Fixed cic. Fixed lpt1 evaluation in cosmogrowth
This commit is contained in:
parent
4bc7bf47a7
commit
7662ea98d4
@ -3,18 +3,25 @@ import numpy as np
|
||||
|
||||
def cicParticles(particles, L, N):
|
||||
|
||||
|
||||
def shifted(i, t):
|
||||
return (i[2]+t[2])%N + N*((i[1]+t[1])%N + N*((i[0]+t[0])%N))
|
||||
|
||||
i =[]
|
||||
r = []
|
||||
for d in xrange(3):
|
||||
q = particles[d]*N/L
|
||||
i.append(np.floor(q).astype(int))
|
||||
r.append(q-i[-1])
|
||||
q = (particles[d]%L)*N/L
|
||||
o = np.floor(q).astype(int)
|
||||
i.append(o)
|
||||
r.append(q-o)
|
||||
|
||||
density = np.bincount(shifted(i, (0,0,0)), weights= r[0]* r[1]* r[2], minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (0,0,1)), weights= r[0]* r[1]*(1-r[2]), minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (0,1,0)), weights= r[0]*(1-r[1])* r[2], minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (0,1,1)), weights= r[0]*(1-r[1])*(1-r[2]), minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (1,0,0)), weights=(1-r[0])* r[1]* r[2], minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (1,0,1)), weights=(1-r[0])* r[1]*(1-r[2]), minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (1,1,0)), weights=(1-r[0])*(1-r[1])* r[2], minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (1,1,1)), weights=(1-r[0])*(1-r[1])*(1-r[2]), minlength=N*N*N)
|
||||
density = np.bincount(shifted(i, (1,1,1)), weights= r[0] * r[1] * r[2], minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (1,1,0)), weights= r[0] * r[1] *(1-r[2]), minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (1,0,1)), weights= r[0] *(1-r[1])* r[2], minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (1,0,0)), weights= r[0] *(1-r[1])*(1-r[2]), minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (0,1,1)), weights=(1-r[0])* r[1] * r[2], minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (0,1,0)), weights=(1-r[0])* r[1] *(1-r[2]), minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (0,0,1)), weights=(1-r[0])*(1-r[1])* r[2], minlength=N*N*N)
|
||||
density += np.bincount(shifted(i, (0,0,0)), weights=(1-r[0])*(1-r[1])*(1-r[2]), minlength=N*N*N)
|
||||
|
||||
return density
|
||||
return density.reshape((N,N,N))
|
||||
|
@ -34,6 +34,7 @@ def compute_power_from_borg(input_borg, a_borg, cosmo, bins=10, range=(0,1)):
|
||||
cgrowth = CosmoGrowth(**cosmo)
|
||||
D1 = cgrowth.D(1)
|
||||
D1_0 = D1/cgrowth.D(a_borg)
|
||||
print("D1_0=%lg" % D1_0)
|
||||
|
||||
density_hat, L = ba.half_pixel_shift(borg_vol)
|
||||
|
||||
@ -76,7 +77,7 @@ def run_generation(input_borg, a_borg, a_ic, **cosmo):
|
||||
|
||||
for j in xrange(3):
|
||||
# Generate psi_j (displacement along j)
|
||||
psi = D1_0*lpt.lpt1(j).flatten()*(N/L)**3
|
||||
psi = D1_0*lpt.lpt1(j).flatten()
|
||||
# Generate posx
|
||||
posx.append(((posq[j] + psi)%L).astype(np.float32))
|
||||
# Generate vel
|
||||
|
@ -57,7 +57,7 @@ class LagrangianPerturbation(object):
|
||||
k2 = self._get_k2()
|
||||
k2[0,0,0] = 1
|
||||
|
||||
return self._gradient(-self.dhat/k2, direction)
|
||||
return self._gradient(self.dhat/k2, direction)
|
||||
|
||||
def new_shape(self,direction, q=3, half=False):
|
||||
N0 = (self.N/2+1) if half else self.N
|
||||
|
@ -10,5 +10,9 @@ cosmo['SIGMA8']=0.8344
|
||||
zstart=0
|
||||
astart=1/(1.+zstart)
|
||||
|
||||
pos,_,density,N,L,_ = bic.run_generation("initial_condition_borg.dat", 0.001, astart, **cosmo)
|
||||
|
||||
dcic = ct.cicParticles(pos, L, N)
|
||||
|
||||
#if __name__=="__main__":
|
||||
# bic.write_icfiles(*bic.run_generation("initial_condition_borg.dat", 0.001, astart, **cosmo), **cosmo)
|
||||
|
Loading…
Reference in New Issue
Block a user