def plot_contours(proportions, samples):
r''' Plot containment contour around desired level.
E.g 90% containment of a PDF on a healpix map
Parameters:
-----------
proportions: list
list of containment level to make contours for.
E.g [0.68,0.9]
samples: array
array of values read in from healpix map
E.g samples = hp.read_map(file)
Returns:
--------
theta_list: list
List of arrays containing theta values for desired contours
phi_list: list
List of arrays containing phi values for desired contours
'''
levels = []
t0 = time()
sorted_samples = list(reversed(list(sorted(samples))))
t1 = time()
nside = hp.pixelfunc.get_nside(samples)
sample_points = np.array(hp.pix2ang(nside, np.arange(len(samples)))).T
for proportion in proportions:
level_index = (np.cumsum(sorted_samples) >
proportion).tolist().index(True)
level = (sorted_samples[level_index] +
(sorted_samples[level_index + 1]
if level_index + 1 < len(samples) else 0)) / 2.0
levels.append(level)
msk = samples != 0
samples = samples[msk]
sample_points = sample_points[msk]
contours_by_level = meander.spherical_contours(sample_points, samples,
levels)
theta_list = []
phi_list = []
for contours in contours_by_level:
for contour in contours:
theta, phi = contour.T
phi[phi < 0] += 2.0 * np.pi
theta_list.append(theta)
phi_list.append(phi)
return theta_list, phi_list
def compute_contours(proportions, samples):
"""Plot containment contour around desired level. E.g 90% containment of a
PDF on a healpix map.
Parameters:
-----------
proportions: list
list of containment level to make contours for.
E.g [0.68,0.9]
samples: array
array of values read in from healpix map
E.g samples = hp.read_map(file)
Returns:
--------
ra_list: list
List of arrays containing RA values for desired contours [deg].
dec_list: list
List of arrays containing Dec values for desired contours [deg].
"""
levels = []
sorted_samples = list(reversed(list(sorted(samples))))
nside = hp.pixelfunc.get_nside(samples)
sample_points = np.array(hp.pix2ang(nside, np.arange(len(samples)))).T
for proportion in proportions:
level_index = (np.cumsum(sorted_samples) >
proportion).tolist().index(True)
level = (sorted_samples[level_index] +
(sorted_samples[level_index + 1]
if level_index + 1 < len(samples) else 0)) / 2.0
levels.append(level)
contours_by_level = meander.spherical_contours(sample_points, samples,
levels)
ra_list = []
dec_list = []
for contours in contours_by_level:
for contour in contours:
theta, phi = contour.T
phi[phi < 0] += 2.0 * np.pi
dec_list.append(90 - np.degrees(theta))
ra_list.append(np.degrees(phi))
return ra_list, dec_list
def compute_contours(proportions, samples, nside=64):
''' Compute containment contour around desired level.
'''
try:
import meander
except:
return
# binnned map to lower resolution in order to save time
samples = hp.pixelfunc.ud_grade(samples, nside)
samples = samples / np.sum(samples)
levels = []
sorted_samples = list(reversed(list(sorted(samples))))
nside = hp.pixelfunc.get_nside(samples)
sample_points = np.array(hp.pix2ang(nside, np.arange(len(samples)))).T
for proportion in proportions:
level_index = (np.cumsum(sorted_samples) > \
proportion).tolist().index(True)
level = (sorted_samples[level_index] + \
(sorted_samples[level_index+1] \
if level_index+1 < len(samples) else 0)) / 2.0
levels.append(level)
contours_by_level = meander.spherical_contours(sample_points, samples,
levels)
theta_list = {}
phi_list = {}
for cc, contours in enumerate(contours_by_level):
_cnt = proportions[cc]
try:
theta_list[_cnt]
phi_list[_cnt]
except:
theta_list[_cnt] = []
phi_list[_cnt] = []
for contour in contours:
theta, phi = contour.T
phi[phi < 0] += 2.0 * np.pi
theta_list[_cnt].append(theta)
phi_list[_cnt].append(phi)
return theta_list, phi_list
