def calc_stellar_dens(Stars, haloX, haloY, haloZ, theRvir, rvirFac, boxsize):
dists = SF.calcdist2(haloX, haloY, haloZ, Stars['p'][:, 0],
Stars['p'][:, 1], Stars['p'][:, 2], boxsize)
cut = dists < theRvir * rvirFac
StellarMass = np.sum(Stars['m'][cut])
StellarDens = StellarMass / ((4.0 / 3.0) * 3.14159 *
(theRvir * rvirFac)**3.0)
return StellarDens
Sx = Sp[:, 0]
Sy = Sp[:, 1]
Sz = Sp[:, 2]
header = readsnapcr(the_snapdir,
Nsnapstring,
0,
snapshot_name=the_prefix,
extension=the_suffix,
havecr=havecr,
h0=1,
cosmological=1,
header_only=1)
h0 = header['hubble']
atime = header['time']
if usepep == 1:
halosA = SF.read_halo_history_pep(rundir, finalno, beginno=beginno,\
singlesnap=0, firever=firever,halonostr=halostr, hubble=h0, comoving=1, maindir=maindir)
afactor = atime
else:
halosA = SF.read_halo_history(rundir,
maindir=maindir,
halonostr=halostr,
hubble=h0,
comoving=0)
afactor = 1.0
redlist = halosA['redshift']
haloid = halosA['ID']
a_scale = 1.0 / (1.0 + redlist)
xcenl = halosA['x'] * afactor
ycenl = halosA['y'] * afactor
zcenl = halosA['z'] * afactor
Rvirl = halosA['R'] * afactor
G = readsnap(the_snapdir,
Nsnapstring,
0,
snapshot_name=the_prefix,
extension=the_suffix)
a = G['header'][2]
z = 1.0 / a - 1.0
redshift = G['header'][3]
boxsize = G['header'][9]
omega_matter = G['header'][10]
omega_L = G['header'][11]
h = G['header'][12]
redshiftstring = "{0:.3f}".format(redshift)
Hubble = hubble_param(a, omega_matter, h)
PhysTemp, PhysRho = SF.convertTemp(G['u'], G['ne'], G['rho'], h)
halostats = SF.find_halo_now(halo_to_do, a, therod=use_fixed_halos)
print 'halo stats', halostats
haloN = halostats[1]
#read halo catalog, assign halo properties
Rvir = halostats[11]
Vsig = halostats[10]
haloX = halostats[2]
haloY = halostats[3]
haloZ = halostats[4]
haloVX = halostats[5]
haloVY = halostats[6]
haloVZ = halostats[7]
else:
plotupt.append('')
print 'labelneed', labelneed
if multifile=='y':
fname=the_snapdir+'/snapdir_'+Nsnapstring+'/snapshot_'+Nsnapstring+'.0.hdf5'
else:
fname=the_snapdir+'/snapshot_'+Nsnapstring+'.hdf5'
print 'fname', fname
print 'usepep', usepep
if cosmo==1:
header=readsnapcr(the_snapdir, Nsnapstring, 0, snapshot_name=the_prefix, extension=the_suffix, havecr=havecr,h0=1,cosmological=1,header_only=1)
h0 = header['hubble']
atime = header['time']
print 'halostr', halostr
if usepep==1:
halosA = SF.read_halo_history_pep(rundir, Nsnap, singlesnap=1, firever=firever,halonostr=halostr, hubble=h0, comoving=1, maindir=maindir)
redlist = halosA['redshift']
haloid = halosA['ID']
xcen = halosA['x']*atime
ycen = halosA['y']*atime
zcen = halosA['z']*atime
vxcen = halosA['xv']
vycen = halosA['yv']
vzcen = halosA['zv']
else:
halosA = SF.read_halo_history(rundir, maindir=maindir, halonostr=halostr,\
hubble=h0, comoving=0, snumadd=snumadd)
redlist = halosA['redshift']
haloid = halosA['ID']
a_scale = 1.0/(1.0+redlist)
xcenl = halosA['x']
import numpy as np
import Sasha_functions as SF
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d
from datetime import date
today = date.today()
Nhalo = 0
H = SF.read_halo_history(Nhalo)
Zs = H['redshift']
IDs = H['ID']
Vsig = H['Vsig']
M = H['M']
Rvir = H['Rvir']
Vmax = H['Vmax']
newtonG = 6.67384e-8
little_h = 0.7
As = 1.0 / (1.0 + Zs)
Vcirc = np.sqrt(
(newtonG * M * 2e33 / little_h) / (Rvir * As * 3.08e21 / little_h)) / 1e5
Vsig1D = Vsig / np.sqrt(3)
Ns = []
for theZ in Zs:
theN = SF.N_for_z(theZ)
Ns.append(theN)
Ns = np.array(Ns)
vesc_order = np.argsort(vesc_ar[count]) mass_sorted_cumsum = np.cumsum(sig_ar[count][vesc_order]) mass_sorted_cumsum /= mass_sorted_cumsum[-1] vesc_med = np.interp(0.5, mass_sorted_cumsum,vesc_ar[count][vesc_order] ) vesc_25 = np.interp(0.25, mass_sorted_cumsum,vesc_ar[count][vesc_order] ) vesc_75 = np.interp(0.75, mass_sorted_cumsum,vesc_ar[count][vesc_order] ) print 'name of ep ',ep_name_ar[count] print 'num of snaps in ep', Neps_ar[count] print 'vesc ',len(vesc_ar[count]) print 'sig ',len(sig_ar[count]) weight_avg_vesc = np.average(vesc_ar[count], weights=sig_ar[count]) print 'weighted average vesc ',weight_avg_vesc print '25th, 50th, 75th percentile vesc ',vesc_25, vesc_med, vesc_75 weighted_avg_sig = np.average(sig_ar[count], weights=sig_ar[count])/area_of_cell print 'weighted average sig ',weighted_avg_sig unweighted_avg_sig = np.mean(sig_ar[count])/area_of_cell print 'unweighted average sig ',unweighted_avg_sig myline = [count, ep_name_ar[count], Neps_ar[count], weight_avg_vesc, vesc_25, vesc_med, vesc_75, weighted_avg_sig, unweighted_avg_sig, maxSF_ar[count], totMass_ar[count], duration_ar[count] ] mystring = SF.line_to_string(myline) f.write(mystring) print count, average_weighted_sig shell_histresults = np.histogram(vesc_ar[count], num_bins, range=(0, 1000), weights=np.array(mass_ar[count])/totalmass) [histx, histy] = ssp.create_plottable_hist(shell_histresults) plt.plot(histx,histy, color=color_ar[count], ls = ls_ar[count], lw=2) count+=1 f.close() plt.legend(my_special_legend, loc='best') plt.savefig(str(today) +'normedeps'+'.pdf')
def surface_density_bycells(S, agecut, poscut, a, h, cell_length=0.3, surface_frac=0.8, density_max_cell_center=True):
#r = np.random.randn(100,3)
r = [S['p'][:,0][agecut][poscut], S['p'][:,1][agecut][poscut], S['p'][:,2][agecut][poscut]]
minx = np.min(S['p'][:,0][agecut][poscut])*a/h
maxx = np.max(S['p'][:,0][agecut][poscut])*a/h
miny = np.min(S['p'][:,1][agecut][poscut])*a/h
maxy = np.max(S['p'][:,1][agecut][poscut])*a/h
minz = np.min(S['p'][:,2][agecut][poscut])*a/h
maxz = np.max(S['p'][:,2][agecut][poscut])*a/h
numxcells = int((maxx-minx)/cell_length)+1
numycells = int((maxy-miny)/cell_length)+1
numzcells = int((maxz-minz)/cell_length)+1
xrange = [minx*h/a, (minx*h/a + float(numxcells)*cell_length*h/a)]
yrange = [miny*h/a, (miny*h/a + float(numycells)*cell_length*h/a)]
zrange = [minz*h/a, (minz*h/a + float(numzcells)*cell_length*h/a)]
# print 'diagnostic x',(xrange[1] - xrange[0])/(cell_length*h/a), numxcells
# print 'diagnostic y',(yrange[1] - yrange[0])/(cell_length*h/a), numycells
# print 'diagnostic x',(zrange[1] - zrange[0])/(cell_length*h/a), numzcells
#rad should be in physical kpc
#num_cells=int(rad*2.0/cell_length)
H, edges = np.histogramdd(r, bins = (numxcells, numycells, numzcells), range=(xrange,yrange,zrange), weights=S['m'][agecut][poscut])
cut = H>0
ix, iy, iz = np.where(cut)
count = 0
Nums = []
cenx = []
ceny = []
cenz = []
#print 'iy ', iy
#print 'len iy ',len(iy)
#print 'edges ',edges
#print 'len edges ',len(edges)
while (count < len(ix)):
theNum = H[ix[count],iy[count],iz[count]]
thecenx = (edges[0][ix[count]] + edges[0][ix[count]+1])/2.0
theceny = (edges[1][iy[count]] + edges[1][iy[count]+1])/2.0
thecenz = (edges[2][iz[count]] + edges[2][iz[count]+1])/2.0
if (density_max_cell_center):
cellxmin_cut = S['p'][:,0][agecut][poscut] > edges[0][ix[count]]
cellxmax_cut = S['p'][:,0][agecut][poscut] < edges[0][ix[count]+1]
cellymin_cut = S['p'][:,1][agecut][poscut] > edges[1][iy[count]]
cellymax_cut = S['p'][:,1][agecut][poscut] < edges[1][iy[count]+1]
cellzmin_cut = S['p'][:,2][agecut][poscut] > edges[2][iz[count]]
cellzmax_cut = S['p'][:,2][agecut][poscut] < edges[2][iz[count]+1]
allcut = cellxmin_cut* cellxmax_cut* cellymin_cut* cellymax_cut * cellzmin_cut * cellzmax_cut
#print 'test test ',len(S['p'][:,0][agecut][poscut][allcut]), S['p'][:,0][agecut][poscut][allcut]
if (len(S['p'][:,0][agecut][poscut][allcut]) > 5):
#print 'first center ',[thecenx, theceny, thecenz], theNum
S_COM = SF.gaussian_KDE_center(S['p'][:,0][agecut][poscut][allcut], S['p'][:,1][agecut][poscut][allcut] , S['p'][:,2][agecut][poscut][allcut] , downsample=False)
[thecenx, theceny, thecenz] = S_COM
#print 'adjusting center ',[thecenx, theceny, thecenz]
Nums.append(theNum)
cenx.append(thecenx)
ceny.append(theceny)
cenz.append(thecenz)
count+=1
cenx = np.array(cenx)
ceny = np.array(ceny)
cenz = np.array(cenz)
Nums = np.array(Nums)
order_of_densities = np.argsort(Nums)[::-1]
#cumsumdens = np.cumsum(Nums[order_of_densities])
sum_of_densities = np.sum(Nums)
current_sum = 0
count = 0
final_x = []
final_y = []
final_z = []
final_Nums = []
#print 'densities in order ',Nums[order_of_densities]
while (current_sum <= surface_frac * sum_of_densities):
current_sum += Nums[order_of_densities][count]
final_x.append(cenx[order_of_densities][count])
final_y.append(ceny[order_of_densities][count])
final_z.append(cenz[order_of_densities][count])
final_Nums.append( Nums[order_of_densities][count])
count+=1
return [final_x, final_y, final_z, final_Nums]
import numpy as np import Sasha_functions as SF import matplotlib.pyplot as plt from scipy.interpolate import interp1d from datetime import date today = date.today() Nhalo = 0 H = SF.read_halo_history(Nhalo) Zs = H['redshift'] IDs = H['ID'] Vsig = H['Vsig'] M = H['M'] Rvir = H['Rvir'] Vmax = H['Vmax'] newtonG = 6.67384e-8 little_h = 0.7 As = 1.0 / (1.0 + Zs) Vcirc = np.sqrt( (newtonG * M * 2e33 /little_h )/(Rvir * As * 3.08e21 / little_h)) / 1e5 Vsig1D = Vsig / np.sqrt(3) Ns = [] for theZ in Zs: theN = SF.N_for_z(theZ) Ns.append(theN) Ns = np.array(Ns) count = 0
boxsize = header[9]
if wanted == 'rhoTwind':
cutz = (np.absolute(partZ)>zdown) & (np.absolute(partZ)<zup) #kpc
cutxy = partX*partX+partY*partY<withinr*withinr
if cosmo==1:
cutv = partXV*partX+partYV*partY\
+partZV*partZ>vcut*np.sqrt(partX*partX+partY*partY+partZ*partZ) #outflowing gas
else:
cutv = partZV*partZ/np.absolute(partZ)>vcut #outflowing gas
cut = cutz*cutxy*cutv
Tb = Tb[cut]
rho = rho[cut]
Neb = Neb[cut]
Gmass = Gmass[cut]
TrueTemp, converted_rho = SF.convertTemp(Tb, Neb, rho)
if wanted == 'rhoT':
if needcontour==1:
totalname = 'CRplot/rhoT/rhoT_'+runtodo+'_sn'+str(startno)+'_'+str(Nsnap)+'_contour.pdf'
else:
totalname = 'CRplot/rhoT/rhoT_'+runtodo+'_sn'+str(startno)+'_'+str(Nsnap)+'.pdf'
elif wanted == 'rhoTwind':
if needcontour==1:
totalname = 'CRplot/rhoTwind/rhoTwind_'+runtodo+'_sn'+str(startno)+'_'+str(Nsnap)+'_contour.pdf'
else:
totalname = 'CRplot/rhoTwind/rhoTwind_'+runtodo+'_sn'+str(startno)+'_'+str(Nsnap)+'.pdf'
y = np.log10(TrueTemp)
x = np.log10(converted_rho)
gridxx = np.linspace(extent[0],extent[1],nobin)
gridyy = np.linspace(extent[2],extent[3],nobin)
#gridxx = np.linspace(np.amin(x),np.amax(x),nobin)
def surface_density_bycells(S,
agecut,
poscut,
a,
h,
cell_length=0.3,
surface_frac=0.8,
density_max_cell_center=True):
#r = np.random.randn(100,3)
r = [
S['p'][:, 0][agecut][poscut], S['p'][:, 1][agecut][poscut],
S['p'][:, 2][agecut][poscut]
]
minx = np.min(S['p'][:, 0][agecut][poscut]) * a / h
maxx = np.max(S['p'][:, 0][agecut][poscut]) * a / h
miny = np.min(S['p'][:, 1][agecut][poscut]) * a / h
maxy = np.max(S['p'][:, 1][agecut][poscut]) * a / h
minz = np.min(S['p'][:, 2][agecut][poscut]) * a / h
maxz = np.max(S['p'][:, 2][agecut][poscut]) * a / h
numxcells = int((maxx - minx) / cell_length) + 1
numycells = int((maxy - miny) / cell_length) + 1
numzcells = int((maxz - minz) / cell_length) + 1
xrange = [
minx * h / a, (minx * h / a + float(numxcells) * cell_length * h / a)
]
yrange = [
miny * h / a, (miny * h / a + float(numycells) * cell_length * h / a)
]
zrange = [
minz * h / a, (minz * h / a + float(numzcells) * cell_length * h / a)
]
# print 'diagnostic x',(xrange[1] - xrange[0])/(cell_length*h/a), numxcells
# print 'diagnostic y',(yrange[1] - yrange[0])/(cell_length*h/a), numycells
# print 'diagnostic x',(zrange[1] - zrange[0])/(cell_length*h/a), numzcells
#rad should be in physical kpc
#num_cells=int(rad*2.0/cell_length)
H, edges = np.histogramdd(r,
bins=(numxcells, numycells, numzcells),
range=(xrange, yrange, zrange),
weights=S['m'][agecut][poscut])
cut = H > 0
ix, iy, iz = np.where(cut)
count = 0
Nums = []
cenx = []
ceny = []
cenz = []
#print 'iy ', iy
#print 'len iy ',len(iy)
#print 'edges ',edges
#print 'len edges ',len(edges)
while (count < len(ix)):
theNum = H[ix[count], iy[count], iz[count]]
thecenx = (edges[0][ix[count]] + edges[0][ix[count] + 1]) / 2.0
theceny = (edges[1][iy[count]] + edges[1][iy[count] + 1]) / 2.0
thecenz = (edges[2][iz[count]] + edges[2][iz[count] + 1]) / 2.0
if (density_max_cell_center):
cellxmin_cut = S['p'][:, 0][agecut][poscut] > edges[0][ix[count]]
cellxmax_cut = S['p'][:,
0][agecut][poscut] < edges[0][ix[count] + 1]
cellymin_cut = S['p'][:, 1][agecut][poscut] > edges[1][iy[count]]
cellymax_cut = S['p'][:,
1][agecut][poscut] < edges[1][iy[count] + 1]
cellzmin_cut = S['p'][:, 2][agecut][poscut] > edges[2][iz[count]]
cellzmax_cut = S['p'][:,
2][agecut][poscut] < edges[2][iz[count] + 1]
allcut = cellxmin_cut * cellxmax_cut * cellymin_cut * cellymax_cut * cellzmin_cut * cellzmax_cut
#print 'test test ',len(S['p'][:,0][agecut][poscut][allcut]), S['p'][:,0][agecut][poscut][allcut]
if (len(S['p'][:, 0][agecut][poscut][allcut]) > 5):
#print 'first center ',[thecenx, theceny, thecenz], theNum
S_COM = SF.gaussian_KDE_center(
S['p'][:, 0][agecut][poscut][allcut],
S['p'][:, 1][agecut][poscut][allcut],
S['p'][:, 2][agecut][poscut][allcut],
downsample=False)
[thecenx, theceny, thecenz] = S_COM
#print 'adjusting center ',[thecenx, theceny, thecenz]
Nums.append(theNum)
cenx.append(thecenx)
ceny.append(theceny)
cenz.append(thecenz)
count += 1
cenx = np.array(cenx)
ceny = np.array(ceny)
cenz = np.array(cenz)
Nums = np.array(Nums)
order_of_densities = np.argsort(Nums)[::-1]
#cumsumdens = np.cumsum(Nums[order_of_densities])
sum_of_densities = np.sum(Nums)
current_sum = 0
count = 0
final_x = []
final_y = []
final_z = []
final_Nums = []
#print 'densities in order ',Nums[order_of_densities]
while (current_sum <= surface_frac * sum_of_densities):
current_sum += Nums[order_of_densities][count]
final_x.append(cenx[order_of_densities][count])
final_y.append(ceny[order_of_densities][count])
final_z.append(cenz[order_of_densities][count])
final_Nums.append(Nums[order_of_densities][count])
count += 1
return [final_x, final_y, final_z, final_Nums]
def calculate_escape_velocity(halo_pos, particle_pos, G, S, D, rmax):
newtonG = 6.67384e-8
pc = 3.08567758e18
kpc = pc * 1e3
a = G['header'][2]
h = G['header'][12]
boxsize = G['header'][9]
UnitMass_in_g = 1.989e43 / h
do_plots = False
Gdists = SF.calcdist2(halo_pos[0], halo_pos[1], halo_pos[2], G['p'][:, 0],
G['p'][:, 1], G['p'][:, 2], boxsize)
Sdists = SF.calcdist2(halo_pos[0], halo_pos[1], halo_pos[2], S['p'][:, 0],
S['p'][:, 1], S['p'][:, 2], boxsize)
Ddists = SF.calcdist2(halo_pos[0], halo_pos[1], halo_pos[2], D['p'][:, 0],
D['p'][:, 1], D['p'][:, 2], boxsize)
particle_dists = SF.calcdist2(halo_pos[0], halo_pos[1], halo_pos[2],
particle_pos[0], particle_pos[1],
particle_pos[2], boxsize)
#print 'particle dist ',particle_dist
Gcut = Gdists < rmax
Scut = Sdists < rmax
Dcut = Ddists < rmax
Gdist_ord = np.argsort(Gdists[Gcut])
Ddist_ord = np.argsort(Ddists[Dcut])
Sdist_ord = np.argsort(Sdists[Scut])
#print Gdists[Gcut][Gdist_ord]
GMenc_vsr = np.cumsum(G['m'][Gcut][Gdist_ord])
SMenc_vsr = np.cumsum(S['m'][Scut][Sdist_ord])
DMenc_vsr = np.cumsum(D['m'][Dcut][Ddist_ord])
# GM_for_r = interp1d(Gdists[Gcut][Gdist_ord], GMenc_vsr, kind='linear', bounds_error=False)
# SM_for_r = interp1d(Sdists[Scut][Sdist_ord], SMenc_vsr, kind='linear', bounds_error=False)
# DM_for_r = interp1d(Ddists[Dcut][Ddist_ord], DMenc_vsr, kind='linear', bounds_error=False)
rspace = np.linspace(min(particle_dists) / 200.0, rmax, num=1000000)
GM_for_r = np.interp(rspace, Gdists[Gcut][Gdist_ord], GMenc_vsr)
SM_for_r = np.interp(rspace, Sdists[Scut][Sdist_ord], SMenc_vsr)
DM_for_r = np.interp(rspace, Ddists[Dcut][Ddist_ord], DMenc_vsr)
#print 'rspace ',rspace
#print 'Ddists[Dcut][Ddist_ord] ',Ddists[Dcut][Ddist_ord]
rspace_physical = rspace * a / h
theM = GM_for_r + SM_for_r + DM_for_r
initpot = (newtonG * theM[0]) / rspace_physical[0]
dpot_array = newtonG * theM / rspace_physical**2.0
if (do_plots):
fig1 = plt.figure(figsize=(10, 9))
plt.plot(rspace, theM, ':r')
plt.savefig('alpha_test_mass.pdf')
fig2 = plt.figure(figsize=(10, 9))
plt.plot(rspace, dpot_array, ':k')
plt.savefig('alpha_test_pot.pdf')
dr = (rspace_physical[-1] - rspace_physical[0]) / 1000000.0
#thepot_ar = scipy.integrate.
thepot_ar = scipy.integrate.cumtrapz(dpot_array,
x=rspace_physical,
dx=dr,
initial=initpot) #this is 0 to r
thepot_cge_ar = thepot_ar * UnitMass_in_g / kpc
mypot = thepot_cge_ar[-1] - np.interp(particle_dists, rspace,
thepot_cge_ar)
testpot = np.interp(1.0, rspace, thepot_cge_ar)
print 'test pot alpha ', testpot
vesc_cge = np.sqrt(mypot) / 1e5 #convert to km/s
return vesc_cge
today = date.today()
print today
z_int_tolerance = 0.5
fhires_tolerance = 0.94
npart_tolerance = 5e4
doplots = 'y'
if (len(sys.argv) < 2):
print 'syntax blah.py haloN'
sys.exit()
haloN = int(sys.argv[1])
H = SF.read_halo_history(haloN)
Zs = H['redshift']
ID = H['ID']
x = H['x']
y = H['y']
z = H['z']
vx = H['vx']
vy = H['vy']
vz = H['vz']
M = H['M']
Mstar = H['Mstar']
Mgas = H['Mgas']
host = H['host']
fhires = H['fhires']
ngas = H['ngas']
sys.exit() finname1 = str(sys.argv[1]) f = open(finname1) dars = np.loadtxt(f) f.close() SF_start = dars[:,13] SF_end = dars[:,15] Mstar = dars[:,8] eta = dars[:,17] epN = dars[:,0] cut1 = Mstar > Mstarlowlim cut2 = Mstar < Mstarupperlim cut = cut1*cut2 foutname = today+'relevant_snaps.txt' f = open(foutname, 'w') count = 0 while (count < len(SF_start[cut])): Nstart = N_for_T(SF_start[cut][count]) Nend = N_for_T(SF_end[cut][count]) print epN[cut][count], Mstar[cut][count]/1e10, Nstart, Nend, eta[cut][count] line = [epN[cut][count], Mstar[cut][count]/1e10, Nstart, Nend, eta[cut][count]] thestring = SF.line_to_string(line) f.write(thestring) count+=1 f.close()
D = readsnap(the_snapdir, Nsnapstring, 1, snapshot_name=the_prefix, extension=the_suffix)
thetime = S['header'][2]
redshift = S['header'][3]
boxsize = S['header'][9]
omega_matter = S['header'][10]
omega_L = S['header'][11]
h = S['header'][12]
a = float(thetime)
print 'using a = ',a
theredshift = (1.0/a - 1)
redshiftstring = "{0:.3f}".format(theredshift)
print 'z = ',"{0:.3f}".format(theredshift)
SFR_time_range, age_in_Gyr = SF.cut_stellar_age(a, Nsnap, S['age'], omega_matter, h)
stellar_age_cut = age_in_Gyr < SFR_time_range/1e9
Syoung = stellar_age_cut
Rstars = where_do_we_go * h / a
RstarsPhys = where_do_we_go
workcount = 0
Hubble = hubble_param(a, omega_matter, h)
###########
#Work function
###########
C = SF.read_halo_catalog(Nsnapstring, redshiftstring)
Nsnapstring,
0,
snapshot_name=the_prefix,
extension=the_suffix)
a = G['header'][2]
redshift = G['header'][3]
redshift1 = redshift
boxsize = G['header'][9]
omega_matter = G['header'][10]
omega_L = G['header'][11]
h = G['header'][12]
redshiftstring = "{0:.3f}".format(redshift)
Hubble = hubble_param(a, omega_matter, h)
halostats = SF.find_halo_now(halo_to_do, a, therod=use_fixed_halos)
haloN = halostats[1]
#read halo catalog, assign halo properties
Rvir = halostats[11]
Vsig = halostats[10]
haloX = halostats[2]
haloY = halostats[3]
haloZ = halostats[4]
haloVX = halostats[5]
haloVY = halostats[6]
haloVZ = halostats[7]
M = halostats[8]
Mstar = halostats[13]
Mgas = halostats[12]
Vmax = halostats[9]
weight_avg_vesc = np.average(vesc_ar[count], weights=sig_ar[count])
print 'weighted average vesc ', weight_avg_vesc
print '25th, 50th, 75th percentile vesc ', vesc_25, vesc_med, vesc_75
weighted_avg_sig = np.average(sig_ar[count],
weights=sig_ar[count]) / area_of_cell
print 'weighted average sig ', weighted_avg_sig
unweighted_avg_sig = np.mean(sig_ar[count]) / area_of_cell
print 'unweighted average sig ', unweighted_avg_sig
myline = [
count, lasta_ar[count], Neps_ar[count], weight_avg_vesc, vesc_25,
vesc_med, vesc_75, weighted_avg_sig, unweighted_avg_sig,
maxSF_ar[count], totMass_ar[count], duration_ar[count]
]
thar.append('z=' + str(lasta_ar[count]))
mystring = SF.line_to_string(myline)
f.write(mystring)
shell_histresults = np.histogram(vesc_ar[count],
num_bins,
range=(0, 1000),
weights=np.array(mass_ar[count]) /
totalmass)
[histx, histy] = ssp.create_plottable_hist(shell_histresults)
plt.plot(histx,
histy,
color=color_ar[count],
ls=ls_ar[count],
lw=2,
alpha=0.5)
count += 1
plt.legend(thar, loc='best')
def gammasfrsnaptestinpput(subdict):
dirneed=subdict['dirneed']
wanted=subdict['wanted']
startno=subdict['startno']
Nsnap=subdict['Nsnap']
snapsep=subdict['snapsep']
the_prefix=subdict['the_prefix']
the_suffix=subdict['the_suffix']
fmeat=subdict['fmeat']
if wanted=='dirgammasfr' or wanted=='dirgamma' or wanted=='dirsfr' or wanted=='dirsm':
plt.figure(figsize=(5,4))
Rfrac=0.25
#Rfrac=0.03
xaxis_snapno=0
normalizedsm=subdict['normalizedsm']
M1labelneed=subdict['M1labelneed']
M1runlabelneed=subdict['M1runlabelneed']
resoneed=subdict['resoneed']
diffusionsolverneed=subdict['diffusionsolverneed']
newlabelneed=subdict['newlabelneed']
strlabelneed=subdict['strlabelneed']
showstarburst=subdict['showstarburst']
legendneed=subdict['legendneed']
correctIa=subdict['correctIa']
refereelabelneed=subdict['refereelabelneed']
for runtodo in dirneed:
print 'runtodo', runtodo
snaplist=[]
enclist=[]
englist=[]
enllist=[]
sml=[]
diskml=[]
bulgeml=[]
nsml=[]
timel=[]
Lgcalist=[]
pretime=0
presnap=startno
havecr=0
if wanted=='dirgammasfr' or wanted=='dirgamma':
info=outdirname(runtodo, Nsnap)
havecr=info['havecr']
if havecr==0:
continue
for i in range(startno,Nsnap, snapsep):
info=outdirname(runtodo, i)
rundir=info['rundir']
maindir=info['maindir']
halostr=info['halostr']
runtitle=info['runtitle']
slabel=info['slabel']
snlabel=info['snlabel']
dclabel=info['dclabel']
resolabel=info['resolabel']
the_snapdir=info['the_snapdir']
Nsnapstring=info['Nsnapstring']
havecr=info['havecr']
Fcal=info['Fcal']
iavesfr=info['iavesfr']
timestep=info['timestep']
cosmo=info['cosmo']
color=info['color']
withinRv=info['withinRv']
usepep=info['usepep']
beginno=info['beginno']
finalno=info['finalno']
firever=info['firever']
initsnap=info['initsnap']
haveB=info['haveB']
M1speed=info['M1speed']
Rvirguess=info['Rvir']
newlabel=info['newlabel']
strlabel=info['strlabel']
labelneed=dclabel
if newlabelneed==1:
labelneed="\n".join(wrap(newlabel,17))
if strlabelneed==1:
labelneed="\n".join(wrap(strlabel,40))
ptitle=title
if runtitle=='SMC':
ptitle='Dwarf'
elif runtitle=='SBC':
ptitle='Starburst'
elif runtitle=='MW':
ptitle=r'$L\star$ Galaxy'
if cosmo==0:
inittime=initsnap
else:
inittime=0
print 'set initial time'
print 'the_snapdir', the_snapdir
print 'Nsnapstring', Nsnapstring
print 'havecr', havecr
print 'withinRv', withinRv
print 'cosmo', cosmo
try:
if cosmo==1:
G = readsnapcr(the_snapdir, Nsnapstring, 0, snapshot_name=the_prefix, extension=the_suffix, havecr=havecr,h0=1,cosmological=1)
S = readsnapcr(the_snapdir, Nsnapstring, 4, snapshot_name=the_prefix, extension=the_suffix, havecr=havecr,h0=1,cosmological=1)
if correctIa==1:
Disk = readsnapcr(the_snapdir, Nsnapstring, 2, snapshot_name=the_prefix, extension=the_suffix, havecr=havecr,h0=1,cosmological=1)
Bulge = readsnapcr(the_snapdir, Nsnapstring, 3, snapshot_name=the_prefix, extension=the_suffix, havecr=havecr,h0=1,cosmological=1)
else:
G = readsnapcr(the_snapdir, Nsnapstring, 0, snapshot_name=the_prefix, extension=the_suffix, havecr=havecr)
S = readsnapcr(the_snapdir, Nsnapstring, 4, snapshot_name=the_prefix, extension=the_suffix, havecr=havecr)
if correctIa==1:
Disk = readsnapcr(the_snapdir, Nsnapstring, 2, snapshot_name=the_prefix, extension=the_suffix, havecr=havecr)
Bulge = readsnapcr(the_snapdir, Nsnapstring, 3, snapshot_name=the_prefix, extension=the_suffix, havecr=havecr)
if havecr>4:
cregyl = G['cregyl']*1e10*solar_mass_in_g*km_in_cm*km_in_cm #in erg (originally in code unit: 1e10Msun*(km/s)^2)
cregyg = G['cregyg']*1e10*solar_mass_in_g*km_in_cm*km_in_cm
if havecr > 0:
cregy_codeunit = G['cregy']
cregy = cregy_codeunit*1e10*solar_mass_in_g*km_in_cm*km_in_cm
Grho = G['rho']
Neb = G['ne']
except KeyError:
print 'Keyerror'
break
try:
header=S['header']
timeneed=header[2]
print 'timeneed', timeneed
Smi=S['m']
Sage=S['age']
if withinRv ==1 and cosmo==1:
Sp = S['p']
Sx = Sp[:,0]
Sy = Sp[:,1]
Sz = Sp[:,2]
header=readsnapcr(the_snapdir, Nsnapstring, 0, snapshot_name=the_prefix, extension=the_suffix, havecr=havecr,h0=1,cosmological=1,header_only=1)
h0 = header['hubble']
atime = header['time']
if usepep==1:
halosA = SF.read_halo_history_pep(rundir, finalno, beginno=beginno,\
singlesnap=0, firever=firever,halonostr=halostr, hubble=h0, comoving=1, maindir=maindir)
afactor=atime
else:
halosA = SF.read_halo_history(rundir, maindir=maindir, halonostr=halostr, hubble=h0, comoving=0)
afactor=1.0
redlist = halosA['redshift']
haloid = halosA['ID']
a_scale = 1.0/(1.0+redlist)
xcenl = halosA['x']*afactor
ycenl = halosA['y']*afactor
zcenl = halosA['z']*afactor
Rvirl = halosA['R']*afactor
xcen = np.interp(atime,a_scale,xcenl)
ycen = np.interp(atime,a_scale,ycenl)
zcen = np.interp(atime,a_scale,zcenl)
Rvir = np.interp(atime,a_scale,Rvirl)
Sxrel = Sx-xcen
Syrel = Sy-ycen
Szrel = Sz-zcen
Sr = np.sqrt(Sxrel*Sxrel+Syrel*Syrel+Szrel*Szrel)
cutrvs = Sr<Rvir*Rfrac
Smi = Smi[cutrvs]
Sage = Sage[cutrvs]
Sm = np.sum(Smi)*1e10 #in solar mass
tcut=Sage>pretime
Nsm = np.sum(Smi[tcut])*1e10
if correctIa==1:
diskm = np.sum(Disk['m'])*1e10
bulgem = np.sum(Bulge['m'])*1e10
except KeyError:
print 'key error'
Sm = 0.
Nsm = 0.
timeneed=0
if correctIa==1:
diskm = 0.
bulgem = 0.
if withinRv ==1:
Gp = G['p']
Gx = Gp[:,0]
Gy = Gp[:,1]
Gz = Gp[:,2]
header=readsnapcr(the_snapdir, Nsnapstring, 0, snapshot_name=the_prefix, extension=the_suffix, havecr=havecr,h0=1,cosmological=1,header_only=1)
h0 = header['hubble']
atime = header['time']
if cosmo==1:
if usepep==1:
halosA = SF.read_halo_history_pep(rundir, finalno,\
beginno=beginno, singlesnap=0, firever=firever,halonostr=halostr,\
hubble=h0, comoving=1, maindir=maindir, snapsep=snapsep)
afactor=atime
else:
halosA = SF.read_halo_history(rundir, maindir=maindir, halonostr=halostr, hubble=h0, comoving=0)
afactor=1.0
redlist = halosA['redshift']
haloid = halosA['ID']
a_scale = 1.0/(1.0+redlist)
xcenl = halosA['x']*afactor
ycenl = halosA['y']*afactor
zcenl = halosA['z']*afactor
Rvirl = halosA['R']*afactor
xcen = np.interp(atime,a_scale,xcenl)
ycen = np.interp(atime,a_scale,ycenl)
zcen = np.interp(atime,a_scale,zcenl)
Rvir = np.interp(atime,a_scale,Rvirl)
else:
xcen=0
ycen=0
zcen=0
Rvir=Rvirguess
Gxrel = Gx-xcen
Gyrel = Gy-ycen
Gzrel = Gz-zcen
Gr = np.sqrt(Gxrel*Gxrel+Gyrel*Gyrel+Gzrel*Gzrel)
cutrv = Gr<Rvir*Rfrac
Grho = Grho[cutrv]
Neb = Neb[cutrv]
if havecr>0:
cregy = cregy[cutrv]
cregy_codeunit = cregy_codeunit[cutrv]
if havecr>4:
cregyl = cregyl[cutrv]
cregyg = cregyg[cutrv]
if cosmo==1:
readtimelist=readtime(firever=2)
snap2list=readtimelist['snaplist']
time2list=readtimelist['timelist']
a2list=readtimelist['alist']
tnow = np.interp(timeneed,a2list,time2list)*1e9
pret = np.interp(pretime,a2list,time2list)*1e9
if havecr>4:
cregygt=np.sum(cregyg)
cregylt=np.sum(cregyl)
if havecr>0:
cregyt =np.sum(cregy)
Lout = outLgamma_nism(Grho,Neb,cregy_codeunit)
Lgcal = np.sum(Lout['Lgamma'])
print 'Lgcal', Lgcal
snaplist.append(float(i))
if cosmo==1:
timel.append(tnow)
else:
timel.append(float(i)*0.98*1e6)
if havecr>0:
enclist.append(cregyt)
if havecr>4:
englist.append(cregygt)
enllist.append(cregylt)
if havecr>0:
Lgcalist.append(Lgcal)
sml.append(Sm)
if correctIa==1:
diskml.append(diskm)
bulgeml.append(bulgem)
nsml.append(Nsm)
pretime=timeneed
del G, S
sml=np.array(sml)
if correctIa==1:
diskml=np.array(diskml)
bulgeml=np.array(bulgeml)
nsml=np.array(nsml)
if havecr>0:
enclist=np.array(enclist)
if havecr>4:
englist=np.array(englist)
enllist=np.array(enllist)
snaplist=np.array(snaplist)
if havecr>0:
Lgcalist=np.array(Lgcalist)
timel=np.array(timel) #in yr
#above is the coefficient for Salpeter only; for Kroupa, the coefficient is 50% larger:
avesfrl=(nsml[1:])/(timel[1:]-timel[:-1]) #in Msun/yr
print 'nsml',nsml
print 'avesfrl', avesfrl
Lsfr = Kroupa_Lsf*avesfrl*solar_mass_in_g/yr_in_sec*cspeed_in_cm_s*cspeed_in_cm_s #times 1.5? 6.2e-4 for Kroupa 3.8e-4 for Salpeter
if correctIa==1:
IaeffSFR=5.3e-8/3.0e-4*(sml[1:]+diskml[1:]+bulgeml[1:])/0.03753/1e9
print 'IaeffSFR', IaeffSFR
LsfrnoIa = Kroupa_Lsf*(avesfrl+IaeffSFR)*solar_mass_in_g/yr_in_sec*cspeed_in_cm_s*cspeed_in_cm_s
print 'Lsfr', Lsfr
print 'timel', timel
if havecr>4:
Lgamma = (enllist[1:]-enllist[:-1])/((timel[1:]-timel[:-1])*yr_in_sec)/(hadronicdecayrate+coulombdecayrate)*hadronicdecayrate*betapi/nopi_per_gamma
Lgamma_sfr = Lgamma/Lsfr
if havecr>0:
Lgcal_sfr = Lgcalist[1:]/Lsfr
if correctIa==1:
Lgamma_sfr_noIa = Lgamma/LsfrnoIa
if haveB>0:
lsn='dashed'
else:
lsn='solid'
if M1labelneed>1 or M1runlabelneed==1:
if M1speed>499:
lsn='solid'
if M1speed>999:
lsn='dashed'
if M1speed>1999:
lsn='dashdot'
if M1speed>3999:
lsn='dotted'
if M1labelneed==1:
if M1speed>499:
labelneed=r'$\tilde{c}=500$'
if M1speed>999:
labelneed=r'$\tilde{c}=1000$'
if M1speed>1999:
labelneed=r'$\tilde{c}=2000$'
if M1speed>3999:
labelneed=r'$\tilde{c}=4000$'
if resoneed==1:
if resolabel=='llr':
labelneed='Lowest res'
lsn = 'solid'
if resolabel=='lr':
labelneed='Low res'
lsn = 'dashed'
if resolabel=='mr':
labelneed='Standard res'
lsn = 'dashdot'
if diffusionsolverneed==1:
if runtodo=='bwmwlrdc27ds':
labelneed='Zeroth moment'
lsn = 'dashed'
else:
labelneed='Two moment'
lsn = 'solid'
if refereelabelneed==1:
if runtodo=='bwsmclrdc28mhdref' or runtodo=='bwmwlrdc28mhdref':
labelneed='Modified'
else:
labelneed='Original'
if xaxis_snapno==1:
xaxisl = snaplist[1:]
xlab = 'snapshot number'
else:
xaxisl = timel[1:]/1e6+inittime
xlab = 'Myr'
if showstarburst==1 and runtitle=='SBC':
if runtodo=='bwsbclr':
pstartno=600
if runtodo=='bwsbclrdc0':
pstartno=590
if runtodo=='bwsbclrdc27':
pstartno=440
if runtodo=='bwsbclrdc28':
pstartno=505
if runtodo=='bwsbclrdc29':
pstartno=370
print 'labelneed', labelneed
if wanted=='dirgammasfr':
if havecr>4:
#plt.plot(xaxisl, np.absolute(Lgamma_sfr), color=color,ls=lsn,lw=2, label=labelneed)
if (M1labelneed==1 and color=='r'):
plt.plot(xaxisl, np.absolute(Lgamma_sfr), color=color,ls=lsn,lw=2)
elif (M1labelneed==2 and lsn=='solid'):
plt.plot(xaxisl, np.absolute(Lgamma_sfr), color=color,ls=lsn,lw=2, label=labelneed)
else:
plt.plot(xaxisl, np.absolute(Lgamma_sfr), color=color,ls=lsn,lw=2, label=labelneed)
#print 'M1speed', M1speed
print 'Lgamma_sfr', Lgamma_sfr
elif havecr>0:
plt.plot(xaxisl, np.absolute(Lgcal_sfr), color=color,ls=lsn,lw=2, label=labelneed)
print 'Lgcal_sfr', Lgcal_sfr
if correctIa==1 and havecr>0:
plt.plot(xaxisl, np.absolute(Lgamma_sfr_noIa),ls=lsn,lw=2, color=color)
print 'Lgamma_sfr_noIa', Lgamma_sfr_noIa
if wanted=='dirgamma':
if havecr>4:
plt.plot(xaxisl, np.absolute(Lgamma), color=color,ls=lsn,lw=2, label=labelneed)
elif havecr>0:
plt.plot(xaxisl, np.absolute(Lgcalist[1:]), color=color,ls=lsn,lw=2, label=labelneed)
if wanted=='dirsfr':
if M1labelneed==1 and color=='r':
plt.plot(xaxisl, np.absolute(avesfrl), color=color,ls=lsn,lw=2)
elif M1speed<501 and (M1runlabelneed==1 or M1labelneed==1):
plt.plot(xaxisl, np.absolute(avesfrl), color=color,ls=lsn,lw=2, label=labelneed)
else:
plt.plot(xaxisl, np.absolute(avesfrl), color=color,ls=lsn,lw=2, label=labelneed)
if showstarburst==1 and runtitle=='SBC':
plt.axvline(x=pstartno, color=color,ls=lsn,lw=1)
if wanted=='dirsm':
if M1labelneed==1 and color=='r':
if normalizedsm==1:
plt.plot(xaxisl, sml[:-1]-sml[0], color=color,ls=lsn,lw=2)
else:
plt.plot(xaxisl, sml[1:], color=color,ls=lsn,lw=2)
else:
if normalizedsm==1:
plt.plot(xaxisl, sml[:-1]-sml[0], color=color,ls=lsn,lw=2, label=labelneed)
else:
plt.plot(xaxisl, sml[1:], color=color,ls=lsn,lw=2, label=labelneed)
if showstarburst==1 and runtitle=='SBC':
plt.axvline(x=pstartno, color=color,ls='dashed',lw=1)
if wanted=='dirgammasfr':
plt.axhline(y=0.0002,ls='--',color='k')
plt.yscale('log')
if runtitle=='SMC' and legendneed==1:
plt.legend(loc='best', fontsize=8)
elif legendneed==1 and M1runlabelneed==1:
plt.legend(loc='best', fontsize=8,ncol=2)
plt.xlabel(xlab, fontsize=16)
plt.ylabel(r'$L_{\gamma}/L_{\rm SF}$', fontsize=16)
figname=plotloc+'CRplot/dirgammasfr/gammasfrsnap_'+fmeat+'.pdf'
if wanted=='dirgamma':
plt.yscale('log')
if runtitle=='SMC' or legendneed==1:
plt.legend(loc='best', fontsize=8,ncol=3)
if legendneed==1 and M1runlabelneed:
plt.legend(loc='best', fontsize=8,ncol=2)
plt.xlabel(xlab, fontsize=16)
plt.ylabel(r'$L_{\gamma} {\rm erg/s}$', fontsize=16)
figname=plotloc+'CRplot/dirgamma/gammasnap_'+fmeat+'.pdf'
if wanted=='dirsfr':
plt.yscale('log')
if runtitle=='SMC' or legendneed==1:
plt.legend(loc='best', fontsize=8,ncol=3)
if M1labelneed==1 and legendneed==1:
plt.legend(loc='best', fontsize=8,ncol=2)
plt.xlabel(xlab, fontsize=16)
plt.ylabel(r'${\rm SFR (M_{\odot}/yr)} $', fontsize=16)
figname=plotloc+'CRplot/dirsfr/sfrsnap_'+fmeat+'.pdf'
if wanted=='dirsm':
if runtitle=='SMC' and legendneed==1:
if strlabelneed==1 or M1labelneed==1:
plt.legend(loc='best', fontsize=10,ncol=2)
else:
plt.legend(loc='best', fontsize=8,ncol=3)
plt.xlabel('Myr', fontsize=16)
plt.ticklabel_format(style='sci',axis='y',scilimits=(0,0))
if normalizedsm==1:
plt.ylabel(r'${\rm M_{*,new} (M_{\odot})} $', fontsize=16)
else:
plt.ylabel(r'${\rm M_* (M_{\odot})} $', fontsize=16)
if normalizedsm==1:
figname=plotloc+'CRplot/dirsm/nsm_'+fmeat+'.pdf'
else:
figname=plotloc+'CRplot/dirsm/sm_'+fmeat+'.pdf'
print 'Saving ', figname
plt.title(ptitle,fontsize=16)
plt.tick_params(axis='both', which='both',direction='in',bottom=True,top=True,left=True,right=True,labelsize=16)
plt.subplots_adjust(left = 0.18, bottom=0.15, right=0.95, top=0.9)
#plt.tight_layout()
plt.savefig(figname)
plt.clf()
return None
dists = SF.calcdist2(haloX, haloY, haloZ, Stars['p'][:,0], Stars['p'][:,1], Stars['p'][:,2], boxsize) cut = dists < theRvir * rvirFac StellarMass = np.sum(Stars['m'][cut]) StellarDens = StellarMass / ((4.0/3.0) * 3.14159 * (theRvir* rvirFac)**3.0) return StellarDens if (len(sys.argv)<2): print 'syntax blah.py haloN [Zmin]' sys.exit() haloN = int(sys.argv[1]) halo_number_string = str(haloN) if (haloN < 10): halo_number_string='0'+halo_number_string H = SF.read_halo_history(haloN, rod=use_fixed_halos) Zs = H['redshift'] ID = H['ID'] x = H['x'] y = H['y'] z = H['z'] vx = H['vx'] vy = H['vy'] vz = H['vz'] M = H['M'] Mstar = H['Mstar'] Mgas = H['Mgas'] host = H['host'] fhires = H['fhires'] ngas = H['ngas']
def calculate_escape_velocity(halo_pos, particle_pos, G, S, D, rmax):
newtonG = 6.67384e-8
pc = 3.08567758e18
kpc = pc * 1e3
a = G['header'][2]
h = G['header'][12]
boxsize = G['header'][9]
UnitMass_in_g=1.989e43 / h
do_plots = False
Gdists = SF.calcdist2(halo_pos[0], halo_pos[1], halo_pos[2], G['p'][:,0], G['p'][:,1], G['p'][:,2], boxsize)
Sdists = SF.calcdist2(halo_pos[0], halo_pos[1], halo_pos[2], S['p'][:,0], S['p'][:,1], S['p'][:,2], boxsize)
Ddists = SF.calcdist2(halo_pos[0], halo_pos[1], halo_pos[2], D['p'][:,0], D['p'][:,1], D['p'][:,2], boxsize)
particle_dists = SF.calcdist2(halo_pos[0], halo_pos[1], halo_pos[2], particle_pos[0], particle_pos[1], particle_pos[2], boxsize)
#print 'particle dist ',particle_dist
Gcut = Gdists < rmax
Scut = Sdists < rmax
Dcut = Ddists < rmax
Gdist_ord = np.argsort(Gdists[Gcut])
Ddist_ord = np.argsort(Ddists[Dcut])
Sdist_ord = np.argsort(Sdists[Scut])
#print Gdists[Gcut][Gdist_ord]
GMenc_vsr = np.cumsum(G['m'][Gcut][Gdist_ord])
SMenc_vsr = np.cumsum(S['m'][Scut][Sdist_ord])
DMenc_vsr = np.cumsum(D['m'][Dcut][Ddist_ord])
# GM_for_r = interp1d(Gdists[Gcut][Gdist_ord], GMenc_vsr, kind='linear', bounds_error=False)
# SM_for_r = interp1d(Sdists[Scut][Sdist_ord], SMenc_vsr, kind='linear', bounds_error=False)
# DM_for_r = interp1d(Ddists[Dcut][Ddist_ord], DMenc_vsr, kind='linear', bounds_error=False)
rspace = np.linspace(min(particle_dists)/200.0, rmax, num=1000000)
GM_for_r = np.interp(rspace, Gdists[Gcut][Gdist_ord], GMenc_vsr)
SM_for_r = np.interp(rspace, Sdists[Scut][Sdist_ord], SMenc_vsr)
DM_for_r = np.interp(rspace, Ddists[Dcut][Ddist_ord], DMenc_vsr)
#print 'rspace ',rspace
#print 'Ddists[Dcut][Ddist_ord] ',Ddists[Dcut][Ddist_ord]
rspace_physical = rspace*a / h
theM = GM_for_r + SM_for_r + DM_for_r
initpot = (newtonG * theM[0])/rspace_physical[0]
dpot_array = newtonG * theM / rspace_physical**2.0
if (do_plots):
fig1 = plt.figure(figsize=(10,9))
plt.plot(rspace, theM, ':r')
plt.savefig('alpha_test_mass.pdf')
fig2 = plt.figure(figsize=(10,9))
plt.plot(rspace, dpot_array, ':k')
plt.savefig('alpha_test_pot.pdf')
dr = (rspace_physical[-1] - rspace_physical[0])/1000000.0
#thepot_ar = scipy.integrate.
thepot_ar = scipy.integrate.cumtrapz(dpot_array, x=rspace_physical, dx=dr, initial=initpot) #this is 0 to r
thepot_cge_ar = thepot_ar * UnitMass_in_g / kpc
mypot = thepot_cge_ar[-1] - np.interp(particle_dists, rspace, thepot_cge_ar)
testpot = np.interp(1.0, rspace, thepot_cge_ar)
print 'test pot alpha ',testpot
vesc_cge = np.sqrt(mypot) / 1e5 #convert to km/s
return vesc_cge
def calc_stellar_dens(Stars, haloX, haloY, haloZ, theRvir, rvirFac, boxsize): dists = SF.calcdist2(haloX, haloY, haloZ, Stars['p'][:,0], Stars['p'][:,1], Stars['p'][:,2], boxsize) cut = dists < theRvir * rvirFac StellarMass = np.sum(Stars['m'][cut]) StellarDens = StellarMass / ((4.0/3.0) * 3.14159 * (theRvir* rvirFac)**3.0) return StellarDens
today = date.today() print today z_int_tolerance = 0.5 fhires_tolerance = 0.94 npart_tolerance = 5e4 doplots = 'y' if (len(sys.argv)<2): print 'syntax blah.py haloN' sys.exit() haloN = int(sys.argv[1]) H = SF.read_halo_history(haloN) Zs = H['redshift'] ID = H['ID'] x = H['x'] y = H['y'] z = H['z'] vx = H['vx'] vy = H['vy'] vz = H['vz'] M = H['M'] Mstar = H['Mstar'] Mgas = H['Mgas'] host = H['host'] fhires = H['fhires'] ngas = H['ngas']
StellarMass = np.sum(Stars['m'][cut])
StellarDens = StellarMass / ((4.0 / 3.0) * 3.14159 *
(theRvir * rvirFac)**3.0)
return StellarDens
if (len(sys.argv) < 2):
print 'syntax blah.py haloN [Zmin]'
sys.exit()
haloN = int(sys.argv[1])
halo_number_string = str(haloN)
if (haloN < 10):
halo_number_string = '0' + halo_number_string
H = SF.read_halo_history(haloN, rod=use_fixed_halos)
Zs = H['redshift']
ID = H['ID']
x = H['x']
y = H['y']
z = H['z']
vx = H['vx']
vy = H['vy']
vz = H['vz']
M = H['M']
Mstar = H['Mstar']
Mgas = H['Mgas']
host = H['host']
fhires = H['fhires']
ngas = H['ngas']
Total_metal_mass = (np.sum(Stellar_met*S['m']) + np.sum(Metallicity*G['m']))
OxyYield = (np.sum(Stellar_oxygen*S['m']) + np.sum(Gas_oxygen*G['m'])) / np.sum(S['m'])
EmpiricalYield = Total_metal_mass / np.sum(S['m'])
a = G['header'][2]
z = 1.0/a - 1.0
redshift = G['header'][3]
boxsize = G['header'][9]
omega_matter = G['header'][10]
omega_L = G['header'][11]
h = G['header'][12]
redshiftstring = "{0:.3f}".format(redshift)
Hubble = hubble_param(a, omega_matter, h)
PhysTemp, PhysRho = SF.convertTemp(G['u'], G['ne'], G['rho'], h)
halostats = SF.find_halo_now(halo_to_do, a, therod=use_fixed_halos)
print 'halo stats', halostats
haloN = halostats[1]
#read halo catalog, assign halo properties
Rvir = halostats[11]
Vsig = halostats[10]
haloX = halostats[2]
haloY = halostats[3]
haloZ = halostats[4]
haloVX =halostats[5]
haloVY = halostats[6]
haloVZ = halostats[7]
f = open(finname1)
dars = np.loadtxt(f)
f.close()
SF_start = dars[:, 13]
SF_end = dars[:, 15]
Mstar = dars[:, 8]
eta = dars[:, 17]
epN = dars[:, 0]
cut1 = Mstar > Mstarlowlim
cut2 = Mstar < Mstarupperlim
cut = cut1 * cut2
foutname = today + 'relevant_snaps.txt'
f = open(foutname, 'w')
count = 0
while (count < len(SF_start[cut])):
Nstart = N_for_T(SF_start[cut][count])
Nend = N_for_T(SF_end[cut][count])
print epN[cut][count], Mstar[cut][count] / 1e10, Nstart, Nend, eta[cut][
count]
line = [
epN[cut][count], Mstar[cut][count] / 1e10, Nstart, Nend,
eta[cut][count]
]
thestring = SF.line_to_string(line)
f.write(thestring)
count += 1
f.close()