Merge branch 'master' of bitbucket.org:glavaux/cosmotool

This commit is contained in:
Guilhem Lavaux 2014-06-12 15:29:57 +02:00
commit 01059f145b
2 changed files with 23 additions and 9 deletions

View File

@ -136,8 +136,12 @@ def whitify(density, L, cosmo, supergenerate=1, func='HU_WIGGLES'):
if supergenerate > 1: if supergenerate > 1:
cond=np.isnan(density_hat_super) cond=np.isnan(density_hat_super)
x = np.random.randn(np.count_nonzero(cond),2)/np.sqrt(2.0) print np.where(np.isnan(density_hat_super))[0].size
density_hat_super[cond] = x[:,0] + 1j * x[:,1] Nz = np.count_nonzero(cond)
density_hat_super.real[cond] = np.random.randn(Nz)
density_hat_super.imag[cond] = np.random.randn(Nz)
density_hat_super[cond] /= np.sqrt(2.0)
print np.where(np.isnan(density_hat_super))[0].size
# Now we have to fix the Nyquist plane # Now we have to fix the Nyquist plane
hNs = Ns/2 hNs = Ns/2
@ -145,6 +149,8 @@ def whitify(density, L, cosmo, supergenerate=1, func='HU_WIGGLES'):
Nplane = nyquist.size Nplane = nyquist.size
nyquist.flat[:Nplane/2] = np.sqrt(2.0)*nyquist.flat[Nplane:Nplane/2:-1].conj() nyquist.flat[:Nplane/2] = np.sqrt(2.0)*nyquist.flat[Nplane:Nplane/2:-1].conj()
print np.where(np.isnan(density_hat_super))[0].size
return np.fft.irfftn(density_hat_super)*Ns**1.5 return np.fft.irfftn(density_hat_super)*Ns**1.5

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@ -10,26 +10,34 @@ cosmo['omega_k_0'] = 0
cosmo['omega_B_0']=0.049 cosmo['omega_B_0']=0.049
cosmo['SIGMA8']=0.8344 cosmo['SIGMA8']=0.8344
cosmo['ns']=0.9624 cosmo['ns']=0.9624
N0=128 N0=256
doSimulation=True doSimulation=True
simShift=True
snap_id=int(sys.argv[1]) snap_id=int(sys.argv[1])
astart=1/100. astart=1/100.
if doSimulation: if doSimulation:
s = ct.loadRamsesAll("/nethome/lavaux/remote2/borgsim/", snap_id, doublePrecision=True) s = ct.loadRamsesAll("/nethome/lavaux/remote2/borgsim2/", snap_id, doublePrecision=True)
astart=s.getTime() astart=s.getTime()
L = s.getBoxsize() L = s.getBoxsize()
dsim = ct.cicParticles(s.getPositions(), L, N0) p = s.getPositions()
Nsim = int( np.round( p[0].size**(1./3)) )
print("Nsim = %d" % Nsim)
if simShift:
p = [(q-0.5*L/Nsim)%L for q in p]
dsim = ct.cicParticles(p[::-1], L, N0)
dsim /= np.average(np.average(np.average(dsim, axis=0), axis=0), axis=0) dsim /= np.average(np.average(np.average(dsim, axis=0), axis=0), axis=0)
dsim -= 1 dsim -= 1
dsim_hat = np.fft.rfftn(dsim)*(L/N0)**3 dsim_hat = np.fft.rfftn(dsim)*(L/N0)**3
Psim, bsim = bic.bin_power(np.abs(dsim_hat)**2/L**3, L, range=(0,1.), bins=150) Psim, bsim = bic.bin_power(np.abs(dsim_hat)**2/L**3, L, range=(0,1.), bins=150)
pos,_,density,N,L,_,_ = bic.run_generation("initial_density_1380.dat", 0.001, astart, cosmo, supersample=2, do_lpt2=True) pos,_,density,N,L,_,_ = bic.run_generation("initial_density_2588.dat", 0.001, astart, cosmo, supersample=2, do_lpt2=True)
dcic = ct.cicParticles(pos, L, N0) dcic = ct.cicParticles(pos, L, N0)
dcic /= np.average(np.average(np.average(dcic, axis=0), axis=0), axis=0) dcic /= np.average(np.average(np.average(dcic, axis=0), axis=0), axis=0)
@ -50,7 +58,7 @@ Pref, bref = bic.compute_ref_power(L, N0, cosmo, range=(0,1.), bins=150)
Pcic /= D1_0**2 Pcic /= D1_0**2
Pdens /= D1_0**2 Pdens /= D1_0**2
borg_evolved = ct.read_borg_vol("final_density_1380.dat") #borg_evolved = ct.read_borg_vol("final_density_1380.dat")
dborg_hat = np.fft.rfftn(borg_evolved.density)*L**3/borg_evolved.density.size #dborg_hat = np.fft.rfftn(borg_evolved.density)*L**3/borg_evolved.density.size
Pborg, bborg = bic.bin_power(np.abs(dborg_hat)**2/L**3, L, range=(0,1.),bins=150) #Pborg, bborg = bic.bin_power(np.abs(dborg_hat)**2/L**3, L, range=(0,1.),bins=150)