Maximum Likelihood Estimation Module

bin_from_edges(start, end)[source]
Parameters:
Return type:

Tuple

bin_configuration(info)[source]
Parameters:

info (Tuple)

Return type:

Tuple

bin_spec_matrix(spec, info)[source]
Parameters:
Return type:

ndarray

bin_cov_matrix(cov, info)[source]
Parameters:
Return type:

ndarray

class MLE(libdir, spec_lib, fit, alpha_per_split=False, rm_same_tube=False, binwidth=20, bmin=51, bmax=1000, verbose=True, avoid_spectra=None)[source]

Bases: object

Parameters:

avoid_spectra (List[str] | None)

FIT_OPTIONS = ['alpha', 'Ad + alpha', 'As + Ad + alpha', 'As + Asd + Ad + alpha', 'beta + alpha', 'Ad + beta + alpha', 'As + Ad + beta + alpha', 'As + Asd + Ad + beta + alpha']
__init__(libdir, spec_lib, fit, alpha_per_split=False, rm_same_tube=False, binwidth=20, bmin=51, bmax=1000, verbose=True, avoid_spectra=None)[source]
Parameters:

avoid_spectra (List[str] | None)

calculate(idx, return_result=False)[source]
Parameters:
Return type:

Any

estimate_angles(idx, overwrite=False, Niter=-1, to_degrees=True)[source]
Parameters:
Return type:

Dict

result_name(idx)[source]

Binning Functions

bin_from_edges(start, end)[source]
Parameters:
Return type:

Tuple

bin_configuration(info)[source]
Parameters:

info (Tuple)

Return type:

Tuple

bin_spec_matrix(spec, info)[source]
Parameters:
Return type:

ndarray

bin_cov_matrix(cov, info)[source]
Parameters:
Return type:

ndarray

Result Class

class _Result(spec, fit, sim_idx, alpha_per_split, rm_same_tube, binwidth, bmin, bmax, bands, freqs)[source]
__init__(spec, fit, sim_idx, alpha_per_split, rm_same_tube, binwidth, bmin, bmax, bands, freqs)[source]

MLE Class

class MLE(libdir, spec_lib, fit, alpha_per_split=False, rm_same_tube=False, binwidth=20, bmin=51, bmax=1000, verbose=True, avoid_spectra=None)[source]
Parameters:

avoid_spectra (List[str] | None)

FIT_OPTIONS = ['alpha', 'Ad + alpha', 'As + Ad + alpha', 'As + Asd + Ad + alpha', 'beta + alpha', 'Ad + beta + alpha', 'As + Ad + beta + alpha', 'As + Asd + Ad + beta + alpha']
__init__(libdir, spec_lib, fit, alpha_per_split=False, rm_same_tube=False, binwidth=20, bmin=51, bmax=1000, verbose=True, avoid_spectra=None)[source]
Parameters:

avoid_spectra (List[str] | None)

calculate(idx, return_result=False)[source]
Parameters:
Return type:

Any

estimate_angles(idx, overwrite=False, Niter=-1, to_degrees=True)[source]
Parameters:
Return type:

Dict

_setup_indexing()[source]
_process_cls(incls)[source]
Parameters:

incls (Dict)

_build_cov(niter, res)[source]
_solve_linear_system(invcov, niter, res)[source]
_summation(v_ij, v_pq, invcov_T)[source]
_compute_linear_system_terms(invcov)[source]
_IND_TERM_CONFIG = {'Ad': <function MLE.<lambda>>, 'alpha': <function MLE.<lambda>>, 'beta': <function MLE.<lambda>>}
_SYSTEM_MATRIX_CONFIG = {('Ad', 'Ad'): <function MLE.<lambda>>, ('Ad', 'alpha'): <function MLE.<lambda>>, ('Ad', 'beta'): <function MLE.<lambda>>, ('alpha', 'alpha'): <function MLE.<lambda>>, ('beta', 'alpha'): <function MLE.<lambda>>, ('beta', 'beta'): <function MLE.<lambda>>}
_convolve_gaussBeams_pwf(mode, fwhm1, fwhm2, lmax)[source]
_C_cmb()[source]
_C_oxo(EiEjo, BiBjo, EiBjo, BiEjo)[source]
_C_fgxfg(EiEj, BiBj, EiBj, BiEj)[source]
_C_fgxo(Eifg_Ejo, Bifg_Bjo, Eifg_Bjo, Bifg_Ejo)[source]
_get_alpha_blocks(niter, res)[source]
_get_ml_alphas(niter, res, add_beta=False)[source]
result_name(idx)[source]