def genPlot(path, teff, logg, metals, am, nm, cm):
# Get the model
mspec= ferre.interpolate(teff,logg,metals,am,nm,cm)
# Plot the model
splot.waveregions(mspec,
labelID='[N/M]=' + str(nm) + ', [C/M]=' + str(cm),
labelTeff=teff,
labellogg=logg,
labelmetals=metals,
labelafe=am)
# Format and save the file
fig = plot.gcf()
fig.set_size_inches(30.0, 15.0, forward=True)
plot.draw()
if not os.path.exists('model_plots/' + path):
os.makedirs('model_plots/' + path)
plot.savefig('model_plots/' + path + '/' +
str(teff) + '_' + str(logg) + '_'
+ str(metals) + '_' + str(am) + '_'
+ str(nm) + '_' + str(cm) + '.png',
format='png', dpi=300)
plot.clf()
plot.close('all');
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
print(nan_ranges) specChunk = spec[0][nan_ranges[0][0]:nan_ranges[0][1]] errChunk = err[0][nan_ranges[0][0]:nan_ranges[0][1]]''' aspec= apread.apStar(locationID, apogeeID, ext=1, header=False)[1] aspecerr= apread.apStar(locationID, apogeeID, ext=2, header=False)[1] # Input needs to be (nspec,nwave) aspec= np.reshape(aspec,(1,len(aspec))) aspecerr= np.reshape(aspecerr,(1,len(aspecerr))) # Fit the continuum from apogee.spec import continuum cont= continuum.fit(aspec,aspecerr,type='aspcap') cspec= apread.aspcapStar(locationID, apogeeID,ext=1,header=False) import apogee.spec.plot as splot splot.waveregions(aspec[0]/cont[0]) splot.waveregions(cspec,overplot=True) '''params = ferre.fit(locationID, apogeeID, teff=teff1, fixteff=True, logg=logg, fixlogg=True, metals=metals, fixmetals=False, am=am, fixam=False, nm=nm, fixnm=False, cm=cm, fixcm=False, verbose=True) ''' '''mspec1= ferre.interpolate(params[0][1],params[0][2],params[0][3],params[0][4],params[0][5],params[0][6]) splot.waveregions(locationID, apogeeID) splot.waveregions(mspec1, overplot=True)'''
# I forget constantly...
import sys
print(sys.version)
# This is for VS code only.
import vsEnvironSetup
vsEnvironSetup.setVariables()
import apogee.tools.read as apread
import apogee.spec.plot as splot
from matplotlib.pyplot import draw, show
data = apread.rcsample()
indx= data['SNR'] > 200.
data= data[indx]
splot.waveregions(data[3513]['LOCATION_ID'],data[3513]['APOGEE_ID'],ext=1,
labelID=data[3513]['APOGEE_ID'],
labelTeff=data[3513]['TEFF'],
labellogg=data[3513]['LOGG'],
labelmetals=data[3513]['METALS'],
labelafe=data[3513]['ALPHAFE'])
draw()
show()
# I forget constantly... import sys print(sys.version) # This is for VS code only. import vsEnvironSetup vsEnvironSetup.setVariables() import apogee.tools.read as apread import apogee.spec.plot as splot import matplotlib.pyplot as plt locationID = 4611 apogeeID = '2M05350392-0529033' # spec, hdr= apread.apStar(locationID,apogeeID,ext=2) # print(spec.shape) # print(list(spec[0])) splot.waveregions(locationID, apogeeID) # plt.plot(spec[0]) fig = plt.gcf() fig.set_size_inches(30.0, 15.0, forward=True) plt.draw() plt.show()
