def windows(*args,**kwargs):
"""
NAME:
windows
PURPOSE:
plot the spectral windows for a given element
INPUT:
Either:
(a) wavelength, spectrum (\AA,spectrum units)
(b) spectrum (assumed on standard APOGEE re-sampled wavelength grid)
(c) location ID, APOGEE ID (default loads aspcapStar, loads extension ext(=1); apStar=True loads apStar spectrum)
+element string (e.g., 'Al'); Adding 1 and 2 splits the windows into two
KEYWORDS:
plot_weights= (False) if True, also plot the weights for the windows (assumes that the spectrum is on the apStarWavegrid)
markLines= mark the location of 'lines' (see apogee.spec.window.lines)
apogee.spec.plot.waveregions keywords
OUTPUT:
plot to output
The final axes allow one to put additional labels on the plot, e.g., for adding the APOGEE ID:
bovy_plot.bovy_text(r'$\mathrm{%s}$' % '2M02420597+0837017',top_left=True)
Note that an ID (e.g., the apogee ID) and Teff, logg, metallicity, and alpha-enhancement labels can be added using the keywords label* above
HISTORY:
2015-01-26 - Written (based on older code) - Bovy (IAS)
"""
pad= kwargs.pop('pad',3)
try:
si,ei= apwindow.waveregions(args[2],pad=pad,asIndex=True)
except IOError:
try:
si, ei= apwindow.waveregions(args[2][:-1],pad=pad,asIndex=True)
except IOError:
raise IOError("Windows for element %s could not be loaded, please specify an existing APOGEE element" % ((args[2].lower().capitalize())))
if args[2][-1] == '1':
si= si[:len(si)//2]
ei= ei[:len(ei)//2]
else:
si= si[len(si)//2:]
ei= ei[len(ei)//2:]
# Remove the number from the element
newargs= (args[0],args[1],args[2][:-1])
for ii in range(len(args)-3):
newargs= newargs+(args[ii+3],)
args= newargs
# Also get the number and total width of all of the windows
dlam= apwindow.total_dlambda(args[2],pad=pad)
numw= apwindow.num(args[2])
# Set spacing between windows
if numw > 20:
kwargs['skipdx']= 0.003
kwargs['_noskipdiags']= True
elif numw > 15:
kwargs['skipdx']= 0.01
# Set initial space to zero
kwargs['_startendskip']= 0
# Set initial figure width
if not kwargs.get('overplot',False) and not 'fig_width' in kwargs:
if dlam > 150.:
kwargs['fig_width']= 8.4
else:
kwargs['fig_width']= 4.2
# Don't tick x
kwargs['_noxticks']= True
# Label the largest wavelength in angstrom
kwargs['_labelwav']= True
# Don't label the lines unless explicitly asked for
kwargs['labelLines']= kwargs.get('labelLines',False)
# Plot the weights as well
if kwargs.pop('plot_weights',False):
kwargs['_plotw']= apwindow.read(args[2],apStarWavegrid=True)
if kwargs.get('apStar',False):
kwargs['yrange']= kwargs.get('yrange',
[0.,1.1*numpy.nanmax(args[1])])
else:
kwargs['yrange']= kwargs.get('yrange',[0.,1.2])
# mark the 'lines'
markLines= kwargs.get('markLines',not 'overplot' in kwargs)
if markLines and not '_markwav' in kwargs:
kwargs['_markwav']= apwindow.lines(args[2])
# Plot
waveregions(args[0],args[1],startindxs=si,endindxs=ei,
*args[3:],**kwargs)
# Add label
bovy_plot.bovy_text(r'$\mathrm{%s}$' % ((args[2].lower().capitalize())),
top_left=True,fontsize=10,backgroundcolor='w')
return None
def windows(*args, **kwargs):
"""
NAME:
windows
PURPOSE:
plot the spectral windows for a given element
INPUT:
Either:
(a) wavelength, spectrum (\AA,spectrum units)
(b) spectrum (assumed on standard APOGEE re-sampled wavelength grid)
(c) location ID, APOGEE ID (default loads aspcapStar, loads extension ext(=1); apStar=True loads apStar spectrum)
+element string (e.g., 'Al'); Adding 1 and 2 splits the windows into two
KEYWORDS:
plot_weights= (False) if True, also plot the weights for the windows (assumes that the spectrum is on the apStarWavegrid)
markLines= mark the location of 'lines' (see apogee.spec.window.lines)
apogee.spec.plot.waveregions keywords
OUTPUT:
plot to output
The final axes allow one to put additional labels on the plot, e.g., for adding the APOGEE ID:
bovy_plot.bovy_text(r'$\mathrm{%s}$' % '2M02420597+0837017',top_left=True)
Note that an ID (e.g., the apogee ID) and Teff, logg, metallicity, and alpha-enhancement labels can be added using the keywords label* above
HISTORY:
2015-01-26 - Written (based on older code) - Bovy (IAS)
"""
pad = kwargs.pop('pad', 3)
try:
si, ei = apwindow.waveregions(args[2], pad=pad, asIndex=True)
except IOError:
try:
si, ei = apwindow.waveregions(args[2][:-1], pad=pad, asIndex=True)
except IOError:
raise IOError(
"Windows for element %s could not be loaded, please specify an existing APOGEE element"
% ((args[2].lower().capitalize())))
if args[2][-1] == '1':
si = si[:len(si) // 2]
ei = ei[:len(ei) // 2]
else:
si = si[len(si) // 2:]
ei = ei[len(ei) // 2:]
# Remove the number from the element
newargs = (args[0], args[1], args[2][:-1])
for ii in range(len(args) - 3):
newargs = newargs + (args[ii + 3], )
args = newargs
# Also get the number and total width of all of the windows
dlam = apwindow.total_dlambda(args[2], pad=pad)
numw = apwindow.num(args[2])
# Set spacing between windows
if numw > 20:
kwargs['skipdx'] = 0.003
kwargs['_noskipdiags'] = True
elif numw > 15:
kwargs['skipdx'] = 0.01
# Set initial space to zero
kwargs['_startendskip'] = 0
# Set initial figure width
if not kwargs.get('overplot', False) and not 'fig_width' in kwargs:
if dlam > 150.:
kwargs['fig_width'] = 8.4
else:
kwargs['fig_width'] = 4.2
# Don't tick x
kwargs['_noxticks'] = True
# Label the largest wavelength in angstrom
kwargs['_labelwav'] = True
# Don't label the lines unless explicitly asked for
kwargs['labelLines'] = kwargs.get('labelLines', False)
# Plot the weights as well
if kwargs.pop('plot_weights', False):
kwargs['_plotw'] = apwindow.read(args[2], apStarWavegrid=True)
if kwargs.get('apStar', False):
kwargs['yrange'] = kwargs.get('yrange',
[0., 1.1 * numpy.nanmax(args[1])])
else:
kwargs['yrange'] = kwargs.get('yrange', [0., 1.2])
# mark the 'lines'
markLines = kwargs.get('markLines', not 'overplot' in kwargs)
if markLines and not '_markwav' in kwargs:
kwargs['_markwav'] = apwindow.lines(args[2])
# Plot
waveregions(args[0],
args[1],
startindxs=si,
endindxs=ei,
*args[3:],
**kwargs)
# Add label
bovy_plot.bovy_text(r'$\mathrm{%s}$' % ((args[2].lower().capitalize())),
top_left=True,
fontsize=10,
backgroundcolor='w')
return None
def plot_afe_spectra(savename,plotname):
# Load the data
data= define_rcsample.get_rcsample()
data= data[data['SNR'] > 200.]
fehindx= (data['FE_H'] <= -0.35)*(data['FE_H'] > -0.45)
fehdata= data[fehindx]
# First compute the residuals and do the EM-PCA smoothing
if not os.path.exists(savename):
nspec= len(fehdata)
spec= numpy.zeros((nspec,7214))
specerr= numpy.zeros((nspec,7214))
for ii in range(nspec):
sys.stdout.write('\r'+"Loading spectrum %i / %i ...\r" % (ii+1,nspec))
sys.stdout.flush()
spec[ii]= apread.aspcapStar(fehdata['LOCATION_ID'][ii],
fehdata['APOGEE_ID'][ii],
ext=1,header=False,aspcapWavegrid=True)
specerr[ii]= apread.aspcapStar(fehdata['LOCATION_ID'][ii],
fehdata['APOGEE_ID'][ii],
ext=2,header=False,
aspcapWavegrid=True)
teffs= fehdata['FPARAM'][:,paramIndx('teff')]
loggs= fehdata['FPARAM'][:,paramIndx('logg')]
metals= fehdata[define_rcsample._FEHTAG]
cf, s, r= apcannon.quadfit(spec,specerr,
teffs-4800.,loggs-2.85,metals+0.3,
return_residuals=True)
pr= numpy.zeros_like(r)
# Deal w/ bad data
_MAXERR= 0.02
npca= 8
pca_input= r
pca_weights= (1./specerr**2.)
pca_weights[pca_weights < 1./_MAXERR**2.]= 0.
nanIndx= numpy.isnan(pca_input) + numpy.isnan(pca_weights)
pca_weights[nanIndx]= 0.
pca_input[nanIndx]= 0.
# Run EM-PCA
m= empca.empca(pca_input,pca_weights,nvec=npca,niter=25)#,silent=False)
for jj in range(nspec):
for kk in range(npca):
pr[jj]+= m.coeff[jj,kk]*m.eigvec[kk]
save_pickles(savename,pr,r,cf)
else:
with open(savename,'rb') as savefile:
pr= pickle.load(savefile)
# Now plot the various elements
colormap= cm.seismic
colorFunc= lambda afe: afe/0.25
widths= [3.5,2.]
yranges= [[-0.05,0.02],[-0.03,0.01]]
for ee, elem in enumerate(['S','Ca1']):
for ii in range(5):
tindx= (fehdata[define_rcsample._AFETAG] > ii*0.05-0.025)\
*(fehdata[define_rcsample._AFETAG] <= (ii+1)*0.05-0.025)
args= (apstack.median(pr[tindx][:12]),elem,)
kwargs= {'markLines':ii==4,
'yrange':yranges[ee],
'ylabel':'',
'cleanZero':False,
'zorder':int(numpy.floor(numpy.random.uniform()*5)),
'color':colormap(colorFunc(ii*0.05)),
'overplot':ii>0,
'fig_width':widths[ee]}
if ii>0: kwargs.pop('fig_width')
splot.windows(*args,**kwargs)
bovy_plot.bovy_end_print(plotname.replace('ELEM',
elem.lower().capitalize()))
# Also do Mg
for ii in range(5):
tindx= (fehdata[define_rcsample._AFETAG] > ii*0.05-0.025)\
*(fehdata[define_rcsample._AFETAG] <= (ii+1)*0.05-0.025)
args= (apstack.median(pr[tindx][:12]),)
kwargs={'startindxs':[3012,3120,3990],
'endindxs':[3083,3158,4012],
'yrange':[-0.05,0.02],
'ylabel':'',
'cleanZero':False,
'_markwav':[15745.017,15753.189,15770.055,15958.836],
'zorder':int(numpy.floor(numpy.random.uniform()*5)),
'color':colormap(colorFunc(ii*0.05)),
'overplot':ii>0,
'fig_width':4.5,
'markLines':True}
if ii>0: kwargs.pop('fig_width')
if ii != 4:
kwargs.pop('_markwav')
kwargs.pop('markLines')
kwargs['_startendskip']= 0
kwargs['_noxticks']= True
kwargs['_labelwav']= True
splot.waveregions(*args,**kwargs)
bovy_plot.bovy_text(r'$\mathrm{Mg}$',
top_left=True,fontsize=10,backgroundcolor='w')
bovy_plot.bovy_end_print(plotname.replace('ELEM','Mg'))
# Also do Si
for ii in range(5):
tindx= (fehdata[define_rcsample._AFETAG] > ii*0.05-0.025)\
*(fehdata[define_rcsample._AFETAG] <= (ii+1)*0.05-0.025)
args= (apstack.median(pr[tindx][:12]),)
kwargs={'startindxs':[4469, 4624,5171, 7205, 7843],
'endindxs':[4488, 4644,5182, 7243, 7871],
'yrange':[-0.05,0.02],
'ylabel':'',
'cleanZero':False,
'_markwav':apwindow.lines('Si'),
'zorder':int(numpy.floor(numpy.random.uniform()*5)),
'color':colormap(colorFunc(ii*0.05)),
'overplot':ii>0,
'fig_width':6.,
'markLines':True}
if ii>0: kwargs.pop('fig_width')
if ii != 4:
kwargs.pop('_markwav')
kwargs.pop('markLines')
kwargs['_startendskip']= 0
kwargs['_noxticks']= True
kwargs['_labelwav']= True
splot.waveregions(*args,**kwargs)
bovy_plot.bovy_text(r'$\mathrm{Si}$',
top_left=True,fontsize=10,backgroundcolor='w')
bovy_plot.bovy_end_print(plotname.replace('ELEM','Si2'))
# Also do Oxygen
for ii in range(5):
tindx= (fehdata[define_rcsample._AFETAG] > ii*0.05-0.025)\
*(fehdata[define_rcsample._AFETAG] <= (ii+1)*0.05-0.025)
args= (apstack.median(pr[tindx][:12]),)
kwargs={'startlams':[15558,16242,16536,16720],
'endlams':[15566,16250,16544,16728],
'yrange':[-0.05,0.02],
'ylabel':'',
'cleanZero':False,
'_markwav':[15562,16246,16539,16723.5],
'zorder':int(numpy.floor(numpy.random.uniform()*5)),
'color':colormap(colorFunc(ii*0.05)),
'overplot':ii>0,
'fig_width':5.,
'markLines':True}
if ii>0: kwargs.pop('fig_width')
if ii != 4:
kwargs.pop('_markwav')
kwargs.pop('markLines')
kwargs['_startendskip']= 0
kwargs['_noxticks']= True
kwargs['_labelwav']= True
splot.waveregions(*args,**kwargs)
bovy_plot.bovy_text(r'$\mathrm{O}$',
top_left=True,fontsize=10,backgroundcolor='w')
bovy_plot.bovy_end_print(plotname.replace('ELEM','O'))
# Also do Ti
for ii in range(5):
tindx= (fehdata[define_rcsample._AFETAG] > ii*0.05-0.025)\
*(fehdata[define_rcsample._AFETAG] <= (ii+1)*0.05-0.025)
args= (apstack.median(pr[tindx][:12]),)
kwargs={'startindxs':[1116,2100,2899],
'endindxs':[1146,2124,2922],
'yrange':[-0.05,0.02],
'ylabel':'',
'cleanZero':False,
'_markwav':apwindow.lines('Ti'),
'zorder':int(numpy.floor(numpy.random.uniform()*5)),
'color':colormap(colorFunc(ii*0.05)),
'overplot':ii>0,
'fig_width':3.5,
'markLines':True}
if ii>0: kwargs.pop('fig_width')
if ii != 4:
kwargs.pop('_markwav')
kwargs.pop('markLines')
kwargs['_startendskip']= 0
kwargs['_noxticks']= True
kwargs['_labelwav']= True
splot.waveregions(*args,**kwargs)
bovy_plot.bovy_text(r'$\mathrm{Ti}$',
top_left=True,fontsize=10,backgroundcolor='w')
bovy_plot.bovy_end_print(plotname.replace('ELEM','Ti'))
return None
