def test_actionAngleTorus_basic():
from galpy.actionAngle import actionAngleTorus
from galpy.potential import MWPotential, rl, vcirc, \
FlattenedPowerPotential, PlummerPotential
tol= -4.
jr= 10.**-10.
jz= 10.**-10.
aAT= actionAngleTorus(pot=MWPotential)
# at R=1, Lz=1
jphi= 1.
angler= numpy.linspace(0.,2.*numpy.pi,101)
anglephi= numpy.linspace(0.,2.*numpy.pi,101)+1.
anglez= numpy.linspace(0.,2.*numpy.pi,101)+2.
RvR= aAT(jr,jphi,jz,angler,anglephi,anglez).T
assert numpy.all(numpy.fabs(RvR[0]-rl(MWPotential,jphi)) < 10.**tol), \
'circular orbit does not have constant radius for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[1]) < 10.**tol), \
'circular orbit does not have zero radial velocity for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[2]-vcirc(MWPotential,rl(MWPotential,jphi))) < 10.**tol), \
'circular orbit does not have constant vT=vc for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[3]) < 10.**tol), \
'circular orbit does not have zero vertical height for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[4]) < 10.**tol), \
'circular orbit does not have zero vertical velocity for actionAngleTorus'
# at Lz=1.5, using Plummer
tol= -3.25
pp= PlummerPotential(normalize=1.)
aAT= actionAngleTorus(pot=pp)
jphi= 1.5
RvR= aAT(jr,jphi,jz,angler,anglephi,anglez).T
assert numpy.all(numpy.fabs(RvR[0]-rl(pp,jphi)) < 10.**tol), \
'circular orbit does not have constant radius for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[1]) < 10.**tol), \
'circular orbit does not have zero radial velocity for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[2]-vcirc(pp,rl(pp,jphi))) < 10.**tol), \
'circular orbit does not have constant vT=vc for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[3]) < 10.**tol), \
'circular orbit does not have zero vertical height for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[4]) < 10.**tol), \
'circular orbit does not have zero vertical velocity for actionAngleTorus'
# at Lz=0.5, using FlattenedPowerPotential
tol= -4.
fp= FlattenedPowerPotential(normalize=1.)
aAT= actionAngleTorus(pot=fp)
jphi= 0.5
RvR= aAT(jr,jphi,jz,angler,anglephi,anglez).T
assert numpy.all(numpy.fabs(RvR[0]-rl(fp,jphi)) < 10.**tol), \
'circular orbit does not have constant radius for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[1]) < 10.**tol), \
'circular orbit does not have zero radial velocity for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[2]-vcirc(fp,rl(fp,jphi))) < 10.**tol), \
'circular orbit does not have constant vT=vc for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[3]) < 10.**tol), \
'circular orbit does not have zero vertical height for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[4]) < 10.**tol), \
'circular orbit does not have zero vertical velocity for actionAngleTorus'
return None
def test_actionAngleTorus_basic():
from galpy.actionAngle import actionAngleTorus
from galpy.potential import MWPotential, rl, vcirc, \
FlattenedPowerPotential, PlummerPotential
tol= -4.
jr= 10.**-10.
jz= 10.**-10.
aAT= actionAngleTorus(pot=MWPotential)
# at R=1, Lz=1
jphi= 1.
angler= numpy.linspace(0.,2.*numpy.pi,101)
anglephi= numpy.linspace(0.,2.*numpy.pi,101)+1.
anglez= numpy.linspace(0.,2.*numpy.pi,101)+2.
RvR= aAT(jr,jphi,jz,angler,anglephi,anglez).T
assert numpy.all(numpy.fabs(RvR[0]-rl(MWPotential,jphi)) < 10.**tol), \
'circular orbit does not have constant radius for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[1]) < 10.**tol), \
'circular orbit does not have zero radial velocity for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[2]-vcirc(MWPotential,rl(MWPotential,jphi))) < 10.**tol), \
'circular orbit does not have constant vT=vc for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[3]) < 10.**tol), \
'circular orbit does not have zero vertical height for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[4]) < 10.**tol), \
'circular orbit does not have zero vertical velocity for actionAngleTorus'
# at Lz=1.5, using Plummer
tol= -3.25
pp= PlummerPotential(normalize=1.)
aAT= actionAngleTorus(pot=pp)
jphi= 1.5
RvR= aAT(jr,jphi,jz,angler,anglephi,anglez).T
assert numpy.all(numpy.fabs(RvR[0]-rl(pp,jphi)) < 10.**tol), \
'circular orbit does not have constant radius for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[1]) < 10.**tol), \
'circular orbit does not have zero radial velocity for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[2]-vcirc(pp,rl(pp,jphi))) < 10.**tol), \
'circular orbit does not have constant vT=vc for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[3]) < 10.**tol), \
'circular orbit does not have zero vertical height for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[4]) < 10.**tol), \
'circular orbit does not have zero vertical velocity for actionAngleTorus'
# at Lz=0.5, using FlattenedPowerPotential
tol= -4.
fp= FlattenedPowerPotential(normalize=1.)
aAT= actionAngleTorus(pot=fp)
jphi= 0.5
RvR= aAT(jr,jphi,jz,angler,anglephi,anglez).T
assert numpy.all(numpy.fabs(RvR[0]-rl(fp,jphi)) < 10.**tol), \
'circular orbit does not have constant radius for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[1]) < 10.**tol), \
'circular orbit does not have zero radial velocity for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[2]-vcirc(fp,rl(fp,jphi))) < 10.**tol), \
'circular orbit does not have constant vT=vc for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[3]) < 10.**tol), \
'circular orbit does not have zero vertical height for actionAngleTorus'
assert numpy.all(numpy.fabs(RvR[4]) < 10.**tol), \
'circular orbit does not have zero vertical velocity for actionAngleTorus'
return None
def vcirc(self,R):
from galpy.potential import vcirc
if self._interpvcirc:
indx= (R >= self._rgrid[0])*(R <= self._rgrid[-1])
out= numpy.empty_like(R)
if numpy.sum(indx) > 0:
if self._logR:
out[indx]= self._vcircInterp(numpy.log(R[indx]))
else:
out[indx]= self._vcircInterp(R[indx])
if numpy.sum(True^indx) > 0:
out[True^indx]= vcirc(self._origPot,R[True^indx])
return out
else:
return vcirc(self._origPot,R)
def circular_velocity(self, r):
vcirc = potential.vcirc(self.pot,
r.value_in(units.kpc) / self.ro,
phi=0,
ro=self.ro,
vo=self.vo) | units.kms
return vcirc
def galactic_velocity(self, gal, interpolants, fixed_potential=None):
"""
Calculates the pre-SN galactic velocity for the tracer particles at their initial radius R.
"""
print('Calculating the pre-SN galactic velocity...\n')
# --- Using galpy's vcirc method, we can easily calculate the rotation velocity at any R
R_vals = self.R
Vcircs = []
for idx, (t0, R) in enumerate(zip(self.t0, R_vals)):
# if fixed_potential, we take the potential at the specified timestep only
if fixed_potential:
t0_pot = fixed_potential
else:
t0_pot = t0
# if interpolants are provided, use these for the calculation
if interpolants:
potential = interpolants[t0_pot]
else:
potential = gal.full_potentials[t0_pot]
Vcircs.append(vcirc(potential, R).value)
self.Vcirc = np.asarray(Vcircs) * u.km / u.s
def estimateBIsochrone(R,z,pot=None):
"""
NAME:
estimateBIsochrone
PURPOSE:
Estimate a good value for the scale of the isochrone potential by matching the slope of the rotation curve
INPUT:
R,z = coordinates (if these are arrays, the median estimated delta is returned, i.e., if this is an orbit)
pot= Potential instance or list thereof
OUTPUT:
b if 1 R,Z given
bmin,bmedian,bmax if multiple R given
HISTORY:
2013-09-12 - Written - Bovy (IAS)
"""
if pot is None: #pragma: no cover
raise IOError("pot= needs to be set to a Potential instance or list thereof")
if isinstance(R,nu.ndarray):
bs= nu.array([estimateBIsochrone(R[ii],z[ii],pot=pot) for ii in range(len(R))])
return (nu.amin(bs[True-nu.isnan(bs)]),
nu.median(bs[True-nu.isnan(bs)]),
nu.amax(bs[True-nu.isnan(bs)]))
else:
r2= R**2.+z**2
r= math.sqrt(r2)
dlvcdlr= dvcircdR(pot,r)/vcirc(pot,r)*r
try:
b= optimize.brentq(lambda x: dlvcdlr-(x/math.sqrt(r2+x**2.)-0.5*r2/(r2+x**2.)),
0.01,100.)
except: #pragma: no cover
b= nu.nan
return b
def sample_galpy_potential(pot,n,rmin,rmax,ro=8.,vo=220.,coordinates='cartesian'):
ran=np.random.rand(n)
rad=np.linspace(rmin,rmax,n)
try:
menc=pot.mass(rad/ro,z=0,t=0,forceint=False)
except:
vc= potential.vcirc(pot,rad/ro,phi=0,t=0.,ro=ro,vo=vo,use_physical=False)
menc=vc**2.*(rad/ro)
menc*=bovy_conversion.mass_in_msol(ro=ro,vo=vo)
r=np.interp(ran, menc/menc[-1], rad)
phi=2.0*np.pi*np.random.rand(n)
theta=np.arccos(1.0-2.0*np.random.rand(n))
x=r*np.sin(theta)*np.cos(phi)
y=r*np.sin(theta)*np.sin(phi)
z=r*np.cos(theta)
sigma_v_1d=vo*potential.vcirc(pot,rad/ro,phi=0,t=0.,ro=ro,vo=vo,use_physical=False)/np.sqrt(3.)
vx=np.random.normal(0.,sigma_v_1d,n)
vy=np.random.normal(0.,sigma_v_1d,n)
vz=np.random.normal(0.,sigma_v_1d,n)
if coordinates=='spherical':
vr = (vx * np.sin(theta) * np.cos(phi)
+ vy * np.sin(theta) * np.sin(phi)
+ vz * np.cos(theta)
)
vtheta = (
vx * np.cos(theta) * np.cos(phi)
+ vy * np.cos(theta) * np.sin(phi)
- vz * np.sin(theta)
)
vphi = vx * -np.sin(phi) + vy * np.cos(phi)
x,y,z=r,phi,theta
vx,vy,vz=vr,vphi,vtheta
elif coordinates=='cylindrical':
x,y,z=bovy_coords.rect_to_cyl(x,y,z)
vx,vy,vz=bovy_coords.rect_to_cyl_vec(vx,vy,vz,x,y,z,True)
return x,y,z,vx,vy,vz
def vcirc(self,R):
if self._interpvcirc:
if self._logR:
return self._vcircInterp(numpy.log(R))
else:
return self._vcircInterp(R)
else:
from galpy.potential import vcirc
return vcirc(self._origPot,R)
def enclosed_mass(self, r):
grav = 4.302e-6 #kpc (km/s)^2/Msun
vc2 = potential.vcirc(self.pot,
r.value_in(units.kpc) / self.ro,
phi=0,
t=self.tgalpy,
ro=self.ro,
vo=self.vo)**2.
menc = vc2 * r.value_in(units.kpc) / grav | units.MSun
return menc
def estimateBIsochrone(pot,R,z,phi=None):
"""
NAME:
estimateBIsochrone
PURPOSE:
Estimate a good value for the scale of the isochrone potential by matching the slope of the rotation curve
INPUT:
pot- Potential instance or list thereof
R,z - coordinates (if these are arrays, the median estimated delta is returned, i.e., if this is an orbit)
phi= (None) azimuth to use for non-axisymmetric potentials (array if R and z are arrays)
OUTPUT:
b if 1 R,Z given
bmin,bmedian,bmax if multiple R given
HISTORY:
2013-09-12 - Written - Bovy (IAS)
2016-02-20 - Changed input order to allow physical conversions - Bovy (UofT)
2016-06-28 - Added phi= keyword for non-axisymmetric potential - Bovy (UofT)
"""
if pot is None: #pragma: no cover
raise IOError("pot= needs to be set to a Potential instance or list thereof")
if isinstance(R,nu.ndarray):
if phi is None: phi= [None for r in R]
bs= nu.array([estimateBIsochrone(pot,R[ii],z[ii],phi=phi[ii],
use_physical=False)
for ii in range(len(R))])
return nu.array([nu.amin(bs[True^nu.isnan(bs)]),
nu.median(bs[True^nu.isnan(bs)]),
nu.amax(bs[True^nu.isnan(bs)])])
else:
r2= R**2.+z**2
r= math.sqrt(r2)
dlvcdlr= dvcircdR(pot,r,phi=phi,use_physical=False)/vcirc(pot,r,phi=phi,use_physical=False)*r
try:
b= optimize.brentq(lambda x: dlvcdlr-(x/math.sqrt(r2+x**2.)-0.5*r2/(r2+x**2.)),
0.01,100.)
except: #pragma: no cover
b= nu.nan
return b
def estimateBIsochrone(pot,R,z,phi=None):
"""
NAME:
estimateBIsochrone
PURPOSE:
Estimate a good value for the scale of the isochrone potential by matching the slope of the rotation curve
INPUT:
pot- Potential instance or list thereof
R,z - coordinates (if these are arrays, the median estimated delta is returned, i.e., if this is an orbit)
phi= (None) azimuth to use for non-axisymmetric potentials (array if R and z are arrays)
OUTPUT:
b if 1 R,Z given
bmin,bmedian,bmax if multiple R given
HISTORY:
2013-09-12 - Written - Bovy (IAS)
2016-02-20 - Changed input order to allow physical conversions - Bovy (UofT)
2016-06-28 - Added phi= keyword for non-axisymmetric potential - Bovy (UofT)
"""
if pot is None: #pragma: no cover
raise IOError("pot= needs to be set to a Potential instance or list thereof")
if isinstance(R,nu.ndarray):
if phi is None: phi= [None for r in R]
bs= nu.array([estimateBIsochrone(pot,R[ii],z[ii],phi=phi[ii],
use_physical=False)
for ii in range(len(R))])
return nu.array([nu.amin(bs[True-nu.isnan(bs)]),
nu.median(bs[True-nu.isnan(bs)]),
nu.amax(bs[True-nu.isnan(bs)])])
else:
r2= R**2.+z**2
r= math.sqrt(r2)
dlvcdlr= dvcircdR(pot,r,phi=phi,use_physical=False)/vcirc(pot,r,phi=phi,use_physical=False)*r
try:
b= optimize.brentq(lambda x: dlvcdlr-(x/math.sqrt(r2+x**2.)-0.5*r2/(r2+x**2.)),
0.01,100.)
except: #pragma: no cover
b= nu.nan
return b
def test_meanvT_staeckel_gl():
qdf= quasiisothermaldf(1./4.,0.2,0.1,1.,1.,
pot=MWPotential,aA=aAS,cutcounter=True)
from galpy.df import dehnendf #baseline
dfc= dehnendf(profileParams=(1./4.,1.0, 0.2),
beta=0.,correct=False)
#In the mid-plane
vtp9= qdf.meanvT(0.9,0.,gl=True)
assert numpy.fabs(vtp9-dfc.meanvT(0.9)) < 0.05, "qdf's meanvT is not close to that of dehnendf"
assert vtp9 < vcirc(MWPotential,0.9), "qdf's meanvT is not less than the circular velocity (which we expect)"
#higher up
assert qdf.meanvR(0.9,0.2,gl=True) < vtp9, "qdf's meanvT above the plane is not less than in the plane (which we expect)"
assert qdf.meanvR(0.9,-0.25,gl=True) < vtp9, "qdf's meanvT above the plane is not less than in the plane (which we expect)"
return None
def VpratioMWBH(Rpkpc):
#MWPotential2014.append(KeplerPotential(amp=4*10**6./bovy_conversion.mass_in_msol(par.Vs,par.Rskpc)))
#a = vcirc(MWPotential2014,Rpkpc/par.Rskpc)
'''
bp= PowerSphericalPotentialwCutoff(alpha=1.8,rc=1.9/8.,normalize=0.05)
mp= MiyamotoNagaiPotential(a=3./8.,b=0.28/8.,normalize=.6)
np= NFWPotential(a=16./8.,normalize=.35)
kp = KeplerPotential(amp=4*10**6./bovy_conversion.mass_in_msol(par.Vs,par.Rskpc))
MWBH = [bp,mp,np,kp]
a = vcirc(MWBH,Rpkpc/par.Rskpc)
'''
MWPotential2014wBH = [
MWPotential2014,
KeplerPotential(amp=4 * 10**6. /
bovy_conversion.mass_in_msol(par.Vs, par.Rskpc))
]
a = vcirc(MWPotential2014wBH, Rpkpc / par.Rskpc)
return a
def kuepper_flattening_post(params: Sequence[float], qmean: float,
qerr: float) -> float:
"""A Kuepper et al. (2015) - flattened force posterior.
Consists solely of the priors and a constraint on q_Phi.
Parameters
----------
params : list
(3,) list. The Mhalo, a, qNFW
qmean : float
qerr : float
Returns
-------
float
"""
Mhalo, a, qNFW = params
if Mhalo < 0.001 or Mhalo > 10.0:
return -1e18
elif a < 0.1 or a > 100.0:
return -1e18
elif qNFW < 0.2 or qNFW > 1.8:
return -1e18
pot: list = setup_potential_kuepper(Mhalo, a)
vcpred = potential.vcirc(pot, 8.0 * u.kpc)
if vcpred < 200.0 or vcpred > 280.0:
return -1e18
FR, FZ = force_pal5_kuepper(pot, qNFW)
qpred = np.sqrt(2.0 * FR / FZ)
post: float = -0.5 * np.square((qpred - qmean) / qerr)
return post
def calcDFResults(options,args,boot=True,nomedian=False):
if len(args) == 2 and options.sample == 'gk':
toptions= copy.copy(options)
toptions.sample= 'g'
toptions.select= 'all'
outg= calcDFResults(toptions,[args[0]],boot=boot,nomedian=True)
toptions.sample= 'k'
toptions.select= 'program'
outk= calcDFResults(toptions,[args[1]],boot=boot,nomedian=True)
#Combine
out= {}
for k in outg.keys():
valg= outg[k]
valk= outk[k]
val= numpy.zeros(len(valg)+len(valk))
val[0:len(valg)]= valg
val[len(valg):len(valg)+len(valk)]= valk
out[k]= val
if nomedian: return out
else: return add_median(out,boot=boot)
raw= read_rawdata(options)
#Bin the data
binned= pixelAfeFeh(raw,dfeh=options.dfeh,dafe=options.dafe)
tightbinned= binned
#Map the bins with ndata > minndata in 1D
fehs, afes= [], []
counter= 0
abindx= numpy.zeros((len(binned.fehedges)-1,len(binned.afeedges)-1),
dtype='int')
for ii in range(len(binned.fehedges)-1):
for jj in range(len(binned.afeedges)-1):
data= binned(binned.feh(ii),binned.afe(jj))
if len(data) < options.minndata:
continue
#print binned.feh(ii), binned.afe(jj), len(data)
fehs.append(binned.feh(ii))
afes.append(binned.afe(jj))
abindx[ii,jj]= counter
counter+= 1
nabundancebins= len(fehs)
fehs= numpy.array(fehs)
afes= numpy.array(afes)
#Load each of the solutions
sols= []
chi2s= []
savename= args[0]
initname= options.init
for ii in range(nabundancebins):
spl= savename.split('.')
newname= ''
for jj in range(len(spl)-1):
newname+= spl[jj]
if not jj == len(spl)-2: newname+= '.'
newname+= '_%i.' % ii
newname+= spl[-1]
savefilename= newname
#Read savefile
try:
savefile= open(savefilename,'rb')
except IOError:
print "WARNING: MISSING ABUNDANCE BIN"
sols.append(None)
chi2s.append(None)
else:
sols.append(pickle.load(savefile))
chi2s.append(pickle.load(savefile))
savefile.close()
#Load samples as well
if options.mcsample:
#Do the same for init
spl= initname.split('.')
newname= ''
for jj in range(len(spl)-1):
newname+= spl[jj]
if not jj == len(spl)-2: newname+= '.'
newname+= '_%i.' % ii
newname+= spl[-1]
options.init= newname
mapfehs= monoAbundanceMW.fehs()
mapafes= monoAbundanceMW.afes()
#Now plot
#Run through the pixels and gather
fehs= []
afes= []
ndatas= []
zmedians= []
#Basic parameters
hrs= []
srs= []
szs= []
hsrs= []
hszs= []
outfracs= []
rds= []
rdexps= []
vcs= []
zhs= []
zhexps= []
dlnvcdlnrs= []
plhalos= []
rorss= []
dvts= []
#derived parameters
surfzs= []
surfz800s= []
surfzdisks= []
massdisks= []
rhoos= []
rhooalts= []
rhodms= []
vcdvcros= []
vcdvcs= []
vescs= []
mloglikemins= []
for ii in range(tightbinned.npixfeh()):
for jj in range(tightbinned.npixafe()):
data= binned(tightbinned.feh(ii),tightbinned.afe(jj))
if len(data) < options.minndata:
continue
#Find abundance indx
fehindx= binned.fehindx(tightbinned.feh(ii))#Map onto regular binning
afeindx= binned.afeindx(tightbinned.afe(jj))
solindx= abindx[fehindx,afeindx]
monoabindx= numpy.argmin((tightbinned.feh(ii)-mapfehs)**2./0.01 \
+(tightbinned.afe(jj)-mapafes)**2./0.0025)
if sols[solindx] is None:
continue
try:
pot= setup_potential(sols[solindx],options,1,interpDens=True,
interpdvcircdr=True,returnrawpot=True)
except RuntimeError:
print "A bin has an unphysical potential ..."
continue
# if 'dpdisk' in options.potential.lower():
# try:
# rawpot= setup_potential(sols[solindx],options,1,
# returnrawpot=True)
# except RuntimeError:
# print "A bin has an unphysical potential ..."
# continue
fehs.append(tightbinned.feh(ii))
afes.append(tightbinned.afe(jj))
zmedians.append(numpy.median(numpy.fabs(data.zc+_ZSUN)))
#vc
s= get_potparams(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.fixvo:
vcs.append(options.fixvo*_REFV0)
else:
vcs.append(s[1]*_REFV0)
#rd
rds.append(numpy.exp(s[0]))
#zh
zhs.append(numpy.exp(s[2-(1-(options.fixvo is None))]))
#rdexp & zhexp
if options.sample == 'g': tz= 1.1/_REFR0/ro
elif options.sample == 'k': tz= 0.84/_REFR0/ro
if 'mpdisk' in options.potential.lower() or 'mwpotential' in options.potential.lower():
mp= potential.MiyamotoNagaiPotential(a=rds[-1],b=zhs[-1])
#rdexp
f= mp.dens(1.,0.125)
dr= 10.**-3.
df= (mp.dens(1.+dr/2.,0.125)-mp.dens(1.-dr/2.,0.125))/dr
rdexps.append(-f/df)
#zhexp
f= mp.dens(1.,tz)
dz= 10.**-3.
df= (mp.dens(1.,tz+dz/2.)-mp.dens(1.,tz-dz/2.))/dz
zhexps.append(-f/df)
elif 'dpdisk' in options.potential.lower():
rdexps.append(numpy.exp(s[0]))
zhexps.append(numpy.exp(s[2-(1-(options.fixvo is None))]))
#ndata
ndatas.append(len(data))
#hr
dfparams= get_dfparams(sols[solindx],0,options)
if options.relative:
thishr= monoAbundanceMW.hr(mapfehs[monoabindx],mapafes[monoabindx])
hrs.append(dfparams[0]*_REFR0/thishr)
else:
hrs.append(dfparams[0]*_REFR0)
#sz
if options.relative:
thissz= monoAbundanceMW.sigmaz(mapfehs[monoabindx],mapafes[monoabindx])
szs.append(dfparams[2]*_REFV0/thissz)
else:
szs.append(dfparams[2]*_REFV0)
#sr
if options.relative:
thissr= monoAbundanceMW.sigmaz(mapfehs[monoabindx],mapafes[monoabindx])*2.#BOVY: UPDATE
srs.append(dfparams[1]*_REFV0/thissr)
else:
srs.append(dfparams[1]*_REFV0)
#hsr
hsrs.append(dfparams[3]*_REFR0)
#hsz
hszs.append(dfparams[4]*_REFR0)
#outfrac
outfracs.append(dfparams[5])
#rhodm
#Setup potential
vo= get_vo(sols[solindx],options,1)
if 'mwpotential' in options.potential.lower():
rhodms.append(pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.)
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
rhodms.append(pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.)
elif options.potential.lower() == 'mpdiskflplhalofixplfixbulgeflat':
rhodms.append(pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.)
elif options.potential.lower() == 'dpdiskplhalofixbulgeflat' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgas' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgasalt' \
or options.potential.lower() == 'dpdiskflplhalofixbulgeflatwgas':
rhodms.append(pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.)
#rhoo
rhoos.append(potential.evaluateDensities(1.,0.,pot)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.)
#surfz
surfzs.append(2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot)),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro)
#surfz800
surfz800s.append(2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot)),0.,0.8/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro)
#surzdisk
if 'mpdisk' in options.potential.lower() or 'mwpotential' in options.potential.lower():
surfzdisks.append(2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot[0])),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro)
surfzdiskzm= 2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot[0])),0.,tz)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
elif 'dpdisk' in options.potential.lower():
surfzdisks.append(2.*pot[0].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.*zhexps[-1]*ro*_REFR0*1000.)
#rhooalt
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
rhooalts.append(rhoos[-1]-pot[0].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.+surfzdiskzm/2./zhexps[-1]/ro/_REFR0/1000./(1.-numpy.exp(-tz/zhexps[-1])))
elif options.potential.lower() == 'dpdiskplhalofixbulgeflat' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgas' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgasalt' \
or options.potential.lower() == 'dpdiskflplhalofixbulgeflatwgas':
rhooalts.append(rhoos[-1])
#massdisk
if options.potential.lower() == 'dpdiskplhalofixbulgeflat' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgas' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgasalt' \
or options.potential.lower() == 'dpdiskflplhalofixbulgeflatwgas':
rhod= pot[0].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
else:
rhod= surfzdiskzm/2./zhexps[-1]/ro/_REFR0/1000./(1.-numpy.exp(-tz/zhexps[-1]))
massdisks.append(rhod*2.*zhexps[-1]*numpy.exp(1./rdexps[-1])*rdexps[-1]**2.*2.*numpy.pi*(ro*_REFR0)**3./10.)
#plhalo
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
plhalos.append(pot[1].alpha)
plhalos.append((1.-pot[1].alpha)/(pot[1].alpha-3.))
elif options.potential.lower() == 'dpdiskplhalofixbulgeflat' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgas' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgasalt' \
or options.potential.lower() == 'dpdiskflplhalofixbulgeflatwgas':
plhalos.append(pot[1].alpha)
rorss.append((1.-pot[1].alpha)/(pot[1].alpha-3.))
#dlnvcdlnr
if options.potential.lower() == 'dpdiskplhalofixbulgeflat' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgas' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgasalt' \
or options.potential.lower() == 'dpdiskflplhalofixbulgeflatwgas':
dlnvcdlnrs.append(potential.dvcircdR(pot,1.))
else:
dlnvcdlnrs.append(potential.dvcircdR(pot,1.))
#vcdvc
if options.potential.lower() == 'dpdiskplhalofixbulgeflat' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgas' \
or options.potential.lower() == 'dpdiskplhalofixbulgeflatwgasalt' \
or options.potential.lower() == 'dpdiskflplhalofixbulgeflatwgas':
vcdvcros.append(pot[0].vcirc(1.)/potential.vcirc(pot,1.))
vcdvcs.append(pot[0].vcirc(2.2*rdexps[-1])/potential.vcirc(pot,2.2*rdexps[-1]))
else:
vcdvcros.append(pot[0].vcirc(1.)/potential.vcirc(pot,1.))
vcdvcs.append(pot[0].vcirc(2.2*rdexps[-1])/potential.vcirc(pot,2.2*rdexps[-1]))
#mloglike
mloglikemins.append(chi2s[solindx])
#escape velocity
vescs.append(potential.vesc(pot,1.)*_REFV0)
if options.fitdvt:
dvts.append(sols[solindx][0])
#Gather
fehs= numpy.array(fehs)
afes= numpy.array(afes)
zmedians= numpy.array(zmedians)
ndatas= numpy.array(ndatas)
#Basic parameters
hrs= numpy.array(hrs)
srs= numpy.array(srs)
szs= numpy.array(szs)
hsrs= numpy.array(hsrs)
hszs= numpy.array(hszs)
outfracs= numpy.array(outfracs)
vcs= numpy.array(vcs)
rds= numpy.array(rds)
zhs= numpy.array(zhs)
rdexps= numpy.array(rdexps)
zhexps= numpy.array(zhexps)
dlnvcdlnrs= numpy.array(dlnvcdlnrs)
plhalos= numpy.array(plhalos)
rorss= numpy.array(rorss)
if options.fitdvt:
dvts= numpy.array(dvts)
#derived parameters
surfzs= numpy.array(surfzs)
surfz800s= numpy.array(surfz800s)
surfzdisks= numpy.array(surfzdisks)
massdisks= numpy.array(massdisks)
rhoos= numpy.array(rhoos)
rhooalts= numpy.array(rhooalts)
rhodms= numpy.array(rhodms)
vcdvcros= numpy.array(vcdvcros)
vcdvcs= numpy.array(vcdvcs)
rexps= numpy.sqrt(2.)*(rds+zhs)/2.2
mloglikemins= numpy.array(mloglikemins)
vescs= numpy.array(vescs)
#Load into dictionary
out= {}
out['feh']= fehs
out['afe']= afes
out['zmedian']= zmedians
out['ndata']= ndatas
out['hr']= hrs
out['sr']= srs
out['sz']= szs
out['hsr']= hsrs
out['hsz']= hszs
out['outfrac']= outfracs
out['vc']= vcs
out['rd']= rds
out['zh']= zhs
out['rdexp']= rdexps
out['zhexp']= zhexps
out['dlnvcdlnr']= dlnvcdlnrs
out['plhalo']= plhalos
out['rors']= rorss
out['surfz']= surfzs
out['surfz800']= surfz800s
out['surfzdisk']= surfzdisks
out['massdisk']= massdisks
out['rhoo']= rhoos
out['rhooalt']= rhooalts
out['rhodm']= rhodms
out['vcdvc']= vcdvcs
out['vcdvcro']= vcdvcros
out['rexp']= rexps
out['mloglikemin']= mloglikemins
out['vesc']= vescs
if options.fitdvt:
out['dvt']= dvts
if nomedian: return out
else: return add_median(out,boot=boot)
def jmomentsurfacemass(self,
R,
z,
n,
m,
o,
nsigma=None,
mc=True,
nmc=10000,
_returnmc=False,
_vrs=None,
_vts=None,
_vzs=None,
**kwargs):
"""
NAME:
jmomentsurfacemass
PURPOSE:
calculate the an arbitrary moment of an action
of the velocity distribution
at R times the surfacmass
INPUT:
R - radius at which to calculate the moment(/ro)
n - jr^n
m - lz^m
o - jz^o
OPTIONAL INPUT:
nsigma - number of sigma to integrate the velocities over (when doing explicit numerical integral)
mc= if True, calculate using Monte Carlo integration
nmc= if mc, use nmc samples
OUTPUT:
<jr^n lz^m jz^o x surface-mass> at R
HISTORY:
2012-08-09 - Written - Bovy (IAS@MPIA)
"""
if nsigma == None:
nsigma = _NSIGMA
logSigmaR = (self._ro - R) / self._hr
sigmaR1 = self._sr * numpy.exp((self._ro - R) / self._hsr)
sigmaz1 = self._sz * numpy.exp((self._ro - R) / self._hsz)
thisvc = potential.vcirc(self._pot, R)
#Use the asymmetric drift equation to estimate va
gamma = numpy.sqrt(0.5)
va= sigmaR1**2./2./thisvc\
*(gamma**2.-1. #Assume close to flat rotation curve, sigphi2/sigR2 =~ 0.5
+R*(1./self._hr+2./self._hsr))
if math.fabs(va) > sigmaR1:
va = 0. #To avoid craziness near the center
if mc:
mvT = (thisvc - va) / gamma / sigmaR1
if _vrs is None:
vrs = numpy.random.normal(size=nmc)
else:
vrs = _vrs
if _vts is None:
vts = numpy.random.normal(size=nmc) + mvT
else:
vts = _vts
if _vzs is None:
vzs = numpy.random.normal(size=nmc)
else:
vzs = _vzs
Is = _jmomentsurfaceMCIntegrand(vzs, vrs, vts,
nump.ones(nmc) * R,
numpy.ones(nmc) * z, self, sigmaR1,
gamma, sigmaz1, mvT, n, m, o)
if _returnmc:
return (numpy.mean(Is) * sigmaR1**2. * gamma * sigmaz1, vrs,
vts, vzs)
else:
return numpy.mean(Is) * sigmaR1**2. * gamma * sigmaz1
else:
return integrate.tplquad(
_jmomentsurfaceIntegrand, 1. / gamma *
(thisvc - va) / sigmaR1 - nsigma, 1. / gamma *
(thisvc - va) / sigmaR1 + nsigma, lambda x: 0.,
lambda x: nsigma, lambda x, y: 0., lambda x, y: nsigma,
(R, z, self, sigmaR1, gamma, sigmaz1, n, m, o), **
kwargs)[0] * sigmaR1**2. * gamma * sigmaz1
def __init__(self,
hr,
sr,
sz,
hsr,
hsz,
pot=None,
aA=None,
cutcounter=False,
_precomputerg=True,
_precomputergrmax=None,
_precomputergnLz=51,
ro=1.,
lo=10. / 220. * 8.):
"""
NAME:
__init__
PURPOSE:
Initialize a quasi-isothermal DF
INPUT:
hr - radial scale length
sr - radial velocity dispersion at the solar radius
sz - vertical velocity dispersion at the solar radius
hsr - radial-velocity-dispersion scale length
hsz - vertial-velocity-dispersion scale length
pot= Potential instance or list thereof
aA= actionAngle instance used to convert (x,v) to actions
cutcounter= if True, set counter-rotating stars' DF to zero
ro= reference radius for surface mass and sigmas
lo= reference angular momentum below where there are significant numbers of retrograde stars
OTHER INPUTS:
_precomputerg= if True (default), pre-compute the rL(L)
_precomputergrmax= if set, this is the maximum R for which to pre-compute rg (default: 5*hr)
_precomputergnLz if set, number of Lz to pre-compute rg for (default: 51)
OUTPUT:
object
HISTORY:
2012-07-25 - Started - Bovy (IAS@MPIA)
"""
self._hr = hr
self._sr = sr
self._sz = sz
self._hsr = hsr
self._hsz = hsz
self._ro = ro
self._lo = lo
self._lnsr = math.log(self._sr)
self._lnsz = math.log(self._sz)
if pot is None:
raise IOError("pot= must be set")
self._pot = pot
if aA is None:
raise IOError("aA= must be set")
self._aA = aA
self._cutcounter = cutcounter
if _precomputerg:
if _precomputergrmax is None:
_precomputergrmax = 5 * self._hr
self._precomputergrmax = _precomputergrmax
self._precomputergnLz = _precomputergnLz
self._precomputergLzmin = 0.01
self._precomputergLzmax= self._precomputergrmax\
*potential.vcirc(self._pot,self._precomputergrmax)
self._precomputergLzgrid = numpy.linspace(self._precomputergLzmin,
self._precomputergLzmax,
self._precomputergnLz)
self._rls = numpy.array(
[potential.rl(self._pot, l) for l in self._precomputergLzgrid])
#Spline interpolate
self._rgInterp = interpolate.InterpolatedUnivariateSpline(
self._precomputergLzgrid, self._rls, k=3)
else:
self._precomputergrmax = 0.
self._rgInterp = None
self._rls = None
self._precomputergnr = None
self._precomputergLzgrid = None
self._precomputerg = _precomputerg
return None
def fct_vlsr(r, r0, v0, l, b):
return (r0 * vcirc(MWPotential2014, r / r0, ro=r0, vo=v0) / r -
vcirc(MWPotential2014, 1, ro=r0, vo=v0)) * np.sin(l) * np.cos(b)
cdfrho=[cdf_bulge(rr[ii]) for ii in range(len(rr))]
icdf= interpolate.InterpolatedUnivariateSpline(cdfrho,rr,k=1)
rand_r=np.empty(nr)
for jj in range(nr):
rand_r[jj] = icdf(np.random.uniform())
rand_theta=np.random.uniform(0.,2.*np.pi,nr)
rand_phi = np.arccos(1.- 2.*np.random.uniform(0.,1.,nr))
R,z,theta=spherical_to_cylindrical(rand_r,rand_theta,rand_phi)
vR=np.zeros(nr)
vz=np.zeros(nr)
vT=vcirc(nobarpot,R/8.)
t_age=np.linspace(tage,0.,1001)/bovy_conversion.time_in_Gyr(vo,ro)
coord=[]
orbits=[]
for ii in range(nr):
coord.append([R[ii]/8.,vR[ii],vT[ii],z[ii]/8.,vz[ii],theta[ii]])
orbits.append(Orbit(coord[ii]))
orbits[ii].turn_physical_off()
orbits[ii].integrate(t_age,barpot)
tout = np.linspace(tage,0.,10)/bovy_conversion.time_in_Gyr(vo,ro)
for kk in tout :
tt = round(kk*bovy_conversion.time_in_Gyr(vo,ro),1)
def calcRapRperi(self,**kwargs):
"""
NAME:
calcRapRperi
PURPOSE:
calculate the apocenter and pericenter radii
INPUT:
OUTPUT:
(rperi,rap)
HISTORY:
2010-12-01 - Written - Bovy (NYU)
"""
if hasattr(self,'_rperirap'): #pragma: no cover
return self._rperirap
EL= self.calcEL(**kwargs)
E, L= EL
if self._vR == 0. and m.fabs(self._vT - vcirc(self._pot,self._R,use_physical=False)) < _EPS: #We are on a circular orbit
rperi= self._R
rap = self._R
elif self._vR == 0. and self._vT > vcirc(self._pot,self._R,use_physical=False): #We are exactly at pericenter
rperi= self._R
if self._gamma != 0.:
startsign= _rapRperiAxiEq(self._R+10.**-8.,E,L,self._pot)
startsign/= m.fabs(startsign)
else: startsign= 1.
rend= _rapRperiAxiFindStart(self._R,E,L,self._pot,rap=True,
startsign=startsign)
rap= optimize.brentq(_rapRperiAxiEq,rperi+0.00001,rend,
args=(E,L,self._pot))
# fprime=_rapRperiAxiDeriv)
elif self._vR == 0. and self._vT < vcirc(self._pot,self._R,use_physical=False): #We are exactly at apocenter
rap= self._R
if self._gamma != 0.:
startsign= _rapRperiAxiEq(self._R-10.**-8.,E,L,self._pot)
startsign/= m.fabs(startsign)
else: startsign= 1.
rstart= _rapRperiAxiFindStart(self._R,E,L,self._pot,
startsign=startsign)
if rstart == 0.: rperi= 0.
else:
rperi= optimize.brentq(_rapRperiAxiEq,rstart,rap-0.000001,
args=(E,L,self._pot))
# fprime=_rapRperiAxiDeriv)
else:
if self._gamma != 0.:
startsign= _rapRperiAxiEq(self._R,E,L,self._pot)
startsign/= m.fabs(startsign)
else:
startsign= 1.
rstart= _rapRperiAxiFindStart(self._R,E,L,self._pot,
startsign=startsign)
if rstart == 0.: rperi= 0.
else:
try:
rperi= optimize.brentq(_rapRperiAxiEq,rstart,self._R,
(E,L,self._pot),
maxiter=200)
except RuntimeError: #pragma: no cover
raise UnboundError("Orbit seems to be unbound")
rend= _rapRperiAxiFindStart(self._R,E,L,self._pot,rap=True,
startsign=startsign)
rap= optimize.brentq(_rapRperiAxiEq,self._R,rend,
(E,L,self._pot))
self._rperirap= (rperi,rap)
return self._rperirap
def plot_DFsingles(options,args):
raw= read_rawdata(options)
#Bin the data
binned= pixelAfeFeh(raw,dfeh=options.dfeh,dafe=options.dafe)
if options.tighten:
tightbinned= pixelAfeFeh(raw,dfeh=options.dfeh,dafe=options.dafe,
fehmin=-1.6,fehmax=0.5,afemin=-0.05,
afemax=0.55)
else:
tightbinned= binned
#Map the bins with ndata > minndata in 1D
fehs, afes= [], []
counter= 0
abindx= numpy.zeros((len(binned.fehedges)-1,len(binned.afeedges)-1),
dtype='int')
for ii in range(len(binned.fehedges)-1):
for jj in range(len(binned.afeedges)-1):
data= binned(binned.feh(ii),binned.afe(jj))
if len(data) < options.minndata:
continue
#print binned.feh(ii), binned.afe(jj), len(data)
fehs.append(binned.feh(ii))
afes.append(binned.afe(jj))
abindx[ii,jj]= counter
counter+= 1
nabundancebins= len(fehs)
fehs= numpy.array(fehs)
afes= numpy.array(afes)
#Load each solutions
sols= []
savename= args[0]
initname= options.init
for ii in range(nabundancebins):
spl= savename.split('.')
newname= ''
for jj in range(len(spl)-1):
newname+= spl[jj]
if not jj == len(spl)-2: newname+= '.'
newname+= '_%i.' % ii
newname+= spl[-1]
savefilename= newname
#Read savefile
try:
savefile= open(savefilename,'rb')
except IOError:
print "WARNING: MISSING ABUNDANCE BIN"
sols.append(None)
else:
sols.append(pickle.load(savefile))
savefile.close()
#Load samples as well
if options.mcsample:
#Do the same for init
spl= initname.split('.')
newname= ''
for jj in range(len(spl)-1):
newname+= spl[jj]
if not jj == len(spl)-2: newname+= '.'
newname+= '_%i.' % ii
newname+= spl[-1]
options.init= newname
mapfehs= monoAbundanceMW.fehs()
mapafes= monoAbundanceMW.afes()
#Now plot
#Run through the pixels and gather
if options.type.lower() == 'afe' or options.type.lower() == 'feh' \
or options.type.lower() == 'fehafe' \
or options.type.lower() == 'afefeh':
plotthis= []
errors= []
else:
plotthis= numpy.zeros((tightbinned.npixfeh(),tightbinned.npixafe()))
for ii in range(tightbinned.npixfeh()):
for jj in range(tightbinned.npixafe()):
data= binned(tightbinned.feh(ii),tightbinned.afe(jj))
if len(data) < options.minndata:
if options.type.lower() == 'afe' or options.type.lower() == 'feh' or options.type.lower() == 'fehafe' \
or options.type.lower() == 'afefeh':
continue
else:
plotthis[ii,jj]= numpy.nan
continue
#Find abundance indx
fehindx= binned.fehindx(tightbinned.feh(ii))#Map onto regular binning
afeindx= binned.afeindx(tightbinned.afe(jj))
solindx= abindx[fehindx,afeindx]
monoabindx= numpy.argmin((tightbinned.feh(ii)-mapfehs)**2./0.01 \
+(tightbinned.afe(jj)-mapafes)**2./0.0025)
if sols[solindx] is None:
if options.type.lower() == 'afe' or options.type.lower() == 'feh' or options.type.lower() == 'fehafe' \
or options.type.lower() == 'afefeh':
continue
else:
plotthis[ii,jj]= numpy.nan
continue
if options.type.lower() == 'q':
s= get_potparams(sols[solindx],options,1)
plotthis[ii,jj]= s[0]
if not options.flatten is None:
plotthis[ii,jj]/= options.flatten
elif options.type.lower() == 'vc':
if options.fixvo:
plotthis[ii,jj]= 1.
else:
s= get_potparams(sols[solindx],options,1)
plotthis[ii,jj]= s[1]
elif options.type.lower() == 'rd':
s= get_potparams(sols[solindx],options,1)
plotthis[ii,jj]= numpy.exp(s[0])
elif options.type.lower() == 'zh':
s= get_potparams(sols[solindx],options,1)
plotthis[ii,jj]= numpy.exp(s[2-(1-(options.fixvo is None))])
elif options.type.lower() == 'ndata':
plotthis[ii,jj]= len(data)
elif options.type.lower() == 'hr':
s= get_dfparams(sols[solindx],0,options)
plotthis[ii,jj]= s[0]*_REFR0
if options.relative:
thishr= monoAbundanceMW.hr(mapfehs[monoabindx],mapafes[monoabindx])
plotthis[ii,jj]/= thishr
elif options.type.lower() == 'sz':
s= get_dfparams(sols[solindx],0,options)
plotthis[ii,jj]= s[2]*_REFV0
if options.relative:
thissz= monoAbundanceMW.sigmaz(mapfehs[monoabindx],mapafes[monoabindx])
plotthis[ii,jj]/= thissz
elif options.type.lower() == 'sr':
s= get_dfparams(sols[solindx],0,options)
plotthis[ii,jj]= s[1]*_REFV0
if options.relative:
thissr= monoAbundanceMW.sigmaz(mapfehs[monoabindx],mapafes[monoabindx])*2.
plotthis[ii,jj]/= thissr
elif options.type.lower() == 'srsz':
#Setup everything
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
aA= setup_aA(pot,options)
dfparams= get_dfparams(sols[solindx],0,options,log=False)
if options.dfmodel.lower() == 'qdf':
#Normalize
hr= dfparams[0]/ro
sr= dfparams[1]/vo
sz= dfparams[2]/vo
hsr= dfparams[3]/ro
hsz= dfparams[4]/ro
#Setup
qdf= quasiisothermaldf(hr,sr,sz,hsr,hsz,pot=pot,
aA=aA,cutcounter=True)
plotthis[ii,jj]= numpy.sqrt(qdf.sigmaR2(1.,1./_REFR0/ro,
ngl=options.ngl,gl=True)\
/qdf.sigmaz2(1.,1./_REFR0/ro,
ngl=options.ngl,gl=True))
elif options.type.lower() == 'outfrac':
s= get_dfparams(sols[solindx],0,options)
plotthis[ii,jj]= s[5]
elif options.type.lower() == 'rhodm':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if 'mwpotential' in options.potential.lower():
plotthis[ii,jj]= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
plotthis[ii,jj]= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskflplhalofixplfixbulgeflat':
plotthis[ii,jj]= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.type.lower() == 'rhoo':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
plotthis[ii,jj]= potential.evaluateDensities(1.,0.,pot)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.type.lower() == 'surfz':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
plotthis[ii,jj]= 2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot)),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
elif options.type.lower() == 'surfzdisk':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if 'mpdisk' in options.potential.lower() or 'mwpotential' in options.potential.lower():
plotthis[ii,jj]= 2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot[0])),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
elif options.type.lower() == 'kz':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
plotthis[ii,jj]= numpy.fabs(potential.evaluatezforces(1.,options.height/ro/_REFR0,pot)/2./numpy.pi/4.302*_REFV0**2.*vo**2./_REFR0/ro)
elif options.type.lower() == 'plhalo':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
plotthis[ii,jj]= pot[1].alpha
elif options.type.lower() == 'qhalo':
#Setup potential
s= get_potparams(sols[solindx],options,1)
if options.potential.lower() == 'mpdiskflplhalofixplfixbulgeflat':
plotthis[ii,jj]= s[4]
elif options.type.lower() == 'dlnvcdlnr':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
plotthis[ii,jj]= potential.dvcircdR(pot,1.)
elif options.type.lower() == 'fd':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if 'mwpotential' in options.potential.lower():
plotthis[ii,jj]= (pot[0].vcirc(1.))**2.
elif options.type.lower() == 'fh':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if 'mwpotential' in options.potential.lower():
plotthis[ii,jj]= (pot[1].vcirc(1.))**2.
elif options.type.lower() == 'fb':
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if 'mwpotential' in options.potential.lower():
plotthis[ii,jj]= (pot[2].vcirc(1.))**2.
elif options.type.lower() == 'afe' or options.type.lower() == 'feh' or options.type.lower() == 'fehafe' \
or options.type.lower() == 'afefeh':
thisplot=[tightbinned.feh(ii),
tightbinned.afe(jj),
len(data)]
if options.subtype.lower() == 'qvc':
s= get_potparams(sols[solindx],options,1)
thisq= s[0]
if not options.flatten is None:
thisq/= options.flatten
thisvc= s[1]
thisplot.extend([thisq,thisvc])
elif options.subtype.lower() == 'rdzh':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
thisplot.extend([thisrd,thiszh])
elif options.subtype.lower() == 'zhvc':
s= get_potparams(sols[solindx],options,1)
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
thisvc= s[1]*_REFV0
thisplot.extend([thiszh,thisvc])
elif options.subtype.lower() == 'dlnvcdlnrvc':
s= get_potparams(sols[solindx],options,1)
thisslope= s[3-(1-(options.fixvo is None))]/30.
thisvc= s[1]*_REFV0
thisplot.extend([thisslope,thisvc])
elif options.subtype.lower() == 'rdvc':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
thisvc= s[1]*_REFV0
thisplot.extend([thisrd,thisvc])
elif options.subtype.lower() == 'rdplhalo':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisplhalo= pot[1].alpha
thisplot.extend([thisrd,thisplhalo])
elif options.subtype.lower() == 'dlnvcdlnrplhalo':
s= get_potparams(sols[solindx],options,1)
thisslope= s[3-(1-(options.fixvo is None))]/30.
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisplhalo= pot[1].alpha
thisplot.extend([thisslope,thisplhalo])
elif options.subtype.lower() == 'dlnvcdlnrzh':
s= get_potparams(sols[solindx],options,1)
thisslope= s[3-(1-(options.fixvo is None))]/30.
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
thisplot.extend([thisslope,thiszh])
elif options.subtype.lower() == 'vc14plhalo':
s= get_potparams(sols[solindx],options,1)
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisplhalo= pot[1].alpha
thisvc14= potential.vcirc(pot,14./_REFR0/ro)*_REFV0*vo
thisplot.extend([thisplhalo,thisvc14])
elif options.subtype.lower() == 'plhalovc':
s= get_potparams(sols[solindx],options,1)
thisvc= s[1]*_REFV0
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisplhalo= pot[1].alpha
thisplot.extend([thisplhalo,thisvc])
elif options.subtype.lower() == 'zhplhalo':
s= get_potparams(sols[solindx],options,1)
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisplhalo= pot[1].alpha
thisplot.extend([thiszh,thisplhalo])
elif options.subtype.lower() == 'rhodmzh':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
if 'mwpotential' in options.potential.lower():
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
thisplot.extend([thisrhodm,thiszh])
elif options.subtype.lower() == 'rhodmsurfz':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
thissurfz= 2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot)),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
if 'mwpotential' in options.potential.lower():
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
thisplot.extend([thisrhodm,thissurfz])
elif options.subtype.lower() == 'surfzzh':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
thissurfz= 2.*integrate.quad((lambda zz: potential.evaluateDensities(1.,zz,pot)),0.,options.height/_REFR0/ro)[0]*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*_REFR0*ro
thisplot.extend([thissurfz,thiszh])
elif options.subtype.lower() == 'rhoozh':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
thiszh= numpy.exp(s[2-(1-(options.fixvo is None))])
thisrhoo= potential.evaluateDensities(1.,0.,pot)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
thisplot.extend([thisrhoo,thiszh])
elif options.subtype.lower() == 'rhodmvc':
s= get_potparams(sols[solindx],options,1)
thisvc= s[1]*_REFV0
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if 'mwpotential' in options.potential.lower():
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
thisplot.extend([thisrhodm,thisvc])
elif options.subtype.lower() == 'rhodmrd':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
thisrdh= numpy.exp(s[0])
if 'mwpotential' in options.potential.lower():
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
thisplot.extend([thisrhodm,thisrd])
elif options.subtype.lower() == 'rhodmplhalo':
s= get_potparams(sols[solindx],options,1)
thisrd= numpy.exp(s[0])
#Setup potential
pot= setup_potential(sols[solindx],options,1)
vo= get_vo(sols[solindx],options,1)
ro= get_ro(sols[solindx],options)
if options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisplhalo= pot[1].alpha
if 'mwpotential' in options.potential.lower():
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
elif options.potential.lower() == 'mpdiskplhalofixbulgeflat':
thisrhodm= pot[1].dens(1.,0.)*_REFV0**2.*vo**2./_REFR0**2./ro**2./4.302*10.**-3.
thisplot.extend([thisrhodm,thisplhalo])
plotthis.append(thisplot)
#Set up plot
if options.type.lower() == 'q':
if not options.flatten is None:
vmin, vmax= 0.9, 1.1
zlabel=r'$\mathrm{flattening}\ q / %.1f$' % options.flatten
elif 'real' in options.outfilename.lower():
vmin, vmax= 0.9, 1.1
medianq= numpy.median(plotthis[numpy.isfinite(plotthis)])
plotthis/= medianq
zlabel=r'$\mathrm{flattening}\ q / %.2f$' % medianq
else:
vmin, vmax= 0.5, 1.2
zlabel=r'$\mathrm{flattening}\ q$'
elif options.type.lower() == 'vc':
vmin, vmax= 0.95, 1.05
zlabel=r'$V_c / %i\ \mathrm{km\,s}^{-1}$' % int(_REFV0)
if 'real' in options.outfilename.lower():
medianvc= numpy.median(plotthis[numpy.isfinite(plotthis)])
plotthis/= medianvc
zlabel=r'$V_c / %i\ \mathrm{km\,s}^{-1}$' % int(_REFV0*medianvc)
elif options.type.lower() == 'rhodm':
vmin, vmax= 0.00, 0.02
zlabel=r'$\rho_{\mathrm{DM}}(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.type.lower() == 'rhoo':
vmin, vmax= 0.00, 0.2
zlabel=r'$\rho(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.type.lower() == 'surfz':
vmin, vmax= 50.,120.
zlabel=r'$\Sigma(%.1f\,\mathrm{kpc};R_0)\ [M_\odot\,\mathrm{pc}^{-2}]$' % options.height
elif options.type.lower() == 'surfzdisk':
vmin, vmax= 20.,90.
zlabel=r'$\Sigma_{\mathrm{disk}}(%.1f\,\mathrm{kpc};R_0)\ [M_\odot\,\mathrm{pc}^{-2}]$' % options.height
elif options.type.lower() == 'kz':
vmin, vmax= 50.,120.
zlabel=r'$K_Z(%.1f\,\mathrm{kpc};R_0)\ [M_\odot\,\mathrm{pc}^{-2}]$' % options.height
elif options.type.lower() == 'dlnvcdlnr':
vmin, vmax= -0.3,0.2
zlabel=r'$\frac{\mathrm{d} \ln V_c}{\mathrm{d} \ln R}$'
elif options.type.lower() == 'fd':
vmin, vmax= 0.00, 1.
zlabel=r'$V_{c,\mathrm{disk}} / V_c\,(R_0)$'
elif options.type.lower() == 'fh':
vmin, vmax= 0.00, 1.
zlabel=r'$V_{c,\mathrm{halo}} / V_c\,(R_0)$'
elif options.type.lower() == 'fb':
vmin, vmax= 0.00, .1
zlabel=r'$V_{c,\mathrm{halo}} / V_c\,(R_0)$'
elif options.type.lower() == 'rd':
vmin, vmax= 0.2, 0.6
zlabel=r'$R_d / R_0$'
elif options.type.lower() == 'zh':
vmin, vmax= 0.0125, 0.075
zlabel=r'$z_h / R_0$'
elif options.type.lower() == 'plhalo':
vmin, vmax= 0.0, 2.
zlabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
elif options.type.lower() == 'qhalo':
vmin, vmax= 0.4, 1.15
zlabel=r'$q_\Phi^{\mathrm{halo}}$'
elif options.type.lower() == 'ndata':
vmin, vmax= numpy.nanmin(plotthis), numpy.nanmax(plotthis)
zlabel=r'$N_\mathrm{data}$'
elif options.type == 'hr':
if options.relative:
vmin, vmax= 0.8, 1.2
zlabel=r'$\mathrm{input / output\ radial\ scale\ length}$'
else:
vmin, vmax= 1.35,4.5
zlabel=r'$\mathrm{model\ radial\ scale\ length\ [kpc]}$'
elif options.type == 'sz':
if options.relative:
vmin, vmax= 0.8, 1.2
zlabel= r'$\mathrm{input / output\ model}\ \sigma_z$'
else:
vmin, vmax= 10.,60.
zlabel= r'$\mathrm{model}\ \sigma_z\ [\mathrm{km\ s}^{-1}]$'
elif options.type == 'sr':
if options.relative:
vmin, vmax= 0.8, 1.2
zlabel= r'$\mathrm{input/output\ model}\ \sigma_R$'
else:
vmin, vmax= 10.,60.
zlabel= r'$\mathrm{model}\ \sigma_R\ [\mathrm{km\ s}^{-1}]$'
elif options.type == 'srsz':
vmin, vmax= 0.5,2.
zlabel= r'$\sigma_R/\sigma_z\ (R_0,1\,\mathrm{kpc})$'
elif options.type == 'outfrac':
vmin, vmax= 0., 1.
zlabel= r'$\mathrm{relative\ number\ of\ outliers}$'
elif options.type == 'afe':
vmin, vmax= 0.0,.5
zlabel=r'$[\alpha/\mathrm{Fe}]$'
elif options.type == 'feh':
vmin, vmax= -1.6,0.4
zlabel=r'$[\mathrm{Fe/H}]$'
elif options.type == 'fehafe':
vmin, vmax= -.7,.7
zlabel=r'$[\mathrm{Fe/H}]-[\mathrm{Fe/H}]_{1/2}([\alpha/\mathrm{Fe}])$'
elif options.type == 'afefeh':
vmin, vmax= -.15,.15
zlabel=r'$[\alpha/\mathrm{Fe}]-[\alpha/\mathrm{Fe}]_{1/2}([\mathrm{Fe/H}])$'
if options.tighten:
xrange=[-1.6,0.5]
yrange=[-0.05,0.55]
else:
xrange=[-2.,0.5]
yrange=[-0.2,0.6]
#Now plot
if options.type.lower() == 'afe' or options.type.lower() == 'feh' \
or options.type.lower() == 'fehafe':
#Gather everything
afe, feh, ndata, x, y= [], [], [], [], []
for ii in range(len(plotthis)):
afe.append(plotthis[ii][1])
feh.append(plotthis[ii][0])
ndata.append(plotthis[ii][2])
x.append(plotthis[ii][3])
y.append(plotthis[ii][4])
afe= numpy.array(afe)
feh= numpy.array(feh)
ndata= numpy.array(ndata)
x= numpy.array(x)
y= numpy.array(y)
#Process ndata
ndata= ndata**.5
ndata= ndata/numpy.median(ndata)*35.
if options.type.lower() == 'afe':
plotc= afe
elif options.type.lower() == 'feh':
plotc= feh
elif options.type.lower() == 'afefeh':
#Go through the bins to determine whether feh is high or low for this alpha
plotc= numpy.zeros(len(afe))
for ii in range(tightbinned.npixfeh()):
fehbin= ii
data= tightbinned.data[(tightbinned.data.feh > tightbinned.fehedges[fehbin])\
*(tightbinned.data.feh <= tightbinned.fehedges[fehbin+1])]
medianafe= numpy.median(data.afe)
for jj in range(len(afe)):
if feh[jj] == tightbinned.feh(ii):
plotc[jj]= afe[jj]-medianafe
else:
#Go through the bins to determine whether feh is high or low for this alpha
plotc= numpy.zeros(len(feh))
for ii in range(tightbinned.npixafe()):
afebin= ii
data= tightbinned.data[(tightbinned.data.afe > tightbinned.afeedges[afebin])\
*(tightbinned.data.afe <= tightbinned.afeedges[afebin+1])]
medianfeh= numpy.median(data.feh)
for jj in range(len(feh)):
if afe[jj] == tightbinned.afe(ii):
plotc[jj]= feh[jj]-medianfeh
onedhists=False
if options.subtype.lower() == 'qvc':
if not options.flatten is None:
xrange= [0.9,1.1]
xlabel=r'$\mathrm{flattening}\ q / %.1f$' % options.flatten
elif 'real' in options.outfilename.lower():
xrange= [0.9,1.1]
medianq= numpy.median(x[numpy.isfinite(x)])
x/= medianq
xlabel=r'$\mathrm{flattening}\ q / %.2f$' % medianq
else:
xrange= [0.5, 1.2]
xlabel=r'$\mathrm{flattening}\ q$'
yrange= [0.95, 1.05]
ylabel=r'$V_c / %i\ \mathrm{km\,s}^{-1}$' % int(_REFV0)
if 'real' in options.outfilename.lower():
medianvc= numpy.median(y[numpy.isfinite(y)])
y/= medianvc
ylabel=r'$V_c / %i\ \mathrm{km\,s}^{-1}$' % int(_REFV0*medianvc)
elif options.subtype.lower() == 'rdzh':
yrange= [0.0125,0.1]
xrange= [0.2,0.8]
xlabel=r'$R_d / R_0$'
ylabel=r'$z_h / R_0$'
elif options.subtype.lower() == 'rdplhalo':
yrange= [0.,2.]
xrange= [0.2,0.8]
xlabel=r'$R_d / R_0$'
ylabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
elif options.subtype.lower() == 'vc14plhalo':
yrange= [210.,280.]
xrange= [0.,2.]
xlabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
ylabel=r'$V_c (R=14\,\mathrm{kpc})\ [\mathrm{km\,s}^{-1}$]'
elif options.subtype.lower() == 'zhplhalo':
yrange= [0.,2.]
xrange= [0.0125,0.1]
ylabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
xlabel=r'$z_h / R_0$'
elif options.subtype.lower() == 'rhodmplhalo':
xrange= [0.,0.02]
yrange= [0.,2.]
ylabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
xlabel=r'$\rho_{\mathrm{DM}}(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.subtype.lower() == 'rhodmzh':
yrange= [0.0125,0.1]
xrange= [0.,0.02]
ylabel=r'$z_h / R_0$'
xlabel=r'$\rho_{\mathrm{DM}}(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.subtype.lower() == 'rhoozh':
yrange= [0.0125,0.1]
xrange= [0.,0.2]
ylabel=r'$z_h / R_0$'
xlabel=r'$\rho(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.subtype.lower() == 'surfzzh':
yrange= [0.0125,0.1]
xrange= [50.+20.*(options.height-1.1),120.+20.*(options.height-1.1)]
ylabel=r'$z_h / R_0$'
xlabel=r'$\Sigma(%.1f\,\mathrm{kpc};R_0)\ [M_\odot\,\mathrm{pc}^{-2}]$' % options.height
elif options.subtype.lower() == 'rhodmsurfz':
yrange= [50.+20.*(options.height-1.1),120.+20.*(options.height-1.1)]
xrange= [0.,0.02]
ylabel=r'$\Sigma(%.1f\,\mathrm{kpc};R_0)\ [M_\odot\,\mathrm{pc}^{-2}]$' % options.height
xlabel=r'$\rho_{\mathrm{DM}}(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.subtype.lower() == 'rhodmrd':
yrange= [0.2,0.8]
xrange= [0.,0.02]
ylabel=r'$R_d / R_0$'
xlabel=r'$\rho_{\mathrm{DM}}(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.subtype.lower() == 'rdvc':
yrange= [210.,250.]
xrange= [0.2,0.8]
xlabel=r'$R_d / R_0$'
ylabel=r'$V_c\ [\mathrm{km\,s}^{-1}]$'
elif options.subtype.lower() == 'zhvc':
yrange= [210.,250.]
xrange= [0.0125,0.1]
xlabel=r'$z_h / R_0$'
ylabel=r'$V_c\ [\mathrm{km\,s}^{-1}]$'
elif options.subtype.lower() == 'dlnvcdlnrvc':
yrange= [210.,250.]
xrange= [-0.2,0.07]
xlabel=r'$\mathrm{d}\ln V_c / \mathrm{d}\ln R\, (R_0)$'
ylabel=r'$V_c\ [\mathrm{km\,s}^{-1}]$'
onedhists=True
elif options.subtype.lower() == 'dlnvcdlnrplhalo':
yrange= [0.,2.]
ylabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
xrange= [-0.2,0.07]
xlabel=r'$\mathrm{d}\ln V_c / \mathrm{d}\ln R\, (R_0)$'
elif options.subtype.lower() == 'dlnvcdlnrzh':
yrange= [0.0125,0.1]
ylabel=r'$z_h / R_0$'
xrange= [-0.2,0.07]
xlabel=r'$\mathrm{d}\ln V_c / \mathrm{d}\ln R\, (R_0)$'
elif options.subtype.lower() == 'rhodmvc':
yrange= [210.,250.]
xrange= [0.,0.02]
ylabel=r'$V_c\ [\mathrm{km\,s}^{-1}]$'
xlabel=r'$\rho_{\mathrm{DM}}(R_0,0)\ [M_\odot\,\mathrm{pc}^{-3}]$'
elif options.subtype.lower() == 'plhalovc':
yrange= [210.,250.]
xrange= [0.,2.]
xlabel=r'$\alpha\ \mathrm{in}\ \rho_{\mathrm{halo}} \propto 1/r^\alpha$'
ylabel=r'$V_c\ [\mathrm{km\,s}^{-1}$]'
bovy_plot.bovy_print(fig_height=3.87,fig_width=5.)
ax= bovy_plot.bovy_plot(x,y,
s=ndata,c=plotc,
cmap='jet',
xlabel=xlabel,ylabel=ylabel,
clabel=zlabel,
xrange=xrange,yrange=yrange,
vmin=vmin,vmax=vmax,
scatter=True,edgecolors='none',
colorbar=True-onedhists,
onedhists=onedhists,
onedhistxnormed=onedhists,
onedhistynormed=onedhists,
bins=15)
if onedhists:
axS, axx, axy= ax
if options.subtype.lower() == 'dlnvcdlnrvc':
#Plot prior on one-d axes
sb= numpy.linspace(-0.2,0.0399,1001)
fsb= numpy.exp(numpy.log((0.04-sb)/0.04)-(0.04-sb)/0.04)
fsb/= numpy.sum(fsb)*(sb[1]-sb[0])
axx.plot(sb,fsb,'-',color='0.65')
tvc= numpy.linspace(150.,350.,1001)
fvc= numpy.exp(-(tvc-225.)**2./2./15.**2.)
fvc/= numpy.sum(fvc)*(tvc[1]-tvc[0])
axy.plot(fvc,tvc,'-',color='0.65')
else:
bovy_plot.bovy_print()
bovy_plot.bovy_dens2d(plotthis.T,origin='lower',cmap='jet',
interpolation='nearest',
xlabel=r'$[\mathrm{Fe/H}]$',
ylabel=r'$[\alpha/\mathrm{Fe}]$',
zlabel=zlabel,
xrange=xrange,yrange=yrange,
vmin=vmin,vmax=vmax,
contours=False,
colorbar=True,shrink=0.78)
if options.type.lower() == 'q' or options.type.lower() == 'vc' \
or options.relative or options.type.lower() == 'rd' \
or options.type.lower() == 'fd' \
or options.type.lower() == 'fh' \
or options.type.lower() == 'fb' \
or options.type.lower() == 'plhalo' \
or options.type.lower() == 'surfz' \
or options.type.lower() == 'surfzdisk' \
or options.type.lower() == 'rhoo' \
or options.type.lower() == 'qhalo' \
or options.type.lower() == 'kz':
bovy_plot.bovy_text(r'$\mathrm{median} = %.2f \pm %.2f$' % (numpy.median(plotthis[numpy.isfinite(plotthis)]),
1.4826*numpy.median(numpy.fabs(plotthis[numpy.isfinite(plotthis)]-numpy.median(plotthis[numpy.isfinite(plotthis)])))),
bottom_left=True,size=14.)
if options.type.lower() == 'zh' or options.type.lower() == 'rhodm':
bovy_plot.bovy_text(r'$\mathrm{median} = %.4f \pm %.4f$' % (numpy.median(plotthis[numpy.isfinite(plotthis)]),
1.4826*numpy.median(numpy.fabs(plotthis[numpy.isfinite(plotthis)]-numpy.median(plotthis[numpy.isfinite(plotthis)])))),
bottom_left=True,size=14.)
bovy_plot.bovy_end_print(options.outfilename)
return None
def __init__(self,
RZPot=None,rgrid=(numpy.log(0.01),numpy.log(20.),101),
zgrid=(0.,1.,101),logR=True,
interpPot=False,interpRforce=False,interpzforce=False,
interpDens=False,
interpvcirc=False,
interpdvcircdr=False,
interpepifreq=False,interpverticalfreq=False,
ro=None,vo=None,
use_c=False,enable_c=False,zsym=True,
numcores=None):
"""
NAME:
__init__
PURPOSE:
Initialize an interpRZPotential instance
INPUT:
RZPot - RZPotential to be interpolated
rgrid - R grid to be given to linspace as in rs= linspace(*rgrid)
zgrid - z grid to be given to linspace as in zs= linspace(*zgrid)
logR - if True, rgrid is in the log of R so logrs= linspace(*rgrid)
interpPot, interpRforce, interpzforce, interpDens,interpvcirc, interpepifreq, interpverticalfreq, interpdvcircdr= if True, interpolate these functions
use_c= use C to speed up the calculation of the grid
enable_c= enable use of C for interpolations
zsym= if True (default), the potential is assumed to be symmetric around z=0 (so you can use, e.g., zgrid=(0.,1.,101)).
numcores= if set to an integer, use this many cores (only used for vcirc, dvcircdR, epifreq, and verticalfreq; NOT NECESSARILY FASTER, TIME TO MAKE SURE)
ro=, vo= distance and velocity scales for translation into internal units (default from configuration file)
OUTPUT:
instance
HISTORY:
2010-07-21 - Written - Bovy (NYU)
2013-01-24 - Started with new implementation - Bovy (IAS)
"""
if isinstance(RZPot,interpRZPotential):
from galpy.potential import PotentialError
raise PotentialError('Cannot setup interpRZPotential with another interpRZPotential')
# Propagate ro and vo
roSet= True
voSet= True
if ro is None:
if isinstance(RZPot,list):
ro= RZPot[0]._ro
roSet= RZPot[0]._roSet
else:
ro= RZPot._ro
roSet= RZPot._roSet
if vo is None:
if isinstance(RZPot,list):
vo= RZPot[0]._vo
voSet= RZPot[0]._voSet
else:
vo= RZPot._vo
voSet= RZPot._voSet
Potential.__init__(self,amp=1.,ro=ro,vo=vo)
# Turn off physical if it hadn't been on
if not roSet: self._roSet= False
if not voSet: self._voSet= False
self._origPot= RZPot
self._rgrid= numpy.linspace(*rgrid)
self._logR= logR
if self._logR:
self._rgrid= numpy.exp(self._rgrid)
self._logrgrid= numpy.log(self._rgrid)
self._zgrid= numpy.linspace(*zgrid)
self._interpPot= interpPot
self._interpRforce= interpRforce
self._interpzforce= interpzforce
self._interpDens= interpDens
self._interpvcirc= interpvcirc
self._interpdvcircdr= interpdvcircdr
self._interpepifreq= interpepifreq
self._interpverticalfreq= interpverticalfreq
self._enable_c= enable_c*ext_loaded
self.hasC= self._enable_c
self._zsym= zsym
if interpPot:
if use_c*ext_loaded:
self._potGrid, err= calc_potential_c(self._origPot,self._rgrid,self._zgrid)
else:
from galpy.potential import evaluatePotentials
potGrid= numpy.zeros((len(self._rgrid),len(self._zgrid)))
for ii in range(len(self._rgrid)):
for jj in range(len(self._zgrid)):
potGrid[ii,jj]= evaluatePotentials(self._origPot,self._rgrid[ii],self._zgrid[jj])
self._potGrid= potGrid
if self._logR:
self._potInterp= interpolate.RectBivariateSpline(self._logrgrid,
self._zgrid,
self._potGrid,
kx=3,ky=3,s=0.)
else:
self._potInterp= interpolate.RectBivariateSpline(self._rgrid,
self._zgrid,
self._potGrid,
kx=3,ky=3,s=0.)
if enable_c*ext_loaded:
self._potGrid_splinecoeffs= calc_2dsplinecoeffs_c(self._potGrid)
if interpRforce:
if use_c*ext_loaded:
self._rforceGrid, err= calc_potential_c(self._origPot,self._rgrid,self._zgrid,rforce=True)
else:
from galpy.potential import evaluateRforces
rforceGrid= numpy.zeros((len(self._rgrid),len(self._zgrid)))
for ii in range(len(self._rgrid)):
for jj in range(len(self._zgrid)):
rforceGrid[ii,jj]= evaluateRforces(self._origPot,self._rgrid[ii],self._zgrid[jj])
self._rforceGrid= rforceGrid
if self._logR:
self._rforceInterp= interpolate.RectBivariateSpline(self._logrgrid,
self._zgrid,
self._rforceGrid,
kx=3,ky=3,s=0.)
else:
self._rforceInterp= interpolate.RectBivariateSpline(self._rgrid,
self._zgrid,
self._rforceGrid,
kx=3,ky=3,s=0.)
if enable_c*ext_loaded:
self._rforceGrid_splinecoeffs= calc_2dsplinecoeffs_c(self._rforceGrid)
if interpzforce:
if use_c*ext_loaded:
self._zforceGrid, err= calc_potential_c(self._origPot,self._rgrid,self._zgrid,zforce=True)
else:
from galpy.potential import evaluatezforces
zforceGrid= numpy.zeros((len(self._rgrid),len(self._zgrid)))
for ii in range(len(self._rgrid)):
for jj in range(len(self._zgrid)):
zforceGrid[ii,jj]= evaluatezforces(self._origPot,self._rgrid[ii],self._zgrid[jj])
self._zforceGrid= zforceGrid
if self._logR:
self._zforceInterp= interpolate.RectBivariateSpline(self._logrgrid,
self._zgrid,
self._zforceGrid,
kx=3,ky=3,s=0.)
else:
self._zforceInterp= interpolate.RectBivariateSpline(self._rgrid,
self._zgrid,
self._zforceGrid,
kx=3,ky=3,s=0.)
if enable_c*ext_loaded:
self._zforceGrid_splinecoeffs= calc_2dsplinecoeffs_c(self._zforceGrid)
if interpDens:
from galpy.potential import evaluateDensities
densGrid= numpy.zeros((len(self._rgrid),len(self._zgrid)))
for ii in range(len(self._rgrid)):
for jj in range(len(self._zgrid)):
densGrid[ii,jj]= evaluateDensities(self._origPot,self._rgrid[ii],self._zgrid[jj])
self._densGrid= densGrid
if self._logR:
self._densInterp= interpolate.RectBivariateSpline(self._logrgrid,
self._zgrid,
numpy.log(self._densGrid+10.**-10.),
kx=3,ky=3,s=0.)
else:
self._densInterp= interpolate.RectBivariateSpline(self._rgrid,
self._zgrid,
numpy.log(self._densGrid+10.**-10.),
kx=3,ky=3,s=0.)
if interpvcirc:
from galpy.potential import vcirc
if not numcores is None:
self._vcircGrid= multi.parallel_map((lambda x: vcirc(self._origPot,self._rgrid[x])),
list(range(len(self._rgrid))),numcores=numcores)
else:
self._vcircGrid= numpy.array([vcirc(self._origPot,r) for r in self._rgrid])
if self._logR:
self._vcircInterp= interpolate.InterpolatedUnivariateSpline(self._logrgrid,self._vcircGrid,k=3)
else:
self._vcircInterp= interpolate.InterpolatedUnivariateSpline(self._rgrid,self._vcircGrid,k=3)
if interpdvcircdr:
from galpy.potential import dvcircdR
if not numcores is None:
self._dvcircdrGrid= multi.parallel_map((lambda x: dvcircdR(self._origPot,self._rgrid[x])),
list(range(len(self._rgrid))),numcores=numcores)
else:
self._dvcircdrGrid= numpy.array([dvcircdR(self._origPot,r) for r in self._rgrid])
if self._logR:
self._dvcircdrInterp= interpolate.InterpolatedUnivariateSpline(self._logrgrid,self._dvcircdrGrid,k=3)
else:
self._dvcircdrInterp= interpolate.InterpolatedUnivariateSpline(self._rgrid,self._dvcircdrGrid,k=3)
if interpepifreq:
from galpy.potential import epifreq
if not numcores is None:
self._epifreqGrid= numpy.array(multi.parallel_map((lambda x: epifreq(self._origPot,self._rgrid[x])),
list(range(len(self._rgrid))),numcores=numcores))
else:
self._epifreqGrid= numpy.array([epifreq(self._origPot,r) for r in self._rgrid])
indx= True^numpy.isnan(self._epifreqGrid)
if numpy.sum(indx) < 4:
if self._logR:
self._epifreqInterp= interpolate.InterpolatedUnivariateSpline(self._logrgrid[indx],self._epifreqGrid[indx],k=1)
else:
self._epifreqInterp= interpolate.InterpolatedUnivariateSpline(self._rgrid[indx],self._epifreqGrid[indx],k=1)
else:
if self._logR:
self._epifreqInterp= interpolate.InterpolatedUnivariateSpline(self._logrgrid[indx],self._epifreqGrid[indx],k=3)
else:
self._epifreqInterp= interpolate.InterpolatedUnivariateSpline(self._rgrid[indx],self._epifreqGrid[indx],k=3)
if interpverticalfreq:
from galpy.potential import verticalfreq
if not numcores is None:
self._verticalfreqGrid= multi.parallel_map((lambda x: verticalfreq(self._origPot,self._rgrid[x])),
list(range(len(self._rgrid))),numcores=numcores)
else:
self._verticalfreqGrid= numpy.array([verticalfreq(self._origPot,r) for r in self._rgrid])
if self._logR:
self._verticalfreqInterp= interpolate.InterpolatedUnivariateSpline(self._logrgrid,self._verticalfreqGrid,k=3)
else:
self._verticalfreqInterp= interpolate.InterpolatedUnivariateSpline(self._rgrid,self._verticalfreqGrid,k=3)
return None
def _sample_galpy_potential(pot,
n,
rmin,
rmax,
ro=8.,
vo=220.,
coordinates='cartesian'):
"""Generate positions and velocities from galpy potentail
Parameters
----------
pot : class
galpy potential
N : int
number of stars in the cluster (default: 1000)
rmin : float
minimum stellar radius (default: 0.01)
rmax : float
maximnum stellar radius (default: 100.)
ro : float
galpy distance scaling parameter
vo : float
galpy velocity scaling parameter
coordinates : str
coordinate system to return (default: cartesian)
Returns
-------
x,y,z,vx,vy,vz : float
positions and velocities of generated points
History
-------
2020 - Written - Webb (UofT)
"""
ran = np.random.rand(n)
rad = np.linspace(rmin, rmax, n)
try:
menc = pot.mass(rad / ro, z=0, t=0, forceint=False)
except:
vc = potential.vcirc(pot,
rad / ro,
phi=0,
t=0.,
ro=ro,
vo=vo,
use_physical=False)
menc = vc**2. * (rad / ro)
menc *= bovy_conversion.mass_in_msol(ro=ro, vo=vo)
r = np.interp(ran, menc / menc[-1], rad)
phi = 2.0 * np.pi * np.random.rand(n)
theta = np.arccos(1.0 - 2.0 * np.random.rand(n))
x = r * np.sin(theta) * np.cos(phi)
y = r * np.sin(theta) * np.sin(phi)
z = r * np.cos(theta)
sigma_v_1d = vo * potential.vcirc(
pot, rad / ro, phi=0, t=0., ro=ro, vo=vo,
use_physical=False) / np.sqrt(3.)
vx = np.random.normal(0., sigma_v_1d, n)
vy = np.random.normal(0., sigma_v_1d, n)
vz = np.random.normal(0., sigma_v_1d, n)
if coordinates == 'spherical':
vr = (vx * np.sin(theta) * np.cos(phi) +
vy * np.sin(theta) * np.sin(phi) + vz * np.cos(theta))
vtheta = (vx * np.cos(theta) * np.cos(phi) +
vy * np.cos(theta) * np.sin(phi) - vz * np.sin(theta))
vphi = vx * -np.sin(phi) + vy * np.cos(phi)
x, y, z = r, phi, theta
vx, vy, vz = vr, vphi, vtheta
elif coordinates == 'cylindrical':
x, y, z = bovy_coords.rect_to_cyl(x, y, z)
vx, vy, vz = bovy_coords.rect_to_cyl_vec(vx, vy, vz, x, y, z, True)
return x, y, z, vx, vy, vz
def f_vlsr(r, R0, v0, l, b):
return (R0 * vcirc(MWPotential2014,r/R0,ro=R0,vo=v0) /
r - vcirc(MWPotential2014,1,ro=R0,vo=v0)) * np.sin(l) * np.cos(b)
def __init__(self,
RZPot=None,rgrid=(0.01,2.,101),zgrid=(0.,0.2,101),logR=False,
interpPot=False,interpRforce=False,interpzforce=False,
interpDens=False,
interpvcirc=False,
interpdvcircdr=False,
interpepifreq=False,interpverticalfreq=False,
use_c=False,enable_c=False,zsym=True,
numcores=None):
"""
NAME:
__init__
PURPOSE:
Initialize an interpRZPotential instance
INPUT:
RZPot - RZPotential to be interpolated
rgrid - R grid to be given to linspace
zgrid - z grid to be given to linspace
logR - if True, rgrid is in the log of R
interpPot, interpRfoce, interpzforce, interpDens,interpvcirc, interpeopifreq, interpverticalfreq, interpdvcircdr= if True, interpolate these functions
use_c= use C to speed up the calculation
enable_c= enable use of C for interpolations
zsym= if True (default), the potential is assumed to be symmetric around z=0 (so you can use, e.g., zgrid=(0.,1.,101)).
numcores= if set to an integer, use this many cores (only used for vcirc, dvcircdR, epifreq, and verticalfreq; NOT NECESSARILY FASTER, TIME TO MAKE SURE)
OUTPUT:
instance
HISTORY:
2010-07-21 - Written - Bovy (NYU)
2013-01-24 - Started with new implementation - Bovy (IAS)
"""
Potential.__init__(self,amp=1.)
self.hasC= True
self._origPot= RZPot
self._rgrid= numpy.linspace(*rgrid)
self._logR= logR
if self._logR:
self._rgrid= numpy.exp(self._rgrid)
self._logrgrid= numpy.log(self._rgrid)
self._zgrid= numpy.linspace(*zgrid)
self._interpPot= interpPot
self._interpRforce= interpRforce
self._interpzforce= interpzforce
self._interpDens= interpDens
self._interpvcirc= interpvcirc
self._interpdvcircdr= interpdvcircdr
self._interpepifreq= interpepifreq
self._interpverticalfreq= interpverticalfreq
self._enable_c= enable_c*ext_loaded
self._zsym= zsym
if interpPot:
if use_c*ext_loaded:
self._potGrid, err= calc_potential_c(self._origPot,self._rgrid,self._zgrid)
else:
from galpy.potential import evaluatePotentials
potGrid= numpy.zeros((len(self._rgrid),len(self._zgrid)))
for ii in range(len(self._rgrid)):
for jj in range(len(self._zgrid)):
potGrid[ii,jj]= evaluatePotentials(self._rgrid[ii],self._zgrid[jj],self._origPot)
self._potGrid= potGrid
if self._logR:
self._potInterp= interpolate.RectBivariateSpline(self._logrgrid,
self._zgrid,
self._potGrid,
kx=3,ky=3,s=0.)
else:
self._potInterp= interpolate.RectBivariateSpline(self._rgrid,
self._zgrid,
self._potGrid,
kx=3,ky=3,s=0.)
if enable_c*ext_loaded:
self._potGrid_splinecoeffs= calc_2dsplinecoeffs_c(self._potGrid)
if interpRforce:
if use_c*ext_loaded:
self._rforceGrid, err= calc_potential_c(self._origPot,self._rgrid,self._zgrid,rforce=True)
else:
from galpy.potential import evaluateRforces
rforceGrid= numpy.zeros((len(self._rgrid),len(self._zgrid)))
for ii in range(len(self._rgrid)):
for jj in range(len(self._zgrid)):
rforceGrid[ii,jj]= evaluateRforces(self._rgrid[ii],self._zgrid[jj],self._origPot)
self._rforceGrid= rforceGrid
if self._logR:
self._rforceInterp= interpolate.RectBivariateSpline(self._logrgrid,
self._zgrid,
self._rforceGrid,
kx=3,ky=3,s=0.)
else:
self._rforceInterp= interpolate.RectBivariateSpline(self._rgrid,
self._zgrid,
self._rforceGrid,
kx=3,ky=3,s=0.)
if enable_c*ext_loaded:
self._rforceGrid_splinecoeffs= calc_2dsplinecoeffs_c(self._rforceGrid)
if interpzforce:
if use_c*ext_loaded:
self._zforceGrid, err= calc_potential_c(self._origPot,self._rgrid,self._zgrid,zforce=True)
else:
from galpy.potential import evaluatezforces
zforceGrid= numpy.zeros((len(self._rgrid),len(self._zgrid)))
for ii in range(len(self._rgrid)):
for jj in range(len(self._zgrid)):
zforceGrid[ii,jj]= evaluatezforces(self._rgrid[ii],self._zgrid[jj],self._origPot)
self._zforceGrid= zforceGrid
if self._logR:
self._zforceInterp= interpolate.RectBivariateSpline(self._logrgrid,
self._zgrid,
self._zforceGrid,
kx=3,ky=3,s=0.)
else:
self._zforceInterp= interpolate.RectBivariateSpline(self._rgrid,
self._zgrid,
self._zforceGrid,
kx=3,ky=3,s=0.)
if enable_c*ext_loaded:
self._zforceGrid_splinecoeffs= calc_2dsplinecoeffs_c(self._zforceGrid)
if interpDens:
if False:
raise NotImplementedError("Using C to calculate an interpolation grid for the density is not supported currently")
self._densGrid, err= calc_dens_c(self._origPot,self._rgrid,self._zgrid)
else:
from galpy.potential import evaluateDensities
densGrid= numpy.zeros((len(self._rgrid),len(self._zgrid)))
for ii in range(len(self._rgrid)):
for jj in range(len(self._zgrid)):
densGrid[ii,jj]= evaluateDensities(self._rgrid[ii],self._zgrid[jj],self._origPot)
self._densGrid= densGrid
if self._logR:
self._densInterp= interpolate.RectBivariateSpline(self._logrgrid,
self._zgrid,
numpy.log(self._densGrid+10.**-10.),
kx=3,ky=3,s=0.)
else:
self._densInterp= interpolate.RectBivariateSpline(self._rgrid,
self._zgrid,
numpy.log(self._densGrid+10.**-10.),
kx=3,ky=3,s=0.)
if False:
self._densGrid_splinecoeffs= calc_2dsplinecoeffs_c(self._densGrid)
if interpvcirc:
from galpy.potential import vcirc
if not numcores is None:
self._vcircGrid= multi.parallel_map((lambda x: vcirc(self._origPot,self._rgrid[x])),
range(len(self._rgrid)),numcores=numcores)
else:
self._vcircGrid= numpy.array([vcirc(self._origPot,r) for r in self._rgrid])
if self._logR:
self._vcircInterp= interpolate.InterpolatedUnivariateSpline(self._logrgrid,self._vcircGrid,k=3)
else:
self._vcircInterp= interpolate.InterpolatedUnivariateSpline(self._rgrid,self._vcircGrid,k=3)
if interpdvcircdr:
from galpy.potential import dvcircdR
if not numcores is None:
self._dvcircdrGrid= multi.parallel_map((lambda x: dvcircdR(self._origPot,self._rgrid[x])),
range(len(self._rgrid)),numcores=numcores)
else:
self._dvcircdrGrid= numpy.array([dvcircdR(self._origPot,r) for r in self._rgrid])
if self._logR:
self._dvcircdrInterp= interpolate.InterpolatedUnivariateSpline(self._logrgrid,self._dvcircdrGrid,k=3)
else:
self._dvcircdrInterp= interpolate.InterpolatedUnivariateSpline(self._rgrid,self._dvcircdrGrid,k=3)
if interpepifreq:
from galpy.potential import epifreq
if not numcores is None:
self._epifreqGrid= multi.parallel_map((lambda x: epifreq(self._origPot,self._rgrid[x])),
range(len(self._rgrid)),numcores=numcores)
else:
self._epifreqGrid= numpy.array([epifreq(self._origPot,r) for r in self._rgrid])
indx= True-numpy.isnan(self._epifreqGrid)
if numpy.sum(indx) < 4:
if self._logR:
self._epifreqInterp= interpolate.InterpolatedUnivariateSpline(self._logrgrid[indx],self._epifreqGrid[indx],k=1)
else:
self._epifreqInterp= interpolate.InterpolatedUnivariateSpline(self._rgrid[indx],self._epifreqGrid[indx],k=1)
else:
if self._logR:
self._epifreqInterp= interpolate.InterpolatedUnivariateSpline(self._logrgrid[indx],self._epifreqGrid[indx],k=3)
else:
self._epifreqInterp= interpolate.InterpolatedUnivariateSpline(self._rgrid[indx],self._epifreqGrid[indx],k=3)
if interpverticalfreq:
from galpy.potential import verticalfreq
if not numcores is None:
self._verticalfreqGrid= multi.parallel_map((lambda x: verticalfreq(self._origPot,self._rgrid[x])),
range(len(self._rgrid)),numcores=numcores)
else:
self._verticalfreqGrid= numpy.array([verticalfreq(self._origPot,r) for r in self._rgrid])
if self._logR:
self._verticalfreqInterp= interpolate.InterpolatedUnivariateSpline(self._logrgrid,self._verticalfreqGrid,k=3)
else:
self._verticalfreqInterp= interpolate.InterpolatedUnivariateSpline(self._rgrid,self._verticalfreqGrid,k=3)
return None
def add_MCs(pot=MWPotential2014,Mmin=10**6.,rand_rotate=False,ro=_REFR0):
'''
Setup Molecular clouds and return their
M,rs,R,vR,vT,z,vz,phi today
rand_rotate : if True, add random rotation to phi between [0,2pi]
'''
hdulist=fits.open('molecular_clouds/J_ApJ_834_57_table1.dat.gz.fits')
aa=hdulist[1].data
l=aa['GLON']
b=aa['GLAT']
#Near or far distance flag (0=near; 1=far)
flag=aa['INF']
Dnear=aa['Dnear']
Dfar=aa['Dfar']
znear=aa['znear']
zfar=aa['zfar']
#R_sph_gal=aa['Rgal']
Rnear=aa['Rnear']
Rfar=aa['Rfar']
Mnear=aa['Mnear']
Mfar=aa['Mfar']
D_all=np.empty(len(l))
zfile=np.empty(len(l))
rs_all=np.empty(len(l))
M_all=np.empty(len(l))
for ii in range(len(l)):
if flag[ii] == 0 :
D_all[ii]=Dnear[ii]
zfile[ii]=znear[ii]
#rs_all[ii]=Rnear[ii]*0.001 #convert to kpc
M_all[ii]=Mnear[ii]
else :
D_all[ii]=Dfar[ii]
zfile[ii]=zfar[ii]
#rs_all[ii]=Rfar[ii]*0.001 #convert to kpc
M_all[ii]=Mfar[ii]
R_all,phi_all,z_all= lbd_to_galcencyl(l,b,D_all*(8.5/8.))
def rs(M):
return 0.1*(M/10**7.)**0.5
for ii in range(len(M_all)):
rs_all[ii]=rs(M_all[ii])
R_all/=ro
z_all/=ro
M=[]
rs=[]
z=[]
R=[]
phi=[]
for ii in range(len(l)):
if M_all[ii] >= Mmin :
M.append(M_all[ii])
rs.append(rs_all[ii])
z.append(z_all[ii])
phi.append(phi_all[ii])
R.append(R_all[ii])
M=np.array(M)
rs=np.array(rs)
z=np.array(z)
R=np.array(R)
phi=np.array(phi)
if rand_rotate :
phi+=2*np.pi*np.random.uniform(low=0.,high=1.,size=len(phi))
print (phi)
vT=np.empty(len(M))
for ii in range(len(M)):
vT[ii]=vcirc(pot,R[ii])
vR=np.zeros(len(M))
vz=np.zeros(len(M))
coord=[]
for ii in range(len(M)):
coord.append([R[ii],vR[ii],vT[ii],z[ii],vz[ii],phi[ii]])
return (M,rs,coord)
def VpratioMW(Rpkpc):
a = vcirc(MWPotential2014, Rpkpc / par.Rskpc)
return a
def VpratioMWBH(Rpkpc):
MWPotential2014wBH= [MWPotential2014,KeplerPotential(amp=4*10**6./bovy_conversion.mass_in_msol(par.Vs,par.Rskpc))]
a = vcirc(MWPotential2014wBH,Rpkpc/par.Rskpc)
return a;
def v_orbit(r):
return 220.0 * vcirc(mp, r / R_0)
