def getExpByName(self,src_names,egy_axis,cth_axis=None,weights=None):
exph = None
cat = Catalog.get()
for s in src_names:
if s == 'ridge':
glon = np.linspace(0,360.,30.)
glat = np.zeros(30)
ra,dec = eq2gal(glon,glat)
for i in range(30):
# print i, ra[i], dec[i]
h = self.eval2(ra[i],dec[i],egy_axis,
cth_axis,wfn=weights)
if exph is None: exph = h
else: exph += h
else:
src = cat.get_source_by_name(s)
h = self.eval2(src['RAJ2000'], src['DEJ2000'],egy_axis,
cth_axis,wfn=weights)
if exph is None: exph = h
else: exph += h
exph /= float(len(src_names))
return exph
def get_hlat_ltcube(self):
import healpy
nbin = 400
ra_edge = np.linspace(0,2*np.pi,nbin+1)
dec_edge = np.linspace(-1,1,nbin+1)
ra_center = 0.5*(ra_edge[1:] + ra_edge[:-1])
dec_center = 0.5*(dec_edge[1:] + dec_edge[:-1])
dec, ra = np.meshgrid(np.arcsin(dec_center),ra_center)
lthist = pHist([ra_edge,dec_edge,self._cth_edges])
srcs = np.loadtxt('src.txt',unpack=False)
ipix = healpy.ang2pix(64,np.ravel(np.pi/2. - dec),
np.ravel(ra),nest=True)
lt = self._ltmap[ipix,::-1]
(l, b) = eq2gal(np.degrees(ra),np.degrees(dec))
gal_msk = (np.abs(b) > 40.) & (np.abs(b) < 80.)
eq_msk = (np.abs(np.degrees(dec)) < 79.9)
msk = gal_msk & eq_msk
for i in range(len(srcs)):
msk &= get_src_mask(np.radians(srcs[i]),ra,dec,5.0)
lt = lt.reshape((nbin,nbin,40))
lt[msk==False,:] = 0
lthist._counts = lt
self._omega_tot = float(len(msk[msk==True]))/(nbin**2)*4*np.pi
self._domega_bin = 4*np.pi/(nbin**2)
h0 = lthist.slice([2],[0])
h1 = lthist.slice([2],[20])
h2 = lthist.slice([2],[30])
plt.figure()
h0.plot()
plt.figure()
h1.plot()
plt.figure()
h2.plot()
plt.show()
def plot(self,im,src_color='k',marker_threshold=0,
label_threshold=20., ax=None,radius_deg=10.0,**kwargs):
if ax is None: ax = plt.gca()
if im.axis(0)._coordsys == 'gal':
ra, dec = gal2eq(im.lon,im.lat)
else:
ra, dec = im.lon, im.lat
#srcs = cat.get_source_by_position(ra,dec,self._roi_radius_deg)
# Try to determine the search radius from the input file
srcs = self.get_source_by_position(ra,dec,radius_deg)
src_lon = []
src_lat = []
labels = []
signif_avg = []
for s in srcs:
# print s['RAJ2000'], s['DEJ2000'], s['GLON'], s['GLAT']
src_lon.append(s['RAJ2000'])
src_lat.append(s['DEJ2000'])
labels.append(s['Source_Name'])
signif_avg.append(s['Signif_Avg'])
if im.axis(0)._coordsys == 'gal':
src_lon, src_lat = eq2gal(src_lon,src_lat)
# pixcrd = im.wcs.wcs_sky2pix(src_lon,src_lat, 0)
pixcrd = im.wcs.wcs_world2pix(src_lon,src_lat, 0)
# ax.autoscale(enable=False, axis='both')
# ax.set_autoscale_on(False)
for i in range(len(labels)):
if signif_avg[i] > label_threshold:
ax.text(pixcrd[0][i]+2.0,pixcrd[1][i]+2.0,labels[i],
color=src_color,size=8,clip_on=True)
if signif_avg[i] > marker_threshold:
ax.plot(pixcrd[0][i],pixcrd[1][i],
linestyle='None',marker='+',
color='g', markerfacecolor = 'None',
markeredgecolor=src_color,clip_on=True)
plt.gca().set_xlim(im.axis(0).lims())
plt.gca().set_ylim(im.axis(1).lims())
def plot(self,im,src_color='k',marker_threshold=0,
label_threshold=20., ax=None,radius_deg=10.0,
**kwargs):
if ax is None: ax = plt.gca()
min_radius_deg = kwargs.get('min_radius_deg',None)
fontweight = kwargs.get('fontweight','normal')
if im.axis(0)._coordsys == 'gal':
ra, dec = gal2eq(im.lon,im.lat)
else:
ra, dec = im.lon, im.lat
#srcs = cat.get_source_by_position(ra,dec,self._roi_radius_deg)
# Try to determine the search radius from the input file
srcs = self.get_source_by_position(ra,dec,radius_deg,
min_radius=min_radius_deg)
src_lon = []
src_lat = []
labels = []
signif_avg = []
for s in srcs:
# print s['RAJ2000'], s['DEJ2000'], s['GLON'], s['GLAT']
src_lon.append(s['RAJ2000'])
src_lat.append(s['DEJ2000'])
labels.append(s['Source_Name'])
signif_avg.append(s['Signif_Avg'])
if im.axis(0)._coordsys == 'gal':
src_lon, src_lat = eq2gal(src_lon,src_lat)
# pixcrd = im.wcs.wcs_sky2pix(src_lon,src_lat, 0)
pixcrd = im.wcs.wcs_world2pix(src_lon,src_lat, 0)
# ax.autoscale(enable=False, axis='both')
# ax.set_autoscale_on(False)
size = kwargs.get('size',8)
for i in range(len(labels)):
scale = (min(max(signif_avg[i],5.0),50.0)-5.0)/45.
mew = 1.0 + 1.0*scale
ms = 5.0 + 3.0*scale
mew = 1.0
ms = 5.0
mew = None
ms = None
if label_threshold is not None and signif_avg[i] > label_threshold:
ax.text(pixcrd[0][i]+2.0,pixcrd[1][i]+2.0,labels[i],
color=src_color,size=size,clip_on=True,
fontweight=fontweight)
if marker_threshold is not None and \
signif_avg[i] > marker_threshold:
ax.plot(pixcrd[0][i],pixcrd[1][i],
linestyle='None',marker='+',
color='g', markerfacecolor = 'None',#mew=mew,ms=ms,
markeredgecolor=src_color,clip_on=True)
plt.gca().set_xlim(im.axis(0).lims())
plt.gca().set_ylim(im.axis(1).lims())
def plot(self,
im,
src_color='k',
marker_threshold=0,
label_threshold=20.,
ax=None,
radius_deg=10.0,
**kwargs):
if ax is None: ax = plt.gca()
min_radius_deg = kwargs.get('min_radius_deg', None)
fontweight = kwargs.get('fontweight', 'normal')
if im.axis(0)._coordsys == 'gal':
ra, dec = gal2eq(im.lon, im.lat)
else:
ra, dec = im.lon, im.lat
#srcs = cat.get_source_by_position(ra,dec,self._roi_radius_deg)
# Try to determine the search radius from the input file
srcs = self.get_source_by_position(ra,
dec,
radius_deg,
min_radius=min_radius_deg)
src_lon = []
src_lat = []
labels = []
signif_avg = []
for s in srcs:
# print s['RAJ2000'], s['DEJ2000'], s['GLON'], s['GLAT']
src_lon.append(s['RAJ2000'])
src_lat.append(s['DEJ2000'])
labels.append(s['Source_Name'])
signif_avg.append(s['Signif_Avg'])
if im.axis(0)._coordsys == 'gal':
src_lon, src_lat = eq2gal(src_lon, src_lat)
# pixcrd = im.wcs.wcs_sky2pix(src_lon,src_lat, 0)
pixcrd = im.wcs.wcs_world2pix(src_lon, src_lat, 0)
# ax.autoscale(enable=False, axis='both')
# ax.set_autoscale_on(False)
for i in range(len(labels)):
scale = (min(max(signif_avg[i], 5.0), 50.0) - 5.0) / 45.
mew = 1.0 + 1.0 * scale
ms = 5.0 + 3.0 * scale
if label_threshold is not None and signif_avg[i] > label_threshold:
ax.text(pixcrd[0][i] + 2.0,
pixcrd[1][i] + 2.0,
labels[i],
color=src_color,
size=8,
clip_on=True,
fontweight=fontweight)
if marker_threshold is not None and \
signif_avg[i] > marker_threshold:
ax.plot(pixcrd[0][i],
pixcrd[1][i],
linestyle='None',
marker='+',
color='g',
markerfacecolor='None',
mew=mew,
ms=ms,
markeredgecolor=src_color,
clip_on=True)
plt.gca().set_xlim(im.axis(0).lims())
plt.gca().set_ylim(im.axis(1).lims())
