def astroNN(dr=None):
"""
NAME:
astroNN
PURPOSE:
download the astroNN file
INPUT:
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2018-10-20 - Written - Bovy (UofT)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.astroNNPath(dr=dr)
if os.path.exists(filePath): return None
# Create the file path
if int(dr) == 14:
downloadPath= 'https://github.com/henrysky/astroNN_spectra_paper_figures/raw/master/astroNN_apogee_dr14_catalog.fits'
else:
downloadPath= filePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath,filePath,dr,verbose=True)
return None
def apogeePlate(dr=None):
"""
NAME:
apogeePlate
PURPOSE:
download the apogeePlate file
INPUT:
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2015-12-27 - Written - Bovy (UofT)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.apogeePlatePath(dr=dr)
if os.path.exists(filePath): return None
# Create the file path
if int(dr) < 16:
downloadPath= os.path.join(path._APOGEE_DATA,'dr%s' % dr,
'apogee','target',os.path.basename(filePath))\
.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
elif int(dr) >= 16: #change of location/format after DR16
downloadPath= filePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath,filePath,dr)
return None
def all_apStar(dr=None):
"""
NAME:
all_apStar
PURPOSE:
Convenience function to download all apStar files for a given DR
INPUT:
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2019-12-23 - Written - Bovy (UofT)
"""
from . import read as apread
if dr is None: dr= path._default_dr()
alldata= apread.allStar(raw=True)
for ii in range(len(alldata)):
try:
_= apread.apStar(alldata['LOCATION_ID'][ii] if int(dr) < 14
else alldata['FIELD'][ii],
alldata['APOGEE_ID'][ii],
telescope=alldata['TELESCOPE'][ii],dr=dr)
except:
print("Failed to download location {}, apogee_id {}, telescope {}"\
.format(alldata['LOCATION_ID'][ii] if int(dr) < 14
else alldata['FIELD'][ii],
alldata['APOGEE_ID'][ii],
alldata['TELESCOPE'][ii]))
return None
def apogeeObject(field_name, dr=None):
"""
NAME:
apogeeObject
PURPOSE:
download an apogeeObject file
INPUT:
field_name - name of the field
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2015-12-27 - Written - Bovy (UofT)
"""
if dr is None: dr = path._default_dr()
# First make sure the file doesn't exist
filePath = path.apogeeObjectPath(field_name, dr=dr)
if os.path.exists(filePath): return None
# Create the file path
downloadPath= os.path.join(path._APOGEE_DATA,'dr%s' % dr,
'apogee','target','apogeeObject',
os.path.basename(filePath))\
.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath, filePath, dr)
return None
def aspcapStar(loc_id,apogee_id,dr=None):
"""
NAME:
aspcapStar
PURPOSE:
download an aspcapStar file
INPUT:
loc_id - location ID
apogee_id - APOGEE ID of the star
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2014-11-25 - Written - Bovy (IAS)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.aspcapStarPath(loc_id,apogee_id,dr=dr)
if os.path.exists(filePath): return None
# Create the file path
downloadPath= filePath.replace(os.path.join(path._APOGEE_DATA,
'dr%s' % dr),
_base_url(dr=dr))
_download_file(downloadPath,filePath,dr)
return None
def allVisit(dr=None):
"""
NAME:
allVisit
PURPOSE:
download the allVisit file
INPUT:
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2014-11-26 - Written - Bovy (IAS)
2015-08-17 - Adjusted for new path (mv old to new) - Bovy (UofT)
"""
if dr is None: dr = path._default_dr()
# First make sure the file doesn't exist
filePath = path.allVisitPath(dr=dr)
if os.path.exists(filePath): return None
# Check whether we can find it in its old place
oldFilePath = path.allVisitPath(dr=dr, _old=True)
if os.path.exists(oldFilePath):
# mv to new place
try:
os.makedirs(os.path.dirname(filePath))
except OSError:
pass
shutil.move(oldFilePath, filePath)
return None
# Create the file path
downloadPath = filePath.replace(
os.path.join(path._APOGEE_DATA, _dr_string(dr)), _base_url(dr=dr))
_download_file(downloadPath, filePath, dr, verbose=True)
return None
def allVisit(dr=None):
"""
NAME:
allVisit
PURPOSE:
download the allVisit file
INPUT:
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2014-11-26 - Written - Bovy (IAS)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.allVisitPath(dr=dr)
if os.path.exists(filePath): return None
# Create the file path, hacked from aspcapStar path
aspPath= path.aspcapStarPath(4140,'dum',dr=dr)
downloadPath= aspPath.replace(os.path.join(path._APOGEE_DATA,
'dr%s' % dr),
_base_url(dr=dr))
head, tail= os.path.split(downloadPath) #strips off filename
downloadPath, tail= os.path.split(head) #strips off location_id
downloadPath= os.path.join(downloadPath,os.path.basename(filePath))
_download_file(downloadPath,filePath,dr,verbose=True)
return None
def apStar(loc_id,apogee_id,dr=None):
"""
NAME:
apStar
PURPOSE:
download an apStar file
INPUT:
loc_id - location ID
apogee_id - APOGEE ID of the star
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2015-01-13 - Written - Bovy (IAS)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.apStarPath(loc_id,apogee_id,dr=dr)
if os.path.exists(filePath): return None
# Create the file path
downloadPath= filePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath,filePath,dr)
return None
def apogeeObject(field_name,dr=None):
"""
NAME:
apogeeObject
PURPOSE:
download an apogeeObject file
INPUT:
field_name - name of the field
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2015-12-27 - Written - Bovy (UofT)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.apogeeObjectPath(field_name,dr=dr)
if os.path.exists(filePath): return None
# Create the file path
downloadPath= os.path.join(path._APOGEE_DATA,'dr%s' % dr,
'apogee','target','apogeeObject',
os.path.basename(filePath))\
.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath,filePath,dr)
return None
def allVisit(dr=None):
"""
NAME:
allVisit
PURPOSE:
download the allVisit file
INPUT:
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2014-11-26 - Written - Bovy (IAS)
2015-08-17 - Adjusted for new path (mv old to new) - Bovy (UofT)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.allVisitPath(dr=dr)
if os.path.exists(filePath): return None
# Check whether we can find it in its old place
oldFilePath= path.allVisitPath(dr=dr,_old=True)
if os.path.exists(oldFilePath):
# mv to new place
try:
os.makedirs(os.path.dirname(filePath))
except OSError: pass
shutil.move(oldFilePath,filePath)
return None
# Create the file path
downloadPath= filePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath,filePath,dr,verbose=True)
return None
def apStar(loc_id,apogee_id,telescope='apo25m',dr=None):
"""
NAME:
apStar
PURPOSE:
download an apStar file
INPUT:
loc_id - location ID
apogee_id - APOGEE ID of the star
telescope= telescope used ('apo25m' [default], 'apo1m', 'lco25m')
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2015-01-13 - Written - Bovy (IAS)
2018-01-22 - Edited for new post-DR14 path structure - Bovy (UofT)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.apStarPath(loc_id,apogee_id,dr=dr,telescope=telescope)
if os.path.exists(filePath): return None
# Create the file path
downloadPath= filePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath,filePath,dr)
return None
def apVisit(plateid, mjd, fiberid, telescope='apo25m', dr=None):
"""
NAME: apVisit
PURPOSE: download a single apVisit file
INPUT:
plateid = 4-digit plate ID
mjd = 5-digit MJD
fiberid = 3-digit fiber ID
telescope= ('apo25m') Telescope at which this plate has been observed ('apo25m' for standard APOGEE-N, 'apo1m' for the 1m telescope)
dr = return the path corresponding to this data release (general default)
OUTPUT: (none; just downloads)
HISTORY: 2016-11 - Meredith Rawls
2019-01-28 - Added telescope keyword, clarified that it's plateid that's needed - Bovy (UofT)
TODO: automatically find all apVisit files for a given apogee ID and download them
"""
if dr is None:
dr = path._default_dr()
# First make sure the file doesn't exist
filePath = path.apVisitPath(plateid, mjd, fiberid,
telescope=telescope,dr=dr)
if os.path.exists(filePath):
return None
# Create the file path
downloadPath = filePath.replace(os.path.join(path._APOGEE_DATA, _dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath, filePath, dr)
return None
def ferreModelLibrary(lib='GK',pca=True,sixd=True,unf=False,dr=None,
convertToBin=True,spider=False):
"""
NAME:
ferreModelLibrary
PURPOSE:
download a FERRE model library
INPUT:
lib= ('GK') spectral library
dr= return the path corresponding to this data release
pca= (True) if True, download the PCA compressed library
sixd= (True) if True, download the 6D library (w/o vmicro)
unf= (False) if True, download the binary library (otherwise ascii)
convertToBin= (True) if True and not unf, convert the ascii file to binary using ferre's ascii2bin (which has to be on the path)
spider= (False) if True, run wget as a spider (doesn't download)
OUTPUT:
(none; just downloads; also downloads the corresponding .hdr)
HISTORY:
2015-01-21 - Written - Bovy (IAS)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.ferreModelLibraryPath(lib=lib,dr=dr,pca=pca,
sixd=sixd,unf=unf)
if not os.path.exists(filePath):
# Create the file path
downloadPath= filePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath,filePath,dr,verbose=True,spider=spider)
if convertToBin and not spider:
sys.stdout.write('\r'+"Converting ascii model library to binary (can take a few minutes) ...\r")
sys.stdout.flush()
try:
p= subprocess.Popen(['ascii2bin'],stdout=subprocess.PIPE,
stdin=subprocess.PIPE,
stderr=subprocess.PIPE,
cwd=os.path.dirname(filePath))
p.stdin.write((os.path.basename(filePath)+'\n')\
.encode('utf-8'))
p.stdin.write(b'unf\n')
stdout, stderr= p.communicate()
except subprocess.CalledProcessError:
print("Conversion of %s to binary failed ..." % (os.path.basename(filePath)))
sys.stdout.write('\r'+_ERASESTR+'\r')
sys.stdout.flush()
# Also download the header
if unf:
headerFilePath= filePath.replace('.unf','.hdr')
else:
headerFilePath= filePath.replace('.dat','.hdr')
if os.path.exists(headerFilePath): return None
headerDownloadPath= headerFilePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(headerDownloadPath,headerFilePath,dr,verbose=True,
spider=spider)
return None
def ferreModelLibrary(lib='GK',pca=True,sixd=True,unf=False,dr=None,
convertToBin=True,spider=False):
"""
NAME:
ferreModelLibrary
PURPOSE:
download a FERRE model library
INPUT:
lib= ('GK') spectral library
dr= return the path corresponding to this data release
pca= (True) if True, download the PCA compressed library
sixd= (True) if True, download the 6D library (w/o vmicro)
unf= (False) if True, download the binary library (otherwise ascii)
convertToBin= (True) if True and not unf, convert the ascii file to binary using ferre's ascii2bin (which has to be on the path)
spider= (False) if True, run wget as a spider (doesn't download)
OUTPUT:
(none; just downloads; also downloads the corresponding .hdr)
HISTORY:
2015-01-21 - Written - Bovy (IAS)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.ferreModelLibraryPath(lib=lib,dr=dr,pca=pca,
sixd=sixd,unf=unf)
if not os.path.exists(filePath):
# Create the file path
downloadPath= filePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath,filePath,dr,verbose=True,spider=spider)
if convertToBin and not spider:
sys.stdout.write('\r'+"Converting ascii model library to binary (can take a few minutes) ...\r")
sys.stdout.flush()
try:
p= subprocess.Popen(['ascii2bin'],stdout=subprocess.PIPE,
stdin=subprocess.PIPE,
stderr=subprocess.PIPE,
cwd=os.path.dirname(filePath))
p.stdin.write((os.path.basename(filePath)+'\n')\
.encode('utf-8'))
p.stdin.write(b'unf\n')
stdout, stderr= p.communicate()
except subprocess.CalledProcessError:
print("Conversion of %s to binary failed ..." % (os.path.basename(filePath)))
sys.stdout.write('\r'+_ERASESTR+'\r')
sys.stdout.flush()
# Also download the header
if unf:
headerFilePath= filePath.replace('.unf','.hdr')
else:
headerFilePath= filePath.replace('.dat','.hdr')
if os.path.exists(headerFilePath): return None
headerDownloadPath= headerFilePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(headerDownloadPath,headerFilePath,dr,verbose=True,
spider=spider)
return None
def _load_precomp(dr=None,fiber='combo',sparse=True):
"""Load a precomputed LSF"""
if dr is None: dr= appath._default_dr()
fileDir= os.path.dirname(appath.apLSFPath('a',dr=dr))
filePath= os.path.join(fileDir,'apogee-lsf-dr%s-%s.fits' % (dr,fiber))
# Download the file if necessary
if not os.path.exists(filePath):
dlink= \
filePath.replace(fileDir,'https://zenodo.org/record/16147/files')
_download_file(dlink,filePath,dr)
x= numpy.linspace(-7.,7.,43)
elsf= fitsio.read(filePath)
if sparse:
return (x,sparsify(elsf))
else:
return (x,elsf)
def path(elem,dr=None):
"""
NAME:
path
PURPOSE:
return the path of a window file
INPUT:
elem - element
dr= return the path corresponding to this data release
OUTPUT:
path string
HISTORY:
2015-02-27 - Written - Bovy (IAS)
"""
if dr is None: dr= _default_dr()
return os.path.join(os.path.dirname(os.path.realpath(__file__)),
'filter/%s/%s.filt' \
% (_dr_string(dr),
(elem.lower().capitalize())))
def path(elem, dr=None):
"""
NAME:
path
PURPOSE:
return the path of a window file
INPUT:
elem - element
dr= return the path corresponding to this data release
OUTPUT:
path string
HISTORY:
2015-02-27 - Written - Bovy (IAS)
"""
if dr is None: dr = _default_dr()
return os.path.join(os.path.dirname(os.path.realpath(__file__)),
'filter/%s/%s.filt' \
% (_dr_string(dr),
(elem.lower().capitalize())))
def _load_precomp(dr=None,fiber='combo',sparse=True):
"""Load a precomputed LSF"""
if dr is None: dr= appath._default_dr()
if dr is 'current':
warnings.warn("Preloaded LSFs for current DR not yet available, falling back on DR12 files")
dr= '12'
fileDir= os.path.dirname(appath.apLSFPath('a',dr=dr))
filePath= os.path.join(fileDir,'apogee-lsf-dr%s-%s.fits' % (dr,fiber))
# Download the file if necessary
if not os.path.exists(filePath):
dlink= \
filePath.replace(fileDir,'https://zenodo.org/record/16147/files')
_download_file(dlink,filePath,dr)
x= numpy.linspace(-7.,7.,43)
elsf= fitsio.read(filePath)
if sparse:
return (x,sparsify(elsf))
else:
return (x,elsf)
def astroNNAges(dr=None):
"""
NAME:
astroNNAges
PURPOSE:
download the astroNN ages file
INPUT:
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2018-02-16 - Written - Bovy (UofT)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.astroNNAgesPath(dr=dr)
if os.path.exists(filePath): return None
# Create the file path
downloadPath= 'http://www.astro.ljmu.ac.uk/~astjmack/APOGEEGaiaAges/'\
'astroNNBayes_ages_goodDR14.fits'
_download_file(downloadPath,filePath,dr,verbose=True)
return None
def astroNNDistances(dr=None):
"""
NAME:
astroNNDistances
PURPOSE:
download the astroNN distances file
INPUT:
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2018-02-15 - Written - Bovy (UofT)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.astroNNDistancesPath(dr=dr)
if os.path.exists(filePath): return None
# Create the file path
downloadPath= 'https://github.com/henrysky/astroNN_gaia_dr2_paper/raw/'\
'master/apogee_dr14_nn_dist.fits'
_download_file(downloadPath,filePath,dr,verbose=True)
return None
def rcsample(dr=None):
"""
NAME:
rcsample
PURPOSE:
download the rcsample file
INPUT:
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2014-11-26 - Written - Bovy (IAS)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.allVisitPath(dr=dr)
if os.path.exists(filePath): return None
# Create the file path
downloadPath=\
os.path.join(_base_url(dr=dr,rc=True),
'apogee/vac/apogee-rc/cat/apogee-rc-DR%s.fits' % dr)
_download_file(downloadPath,filePath,dr)
return None
def apLSF(chip, dr=None):
"""
NAME:
apLSF
PURPOSE:
download an apLSF file
INPUT:
chip - chip 'a', 'b', or 'c'
dr= return the path corresponding to this data release
OUTPUT:
(none; just downloads)
HISTORY:
2015-03-12 - Written - Bovy (IAS)
"""
if dr is None: dr = path._default_dr()
# First make sure the file doesn't exist
filePath = path.apLSFPath(chip, dr=dr)
if os.path.exists(filePath): return None
# Create the file path
downloadPath = filePath.replace(
os.path.join(path._APOGEE_DATA, _dr_string(dr)), _base_url(dr=dr))
_download_file(downloadPath, filePath, dr, verbose=True)
return None
def rcsample(dr=None):
"""
NAME:
rcsample
PURPOSE:
download the rcsample file
INPUT:
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2014-11-26 - Written - Bovy (IAS)
"""
if dr is None: dr = path._default_dr()
# First make sure the file doesn't exist
filePath = path.rcsamplePath(dr=dr)
if os.path.exists(filePath): return None
# Check whether we can find it in its old place
oldFilePath = path.rcsamplePath(dr=dr, _old=True)
if os.path.exists(oldFilePath):
# mv to new place
try:
os.makedirs(os.path.dirname(filePath))
except OSError:
pass
shutil.move(oldFilePath, filePath)
return None
# Create the file path
if dr == '11': # special case, bc in DR12 SAS
downloadPath = filePath.replace(
os.path.join(path._APOGEE_DATA, _dr_string('12')),
_base_url(dr='12'))
else:
downloadPath = filePath.replace(
os.path.join(path._APOGEE_DATA, _dr_string(dr)), _base_url(dr=dr))
_download_file(downloadPath, filePath, dr, verbose=False)
return None
def rcsample(dr=None):
"""
NAME:
rcsample
PURPOSE:
download the rcsample file
INPUT:
dr= return the path corresponding to this data release (general default)
OUTPUT:
(none; just downloads)
HISTORY:
2014-11-26 - Written - Bovy (IAS)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.rcsamplePath(dr=dr)
if os.path.exists(filePath): return None
# Check whether we can find it in its old place
oldFilePath= path.rcsamplePath(dr=dr,_old=True)
if os.path.exists(oldFilePath):
# mv to new place
try:
os.makedirs(os.path.dirname(filePath))
except OSError: pass
shutil.move(oldFilePath,filePath)
return None
# Create the file path
if dr == '11': # special case, bc in DR12 SAS
downloadPath= filePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string('12')),
_base_url(dr='12'))
else:
downloadPath= filePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath,filePath,dr,verbose=False)
return None
def apLSF(chip,dr=None):
"""
NAME:
apLSF
PURPOSE:
download an apLSF file
INPUT:
chip - chip 'a', 'b', or 'c'
dr= return the path corresponding to this data release
OUTPUT:
(none; just downloads)
HISTORY:
2015-03-12 - Written - Bovy (IAS)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.apLSFPath(chip,dr=dr)
if os.path.exists(filePath): return None
# Create the file path
downloadPath= filePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath,filePath,dr,verbose=True)
return None
def apVisit(loc_id, mjd, fiberid, dr=None):
"""
NAME: apVisit
PURPOSE: download a single apVisit file
INPUT:
loc_id = 4-digit location ID (field for 1m targets)
mjd = 5-digit MJD
fiberid = 3-digit fiber ID
dr = return the path corresponding to this data release (general default)
OUTPUT: (none; just downloads)
HISTORY: 2016-11 - Meredith Rawls
TODO: automatically find all apVisit files for a given apogee ID and download them
"""
if dr is None:
dr = path._default_dr()
# First make sure the file doesn't exist
filePath = path.apVisitPath(loc_id, mjd, fiberid, dr=dr)
if os.path.exists(filePath):
return None
# Create the file path
downloadPath = filePath.replace(
os.path.join(path._APOGEE_DATA, _dr_string(dr)), _base_url(dr=dr))
_download_file(downloadPath, filePath, dr)
return None
def apVisit(loc_id, mjd, fiberid, dr=None):
"""
NAME: apVisit
PURPOSE: download a single apVisit file
INPUT:
loc_id = 4-digit location ID (field for 1m targets)
mjd = 5-digit MJD
fiberid = 3-digit fiber ID
dr = return the path corresponding to this data release (general default)
OUTPUT: (none; just downloads)
HISTORY: 2016-11 - Meredith Rawls
TODO: automatically find all apVisit files for a given apogee ID and download them
"""
if dr is None:
dr = path._default_dr()
# First make sure the file doesn't exist
filePath = path.apVisitPath(loc_id, mjd, fiberid, dr=dr)
if os.path.exists(filePath):
return None
# Create the file path
downloadPath = filePath.replace(os.path.join(path._APOGEE_DATA, _dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath, filePath, dr)
return None
2018-02-05 - Updated to account for changing detector ranges - Price-Jones (UofT)
"""
filePath= path.modelSpecPath(lib=lib,teff=teff,logg=logg,metals=metals,
cfe=cfe,nfe=nfe,afe=afe,vmicro=vmicro,dr=dr)
if not os.path.exists(filePath):
download.modelSpec(lib=lib,teff=teff,logg=logg,metals=metals,
cfe=cfe,nfe=nfe,afe=afe,vmicro=vmicro,dr=dr,
**kwargs)
# Need to use astropy's fits reader, bc the file has issues
import astropy.io.fits as apyfits
from astropy.utils.exceptions import AstropyUserWarning
import warnings
warnings.filterwarnings('ignore',category=AstropyUserWarning)
hdulist= apyfits.open(filePath)
# Find index of nearest grid point in Teff, logg, and metals
if dr is None: dr= path._default_dr()
if dr == '12':
logggrid= numpy.linspace(0.,5.,11)
metalsgrid= numpy.linspace(-2.5,0.5,7)
if lib.lower() == 'gk':
teffgrid= numpy.linspace(3500.,6000.,11)
teffIndx= numpy.argmin(numpy.fabs(teff-teffgrid))
elif lib.lower() == 'f':
teffgrid= numpy.linspace(5500.,8000.,11)
teffIndx= numpy.argmin(numpy.fabs(teff-teffgrid))
loggIndx= numpy.argmin(numpy.fabs(logg-logggrid))
metalsIndx= numpy.argmin(numpy.fabs(metals-metalsgrid))
if header and not ext == 234:
return (hdulist[ext].data[metalsIndx,loggIndx,teffIndx],
hdulist[ext].header)
elif not ext == 234:
from sewingmachine import equivalentwidths, linelist
import numpy as np
from astropy.io import fits
import apogee.tools.read as apread
import apogee.tools.path as appath
import apogee.spec.plot as splot
from tqdm import tqdm
import os
_DEFAULT_DR = appath._default_dr()
def measure_apogee(allStar, linelist_obj, output_fits=False, *args, **kwargs):
if isinstance(linelist_obj, str):
linelist_obj = linelist.Linelist(linelist_obj)
loc_ids, apogee_ids = make_speclist(allStar)
lams = splot.apStarWavegrid()
ews = np.empty([np.shape(allStar)[0], np.shape(linelist_obj.labels)[0]])
errs = np.empty([np.shape(allStar)[0], np.shape(linelist_obj.labels)[0]])
try:
dr = int(_DEFAULT_DR)
except ValueError:
dr = 16
if dr <= 13:
lockey = 'LOCATION_ID'
else:
lockey = 'FIELD'
for i in tqdm(range(len(apogee_ids))):
try:
try:
loc, id = str(allStar[lockey][i],
def modelSpec(lib='GK',teff=4500,logg=2.5,metals=0.,
cfe=0.,nfe=0.,afe=0.,vmicro=2.,
dr=None,rmHDU1=True,rmHDU2=True):
"""
NAME:
modelSpec
PURPOSE:
download a model spectrum file
INPUT:
lib= ('GK') spectral library
teff= (4500) grid-point Teff
logg= (2.5) grid-point logg
metals= (0.) grid-point metallicity
cfe= (0.) grid-point carbon-enhancement
nfe= (0.) grid-point nitrogen-enhancement
afe= (0.) grid-point alpha-enhancement
vmicro= (2.) grid-point microturbulence
dr= return the path corresponding to this data release
rmHUD1= (True) if True, rm the first (v. large) HDU with the high-resolution model spectrum
rmHDU2= (True) if True, rm the second (quite large) HDU with the model spectrum convolved with the LSF
OUTPUT:
(none; just downloads)
HISTORY:
2015-01-20 - Written - Bovy (IAS)
"""
if dr is None: dr= path._default_dr()
# First make sure the file doesn't exist
filePath= path.modelSpecPath(lib=lib,teff=teff,logg=logg,metals=metals,
cfe=cfe,nfe=nfe,afe=afe,vmicro=vmicro,dr=dr)
if os.path.exists(filePath): return None
# Create the file path
downloadPath= filePath.replace(os.path.join(path._APOGEE_DATA,
_dr_string(dr)),
_base_url(dr=dr))
_download_file(downloadPath,filePath,dr,verbose=True)
# Post-processing of the file, removing the big first HDU or the first two for local storage
if rmHDU1 or rmHDU2:
# Open the file, need to use astropy's fits reader, bc the file has issues
import astropy.io.fits as apyfits
from astropy.utils.exceptions import AstropyUserWarning
import warnings
warnings.filterwarnings('ignore',category=AstropyUserWarning)
hdulist= apyfits.open(filePath)
if rmHDU1:
hdu= apyfits.PrimaryHDU(numpy.zeros((2,2)))
else:
hdu= hdulist[0].copy()
inp= [hdu]
if rmHDU2:
hdu2= apyfits.ImageHDU(numpy.zeros((2,2)))
else:
hdu2= hdulist[1].copy()
inp.append(hdu2)
inp.extend(hdulist[2:])
newHdulist= apyfits.HDUList(inp)
# Fix any issues in the headers
for ii in range(5):
if '[A/M]' in newHdulist[ii].header:
newHdulist[ii].header['AM']= newHdulist[ii].header.pop('[A/M]',None)
if '[C/M]' in newHdulist[ii].header:
newHdulist[ii].header['CM']= newHdulist[ii].header.pop('[C/M]',None)
if '[N/M]' in newHdulist[ii].header:
newHdulist[ii].header['NM']= newHdulist[ii].header.pop('[N/M]',None)
# Overwrite file
newHdulist.writeto(filePath,clobber=True,output_verify='silentfix')
return None
def mcmc(spec,specerr,
fparam=None,
teff=4750.,logg=2.5,metals=0.,am=0.,nm=0.,cm=0.,vm=None,
nsamples=1000,nwalkers=40,
initsig=[20.,0.05,0.025,0.025,0.025,0.025,0.025],
fixteff=False,fixlogg=False,fixmetals=False,fixam=False,fixcm=False,
fixnm=False,fixvm=False,
lib='GK',pca=True,sixd=True,dr=None,
inter=3,f_format=1,f_access=None,
verbose=False):
"""
NAME:
mcmc
PURPOSE:
Perform MCMC of the 6/7 parameter global fit of model spectra to a given data spectrum
INPUT:
Either:
(1) location ID - single or list/array of location IDs
APOGEE ID - single or list/array of APOGEE IDs; loads aspcapStar
(2) spec - spectrum: can be (nwave) or (nspec,nwave)
specerr - spectrum errors: can be (nwave) or (nspec,nwave)
Input parameters (can be 1D arrays)
Either:
(1) fparam= (None) output of ferre.fit
(2) teff= (4750.) Effective temperature (K)
logg= (2.5) log10 surface gravity / cm s^-2
metals= (0.) overall metallicity
am= (0.) [alpha/M]
nm= (0.) [N/M]
cm= (0.) [C/M]
vm= if using the 7D library, also specify the microturbulence
MCMC options:
nsamples= (1000) number of samples to get
nwalkers= (40) number of ensemble walkers to use in the MCMC
initsig= std. dev. of the initial ball of walkers around
[Teff,logg,log10vmicro,metals,cm,nm,am]
specify log10vmicro even when using a 6D library
fixteff= (True) if True, fix teff at the input value
fixlogg= (True) if True, fix logg at the input value
fixvm= (True) if True, fix vm at the input value (only if sixd is False)
fixmetals= (None) if True, fix metals at the input value
fixam= (None) if True, fix am at the input value
fixcm= (None) if True, fix cm at the input value
fixnm= (None) if True, fix nm at the input value
Library options:
lib= ('GK') spectral library
pca= (True) if True, use a PCA compressed library
sixd= (True) if True, use the 6D library (w/o vm)
dr= data release
FERRE options:
inter= (3) order of the interpolation
f_format= (1) file format (0=ascii, 1=unf)
f_access= (None) 0: load whole library, 1: use direct access (for small numbers of interpolations), None: automatically determine a good value (currently, 1)
verbose= (False) if True, run FERRE in verbose mode
OUTPUT:
TBD
HISTORY:
2015-04-08 - Written - Bovy (IAS)
"""
# Parse fparam
if not fparam is None:
teff= fparam[:,paramIndx('TEFF')]
logg= fparam[:,paramIndx('LOGG')]
metals= fparam[:,paramIndx('METALS')]
am= fparam[:,paramIndx('ALPHA')]
nm= fparam[:,paramIndx('N')]
cm= fparam[:,paramIndx('C')]
if sixd:
vm= None
else:
vm= fparam[:,paramIndx('LOG10VDOP')]
# Make sure the Teff etc. have the right dimensionality
if len(spec.shape) == 1:
nspec= 1
else:
raise ValueError("apogee.modelspec.ferre.mcmc only works for a single spectrum")
nspec= spec.shape[0]
if nspec > 1 and isinstance(teff,float):
teff= teff*numpy.ones(nspec)
if nspec > 1 and isinstance(logg,float):
logg= logg*numpy.ones(nspec)
if nspec > 1 and isinstance(metals,float):
metals= metals*numpy.ones(nspec)
if nspec > 1 and isinstance(am,float):
am= am*numpy.ones(nspec)
if nspec > 1 and isinstance(nm,float):
nm= nm*numpy.ones(nspec)
if nspec > 1 and isinstance(cm,float):
cm= cm*numpy.ones(nspec)
if nspec > 1 and not vm is None and isinstance(vm,float):
vm= vm*numpy.ones(nspec)
if dr is None: dr= appath._default_dr()
# Setup the walkers
ndim= 7-sixd-fixvm+sixd*fixvm-fixteff-fixlogg-fixmetals-fixam-fixcm-fixnm
p0= []
for ii in range(nwalkers):
tp0= []
# Teff
if not fixteff:
tteff= teff+numpy.random.normal()*initsig[0]
if tteff > 6000.: tteff= 6000.
if tteff < 3500.: tteff= 3500.
tp0.append(tteff)
# logg
if not fixlogg:
tlogg= logg+numpy.random.normal()*initsig[1]
if logg > 5.: tlogg= 5.
if logg < 0.: tlogg= 0.
tp0.append(tlogg)
# log10vmicro
if not (fixvm or sixd):
tvm= numpy.log10(vm)+numpy.random.normal()*initsig[2]
if tvm > numpy.log10(8.0): tvm= numpy.log10(8.0)
if tvm < numpy.log10(0.5): tvm= numpy.log10(0.5)
tp0.append(tvm)
# metals
if not fixmetals:
tmetals= metals+numpy.random.normal()*initsig[3]
if metals > 0.5: tmetals= 0.5
if metals < -2.5: tmetals= -2.5
tp0.append(tmetals)
# cm
if not fixcm:
tcm= cm+numpy.random.normal()*initsig[4]
if cm > 1.0: tcm= 1.0
if cm < -1.0: tcm= -1.
tp0.append(tcm)
# nm
if not fixnm:
tnm= nm+numpy.random.normal()*initsig[5]
if nm > 0.5: tnm= 1.0
if nm < -1.0: tnm= -1.0
tp0.append(tnm)
# am
if not fixam:
tam= am+numpy.random.normal()*initsig[6]
if am > 0.5: tam= 1.0
if am < -1.0: tam= -1.0
tp0.append(tam)
p0.append(numpy.array(tp0)[:,0])
p0= numpy.array(p0)
# Prepare the data
dspec= numpy.tile(spec,(nwalkers,1))
dspecerr= numpy.tile(specerr,(nwalkers,1))
# Run MCMC
sampler= apogee.util.emcee.EnsembleSampler(nwalkers,ndim,_mcmc_lnprob,
args=[dspec,dspecerr,
teff,logg,vm,metals,
cm,nm,am,
fixteff,fixlogg,fixvm,
fixmetals,fixcm,fixnm,
fixam,sixd,pca,
dr,lib,
inter,f_format,f_access])
# Burn-in 10% of nsamples
pos, prob, state = sampler.run_mcmc(p0,nsamples//10)
sampler.reset()
# Run main MCMC
sampler.run_mcmc(pos,nsamples)
return sampler.flatchain
def fit(spec,specerr,
teff=4750.,logg=2.5,metals=0.,am=0.,nm=0.,cm=0.,vm=None,
fixteff=False,fixlogg=False,fixmetals=False,fixam=False,fixcm=False,
fixnm=False,fixvm=False,
lib='GK',pca=True,sixd=True,dr=None,
offile=None,
inter=3,f_format=1,f_access=None,
errbar=1,indini=[1,1,1,2,2,3],init=1,initcannon=False,
verbose=False):
"""
NAME:
fit
PURPOSE:
Fit a model spectrum to a given data spectrum
INPUT:
Either:
(1) location ID - single or list/array of location IDs
APOGEE ID - single or list/array of APOGEE IDs; loads aspcapStar
(2) spec - spectrum: can be (nwave) or (nspec,nwave)
specerr - spectrum errors: can be (nwave) or (nspec,nwave)
Input parameters (can be 1D arrays); only used when init=0
teff= (4750.) Effective temperature (K)
logg= (2.5) log10 surface gravity / cm s^-2
metals= (0.) overall metallicity
am= (0.) [alpha/M]
nm= (0.) [N/M]
cm= (0.) [C/M]
vm= if using the 7D library, also specify the microturbulence
Fit options:
fixteff= (False) if True, fix teff at the input value
fixlogg= (False) if True, fix logg at the input value
fixmetals= (False) if True, fix metals at the input value
fixam= (False) if True, fix am at the input value
fixcm= (False) if True, fix cm at the input value
fixnm= (False) if True, fix nm at the input value
fixvm= (False) if True, fix vm at the input value (only if sixd is False)
Library options:
lib= ('GK') spectral library
pca= (True) if True, use a PCA compressed library
sixd= (True) if True, use the 6D library (w/o vm)
dr= data release
FERRE options:
inter= (3) order of the interpolation
errbar= (1) method for calculating the error bars
indini= ([1,1,1,2,2,3]) how to initialize the search (int or array/list with ndim entries)
init= (1) if 0, initialize the search at the parameters in the pfile
f_format= (1) file format (0=ascii, 1=unf)
f_access= (None) 0: load whole library, 1: use direct access (for small numbers of interpolations), None: automatically determine a good value (currently, 1)
Other options:
initcannon= (False) If True, initialize a single run by first running the Cannon using the default Cannon fit (sets init=0)
Output options:
offile= (None) if offile is set, the FERRE OFFILE is saved to this file, otherwise this file is removed
verbose= (False) if True, run FERRE in verbose mode
OUTPUT:
best-fit parameters (nspec,nparams); in the same order as the FPARAM APOGEE data product
HISTORY:
2015-01-29 - Written - Bovy (IAS)
"""
# Initialize using the Cannon?
if initcannon:
init= 0 # just run one fit using the Cannon as a starting guess
initparams= cannon.polylabels(spec,specerr)
if not fixteff: teff= initparams[:,0]
if not fixlogg: logg= initparams[:,1]
if not fixmetals: metals= initparams[:,2]
if not fixam: am= initparams[:,3]
if not fixcm: cm= numpy.zeros_like(initparams[:,0])
if not fixnm: nm= numpy.zeros_like(initparams[:,0])
# Make sure the Teff etc. have the right dimensionality
if len(spec.shape) == 1:
nspec= 1
else:
nspec= spec.shape[0]
if nspec > 1 and isinstance(teff,float):
teff= teff*numpy.ones(nspec)
if nspec > 1 and isinstance(logg,float):
logg= logg*numpy.ones(nspec)
if nspec > 1 and isinstance(metals,float):
metals= metals*numpy.ones(nspec)
if nspec > 1 and isinstance(am,float):
am= am*numpy.ones(nspec)
if nspec > 1 and isinstance(nm,float):
nm= nm*numpy.ones(nspec)
if nspec > 1 and isinstance(cm,float):
cm= cm*numpy.ones(nspec)
if nspec > 1 and not vm is None and isinstance(vm,float):
vm= vm*numpy.ones(nspec)
if dr is None: dr= appath._default_dr()
# Fix any of the parameters?
indv= []
indini= copy.copy(indini) # need to copy bc passed by reference
if isinstance(indini,numpy.ndarray) and \
((not sixd and fixvm) or fixcm or fixnm or fixam or fixmetals \
or fixlogg or fixteff):
indini= list(indini)
if not sixd and not fixvm:
indv.append(1)
elif not sixd:
if isinstance(indini,list): indini[0]= -1
if not fixcm:
indv.append(2-sixd)
else:
if isinstance(indini,list): indini[1-sixd]= -1
if not fixnm:
indv.append(3-sixd)
else:
if isinstance(indini,list): indini[2-sixd]= -1
if not fixam:
indv.append(4-sixd)
else:
if isinstance(indini,list): indini[3-sixd]= -1
if not fixmetals:
indv.append(5-sixd)
else:
if isinstance(indini,list): indini[4-sixd]= -1
if not fixlogg:
indv.append(6-sixd)
else:
if isinstance(indini,list): indini[5-sixd]= -1
if not fixteff:
indv.append(7-sixd)
else:
if isinstance(indini,list): indini[6-sixd]= -1
if isinstance(indini,list):
while -1 in indini: indini.remove(-1)
# Setup temporary directory to run FERRE from
tmpDir= tempfile.mkdtemp(dir='./')
try:
# First write the ipf file with the parameters
write_ipf(tmpDir,teff,logg,metals,am,nm,cm,vm=vm)
# Write the file with the fluxes and the flux errors
write_ffile(tmpDir,spec,specerr=specerr)
# Now write the input.nml file
if f_access is None:
f_access= 1
write_input_nml(tmpDir,'input.ipf','output.dat',ndim=7-sixd,
nov=7-sixd-fixcm-fixnm-fixam-fixmetals\
-fixlogg-fixteff,
indv=indv,
synthfile=appath.ferreModelLibraryPath\
(lib=lib,pca=pca,sixd=sixd,dr=dr,
header=True,unf=False),
ffile='input.frd',erfile='input.err',
opfile='output.opf',
inter=inter,f_format=f_format,
errbar=errbar,indini=indini,init=init,
f_access=f_access)
# Run FERRE
run_ferre(tmpDir,verbose=verbose)
# Read the output
cols= (1,2,3,4,5,6)
tmpOut= numpy.loadtxt(os.path.join(tmpDir,'output.opf'),usecols=cols)
if len(spec.shape) == 1 or spec.shape[0] == 1:
out= numpy.zeros((1,7))
tmpOut= numpy.reshape(tmpOut,(1,7-sixd))
else:
out= numpy.zeros((nspec,7))
out[:,paramIndx('TEFF')]= tmpOut[:,-1]
out[:,paramIndx('LOGG')]= tmpOut[:,-2]
out[:,paramIndx('METALS')]= tmpOut[:,-3]
out[:,paramIndx('ALPHA')]= tmpOut[:,-4]
out[:,paramIndx('N')]= tmpOut[:,-5]
out[:,paramIndx('C')]= tmpOut[:,-6]
if sixd and dr == '12':
out[:,paramIndx('LOG10VDOP')]=\
numpy.log10(2.478-0.325*out[:,paramIndx('LOGG')])
else:
out[:,paramIndx('LOG10VDOP')]= tmpOut[:,0]
if not offile is None:
os.rename(os.path.join(tmpDir,'output.dat'),offile)
finally:
# Clean up
if os.path.exists(os.path.join(tmpDir,'input.ipf')):
os.remove(os.path.join(tmpDir,'input.ipf'))
if os.path.exists(os.path.join(tmpDir,'input.frd')):
os.remove(os.path.join(tmpDir,'input.frd'))
if os.path.exists(os.path.join(tmpDir,'input.err')):
os.remove(os.path.join(tmpDir,'input.err'))
if os.path.exists(os.path.join(tmpDir,'input.nml')):
os.remove(os.path.join(tmpDir,'input.nml'))
if os.path.exists(os.path.join(tmpDir,'output.dat')):
os.remove(os.path.join(tmpDir,'output.dat'))
if os.path.exists(os.path.join(tmpDir,'output.opf')):
os.remove(os.path.join(tmpDir,'output.opf'))
os.rmdir(tmpDir)
return out
def modelSpec(lib='GK',
teff=4500,
logg=2.5,
metals=0.,
cfe=0.,
nfe=0.,
afe=0.,
vmicro=2.,
dr=None,
header=True,
ext=234,
apStarWavegrid=None,
**kwargs):
"""
NAME:
modelSpec
PURPOSE:
Read a model spectrum file
INPUT:
lib= ('GK') spectral library
teff= (4500) grid-point Teff
logg= (2.5) grid-point logg
metals= (0.) grid-point metallicity
cfe= (0.) grid-point carbon-enhancement
nfe= (0.) grid-point nitrogen-enhancement
afe= (0.) grid-point alpha-enhancement
vmicro= (2.) grid-point microturbulence
dr= return the path corresponding to this data release
ext= (234) extension to load (if ext=234, the blue, green, and red spectra will be combined [onto the aspcapStar wavelength grid by default, just concatenated if apStarWavegrid=False), with NaN where there is no model)
apStarWavegrid= (True) if False and ext=234, don't put the spectrum on the apStar wavelength grid, but just concatenate the blue, green, and red detector
header= (True) if True, also return the header (not for ext=234)
dr= return the path corresponding to this data release (general default)
+download kwargs
OUTPUT:
model spectrum or (model spectrum file, header)
HISTORY:
2015-01-13 - Written - Bovy (IAS)
"""
filePath = path.modelSpecPath(lib=lib,
teff=teff,
logg=logg,
metals=metals,
cfe=cfe,
nfe=nfe,
afe=afe,
vmicro=vmicro,
dr=dr)
if not os.path.exists(filePath):
download.modelSpec(lib=lib,
teff=teff,
logg=logg,
metals=metals,
cfe=cfe,
nfe=nfe,
afe=afe,
vmicro=vmicro,
dr=dr,
**kwargs)
# Need to use astropy's fits reader, bc the file has issues
import astropy.io.fits as apyfits
from astropy.utils.exceptions import AstropyUserWarning
import warnings
warnings.filterwarnings('ignore', category=AstropyUserWarning)
hdulist = apyfits.open(filePath)
# Find index of nearest grid point in Teff, logg, and metals
if dr is None: dr = path._default_dr()
if dr == '12':
logggrid = numpy.linspace(0., 5., 11)
metalsgrid = numpy.linspace(-2.5, 0.5, 7)
if lib.lower() == 'gk':
teffgrid = numpy.linspace(3500., 6000., 11)
teffIndx = numpy.argmin(numpy.fabs(teff - teffgrid))
elif lib.lower() == 'f':
teffgrid = numpy.linspace(5500., 8000., 11)
teffIndx = numpy.argmin(numpy.fabs(teff - teffgrid))
loggIndx = numpy.argmin(numpy.fabs(logg - logggrid))
metalsIndx = numpy.argmin(numpy.fabs(metals - metalsgrid))
if header and not ext == 234:
return (hdulist[ext].data[metalsIndx, loggIndx,
teffIndx], hdulist[ext].header)
elif not ext == 234:
return hdulist[ext].data[metalsIndx, loggIndx, teffIndx]
else: #ext == 234, combine 2,3,4
out = numpy.zeros(7214)
out[:2920] = hdulist[2].data[metalsIndx, loggIndx, teffIndx]
out[2920:5320] = hdulist[3].data[metalsIndx, loggIndx, teffIndx]
out[5320:] = hdulist[4].data[metalsIndx, loggIndx, teffIndx]
return out
def modelSpec(lib='GK',teff=4500,logg=2.5,metals=0.,
cfe=0.,nfe=0.,afe=0.,vmicro=2.,
dr=None,header=True,ext=234,apStarWavegrid=None,**kwargs):
"""
NAME:
modelSpec
PURPOSE:
Read a model spectrum file
INPUT:
lib= ('GK') spectral library
teff= (4500) grid-point Teff
logg= (2.5) grid-point logg
metals= (0.) grid-point metallicity
cfe= (0.) grid-point carbon-enhancement
nfe= (0.) grid-point nitrogen-enhancement
afe= (0.) grid-point alpha-enhancement
vmicro= (2.) grid-point microturbulence
dr= return the path corresponding to this data release
ext= (234) extension to load (if ext=234, the blue, green, and red spectra will be combined [onto the aspcapStar wavelength grid by default, just concatenated if apStarWavegrid=False), with NaN where there is no model)
apStarWavegrid= (True) if False and ext=234, don't put the spectrum on the apStar wavelength grid, but just concatenate the blue, green, and red detector
header= (True) if True, also return the header (not for ext=234)
dr= return the path corresponding to this data release (general default)
+download kwargs
OUTPUT:
model spectrum or (model spectrum file, header)
HISTORY:
2015-01-13 - Written - Bovy (IAS)
"""
filePath= path.modelSpecPath(lib=lib,teff=teff,logg=logg,metals=metals,
cfe=cfe,nfe=nfe,afe=afe,vmicro=vmicro,dr=dr)
if not os.path.exists(filePath):
download.modelSpec(lib=lib,teff=teff,logg=logg,metals=metals,
cfe=cfe,nfe=nfe,afe=afe,vmicro=vmicro,dr=dr,
**kwargs)
# Need to use astropy's fits reader, bc the file has issues
import astropy.io.fits as apyfits
from astropy.utils.exceptions import AstropyUserWarning
import warnings
warnings.filterwarnings('ignore',category=AstropyUserWarning)
hdulist= apyfits.open(filePath)
# Find index of nearest grid point in Teff, logg, and metals
if dr is None: dr= path._default_dr()
if dr == '12':
logggrid= numpy.linspace(0.,5.,11)
metalsgrid= numpy.linspace(-2.5,0.5,7)
if lib.lower() == 'gk':
teffgrid= numpy.linspace(3500.,6000.,11)
teffIndx= numpy.argmin(numpy.fabs(teff-teffgrid))
elif lib.lower() == 'f':
teffgrid= numpy.linspace(5500.,8000.,11)
teffIndx= numpy.argmin(numpy.fabs(teff-teffgrid))
loggIndx= numpy.argmin(numpy.fabs(logg-logggrid))
metalsIndx= numpy.argmin(numpy.fabs(metals-metalsgrid))
if header and not ext == 234:
return (hdulist[ext].data[metalsIndx,loggIndx,teffIndx],
hdulist[ext].header)
elif not ext == 234:
return hdulist[ext].data[metalsIndx,loggIndx,teffIndx]
else: #ext == 234, combine 2,3,4
out= numpy.zeros(7214)
out[:2920]= hdulist[2].data[metalsIndx,loggIndx,teffIndx]
out[2920:5320]= hdulist[3].data[metalsIndx,loggIndx,teffIndx]
out[5320:]= hdulist[4].data[metalsIndx,loggIndx,teffIndx]
return out
def modelSpec(lib='GK',
teff=4500,
logg=2.5,
metals=0.,
cfe=0.,
nfe=0.,
afe=0.,
vmicro=2.,
dr=None,
rmHDU1=True,
rmHDU2=True):
"""
NAME:
modelSpec
PURPOSE:
download a model spectrum file
INPUT:
lib= ('GK') spectral library
teff= (4500) grid-point Teff
logg= (2.5) grid-point logg
metals= (0.) grid-point metallicity
cfe= (0.) grid-point carbon-enhancement
nfe= (0.) grid-point nitrogen-enhancement
afe= (0.) grid-point alpha-enhancement
vmicro= (2.) grid-point microturbulence
dr= return the path corresponding to this data release
rmHUD1= (True) if True, rm the first (v. large) HDU with the high-resolution model spectrum
rmHDU2= (True) if True, rm the second (quite large) HDU with the model spectrum convolved with the LSF
OUTPUT:
(none; just downloads)
HISTORY:
2015-01-20 - Written - Bovy (IAS)
"""
if dr is None: dr = path._default_dr()
# First make sure the file doesn't exist
filePath = path.modelSpecPath(lib=lib,
teff=teff,
logg=logg,
metals=metals,
cfe=cfe,
nfe=nfe,
afe=afe,
vmicro=vmicro,
dr=dr)
if os.path.exists(filePath): return None
# Create the file path
downloadPath = filePath.replace(
os.path.join(path._APOGEE_DATA, _dr_string(dr)), _base_url(dr=dr))
_download_file(downloadPath, filePath, dr, verbose=True)
# Post-processing of the file, removing the big first HDU or the first two for local storage
if rmHDU1 or rmHDU2:
# Open the file, need to use astropy's fits reader, bc the file has issues
import astropy.io.fits as apyfits
from astropy.utils.exceptions import AstropyUserWarning
import warnings
warnings.filterwarnings('ignore', category=AstropyUserWarning)
hdulist = apyfits.open(filePath)
if rmHDU1:
hdu = apyfits.PrimaryHDU(numpy.zeros((2, 2)))
else:
hdu = hdulist[0].copy()
inp = [hdu]
if rmHDU2:
hdu2 = apyfits.ImageHDU(numpy.zeros((2, 2)))
else:
hdu2 = hdulist[1].copy()
inp.append(hdu2)
inp.extend(hdulist[2:])
newHdulist = apyfits.HDUList(inp)
# Fix any issues in the headers
for ii in range(5):
if '[A/M]' in newHdulist[ii].header:
newHdulist[ii].header['AM'] = newHdulist[ii].header.pop(
'[A/M]', None)
if '[C/M]' in newHdulist[ii].header:
newHdulist[ii].header['CM'] = newHdulist[ii].header.pop(
'[C/M]', None)
if '[N/M]' in newHdulist[ii].header:
newHdulist[ii].header['NM'] = newHdulist[ii].header.pop(
'[N/M]', None)
# Overwrite file
newHdulist.writeto(filePath, clobber=True, output_verify='silentfix')
return None
def pixels_cannon(*args, **kwargs):
"""
NAME:
pixels_cannon
PURPOSE:
determine continuum pixels using a Cannon-like technique (Ness et al. 2015)
INPUT:
Either:
a) Input for running the apogee.spec.cannon:
spec - spectra to fit (nspec,nlambda)
specerrs - errors on the spectra (nspec,nlambda); assume no covariances
label1, label2, ... - labels (nspec); best to subtract reference values before running this
type= ('lin') type of Cannon to run:
'lin' - linear Cannon
'quad' - quadratic Cannon
b) Output from a previous Cannon run:
coefficients - coefficients from the fit (ncoeffs,nlambda)
scatter - scatter from the fit (nlambda)
KEYWORDS:
baseline_dev= (0.015) maximum deviation from baseline
label1_max= (10.**-5.) maximum deviation in first linear coefficient
label2_max= (0.006) similar for the second
label3_max= (0.012) similar for the third
labelN_max= same with default 0.03
...
scatter_max= (0.015) maximum scatter of residuals
dr= (module-wide default) data release
OUTPUT:
Boolean index into the wavelength range with True for continuum pixels
HISTORY:
2015-02-05 - Written - Bovy (IAS@KITP)
"""
# Grab kwargs
type = kwargs.pop('type', 'lin')
dr = kwargs.pop('dr', path._default_dr())
# Parse input
if len(args) == 0: # Use default fit
from apogee.spec._train_cannon import load_fit
coeffs, scatter, baseline_labels = load_fit()
type = 'quad'
else:
spec = args[0]
specerr = args[1]
# Determine the type of input
if len(specerr.shape) == 2:
# Run the Cannon
if type.lower() == 'lin':
coeffs, scatter = cannon.linfit(*args)
elif type.lower() == 'quad':
coeffs, scatter = cannon.quadfit(*args)
else:
coeffs = spec
scatter = specerr
ncoeffs = coeffs.shape[0]
if type.lower() == 'lin':
nlabels = ncoeffs - 1
elif type.lower() == 'quad':
nlabels = int((-3 + numpy.sqrt(9 + 8 * (ncoeffs - 1)))) // 2
# Determine continuum pixels
out = numpy.ones(len(scatter), dtype='bool')
# Deviation from baseline
out[numpy.fabs(coeffs[0] - 1.) > kwargs.get('baseline_dev', 0.015)] = False
# Large dependence on labels
maxs = numpy.zeros(nlabels)
maxs[0] = kwargs.get('label1_max', 10.**-5.)
maxs[1] = kwargs.get('label2_max', 0.006)
maxs[2] = kwargs.get('label3_max', 0.012)
for ii in range(nlabels - 3):
maxs[ii + 3] = kwargs.get('label%i_max' % (ii + 4), 0.03)
for ii in range(1, nlabels + 1):
out[numpy.fabs(coeffs[ii]) > maxs[ii - 1]] = False
# Large residuals
out[scatter > kwargs.get('scatter_max', 0.015)] = False
_, _, _, aspcapDR12length = _aspcapPixelLimits(dr='12')
if int(dr) > 12 and coeffs.shape[1] == aspcapDR12length:
# Want continuum pixels on >DR12 ASPCAP grid, but using coefficients
# from <= DR12 grid
dr_module = path._default_dr()
path.change_dr(12)
out = toApStarGrid(out)
path.change_dr(dr)
out = toAspcapGrid(out)
path.change_dr(dr_module)
return out
def elemfit(spec,specerr,elem,
fparam=None,
teff=4750.,logg=2.5,metals=0.,am=0.,nm=0.,cm=0.,vm=None,
fixteff=True,fixlogg=True,fixmetals=None,fixam=None,
fixcm=None,
fixnm=None,fixvm=True,
estimate_err=False,
lib='GK',pca=True,sixd=True,dr=None,
offile=None,
inter=3,f_format=1,f_access=None,
errbar=1,indini=[1,1,1,2,2,3],init=0,
verbose=False):
"""
NAME:
elemfit
PURPOSE:
Fit a model spectrum to a given data spectrum for a given element window
INPUT:
Either:
(1) location ID - single or list/array of location IDs
APOGEE ID - single or list/array of APOGEE IDs; loads aspcapStar
(2) spec - spectrum: can be (nwave) or (nspec,nwave)
specerr - spectrum errors: can be (nwave) or (nspec,nwave)
elem - element to fit (e.g., 'Al')
estimate_err= (False) if True, estimate the error from Delta chi^2=1; only works for errors <~ 0.3 dex, code returns numpy.nan when error is larger
Input parameters (can be 1D arrays); only used when init=0
Either:
(1) fparam= (None) output of ferre.fit
(2) teff= (4750.) Effective temperature (K)
logg= (2.5) log10 surface gravity / cm s^-2
metals= (0.) overall metallicity
am= (0.) [alpha/M]
nm= (0.) [N/M]
cm= (0.) [C/M]
vm= if using the 7D library, also specify the microturbulence
Fit options:
fixteff= (True) if True, fix teff at the input value
fixlogg= (True) if True, fix logg at the input value
fixvm= (True) if True, fix vm at the input value (only if sixd is False)
The following are set to False based on the element being fit (C -> fixcm=False, N -> fixnm=False, O,Mg,S,Si,Ca,Ti -> fixam=False, rest -> fixmetals=False)
fixmetals= (None) if True, fix metals at the input value
fixam= (None) if True, fix am at the input value
fixcm= (None) if True, fix cm at the input value
fixnm= (None) if True, fix nm at the input value
Library options:
lib= ('GK') spectral library
pca= (True) if True, use a PCA compressed library
sixd= (True) if True, use the 6D library (w/o vm)
dr= data release
FERRE options:
inter= (3) order of the interpolation
errbar= (1) method for calculating the error bars
indini= ([1,1,1,2,2,3]) how to initialize the search (int or array/list with ndim entries)
init= (0) if 0, initialize the search at the parameters in the pfile
f_format= (1) file format (0=ascii, 1=unf)
f_access= (None) 0: load whole library, 1: use direct access (for small numbers of interpolations), None: automatically determine a good value (currently, 1)
Output options:
offile= (None) if offile is set, the FERRE OFFILE is saved to this file, otherwise this file is removed
verbose= (False) if True, run FERRE in verbose mode
OUTPUT:
best-fit parameters (nspec,nparams); in the same order as the FPARAM APOGEE data product (fixed inputs are repeated in the output)
if estimate_err: tuple with best-fit (see above) and error on the element abundance
HISTORY:
2015-02-27 - Written - Bovy (IAS)
"""
# Parse fparam
if not fparam is None:
teff= fparam[:,paramIndx('TEFF')]
logg= fparam[:,paramIndx('LOGG')]
metals= fparam[:,paramIndx('METALS')]
am= fparam[:,paramIndx('ALPHA')]
nm= fparam[:,paramIndx('N')]
cm= fparam[:,paramIndx('C')]
if sixd:
vm= None
else:
vm= fparam[:,paramIndx('LOG10VDOP')]
# Make sure the Teff etc. have the right dimensionality
if len(spec.shape) == 1:
nspec= 1
else:
nspec= spec.shape[0]
if nspec > 1 and isinstance(teff,float):
teff= teff*numpy.ones(nspec)
if nspec > 1 and isinstance(logg,float):
logg= logg*numpy.ones(nspec)
if nspec > 1 and isinstance(metals,float):
metals= metals*numpy.ones(nspec)
if nspec > 1 and isinstance(am,float):
am= am*numpy.ones(nspec)
if nspec > 1 and isinstance(nm,float):
nm= nm*numpy.ones(nspec)
if nspec > 1 and isinstance(cm,float):
cm= cm*numpy.ones(nspec)
if nspec > 1 and not vm is None and isinstance(vm,float):
vm= vm*numpy.ones(nspec)
if dr is None: dr= appath._default_dr()
# Set fixXX based on element being fit, first set None to True
if fixcm is None: fixcm= True
if fixnm is None: fixnm= True
if fixam is None: fixam= True
if fixmetals is None: fixmetals= True
if elem.lower() == 'c':
fixcm= False
elif elem.lower() == 'n':
fixnm= False
elif elem.lower() in ['o','mg','s','si','ca','ti']:
fixam= False
else:
fixmetals= False
# Fix any of the parameters?
indv= []
indini= copy.copy(indini) # need to copy bc passed by reference
if isinstance(indini,numpy.ndarray) and \
((not sixd and fixvm) or fixcm or fixnm or fixam or fixmetals \
or fixlogg or fixteff):
indini= list(indini)
if not sixd and not fixvm:
indv.append(1)
elif not sixd:
if isinstance(indini,list): indini[0]= -1
if not fixcm:
indv.append(2-sixd)
else:
if isinstance(indini,list): indini[1-sixd]= -1
if not fixnm:
indv.append(3-sixd)
else:
if isinstance(indini,list): indini[2-sixd]= -1
if not fixam:
indv.append(4-sixd)
else:
if isinstance(indini,list): indini[3-sixd]= -1
if not fixmetals:
indv.append(5-sixd)
else:
if isinstance(indini,list): indini[4-sixd]= -1
if not fixlogg:
indv.append(6-sixd)
else:
if isinstance(indini,list): indini[5-sixd]= -1
if not fixteff:
indv.append(7-sixd)
else:
if isinstance(indini,list): indini[6-sixd]= -1
if isinstance(indini,list):
while -1 in indini: indini.remove(-1)
if init == 0: indini= 0
# Setup temporary directory to run FERRE from
tmpDir= tempfile.mkdtemp(dir='./')
try:
# First write the ipf file with the parameters
write_ipf(tmpDir,teff,logg,metals,am,nm,cm,vm=vm)
# Write the file with the fluxes and the flux errors
write_ffile(tmpDir,spec,specerr=specerr)
# Now write the input.nml file
if f_access is None:
f_access= 1
write_input_nml(tmpDir,'input.ipf','output.dat',ndim=7-sixd,
nov=7-sixd-fixcm-fixnm-fixam-fixmetals\
-fixlogg-fixteff,
indv=indv,
synthfile=appath.ferreModelLibraryPath\
(lib=lib,pca=pca,sixd=sixd,dr=dr,
header=True,unf=False),
ffile='input.frd',erfile='input.err',
opfile='output.opf',
inter=inter,f_format=f_format,
errbar=errbar,indini=indini,init=init,
f_access=f_access,
filterfile=apwindow.path(elem,dr=dr))
# Run FERRE
run_ferre(tmpDir,verbose=verbose)
# Read the output
cols= (1,2,3,4,5,6)
tmpOut= numpy.loadtxt(os.path.join(tmpDir,'output.opf'),usecols=cols)
if len(spec.shape) == 1 or spec.shape[0] == 1:
out= numpy.zeros((1,7))
tmpOut= numpy.reshape(tmpOut,(1,7-sixd))
else:
out= numpy.zeros((nspec,7))
out[:,paramIndx('TEFF')]= tmpOut[:,-1]
out[:,paramIndx('LOGG')]= tmpOut[:,-2]
out[:,paramIndx('METALS')]= tmpOut[:,-3]
out[:,paramIndx('ALPHA')]= tmpOut[:,-4]
out[:,paramIndx('N')]= tmpOut[:,-5]
out[:,paramIndx('C')]= tmpOut[:,-6]
if sixd and dr == '12':
out[:,paramIndx('LOG10VDOP')]=\
numpy.log10(2.478-0.325*out[:,paramIndx('LOGG')])
else:
out[:,paramIndx('LOG10VDOP')]= tmpOut[:,0]
if not offile is None:
os.rename(os.path.join(tmpDir,'output.dat'),offile)
finally:
# Clean up
if os.path.exists(os.path.join(tmpDir,'input.ipf')):
os.remove(os.path.join(tmpDir,'input.ipf'))
if os.path.exists(os.path.join(tmpDir,'input.frd')):
os.remove(os.path.join(tmpDir,'input.frd'))
if os.path.exists(os.path.join(tmpDir,'input.err')):
os.remove(os.path.join(tmpDir,'input.err'))
if os.path.exists(os.path.join(tmpDir,'input.nml')):
os.remove(os.path.join(tmpDir,'input.nml'))
if os.path.exists(os.path.join(tmpDir,'output.dat')):
os.remove(os.path.join(tmpDir,'output.dat'))
if os.path.exists(os.path.join(tmpDir,'output.opf')):
os.remove(os.path.join(tmpDir,'output.opf'))
os.rmdir(tmpDir)
if estimate_err:
# Determine the chi2 and the error
elem_linspace= (-0.5,0.5,51)
elems= numpy.linspace(*elem_linspace)
c2= elemchi2(spec,specerr,elem,
elem_linspace=elem_linspace,
fparam=out,lib=lib,pca=pca,sixd=sixd,dr=dr,
inter=inter,f_format=f_format,f_access=f_access,
verbose=verbose)
from scipy import interpolate, optimize
outerr= numpy.empty(nspec)
for ii in range(nspec):
spl= \
interpolate.InterpolatedUnivariateSpline(elems,
c2[ii]-numpy.amin(c2[ii]))
try:
ul= optimize.brentq(lambda x: spl(x)-1.,
0.,elem_linspace[1]-0.01)
ll= optimize.brentq(lambda x: spl(x)-1.,
elem_linspace[0]+0.01,0.)
outerr[ii]= (ul-ll)/2.
except ValueError:
outerr[ii]= numpy.nan
return (out,outerr)
else:
return out
