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Fixed cic. Fixed lpt1 evaluation in cosmogrowth

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Guilhem Lavaux 2014-06-03 10:48:54 +02:00
parent 4bc7bf47a7
commit 7662ea98d4
4 changed files with 28 additions and 16 deletions
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35
python/cosmotool/cic.py
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@ -3,18 +3,25 @@ import numpy as np
def cicParticles(particles, L, N):
for d in xrange(3):
q = particles[d]*N/L
i.append(np.floor(q).astype(int))
r.append(q-i[-1])
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)
return density
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]%L)*N/L
o = np.floor(q).astype(int)
i.append(o)
r.append(q-o)
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.reshape((N,N,N))