def generate_pdf_tables():
tabout = []
if (PROJ == "perpendicular"):
ioncds = ioformat.rcol(fnamex, cols, separator=",", linestart=1)
foutname = "pdfs/" + modelstr + "_i9_x_pdf.dat"
else:
ioncds = ioformat.rcol(fnamey, cols, separator=",", linestart=1)
foutname = "pdfs/" + modelstr + "_i9_y_pdf.dat"
edges = linspace(0., 1., NCELLS + 1)
# pdb.set_trace()
for i in range(9):
idx = ionidxs[i]
if (idx == -1):
tabout.append(array([0.0] * (NCELLS + 1)))
print("---")
continue
ionname = ionnames[idx]
print(ionname)
ioncds[idx - 1].sort()
# pdb.set_trace()
prob = log10(ioncds[idx - 1][::-1][:NPIXLIM][::(int)(NPIXLIM /
NCELLS)][:NCELLS +
1])
# prob = log10(ioncds[idx-1][::-1][:NPIXLIM][::(int)(NPIXLIM/NCELLS)-1])
tabout.append(prob)
fout = open(foutname, "w")
fout.write("#P(>logN) HI HeII CIII CIV OIV OVI NeVIII MgII SiIV\n")
for i in range(NCELLS + 1):
line = "%5.3f " % (edges[i])
for j in range(9):
line += "%6.3f " % (tabout[j][i])
line += "\n"
fout.write(line)
fout.close()
def read_gal_data(skidbase, snapstr):
fgal = "%s/gal_z%s.stat" % (skidbase, snapstr)
fso = "%s/so_z%s.sovcirc" % (skidbase, snapstr)
mstar = ioformat.rcol(fgal, [4])
mvir = ioformat.rcol(fso, [1], linestart=1)
gals = []
for i in range(len(mstar)):
gals.append(skidgal(mstar[i], mvir[i]))
return gals
def plot_smhm_model(mi, axs, shade=False, mhcorr=1.0):
modelname = models[mi]
clr = clrs[mi]
smhmlist = [\
fbase + modelname + "/" + "smhm_" + zstr2[0]+".txt",
fbase + modelname + "/" + "smhm_" + zstr2[1]+".txt",
fbase + modelname + "/" + "smhm_" + zstr2[2]+".txt",
fbase + modelname + "/" + "smhm_" + zstr2[3]+".txt"
]
for i in range(len(smhmlist)):
# ms, mvir, flag, mh = ioformat.rcol(smhmlist[i], [0,1,2,3], linestart=1)
ms, mh, flag = ioformat.rcol(smhmlist[i], [0,1,2], linestart=1)
x, y = [], []
mh = array(mh) / mhcorr
for j in range(len(flag)):
if(flag[j] == 1.0): # Only plot the central
x.append(mh[j])
if(PLOT_MASS_RATIO == True): y.append(ms[j]/mh[j])
else: y.append(ms[j])
# plt.plot(x, y, "b.", alpha=0.2)
x, y = bin1d.subsample(x, y, nonzero=True)
s = bin1d.bin1d(x, y, nbins=40, logbins=True, bounds=0.95)
xline, yline = log10(s.cen), log10(s.median)
uline, lline = log10(s.ubound), log10(s.lbound)
axs[i].plot(xline, yline, "-", color=clr, linewidth=2)
maxidx = -4
if(shade == True):
axs[i].fill(append(xline[:maxidx],xline[maxidx-1::maxidx+1]), append(uline[:maxidx],lline[maxidx-1::maxidx+1]), color=colors[i], alpha=0.2)
def build_mvir_bins(stars, soname):
msub = ioformat.rcol(soname, [6], linestart=1)
flag = [0] * len(msub)
mvbins = binned_by_virial_mass(nbins=40, mmin=10.0, mmax=14.0)
for s in stars: # loop over all stars
hidx = s['HID']-1
mvir = msub[hidx] / HUBBLEPARAM
if(isinf(log10(mvir))): continue
bidx = mvbins.find_idx_for_bin(log10(mvir))
mvbins.stotal[bidx] += s['StarMass']
mvbins.total[bidx] += s['Mass']
if(s['a_last'] == 0): # primordial
if(s['Tmax'] > TMAX_CUT):
mvbins.hot[bidx] += s['Mass'] - s['WindMass']
mvbins.whot[bidx] += s['WindMass']
else:
mvbins.cold[bidx] += s['Mass'] - s['WindMass']
mvbins.wcold[bidx] += s['WindMass']
elif(s['a_last'] < 0): # wind
if(abs(s['Tmax']) > TMAX_CUT): mvbins.whot[bidx] += s['Mass']
else: mvbins.wcold[bidx] += s['Mass']
else: mvbins.other[bidx] += s['Mass']
if(flag[hidx] == 0):
flag[hidx] = 1
mvbins.totalmass[bidx] += mvir
mvbins.totalmass *= (OMEGAB / OMEGAM) * 2.0e33
return mvbins
def read_sm(mh):
fname = SMBASE
fname += sm_name_prefix
i = (int)(mh - 11.0)
fname += mhstrs[i] + sm_name_suffix
print ("Reading: ", fname)
a, frac, e1, e2 = ioformat.rcol(fname, [0,1,2,3])
return a, frac, e1, e2
def show():
import matplotlib.pyplot as plt
x, y, z = ioformat.rcol(foutname, [1, 2, 3])
plt.plot(x, z, "b.-")
for i in range(len(x)):
plt.text(x[i], z[i], str(400 - i), fontsize=6)
plt.axis([-0.5, 0.5, -0.5, 0.5])
plt.show()
def read_smmr(z, mhthen=False):
fname = SMMRBASE
fname += smmr_name_prefix
if(mhthen == True): fname += "then_"
i = (int)(z)
fname += zstrs[i] + smmr_name_suffix
print ("Reading: ", fname)
mh, dm, e1, d2 = ioformat.rcol(fname, [0,1,2,3], linestart=1)
return mh, dm, e1, d2
def write_starhost_file(modelname, unit_m):
# modelname = "l50n288-phew-m5"
# unit_m = 3.4e6 * 8.
galname, soname, finname, foutname = find_fnames(modelname)
stars = genfromtxt(finname, names=True)
mstar = ioformat.rcol(galname, [4], linestart=0)
msub = ioformat.rcol(soname, [6], linestart=1)
mstar = log10(array(mstar) * unit_m * 1.e10 / 0.7)
msub = log10(array(msub) / 0.7)
stars['Mass'] *= unit_m * 1.e10 / 0.7
print "Start Writing"
fout = open(foutname, "w")
fout.write("#Mass Mstar Msub Tmax Flag\n")
for s in stars:
gidx, hidx = (int)(s['GID']) - 1, (int)(s['HID']) - 1
if (gidx < 0 or hidx < 0): continue
ms, mh = mstar[gidx], msub[hidx]
if (gidx == hidx): flag = 1
else: flag = 0
line = "%7.5e %6.3f %6.3f %5.3f %d\n" % \
(s['Mass'], ms, mh, s['Tmax'], flag)
fout.write(line)
fout.close()
def draw(ax=None, pcolor="blue", marker="o", tshift=0.0):
x, y, z = ioformat.rcol(galname, [18, 19, 20])
x = (array(x) + 0.5) * LBOX
y = (array(y) + 0.5) * LBOX
z = (array(z) + 0.5) * LBOX
msub, rsub = ioformat.rcol(soname, [6, 7], linestart=1)
print ("Start Drawing.")
if(ax == None):
fig = plt.figure(figsize=(8,8))
ax = fig.add_subplot(111)
n = 0
# xs, ys, sizes = [], [], []
for i in range(len(x)):
if(msub[i] == 0): continue
if(XYRANGE == True):
if(x[i] < XRANGE[0] or x[i] > XRANGE[1]): continue
if(y[i] < YRANGE[0] or y[i] > YRANGE[1]): continue
if(z[i] < ZRANGE[0] or z[i] > ZRANGE[1]): continue
if(log10(msub[i] / HUBBLEPARAM) > MSUB_MIN):
# xs.append(x[i])
# ys.append(y[i])
# sizes.append(rsub[i] / 1.e3) # Convert to kpc
plt.gca().add_artist(Circle((x[i], y[i]), rsub[i]/1.e3, alpha=0.6, fc="blue"))
if(LABEL == True):
lbl = "%d %4.1f" % (i+1, log10(msub[i]/HUBBLEPARAM))
plt.text(x[i], y[i], lbl, fontsize=6)
# print xs[-1], ys[-1], sizes[-1]
n += 1
print ("Number of Galaxies Shown: ", n)
# ax.scatter(x, y, s=sizes, alpha=0.6, color=pcolor, marker=marker)
# ax.plot(xs, ys, "r.", markersize=5)
ax.set_xlim(XBOUNDS)
ax.set_ylim(YBOUNDS)
ax.set_xlabel("Mpc/h")
ax.set_ylabel("Mpc/h")
plt.savefig("/scratch/shuiyao/figures/tmp.png")
def find_total_mass(stars, soname):
mtot = 0.0
msub = ioformat.rcol(soname, [6], linestart=1)
ncount = 0
for s in stars:
m = msub[s['HID'] - 1]
if(m > 0):
mtot += m
ncount += 1
msub[s['HID'] - 1] = 0.0 # Once added, reset to 0 to prevent repeated counting
mtot = mtot / HUBBLEPARAM
print ("Total amount of haloes found: %d." % (ncount))
print (" - Average mass (log): %5.2f." % log10((mtot / float(ncount))))
mtot = mtot * 2.e33
return mtot
def draw_frame():
from matplotlib.lines import Line2D
from pltastro import legend
lgd1 = legend.legend(axs[0])
lgd1.loc = "lower left"
# lgd1.addLine((lgds[2], "black", ":", 1))
for i in range(len(lgds)):
lgd1.addLine((lgds[i], "black", lstyles[i], 1))
lgd1.draw()
lgd2 = legend.legend(axs[0])
lgd2.loc = "lower right"
lgd2.addLine(("cold", "blue", "-", 1))
lgd2.addLine(("hot", "red", "-", 1))
# lgd2.addLine(("cold wind", "cyan", "-", 1))
# lgd2.addLine(("hot wind", "magenta", "-", 1))
# lgd2.addLine(("hot wind", "magenta", "-", 1))
if(SHOW_ALLWINDS):
lgd2.addLine(("all wind", color_allw, "-", 1))
lgd2.draw()
FBEHROOZI = DIRS['SCI']+"REFERENCES/behroozi13/smmr/"
if(REDSHIFT == 2.0):
snapnum, zstr_behroozi = "058", "2.00"
if(REDSHIFT == 0.0):
snapnum, zstr_behroozi = "108", "0.10"
if(REDSHIFT == 1.0):
snapnum, zstr_behroozi = "078", "1.00"
if(REDSHIFT == 0.25):
snapnum, zstr_behroozi = "098", "0.10"
mh, ms, err1, err2 = ioformat.rcol(FBEHROOZI+"c_smmr_z"+zstr_behroozi+"_red_all_smf_m1p1s1_bolshoi_fullcosmos_ms.dat", [0,1,2,3], linestart=1)
ms = array(ms) - log10(0.156)
axs[0].plot(mh, ms, "o", color="green", markersize=6)
axs[0].errorbar(mh, ms, yerr=[err1, err2], color="green")
axs[0].set_title("z = "+str(REDSHIFT)[:3], fontsize=16)
axs[0].plot([10.9, 10.9], [-4.0, -0.5], "k--")
axs[0].plot([10.0, 10.0], [-4.0, -0.5], "k-")
axs[1].plot([10.9, 10.9], [0.0, 1.1], "k--")
axs[1].plot([10.0, 10.0], [0.0, 1.1], "k-")
plt.savefig(DIRS['FIGURE']+"tmp.pdf")
plt.show()
def plot_last_signal():
mvir, rvir, rlast, mclast = ioformat.rcol(fwind, [8, 10, 6, 5], linestart=1)
mbin_min = [11.25, 11.75, 12.25, 12.75]
mbin_max = [11.75, 12.25, 12.75, 13.75]
clrs = ["magenta", "red", "orange", "yellow"]
wpmbin = []
class mvir_bin():
def __init__(self, mmin, mmax):
self.mmin = mmin
self.mmax = mmax
self.rlast = []
self.rratio = []
self.mclast = []
ax = plt.figure(1, figsize=(6,6)).add_subplot(111)
for i in range(len(mbin_min)):
wpmbin.append(mvir_bin(mbin_min[i], mbin_max[i]))
for j in range(len(mvir)):
if (mbin_min[i] < mvir[j] < mbin_max[i]):
wpmbin[-1].rlast.append(rlast[j])
wpmbin[-1].mclast.append(mclast[j])
wpmbin[-1].rratio.append(rlast[j]/rvir[j])
# x, y = bin1d.subsample(wpmbin[-1].mclast, wpmbin[-1].rlast, nonzero=True)
# print len(wpmbin[-1].mclast), len(wpmbin[-1].rratio)
if(len(wpmbin[-1].mclast) > 0):
x, y = bin1d.subsample(wpmbin[-1].mclast, wpmbin[-1].rratio, nonzero=True)
s = bin1d.bin1d(x, y, nbins=10, bounds=boundsvalue)
xline, yline = s.value, s.median
uline, lline = s.ubound, s.lbound
p, = ax.plot(xline, yline, "-", color=clrs[i]) # Draw line for all models
pf, = plt.fill(xline+xline[::-1], uline+lline[::-1], color=clrs[i], alpha=alphavalue)
plt.ylabel(r'$r_{last} / R_{vir}$')
plt.xlabel(r'$Mc_{last}$')
legends = []
legends.append(mpatches.Patch(color="yellow"))
legends.append(mpatches.Patch(color="orange"))
legends.append(mpatches.Patch(color="red"))
legends.append(mpatches.Patch(color="magenta"))
plt.legend(legends, [r'$12.75<M_{vir}<13.75$',r'$12.25<M_{vir}<12.75$',r'$11.75<M_{vir}<12.25$',r'$11.25<M_{vir}<11.75$'], loc=1, fontsize=12)
plt.show()
def Mclast():
fig = plt.figure(1, figsize=(6,9))
gs = gridspec.GridSpec(2,1,height_ratios=[4,1])
ax = plt.subplot(gs[0])
mvir, mclast, mratio = ioformat.rcol(fwind, [1,5,14], linestart=1)
print("Mvir Range: ", min(mvir), max(mvir))
x, y = [], []
for i in range(len(mclast)):
if(mclast[i] > mclast_cut and mratio[i] < 20.0):
x.append(mvir[i])
y.append(mclast[i])
xbins = linspace(11.0, 13.5, 30)
ybins = linspace(0.05, 1.0, 40)
xgrid, ygrid = meshgrid(xbins, ybins)
z, edx, edy = histogram2d(x, y, bins=[xbins,ybins])
z = z.T + 0.01
zf = ndimage.gaussian_filter(z, sigma=1.0, order=0)
cont = ax.contour(xbins[1:], ybins[1:], zf, colors="red")
#plt.pcolor(xgrid, ygrid, z, cmap="Purples", norm=LogNorm(vmin=z.min(), vmax=z.max()))
ax.pcolor(xgrid, ygrid, z, cmap="Purples")
setp(ax.get_xticklabels(), visible=False)
ax.set_ylabel("Mc (Rejoin)")
plt.title(modelname+", Z~1.0")
ax = plt.subplot(gs[1])
plt.subplots_adjust(hspace=0.0, top=0.9, bottom=0.15)
hist1, bins = histogram(mvir, bins=linspace(11.0,13.5,30))
hist2, bins = histogram(x, bins=linspace(11.0,13.5,30))
hist = []
for i in range(len(hist1)):
if(hist1[i] > 0): hist.append(float(hist2[i])/float(hist1[i]))
else: hist.append(0.0)
#width=0.8*(bins[1]-bins[0])
center = (bins[:-1] + bins[1:]) / 2.0
ax.plot(center, hist, "b.-")
ax.set_ylim(0.0, 1.0)
ax.set_xlabel("Mvir")
ax.set_ylabel("f_rej")
plt.show()
def load_files():
global pids
global mass
global hid
global attrs
global haloes
print("Loading Files... ")
hf = h5py.File(snapname, "r")
header = hf['Header']
attrs = header.attrs
attrs.keys()
gp = hf['PartType0']
gp.keys()
pids = gp['ParticleIDs']
mass = gp['Masses']
hid = ioformat.rcol(sogrpname, [0], [0])
haloes = genfromtxt(sovcircname,
usecols=(1, 2, 6, 7),
names=['Mvir', 'Rvir', 'Msub', 'Rsub'],
skip_header=1)
mlra = 4.46e-15 * 1.e7**2 / (rho0 * r_c**2) print log(mlra * 50. * ac.myr) # https://www.dropbox.com/home/Ion%20Analysis # Very crudely read from J'Neil's absorption images # x300v1000: # OVI 13 - 14; # HI 13 - 18 # CIV 15 - 17 # x300v1700: # HI 17 - 18 # CIV 15 - 16 # OVI 13 - 14 ionfile = "/scratch/shuiyao/specexbin/ionfiles/specions_i9_gizmo.dat" fmass = ioformat.rcol(ionfile, [4]) n_c = 1.0 rho_c = n_c * pc.mh * 0.62 r_c = 100 * ac.pc M_c = 4. / 3. * pi * r_c**3 * rho_c Z = Zsolar = 0.0122 print "Mc = ", M_c / ac.msolar # On average: N_c = 4. / 3. * n_c * pi * r_c print "N_c (avg.) = ", N_c # Scale: n_c ~ r_c ^ (-3), N_c ~ n_c * r_c ~ r_c ^ (-2) print "N_c (peak) ~ N_c (avg.) * 25." from ionfrac import IonFrac
zmin = [2.0, 1.0]
MMIN, MMAX = 10.5, 13.0
NMBINS = 15
fig = plt.figure(1, figsize=(8, 7))
gs = gridspec.GridSpec(3, 2, height_ratios=[4, 1, 1])
patterns = []
for zi in [0, 1]:
ax1 = plt.subplot(gs[zi])
ax2 = plt.subplot(gs[zi + 2])
ax3 = plt.subplot(gs[zi + 4])
for fi, fwind in enumerate(flist[zi]):
if (DO_TMAX):
fwindtmax = fwind[:-3] + "_tmax." + fwind[-2:]
tmaxs = ioformat.rcol(fwindtmax, [0])
x, y, xhot, xhotsub, yhot, yhotsub = [], [], [], [], [], []
# ai, af, msi(FoF), msf(FoF), mstar(SKID), mvir(SO), flag(sopar)
ai, af, mstar, mvir, flag = ioformat.rcol(fwind, [1, 2, 5, 6, 8], [4],
linestart=1)
zs = 1. / array(ai) - 1.
trec = calc_trec(ai, af, True)
tlim = calc_trec([1. / (zmin[zi] + 1.)], [0.9999], True)
for i in range(len(trec)):
if (mvir[i] > MMIN and flag[i] == 1):
# WARNING: In some earlier version, there's a bug that for ungrouped particles, mvir = -inf but mstar = mstar[-1]. So make sure use mvir[i] > MMIN is fine, but using mstar[i] would not be fine.
x.append(mvir[i])
y.append(trec[i])
if (DO_TMAX):
if (tmaxs[i] > 5.5): # Winds that became hot
xhot.append(mvir[i])
elif (REDSHIFT == 1.0):
AMIN, AMAX, odir = "0.500", amaxs[2], FBASE + "z1/"
elif (REDSHIFT == 0.2):
AMIN, AMAX, odir = "0.833333", amaxs[3], FBASE + "z0/"
else:
print(errormsg)
sys.exit(1)
if (os.path.exists(odir) == 0):
print(errormsg)
print("Error: ", FBASE, "not found. Exit.")
sys.exit(1)
print("Ncpu = ", NCPU)
print("Directory: ", odir)
widfile = odir + "wid.dat"
wids = ioformat.rcol(widfile, [0], [0])
wids = set(wids) # Enabling fast search with wid in wids
print(len(wids), "Wind IDs read...")
tstart = time.time()
tmid = tstart
for icpu in range(NCPU):
print("Search File #", icpu, " | t = ", time.time() - tmid)
tmid = time.time()
ifile = open(FBASE + "phews." + str(icpu), "r")
ofile = open(odir + "phews." + str(icpu), "w")
ifile.readline()
for line in ifile:
spt = line.split()
if (spt[0] > "1"): continue # a > 1, never should happen
if (spt[0] < AMIN): continue # a < amin, Not selected
# mstars = array(mstars)
# hostmask = (halos['Msub'] > 0) & (mstars > 0)
# mstars = mstars[hostmask]
# msubs = log10(halos[hostmask]['Msub'] / HPARAM)
# # mfits = interp1d(msubs[::10], mstars[::10], kind="quadratic")
# mask = (msubs > 11.0) & (mstars > 8.0)
# msubs = msubs[mask]
# mstars = mstars[mask]
# coefs = polyfit(msubs, mstars, 2)
# x = linspace(10., 13.5, 100)
# y = polyval(coefs, x)
# plt.plot(msubs[::3], mstars[::3], "b.", alpha=0.4)
# plt.plot(x, y, "r-")
sohid = ioformat.rcol(sogrpname, [0], [0], linestart=1)
hf = h5py.File(snapname, "r")
print("File Read.")
header = hf['Header'] # Read the header
Ngas = header.attrs['NumPart_Total'][0]
Ndark = header.attrs['NumPart_Total'][1]
Nstar = header.attrs['NumPart_Total'][4]
gp = hf['PartType0'] # Gas Particles
gp.keys()
print("Reading HDF5: ", snapname)
# Get gas properties
mass = array(gp['Masses']) # Mass
u = array(gp['InternalEnergy']) # Temperature in K
def V25Vc(fname, ax1, ax2, titlename, simname):
import cosmology
if (FFORMAT == "OLD"):
mvir, rvir, vinit, v25 = ioformat.rcol(fname, [1, 2, 3, 4],
linestart=1)
else:
mvir, rvir, vinit, v25, rreturn = ioformat.rcol(fname, [1, 2, 3, 4, 5],
linestart=1)
# vc = sqrt(pc.G * 10.**array(mvir) * ac.msolar / (array(rvir) * ac.kpc)) / 1.e5
vc = []
for i in range(len(mvir)):
vc.append(cosmology.Vc(10.**mvir[i] * ac.msolar, REDSHIFT) / 1.e5)
print("Mvir Range: ", min(mvir), max(mvir))
print("Vc Range: ", min(vc), max(vc))
# ax1.plot(vc[::100], v25[::100], "b.")
# ax1.plot(vc2, v252, ".", color="teal")
if (FFORMAT == "NEW"):
# Rreturn < 0.25 Rvir!
for i in range(len(v25)):
if (0.0 < rreturn[i] < 0.25 * rvir[i]):
v25[i] = -1
plotmedian(vc, v25, "cyan", nbins=15, ax=ax1, xmin=XMIN, xmax=XMAX)
plotmedian(vc, vinit, "red", nbins=15, ax=ax1, xmin=XMIN, xmax=XMAX)
xbins = logspace(log10(XMIN), log10(XMAX), (int)(XBINS))
ybins = logspace(log10(YMIN), log10(YMAX), (int)(YBINS))
xgrid, ygrid = meshgrid(xbins, ybins)
z, edx, edy = histogram2d(vc, v25, bins=[xbins, ybins])
z = z + 0.1
z = z.T
zf = ndimage.gaussian_filter(z, sigma=0.3, order=0)
ax1.pcolor(xbins[1:],
ybins[1:],
zf,
cmap=plt.cm.Purples,
norm=LogNorm(vmin=z.min(), vmax=z.max()))
# Lines from Muratov 2015
xline = linspace(XMIN, XMAX, 100)
y50line = 0.854 * xline**1.12
y95line = 1.85 * xline**1.10
xsig16 = array([50., 85.])
ysig16 = 0.7 * xsig16**1.60
ax1.plot(xline, y50line, "k-")
ax1.plot(xline, y95line, "k--")
# ax1.plot(xsig16, ysig16, "g-")
# Figure captions
ax1.set_xlim(XMIN, XMAX)
ax1.set_ylim(YMIN, YMAX)
ax1.set_title(titlename)
ax1.text(0.20, 0.02, simname, fontsize=12, transform=ax1.transAxes)
ax1.set_xscale("log")
ax1.set_yscale("log")
ax1.legend([r"$V_{25}$", r"$V_{init}$"], fontsize=16)
fig.subplots_adjust(hspace=0)
setp(ax1.get_xticklabels(), visible=False)
# Count the fraction that makes NOT to R25
FRAC_STEP = 25.
frac = [0.] * int(XMAX / FRAC_STEP)
Ncount = [0.] * int(XMAX / FRAC_STEP)
x = linspace(10., XMAX, int(XMAX / FRAC_STEP)) - 5.
for i in range(len(vc)):
idx = int(vc[i] / FRAC_STEP)
if (idx > int(XMAX / FRAC_STEP) - 1):
idx = int(XMAX / FRAC_STEP) - 1
Ncount[idx] += 1.
if (v25[i] != -1):
frac[idx] += 1.
Ntot = sum(Ncount)
for i in range(len(frac)):
if (Ncount[i] > 0.):
frac[i] = frac[i] / Ncount[i]
ax2.plot(x, frac, "k.-")
print("Ncount = ", Ncount)
print("frac = ", frac)
Ncount_Norm = 2. * max(Ncount) / Ntot
ax2.bar(x, (array(Ncount) / Ntot) / Ncount_Norm,
align="center",
width=0.8 * (x[1] - x[0]),
color="grey")
ax2.set_xlim(XMIN, XMAX)
ax2.set_ylim(0., 1.1)
ax2.set_xscale("log")
ax2.yaxis.set_ticks([0., 0.2, 0.4, 0.6, 0.8, 1.0])
ax2.axhline(1.0, XMIN, XMAX, color="grey", linestyle=":")
ax2.set_xlabel(r"$V_c [km/s]$")
xerr=Merr[0],
yerr=0.05,
uplims=True,
color="black",
fmt='o')
# axs[1].plot(Merb, Zmid-OHSOLAR-0.3, color="purple", linestyle="-", linewidth=2)
axs[1].text(0.02,
0.02,
"Erb+ (2006)",
transform=axs[1].transAxes,
fontsize=12,
color="black")
if PLOT_T04 == True:
ax = axs[3]
Mt04, Z16t04, Z50t04, Z84t04 = ioformat.rcol("../mzr/tremonti04.dat",
[0, 2, 3, 4],
linestart=1)
Z16t04 = array(Z16t04) - OHSOLAR
Z50t04 = array(Z50t04) - OHSOLAR
Z84t04 = array(Z84t04) - OHSOLAR
p, = ax.plot(Mt04, Z50t04, color="black", linestyle="-")
# ax.plot(Mt04, Z50t04-0.3, color="purple", linestyle="-", linewidth=2)
ax.plot(Mt04, Z16t04, color="black", linestyle="--")
ax.plot(Mt04, Z84t04, color="black", linestyle="--")
plist.append(p)
axs[3].text(0.02,
0.02,
"Tremonti+ (2004)",
transform=axs[3].transAxes,
fontsize=12,
color="black")
import ioformat
a = ioformat.rcol("./outputs_z108.txt", [0])
fout = open("redshifts.txt", "w")
fout.write("#snapnum a zred\n")
for i in range(len(a)):
z = 1. / a[i] - 1.
line = "%3d %7.5f %7.5f\n" % (i, a[i], z)
fout.write(line)
fout.close()
print("DONE.")
def V25Vc(fname=fwindsinfo):
import ioformat
from matplotlib import gridspec
fig = plt.figure(1, figsize=(8, 8))
gs = gridspec.GridSpec(2, 1, height_ratios=[4, 1])
ax1 = plt.subplot(gs[0])
ax2 = plt.subplot(gs[1])
mvir, rvir, vinit, v25, rreturn = ioformat.rcol(fname, [1, 2, 3, 4, 5],
linestart=1)
vc = sqrt(pc.G * 10.**array(mvir) * ac.msolar /
(array(rvir) * ac.kpc)) / 1.e5
print("Mvir Range: ", min(mvir), max(mvir))
print("Vc Range: ", min(vc), max(vc))
# ax1.plot(vc[::100], v25[::100], "b.")
# ax1.plot(vc2, v252, ".", color="teal")
# Rreturn < 0.25 Rvir!
for i in range(len(v25)):
if (0.0 < rreturn[i] < 0.25 * rvir[i]):
v25[i] = -1
plotmedian(vc, v25, "blue", nbins=15, ax=ax1, xmin=XMIN, xmax=XMAX)
plotmedian(vc, vinit, "red", nbins=15, ax=ax1, xmin=XMIN, xmax=XMAX)
xbins = logspace(log10(XMIN), log10(XMAX), XBINS)
ybins = logspace(log10(YMIN), log10(YMAX), YBINS)
xgrid, ygrid = meshgrid(xbins, ybins)
z, edx, edy = histogram2d(vc, v25, bins=[xbins, ybins])
z = z + 0.1
z = z.T
zf = ndimage.gaussian_filter(z, sigma=0.3, order=0)
# cont = ax1.contour(xbins[1:], ybins[1:], zf, 10, colors="black")
# cont = ax1.contourf(xbins[1:], ybins[1:], zf, CONTLEVELS, cmap=plt.cm.Purples, norm=LogNorm(vmin=z.min(), vmax=z.max()))
# cont = ax1.contour(xbins[1:], ybins[1:], zf, CONTLEVELS, cmap=plt.cm.Reds, norm=LogNorm(vmin=z.min(), vmax=z.max()))
# cont = ax1.contourf(xbins[1:], ybins[1:], zf, 6, cmap=plt.cm.Purples, vmin=z.min(), vmax=z.max())
# ax1.plot(vc[::200], v25[::200], "k.", markersize=2)
ax1.pcolor(xbins[1:],
ybins[1:],
zf,
cmap=plt.cm.Purples,
norm=LogNorm(vmin=z.min(), vmax=z.max()))
xline = linspace(XMIN, XMAX, 100)
y50line = 0.854 * xline**1.12
y95line = 1.85 * xline**1.10
ax1.plot(xline, y50line, "k-")
ax1.plot(xline, y95line, "k--")
ax2.set_xlabel(r"$V_c [km/s]$")
ax1.set_ylabel(r"$V_{25} [km/s]$")
ax1.set_xlim(XMIN, XMAX)
ax1.set_ylim(YMIN, YMAX)
# ax1.set_ylim(9.,12.)
ax1.set_title(modelname + ", Z = " + str(REDSHIFT))
ax1.set_xscale("log")
ax1.set_yscale("log")
ax1.legend([r"$V_{25}$", r"$V_{init}$"], fontsize=16)
fig.subplots_adjust(hspace=0)
setp(ax1.get_xticklabels(), visible=False)
# Count the fraction that makes NOT to R25
FRAC_STEP = 25.
frac = [0.] * int(XMAX / FRAC_STEP)
Ncount = [0.] * int(XMAX / FRAC_STEP)
x = linspace(10., XMAX, int(XMAX / FRAC_STEP)) - 5.
for i in range(len(vc)):
idx = int(vc[i] / FRAC_STEP)
if (idx > int(XMAX / FRAC_STEP) - 1):
idx = int(XMAX / FRAC_STEP) - 1
Ncount[idx] += 1.
if (v25[i] != -1):
frac[idx] += 1.
# if(FFORMAT == "NEW"):
# if(0. < rreturn[i] < 0.25 * rvir[i]):
# frac[idx] -= 1. # Rreturn < 0.25 Rvir!
Ntot = sum(Ncount)
for i in range(len(frac)):
if (Ncount[i] > 0.):
frac[i] = frac[i] / Ncount[i]
ax2.plot(x, frac, "k.-")
# ax2.plot(x, array(Ncount)/Ntot, "-", color="teal")
Ncount_Norm = 2. * max(Ncount) / Ntot
ax2.bar(x, (array(Ncount) / Ntot) / Ncount_Norm,
align="center",
width=0.8 * (x[1] - x[0]),
color="grey")
ax2.set_xlim(XMIN, XMAX)
ax2.set_ylim(0., 1.1)
ax2.set_xscale("log")
ax2.xaxis.set_ticks([XMIN, 50., 100., 200., XMAX])
ax2.xaxis.set_ticklabels([str(XMIN), "50", "100", "200", str(XMAX)])
ax2.yaxis.set_ticks([0., 0.2, 0.4, 0.6, 0.8])
# ax2.set_ylabel(r"$f(R_{25} < R_{return})$")
ax2.set_ylabel(r"$f(R_{25} < R_{recouple})$")
plt.savefig("/scratch/shuiyao/figures/tmp.pdf")
plt.show()
frac_red(x, y)
x, y = bin1d.subsample(x, y, nonzero=True)
s = bin1d.bin1d(x, y, nbins=40, logbins=True, bounds=0.84)
xline, yline = s.cen, s.median
uline, lline = s.ubound, s.lbound
f.close()
p, = axs[i].plot(log10(array(xline)), yline, "-", color="magenta") # Draw line for all models
if(i == 0):
plist.append(p)
# axs[2].legend([plist[0], plist[1], plist[-1], pflist[0], pflist[1]], ["ezwDESPH","RefHres","Ref", "ezwDESPH","RefHres"], prop={'size':12}, loc=1)
# axs[2].legend([plist[0], plist[1], plist[-1], pflist[0]], ["ezwDESPH","RefHres","Ref", "RefHres"], prop={'size':12}, loc=1)
axs[2].legend([plist[0], plist[1], plist[-1], pflist[0]], lgds, prop={'size':12}, loc=1)
if PLOT_T04 ==True:
Mt04, Z16t04, Z50t04, Z84t04 = ioformat.rcol("../mzr/tremonti04.dat", [0,2,3,4], linestart=1)
Z16t04 = array(Z16t04) - OHSOLAR
Z50t04 = array(Z50t04) - OHSOLAR
Z84t04 = array(Z84t04) - OHSOLAR
p, = ax.plot(Mt04, Z50t04, color="green", linestyle="-")
ax.plot(Mt04, Z16t04, color="green", linestyle="--")
ax.plot(Mt04, Z84t04, color="green", linestyle="--")
plist.append(p)
axs[3].text(0.02, 0.02, "Tremonti+ (2004)", transform=axs[3].transAxes, fontsize=12, color="green")
if PLOT_P14 == True:
# Mp14, F50p14, F16p14, F84p14 = ioformat.rcol("../fgas/peeples14.dat", [0,1,2,3], linestart=5)
from numpy import loadtxt
Mp14, F50p14, F16p14, F84p14 = loadtxt("../fgas/peeples14.dat", unpack=True)
F50p14 = array(F50p14) / (1. + array(F50p14))
F16p14 = array(F16p14) / (1. + array(F16p14))
phib.append(log10(phi[i] / 0.7**3))
# phib.append(log10(phi[i]))
ms = fm18(mhb)
fig, ax = plt.subplots(1, 1, figsize=(6, 6))
ax.plot(ms, phib, "k--")
if (REDSHIFT == 1.0):
gsmfs_tomczak14 = [ \
"../REFERENCES/tomczak14/t14_z0.2_z0.5.dat",\
"../REFERENCES/tomczak14/t14c_z0.75_z1.25.dat",\
"../REFERENCES/tomczak14/t14c_z1.5_z2.5.dat",\
]
colors = ["green", "red", "blue"]
i = 1
ms, phi, e1, e2 = ioformat.rcol(gsmfs_tomczak14[i], [0, 1, 2, 3],
linestart=3)
lower = -array(e2)
upper = array(e1)
ax.errorbar(ms, phi, yerr=[lower, upper], color=colors[i], fmt='o')
if (REDSHIFT == 0.0):
gsmf_baldry12 = "../REFERENCES/Baldry12/gsmf_baldry12_z0.dat"
ms, phi, err = ioformat.rcol(gsmf_baldry12, [0, 2, 3], linestart=3)
phi = array(phi) / 1.e3
err = array(err) / 1.e3
lower = log10(phi) - log10(phi - err)
upper = log10(phi + err) - log10(phi)
phi = log10(phi)
ax.errorbar(ms, phi, yerr=[lower, upper], color="black", fmt='o')
plt.show()
unit_mass = 4.3e5 * (BOXSIZE / 25000.)**3
XTOL = 0.02
MTOL = 1.0
fbase = "/scratch/shuiyao/data/"
model = "l12n144-phew-movie"
gid = 1477
foutname = "progen_" + ("00000" + str(gid))[-5:]
fout = open(foutname, "w")
snapi = snapend
dtime = tcosmic(ascales[snapi]) - tcosmic(ascales[snapi - 1])
dtime = dtime * ac.yr / unit_Time
snapstr = ("000" + str(snapi))[-3:]
fgalname = fbase + model + "/gal_z" + snapstr + ".stat"
mgal, xgal, ygal, zgal, vxgal, vygal, vzgal = ioformat.rcol(
fgalname, [4, 18, 19, 20, 15, 16, 17])
idx = gid - 1
xprev = xgal[idx] - vxgal[idx] * dtime
yprev = ygal[idx] - vygal[idx] * dtime
zprev = zgal[idx] - vzgal[idx] * dtime
mprev = mgal[idx]
fout.write("%5d %7.5f %7.5f %7.5f %6.3f\n" % (idx, xprev, yprev, zprev,\
log10(mprev * unit_mass * 1.e10 / 0.7)))
mgalz0 = log10(mprev * unit_mass * 1.e10 / 0.7)
for snapi in range(snapbeg, snapend)[::-1]:
dtime = tcosmic(ascales[snapi]) - tcosmic(ascales[snapi - 1])
dtime = dtime * ac.yr / unit_Time
snapstr = ("000" + str(snapi))[-3:]
fgalname = fbase + model + "/gal_z" + snapstr + ".stat"
from numpy import genfromtxt, array, exp, mean, median
import ioformat
import matplotlib.pyplot as plt
from math import factorial
f = "example.wind"
h, rc = ioformat.rcol(f, [5, 6])
ratio = array(rc) / array(h)
y = (ratio**2) * 1000.0
def p(n, y):
return y**n * exp(-y) / (float)(factorial(n))
P0 = p(0, y)
P1 = p(1, y)
P2 = p(2, y)
# P(x) = y^xe^-y/x!, y = mean(x)
"--",
color=clrs_t[2])
axs[panel].plot(tabref['Ncen'] + Ncorr,
rcumsum(tabref['t25y']) / ncorr,
"--",
color=clrs_t[3])
axs[panel].text(0.4,
0.85,
ionname,
fontsize=12,
transform=axs[panel].transAxes)
else:
print "Creating New Files."
fout = open(foutname, "w")
fout.write("#Ncen t90x t75x t50x t25x t90y t75y t50y t25y\n")
ioncds = ioformat.rcol(fnamex, cols, separator=",", linestart=1)
hx = []
for ioni in range(len(ioncds)): # t90 t75 t50 t25
ioncds[ioni] = convert_list(ioncds[ioni])
hist, edges = histogram(ioncds[ioni], bins=nbins)
hx.append(hist)
ioncds = ioformat.rcol(fnamey, cols, separator=",", linestart=1)
hy = []
for ioni in range(len(ioncds)): # t90 t75 t50 t25
ioncds[ioni] = convert_list(ioncds[ioni])
hist, edges = histogram(ioncds[ioni], bins=nbins)
hy.append(hist)
cen = 0.5 * (edges[1:] + edges[:-1])
for i in range(len(cen)):
fout.write("%5.2f %6d %6d %6d %6d %6d %6d %6d %6d\n" % \
(cen[i], hx[0][i], hx[1][i], hx[2][i], hx[3][i], \
def convert_list(lst):
lst = array(lst)
lst = lst[lst > 0]
lst = log10(lst)
return lst
# 1 2 3 4 5 6 7 8 9 10
# OVI CIV NV CII NeVIII CIII MgII SiIII SiIV HI
ionnames = ["XX","OVI","CIV","NV","CII","NeVIII","CIII","MgII","SiIII","SiIV","HI"]
ionorder = [-1, 5, 3, -1, -1, 6, 2, 7, -1, 8, 0]
# cols = array([1, 5, 10]) # High-ions
# cols = array([2, 6, 7, 9, 10])
cols = array([1, 2, 5, 6, 7, 9, 10])
tab = ioformat.rcol(fnamey, cols + offset, separator=",", linestart=1)
for i in range(len(tab)): tab[i] = array(tab[i])
idxs = (tab[-1] > 1.e16)
for i in range(len(tab)): tab[i] = log10(tab[i][idxs])
# Strong Correlations
# HI: MgII, CIII 2
# OVI: NeVIII 1
# CIV: SiIV 1
# No/Weak Correlations
# HI: CIV, OVI 2
# CIV: CIII, OVI 2
from pltastro import frame, draw
frm = frame.multi(4,2)
pars = frm.params
import matplotlib.pyplot as plt from numpy import genfromtxt, array, log10, linspace import config_mpl import ioformat f1 = "/proj/shuiyao/l25n144-phew-rcloud/WINDS/winds.45" f2 = "/proj/shuiyao/l25n288-phew-m5/WINDS.red/winds.45" # f1 = "/proj/shuiyao/P50N288s/p50n288fiducial/WINDS/winds.3" # f2 = "/proj/shuiyao/p50n576fi/WINDS/winds.3" # tab1 = genfromtxt(f1, names=True) # tab2 = genfromtxt(f2, names=True) a1, sig1 = ioformat.rcol(f1, [0,3], linestart=1) a2, sig2 = ioformat.rcol(f2, [0,3], linestart=1) # step = 10 # plt.plot(tab1['a'][::step], tab1['Siggal'][::step], "b.", alpha=0.2) # plt.plot(tab2['a'][::step], tab2['Siggal'][::step], "r.", alpha=0.2) # plt.hist(tab1['Siggal'], bins=linspace(0., 300., 50), color="blue", histtype="step") # plt.hist(tab2['Siggal'][::8], bins=linspace(0., 300., 50), color="red", histtype="step") a1, a2 = array(a1), array(a2) sig1, sig2 = array(sig1), array(sig2) sig1b = sig1[a1 > 0.5] sig2b = sig2[a2 > 0.5] plt.hist(sig1, bins=linspace(0., 150., 50), color="blue", histtype="step") plt.hist(sig2[::4], bins=linspace(0., 150., 50), color="red", histtype="step")
def load_central_stars(fname):
stars = read_starinfo(fname)
nstars = len(stars)
stars = stars[stars['GID'] == stars['HID']] # Only central galaxies
print "Stars from central galaxies: %d/%d (%4.1f%%)" % \
(len(stars), nstars, (float)(len(stars)) / (float)(nstars) * 100.)
return stars
galsm11 = ("m11", 11.0, 11.5)
galsm12 = ("m12", 11.85, 12.15)
galsm13 = ("m13", 12.85, 13.15)
galss = [galsm11, galsm12, galsm13]
redz = ioformat.rcol("redshifts.txt", [0])
def show_lineage_of_selected_galaxies(modelname, gal_selection, ax=None):
name, mmin, mmax = gal_selection[0], gal_selection[1], gal_selection[2]
# folder = "/scratch/shuiyao/scidata/mergertree/"+modelname+"_old/"
folder = "/scratch/shuiyao/scidata/mergertree/" + modelname + "/"
fin = open(folder + "lineages_" + name + ".dat", "r")
xs = log10(array(redz) + 1)
xarr, yarr = [], []
for line in fin:
spt = line.split()[1:]
mstars = array(spt, dtype='float')[::-1]
for i in range(len(mstars)):
xarr.append(xs[i])
yarr.append(mstars[i])
