over kappas
lognormals = []
for i in range(len(dct["mean_r"])):
lognormals.append(lognormal(dct["mean_r"][i], dct["gstdev"][i], dct["n_tot"][i]))
dry_distros[dct["kappa"]] = sum_of_lognormals(lognormals)
opts_init.dry_distros = dry_distros
# better resolution for the SD tail
if opts["large_tail"]:
opts_init.sd_conc_large_tail = 1
opts_init.n_sd_max = int(1e6) # some more space for the tail SDs
# switch off sedimentation and collisions
opts_init.sedi_switch = False
opts_init.coal_switch = False
# switching on chemistry if either dissolving, dissociation or reactions are chosen
opts_init.chem_switch = False
if opts["chem_dsl"] or opts["chem_dsc"] or opts["chem_rct"]:
opts_init.chem_switch = True
opts_init.sstp_chem = opts["sstp_chem"]
# initialisation
micro = lgrngn.factory(lgrngn.backend_t.serial, opts_init)
ambient_chem = {}
if micro.opts_init.chem_switch:
ambient_chem = dict((v, state[k]) for k,v in _Chem_g_id.iteritems())
micro.init(state["th_d"], state["r_v"], state["rhod"], ambient_chem=ambient_chem)
# sanity check
_stats(state, info)
if (state["RH"] > 1): raise Exception("Please supply initial T,p,r_v below supersaturation")
return micro
def _micro_init(opts, state, info):
# sanity check
_stats(state, info)
if (state["RH"] > 1): raise Exception("Please supply initial T,p,r_v below supersaturation")
# using nested function to get access to opts
def lognormal(lnr):
from math import exp, log, sqrt, pi
return opts["n_tot"] * exp(
-(lnr - log(opts["mean_r"]))**2 / 2 / log(opts["gstdev"])**2
) / log(opts["gstdev"]) / sqrt(2*pi);
# lagrangian scheme options
opts_init = lgrngn.opts_init_t()
for opt in ["dt", "sd_conc", "chem_rho", "sstp_cond"]:
setattr(opts_init, opt, opts[opt])
opts_init.n_sd_max = opts_init.sd_conc
opts_init.dry_distros = {opts["kappa"]:lognormal}
# switch off sedimentation and collisions
opts_init.sedi_switch = False
opts_init.coal_switch = False
# switching on chemistry if either dissolving, dissociation or reactions are chosen
opts_init.chem_switch = False
if opts["chem_dsl"] or opts["chem_dsc"] or opts["chem_rct"]:
opts_init.chem_switch = True
opts_init.sstp_chem = opts["sstp_chem"]
# initialisation
micro = lgrngn.factory(lgrngn.backend_t.serial, opts_init)
ambient_chem = {}
if micro.opts_init.chem_switch:
ambient_chem = dict((v, state[k]) for k,v in _Chem_g_id.iteritems())
micro.init(state["th_d"], state["r_v"], state["rhod"], ambient_chem=ambient_chem)
return micro
import sys
sys.path.insert(0, "../../bindings/python/")
from libcloudphxx import lgrngn
from math import exp, log, sqrt, pi
import numpy as np
opts_init = lgrngn.opts_init_t()
opts_init.dt = 1
rhod = 1. * np.ones((1,))
th = 300. * np.ones((1,))
rv = 0.01 * np.ones((1,))
def lognormal(lnr):
mean_r = .04e-6 / 2
stdev = 1.4
n_tot = 60e6
return n_tot * exp(
-pow((lnr - log(mean_r)), 2) / 2 / pow(log(stdev),2)
) / log(stdev) / sqrt(2*pi);
kappa = .61
opts_init.dry_distros = {kappa:lognormal}
opts_init.sd_conc = 50
opts_init.n_sd_max = 50
opts_init.coal_switch = False
opts_init.sedi_switch = False
from libcloudphxx import lgrngn
from numpy import array as arr_t, frombuffer, repeat, zeros, float64, ones
from math import exp, log, sqrt, pi
def lognormal(lnr):
mean_r = .04e-6 / 2
stdev = 1.4
n_tot = 60e6
return n_tot * exp(
-pow((lnr - log(mean_r)), 2) / 2 / pow(log(stdev),2)
) / log(stdev) / sqrt(2*pi);
opts_init = lgrngn.opts_init_t()
kappa = .61
opts_init.dry_distros = {kappa:lognormal}
opts_init.kernel = lgrngn.kernel_t.geometric
opts_init.terminal_velocity = lgrngn.vt_t.beard76
opts_init.dt = 1
opts_init.sd_conc = 64
opts_init.n_sd_max = 512
opts_init.rng_seed = 396
opts_init.src_dry_distros = {kappa:lognormal}
opts_init.src_sd_conc = 64
opts_init.src_z1 = opts_init.dz
print "nx = ", opts_init.nx
print "ny = ", opts_init.ny
print "nz = ", opts_init.nz
def test(turb_cond):
print 'turb_cond = ', turb_cond
opts_init = lgrngn.opts_init_t()
kappa = .61
opts_init.dry_distros = {kappa:lognormal}
opts_init.coal_switch=0
opts_init.sedi_switch=0
opts_init.dt = 1
opts_init.sd_conc = 64
opts_init.n_sd_max = 512
opts_init.rng_seed = 396
opts_init.exact_sstp_cond = True # test would fail with per-cell sstp logic
opts_init.turb_cond_switch = turb_cond
spinup = 20
backend = lgrngn.backend_t.serial
opts = lgrngn.opts_t()
opts.sedi=0
opts.coal=0
opts.cond=1
opts.turb_cond=turb_cond
opts_init.nx = 2
opts_init.dx = 1
opts_init.x1 = opts_init.nx * opts_init.dx
opts_init.nz = 1
opts_init.dz = 1
opts_init.z1 = opts_init.nz * opts_init.dz
rhod = 1. * ones((opts_init.nx, opts_init.nz))
Cx = 1. * ones((opts_init.nx+1, opts_init.nz))
Cz = 0. * ones((opts_init.nx, opts_init.nz+1))
eps = 1e-4 * ones((opts_init.nx, opts_init.nz))
for sstp_cond in [1,2,5]:
print 'sstp_cond = ' + str(sstp_cond)
opts.adve=0
opts_init.sstp_cond = sstp_cond
prtcls = lgrngn.factory(backend, opts_init)
th = 300 * ones((opts_init.nx, opts_init.nz))
rv = .0025 * ones((opts_init.nx, opts_init.nz))
rv[1,0] = 0.0095
prtcls.init(th, rv, rhod, Cx=Cx, Cz=Cz)
#equilibrium wet moment post spinup
prtcls.diag_all()
prtcls.diag_wet_mom(3);
wet_post_init = copy(frombuffer(prtcls.outbuf()).reshape(opts_init.nx, opts_init.nz))
water_post_init = 1000. * 4./3. * pi * wet_post_init + rv
#spinup to get equilibrium
if(turb_cond):
prtcls.step_sync(opts, th, rv, diss_rate=eps)
else:
prtcls.step_sync(opts, th, rv)
for it in range(spinup):
prtcls.step_async(opts)
if(turb_cond):
prtcls.step_sync(opts, th, rv, diss_rate=eps)
else:
prtcls.step_sync(opts, th, rv)
#equilibrium wet moment post spinup
prtcls.diag_all()
prtcls.diag_wet_mom(3);
wet_post_spin = copy(frombuffer(prtcls.outbuf()).reshape(opts_init.nx, opts_init.nz))
water_post_spin = 1000. * 4./3. * pi * wet_post_spin + rv
assert allclose(water_post_spin, water_post_init, atol=0, rtol=1e-10) #some discrepancy due to water density
#advect SDs
opts.adve=1
prtcls.step_async(opts)
#equilibrium wet moment post adve
prtcls.diag_all()
prtcls.diag_wet_mom(3);
wet_post_adve = copy(frombuffer(prtcls.outbuf()).reshape(opts_init.nx, opts_init.nz))
wet_post_adve_roll = roll(wet_post_adve,1).copy()
assert all(wet_post_adve_roll == wet_post_spin)
#advect rv
tmp = rv.copy()
rv[0,0] = tmp[1,0]
rv[1,0] = tmp[0,0]
#advect th
tmp = th.copy()
th[0,0] = tmp[1,0]
th[1,0] = tmp[0,0]
#condensation with advected SDs and rv
if(turb_cond):
prtcls.step_sync(opts, th, rv, diss_rate=eps)
else:
prtcls.step_sync(opts, th, rv)
#wet mom post adve and cond
prtcls.diag_all()
prtcls.diag_wet_mom(3);
wet_post_adve_cond = copy(frombuffer(prtcls.outbuf()).reshape(opts_init.nx, opts_init.nz))
assert allclose(wet_post_adve, wet_post_adve_cond, atol=0, rtol=3e-2)
def test(turb_cond):
print 'turb_cond = ', turb_cond
opts_init = lgrngn.opts_init_t()
kappa = .61
opts_init.dry_distros = {kappa: lognormal}
opts_init.coal_switch = 0
opts_init.sedi_switch = 0
opts_init.dt = 1
opts_init.sd_conc = 64
opts_init.n_sd_max = 512
opts_init.rng_seed = 396
opts_init.exact_sstp_cond = True # test would fail with per-cell sstp logic
opts_init.turb_cond_switch = turb_cond
spinup = 20
backend = lgrngn.backend_t.serial
opts = lgrngn.opts_t()
opts.sedi = 0
opts.coal = 0
opts.cond = 1
opts.turb_cond = turb_cond
opts_init.nx = 2
opts_init.dx = 1
opts_init.x1 = opts_init.nx * opts_init.dx
opts_init.nz = 1
opts_init.dz = 1
opts_init.z1 = opts_init.nz * opts_init.dz
rhod = 1. * ones((opts_init.nx, opts_init.nz))
Cx = 1. * ones((opts_init.nx + 1, opts_init.nz))
Cz = 0. * ones((opts_init.nx, opts_init.nz + 1))
eps = 1e-4 * ones((opts_init.nx, opts_init.nz))
for sstp_cond in [1, 2, 5]:
print 'sstp_cond = ' + str(sstp_cond)
opts.adve = 0
opts_init.sstp_cond = sstp_cond
prtcls = lgrngn.factory(backend, opts_init)
th = 300 * ones((opts_init.nx, opts_init.nz))
rv = .0025 * ones((opts_init.nx, opts_init.nz))
rv[1, 0] = 0.0095
prtcls.init(th, rv, rhod, Cx=Cx, Cz=Cz)
#equilibrium wet moment post spinup
prtcls.diag_all()
prtcls.diag_wet_mom(3)
wet_post_init = copy(
frombuffer(prtcls.outbuf()).reshape(opts_init.nx, opts_init.nz))
water_post_init = 1000. * 4. / 3. * pi * wet_post_init + rv
#spinup to get equilibrium
if (turb_cond):
prtcls.step_sync(opts, th, rv, diss_rate=eps)
else:
prtcls.step_sync(opts, th, rv)
for it in range(spinup):
prtcls.step_async(opts)
if (turb_cond):
prtcls.step_sync(opts, th, rv, diss_rate=eps)
else:
prtcls.step_sync(opts, th, rv)
#equilibrium wet moment post spinup
prtcls.diag_all()
prtcls.diag_wet_mom(3)
wet_post_spin = copy(
frombuffer(prtcls.outbuf()).reshape(opts_init.nx, opts_init.nz))
water_post_spin = 1000. * 4. / 3. * pi * wet_post_spin + rv
assert allclose(water_post_spin, water_post_init, atol=0,
rtol=1e-10) #some discrepancy due to water density
#advect SDs
opts.adve = 1
prtcls.step_async(opts)
#equilibrium wet moment post adve
prtcls.diag_all()
prtcls.diag_wet_mom(3)
wet_post_adve = copy(
frombuffer(prtcls.outbuf()).reshape(opts_init.nx, opts_init.nz))
wet_post_adve_roll = roll(wet_post_adve, 1).copy()
assert all(wet_post_adve_roll == wet_post_spin)
#advect rv
tmp = rv.copy()
rv[0, 0] = tmp[1, 0]
rv[1, 0] = tmp[0, 0]
#advect th
tmp = th.copy()
th[0, 0] = tmp[1, 0]
th[1, 0] = tmp[0, 0]
#condensation with advected SDs and rv
if (turb_cond):
prtcls.step_sync(opts, th, rv, diss_rate=eps)
else:
prtcls.step_sync(opts, th, rv)
#wet mom post adve and cond
prtcls.diag_all()
prtcls.diag_wet_mom(3)
wet_post_adve_cond = copy(
frombuffer(prtcls.outbuf()).reshape(opts_init.nx, opts_init.nz))
assert allclose(wet_post_adve, wet_post_adve_cond, atol=0, rtol=3e-2)
