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n_r.py
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n_r.py
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from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
import pylab as py
import sys
import time
from functions import simul_data,rotation,projections,poisson_realization
start_time = time.time()
list1 = []
for i in range(16):
list1.append('/Users/anadiazrivero/Desktop/ETHOS/CDM/fof_subhalo_tab_127.%s.hdf5' % i)
Rng = 600
subh_mass,subh_pos,r1,r2 = simul_data(list1,Rnge=Rng) #in 10^10 M_sun/h, kpc/h
subh_mass = [i*10**(10) for i in subh_mass]
plot_N3d = True
plot_N2d = False
if plot_N3d == True:
r = [np.sqrt(i**2+j**2+k**2) for i,j,k, in subh_pos]
binsr = np.arange(1,500,5)
counts,bins,bars = plt.hist(r,bins=binsr)
plt.ylabel('N_sub')
plt.xlabel('r_3D (kpc/h)')
plt.show()
plt.clf()
def nr_3d(coords,masses,mcut=False,mhigh=1,mlow=1):
if mcut == True:
arr = zip(coords,masses)
arr2 = []
for a,b in zip(mlow,mhigh):
arr3 = [i for i in arr if a < i[1] < b]
arr2.append(arr3)
x = []
y = []
z = []
for i in arr2:
pos,mass = zip(*i)
xx,yy,zz = zip(*pos)
x.append(xx)
y.append(yy)
z.append(zz)
#print np.shape(x),np.shape(y),np.shape(z)
else:
x,y,z = zip(*coords)
pix_num = 50
pix_size = Rng/pix_num
H = []
xe = []
ye = []
ze = []
Rmax = []
for i,j,k in zip(x,y,z):
i = np.asarray(i)
j = np.asarray(j)
k = np.asarray(k)
r2 = np.sqrt(i**2+j**2+k**2)
Rmax.append(max(r2))
counts,[xedges,yedges,zedges] = np.histogramdd((i,j,k),bins=(pix_num,pix_num,pix_num))
H.append(counts)
xe.append(xedges)
ye.append(yedges)
ze.append(zedges)
xe2 = []
for i in xe:
xedges = [j+0.5*pix_size for j in i[:-1]]
xe2.append(xedges)
ye2 = []
for i in ye:
yedges = [j+0.5*pix_size for j in i[:-1]]
ye2.append(yedges)
ze2 = []
for i in ze:
zedges = [j+0.5*pix_size for j in i[:-1]]
ze2.append(zedges)
nr_tot = []
R_tot = []
for i,j,k,l,q in zip(H,xe2,ye2,ze2,Rmax):
im = np.array(i)
xx,yy,zz = np.meshgrid(j,k,l)
r = np.sqrt(xx**2+yy**2+zz**2)
rmax = q
dr = pix_size
R = np.arange(rmax/dr)*dr
R_tot.append(R)
nr = []
for u in range(len(R)):
rmin = u*dr
rmax = rmin + dr
index = (r>=rmin) * (r<=rmax)
nr.append(im[index].mean())
nr_tot.append(nr)
return R_tot,nr_tot
mhigh = [1e10,1e9,1e8,1e7]
mlow = [1e9,1e8,1e7,1e6]
R,nr = nr_3d(subh_pos,subh_mass,mcut=True,mhigh=mhigh,mlow=mlow)
plt.rc('text', usetex=True)
mhigh = [10,9,8,7]
mlow = [9,8,7,6]
for i,j,k,l in zip(nr,R,mlow,mhigh):
aq = np.asarray(i)/np.mean(i)
#plt.loglog(j,aq,label='$%.1e M_{\odot} < M_{sub} < %.1e M_{\odot}$' % (k,l))
plt.loglog(j,aq,label='$10^{%s} M_{\odot} < M_{sub} < 10^{%s} M_{\odot}$' % (k,l))
plt.xlabel('$r_{3D}$ $[kpc/h]$',fontsize=20)
plt.ylabel('$n(r)/<n>$',fontsize=20)
#plt.title('n(r) in 3d')
plt.tick_params(axis='both', which='major', labelsize=15)
plt.legend(prop={'size': 16})
plt.show()
shft = 0
rnge = 1000
coordsm,avg_num_subh = projections(subh_pos,subh_mass,r1,r2,rnge=rnge,shift=shft,num_proj=100)
#coordsm,avg_num_subh = projections(subh_pos,subh_mass,r1,r2,rnge=rnge,shift=shft,num_proj=100)
print "Done"
coords = []
for i in coordsm:
r,m,_,_ = zip(*i)
coords.append(r)
if plot_N2d == True:
#plot as 1d hist
pos_2d = [i for j in coords for i in j]
r_2d = [np.sqrt(i**2+j**2) for i,j in pos_2d]
binsr = np.arange(1,600,5)
counts,bins,bars = plt.hist(r_2d,bins=binsr)
plt.ylabel('N_sub')
plt.xlabel('r_2D (kpc/h)')
plt.show()
plt.clf()
#plot as line
counts = [i/len(coords) for i in counts]
diff = binsr[1]-binsr[0]
binsr = [i + 0.5*diff for i in binsr][:-1]
plt.plot(binsr,counts)
plt.ylabel('N_sub')
plt.xlabel('r_2D (kpc/h)')
plt.show()
def nr_2d(coords,bns=20,rnge=100):
bin_size = rnge/bns
nr = []
n_avg = []
xlim = []
ylim = []
for i in coords:
x,y = zip(*i)
N,xedges,yedges = np.histogram2d(x,y,bins=bns)
xedges = [i+0.5*bin_size for i in xedges[:-1]]
yedges = [i+0.5*bin_size for i in yedges[:-1]]
xlim.append(xedges)
ylim.append(yedges)
n = [i/bin_size**2 for i in N]
nr.append(n)
Nbar = N.mean()
n_avg.append(Nbar/bin_size**2)
return nr,n_avg,bin_size,xlim,ylim
nr,n_avg,bin_size,xlim,ylim = nr_2d(coords,bns=500,rnge=rnge)
print bin_size
u = [sum(x)/len(coords) for x in zip(*nr)]
xavg = [sum(i)/len(coords) for i in zip(*xlim)]
yavg = [sum(i)/len(coords) for i in zip(*ylim)]
im = np.array(u)
xx,yy = np.meshgrid(xavg,yavg)
r = np.sqrt(xx**2+yy**2)
rmax = max(xavg)
dr = bin_size
R = np.arange(rmax/dr)*dr
nr = []
for i in range(len(R)):
rmin = i*dr
rmax = rmin + dr
index = (r>=rmin) * (r<=rmax)
nr.append(im[index].mean())
plt.rc('text', usetex=True)
fig,ax = plt.subplots(1)
ax.axhline(nr[1],min(R),1000,c='r')
ax.axvline(15,1e-5,1,c='r',ls='dashed')
ax.loglog(R,nr)
ax.set_xlabel('$r_{2D}$ $[kpc/h]$',fontsize=20)
ax.set_ylabel('$n(r)$',fontsize=20)
ax.set_xlim(min(R),1000)
ax.set_ylim(min(nr),2*1e-1)
plt.tick_params(axis='both', which='major', labelsize=15)
plt.title('n(r) in 2d')
plt.show()
print("--- %s seconds ---" % (time.time() - start_time))