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estcl.py
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estcl.py
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'''
Estimation of Cl.
'''
import pymaster as nmt
import numpy as np
import healpy as hp
import collections
import sys
import time
class estcl:
'''Estimation of Cl, w/ PyMaster or Healpy.'''
def __init__(self, nside, fields):
# maps and masks
self.fields = collections.OrderedDict() # map & mask
self.nside = nside # nside for all the maps and masks
for fld in fields:
self.fields[fld] = collections.OrderedDict()
# bandpower settings
self.bps = collections.OrderedDict()
# bins, two columns [lmin, lmax], closed on both sides.
self.bps['bins'] = None
self.bps['ells'] = None
self.bps['elle'] = None # effective ell
self.bps['lerr'] = None # ell err
self.bps['ibpws'] = None # index of bandpower for each ell
self.bps['weights'] = None # weight of each cl over bin
self.bps['b'] = None # pymaster bin file
# power spectrum related
self.cls = collections.OrderedDict()
# PyMaster workspace
self.wsps = collections.OrderedDict() # only depends on the mask
def add_field(self, fields):
'''Add fields.'''
for fld in fields:
self.fields[fld] = collections.OrderedDict()
def read_map(self, fields, fmaps):
'''Read maps for fields.'''
for i, field in enumerate(fields):
print('>> field: {0:s}'.format(field))
print('> map {0:s}'.format(fmaps[i]))
self.fields[field]['map'] = hp.read_map(
fmaps[i], dtype=None).astype(np.float64)
# check nside
if hp.get_nside(self.fields[field]['map']) != self.nside:
sys.exit('!! exit: nside does not match !!')
def read_mask(self, fields, fmasks):
'''Read masks for fields.'''
for i, field in enumerate(fields):
print('>> field: {0:s}'.format(field))
print('> mask {0:s}'.format(fmasks[i]))
self.fields[field]['mask'] = hp.read_map(
fmasks[i], dtype=None).astype(np.float64)
# check nside
if hp.get_nside(self.fields[field]['mask']) != self.nside:
sys.exit('!! exit: nside does not match !!')
def ini_bins(self, bins, weight_m=0, cal_nmt_bin=True):
'''Initialize bins.'''
if type(bins) == np.ndarray:
self.bps['bins'] = bins
elif type(bins) == str:
# read the bins, two columns [lmin, lmax], closed on both sides
print('>> Loading bin file: {0:s}'.format(bins))
self.bps['bins'] = np.loadtxt(bins, dtype=np.int)
else:
sys.exit('!! no bins or fb')
print('>> Bins initialized.')
# generate the bandpower index and weight of each Cl
ells = np.arange(self.bps['bins'][0, 0], self.bps['bins'][-1, -1] + 1,
dtype=np.int)
self.bps['ells'] = ells
self.bps['ibpws'] = -1 + np.zeros_like(ells, dtype=np.int)
self.bps['weights'] = np.zeros_like(ells, dtype=np.float)
# set the effective ell at the mean ell
self.bps['elle'] = np.mean(self.bps['bins'], axis=1)
self.bps['lerr'] = (self.bps['bins'][:, 1] -
self.bps['bins'][:, 0] + 1) / 2.
for i, bb in enumerate(self.bps['bins']):
idx = np.where((ells >= bb[0]) & (ells <= bb[1]))[0]
self.bps['ibpws'][idx] = i
if weight_m == 0: # uniform
w_, w_e = 1., 1.
elif weight_m == 1: # ell
w_, w_e = ells[idx], self.bps['elle'][i]
elif weight_m == 2: # ell*(ell+1)
w_ = ells[idx] * (1. + ells[idx])
w_e = self.bps['elle'][i] * (self.bps['elle'][i] + 1)
else:
sys.exit('!! exit: wrong weight_m !!')
self.bps['weights'][idx] = w_ / w_e / idx.shape[0]
if cal_nmt_bin:
self.bps['b'] = nmt.NmtBin(self.nside, bpws=self.bps['ibpws'],
ells=self.bps['ells'], weights=self.bps['weights'])
def write_bins(self, fo):
'''Output the bandpower bins information.'''
header = 'ell bandpower weight'
data = np.column_stack((self.bps['ells'], self.bps['ibpws'],
self.bps['weights']))
fmt = '%5d %5d %15.7e'
np.savetxt(fo, data, header=header, fmt=fmt)
print(':: Bins written to: {0:s}'.format(fo))
def have_cl(self, cl):
'''Check if Cl is in self.cls.'''
return cl in self.cls.keys()
def have_fld(self, fld):
'''Check if fld is in self.fields.'''
return fld in self.fields.keys()
def have_wsp(self, wsp):
'''Check if wsp is in self.wsps.'''
return wsp in self.wsps.keys()
def est_nmt(self, f1, f2, cl_label, re=False, save_wsp=False, rc_wsp=True):
'''Estimate w/ PyMaster, f1 & f2(f1) cross(auto) Cl.'''
print('>> Estimating {0:s} with PyMaster...'.format(cl_label))
t0 = time.time()
# check f1 & f2
if not self.have_fld(f1) or not self.have_fld(f2):
sys.exit('!! exit: no such field !!')
fld1 = nmt.NmtField(self.fields[f1]['mask'],
[self.fields[f1]['map']])
if f2 == f1: # auto
fld2 = fld1
else: # cross
fld2 = nmt.NmtField(self.fields[f2]['mask'],
[self.fields[f2]['map']])
if rc_wsp or not self.have_wsp(f1+f2):
w = nmt.NmtWorkspace()
print('> computing coupling matrix')
if self.bps['b'] is None:
self.bps['b'] = nmt.NmtBin(self.nside, bpws=self.bps['ibpws'],
ells=self.bps['ells'], weights=self.bps['weights'])
w.compute_coupling_matrix(fld1, fld2, self.bps['b'])
if save_wsp:
self.wsps[f1+f2] = w
else: # if masks not changed
w = self.wsps[f1+f2]
print('> computing coupled cl')
cl_coupled = nmt.compute_coupled_cell(fld1, fld2)
print('> decoupling cl')
cl_decoupled = w.decouple_cell(cl_coupled)[0]
self.cls[cl_label] = cl_decoupled
print('<< time elapsed: {0:.2f} s'.format(time.time()-t0))
if re:
return cl_decoupled
def est_hp(self, f1, f2, cl_label, apply_mask=True, re=False):
'''Estimate w/ Healpy, f1 & f2(f1) cross(auto) Cl.'''
print('>> Estimating {0:s} with Healpy...'.format(cl_label))
t0 = time.time()
# check f1 & f2
if not self.have_fld(f1) or not self.have_fld(f2):
sys.exit('!! exit: no such field !!')
auto = True if f1 == f2 else False # auto or cross
# get fsky of overlapped mask
fsky = np.mean(self.fields[f1]['mask'] * self.fields[f2]['mask'])
print('> fsky = {0:f}'.format(fsky))
if apply_mask: # explicitly apply mask on the map
map1 = self.fields[f1]['mask'] * self.fields[f1]['map']
if not auto:
map2 = self.fields[f2]['mask'] * self.fields[f2]['map']
else:
map1 = self.fields[f1]['map']
if not auto:
map2 = self.fields[f2]['map']
lmin, lmax = self.bps['ells'][0], self.bps['ells'][-1]
if auto:
cl = hp.anafast(map1, lmax=lmax)[lmin:] / fsky
else:
cl = hp.anafast(map1, map2, lmax=lmax)[lmin:] / fsky
# binning
nbins = self.bps['bins'].shape[0]
cl_b = np.zeros(nbins)
for i in range(nbins):
idx = self.bps['ibpws'] == i
cl_b[i] = np.sum(self.bps['weights'][idx] * cl[idx])
self.cls[cl_label] = cl_b
print('<< time elapsed: {0:.2f} s'.format(time.time()-t0))
if re:
return cl_b
def get_cl(self, cl_label):
'''Return the Cl.'''
if not self.have_cl(cl_label):
sys.exit('!! exit: no such cl : {0:s}'.format(cl_label))
return self.cls[cl_label]
@property
def eff_ells(self):
'''Return the effective ells.'''
return self.bps['elle']
@property
def bins_half_width(self):
'''Return the half bin width.'''
return self.bps['lerr']
def write_cl(self, fo, cl_label):
'''Write Cls to file.'''
if not self.have_cl(cl_label):
sys.exit('!! exit: no such cl : {0:s}'.format(cl_label))
header = 'ell {0:s} xerr'.format(cl_label)
fmt = '%10g %23.15e %10g'
data = np.column_stack((self.bps['elle'], self.cls[cl_label],
self.bps['lerr']))
np.savetxt(fo, data, header=header, fmt=fmt)