def plot_hrhrvshr(options,args):
"""Plot hr^out/hr^in as a function of hr for various sr"""
if len(args) == 0.:
print "Must provide a savefilename ..."
print "Returning ..."
return None
if os.path.exists(args[0]):
#Load
savefile= open(args[0],'rb')
plotthis= pickle.load(savefile)
hrs= pickle.load(savefile)
srs= pickle.load(savefile)
savefile.close()
else:
#Grid of models to test
hrs= numpy.linspace(options.hrmin,options.hrmax,options.nhr)
srs= numpy.linspace(options.srmin,options.srmax,options.nsr)
#Tile
hrs= numpy.tile(hrs,(options.nsr,1)).T
srs= numpy.tile(srs,(options.nhr,1))
plotthis= numpy.zeros((options.nhr,options.nsr))
#Setup potential and aA
poptions= setup_options(None)
#poptions.potential= 'dpdiskplhalofixbulgeflatwgasalt'
#params= [0.,0.,0.,0.,0.,0.,-1.16315,1.,-3.,0.4,0.]
poptions.potential= 'btii'
params= None
#pot= MWPotential
pot= setup_potential(params,poptions,1)
if options.aAmethod.lower() == 'staeckel':
aA= actionAngleStaeckel(pot=pot,delta=0.45,c=True)
else:
aA=actionAngleAdiabaticGrid(pot=pot,nR=16,nEz=16,nEr=31,nLz=31,
zmax=1.,Rmax=5.)
for ii in range(options.nhr):
for jj in range(options.nsr):
qdf= quasiisothermaldf(hrs[ii,jj]/8.,srs[ii,jj]/220.,
srs[ii,jj]/numpy.sqrt(3.)/220.,
7./8.,1.,
pot=pot,aA=aA)
plotthis[ii,jj]= qdf.estimate_hr(1.,z=0.8/8.,
dR=0.33,
gl=True)/hrs[ii,jj]*8.
print ii*options.nsr+jj+1, options.nsr*options.nhr, \
hrs[ii,jj], srs[ii,jj], plotthis[ii,jj]
#Save
save_pickles(args[0],plotthis,hrs,srs)
#Now plot
bovy_plot.bovy_print(fig_width=6.,
text_fontsize=20.,
legend_fontsize=24.,
xtick_labelsize=18.,
ytick_labelsize=18.,
axes_labelsize=24.)
indx= 0
lines= []
colors= [cm.jet(ii/float(options.nsr-1.)*1.+0.) for ii in range(options.nsr)]
lss= ['-' for ii in range(options.nsr)]#,'--','-.','..']
labels= []
lines.append(bovy_plot.bovy_plot(hrs[:,indx],plotthis[:,indx],
color=colors[indx],ls=lss[indx],
xrange=[0.5,5.5],
yrange=[0.,2.],
xlabel=r'$h^{\mathrm{in}}_R\ \mathrm{at}\ 8\,\mathrm{kpc}$',
ylabel=r'$h^{\mathrm{out}}_R / h^{\mathrm{in}}_R$'))
labels.append(r'$\sigma_R = %.0f \,\mathrm{km\,s}^{-1}$' % srs[0,indx])
for indx in range(1,options.nsr):
lines.append(bovy_plot.bovy_plot(hrs[:,indx],plotthis[:,indx],
color=colors[indx],ls=lss[indx],
overplot=True))
labels.append(r'$\sigma_R = %.0f \,\mathrm{km\,s}^{-1}$' % srs[0,indx])
"""
#Legend
pyplot.legend(lines,#(line1[0],line2[0],line3[0],line4[0]),
labels,#(r'$v_{bc} = 0$',
# r'$v_{bc} = 1\,\sigma_{bc}$',
# r'$v_{bc} = 2\,\sigma_{bc}$',
# r'$v_{bc} = 3\,\sigma_{bc}$'),
loc='lower right',#bbox_to_anchor=(.91,.375),
numpoints=2,
prop={'size':14},
frameon=False)
"""
#Add colorbar
map = cm.ScalarMappable(cmap=cm.jet)
map.set_array(srs[0,:])
map.set_clim(vmin=numpy.amin(srs[0,:]),vmax=numpy.amax(srs[0,:]))
cbar= pyplot.colorbar(map,fraction=0.15)
cbar.set_clim(numpy.amin(srs[0,:]),numpy.amax(srs[0,:]))
cbar.set_label(r'$\sigma_R \,(\mathrm{km\,s}^{-1})$')
bovy_plot.bovy_end_print(options.plotfilename)
def plot_hzszq(options,args):
"""Plot sz,hz, q"""
if len(args) == 0.:
print "Must provide a savefilename ..."
print "Returning ..."
return None
nqs, nszs, nhzs= 31, 51, 51
#nqs, nszs, nhzs= 5,5,5
if os.path.exists(args[0]):
#Load
savefile= open(args[0],'rb')
hzs= pickle.load(savefile)
szs= pickle.load(savefile)
qs= pickle.load(savefile)
savefile.close()
else:
qs= numpy.linspace(0.5,1.,nqs)
szs= numpy.linspace(15.,50.,nszs)
hzs= numpy.zeros((nqs,nszs))
for ii in range(nqs):
print "Working on potential %i / %i ..." % (ii+1,nqs)
#Setup potential
lp= LogarithmicHaloPotential(normalize=1.,q=qs[ii])
if options.aAmethod.lower() == 'staeckel':
aA= actionAngleStaeckel(pot=lp,delta=0.45,c=True)
else:
aA=actionAngleAdiabaticGrid(pot=pot,nR=16,nEz=16,nEr=31,nLz=31,
zmax=1.,Rmax=5.)
for jj in range(nszs):
qdf= quasiisothermaldf(options.hr/8.,2.*szs[jj]/220.,
szs[jj]/220.,7./8.,7./8.,pot=lp,
aA=aA,cutcounter=True)
hzs[ii,jj]= qdf.estimate_hz(1.,z=0.125)
#Save
save_pickles(args[0],hzs,szs,qs)
#Re-sample
hzsgrid= numpy.linspace(50.,1500.,nhzs)/8000.
qs2d= numpy.zeros((nhzs,nszs))
for ii in range(nszs):
interpQ= interpolate.UnivariateSpline(hzs[:,ii],qs,k=3)
qs2d[:,ii]= interpQ(hzsgrid)
qs2d[(hzsgrid < hzs[0,ii]),ii]= numpy.nan
qs2d[(hzsgrid > hzs[-1,ii]),ii]= numpy.nan
#Now plot
bovy_plot.bovy_print(fig_width=6.,
text_fontsize=20.,
legend_fontsize=24.,
xtick_labelsize=18.,
ytick_labelsize=18.,
axes_labelsize=24.)
bovy_plot.bovy_dens2d(qs2d.T,origin='lower',cmap='jet',
interpolation='gaussian',
# interpolation='nearest',
ylabel=r'$\sigma_z\ [\mathrm{km\,s}^{-1}]$',
xlabel=r'$h_z\ [\mathrm{pc}]$',
zlabel=r'$\mathrm{flattening}\ q$',
yrange=[szs[0],szs[-1]],
xrange=[8000.*hzsgrid[0],8000.*hzsgrid[-1]],
# vmin=0.5,vmax=1.,
contours=False,
colorbar=True,shrink=0.78)
_OVERPLOTMAPS= True
if _OVERPLOTMAPS:
fehs= monoAbundanceMW.fehs()
afes= monoAbundanceMW.afes()
npops= len(fehs)
mapszs= []
maphzs= []
for ii in range(npops):
thissz, thiserr= monoAbundanceMW.sigmaz(fehs[ii],afes[ii],err=True)
if thiserr/thissz > 0.1:
continue
thishz, thiserr= monoAbundanceMW.hz(fehs[ii],afes[ii],err=True)
if thiserr/thishz > 0.1:
continue
mapszs.append(thissz)
maphzs.append(thishz)
mapszs= numpy.array(mapszs)
maphzs= numpy.array(maphzs)
bovy_plot.bovy_plot(maphzs,mapszs,'ko',overplot=True,mfc='none',mew=1.5)
bovy_plot.bovy_text(r'$h_R = %i\,\mathrm{kpc}$' % int(options.hr),
bottom_right=True)
bovy_plot.bovy_end_print(options.plotfilename)
def plot_szszvssz(options,args):
"""Plot sz^out/sz^in as a function of sz for various hr"""
if len(args) == 0.:
print "Must provide a savefilename ..."
print "Returning ..."
return None
if os.path.exists(args[0]):
#Load
savefile= open(args[0],'rb')
plotthis= pickle.load(savefile)
szs= pickle.load(savefile)
hrs= pickle.load(savefile)
savefile.close()
else:
#Grid of models to test
if options.subtype.lower() == 'sr':
szs= numpy.linspace(options.srmin,options.srmax,options.nsz)
else:
szs= numpy.linspace(options.szmin,options.szmax,options.nsz)
hrs= numpy.linspace(options.hrmin,options.hrmax,options.nhr)
#Tile
szs= numpy.tile(szs,(options.nhr,1)).T
hrs= numpy.tile(hrs,(options.nsz,1))
plotthis= numpy.zeros((options.nsz,options.nhr))
#Setup potential and aA
poptions= setup_options(None)
#poptions.potential= 'dpdiskplhalofixbulgeflatwgasalt'
#params= [0.,0.,0.,0.,0.,0.,-1.16315,1.,-3.,0.4,0.]
poptions.potential= 'btii'
params= None
#pot= MWPotential
pot= setup_potential(params,poptions,1)
if options.aAmethod.lower() == 'staeckel':
aA= actionAngleStaeckel(pot=pot,delta=0.45,c=True)
else:
aA=actionAngleAdiabaticGrid(pot=pot,nR=16,nEz=16,nEr=31,nLz=31,
zmax=1.,Rmax=5.)
for ii in range(options.nsz):
for jj in range(options.nhr):
if options.subtype.lower() == 'sr':
qdf= quasiisothermaldf(hrs[ii,jj]/8.,
szs[ii,jj]/220.,
szs[ii,jj]/220./numpy.sqrt(3.),
7./8.,1.,
pot=pot,aA=aA)
else:
qdf= quasiisothermaldf(hrs[ii,jj]/8.,
szs[ii,jj]/220.*numpy.sqrt(3.),
szs[ii,jj]/220.,
7./8.,1.,
pot=pot,aA=aA)
if options.subtype.lower() == 'sr':
plotthis[ii,jj]= numpy.sqrt(qdf.sigmaR2(1.,0.8/8.,
gl=True))/szs[ii,jj]*220.
else:
plotthis[ii,jj]= numpy.sqrt(qdf.sigmaz2(1.,0.8/8.,
gl=True))/szs[ii,jj]*220.
print ii*options.nhr+jj+1, options.nhr*options.nsz, \
szs[ii,jj], hrs[ii,jj], plotthis[ii,jj]
#Save
save_pickles(args[0],plotthis,szs,hrs)
#Now plot
bovy_plot.bovy_print(fig_width=6.,
text_fontsize=20.,
legend_fontsize=24.,
xtick_labelsize=18.,
ytick_labelsize=18.,
axes_labelsize=24.)
indx= 0
lines= []
colors= [cm.jet(ii/float(options.nhr-1.)*1.+0.) for ii in range(options.nhr)]
lss= ['-' for ii in range(options.nhr)]#,'--','-.','..']
labels= []
if options.subtype.lower() == 'sr':
lines.append(bovy_plot.bovy_plot(szs[:,indx],plotthis[:,indx],
color=colors[indx],ls=lss[indx],
xrange=[10.,85.],
yrange=[0.8,1.5],
xlabel=r'$\sigma^{\mathrm{in}}_R\ \mathrm{at}\ R = 8\,\mathrm{kpc}$',
ylabel=r'$\sigma^{\mathrm{out}}_R / \sigma^{\mathrm{in}}_R$'))
else:
lines.append(bovy_plot.bovy_plot(szs[:,indx],plotthis[:,indx],
color=colors[indx],ls=lss[indx],
xrange=[10.,115.],
yrange=[0.5,1.2],
xlabel=r'$\sigma^{\mathrm{in}}_Z\ \mathrm{at}\ R = 8\,\mathrm{kpc}$',
ylabel=r'$\sigma^{\mathrm{out}}_Z / \sigma^{\mathrm{in}}_Z$'))
for indx in range(1,options.nhr):
lines.append(bovy_plot.bovy_plot(szs[:,indx],plotthis[:,indx],
color=colors[indx],ls=lss[indx],
overplot=True))
#Add colorbar
map = cm.ScalarMappable(cmap=cm.jet)
map.set_array(hrs[0,:])
map.set_clim(vmin=numpy.amin(hrs[0,:]),vmax=numpy.amax(hrs[0,:]))
cbar= pyplot.colorbar(map,fraction=0.15)
cbar.set_clim(numpy.amin(hrs[0,:]),numpy.amax(hrs[0,:]))
cbar.set_label(r'$h_R\, (\mathrm{kpc})$')
bovy_plot.bovy_end_print(options.plotfilename)
