def test_gravity(comm):
from pmesh.pm import ParticleMesh
import fastpm.operators as operators
pm = ParticleMesh(BoxSize=4.0, Nmesh=(4, 4), comm=comm, method='cic', dtype='f8')
vm = fastpm.Evolution(pm, shift=0.5)
dlink = pm.generate_whitenoise(12345, mode='complex')
code = vm.code()
code.Decompress(C='dlin_k')
code.LPTDisplace(dlin_k='dlin_k', D1=1.0, v1=0, D2=0.0, v2=0.0)
code.ForcePaint()
code.Force(factor=0.1)
code.Chi2(variable='f')
print(code)
# FIXME: without the shift some particles have near zero dx1.
# or near 1 dx1.
# the gradient is not well approximated by the numerical if
# any of the left or right value shifts beyond the support of
# the window.
#
dlink, ampl = _addampl(dlink)
_test_model(code, dlink, ampl)
def test_kdk(comm):
# Or use an object from astropy.
cosmo = lambda : None
cosmo.Om0 = 0.3
cosmo.Ode0 = 0.7
cosmo.Ok0 = 0.0
pm = ParticleMesh(BoxSize=128.0, Nmesh=(4,4,4), comm=comm, dtype='f8')
vm = fastpm.Evolution(pm, B=1, shift=0.5)
dlink = pm.generate_whitenoise(12345, mode='complex', unitary=True)
dlink, ampl = _addampl(dlink)
data = dlink.c2r()
data[...] = 0
sigma = data.copy()
sigma[...] = 1.0
code = vm.code()
code.Decompress(C='dlin_k')
code.KDKSimulation(dlin_k='dlin_k', mesh='mesh', cosmo=cosmo, astart=0.1, aend=1.0, Nsteps=5)
code.Decompose()
code.Paint()
code.Residual(data_x=data, sigma_x=sigma)
code.Chi2(variable='residual')
_test_model(code, dlink, ampl)
def test_prior(comm):
from pmesh.pm import ParticleMesh
pm = ParticleMesh(BoxSize=128.0, Nmesh=(4, 4), comm=comm)
vm = fastpm.Evolution(pm, shift=0.5)
dlink = pm.generate_whitenoise(1234, mode='complex')
code = vm.code()
code.Prior(dlin_k='dlin_k', powerspectrum=lambda k : 1.0)
code.CopyVariable(x='prior', y='chi2')
dlink, ampl = _addampl(dlink)
_test_model(code, dlink, ampl)
def test_lpt(comm):
from pmesh.pm import ParticleMesh
pm = ParticleMesh(BoxSize=128.0, Nmesh=(4, 4), comm=comm)
vm = fastpm.Evolution(pm, shift=0.5)
dlink = pm.generate_whitenoise(1234, mode='complex')
code = vm.code()
code.Decompress(C='dlin_k')
code.LPTDisplace(dlin_k='dlin_k', D1=1.0, v1=0, D2=0.0, v2=0.0)
code.Chi2(variable='s')
dlink, ampl = _addampl(dlink)
_test_model(code, dlink, ampl)
def test_resample(comm):
if comm.size == 4:
comm.barrier()
from pmesh.pm import ParticleMesh
# testing the gradient of down sampling, which we use the most.
pm = ParticleMesh(BoxSize=128.0, Nmesh=(8, 8), comm=comm)
vm = fastpm.Evolution(pm, shift=0.5)
dlink = pm.generate_whitenoise(1234, mode='complex')
dlink, ampl = _addampl(dlink)
code = vm.code()
code.Decompress(C='dlin_k')
code.C2R(C='dlin_k', R='mesh')
code.Resample(Neff=4)
code.Chi2(variable='mesh')
_test_model(code, dlink, ampl)
def test_lpt_prior(comm):
from pmesh.pm import ParticleMesh
pm = ParticleMesh(BoxSize=128.0, Nmesh=(4, 4), comm=comm)
vm = fastpm.Evolution(pm, shift=0.5)
dlink = pm.generate_whitenoise(1234, mode='complex')
code = vm.code()
code.Decompress(C='dlin_k')
code.LPTDisplace(dlin_k='dlin_k', D1=1.0, v1=0, D2=0.0, v2=0.0)
code.Decompose()
code.Paint()
code.Chi2(variable='mesh')
code.Prior(powerspectrum=lambda k : 1.0)
code.Multiply(a='prior', b='prior', f=0.1)
code.Add(a='prior', b='chi2', c='chi2')
dlink, ampl = _addampl(dlink)
_test_model(code, dlink, ampl)