def CRerdistestinput(subdict):
startno=subdict['startno']
Nsnap=subdict['Nsnap']
snapsep=subdict['snapsep']
wanted=subdict['wanted']
dirneed=subdict['dirneed']
fmeat=subdict['fmeat']
dirdict = collections.defaultdict(dict)
keylist = np.array([])
for ir, runtodo in enumerate(dirneed):
keylist=np.append(keylist,keystore[ir])
dirdict[keystore[ir]]=[runtodo]
noplots=len(dirdict.keys())
print 'noplots', noplots
fig, ax = PS.setupfig(nrows=noplots, ncols=1,sharex=True,sharey=False)
for i, key in enumerate(keylist):
items=dirdict[key]
for j, runtodo in enumerate(items):
ssdict = collections.defaultdict(dict)
ssdict = subdict
ssdict['runtodo'] = runtodo
print 'runtodo', runtodo
plotdict = CR_r_energy_distribution(ssdict)
xlab = plotdict[wanted]['xlab'];
ylab = plotdict[wanted]['ylab'];
ptitle = plotdict[wanted]['ptitle']
filename = plotdict[wanted]['filename'];
print 'filename', filename
for k,inkey in enumerate(plotdict[wanted]['xnl']):
xnl = plotdict[wanted]['xnl'][inkey];
ynl = plotdict[wanted]['ynl'][inkey];
labelneed = plotdict[wanted]['labelneed'];
color = plotdict[wanted]['color'];
lsn = plotdict[wanted]['lsn'][inkey];
lw = plotdict[wanted]['lw'][inkey];
marker = plotdict[wanted]['marker'][inkey];
linelabel = plotdict[wanted]['linelab'][inkey];
legendneed = 1
if i==noplots-1 and j==0:
label = linelabel
else:
label = '_nolegend_'
if noplots==1:
ax.plot(xnl,ynl,label=label,lw=lw,ls=lsn,color=color,marker=marker)
else:
ax[i].plot(xnl,ynl,label=label,lw=lw,ls=lsn,color=color,marker=marker)
if i<noplots-1: xlab=''
if noplots==1:
ax.text(0.25, 0.1, ptitle, horizontalalignment='center',
verticalalignment='center', transform=ax.transAxes,fontsize=22)
else:
ax[i].text(0.25, 0.1, ptitle, horizontalalignment='center',
verticalalignment='center', transform=ax[i].transAxes,fontsize=22)
if noplots==1:
PS.miscsetup(ax,logx=0,logy=1,xlab=xlab,ylab=ylab,legendneed=legendneed,labfs=22,legfs=12)
else:
PS.miscsetup(ax[i],logx=0,logy=1,xlab=xlab,ylab=ylab,legendneed=legendneed,labfs=22,legfs=12)
PS.finishsave(plt,filename)
return None
def kslawtestinput(subdict):
startno = subdict['startno']
Nsnap = subdict['Nsnap']
snapsep = subdict['snapsep']
wanted = subdict['wanted']
dirneed = subdict['dirneed']
fmeat = subdict['fmeat']
dirdict = collections.defaultdict(dict)
keylist = np.array([])
noplots = 1
fig, ax = PS.setupfig(nrows=noplots, ncols=1, sharex=True, sharey=False)
for j, runtodo in enumerate(dirneed):
ssdict = collections.defaultdict(dict)
ssdict = subdict
ssdict['runtodo'] = runtodo
print 'runtodo', runtodo
plotdict = kslaw(ssdict)
xlab = plotdict[wanted]['xlab']
ylab = plotdict[wanted]['ylab']
ptitle = plotdict[wanted]['ptitle']
filename = plotdict[wanted]['filename']
xnl = plotdict[wanted]['xnl']
ynl = plotdict[wanted]['ynl']
labelneed = plotdict[wanted]['labelneed']
color = plotdict[wanted]['color']
lsn = plotdict[wanted]['lsn']
lw = plotdict[wanted]['lw']
marker = plotdict[wanted]['marker']
legendneed = 1
ax.plot(xnl,
ynl,
label=labelneed,
lw=lw,
ls=lsn,
color=color,
marker=marker,
alpha=0.7)
PS.miscsetup(ax,
logx=1,
logy=1,
xlab=xlab,
ylab=ylab,
legendneed=0,
labfs=22,
legfs=12)
PS.finishsave(plt, filename)
return None
def doplot(plotdict, plotneed, markerl, colorl, labell, neederr=0):
fig, ax = PS.setupfig()
xnl = plotdict[plotneed]['xnl']
ynl = plotdict[plotneed]['ynl']
xlab = plotdict[plotneed]['xlab']
ylab = plotdict[plotneed]['ylab']
selectl = plotdict[plotneed]['selectl']
filename = plotdict[plotneed]['filename']
if neederr == 1 and (plotneed == 'mlmv' or plotneed == 'mlms'):
yld = plotdict[plotneed]['yld']
ylu = plotdict[plotneed]['ylu']
for i in range(len(labell)):
if neederr == 1 and (plotneed == 'mlmv' or plotneed == 'mlms'):
ax.errorbar(xnl[selectl == i],
ynl[selectl == i],
yerr=[yld[selectl == i], ylu[selectl == i]],
color=colorl[i],
fmt=markerl[i],
markersize=7,
label=labell[i])
else:
ax.plot(xnl[selectl == i],
ynl[selectl == i],
marker=markerl[i],
ls='none',
color=colorl[i],
label=labell[i])
PS.miscsetup(ax,
logx=1,
logy=1,
xlab=xlab,
ylab=ylab,
legendneed=1,
labfs=22,
legfs=12)
PS.finishsave(plt, filename)
def gasdenThistestinput(subdict):
startno=subdict['startno']
Nsnap=subdict['Nsnap']
snapsep=subdict['snapsep']
wanted=subdict['wanted']
dirneed=np.array(subdict['dirneed'])
fmeat=subdict['fmeat']
title=subdict['title']
dirdict = collections.defaultdict(dict)
keylist = np.array([])
for ir, subdirneed in enumerate(dirneed):
keylist=np.append(keylist,keystore[ir])
if dirneed.ndim>1:
dirdict[keystore[ir]]=subdirneed
else:
dirdict[keystore[ir]]=[subdirneed]
if dirneed.ndim>1:
noplots=len(keylist)
else:
noplots=1
print 'noplots', noplots
fig, ax = PS.setupfig(nrows=noplots, ncols=1,sharex=True,sharey=False)
linelablist=[]
lxlist=[]
for i, key in enumerate(keylist):
items=dirdict[key]
for j, runtodo in enumerate(items):
ssdict = collections.defaultdict(dict)
ssdict = subdict
ssdict['runtodo'] = runtodo
print 'runtodo', runtodo
if dirneed.ndim>1:
ssdict['fmeat']=fmeat[-1]
ssdict['title']=title[i]
plotdict = gasdenThis_out(ssdict)
xlab = plotdict[wanted]['xlab'];
ylab = plotdict[wanted]['ylab'];
ptitle = plotdict[wanted]['ptitle']
filename = plotdict[wanted]['filename'];
for k,inkey in enumerate(plotdict[wanted]['xnl']):
xnl = plotdict[wanted]['xnl'][inkey];
ynl = plotdict[wanted]['ynl'][inkey];
labelneed = plotdict[wanted]['labelneed'];
color = plotdict[wanted]['color'];
lsn = plotdict[wanted]['lsn'][inkey];
lw = plotdict[wanted]['lw'];
marker = plotdict[wanted]['marker'];
linelabel = plotdict[wanted]['linelab'][inkey];
legendneed = 1
if i==0 and j==0:
label = linelabel
else:
label = '_nolegend_'
print 'xnl', xnl
print 'ynl', ynl
if noplots==1:
ax.plot(xnl,ynl,label=label,lw=lw,ls=lsn,color=color,marker=marker)
else:
ax[i].plot(xnl,ynl,label=label,lw=lw,ls=lsn,color=color,marker=marker)
if k==0 and i==noplots-1:
lxlist.append(mlines.Line2D([], [], color=color, ls=lsn,label=labelneed))
linelablist = np.append(linelablist,labelneed)
if i<noplots-1: xlab=''
if i>1: legendneed=0
if noplots==1:
ax.set_title(ptitle, fontsize=22)
legend1 = ax.legend(lxlist, linelablist, loc='lower left',fontsize=12,ncol=1)
ax.add_artist(legend1)
else:
ax[i].set_title(ptitle, fontsize=22)
if i==noplots-1:
legend1 = ax[i].legend(lxlist, linelablist, loc='lower left',fontsize=12,ncol=1)
ax[i].add_artist(legend1)
if noplots==1:
PS.miscsetup(ax,logx=0,logy=1,xlab=xlab,ylab=ylab,legendneed=legendneed,labfs=22,legfs=12)
else:
PS.miscsetup(ax[i],logx=0,logy=1,xlab=xlab,ylab=ylab,legendneed=legendneed,labfs=22,legfs=12)
if not (i==0 or i==noplots-1):
if noplots==1:
ax.legend().set_visible(False)
else:
ax[i].legend().set_visible(False)
#plt.legend(loc='upper right',fontsize=12)
PS.finishsave(plt,filename)
return None
def vzcylouttestinput(subdict):
startno = subdict['startno']
Nsnap = subdict['Nsnap']
snapsep = subdict['snapsep']
wanted = subdict['wanted']
dirneed = subdict['dirneed']
fmeat = subdict['fmeat']
dirdict = collections.defaultdict(dict)
keylist = np.array([])
for ir, runtodo in enumerate(dirneed):
keylist = np.append(keylist, keystore[ir])
dirdict[keystore[ir]] = [runtodo]
#noplots=len(dirdict.keys())
noplots = 1
print 'noplots', noplots
fig, ax = PS.setupfig(nrows=noplots, ncols=1, sharex=True, sharey=False)
for i, key in enumerate(keylist):
items = dirdict[key]
for j, runtodo in enumerate(items):
ssdict = collections.defaultdict(dict)
ssdict = subdict
ssdict['runtodo'] = runtodo
print 'runtodo', runtodo
plotdict = vzcylout_out(ssdict)
xlab = plotdict[wanted]['xlab']
ylab = plotdict[wanted]['ylab']
ptitle = plotdict[wanted]['ptitle']
filename = plotdict[wanted]['filename']
xnl = plotdict[wanted]['xnl']
ynl = plotdict[wanted]['ynl']
labelneed = plotdict[wanted]['labelneed']
color = plotdict[wanted]['color']
lsn = plotdict[wanted]['lsn']
lw = plotdict[wanted]['lw']
marker = plotdict[wanted]['marker']
linelabel = plotdict[wanted]['linelab']
legendneed = 1
if i == 0 and j == 0:
label = linelabel
else:
label = '_nolegend_'
print 'xnl', xnl
print 'ynl', ynl
if noplots == 1:
ax.plot(xnl,
ynl,
label=labelneed,
lw=lw,
ls=lsn,
color=color,
marker=marker)
else:
ax[i].plot(xnl,
ynl,
label=labelneed,
lw=lw,
ls=lsn,
color=color,
marker=marker)
if i < noplots - 1: xlab = ''
if i > 1: legendneed = 0
if noplots == 1:
ax.set_title(ptitle, fontsize=16)
else:
ax[i].set_title(ptitle, fontsize=16)
#ax.text(0.25, 0.95, ptitle, horizontalalignment='center',
#verticalalignment='center', transform=ax.transAxes,fontsize=22)
if noplots == 1:
PS.miscsetup(ax,
logx=0,
logy=1,
xlab=xlab,
ylab=ylab,
legendneed=legendneed,
labfs=22,
legfs=12)
else:
PS.miscsetup(ax[i],
logx=0,
logy=1,
xlab=xlab,
ylab=ylab,
legendneed=legendneed,
labfs=22,
legfs=12)
PS.finishsave(plt, filename)
return None
def CRerzdis_single_testinput(subdict):
startno = subdict['startno']
Nsnap = subdict['Nsnap']
snapsep = subdict['snapsep']
wanted = subdict['wanted']
dirneed = np.array(subdict['dirneed'])
fmeat = subdict['fmeat']
title = subdict['title']
dirdict = collections.defaultdict(dict)
keylist = np.array([])
for ir, subdirneed in enumerate(dirneed):
keylist = np.append(keylist, keystore[ir])
if dirneed.ndim > 1:
dirdict[keystore[ir]] = subdirneed
else:
dirdict[keystore[ir]] = [subdirneed]
noplots = 1
print 'noplots', noplots
fig, ax = PS.setupfig(nrows=noplots, ncols=1, sharex=True, sharey=False)
linelablist = []
lxlist = []
for i, key in enumerate(keylist): #i for different runs
items = dirdict[key]
for j, runtodo in enumerate(items): #j for different CR models
ssdict = collections.defaultdict(dict)
ssdict = subdict
ssdict['runtodo'] = runtodo
print 'runtodo', runtodo
plotdict = CR_rz_energy_distribution_single(ssdict)
xlab = plotdict[wanted]['xlab']
ylab = plotdict[wanted]['ylab']
ptitle = plotdict[wanted]['ptitle']
filename = plotdict[wanted]['filename']
print 'filename', filename
for k, inkey in enumerate(
plotdict[wanted]['xnl']): #k for different energies
xnl = plotdict[wanted]['xnl'][inkey]
ynl = plotdict[wanted]['ynl'][inkey]
labelneed = plotdict[wanted]['labelneed']
#CR models
color = plotdict[wanted]['color']
lsn = plotdict[wanted]['lsn']
lw = plotdict[wanted]['lw'][inkey]
marker = plotdict[wanted]['marker']
linelabel = plotdict[wanted]['linelab']
#runlabel
legendneed = 1
if j == 1:
label = linelabel
else:
label = '_nolegend_'
print 'j,label', j, label
if noplots == 1:
ax.plot(xnl,
ynl,
label=label,
lw=lw,
ls=lsn,
color=color,
marker=marker)
else:
ax[i].plot(xnl,
ynl,
label=label,
lw=lw,
ls=lsn,
color=color,
marker=marker)
if i == 0:
lxlist.append(
mlines.Line2D([], [],
color=color,
ls='solid',
label=labelneed))
linelablist = np.append(linelablist, labelneed)
if i < noplots - 1: xlab = ''
legend1 = ax.legend(lxlist,
linelablist,
loc='lower left',
fontsize=12,
ncol=1)
ax.add_artist(legend1)
if noplots == 1:
PS.miscsetup(ax,
logx=0,
logy=1,
xlab=xlab,
ylab=ylab,
legendneed=legendneed,
labfs=22,
legfs=12,
locneed='upper right')
else:
PS.miscsetup(ax[i],
logx=0,
logy=1,
xlab=xlab,
ylab=ylab,
legendneed=legendneed,
labfs=22,
legfs=12,
locneed='upper right')
PS.finishsave(plt, filename)
return None
def sfrhotgasmass_testinput(subdict):
nested_dict = lambda: collections.defaultdict(nested_dict)
plotdict = nested_dict()
startno = subdict['startno']
Nsnap = subdict['Nsnap']
snapsep = subdict['snapsep']
wanted = subdict['wanted']
dirneed = subdict['dirneed']
fmeat = subdict['fmeat']
withinr = subdict['withinr']
withoutr = subdict['withoutr']
maxlength = subdict['maxlength']
minsfr = subdict['minsfr']
maxsfr = subdict['maxsfr']
title = ''
titleneed = title
ptitle = title
needlog = 0
dclabelneed = 1
correctIa = 0
useM1 = 0
resoneed = 0
rotface = 1
loccen = 1
newlabelneed = 1
findradiusatnism = 1 #find the radius that has that ISM density (negative to turn off)
#withinr=5. #withinr will change according to the above
dr = 2.
fig, ax = PS.setupfig(nrows=1, ncols=1, sharex=True, sharey=False)
if wanted == 'sfrhotgasmass':
ncount = 0
ncrcount = 0
nbcount = 0
energylabel = 1
usesolarcircle = 0
usecentral = 0
if usesolarcircle == 1:
fmeat += '_usesolarcircle'
elif usecentral == 1:
fmeat += '_usecentral'
sfrl = []
gmhiml = []
coloril = []
runtodol = []
for runtodo in dirneed:
for i in range(startno, Nsnap, snapsep):
info = SSF.outdirname(runtodo, i)
rundir = info['rundir']
runtitle = info['runtitle']
slabel = info['slabel']
snlabel = info['snlabel']
dclabel = info['dclabel']
resolabel = info['resolabel']
the_snapdir = info['the_snapdir']
the_prefix = info['the_prefix']
the_suffix = info['the_suffix']
Nsnapstring = info['Nsnapstring']
havecr = info['havecr']
Fcal = info['Fcal']
iavesfr = info['iavesfr']
timestep = info['timestep']
maindir = info['maindir']
haveB = info['haveB']
cosmo = info['cosmo']
newlabel = info['newlabel']
color = info['color']
usepep = info['usepep']
snumadd = info['snumadd']
halostr = info['halostr']
h0 = info['h0']
highres = info['highres']
ptitle = title
if runtitle == 'SMC':
ptitle = 'Dwarf'
elif runtitle == 'SBC':
ptitle = 'Starburst'
elif runtitle == 'MW':
ptitle = r'$L\star$ Galaxy'
labelneed = dclabel
if newlabelneed == 1:
labelneed = "\n".join(wrap(newlabel, 17))
try:
usesnipshot = 1
if usesnipshot == 1:
print 'usesnipshot'
commonpath = '/home/tkc004/scratch/snipshot/philruns/'
fname = commonpath + rundir + '/output/withinr20GS/snipshot_' + Nsnapstring + '.hdf5'
data = RSS.readsnipshot(fname, ptypelist=[0, 4])
G = data[0]
S = data[1]
oheader = readsnapcr(the_snapdir,
Nsnapstring,
0,
snapshot_name=the_prefix,
extension=the_suffix,
havecr=havecr,
h0=h0,
cosmological=cosmo,
header_only=0,
oheader_only=1)
S['header'] = oheader
#print 'oheader', oheader
else:
G = SSF.readsnapwcen(the_snapdir, Nsnapstring, 0, snapshot_name=the_prefix, extension=the_suffix,\
havecr=havecr,h0=h0,cosmo=cosmo, usepep=usepep, maindir=maindir,snumadd=snumadd,rotface=rotface,\
loccen=loccen,runtodo=runtodo,rundir=rundir,halostr=halostr)
S = SSF.readsnapwcen(the_snapdir, Nsnapstring, 4, snapshot_name=the_prefix, extension=the_suffix,\
havecr=havecr,h0=h0,cosmo=cosmo, usepep=usepep, maindir=maindir,snumadd=snumadd,rotface=rotface,\
loccen=loccen,runtodo=runtodo,rundir=rundir,halostr=halostr)
Gmdata = SSF.calGmatT(G, withinr=withinr, nbin=2)
gmhim = np.sum(Gmdata['mgrhot'])
gmhiml = np.append(gmhiml, gmhim)
sfrdata = SSF.calsfr(S, cosmo=cosmo)
del G, S
sfr = sfrdata['sfr']
sfrl = np.append(sfrl, sfr)
colori = highres
coloril = np.append(coloril, colori)
runtodol = np.append(runtodol, runtodo)
except (ZeroDivisionError, IndexError):
continue
if wanted == 'sfrhotgasmass':
neederrbar = 1
if neederrbar == 1:
for runtodo in dirneed:
Sds = sfrl[runtodol == runtodo]
sHs = gmhiml[runtodol == runtodo]
cls = coloril[runtodol == runtodo]
Sdmed = np.median(Sds)
sHmed = np.median(sHs)
clmed = np.median(cls)
Sdu = np.percentile(Sds, 84) - Sdmed
Sdd = Sdmed - np.percentile(Sds, 15.8)
sHu = np.percentile(sHs, 84) - sHmed
sHd = sHmed - np.percentile(sHs, 15.8)
if clmed == 0:
color = 'k'
marker = 's'
if clmed == 1:
color = 'r'
marker = '^'
if clmed == 3:
color = 'g'
marker = 'o'
ax.errorbar(Sdmed,
sHmed,
xerr=[[Sdd], [Sdu]],
yerr=[[sHd], [sHu]],
color=color,
fmt=marker,
markersize=7)
else:
ax.plot(sfrl[coloril == 1],
gmhiml[coloril == 1],
color='r',
ls='None',
marker='^')
ax.plot(sfrl[coloril == 3],
gmhiml[coloril == 3],
color='g',
ls='None',
marker='s')
xlab = r'${\rm SFR\;[M_\odot/yr]}$'
if wanted == 'sfrhotgasmass':
ylab = r'$M(T>10^5\;{\rm K})\;[{\rm M_\odot}]$'
ax.set_title(ptitle, fontsize=16)
PS.miscsetup(ax,
logx=0,
logy=0,
xlab=xlab,
ylab=ylab,
legendneed=0,
labfs=22,
legfs=12)
import matplotlib.lines as mlines
potr = mlines.Line2D([], [], color='r', ls='None', marker='^')
potg = mlines.Line2D([], [], color='g', ls='None', marker='s')
lxlist = [potr, potg]
lablist = ['MHD+', 'CR+']
legend1 = plt.legend(lxlist,
lablist,
loc='upper left',
fontsize=14,
ncol=1)
plt.gca().add_artist(legend1)
if wanted == 'sfrhotgasmass':
filename = plotloc + 'CRplot/sfrhotgasmass/sfrhotgasmass_' + fmeat + '_sn' + str(
startno) + '_' + str(Nsnap) + '.pdf'
PS.finishsave(plt, filename)
def sfrturtestinput(subdict):
nested_dict = lambda: collections.defaultdict(nested_dict)
plotdict = nested_dict()
startno = subdict['startno']
Nsnap = subdict['Nsnap']
snapsep = subdict['snapsep']
wanted = subdict['wanted']
dirneed = subdict['dirneed']
fmeat = subdict['fmeat']
withinr = subdict['withinr']
withoutr = subdict['withoutr']
maxlength = subdict['maxlength']
minsfr = subdict['minsfr']
maxsfr = subdict['maxsfr']
title = ''
titleneed = title
ptitle = title
needlog = 0
dclabelneed = 1
correctIa = 0
useM1 = 0
resoneed = 0
rotface = 1
loccen = 1
newlabelneed = 1
findradiusatnism = 1 #find the radius that has that ISM density (negative to turn off)
withinr = 5. #withinr will change according to the above
dr = 2.
fig, ax = PS.setupfig(nrows=1, ncols=1, sharex=True, sharey=False)
if wanted=='sfrtur' or wanted=='sfrtur_m' or wanted=='sigmatur_mweighted'\
or wanted=='vth_mweighted' or wanted=='vcr_mweighted'\
or wanted=='vA_mweighted' or wanted=='v_mweighted':
ncount = 0
ncrcount = 0
nbcount = 0
energylabel = 1
usesolarcircle = 0
usecentral = 0
if usesolarcircle == 1:
fmeat += '_usesolarcircle'
elif usecentral == 1:
fmeat += '_usecentral'
turt = []
thermt = []
crt = []
Begyt = []
sfrl = []
gml = []
coloril = []
for runtodo in dirneed:
info = SSF.outdirname(runtodo, Nsnap)
rundir = info['rundir']
runtitle = info['runtitle']
slabel = info['slabel']
snlabel = info['snlabel']
dclabel = info['dclabel']
resolabel = info['resolabel']
the_snapdir = info['the_snapdir']
the_prefix = info['the_prefix']
the_suffix = info['the_suffix']
Nsnapstring = info['Nsnapstring']
havecr = info['havecr']
Fcal = info['Fcal']
iavesfr = info['iavesfr']
timestep = info['timestep']
maindir = info['maindir']
haveB = info['haveB']
cosmo = info['cosmo']
newlabel = info['newlabel']
color = info['color']
usepep = info['usepep']
snumadd = info['snumadd']
halostr = info['halostr']
h0 = info['h0']
highres = info['highres']
ptitle = title
if runtitle == 'SMC':
ptitle = 'Dwarf'
elif runtitle == 'SBC':
ptitle = 'Starburst'
elif runtitle == 'MW':
ptitle = r'$L\star$ Galaxy'
labelneed = dclabel
if newlabelneed == 1:
labelneed = "\n".join(wrap(newlabel, 17))
for i in range(startno, Nsnap, snapsep):
try:
info = SSF.outdirname(runtodo, i)
Nsnapstring = info['Nsnapstring']
egydata=CRTF.energyoutput(runtodo,i,usesolarcircle=usesolarcircle,usecentral=usecentral,\
cylr=withinr,cylrin=withoutr,cylz=maxlength)
turl = egydata['turl']
therml = egydata['therml']
cregyl = egydata['cregyl']
Begyl = egydata['Begyl']
gm = np.sum(egydata['gminl']) #in g
turt = np.append(turt, np.sum(turl))
thermt = np.append(thermt, np.sum(therml))
crt = np.append(crt, np.sum(cregyl))
Begyt = np.append(Begyt, np.sum(Begyl))
gml = np.append(gml, gm)
S = SSF.readsnapwcen(the_snapdir, Nsnapstring, 4, snapshot_name=the_prefix, extension=the_suffix,\
havecr=havecr,h0=h0,cosmo=cosmo, usepep=usepep, maindir=maindir,snumadd=snumadd,rotface=rotface,\
loccen=loccen,runtodo=runtodo,rundir=rundir,halostr=halostr)
sfrdata = SSF.calsfr(S, cosmo=cosmo)
sfr = sfrdata['sfr']
sfrl = np.append(sfrl, sfr)
colori = highres
coloril = np.append(coloril, colori)
except (ZeroDivisionError, IndexError):
continue
turt = np.array(turt)
thermt = np.array(thermt)
crt = np.array(crt)
Begyt = np.array(Begyt)
sigmaz = np.sqrt(turt / gml) / km_in_cm
vth = np.sqrt(thermt * (GAMMA - 1) * (GAMMA) / gml) / km_in_cm
vcr = np.sqrt(crt * (CRgamma - 1) * (CRgamma) / gml) / km_in_cm
vA = np.sqrt(Begyt / gml * 2.0) / km_in_cm
print 'sfrl', sfrl
print 'turt', turt
print 'sigmaz', sigmaz
print 'vth', vth
print 'vA', vA
print 'coloril', coloril
if wanted == 'sfrtur':
ax.plot(sfrl[coloril == 0],
turt[coloril == 0],
color='k',
ls='None',
marker='s')
ax.plot(sfrl[coloril == 1],
turt[coloril == 1],
color='r',
ls='None',
marker='s')
ax.plot(sfrl[coloril == 3],
turt[coloril == 3],
color='g',
ls='None',
marker='s')
if wanted == 'sfrtur_m':
ax.plot(sfrl[coloril == 0],
turt[coloril == 0] / gml[coloril == 0],
color='k',
ls='None',
marker='s')
ax.plot(sfrl[coloril == 1],
turt[coloril == 1] / gml[coloril == 1],
color='r',
ls='None',
marker='s')
ax.plot(sfrl[coloril == 3],
turt[coloril == 3] / gml[coloril == 3],
color='g',
ls='None',
marker='s')
if wanted == 'sigmatur_mweighted' or wanted == 'v_mweighted':
ax.plot(sfrl[coloril == 0],
sigmaz[coloril == 0],
color='k',
ls='None',
marker='d')
ax.plot(sfrl[coloril == 1],
sigmaz[coloril == 1],
color='r',
ls='None',
marker='d')
ax.plot(sfrl[coloril == 3],
sigmaz[coloril == 3],
color='g',
ls='None',
marker='d')
ax.set_ylim(ymin=1, ymax=30)
ax.set_xlim(xmin=minsfr, xmax=maxsfr)
if wanted == 'vth_mweighted' or wanted == 'v_mweighted':
ax.plot(sfrl[coloril == 0],
vth[coloril == 0],
color='k',
ls='None',
marker='^')
ax.plot(sfrl[coloril == 1],
vth[coloril == 1],
color='r',
ls='None',
marker='^')
ax.plot(sfrl[coloril == 3],
vth[coloril == 3],
color='g',
ls='None',
marker='^')
ax.set_ylim(ymin=1, ymax=30)
ax.set_xlim(xmin=minsfr, xmax=maxsfr)
if wanted == 'vcr_mweighted' or wanted == 'v_mweighted':
ax.plot(sfrl[coloril == 0],
vcr[coloril == 0],
color='k',
ls='None',
marker='o')
ax.plot(sfrl[coloril == 1],
vcr[coloril == 1],
color='r',
ls='None',
marker='o')
ax.plot(sfrl[coloril == 3],
vcr[coloril == 3],
color='g',
ls='None',
marker='o')
ax.set_ylim(ymin=1, ymax=30)
ax.set_xlim(xmin=minsfr, xmax=maxsfr)
if wanted == 'vA_mweighted' or wanted == 'v_mweighted':
ax.plot(sfrl[coloril == 0],
vA[coloril == 0],
color='k',
ls='None',
marker='s')
ax.plot(sfrl[coloril == 1],
vA[coloril == 1],
color='r',
ls='None',
marker='s')
ax.plot(sfrl[coloril == 3],
vA[coloril == 3],
color='g',
ls='None',
marker='s')
ax.set_ylim(ymin=1, ymax=30)
ax.set_xlim(xmin=minsfr, xmax=maxsfr)
xlab = r'${\rm SFR\;[M_\odot/yr]}$'
if wanted == 'sfrtur':
ylab = r'${\rm E_{tur}\;[erg]}$'
if wanted == 'sfrtur_m':
ylab = r'${\rm E_{tur}/m\;[erg/g]}$'
if wanted == 'sigmatur_mweighted':
ylab = r'${\rm \langle\sigma_{tur}\rangle\;[km/s]}$'
if wanted == 'vth_mweighted':
ylab = r'${\rm \langle c_{th}\rangle\;[km/s]}$'
if wanted == 'vcr_mweighted':
ylab = r'${\rm \langle c_{cr}\rangle\;[km/s]}$'
if wanted == 'vA_mweighted':
ylab = r'${\rm \langle v_{A}\rangle\;[km/s]}$'
if wanted == 'v_mweighted':
ylab = r'${\rm \langle c\rangle\;[km/s]}$'
ax.set_title(ptitle, fontsize=16)
PS.miscsetup(ax,
logx=1,
logy=1,
xlab=xlab,
ylab=ylab,
legendneed=0,
labfs=22,
legfs=12)
import matplotlib.lines as mlines
potk = mlines.Line2D([], [], color='k', ls='None', marker='s')
potr = mlines.Line2D([], [], color='r', ls='None', marker='s')
potg = mlines.Line2D([], [], color='g', ls='None', marker='s')
#potk = plt.plot([],[], ls='None',marker='s', color='k')
#potr = plt.plot([],[], ls='None',marker='s', color='r')
#potg = plt.plot([],[], ls='None',marker='s', color='g')
lxlist = [potk, potr, potg]
lablist = ['no CR', 'MHD no CR', r'MHD $\kappa$=3e29']
legend1 = plt.legend(lxlist,
lablist,
loc='lower left',
fontsize=14,
ncol=1)
plt.gca().add_artist(legend1)
if wanted == 'v_mweighted':
pottur = mlines.Line2D([], [], color='r', ls='None', marker='d')
potth = mlines.Line2D([], [], color='r', ls='None', marker='^')
potcr = mlines.Line2D([], [], color='r', ls='None', marker='o')
potvA = mlines.Line2D([], [], color='r', ls='None', marker='s')
lxvlist = [pottur, potth, potcr, potvA]
labvlist = [
r'${\rm \langle\sigma_{tur}\rangle}$',
r'${\rm \langle c_{th}\rangle}$',
r'${\rm \langle c_{cr}\rangle}$',
r'${\rm \langle v_{A}\rangle}$'
]
legend1v = plt.legend(lxvlist,
labvlist,
loc='lower right',
fontsize=14,
ncol=1)
plt.gca().add_artist(legend1v)
if wanted == 'sfrtur':
filename = plotloc + 'CRplot/sfrtur/sfrtur_' + fmeat + '_sn' + str(
startno) + '_' + str(Nsnap) + '.pdf'
if wanted == 'sfrtur_m':
filename = plotloc + 'CRplot/sfrtur/sfrtur_m_' + fmeat + '_sn' + str(
startno) + '_' + str(Nsnap) + '.pdf'
if wanted == 'sigmatur_mweighted':
filename = plotloc + 'CRplot/sigmatur_mweighted/sigmatur_mweighted_' + fmeat + '_sn' + str(
startno) + '_' + str(Nsnap) + '.pdf'
if wanted == 'vth_mweighted':
filename = plotloc + 'CRplot/vth_mweighted/vth_mweighted_' + fmeat + '_sn' + str(
startno) + '_' + str(Nsnap) + '.pdf'
if wanted == 'vcr_mweighted':
filename = plotloc + 'CRplot/vcr_mweighted/vcr_mweighted_' + fmeat + '_sn' + str(
startno) + '_' + str(Nsnap) + '.pdf'
if wanted == 'vA_mweighted':
filename = plotloc + 'CRplot/vA_mweighted/vA_mweighted_' + fmeat + '_sn' + str(
startno) + '_' + str(Nsnap) + '.pdf'
if wanted == 'v_mweighted':
filename = plotloc + 'CRplot/v_mweighted/v_mweighted_' + fmeat + '_sn' + str(
startno) + '_' + str(Nsnap) + '.pdf'
PS.finishsave(plt, filename)
def sfrmockturtestinput(subdict):
nested_dict = lambda: collections.defaultdict(nested_dict)
plotdict = nested_dict()
startno = subdict['startno']
Nsnap = subdict['Nsnap']
snapsep = subdict['snapsep']
wanted = subdict['wanted']
dirneed = subdict['dirneed']
fmeat = subdict['fmeat']
withinr = subdict['withinr']
withoutr = subdict['withoutr']
maxlength = subdict['maxlength']
minsfr = subdict['minsfr']
maxsfr = subdict['maxsfr']
maxlength = subdict['maxlength']
usesnipshot = subdict['usesnipshot']
title = ''
titleneed = title
ptitle = title
needlog = 0
dclabelneed = 1
correctIa = 0
useM1 = 0
resoneed = 0
rotface = 1
loccen = 1
newlabelneed = 1
fig, ax = PS.setupfig(nrows=1, ncols=1, sharex=True, sharey=False)
the_prefix = 'snapshot'
the_suffix = '.hdf5'
sigmaHIlosgridl = np.array([])
SFRdengridl = np.array([])
coloril = np.array([])
runtodol = np.array([])
for runtodo in dirneed:
for i in range(startno, Nsnap, snapsep):
info = SSF.outdirname(runtodo, i)
rundir = info['rundir']
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']
haveB = info['haveB']
Fcal = info['Fcal']
iavesfr = info['iavesfr']
timestep = info['timestep']
color = info['color']
h0 = info['h0']
cosmo = info['cosmo']
usepep = info['usepep']
maindir = info['maindir']
snumadd = info['snumadd']
halostr = info['halostr']
highres = info['highres']
rotface = 1
loccen = 1
if usesnipshot == 1:
commonpath = '/home/tkc004/scratch/snipshot/philruns/'
fname = commonpath + rundir + '/output/withinr20GS/snipshot_' + Nsnapstring + '.hdf5'
data = RSS.readsnipshot(fname, ptypelist=[0, 4])
G = data[0]
S = data[1]
oheader = readsnapcr(the_snapdir,
Nsnapstring,
0,
snapshot_name=the_prefix,
extension=the_suffix,
havecr=havecr,
h0=h0,
cosmological=cosmo,
header_only=0,
oheader_only=1)
S['header'] = oheader
#print 'oheader', oheader
else:
S = SSF.readsnapwcen(the_snapdir, Nsnapstring, 4, snapshot_name=the_prefix, extension=the_suffix,\
havecr=havecr,h0=h0,cosmo=cosmo, usepep=usepep, maindir=maindir,snumadd=snumadd,rotface=rotface,\
loccen=loccen,runtodo=runtodo,rundir=rundir,halostr=halostr)
G = SSF.readsnapwcen(the_snapdir, Nsnapstring, 0, snapshot_name=the_prefix, extension=the_suffix,\
havecr=havecr,h0=h0,cosmo=cosmo, usepep=usepep, maindir=maindir,snumadd=snumadd,rotface=rotface,\
loccen=loccen,runtodo=runtodo,rundir=rundir,halostr=halostr)
Sdata = SSF.calsfr(S, tintval=0.01, cosmo=1, withinr=20)
sfrl = Sdata['sfrl']
Sxl = Sdata['Sxl']
Syl = Sdata['Syl']
Szl = Sdata['Szl']
if wanted == 'SFRturrad':
xlist = np.linspace(-10, 10, num=40)
ylist = np.linspace(-10, 10, num=40)
rlist = np.linspace(0, 15, num=10)
data = calsigmaHIlos(G, xlist, ylist, maxlength)
newdata = SSF.calSFRsurdenxynew(sfrl, Sxl, Syl, Szl, xlist,
ylist, maxlength)
sigmaHIlosgrid = data['sigmaHIlosgrid']
HIm = data['HImgrid']
Hpos = data['pos']
sHIr = SSF.fromxytorad(sigmaHIlosgrid, Hpos, HIm, rlist)
SFRdengrid = newdata['SFRdengrid']
sarea = newdata['areagrid']
spos = newdata['pos']
SFRr = SSF.fromxytorad(SFRdengrid, spos, sarea, rlist)
sigmaHIlosgridl = np.append(sigmaHIlosgridl, sHIr)
SFRdengridl = np.append(SFRdengridl, SFRr)
if wanted == 'SFRturtot':
Sscaledata = SSF.findscalelength(S,
halfmassscale=0,
usecylr=1,
usecylz=0,
cutrout=10.,
cutzout=5.)
rs = Sscaledata['rs']
Sscalearea = 4.0 * np.pi * rs * rs #in kpc2
SFRtot = np.sum(sfrl) #in Msun/yr
SFRperarea = SFRtot / Sscalearea
SFRdengridl = np.append(SFRdengridl, SFRperarea)
vertical = 0
horizontal = 1
dr = 0.5 #kpc
griddir = 'grid0_5kpc'
usehalfz = 0
data = SSF.calrhogfrompreexist(runtodo,i,withinr,maxlength,\
usehalfz=usehalfz,griddir=griddir,\
cutcold=0,vertical=vertical,\
horizontal=horizontal,withoutr=withoutr,\
dr=dr,outHI=1)
pthl = data['pthl']
rhol = data['rhol']
pturHIl = data['pturHIl']
rhoHIl = data['rhoHIl']
volll = data['volll']
print 'rhol', rhol
massl = volll / rhol
vturHI2l = pturHIl / rhoHIl * massl
vth2l = pthl / rhol * GAMMA * massl
massl[~np.isfinite(massl)] = 0.0
vturHI2l[~np.isfinite(vturHI2l)] = 0.0
vth2l[~np.isfinite(vth2l)] = 0.0
vHIdis = np.sqrt(
np.sum(vturHI2l + vth2l) / np.sum(massl)) / km_in_cm
print 'runtodo', runtodo
print 'np.sqrt(np.sum(vturHI2l))', np.sqrt(np.sum(vturHI2l))
print 'np.sqrt(np.sum(vth2l))', np.sqrt(np.sum(vth2l))
sigmaHIlosgridl = np.append(sigmaHIlosgridl, vHIdis)
runtodol = np.append(runtodol, runtodo)
#print 'vHIdis', vHIdis
#print 'runtodo', runtodo
#print 'i', i
colori = highres
coloril = np.append(coloril, colori)
#print 'coloril', coloril
#print 'sigmaHIlosgridl', sigmaHIlosgridl
#print 'SFRdengridl', SFRdengridl
if wanted == 'SFRturrad':
ax.plot(SFRdengridl, sigmaHIlosgridl, color='k', ls='None', marker='s')
if wanted == 'SFRturtot':
neederrbar = 1
if neederrbar == 1:
for runtodo in dirneed:
Sds = SFRdengridl[runtodol == runtodo]
sHs = sigmaHIlosgridl[runtodol == runtodo]
cls = coloril[runtodol == runtodo]
Sdmed = np.median(Sds)
sHmed = np.median(sHs)
clmed = np.median(cls)
Sdu = np.percentile(Sds, 84) - Sdmed
Sdd = Sdmed - np.percentile(Sds, 15.8)
sHu = np.percentile(sHs, 84) - sHmed
sHd = sHmed - np.percentile(sHs, 15.8)
print 'Sdu,Sdmed,Sdd', Sdu, Sdmed, Sdd
print 'sHu,sHmed,sHd', sHu, sHmed, sHd
if clmed == 0:
color = 'k'
marker = 's'
if clmed == 1:
color = 'r'
marker = '^'
if clmed == 3:
color = 'g'
marker = 'o'
ax.errorbar(Sdmed,
sHmed,
xerr=[[Sdd], [Sdu]],
yerr=[[sHd], [sHu]],
color=color,
fmt=marker,
markersize=7)
else:
ax.plot(SFRdengridl[coloril == 0],
sigmaHIlosgridl[coloril == 0],
color='k',
ls='None',
marker='s')
ax.plot(SFRdengridl[coloril == 1],
sigmaHIlosgridl[coloril == 1],
color='r',
ls='None',
marker='^')
ax.plot(SFRdengridl[coloril == 3],
sigmaHIlosgridl[coloril == 3],
color='g',
ls='None',
marker='o')
plotobserved = 1
if plotobserved == 1:
ftxt = open(programdir + '/data/DibsigmaSFRA.txt', 'r')
ftxt.readline()
dars = ftxt.readlines()
ftxt.close()
obslogSFRA = []
obssigma = []
for line in dars:
xsd = line.split()
obslogSFRA = np.append(obslogSFRA, float(xsd[0]))
obssigma = np.append(obssigma, float(xsd[1]))
ax.plot(np.power(10, obslogSFRA),
obssigma,
markeredgecolor='k',
markerfacecolor="None",
ls='None',
marker='D')
#ax.plot(np.power(10,-1.59832), 34.8944,markeredgecolor='k',markerfacecolor="k",ls='None',marker='D')
ax.set_ylim(ymin=1, ymax=50)
ax.set_xlim(xmin=1e-5, xmax=0.5)
xlab = r'${\rm \Sigma_{SFR}\;[M_\odot/yr/kpc^2]}$'
ylab = r'${\rm \sigma_{HI}[km/s]}$'
ax.set_title(ptitle, fontsize=16)
PS.miscsetup(ax,
logx=1,
logy=0,
xlab=xlab,
ylab=ylab,
legendneed=0,
labfs=22,
legfs=12)
import matplotlib.lines as mlines
potk = mlines.Line2D([], [], color='k', ls='None', marker='s')
potr = mlines.Line2D([], [], color='r', ls='None', marker='^')
potg = mlines.Line2D([], [], color='g', ls='None', marker='o')
poto = mlines.Line2D([], [],
markeredgecolor='k',
markerfacecolor="None",
ls='None',
marker='D')
lxlist = [
#potk,
potr,
potg,
poto
]
lablist = [
#'no CR',
#'MHD no CR',
'MHD+',
'CR+',
#r'MHD $\kappa$=3e29',
'Obs'
]
legend1 = plt.legend(lxlist,
lablist,
loc='upper left',
fontsize=14,
ncol=1)
plt.gca().add_artist(legend1)
if wanted == 'SFRturrad':
filename = plotloc + 'CRplot/sfrtur/Sigmasfr_sigmaHI_' + fmeat + '_sn' + str(
startno) + '_' + str(Nsnap) + '.pdf'
if wanted == 'SFRturtot':
filename = plotloc + 'CRplot/sfrtur/Sigmasfr_sigmaHItot_' + fmeat + '_sn' + str(
startno) + '_' + str(Nsnap) + '.pdf'
PS.finishsave(plt, filename)
def Tztrack_outtestinput(subdict):
dirneed = subdict['dirneed']
wanted = subdict['wanted']
Tcut_t = subdict['Tcut_t'] #K
highTcut_t = subdict['highTcut_t']
hotwarmmode = subdict['hotwarmmode']
trackstart = subdict['trackstart']
if hotwarmmode == 1:
modedict = collections.defaultdict(dict)
modelist = ['hot', 'warm']
modedict['warm']['Tcut_t'] = 1.0
modedict['warm']['highTcut_t'] = 1.0e5
modedict['hot']['Tcut_t'] = 1.0e5
modedict['hot']['highTcut_t'] = 1.0e10
modedict['warm']['lsn'] = 'dashed'
modedict['hot']['lsn'] = 'dotted'
else:
modedict = collections.defaultdict(dict)
modelist = ['normal']
modedict['normal']['Tcut_t'] = Tcut_t
modedict['normal']['highTcut_t'] = highTcut_t
dirdict = collections.defaultdict(dict)
keylist = np.array([])
for ir, subdirneed in enumerate(dirneed):
keylist = np.append(keylist, keystore[ir])
dirdict[keystore[ir]] = subdirneed
noplots = 1
fig, ax = PS.setupfig(nrows=noplots, ncols=1, sharex=True, sharey=False)
for i, key in enumerate(keylist):
items = dirdict[key]
ssdict = collections.defaultdict(dict)
ssdict = subdict
for j, runtodo in enumerate(items):
ssdict['runtodo'] = runtodo
print 'runtodo', runtodo
for labelcount, modekey in enumerate(modelist):
ssdict['Tcut_t'] = modedict[modekey]['Tcut_t']
ssdict['highTcut_t'] = modedict[modekey]['highTcut_t']
print 'modekey', modekey
print 'ssdict[Tcut_t]', ssdict['Tcut_t']
print 'ssdict[highTcut_t]', ssdict['highTcut_t']
plotdict = Tztrack_out(ssdict)
xlab = plotdict[wanted]['xlab']
ylab = plotdict[wanted]['ylab']
ptitle = plotdict[wanted]['ptitle']
filename = plotdict[wanted]['filename']
xpoints = plotdict[wanted]['xnl']
ypoints = plotdict[wanted]['ynl']
labelneed = plotdict[wanted]['labelneed']
color = plotdict[wanted]['color']
lsn = plotdict[wanted]['lsn']
if hotwarmmode == 1:
lsn = modedict[modekey]['lsn']
lw = plotdict[wanted]['lw']
marker = plotdict[wanted]['marker']
linelabel = plotdict[wanted]['linelab']
legendneed = plotdict[wanted]['legendneed']
print 'xpoints,ypoints', xpoints, ypoints
if labelcount == 0:
ax.plot(xpoints,
ypoints,
label=labelneed,
lw=lw,
ls=lsn,
color=color)
else:
ax.plot(xpoints,
ypoints,
lw=lw,
ls=lsn,
color=color,
marker=marker)
ax.scatter(xpoints[1:-1], ypoints[1:-1], color=color)
if labelcount == 0 and j == 0:
ax.scatter(xpoints[0],
ypoints[0],
color=color,
marker='s',
s=4 * rcParams['lines.markersize']**2,
label='Start')
ax.scatter(xpoints[-1],
ypoints[-1],
color=color,
marker='>',
s=4 * rcParams['lines.markersize']**2,
label='End')
else:
ax.scatter(xpoints[0],
ypoints[0],
color=color,
marker='s',
s=4 * rcParams['lines.markersize']**2)
ax.scatter(xpoints[-1],
ypoints[-1],
color=color,
marker='>',
s=4 * rcParams['lines.markersize']**2)
logx = 1
if trackstart == 1:
logx = 0
PS.miscsetup(ax,
logx=logx,
logy=1,
xlab=xlab,
ylab=ylab,
legendneed=legendneed,
labfs=22,
legfs=20)
if hotwarmmode == 1:
plt.xlim([np.log10(5.0), 2.0])
if trackstart == 1:
plt.xlim([np.log10(0.5), 2.0])
PS.finishsave(plt, filename)
return None
def sfrtestinput(subdict):
nested_dict = lambda: collections.defaultdict(nested_dict)
plotdict = nested_dict()
startno = subdict['startno']
Nsnap = subdict['Nsnap']
snapsep = subdict['snapsep']
wanted = subdict['wanted']
dirneed = subdict['dirneed']
fmeat = subdict['fmeat']
withinr = subdict['withinr']
withoutr = subdict['withoutr']
maxlength = subdict['maxlength']
minsfr = subdict['minsfr']
maxsfr = subdict['maxsfr']
title = ''
titleneed = title
ptitle = title
needlog = 0
dclabelneed = 1
correctIa = 0
useM1 = 0
resoneed = 0
rotface = 1
loccen = 1
newlabelneed = 1
findradiusatnism = 1 #find the radius that has that ISM density (negative to turn off)
withinr = 5. #withinr will change according to the above
dr = 2.
fig, ax = PS.setupfig(nrows=1, ncols=1, sharex=True, sharey=False)
if wanted == 'sfr':
ncount = 0
ncrcount = 0
nbcount = 0
energylabel = 1
usesolarcircle = 0
usecentral = 0
if usesolarcircle == 1:
fmeat += '_usesolarcircle'
elif usecentral == 1:
fmeat += '_usecentral'
turt = []
thermt = []
crt = []
Begyt = []
sfrl = []
gml = []
coloril = []
runtodol = []
for runtodo in dirneed:
info = SSF.outdirname(runtodo, Nsnap)
rundir = info['rundir']
runtitle = info['runtitle']
slabel = info['slabel']
snlabel = info['snlabel']
dclabel = info['dclabel']
resolabel = info['resolabel']
the_snapdir = info['the_snapdir']
the_prefix = info['the_prefix']
the_suffix = info['the_suffix']
Nsnapstring = info['Nsnapstring']
havecr = info['havecr']
Fcal = info['Fcal']
iavesfr = info['iavesfr']
timestep = info['timestep']
maindir = info['maindir']
haveB = info['haveB']
cosmo = info['cosmo']
newlabel = info['newlabel']
color = info['color']
usepep = info['usepep']
snumadd = info['snumadd']
halostr = info['halostr']
h0 = info['h0']
highres = info['highres']
ptitle = title
if runtitle == 'SMC':
ptitle = 'Dwarf'
elif runtitle == 'SBC':
ptitle = 'Starburst'
elif runtitle == 'MW':
ptitle = r'$L\star$ Galaxy'
labelneed = dclabel
if newlabelneed == 1:
labelneed = "\n".join(wrap(newlabel, 17))
for i in range(startno, Nsnap, snapsep):
try:
info = SSF.outdirname(runtodo, i)
Nsnapstring = info['Nsnapstring']
S = SSF.readsnapwcen(the_snapdir, Nsnapstring, 4, snapshot_name=the_prefix, extension=the_suffix,\
havecr=havecr,h0=h0,cosmo=cosmo, usepep=usepep, maindir=maindir,snumadd=snumadd,rotface=rotface,\
loccen=loccen,runtodo=runtodo,rundir=rundir,halostr=halostr)
sfrdata = SSF.calsfr(S, cosmo=cosmo)
sfr = sfrdata['sfr']
runtodol = np.append(runtodol, runtodo)
sfrl = np.append(sfrl, sfr)
colori = highres
coloril = np.append(coloril, colori)
except (ZeroDivisionError, IndexError):
continue
print 'runtodol', runtodol
print 'sfrl', sfrl
def Blitzmidplanepressure_testinput(subdict):
nested_dict = lambda: collections.defaultdict(nested_dict)
plotdict = nested_dict()
startno=subdict['startno']
Nsnap=subdict['Nsnap']
snapsep=subdict['snapsep']
wanted=subdict['wanted']
dirneed=subdict['dirneed']
fmeat=subdict['fmeat']
withinr=subdict['withinr']
withoutr=subdict['withoutr']
maxlength=subdict['maxlength']
minsfr=subdict['minsfr']
maxsfr=subdict['maxsfr']
maxlength=subdict['maxlength']
usesnipshot=subdict['usesnipshot']
title=''
titleneed=title
ptitle=title
needlog=0
dclabelneed=1
correctIa=0
useM1=0
resoneed=0
rotface=1
loccen=1
newlabelneed=1
the_prefix = 'snapshot'
the_suffix = '.hdf5'
sigmaHIlosgridl=np.array([])
SFRdengridl=np.array([])
coloril=np.array([])
runtodol=np.array([])
for runtodo in dirneed:
fig, ax = PS.setupfig(nrows=1, ncols=1,sharex=True,sharey=False)
i=Nsnap
info=SSF.outdirname(runtodo, i)
rundir=info['rundir']
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']
haveB=info['haveB']
Fcal=info['Fcal']
iavesfr=info['iavesfr']
timestep=info['timestep']
color=info['color']
h0=info['h0']
cosmo=info['cosmo']
usepep=info['usepep']
maindir=info['maindir']
snumadd=info['snumadd']
halostr=info['halostr']
highres=info['highres']
rotface = 1
loccen = 1
if usesnipshot==1:
commonpath='/home/tkc004/scratch/snipshot/philruns/'
fname=commonpath+rundir+'/output/withinr20GS/snipshot_'+Nsnapstring+'.hdf5'
data = RSS.readsnipshot(fname,ptypelist = [0,4])
G = data[0];
S = data[1];
oheader = readsnapcr(the_snapdir, Nsnapstring, 0, snapshot_name=the_prefix,\
extension=the_suffix, havecr=havecr,h0=h0,cosmological=cosmo,\
header_only=0,oheader_only=1)
S['header']=oheader
#print 'oheader', oheader
else:
S = SSF.readsnapwcen(the_snapdir, Nsnapstring, 4, snapshot_name=the_prefix, extension=the_suffix,\
havecr=havecr,h0=h0,cosmo=cosmo, usepep=usepep, maindir=maindir,snumadd=snumadd,rotface=rotface,\
loccen=loccen,runtodo=runtodo,rundir=rundir,halostr=halostr)
G = SSF.readsnapwcen(the_snapdir, Nsnapstring, 0, snapshot_name=the_prefix, extension=the_suffix,\
havecr=havecr,h0=h0,cosmo=cosmo, usepep=usepep, maindir=maindir,snumadd=snumadd,rotface=rotface,\
loccen=loccen,runtodo=runtodo,rundir=rundir,halostr=halostr)
rlist = np.linspace(0,10,num=10)
gasdenlist = SSF.calsurden(G,rlist,maxlength)
stardenlist = SSF.calsurden(S,rlist,maxlength)
propconst = Msun_in_g/pc_in_cm/pc_in_cm
gasdenlist = gasdenlist*propconst
stardenlist = stardenlist*propconst
Sscaledata = SSF.findscalelength(S, halfmassscale=0, usecylr=0, usecylz=1, cutrout =10., cutzout = 5.)
hstar = Sscaledata['rs']
hstar =hstar*kpc_in_cm
Gscaledata = SSF.findscalelength(G, halfmassscale=0, usecylr=0, usecylz=1, cutrout =10., cutzout = 5.)
hgas = Gscaledata['rs']
hgas = hgas*kpc_in_cm
vertical=0; horizontal=1;
dr = 0.5 #kpc
griddir = 'grid0_5kpc'
usehalfz=0
data = SSF.calrhogfrompreexist(runtodo,i,withinr,maxlength,\
usehalfz=usehalfz,griddir=griddir,\
cutcold=0,vertical=vertical,\
horizontal=horizontal,withoutr=withoutr,\
dr=dr,outHI=1)
pthl = data['pthl']; rhol = data['rhol'];
pturHIl = data['pturHIl']; rhoHIl = data['rhoHIl'];
volll = data['volll']
massl = volll/rhol
vturHI2l = pturHIl/rhoHIl*massl
vth2l = pthl/rhol*GAMMA*massl
massl[~np.isfinite(massl)]=0.0
vturHI2l[~np.isfinite(vturHI2l)]=0.0
vth2l[~np.isfinite(vth2l)]=0.0
vHIdis = np.sqrt(np.sum(vturHI2l+vth2l)/np.sum(massl))
#finally Blitz & Rosolowsky 2004 formula:
pext = np.sqrt(2.0*NewtonG_in_cgs*stardenlist/hstar)*gasdenlist*vHIdis
#with gas gravity:
pextg = np.sqrt(2.0*NewtonG_in_cgs)*gasdenlist*vHIdis*\
(np.sqrt(stardenlist/hstar)+np.sqrt(np.pi/4.0*gasdenlist/hgas))
ax.plot(rlist, pext)
ax.plot(rlist, pextg,ls='dashed')
xlab = r'$ r\;[{\rm kpc]}$'
ylab = r'$ P_{\rm ext}[{\rm dyne/cm^2]}$'
ax.set_title(ptitle, fontsize=16)
PS.miscsetup(ax,logx=0,logy=1,xlab=xlab,ylab=ylab,legendneed=0,labfs=22,legfs=12)
filename=plotloc+'CRplot/Pext/Pext_Blitz_'+runtodo+'_sn'+str(Nsnap)+'.pdf'
PS.finishsave(plt,filename)
def main():
#startno=450
#Nsnap=500
startno = 550
Nsnap = 600
snapsep = 50
wanted = 'Tztrack'
trackstart = 1
dirdict = collections.defaultdict(dict)
keylist = ['plot1']
dirdict['plot1'] = ['m12imhdcvhr']
#dirdict['plot1']=['m12icr_700hr']
noplots = len(dirdict.keys())
fig, ax = PS.setupfig(nrows=noplots, ncols=1, sharex=True, sharey=False)
fmeat = ''
for i, key in enumerate(keylist):
items = dirdict[key]
for j, runtodo in enumerate(items):
print 'runtodo', runtodo
plotdict = calTz(runtodo,
wanted,
startno,
Nsnap,
snapsep,
fmeat,
trackstart=trackstart)
xlab = plotdict[wanted]['xlab']
ylab = plotdict[wanted]['ylab']
ptitle = plotdict[wanted]['ptitle']
filename = plotdict[wanted]['filename']
xpoints = plotdict[wanted]['xnl']
ypoints = plotdict[wanted]['ynl']
labelneed = plotdict[wanted]['labelneed']
color = plotdict[wanted]['color']
lsn = plotdict[wanted]['lsn']
lw = plotdict[wanted]['lw']
marker = plotdict[wanted]['marker']
linelabel = plotdict[wanted]['linelab']
legendneed = plotdict[wanted]['legendneed']
print 'lw', lw
print 'lsn', lsn
print 'color', color
print 'marker', marker
if noplots == 1:
ax.plot(xpoints,
ypoints,
label=labelneed,
lw=lw,
ls=lsn,
color=color,
marker=marker)
else:
ax[i].plot(xpoints,
ypoints,
label=labelneed,
lw=lw,
ls=lsn,
color=color,
marker=marker)
ax.scatter(xpoints[1:-1], ypoints[1:-1], color=color)
ax.scatter(xpoints[0],
ypoints[0],
color=color,
marker='s',
s=4 * rcParams['lines.markersize']**2)
ax.scatter(xpoints[-1],
ypoints[-1],
color=color,
marker='>',
s=4 * rcParams['lines.markersize']**2)
if i < noplots - 1: xlab = ''
if noplots == 1:
ax.text(0.25,
0.95,
ptitle,
horizontalalignment='center',
verticalalignment='center',
transform=ax.transAxes,
fontsize=22)
PS.miscsetup(ax,
logx=1,
logy=1,
xlab=xlab,
ylab=ylab,
legendneed=legendneed,
labfs=22,
legfs=12)
else:
ax[i].text(0.25,
0.95,
ptitle,
horizontalalignment='center',
verticalalignment='center',
transform=ax[i].transAxes,
fontsize=22)
PS.miscsetup(ax[i],
logx=1,
logy=1,
xlab=xlab,
ylab=ylab,
legendneed=legendneed,
labfs=22,
legfs=12)
PS.finishsave(plt, filename)
