########NONAXI
if addNonAxi:
nonAxiFile= 'predict_l_vhelio_nonaxi.sav'
if os.path.exists(nonAxiFile):
nonaxi_file= open(nonAxiFile,'rb')
nonaxils= pickle.load(nonaxi_file)
nonaxiEl= pickle.load(nonaxi_file)
nonaxiBar= pickle.load(nonaxi_file)
nonaxi_file.close()
else:
print "Working on NonAxi ..."
elfile= '/work/bovy/data/bovy/nonaximw/elliptical/el_rect_so_0.2_res_51_grid_101_tform_-150._tsteady_125._cp_0.05_nsigma_4.sav'
print "Reading bar file ..."
barfile= '/work/bovy/data/bovy/nonaximw/bar/bar_rect_vr_tform-150_tsteady-4pi_51_101.sav'
#elliptical
surfmass,meanvr,meanvt,sigmar2,sigmat2,sigmart,vertexdev,surfmass_init,meanvt_init,sigmar2_init,sigmat2_init,ii,jj,grid = read_output(elfile)
xgrid, ygrid= marginalize_phasedist.phiR_input(51,0.5,2.)
interpObj= marginalize_phasedist.interp_velocity_field(xgrid,ygrid,surfmass,meanvr,meanvt)
interpObjAxi= marginalize_phasedist.interp_velocity_field(xgrid,ygrid,surfmass_init,0.,meanvt_init)
nonaxils= numpy.linspace(30.,330.,501)
nonaxiEl= numpy.zeros(len(nonaxils))
phio=70.
print "Calculating elliptical perturbation ..."
print "WARNING: DOES NOT CORRECTLY USE SURFMASS"
for ii in range(len(nonaxils)):
print ii
nonaxiEl[ii]= marginalize_phasedist.mvlos_l(nonaxils[ii],interpObj,degree=True,phio=phio)-marginalize_phasedist.mvlos_l(nonaxils[ii],interpObjAxi,degree=True,phio=phio)
#Bar
surfmass,meanvr,meanvt,sigmar2,sigmat2,sigmart,vertexdev,surfmass_init,meanvt_init,sigmar2_init,sigmat2_init,ii,jj,grid = read_output(barfile)
interpObj= marginalize_phasedist.interp_velocity_field(xgrid,ygrid,surfmass,meanvr,meanvt)
interpObjAxi= marginalize_phasedist.interp_velocity_field(xgrid,ygrid,surfmass_init,0.,meanvt_init)
def calc_nonaxi(params, barfile, options, data, logpiso, nlocs, locations,
phio):
#Average over data and integrate over distance
surfmass, meanvr, meanvt, sigmar2, sigmat2, sigmart, vertexdev, surfmass_init, meanvt_init, sigmar2_init, sigmat2_init, ii, jj, grid = read_output(
barfile)
xgrid, ygrid = marginalize_phasedist.phiR_input(51, 0.5, 2.)
interpObj = marginalize_phasedist.interp_velocity_field(
xgrid, ygrid, surfmass, meanvr, meanvt)
interpObjAxi = marginalize_phasedist.interp_velocity_field(
xgrid, ygrid, surfmass_init, 0., meanvt_init)
avg_plate_model = numpy.zeros(nlocs)
for ii in range(nlocs):
#Calculate vlos | los
indx = (data['LOCATION'] == locations[ii])
thesedata = data[indx]
thislogpiso = logpiso[indx, :]
if not options.multi is None:
mvlos = multi.parallel_map((lambda x: mvlosnonaxi(
params, interpObj, interpObjAxi, thesedata[x], options,
thislogpiso[x, :], phio)),
range(len(thesedata)),
numcores=numpy.amin([
len(thesedata),
multiprocessing.cpu_count(),
options.multi
]))
else:
mvlos = numpy.zeros(len(data))
for jj in range(len(thesedata)):
print jj
mvlos[jj] = mvlosnonaxi(params, interpObj, interpObjAxi,
thesedata[jj], options,
thislogpiso[jj, :], phio)
#Calculate mean and velocity dispersion
avg_plate_model[ii] = numpy.mean(mvlos)
return avg_plate_model * _REFV0 * params[0]
########NONAXI
if addNonAxi:
nonAxiFile = 'predict_l_vhelio_nonaxi.sav'
if os.path.exists(nonAxiFile):
nonaxi_file = open(nonAxiFile, 'rb')
nonaxils = pickle.load(nonaxi_file)
nonaxiEl = pickle.load(nonaxi_file)
nonaxiBar = pickle.load(nonaxi_file)
nonaxi_file.close()
else:
print "Working on NonAxi ..."
elfile = '/work/bovy/data/bovy/nonaximw/elliptical/el_rect_so_0.2_res_51_grid_101_tform_-150._tsteady_125._cp_0.05_nsigma_4.sav'
print "Reading bar file ..."
barfile = '/work/bovy/data/bovy/nonaximw/bar/bar_rect_vr_tform-150_tsteady-4pi_51_101.sav'
#elliptical
surfmass, meanvr, meanvt, sigmar2, sigmat2, sigmart, vertexdev, surfmass_init, meanvt_init, sigmar2_init, sigmat2_init, ii, jj, grid = read_output(
elfile)
xgrid, ygrid = marginalize_phasedist.phiR_input(51, 0.5, 2.)
interpObj = marginalize_phasedist.interp_velocity_field(
xgrid, ygrid, surfmass, meanvr, meanvt)
interpObjAxi = marginalize_phasedist.interp_velocity_field(
xgrid, ygrid, surfmass_init, 0., meanvt_init)
nonaxils = numpy.linspace(30., 330., 501)
nonaxiEl = numpy.zeros(len(nonaxils))
phio = 70.
print "Calculating elliptical perturbation ..."
print "WARNING: DOES NOT CORRECTLY USE SURFMASS"
for ii in range(len(nonaxils)):
print ii
nonaxiEl[ii] = marginalize_phasedist.mvlos_l(
nonaxils[ii], interpObj, degree=True,
phio=phio) - marginalize_phasedist.mvlos_l(
def calc_nonaxi(params, barfile, options, data, logpiso, nlocs, locations, phio):
# Average over data and integrate over distance
surfmass, meanvr, meanvt, sigmar2, sigmat2, sigmart, vertexdev, surfmass_init, meanvt_init, sigmar2_init, sigmat2_init, ii, jj, grid = read_output(
barfile
)
xgrid, ygrid = marginalize_phasedist.phiR_input(51, 0.5, 2.0)
interpObj = marginalize_phasedist.interp_velocity_field(xgrid, ygrid, surfmass, meanvr, meanvt)
interpObjAxi = marginalize_phasedist.interp_velocity_field(xgrid, ygrid, surfmass_init, 0.0, meanvt_init)
avg_plate_model = numpy.zeros(nlocs)
for ii in range(nlocs):
# Calculate vlos | los
indx = data["LOCATION"] == locations[ii]
thesedata = data[indx]
thislogpiso = logpiso[indx, :]
if not options.multi is None:
mvlos = multi.parallel_map(
(
lambda x: mvlosnonaxi(
params, interpObj, interpObjAxi, thesedata[x], options, thislogpiso[x, :], phio
)
),
range(len(thesedata)),
numcores=numpy.amin([len(thesedata), multiprocessing.cpu_count(), options.multi]),
)
else:
mvlos = numpy.zeros(len(data))
for jj in range(len(thesedata)):
print jj
mvlos[jj] = mvlosnonaxi(
params, interpObj, interpObjAxi, thesedata[jj], options, thislogpiso[jj, :], phio
)
# Calculate mean and velocity dispersion
avg_plate_model[ii] = numpy.mean(mvlos)
return avg_plate_model * _REFV0 * params[0]
V= numpy.array([[l[2],l[4]],[l[4],l[3]]])
return -numpy.sum(logmultiskewnormal(x,m,V,[0.,0.]))
def altoptm(l,df,zs):
m= numpy.array([l[0],l[1]])
V= numpy.array([[l[2],l[4]],[l[4],l[3]]])
a= numpy.array([l[5],l[6]])
return numpy.sum((multiskewnormal(zs,m,V,a)-df)**2.)
savefilename= 'testMultiSkews2.sav'
dfstr= 'dehnen'
s= numpy.exp(numpy.linspace(numpy.log(0.0125),numpy.log(0.2),21))
so= s[-1]
#so= 0.2
elsavefilename= os.path.join(OUTDIR,
'el_rect_so_%.6f_res_%i_grid_%i_tform_%.5f_tsteady_%.5f_cp_%.5f_nsigma_%.1f' % (so,101,101,-150.,125.,0.05,5) +
'_'+dfstr+'_%.6f_%.6f_%.6f.sav' % (1./3.,1.,0.))
surfmass,meanvr,meanvt,sigmar2,sigmat2,sigmart,vertexdev,surfmass_init,meanvt_init,sigmar2_init,sigmat2_init,ii,jj,grid = read_output(elsavefilename)
indx= int(long(numpy.floor(45./180.*101)))
grid= grid[indx]
if os.path.exists(savefilename):
savefile= open(savefilename,'rb')
vs= pickle.load(savefile)
savefile.close()
else:
#Set up everything up for sampling
sortindx= numpy.argsort(grid.df.flatten())[::-1]
cumul= numpy.cumsum(numpy.sort(grid.df.flatten())[::-1])/numpy.sum(grid.df.flatten())
vrs= numpy.zeros(grid.df.shape)
vts= numpy.zeros(grid.df.shape)
for ii in range(grid.df.shape[1]):
vrs[:,ii]= grid.vRgrid.reshape((101,1))
for ii in range(grid.df.shape[0]):
