def skyplot(crec, title='', axes=None, fignum=30, ait_kw={}, **kwargs):
""" make an AIT skyplot of a HEALpix array
crec : array
must be sorted according to the HEALpix index
title : string
set the figure title
ait_kw : dict
to set kwargs for image.AIT, perhaps pixelsize
Other args passed to imshow
"""
n = len(crec)
nside = int(np.sqrt(n/12))
assert n==12*nside**2, 'wrong length to be healpix array'
band = Band(nside)
def skyplotfun(v):
skydir = SkyDir(Hep3Vector(v[0],v[1],v[2]))
index = band.index(skydir)
return crec[index]
if axes is None:
plt.close(fignum)
fig = plt.figure(fignum, figsize=(12,6))
ait=image.AIT(PySkyFunction(skyplotfun) ,axes=axes, **ait_kw)
ait.imshow(title=title, **kwargs)
return ait
def plot(self, title='', axes=None, fignum=30, ait_kw={}, **kwargs):
""" make an AIT skyplot from the array
title : string
set the figure title
ait_kw : dict
to set kwargs for image.AIT, perhaps pixelsize
Other args passed to imshow, for example norm: to make a log plot,
from matplotlib.colors import LogNorm
plot(norm=LogNorm(vmin=1,vmax=10))
It returns a image.AIT object, which has a colorbar member that can be adjusted.
"""
cbtext = kwargs.pop('cbtext', '')
ait_kw.update(cbtext=cbtext)
band = Band(self.nside)
def skyplotfun(v):
skydir = SkyDir(Hep3Vector(v[0], v[1], v[2]))
return self(skydir)
if axes is None:
plt.close(fignum)
fig = plt.figure(fignum, figsize=(12, 6))
axes = plt.gca()
ait = image.AIT(PySkyFunction(skyplotfun), axes=axes, **ait_kw)
ait.imshow(title=title, **kwargs)
return ait
def plot(self, title=None, axes=None, fignum=30, ait_kw={}, log=False, **kwargs):
""" make an AIT skyplot from the array
title : string
set the figure title. If None, use the name
ait_kw : dict
to set kwargs for image.AIT, perhaps pixelsize
Other args passed to imshow, for example norm: to make a log plot,
from matplotlib.colors import LogNorm
plot(norm=LogNorm(vmin=1,vmax=10))
It returns a image.AIT object, which has a colorbar member that can be adjusted.
"""
cbtext = kwargs.pop('cbtext', '')
if log:
vmin=kwargs.pop('vmin', None)
vmax=kwargs.pop('vmax', None)
kwargs['norm']=LogNorm(vmin=vmin,vmax=vmax)
ait_kw.update(cbtext=cbtext)
band = Band(self.nside)
def skyplotfun(v):
skydir = SkyDir(Hep3Vector(v[0],v[1],v[2]))
return self(skydir)
if axes is None:
plt.close(fignum)
fig = plt.figure(fignum, figsize=(12,6))
axes = plt.gca()
else:
fig = axes.figure
ait=image.AIT(PySkyFunction(skyplotfun) ,axes=axes, **ait_kw)
ait.imshow( **kwargs)
axes.set_title(self.name if title is None else title, loc='left')
fig.set_facecolor('white')
return ait
def make_3panel(self,
center,
size=10,
pixelsize=0.02,
galactic=False,
scale=1,
label_1FGL=True,
labels=None,
separate_figures=False,
fignum_base=10):
import pylab as P
from matplotlib.colorbar import ColorbarBase
from matplotlib.colors import Normalize
from uw.utilities.image import ZEA
cmap = P.cm.jet
cmap.set_bad('white')
if separate_figures:
axes = []
for i in xrange(1, 4):
P.figure(i + fignum_base)
axes += [P.gca()]
else:
axes = [P.subplot(1, 3, i) for i in xrange(1, 4)]
zeas = [
ZEA(center,
size=size,
pixelsize=pixelsize,
galactic=galactic,
axes=ax) for ax in axes
]
mods = [1, 2, 0]
for i in xrange(0, 3):
self.set_mode(mods[i])
zeas[i].fill(PySkyFunction(self))
zeas[i].grid()
axes[i].imshow(zeas[i].image**(0.5 if scale else 1), cmap=cmap)
if label_1FGL:
names, skydirs = self.get_1FGL_sources(zeas[0])
for na, sd in zip(names, skydirs):
for z in zeas:
z.plot_source(na, sd, color='white')
if labels is not None:
names, skydirs = labels
for na, sd in zip(names, skydirs):
for z in zeas:
z.plot_source(na, sd, color='white')
if separate_figures:
# basically a "show"
for i in xrange(1, 4):
P.figure(i + fignum_base)
axes[i - 1].set_autoscale_on(True)
cb = ColorbarBase(axes[i - 1],
orientation='vertical',
cmap=cmap)
#P.colorbar()
return axes, zeas
def plot_tsmap(roi,
name=None,
center=None,
size=0.5,
pixelsize=None,
outdir=None,
which=0,
catsig=99,
axes=None,
fignum=99,
bandfits=True,
galmap=True,
galactic=False,
assoc=None,
notitle=False,
nolegend=False,
markercolor='blue',
markersize=12,
primary_markercolor='green',
primary_markersize=14,
**kwargs):
""" create a TS map for the source. These are localization style
TS maps (where the source is not in the background model) and
are useful for source localization.
roi: an ROIAnalsyis object
Optional keyword arguments:
========= =======================================================
Keyword Description
========= =======================================================
name [None] -- provide name for title, and to save figure if outdir set
center [None] -- center, default the roi center
outdir [None] if set, save sed into <outdir>/<source_name>_tsmap.png if outdir is a directory, save into filename=<outdir> if not.
catsig [99] -- if set and less than 1.0, draw cross with this size (degrees)
size [0.5] -- width=height (deg)
pixelsize [None] -- if not set, will be 20 x20 pixels
galmap [True] -- if set, draw a galactic coordinate image with the source position shown
galactic [False] -- plot using galactic coordinates
which [0] -- chose a different source in the ROI to plot
can be an index for point sources, or a name to also get extended sources
assoc [None] -- if set, a list of tuple of associated sources
notitle [False] -- set to turn off (allows setting the current Axes object title)
nolegend [False]
markersize [12] -- set 0 to not plot nearby sources in the model
markercolor [blue]
========= =======================================================
returns the image.TSplot object for plotting positions, for example
"""
kwargs = {} #fix later
localizer = roi_localize.localizer(roi, which, bandfits=bandfits)
tsm = PySkyFunction(localizer)
sdir = center if center is not None else roi.roi_dir
if axes is None:
plt.figure(fignum, figsize=(5, 5))
plt.clf()
tsp = image.TSplot(tsm,
sdir,
size,
pixelsize=pixelsize if pixelsize is not None else size /
20.,
axes=axes,
galactic=galactic,
galmap=galmap,
**kwargs)
if 'qform' in roi.__dict__ and roi.qform is not None:
sigma = math.sqrt(roi.qform.par[3] *
roi.qform.par[4]) # why do I need this?
qual = roi.qform.par[6]
if sigma < 1 and qual < 50:
tsp.overplot(roi.qform, sigma)
else:
print 'bad fit sigma %g, >1 or qual %.1f >50' % (sigma, qual)
tsp.show(colorbar=False)
if catsig < 1:
tsp.cross(sdir, catsig, lw=2, color='grey')
# plot the primary source, any nearby from the fit
x, y = tsp.zea.pixel(sdir)
tsp.zea.axes.plot([x], [y],
'*',
color=primary_markercolor,
label=name,
markersize=primary_markersize)
marker = 'ov^<>1234sphH'
i = k = 0
if markersize != 0:
for ps in roi.psm.point_sources: # skip
x, y = tsp.zea.pixel(ps.skydir)
if ps.name == name or x < 0 or x > tsp.zea.nx or y < 0 or y > tsp.zea.ny:
continue
tsp.zea.axes.plot([x], [y],
marker[k % 12],
color=markercolor,
label=ps.name,
markersize=markersize)
k += 1
tsp.plot(tsp.tsmaxpos, symbol='+', color='k') # at the maximum
if not notitle: plt.title(name, fontsize=24)
if assoc is not None:
# eventually move this to image.TSplot
last_loc, i = SkyDir(0, 90), 0
for aname, loc, prob, catid in zip(assoc['name'], assoc['dir'],
assoc['prob'], assoc['cat']):
#print 'associate with %s, prob=%.2f' % (aname.strip(),prob)
if catid in ('ibis', ):
print '---skip gamma cat %s' % catid
continue
if i > 8:
print '---skip because too many for display'
continue
x, y = tsp.zea.pixel(loc)
diff = np.degrees(loc.difference(last_loc))
last_loc = loc
if diff > 1e-3: k += 1 # new marker only if changed place
tsp.zea.axes.plot([x], [y],
marker=marker[k % 12],
color='green',
linestyle='None',
label='%s[%s] %.2f' %
(aname.strip(), catid, prob),
markersize=markersize)
i += 1
fs = plt.rcParams['font.size']
plt.rcParams.update({'legend.fontsize': 7, 'font.size': 7})
# put legend on left.
if not nolegend:
tsp.zea.axes.legend(loc=2, numpoints=1, bbox_to_anchor=(-0.15, 1.0))
plt.rcParams['font.size'] = fs
if outdir is not None:
if os.path.isdir(outdir):
plt.savefig(os.path.join(outdir, '%s_tsmap.png' % name.strip()))
else:
plt.savefig(outdir)
return tsp
def get_pyskyfun(self):
return PySkyFunction(self)
def make_zea(self, center, size=10, pixelsize=0.02, galactic=False):
z = ZEA(center, size=size, pixelsize=pixelsize, galactic=galactic)
z.fill(PySkyFunction(self))
self.z = z
def make_map(self,
center,
size=10,
pixelsize=0.02,
galactic=False,
axes=None,
scale=1,
thresh_low=0,
thresh_high=np.inf,
label_1FGL=True,
mode=1,
cmap=None,
log_transform=False,
labels=None):
"""
scale : 0 == linear, 1 == sqrt
"""
import pylab as P
from uw.utilities.image import ZEA
from matplotlib.colorbar import ColorbarBase
from matplotlib.colors import Normalize
self.set_mode(mode)
if axes is None: axes = P.gca()
cmap = cmap or P.cm.jet
cmap.set_bad('white')
z = ZEA(center,
size=size,
pixelsize=pixelsize,
galactic=galactic,
axes=axes)
z.fill(PySkyFunction(self))
im = z.image.copy()
print 'Max Value: %.2f' % (im.max())
im[im < thresh_low] = np.nan
im[im > thresh_high] = thresh_high
z.grid()
im = im**(0.5 if scale else 1)
if log_transform:
im[im < 1] = 1
im = np.log10(im)
P.imshow(im, cmap=cmap)
#P.colorbar(ax=axes,cmap=cmap,orientation='horizontal')
#P.contour(im,np.asarray([9,16,25,50,100,1000])**(0.5 if scale else 1))
#P.contour(im,10)
#contours = np.asarray([9,16,25,36,49,64,81,100,225,400,625,900,1225,1600])**(0.5 if scale else 1)
#if log_transform: contours = np.log10(contours)
#P.contour(im,contours)
if label_1FGL:
names, skydirs = self.get_1FGL_sources(z)
for na, sd in zip(names, skydirs):
z.plot_source(na,
sd,
color='gray' if thresh_low > 0 else 'white')
if labels is not None:
try:
names, skydirs = labels
except:
skydirs = labels
names = ['S%d' % (i) for i in xrange(len(labels))]
for na, sd in zip(names, skydirs):
z.plot_source(na,
sd,
color='gray' if thresh_low > 0 else 'white')
return z
def make_zea(self, center, size=10, pixelsize=0.02, galactic=False):
from uw.utilities.image import ZEA
z = ZEA(center, size=size, pixelsize=pixelsize, galactic=galactic)
z.fill(PySkyFunction(self))
self.z = z
