def determine_kxky_error():
#Load fiducial bar model
spvlos= galpy_simulations.vlos('../sim/bar_rect_alpha0.015%s.sav' % _HIVRESSTR)[1::2,1::2]
#spvlos= galpy_simulations.vlos('../sim/spiral_rect_omegas0.33_alpha-14%s.sav' % _HIVRESSTR)[1::2,1::2]*0.85
#spvlos= galpy_simulations.vlos('../sim/spiral_rect_omegas0.33_alpha-7%s.sav' % _HIVRESSTR)[1::2,1::2]*0.25
psd2d= bovy_psd.psd2d(spvlos)
kmax= 1./_RCDX
#Calculate maximum
psd2d[psd2d.shape[0]/2-1:psd2d.shape[0]/2+2,psd2d.shape[1]/2-1:psd2d.shape[1]/2+2]= 0.
tmax= numpy.unravel_index(numpy.argmax(psd2d),psd2d.shape)
tmax0= float(psd2d.shape[0]/2-tmax[0])/psd2d.shape[0]*2
tmax1= float(tmax[1]-psd2d.shape[1]/2)/psd2d.shape[1]*2
print tmax0*kmax, tmax1*kmax
bovy_plot.bovy_print()
bovy_plot.bovy_dens2d(psd2d.T,origin='lower',cmap='jet',
interpolation='nearest',
xrange=[-kmax,kmax],
yrange=[-kmax,kmax],
xlabel=r'$k_x\,(\mathrm{kpc}^{-1})$',
ylabel=r'$k_y\,(\mathrm{kpc}^{-1})$')
bovy_plot.bovy_end_print('/Users/bovy/Desktop/test.png')
#Read the data for the noise
data= apread.rcsample()
if _ADDLLOGGCUT:
data= data[data['ADDL_LOGG_CUT'] == 1]
#Cut
indx= (numpy.fabs(data['RC_GALZ']) < 0.25)*(data['METALS'] > -1000.)
print "Using %i stars for low-Z 2D kinematics analysis" % numpy.sum(indx)
data= data[indx]
#Get residuals
dx= _RCDX
pix= pixelize_sample.pixelXY(data,
xmin=_RCXMIN,xmax=_RCXMAX,
ymin=_RCYMIN,ymax=_RCYMAX,
dx=dx,dy=dx)
resvunc= pix.plot('VHELIO_AVG',
func=lambda x: 1.4826*numpy.median(numpy.fabs(x-numpy.median(x)))/numpy.sqrt(len(x)),
returnz=True,justcalc=True)
#Now do 1000 MC simulations to determine the error on kmax
nmc= 1000
kxmax= numpy.zeros(nmc)
kymax= numpy.zeros(nmc)
for ii in range(nmc):
newresv= spvlos+numpy.random.normal(size=spvlos.shape)*resvunc/220.
simpsd2d= bovy_psd.psd2d(newresv*220.)
simpsd2d[simpsd2d.shape[0]/2-1:simpsd2d.shape[0]/2+2,simpsd2d.shape[1]/2-1:simpsd2d.shape[1]/2+2]= 0.
tmax= numpy.unravel_index(numpy.argmax(simpsd2d),psd2d.shape)
tmax0= float(psd2d.shape[0]/2-tmax[0])/psd2d.shape[0]*2
tmax1= float(tmax[1]-psd2d.shape[1]/2)/psd2d.shape[1]*2
kmax= 1./_RCDX
kxmax[ii]= tmax0*kmax
kymax[ii]= tmax1*kmax
print numpy.mean(kxmax), numpy.std(kxmax)
print numpy.mean(kymax), numpy.std(kymax)
return None
def plot_psd2d(plotfilename):
data= apread.rcsample()
if _ADDLLOGGCUT:
data= data[data['ADDL_LOGG_CUT'] == 1]
#Cut
indx= (numpy.fabs(data['RC_GALZ']) < 0.25)*(data['METALS'] > -1000.)
print "Using %i stars for low-Z 2D kinematics analysis" % numpy.sum(indx)
data= data[indx]
#Get residuals
dx= _RCDX
binsize= .8#.765
pix= pixelize_sample.pixelXY(data,
xmin=_RCXMIN,xmax=_RCXMAX,
ymin=_RCYMIN,ymax=_RCYMAX,
dx=dx,dy=dx)
resv= pix.plot(lambda x: dvlosgal(x,vtsun=220.+22.6),
returnz=True,justcalc=True)
resvunc= pix.plot('VHELIO_AVG',
func=lambda x: 1.4826*numpy.median(numpy.fabs(x-numpy.median(x)))/numpy.sqrt(len(x)),
returnz=True,justcalc=True)
psd2d= bovy_psd.psd2d(resv)
tmax= numpy.unravel_index(numpy.argmax(psd2d),psd2d.shape)
tmax0= float(psd2d.shape[0]/2-tmax[0])/psd2d.shape[0]*2
tmax1= float(tmax[1]-psd2d.shape[1]/2)/psd2d.shape[1]*2
kmax= 1./_RCDX
print tmax0*kmax, tmax1*kmax
#kmax= numpy.amax(numpy.fft.fftfreq(resv.shape[0]*2,_RCDX))
bovy_plot.bovy_print()
bovy_plot.bovy_dens2d(psd2d.T,origin='lower',cmap='jet',
interpolation='nearest',
xrange=[-kmax,kmax],
yrange=[-kmax,kmax],
xlabel=r'$k_x\,(\mathrm{kpc}^{-1})$',
ylabel=r'$k_y\,(\mathrm{kpc}^{-1})$')
bovy_plot.bovy_end_print(plotfilename)
if True:
spvlos= galpy_simulations.vlos('../sim/bar_rect_alpha0.015_hivres.sav')[1::2,1::2]
potscale= 1.
kmax= 1./_RCDX
print tmax0*kmax, tmax1*kmax
#kmax= numpy.amax(numpy.fft.fftfreq(resv.shape[0]*2,_RCDX))
bovy_plot.bovy_print()
bovy_plot.bovy_dens2d(psd2d.T,origin='lower',cmap='jet',
interpolation='nearest',
xrange=[-kmax,kmax],
yrange=[-kmax,kmax],
xlabel=r'$k_x\,(\mathrm{kpc}^{-1})$',
ylabel=r'$k_y\,(\mathrm{kpc}^{-1})$')
bovy_plot.bovy_end_print(plotfilename)
if True:
spvlos= galpy_simulations.vlos('../sim/bar_rect_alpha0.015_hivres.sav')[1::2,1::2]
potscale= 1.
k spvlos+= numpy.random.normal(size=spvlos.shape)*resvunc/220./potscale
simpsd2d= bovy_psd.psd2d(spvlos*220.*potscale)
bovy_plot.bovy_print()
bovy_plot.bovy_dens2d(simpsd2d.T,
origin='lower',cmap='jet',
interpolation='nearest',
xrange=[-kmax,kmax],
yrange=[-kmax,kmax],
xlabel=r'$k_x\,(\mathrm{kpc}^{-1})$',
ylabel=r'$k_y\,(\mathrm{kpc}^{-1})$')
fileparts= re.split(r'\.',plotfilename)
nparts= len(fileparts)
simfilename= ''
for ii in range(nparts):
if ii == nparts-2: simfilename+= fileparts[ii]+'_simpsd2d.'
elif ii == nparts-1: simfilename+= fileparts[ii]
else: simfilename+= fileparts[ii]+'.'