def dust_vals_disk(self,lcen,bcen,dist,radius):
"""
NAME:
dust_vals_disk
PURPOSE:
return the distribution of extinction within a small disk as samples
INPUT:
lcen, bcen - Galactic longitude and latitude of the center of the disk (deg)
dist - distance in kpc
radius - radius of the disk (deg)
OUTPUT:
(pixarea,extinction) - arrays of pixel-area in sq rad and extinction value
HISTORY:
2015-03-07 - Written - Bovy (IAS)
"""
# Find all of the (l,b) of the pixels within radius of (lcen,bcen)
indx= cos_sphere_dist(self._sintheta,self._costheta,
self._sinphi,self._cosphi,
numpy.sin((90.-bcen)*_DEGTORAD),
numpy.cos((90.-bcen)*_DEGTORAD),
numpy.sin(lcen*_DEGTORAD),
numpy.cos(lcen*_DEGTORAD)) \
>= numpy.cos(radius*_DEGTORAD)
ll= self._saledata['GLON'][indx]
bb= self._saledata['GLAT'][indx]
# Now get the extinctions for these pixels
pixarea= []
extinction= []
for l,b in zip(ll,bb):
lbIndx= self._lbIndx(l,b)
extinction.append(self._evaluate(l,b,dist,_lbIndx=lbIndx))
pixarea.append(self._dl[lbIndx]*self._db[lbIndx]*_DEGTORAD**2.)
pixarea= numpy.array(pixarea)
extinction= numpy.array(extinction)
return (pixarea,extinction)
def dust_vals_disk(self, lcen, bcen, dist, radius):
"""
NAME:
dust_vals_disk
PURPOSE:
return the distribution of extinction within a small disk as samples
INPUT:
lcen, bcen - Galactic longitude and latitude of the center of the disk (deg)
dist - distance in kpc
radius - radius of the disk (deg)
OUTPUT:
(pixarea,extinction) - arrays of pixel-area in sq rad and extinction value
HISTORY:
2015-03-07 - Written - Bovy (IAS)
"""
# Find all of the (l,b) of the pixels within radius of (lcen,bcen)
lmin = round((lcen - radius - self._dl) / self._dl) * self._dl
lmax = round((lcen + radius + self._dl) / self._dl) * self._dl
bmin = round((bcen - radius - self._db) / self._db) * self._db
bmax = round((bcen + radius + self._db) / self._db) * self._db
ls = numpy.arange(lmin, lmax + self._dl, self._dl)
bs = numpy.arange(bmin, bmax + self._db, self._db)
ll, bb = numpy.meshgrid(ls, bs, indexing='ij')
ll = ll.flatten()
bb = bb.flatten()
indx= cos_sphere_dist(numpy.sin((90.-bb)*_DEGTORAD),
numpy.cos((90.-bb)*_DEGTORAD),
numpy.sin(ll*_DEGTORAD),
numpy.cos(ll*_DEGTORAD),
numpy.sin((90.-bcen)*_DEGTORAD),
numpy.cos((90.-bcen)*_DEGTORAD),
numpy.sin(lcen*_DEGTORAD),
numpy.cos(lcen*_DEGTORAD)) \
>= numpy.cos(radius*_DEGTORAD)
ll = ll[indx]
bb = bb[indx]
# Now get the extinctions for these pixels
pixarea = self._dl * self._db * _DEGTORAD**2. + numpy.zeros(
numpy.sum(indx))
extinction = []
for l, b in zip(ll, bb):
extinction.append(self._evaluate(l, b, dist))
extinction = numpy.array(extinction)
return (pixarea, extinction)
def dust_vals_disk(self,lcen,bcen,dist,radius):
"""
NAME:
dust_vals_disk
PURPOSE:
return the distribution of extinction within a small disk as samples
INPUT:
lcen, bcen - Galactic longitude and latitude of the center of the disk (deg)
dist - distance in kpc
radius - radius of the disk (deg)
OUTPUT:
(pixarea,extinction) - arrays of pixel-area in sq rad and extinction value
HISTORY:
2015-03-07 - Written - Bovy (IAS)
"""
# Find all of the (l,b) of the pixels within radius of (lcen,bcen)
lmin= round((lcen-radius-self._dl)/self._dl)*self._dl
lmax= round((lcen+radius+self._dl)/self._dl)*self._dl
bmin= round((bcen-radius-self._db)/self._db)*self._db
bmax= round((bcen+radius+self._db)/self._db)*self._db
ls= numpy.arange(lmin,lmax+self._dl,self._dl)
bs= numpy.arange(bmin,bmax+self._db,self._db)
ll,bb= numpy.meshgrid(ls,bs,indexing='ij')
ll= ll.flatten()
bb= bb.flatten()
indx= cos_sphere_dist(numpy.sin((90.-bb)*_DEGTORAD),
numpy.cos((90.-bb)*_DEGTORAD),
numpy.sin(ll*_DEGTORAD),
numpy.cos(ll*_DEGTORAD),
numpy.sin((90.-bcen)*_DEGTORAD),
numpy.cos((90.-bcen)*_DEGTORAD),
numpy.sin(lcen*_DEGTORAD),
numpy.cos(lcen*_DEGTORAD)) \
>= numpy.cos(radius*_DEGTORAD)
ll= ll[indx]
bb= bb[indx]
# Now get the extinctions for these pixels
pixarea= self._dl*self._db*_DEGTORAD**2.+numpy.zeros(numpy.sum(indx))
extinction= []
for l,b in zip(ll,bb):
extinction.append(self._evaluate(l,b,dist))
extinction= numpy.array(extinction)
return (pixarea,extinction)
def _evaluate(self, l, b, d, norescale=False, _fd=1., _fs=1., _fo=1.):
"""
NAME:
_evaluate
PURPOSE:
evaluate the dust-map
INPUT:
l- Galactic longitude (deg)
b- Galactic latitude (deg)
d- distance (kpc) can be array
norescale= (False) if True, don't apply re-scalings
_fd, _fs, _fo= (1.) amplitudes of the different components
OUTPUT:
extinction
HISTORY:
2013-12-10 - Started - Bovy (IAS)
"""
if isinstance(l, numpy.ndarray) or isinstance(b, numpy.ndarray):
raise NotImplementedError(
"array input for l and b for Drimmel dust map not implemented")
cl = numpy.cos(l * _DEGTORAD)
sl = numpy.sin(l * _DEGTORAD)
cb = numpy.cos(b * _DEGTORAD)
sb = numpy.sin(b * _DEGTORAD)
#Setup arrays
avori = numpy.zeros_like(d)
avspir = numpy.zeros_like(d)
avdisk = numpy.zeros_like(d)
#Find nearest pixel in COBE map for the re-scaling
rfIndx = numpy.argmax(
cos_sphere_dist(self._rf_sintheta, self._rf_costheta,
self._rf_sinphi, self._rf_cosphi,
numpy.sin(numpy.pi / 2. - b * _DEGTORAD),
numpy.cos(numpy.pi / 2. - b * _DEGTORAD), sl, cl))
rfdisk, rfspir, rfori = 1., 1., 1,
if self._drimmelMaps['rf_comp'][rfIndx] == 1 and not norescale:
rfdisk = self._drimmelMaps['rf'][rfIndx]
elif self._drimmelMaps['rf_comp'][rfIndx] == 2 and not norescale:
rfspir = self._drimmelMaps['rf'][rfIndx]
elif self._drimmelMaps['rf_comp'][rfIndx] == 3 and not norescale:
rfori = self._drimmelMaps['rf'][rfIndx]
#Find maximum distance
dmax = 100.
if b != 0.: dmax = .49999 / numpy.fabs(sb) - self._zsun / sb
if cl != 0.:
tdmax = (14.9999 / numpy.fabs(cl) - self._xsun / cl)
if tdmax < dmax: dmax = tdmax
if sl != 0.:
tdmax = 14.9999 / numpy.fabs(sl)
if tdmax < dmax: dmax = tdmax
d = copy.copy(d)
d[d > dmax] = dmax
#Rectangular coordinates
X = d * cb * cl
Y = d * cb * sl
Z = d * sb + self._zsun
#Local grid
#Orion
locIndx = (numpy.fabs(X) < 1.) * (numpy.fabs(Y) < 2.)
if numpy.sum(locIndx) > 0:
xi = X[locIndx] / self._dx_ori2 + float(self._nx_ori2 - 1) / 2.
yj = Y[locIndx] / self._dy_ori2 + float(self._ny_ori2 - 1) / 2.
zk = Z[locIndx] / self._dz_ori2 + float(self._nz_ori2 - 1) / 2.
avori[locIndx] = map_coordinates(self._drimmelMaps['avori2'],
[xi, yj, zk],
mode='constant',
cval=0.)
#local disk
locIndx = (numpy.fabs(X) < 0.75) * (numpy.fabs(Y) < 0.75)
if numpy.sum(locIndx) > 0:
xi = X[locIndx] / self._dx_diskloc + float(self._nx_diskloc -
1) / 2.
yj = Y[locIndx] / self._dy_diskloc + float(self._ny_diskloc -
1) / 2.
zk = Z[locIndx] / self._dz_diskloc + float(self._nz_diskloc -
1) / 2.
avdisk[locIndx] = map_coordinates(self._drimmelMaps['avdloc'],
[xi, yj, zk],
mode='constant',
cval=0.)
#Go to Galactocentric coordinates
X = X + self._xsun
#Stars beyond the local grid
#Orion
globIndx = True - (numpy.fabs(X - self._xsun) < 1.) * (numpy.fabs(Y) <
2.)
if numpy.sum(globIndx) > 0:
#Orion grid is different from other global grids, so has its own dmax
dmax = 100.
if b != 0.: dmax = .49999 / numpy.fabs(sb) - self._zsun / sb
if cl > 0.:
tdmax = (2.374999 / numpy.fabs(cl))
if tdmax < dmax: dmax = tdmax
if cl < 0.:
tdmax = (1.374999 / numpy.fabs(cl))
if tdmax < dmax: dmax = tdmax
if sl != 0.:
tdmax = (3.749999 / numpy.fabs(sl))
if tdmax < dmax: dmax = tdmax
dori = copy.copy(d)
dori[dori > dmax] = dmax
Xori = dori * cb * cl + self._xsun
Yori = dori * cb * sl
Zori = dori * sb + self._zsun
xi = Xori[globIndx] / self._dx_ori + 2.5 * float(self._nx_ori - 1)
yj = Yori[globIndx] / self._dy_ori + float(self._ny_ori - 1) / 2.
zk = Zori[globIndx] / self._dz_ori + float(self._nz_ori - 1) / 2.
avori[globIndx] = map_coordinates(self._drimmelMaps['avori'],
[xi, yj, zk],
mode='constant',
cval=0.)
#disk & spir
xi = X / self._dx_disk + float(self._nx_disk - 1) / 2.
yj = Y / self._dy_disk + float(self._ny_disk - 1) / 2.
zk = Z / self._dz_disk + float(self._nz_disk - 1) / 2.
avspir = map_coordinates(self._drimmelMaps['avspir'], [xi, yj, zk],
mode='constant',
cval=0.)
globIndx = True - (numpy.fabs(X - self._xsun) < 0.75) * (numpy.fabs(Y)
< 0.75)
if numpy.sum(globIndx) > 0:
avdisk[globIndx] = map_coordinates(self._drimmelMaps['avdisk'],
[xi, yj, zk],
mode='constant',
cval=0.)[globIndx]
#Return
out = _fd * rfdisk * avdisk + _fs * rfspir * avspir + _fo * rfori * avori
if self._filter is None: # From Rieke & Lebovksy (1985); if sf10, first put ebv on SFD scale
return out / 3.09 / ((1 - self._sf10) + self._sf10 * 0.86)
else:
return out/3.09/((1-self._sf10)+self._sf10*0.86)\
*aebv(self._filter,sf10=self._sf10)
def _evaluate(self,l,b,d,norescale=False,
_fd=1.,_fs=1.,_fo=1.):
"""
NAME:
_evaluate
PURPOSE:
evaluate the dust-map
INPUT:
l- Galactic longitude (deg)
b- Galactic latitude (deg)
d- distance (kpc) can be array
norescale= (False) if True, don't apply re-scalings
_fd, _fs, _fo= (1.) amplitudes of the different components
OUTPUT:
extinction
HISTORY:
2013-12-10 - Started - Bovy (IAS)
"""
if isinstance(l,numpy.ndarray) or isinstance(b,numpy.ndarray):
raise NotImplementedError("array input for l and b for Drimmel dust map not implemented")
cl= numpy.cos(l*_DEGTORAD)
sl= numpy.sin(l*_DEGTORAD)
cb= numpy.cos(b*_DEGTORAD)
sb= numpy.sin(b*_DEGTORAD)
#Setup arrays
avori= numpy.zeros_like(d)
avspir= numpy.zeros_like(d)
avdisk= numpy.zeros_like(d)
#Find nearest pixel in COBE map for the re-scaling
rfIndx= numpy.argmax(cos_sphere_dist(self._rf_sintheta,
self._rf_costheta,
self._rf_sinphi,
self._rf_cosphi,
numpy.sin(numpy.pi/2.-b*_DEGTORAD),
numpy.cos(numpy.pi/2.-b*_DEGTORAD),
sl,cl))
rfdisk, rfspir, rfori= 1., 1., 1,
if self._drimmelMaps['rf_comp'][rfIndx] == 1 and not norescale:
rfdisk= self._drimmelMaps['rf'][rfIndx]
elif self._drimmelMaps['rf_comp'][rfIndx] == 2 and not norescale:
rfspir= self._drimmelMaps['rf'][rfIndx]
elif self._drimmelMaps['rf_comp'][rfIndx] == 3 and not norescale:
rfori= self._drimmelMaps['rf'][rfIndx]
#Find maximum distance
dmax= 100.
if b != 0.: dmax= .49999/numpy.fabs(sb) - self._zsun/sb
if cl != 0.:
tdmax= (14.9999/numpy.fabs(cl)-self._xsun/cl)
if tdmax < dmax: dmax= tdmax
if sl != 0.:
tdmax = 14.9999/numpy.fabs(sl)
if tdmax < dmax: dmax= tdmax
d= copy.copy(d)
d[d > dmax]= dmax
#Rectangular coordinates
X= d*cb*cl
Y= d*cb*sl
Z= d*sb+self._zsun
#Local grid
#Orion
locIndx= (numpy.fabs(X) < 1.)*(numpy.fabs(Y) < 2.)
if numpy.sum(locIndx) > 0:
xi = X[locIndx]/self._dx_ori2+float(self._nx_ori2-1)/2.
yj = Y[locIndx]/self._dy_ori2+float(self._ny_ori2-1)/2.
zk = Z[locIndx]/self._dz_ori2+float(self._nz_ori2-1)/2.
avori[locIndx]= map_coordinates(self._drimmelMaps['avori2'],
[xi,yj,zk],
mode='constant',cval=0.)
#local disk
locIndx= (numpy.fabs(X) < 0.75)*(numpy.fabs(Y) < 0.75)
if numpy.sum(locIndx) > 0:
xi = X[locIndx]/self._dx_diskloc+float(self._nx_diskloc-1)/2.
yj = Y[locIndx]/self._dy_diskloc+float(self._ny_diskloc-1)/2.
zk = Z[locIndx]/self._dz_diskloc+float(self._nz_diskloc-1)/2.
avdisk[locIndx]= map_coordinates(self._drimmelMaps['avdloc'],
[xi,yj,zk],
mode='constant',cval=0.)
#Go to Galactocentric coordinates
X= X+self._xsun
#Stars beyond the local grid
#Orion
globIndx= True-(numpy.fabs(X-self._xsun) < 1.)*(numpy.fabs(Y) < 2.)
if numpy.sum(globIndx) > 0:
#Orion grid is different from other global grids, so has its own dmax
dmax= 100.
if b != 0.: dmax= .49999/numpy.fabs(sb) - self._zsun/sb
if cl > 0.:
tdmax = (2.374999/numpy.fabs(cl))
if tdmax < dmax: dmax= tdmax
if cl < 0.:
tdmax = (1.374999/numpy.fabs(cl))
if tdmax < dmax: dmax= tdmax
if sl != 0.:
tdmax = (3.749999/numpy.fabs(sl))
if tdmax < dmax: dmax= tdmax
dori= copy.copy(d)
dori[dori > dmax]= dmax
Xori= dori*cb*cl+self._xsun
Yori= dori*cb*sl
Zori= dori*sb+self._zsun
xi = Xori[globIndx]/self._dx_ori + 2.5*float(self._nx_ori-1)
yj = Yori[globIndx]/self._dy_ori + float(self._ny_ori-1)/2.
zk = Zori[globIndx]/self._dz_ori + float(self._nz_ori-1)/2.
avori[globIndx]= map_coordinates(self._drimmelMaps['avori'],
[xi,yj,zk],
mode='constant',cval=0.)
#disk & spir
xi = X/self._dx_disk+float(self._nx_disk-1)/2.
yj = Y/self._dy_disk+float(self._ny_disk-1)/2.
zk = Z/self._dz_disk+float(self._nz_disk-1)/2.
avspir= map_coordinates(self._drimmelMaps['avspir'],
[xi,yj,zk],
mode='constant',cval=0.)
globIndx= True-(numpy.fabs(X-self._xsun) < 0.75)*(numpy.fabs(Y) < 0.75)
if numpy.sum(globIndx) > 0:
avdisk[globIndx]= map_coordinates(self._drimmelMaps['avdisk'],
[xi,yj,zk],
mode='constant',
cval=0.)[globIndx]
#Return
out=_fd*rfdisk*avdisk+_fs*rfspir*avspir+_fo*rfori*avori
if self._filter is None: # From Rieke & Lebovksy (1985); if sf10, first put ebv on SFD scale
return out/3.09/((1-self._sf10)+self._sf10*0.78)
else:
return out/3.09/((1-self._sf10)+self._sf10*0.78)\
*aebv(self._filter,sf10=self._sf10)
