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add demo_QE notebook (and use NamedTuple for exps) #6

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add demo_QE notebook (and use NamedTuple for exps) #6

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add demo_QE notebook (and use NamedTuple for exps)
cmbant Nov 30, 2021
abf4b7a
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cmbant Nov 30, 2021
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295 changes: 295 additions & 0 deletions demo_QE.ipynb
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4 changes: 2 additions & 2 deletions demo_basics.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -239,9 +239,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.3"
"version": "3.9.6"
}
},
"nbformat": 4,
"nbformat_minor": 1
"nbformat_minor": 4
}
24 changes: 18 additions & 6 deletions lensit/__init__.py
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Expand Up @@ -5,6 +5,7 @@

import numpy as np
import os
from typing import NamedTuple

from lensit.ffs_covs import ffs_cov, ell_mat
from lensit.sims import ffs_phas, ffs_maps, ffs_cmbs
Expand Down Expand Up @@ -105,7 +106,7 @@ def get_maps_lib(exp, LDres, HDres=14, cache_lenalms=True, cache_maps=False,
Args:
exp: experimental configuration (see *get_config*)
LDres: the data is generated on a square patch with :math:` 2^{\rm LDres}` pixels on a side
HDres: The physical size of the path is :math:`\sim 0.74 \cdot 2^{\rm HDres}` arcmin
HDres: The physical size of the patch is :math:`\sim 0.74 \cdot 2^{\rm HDres}` arcmin
cache_lenalms: saves the lensed CMBs when produced for the first time (defaults to True)
cache_maps: saves the data maps when produced for the first time (defaults to False)
nsims: number of simulations in the library
Expand All @@ -115,7 +116,7 @@ def get_maps_lib(exp, LDres, HDres=14, cache_lenalms=True, cache_maps=False,
All simulations random phases (CMB sky and noise) will be generated at the very first call if not performed previously; this might take some time

"""
sN_uKamin, sN_uKaminP, Beam_FWHM_amin, ellmin, ellmax = get_config(exp)
name, sN_uKamin, sN_uKaminP, Beam_FWHM_amin, ellmin, ellmax = get_config(exp)
len_cmbs = get_lencmbs_lib(res=HDres, cache_sims=cache_lenalms, nsims=nsims)
lmax_sky = len_cmbs.lib_skyalm.ellmax
cl_transf = gauss_beam(Beam_FWHM_amin / 60. * np.pi / 180., lmax=lmax_sky)
Expand All @@ -133,7 +134,7 @@ def get_maps_lib(exp, LDres, HDres=14, cache_lenalms=True, cache_maps=False,
for _i, idx in enumerate_progress(np.arange(nsims), label='Generating Noise phases'):
pixpha.get_sim(idx)
pbs.barrier()
sims_libdir = os.path.join(_get_lensitdir()[0], 'temp', '%s_sims'%nsims,'fsky%04d'%fsky, 'res%s'%LDres,'%s'%exp, 'maps')
sims_libdir = os.path.join(_get_lensitdir()[0], 'temp', '%s_sims'%nsims,'fsky%04d'%fsky, 'res%s'%LDres,'%s'%name, 'maps')
return ffs_maps.lib_noisemap(sims_libdir, lib_datalm, len_cmbs, cl_transf, nTpix, nPpix, nPpix,
pix_pha=pixpha, cache_sims=cache_maps)

Expand All @@ -149,7 +150,7 @@ def get_isocov(exp, LD_res, HD_res=14, pyFFTWthreads=int(os.environ.get('OMP_NUM

"""
ellmax_sky = 6000
sN_uKamin, sN_uKaminP, Beam_FWHM_amin, ellmin, ellmax = get_config(exp)
name, sN_uKamin, sN_uKaminP, Beam_FWHM_amin, ellmin, ellmax = get_config(exp)
cls_unl, cls_len = get_fidcls(ellmax_sky=ellmax_sky)

cls_noise = {'t': (sN_uKamin * np.pi / 180. / 60.) ** 2 * np.ones(ellmax_sky + 1),
Expand All @@ -161,15 +162,26 @@ def get_isocov(exp, LD_res, HD_res=14, pyFFTWthreads=int(os.environ.get('OMP_NUM
lib_skyalm = ell_mat.ffs_alm_pyFFTW(get_ellmat(LD_res, HD_res=HD_res),
filt_func=lambda ell: (ell <= ellmax_sky), num_threads=pyFFTWthreads)

lib_dir = os.path.join(_get_lensitdir()[0], 'temp', 'Covs', '%s' % exp, 'LD%sHD%s' % (LD_res, HD_res))
lib_dir = os.path.join(_get_lensitdir()[0], 'temp', 'Covs', '%s' % name, 'LD%sHD%s' % (LD_res, HD_res))
return ffs_cov.ffs_diagcov_alm(lib_dir, lib_alm, cls_unl, cls_len, cl_transf, cls_noise, lib_skyalm=lib_skyalm)


class ExptConfig(NamedTuple):
name: str
sN_uKamin: float
sN_uKaminP: float
Beam_FWHM_amin: float
ellmin: float
ellmax: float


def get_config(exp):
"""Returns noise levels, beam size and multipole cuts for some configurations

"""
if isinstance(exp, ExptConfig):
return exp

sN_uKaminP = None
if exp == 'Planck':
sN_uKamin = 35.
Expand Down Expand Up @@ -228,4 +240,4 @@ def get_config(exp):
ellmax = 0
assert 0, '%s not implemented' % exp
sN_uKaminP = sN_uKaminP or np.sqrt(2.) * sN_uKamin
return sN_uKamin, sN_uKaminP, Beam_FWHM_amin, ellmin, ellmax
return ExptConfig(exp, sN_uKamin, sN_uKaminP, Beam_FWHM_amin, ellmin, ellmax)