def modelBHFitGrid(inFolder=None,plotOnly=False):
# routine to conduct a grid search over SMBH positions
cubeimg = pyfits.getdata(datadir + cuberoot + '_img.fits')
xaxis = np.arange(cubeimg.shape[0]) * 0.05
yaxis = np.arange(cubeimg.shape[1]) * 0.05
# original angles
Lorg = -42.8
Iorg = 54.1
Aorg = -34.5
CPA = -56.
# BH step size, in pixels
dPix = 1.
# number of steps away from the original angle in each direction (-/+)
# halfN = 1 gives 3 total steps, =2 gives 5 steps
halfN = 2.
N = (halfN*2)+1
startpos = [0.,0.]
posgridx = np.arange(startpos[0]-(halfN*dPix),startpos[0]+(halfN*dPix)+0.5,dPix)
posgridy = np.arange(startpos[1]-(halfN*dPix),startpos[1]+(halfN*dPix)+0.5,dPix)
if not plotOnly:
# create the new folder
FORMAT = '%Y%m%d_%H-%M-%S'
now = datetime.datetime.now().strftime(FORMAT)
newfolder = modeldir+'nonaligned_SMBH_grid_'+now+'/'
os.mkdir(newfolder)
#newfolder='/Users/kel/Documents/Projects/M31/models/Peiris/2003/nonaligned_grid_rotate_20160919_17-09-05/'
for pX in posgridx:
for pY in posgridy:
testpos = [pX,pY]
modelConvertBin(testSMBH=testpos,l98bin=False,verbose=False,tess=True,pathstem=newfolder)
modelCompRes(inModel=newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f.dat' % (testpos[0],testpos[1]),toPlot=False)
# plotting
py.close(2)
py.figure(2, figsize=(17,12))
py.subplots_adjust(left=0.05, right=0.94, top=0.95)
nPlot = N**2
# flux plots
py.clf()
plYY = np.fliplr([posgridy])[0]
plXX = np.fliplr([posgridx])[0]
pX,pY = np.meshgrid(plXX,plYY)
pX = pX.flatten()
pY = pY.flatten()
for pp in np.arange(nPlot):
py.subplot(N,N,pp+1)
#inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (pL[pp],pI[pp],AA,CPA)
if inFolder:
inRes = inFolder+'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f_residuals.dat' % (pX[pp],pY[pp])
else:
inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f_residuals.dat' % (pX[pp],pY[pp])
res = ppxf_m31.modelFitResults(inRes)
py.imshow(np.rot90(py.ma.masked_where(cubeimg==0.,res.nstar.T),3),vmin=-0.25,vmax=0.25,
extent=[xaxis[0], xaxis[-1], yaxis[0], yaxis[-1]])
# with the rotation+transposition of the residual image, the sign of dx is flipped (dy stays the same)
pltitle = '%.1f, %.1f' % (-1.*pX[pp],pY[pp])
py.title(pltitle)
py.xticks([])
py.yticks([])
cbar = py.colorbar(orientation='horizontal',ticks=[-.25,0.,.25])
clab = 'Flux res., $\\bullet_{model}$ at dx,dy'
cbar.set_label(clab)
if inFolder:
figname = inFolder + 'residuals_flux_SMBH.png'
else:
figname=newfolder + 'residuals_flux_SMBH.png'
py.savefig(figname)
# velocity plots - can probably integrate with flux plotting
py.clf()
for pp in np.arange(nPlot):
py.subplot(N,N,pp+1)
#inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (pL[pp],pI[pp],AA,CPA)
if inFolder:
inRes = inFolder+'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f_residuals.dat' % (pX[pp],pY[pp])
else:
inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f_residuals.dat' % (pX[pp],pY[pp])
res = ppxf_m31.modelFitResults(inRes)
py.imshow(np.rot90(py.ma.masked_where(cubeimg==0.,res.velocity.T),3),vmin=-100.,vmax=200.,
extent=[xaxis[0], xaxis[-1], yaxis[0], yaxis[-1]])
pltitle = '%.1f, %.1f' % (-1.*pX[pp],pY[pp])
py.title(pltitle)
py.xticks([])
py.yticks([])
cbar = py.colorbar(orientation='horizontal',ticks=[-100,0.,200])
clab = 'Velocity res., $\\bullet_{model}$ at dx,dy'
cbar.set_label(clab)
if inFolder:
figname = inFolder + 'residuals_velocity_SMBH.png'
else:
figname=newfolder + 'residuals_velocity_SMBH.png'
py.savefig(figname)
# sigma plots
py.clf()
for pp in np.arange(nPlot):
py.subplot(N,N,pp+1)
#inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (pL[pp],pI[pp],AA,CPA)
if inFolder:
inRes = inFolder+'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f_residuals.dat' % (pX[pp],pY[pp])
else:
inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f_residuals.dat' % (pX[pp],pY[pp])
res = ppxf_m31.modelFitResults(inRes)
py.imshow(np.rot90(py.ma.masked_where(cubeimg==0.,res.sigma.T),3),vmin=-100.,vmax=100.,
extent=[xaxis[0], xaxis[-1], yaxis[0], yaxis[-1]])
pltitle = '%.1f, %.1f' % (-1.*pX[pp],pY[pp])
py.title(pltitle)
py.xticks([])
py.yticks([])
cbar = py.colorbar(orientation='horizontal',ticks=[-100,0.,100])
clab = 'Sigma res., $\\bullet_{model}$ at dx,dy'
cbar.set_label(clab)
if inFolder:
figname = inFolder + 'residuals_sigma_SMBH.png'
else:
figname=newfolder + 'residuals_sigma_SMBH.png'
py.savefig(figname)
def modelBHFitGrid(inFolder=None, plotOnly=False):
# routine to conduct a grid search over SMBH positions
cubeimg = pyfits.getdata(datadir + cuberoot + '_img.fits')
xaxis = np.arange(cubeimg.shape[0]) * 0.05
yaxis = np.arange(cubeimg.shape[1]) * 0.05
# original angles
Lorg = -42.8
Iorg = 54.1
Aorg = -34.5
CPA = -56.
# BH step size, in pixels
dPix = 1.
# number of steps away from the original angle in each direction (-/+)
# halfN = 1 gives 3 total steps, =2 gives 5 steps
halfN = 2.
N = (halfN * 2) + 1
startpos = [0., 0.]
posgridx = np.arange(startpos[0] - (halfN * dPix),
startpos[0] + (halfN * dPix) + 0.5, dPix)
posgridy = np.arange(startpos[1] - (halfN * dPix),
startpos[1] + (halfN * dPix) + 0.5, dPix)
if not plotOnly:
# create the new folder
FORMAT = '%Y%m%d_%H-%M-%S'
now = datetime.datetime.now().strftime(FORMAT)
newfolder = modeldir + 'nonaligned_SMBH_grid_' + now + '/'
os.mkdir(newfolder)
#newfolder='/Users/kel/Documents/Projects/M31/models/Peiris/2003/nonaligned_grid_rotate_20160919_17-09-05/'
for pX in posgridx:
for pY in posgridy:
testpos = [pX, pY]
modelConvertBin(testSMBH=testpos,
l98bin=False,
verbose=False,
tess=True,
pathstem=newfolder)
modelCompRes(
inModel=newfolder +
'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f.dat'
% (testpos[0], testpos[1]),
toPlot=False)
# plotting
py.close(2)
py.figure(2, figsize=(17, 12))
py.subplots_adjust(left=0.05, right=0.94, top=0.95)
nPlot = N**2
# flux plots
py.clf()
plYY = np.fliplr([posgridy])[0]
plXX = np.fliplr([posgridx])[0]
pX, pY = np.meshgrid(plXX, plYY)
pX = pX.flatten()
pY = pY.flatten()
for pp in np.arange(nPlot):
py.subplot(N, N, pp + 1)
#inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (pL[pp],pI[pp],AA,CPA)
if inFolder:
inRes = inFolder + 'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f_residuals.dat' % (
pX[pp], pY[pp])
else:
inRes = newfolder + 'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f_residuals.dat' % (
pX[pp], pY[pp])
res = ppxf_m31.modelFitResults(inRes)
py.imshow(np.rot90(py.ma.masked_where(cubeimg == 0., res.nstar.T), 3),
vmin=-0.25,
vmax=0.25,
extent=[xaxis[0], xaxis[-1], yaxis[0], yaxis[-1]])
# with the rotation+transposition of the residual image, the sign of dx is flipped (dy stays the same)
pltitle = '%.1f, %.1f' % (-1. * pX[pp], pY[pp])
py.title(pltitle)
py.xticks([])
py.yticks([])
cbar = py.colorbar(orientation='horizontal', ticks=[-.25, 0., .25])
clab = 'Flux res., $\\bullet_{model}$ at dx,dy'
cbar.set_label(clab)
if inFolder:
figname = inFolder + 'residuals_flux_SMBH.png'
else:
figname = newfolder + 'residuals_flux_SMBH.png'
py.savefig(figname)
# velocity plots - can probably integrate with flux plotting
py.clf()
for pp in np.arange(nPlot):
py.subplot(N, N, pp + 1)
#inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (pL[pp],pI[pp],AA,CPA)
if inFolder:
inRes = inFolder + 'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f_residuals.dat' % (
pX[pp], pY[pp])
else:
inRes = newfolder + 'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f_residuals.dat' % (
pX[pp], pY[pp])
res = ppxf_m31.modelFitResults(inRes)
py.imshow(np.rot90(py.ma.masked_where(cubeimg == 0., res.velocity.T),
3),
vmin=-100.,
vmax=200.,
extent=[xaxis[0], xaxis[-1], yaxis[0], yaxis[-1]])
pltitle = '%.1f, %.1f' % (-1. * pX[pp], pY[pp])
py.title(pltitle)
py.xticks([])
py.yticks([])
cbar = py.colorbar(orientation='horizontal', ticks=[-100, 0., 200])
clab = 'Velocity res., $\\bullet_{model}$ at dx,dy'
cbar.set_label(clab)
if inFolder:
figname = inFolder + 'residuals_velocity_SMBH.png'
else:
figname = newfolder + 'residuals_velocity_SMBH.png'
py.savefig(figname)
# sigma plots
py.clf()
for pp in np.arange(nPlot):
py.subplot(N, N, pp + 1)
#inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (pL[pp],pI[pp],AA,CPA)
if inFolder:
inRes = inFolder + 'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f_residuals.dat' % (
pX[pp], pY[pp])
else:
inRes = newfolder + 'nonaligned_OSIRIScoords_fit_full_smooth_SMBH_x%+.1f_y%+.1f_residuals.dat' % (
pX[pp], pY[pp])
res = ppxf_m31.modelFitResults(inRes)
py.imshow(np.rot90(py.ma.masked_where(cubeimg == 0., res.sigma.T), 3),
vmin=-100.,
vmax=100.,
extent=[xaxis[0], xaxis[-1], yaxis[0], yaxis[-1]])
pltitle = '%.1f, %.1f' % (-1. * pX[pp], pY[pp])
py.title(pltitle)
py.xticks([])
py.yticks([])
cbar = py.colorbar(orientation='horizontal', ticks=[-100, 0., 100])
clab = 'Sigma res., $\\bullet_{model}$ at dx,dy'
cbar.set_label(clab)
if inFolder:
figname = inFolder + 'residuals_sigma_SMBH.png'
else:
figname = newfolder + 'residuals_sigma_SMBH.png'
py.savefig(figname)
def modelMorphFitGrid(inFolder=None,plotOnly=False):
# routine to conduct a grid search over the coordinate transformation angles
# (angles in Peiris & Tremaine 2003 eq 4)
cubeimg = pyfits.getdata(datadir + cuberoot + '_img.fits')
xaxis = np.arange(cubeimg.shape[0]) * 0.05
yaxis = np.arange(cubeimg.shape[1]) * 0.05
# original angles
Lorg = -42.8
Iorg = 54.1
Aorg = -34.5
# not changing CPA
CPA = -56.
# angle step size, in degrees
dAng = 3.
# number of steps away from the original angle in each direction (-/+)
# halfN = 1 gives 3 total steps, =2 gives 5 steps
halfN = 1.
N = (halfN*2)+1
Lgrid = np.arange(Lorg-(halfN*dAng),Lorg+(halfN*dAng)+1,dAng)
Igrid = np.arange(Iorg-(halfN*dAng),Iorg+(halfN*dAng)+1,dAng)
Agrid = np.arange(Aorg-(halfN*dAng),Aorg+(halfN*dAng)+1,dAng)
if not plotOnly:
# create the new folder
FORMAT = '%Y%m%d_%H-%M-%S'
now = datetime.datetime.now().strftime(FORMAT)
newfolder = modeldir+'nonaligned_grid_rotate_'+now+'/'
os.mkdir(newfolder)
#newfolder='/Users/kel/Documents/Projects/M31/models/Peiris/2003/nonaligned_grid_rotate_20160919_17-09-05/'
for LL in Lgrid:
for II in Igrid:
for AA in Agrid:
testAng = [LL,II,AA,CPA]
modelConvertBin(testAngles=testAng,l98bin=False,verbose=False,tess=True,pathstem=newfolder)
modelCompRes(inModel=newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (testAng[0],testAng[1],testAng[2],testAng[3]),toPlot=False)
# plotting
py.close(2)
py.figure(2)
py.subplots_adjust(left=0.05, right=0.94, top=0.95)
nPlot = N**2
# flux plots
for AA in Agrid:
py.clf()
plLL = np.fliplr([Lgrid])[0]
pI,pL = np.meshgrid(Igrid,plLL)
pI = pI.flatten()
pL = pL.flatten()
for pp in np.arange(nPlot):
py.subplot(N,N,pp+1)
#inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (pL[pp],pI[pp],AA,CPA)
if inFolder:
inRes = inFolder + 'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f_residuals.dat' % (pL[pp],pI[pp],AA,CPA)
else:
inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f_residuals.dat' % (pL[pp],pI[pp],AA,CPA)
res = ppxf_m31.modelFitResults(inRes)
py.imshow(np.rot90(py.ma.masked_where(cubeimg==0.,res.nstar.T),3),vmin=-0.25,vmax=0.25,
extent=[xaxis[0], xaxis[-1], yaxis[0], yaxis[-1]])
pltitle = '$\\theta_l$ = %.1f, $\\theta_i$ = %.1f' % (pL[pp],pI[pp])
py.title(pltitle)
py.xticks([])
py.yticks([])
cbar = py.colorbar(orientation='horizontal',ticks=[-.25,0.,.25])
clab = 'Flux residuals, $\\theta_a$ = %.1f' % (AA)
cbar.set_label(clab)
if inFolder:
figname = inFolder + 'residuals_flux_thetaA_%.1f.png' %(AA)
else:
figname=newfolder + 'residuals_flux_thetaA_%.1f.png' %(AA)
py.savefig(figname)
# velocity plots - can probably integrate with flux plotting
for AA in Agrid:
py.clf()
plLL = np.fliplr([Lgrid])[0]
pI,pL = np.meshgrid(Igrid,plLL)
pI = pI.flatten()
pL = pL.flatten()
for pp in np.arange(nPlot):
py.subplot(N,N,pp+1)
#inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (pL[pp],pI[pp],AA,CPA)
if inFolder:
inRes = inFolder + 'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f_residuals.dat' % (pL[pp],pI[pp],AA,CPA)
else:
inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f_residuals.dat' % (pL[pp],pI[pp],AA,CPA)
res = ppxf_m31.modelFitResults(inRes)
py.imshow(np.rot90(py.ma.masked_where(cubeimg==0.,res.velocity.T),3),vmin=-100.,vmax=200.,
extent=[xaxis[0], xaxis[-1], yaxis[0], yaxis[-1]])
pltitle = '$\\theta_l$ = %.1f, $\\theta_i$ = %.1f' % (pL[pp],pI[pp])
py.title(pltitle)
py.xticks([])
py.yticks([])
cbar = py.colorbar(orientation='horizontal',ticks=[-100.,0.,200.])
clab = 'Velocity residuals, $\\theta_a$ = %.1f' % (AA)
cbar.set_label(clab)
if inFolder:
figname = inFolder + 'residuals_velocity_thetaA_%.1f.png' %(AA)
else:
figname=newfolder + 'residuals_velocity_thetaA_%.1f.png' %(AA)
py.savefig(figname)
# sigma plots
for AA in Agrid:
py.clf()
plLL = np.fliplr([Lgrid])[0]
pI,pL = np.meshgrid(Igrid,plLL)
pI = pI.flatten()
pL = pL.flatten()
for pp in np.arange(nPlot):
py.subplot(N,N,pp+1)
#inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (pL[pp],pI[pp],AA,CPA)
if inFolder:
inRes = inFolder + 'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f_residuals.dat' % (pL[pp],pI[pp],AA,CPA)
else:
inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f_residuals.dat' % (pL[pp],pI[pp],AA,CPA)
res = ppxf_m31.modelFitResults(inRes)
py.imshow(np.rot90(py.ma.masked_where(cubeimg==0.,res.sigma.T),3),vmin=-100.,vmax=100.,
extent=[xaxis[0], xaxis[-1], yaxis[0], yaxis[-1]])
pltitle = '$\\theta_l$ = %.1f, $\\theta_i$ = %.1f' % (pL[pp],pI[pp])
py.title(pltitle)
py.xticks([])
py.yticks([])
cbar = py.colorbar(orientation='horizontal',ticks=[-100.,0.,100.])
clab = 'Sigma residuals, $\\theta_a$ = %.1f' % (AA)
cbar.set_label(clab)
if inFolder:
figname = inFolder + 'residuals_sigma_thetaA_%.1f.png' %(AA)
else:
figname=newfolder + 'residuals_sigma_thetaA_%.1f.png' %(AA)
py.savefig(figname)
def modelMorphFitGrid(inFolder=None, plotOnly=False):
# routine to conduct a grid search over the coordinate transformation angles
# (angles in Peiris & Tremaine 2003 eq 4)
cubeimg = pyfits.getdata(datadir + cuberoot + '_img.fits')
xaxis = np.arange(cubeimg.shape[0]) * 0.05
yaxis = np.arange(cubeimg.shape[1]) * 0.05
# original angles
Lorg = -42.8
Iorg = 54.1
Aorg = -34.5
# not changing CPA
CPA = -56.
# angle step size, in degrees
dAng = 3.
# number of steps away from the original angle in each direction (-/+)
# halfN = 1 gives 3 total steps, =2 gives 5 steps
halfN = 1.
N = (halfN * 2) + 1
Lgrid = np.arange(Lorg - (halfN * dAng), Lorg + (halfN * dAng) + 1, dAng)
Igrid = np.arange(Iorg - (halfN * dAng), Iorg + (halfN * dAng) + 1, dAng)
Agrid = np.arange(Aorg - (halfN * dAng), Aorg + (halfN * dAng) + 1, dAng)
if not plotOnly:
# create the new folder
FORMAT = '%Y%m%d_%H-%M-%S'
now = datetime.datetime.now().strftime(FORMAT)
newfolder = modeldir + 'nonaligned_grid_rotate_' + now + '/'
os.mkdir(newfolder)
#newfolder='/Users/kel/Documents/Projects/M31/models/Peiris/2003/nonaligned_grid_rotate_20160919_17-09-05/'
for LL in Lgrid:
for II in Igrid:
for AA in Agrid:
testAng = [LL, II, AA, CPA]
modelConvertBin(testAngles=testAng,
l98bin=False,
verbose=False,
tess=True,
pathstem=newfolder)
modelCompRes(
inModel=newfolder +
'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat'
% (testAng[0], testAng[1], testAng[2], testAng[3]),
toPlot=False)
# plotting
py.close(2)
py.figure(2)
py.subplots_adjust(left=0.05, right=0.94, top=0.95)
nPlot = N**2
# flux plots
for AA in Agrid:
py.clf()
plLL = np.fliplr([Lgrid])[0]
pI, pL = np.meshgrid(Igrid, plLL)
pI = pI.flatten()
pL = pL.flatten()
for pp in np.arange(nPlot):
py.subplot(N, N, pp + 1)
#inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (pL[pp],pI[pp],AA,CPA)
if inFolder:
inRes = inFolder + 'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f_residuals.dat' % (
pL[pp], pI[pp], AA, CPA)
else:
inRes = newfolder + 'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f_residuals.dat' % (
pL[pp], pI[pp], AA, CPA)
res = ppxf_m31.modelFitResults(inRes)
py.imshow(np.rot90(py.ma.masked_where(cubeimg == 0., res.nstar.T),
3),
vmin=-0.25,
vmax=0.25,
extent=[xaxis[0], xaxis[-1], yaxis[0], yaxis[-1]])
pltitle = '$\\theta_l$ = %.1f, $\\theta_i$ = %.1f' % (pL[pp],
pI[pp])
py.title(pltitle)
py.xticks([])
py.yticks([])
cbar = py.colorbar(orientation='horizontal', ticks=[-.25, 0., .25])
clab = 'Flux residuals, $\\theta_a$ = %.1f' % (AA)
cbar.set_label(clab)
if inFolder:
figname = inFolder + 'residuals_flux_thetaA_%.1f.png' % (AA)
else:
figname = newfolder + 'residuals_flux_thetaA_%.1f.png' % (AA)
py.savefig(figname)
# velocity plots - can probably integrate with flux plotting
for AA in Agrid:
py.clf()
plLL = np.fliplr([Lgrid])[0]
pI, pL = np.meshgrid(Igrid, plLL)
pI = pI.flatten()
pL = pL.flatten()
for pp in np.arange(nPlot):
py.subplot(N, N, pp + 1)
#inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (pL[pp],pI[pp],AA,CPA)
if inFolder:
inRes = inFolder + 'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f_residuals.dat' % (
pL[pp], pI[pp], AA, CPA)
else:
inRes = newfolder + 'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f_residuals.dat' % (
pL[pp], pI[pp], AA, CPA)
res = ppxf_m31.modelFitResults(inRes)
py.imshow(np.rot90(
py.ma.masked_where(cubeimg == 0., res.velocity.T), 3),
vmin=-100.,
vmax=200.,
extent=[xaxis[0], xaxis[-1], yaxis[0], yaxis[-1]])
pltitle = '$\\theta_l$ = %.1f, $\\theta_i$ = %.1f' % (pL[pp],
pI[pp])
py.title(pltitle)
py.xticks([])
py.yticks([])
cbar = py.colorbar(orientation='horizontal', ticks=[-100., 0., 200.])
clab = 'Velocity residuals, $\\theta_a$ = %.1f' % (AA)
cbar.set_label(clab)
if inFolder:
figname = inFolder + 'residuals_velocity_thetaA_%.1f.png' % (AA)
else:
figname = newfolder + 'residuals_velocity_thetaA_%.1f.png' % (AA)
py.savefig(figname)
# sigma plots
for AA in Agrid:
py.clf()
plLL = np.fliplr([Lgrid])[0]
pI, pL = np.meshgrid(Igrid, plLL)
pI = pI.flatten()
pL = pL.flatten()
for pp in np.arange(nPlot):
py.subplot(N, N, pp + 1)
#inRes = newfolder+'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f.dat' % (pL[pp],pI[pp],AA,CPA)
if inFolder:
inRes = inFolder + 'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f_residuals.dat' % (
pL[pp], pI[pp], AA, CPA)
else:
inRes = newfolder + 'nonaligned_OSIRIScoords_fit_full_smooth_%.1f_%.1f_%.1f_%.1f_residuals.dat' % (
pL[pp], pI[pp], AA, CPA)
res = ppxf_m31.modelFitResults(inRes)
py.imshow(np.rot90(py.ma.masked_where(cubeimg == 0., res.sigma.T),
3),
vmin=-100.,
vmax=100.,
extent=[xaxis[0], xaxis[-1], yaxis[0], yaxis[-1]])
pltitle = '$\\theta_l$ = %.1f, $\\theta_i$ = %.1f' % (pL[pp],
pI[pp])
py.title(pltitle)
py.xticks([])
py.yticks([])
cbar = py.colorbar(orientation='horizontal', ticks=[-100., 0., 100.])
clab = 'Sigma residuals, $\\theta_a$ = %.1f' % (AA)
cbar.set_label(clab)
if inFolder:
figname = inFolder + 'residuals_sigma_thetaA_%.1f.png' % (AA)
else:
figname = newfolder + 'residuals_sigma_thetaA_%.1f.png' % (AA)
py.savefig(figname)
