smica.component.SourceAmpl Class Reference

Inheritance diagram for smica.component.SourceAmpl:

Public Member Functions
def	__init__
def	is_astro
def	set_ampl
def	set_powspec
def	powspec
def	ampl
def	get_dim
def	set_theta
def	get_theta
def	score_powspec
def	get_thetascore
def	get_thetaroot
def	get_thetafim
def	close_form
Public Member Functions inherited from smica.component.Source
def	is_astro
def	set_dim
def	__init__
def	set_mixmat
def	fix_mixmat
def	set_powspec
def	fix_powspec
def	mixmat
def	powspec
def	autopowspec
def	covariance
def	score_mixmat
def	score_powspec
def	plot_mixmat
def	plot_powspec
Public Member Functions inherited from smica.component.Component
def	plot_power
def	plot_em
def	set_gaussian_prior
def	get_penalty
def	get_score_penalty
def	get_fim_penalty

Public Attributes
	ndet
	nbin
	name
	offset
Public Attributes inherited from smica.component.Source
	dim
	ndet
	nbin
	name
Public Attributes inherited from smica.component.Component
	mu
	sigma_inv

Detailed Description

A one dimensional source component of fixed shape.

The mixing matrix is a column vector (ndet, 1) and power spectrum
is described by a vector (1, nbin) multiply by a constant factor.
This factor is considered as the only free parameter for power
spectrum.

Constructor & Destructor Documentation

def smica.component.SourceAmpl.__init__	(		self,
			ndet,
			nbin,
			name = None,
			offset = None
	)

Initialize component parameters arrays.

Parameters
----------
ndet : number of detectors
nbin : number of bins
name : name of the component

Member Function Documentation

def smica.component.SourceAmpl.ampl

(

self)

Return scalar factor ampl.

Returns
-------
ampl : scalar.

def smica.component.SourceAmpl.close_form	(		self,
			stats,
			N
	)

Update local parameters (ie power spectra array) using a close form algorithm.

Parameters
----------
stats : array-like, shape (ndet, ndet, nbin).
Second order statistics ie empirical covariance matrices of
the observations.
N : array-like, shape (ndet, ndet, nbin).
Covariance matrices of the model deprived from the
contribution of the component.

def smica.component.SourceAmpl.get_dim

(

self)

Return the number of free parameters of the component.

def smica.component.SourceAmpl.get_theta	(		self,
			mixmat = None,
			ampl = None
	)

Return component parameters as a vector.

Parameters
----------
mixmat : array-like, shape (ndet, 1).
If None, values are read from inner mixing matrix.
ampl : array-like, shape (1,1).
If None, values are read from inner amplitude scalar value.

Returns
----------
array-like, shape (N, 1), where N is the number of free parameters.

def smica.component.SourceAmpl.get_thetafim	(		self,
			iRr,
			w
	)

Return Fisher Information Matrix.

Parameters
----------
iRr : array-like, shape (ndet, ndet, nbin).
iRr is the square root of the inverse of the covariance of the
model, which is constant for all components.
w : array-like, shape (1, nbin). w is the number of modes for each bin.

Returns
----------
array-like, shape (N, N), where N is the number of free parameters.

def smica.component.SourceAmpl.get_thetaroot	(		self,
			iRr,
			bin = 0
	)

Return root contribution to the Fisher Information Matrix for a given bin.

Parameters
----------
iRr : array-like, shape (ndet, ndet).
iRr is the square root of the inverse of the covariance of the
model, which is constant for all components.
bin : int, bin number

Returns
----------
array-like, shape (mxm, N), where N is the number of free parameters.

def smica.component.SourceAmpl.get_thetascore	(		self,
			D
	)

Return likelihood first derivative values wrt component
parameters as a vector.

Parameters
----------
D : array-like, shape (ndet, ndet, nbin).
D is the first derivative of the likelihood wrt the covariance
of the model, which is constant for all components.

Returns
----------
array-like, shape (N, 1), where N is the number of free parameters.

def smica.component.SourceAmpl.powspec	(		self,
			bin = None
	)

Return power spectra array (multiply by factor ampl).

Parameters
----------
bin : bin number. If None, complete array is returned.

Returns
-------
array, shape (dim, dim, nbin).

def smica.component.SourceAmpl.score_powspec	(		self,
			D
	)

Return first derivative of the likelihood wrt power
spectra parameters (ie scalar factor ampl).

Parameters
----------
D : array-like, shape (ndet, ndet, nbin).
D is the first derivative of the likelihood wrt the covariance
of the model, which is constant for all components.

Returns
-------
array, shape (1,1).
The score of fixed parameters is set to zero.

def smica.component.SourceAmpl.set_ampl	(		self,
			ampl,
			fixed = None
	)

Set amplitude value.

Parameters
----------
ampl : scalar.
fixed : scalar.
If not equal to zero, fixes the parameters ampl.
It is also possible to use keywords 'all' and
'null' to fix (respectively) all parameters or none.

def smica.component.SourceAmpl.set_powspec	(		self,
			powspec,
			bin = None,
			fixed = None
	)

Set power spectra array.

Parameters
----------
powspec : array-like, shape (dim, dim, nbin).
bin : bin number. If None, all bins are set.
fixed : array-like, shape (dim, dim, nbin)
Entries which are not equal to zero point to
fixed indices.  It is also possible to use keywords 'all' and
'null' to fix (respectively) all parameters or none.

def smica.component.SourceAmpl.set_theta	(		self,
			theta
	)

Set new values for component parameters.

Parameters
----------
theta : array-like, shape (N, 1), where N is the number of free parameters.

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The documentation for this class was generated from the following file:

• smica/component.py