Detailed Description

Collection of commonly used Prior functions and utilities.

Prototypes
void	LALInferenceInitCBCPrior (LALInferenceRunState *runState)
	Initialize the prior based on command line arguments. More...

void	LALInferenceInitLIBPrior (LALInferenceRunState *runState)
	Initialize the LIB prior based on command line arguments. More...

REAL8	logGlitchAmplitudeDensity (REAL8 A, REAL8 Q, REAL8 f)
	Return the log Prior for the glitch amplitude. More...

REAL8	LALInferenceInspiralPrior (LALInferenceRunState runState, LALInferenceVariables params, LALInferenceModel *model)
	Return the logarithmic prior density of the variables specified, for the non-spinning/spinning inspiral signal case. More...

UINT4	LALInferenceInspiralCubeToPrior (LALInferenceRunState runState, LALInferenceVariables params, LALInferenceModel model, double Cube, void *context)
	Convert the hypercube parameter to physical parameters, for the non-spinning/spinning inspiral signal case. More...

void	LALInferenceCyclicReflectiveBound (LALInferenceVariables parameter, LALInferenceVariables priorArgs)
	Apply cyclic and reflective boundaries to `parameter` to bring it back within the allowed prior ranges that are specified in `priorArgs`. More...

void	LALInferenceRotateInitialPhase (LALInferenceVariables *parameter)
	Rotate initial phase if polarisation angle is cyclic around ranges. More...

REAL8	LALInferenceInspiralSkyLocPrior (LALInferenceRunState runState, LALInferenceVariables params, LALInferenceModel *model)
	Return the logarithmic prior density of the variables as specified for the sky localisation project (see: https://www.lsc-group.phys.uwm.edu/ligovirgo/cbcnote/SkyLocComparison#priors ), for the non-spinning/spinning inspiral signal case. More...

UINT4	LALInferenceInspiralSkyLocCubeToPrior (LALInferenceRunState runState, LALInferenceVariables params, LALInferenceModel model, double Cube, void *context)
	Convert the hypercube parameter to physical parameters, for the prior density of the variables as specified for the sky localisation project (see: https://www.lsc-group.phys.uwm.edu/ligovirgo/cbcnote/SkyLocComparison#priors ), for the non-spinning/spinning inspiral signal case. More...

void	LALInferenceAddMinMaxPrior (LALInferenceVariables priorArgs, const char name, REAL8 min, REAL8 max, LALInferenceVariableType type)
	Function to add the minimum and maximum values for the uniform prior onto the `priorArgs`. More...

void	LALInferenceGetMinMaxPrior (LALInferenceVariables priorArgs, const char name, REAL8 min, REAL8 max)
	Get the minimum and maximum values of the uniform prior from the `priorArgs` list, given a name. More...

void	LALInferenceRemoveMinMaxPrior (LALInferenceVariables priorArgs, const char name)
	Function to remove the minimum and maximum values for the uniform prior onto the `priorArgs`. More...

void	LALInferenceAddGaussianPrior (LALInferenceVariables priorArgs, const char name, REAL8 mu, REAL8 sigma, LALInferenceVariableType type)
	Function to add the mu and sigma values for the Gaussian prior onto the `priorArgs`. More...

void	LALInferenceGetGaussianPrior (LALInferenceVariables priorArgs, const char name, REAL8 mu, REAL8 sigma)
	Get the mu and sigma values of the Gaussian prior from the `priorArgs` list, given a name. More...

void	LALInferenceRemoveGaussianPrior (LALInferenceVariables priorArgs, const char name)
	Function to remove the mu and sigma values for the Gaussian prior onto the `priorArgs`. More...

void	LALInferenceAddGMMPrior (LALInferenceVariables priorArgs, const char name, REAL8Vector *mus, gsl_matrix covs, REAL8Vector weights, REAL8Vector minrange, REAL8Vector *maxrange)
	Add a Gaussian Mixture Model prior. More...

int	LALInferenceCheckGMMPrior (LALInferenceVariables priorArgs, const char name)
	Check for a Gaussian Mixture Model prior. More...

void	LALInferenceRemoveGMMPrior (LALInferenceVariables priorArgs, const char name)
	Remove a Gaussian Mixture Model prior. More...

void	LALInferenceGetGMMPrior (LALInferenceVariables priorArgs, const char name, REAL8Vector *mus, REAL8Vector sigmas, gsl_matrix cors, gsl_matrix invcors, REAL8Vector weights, REAL8Vector minrange, REAL8Vector maxrange, REAL8Vector dets, UINT4 idx, CHAR **fullname)
	Get the parameters defining a Gaussian Mixture Model prior. More...

void	LALInferenceAddLogUniformPrior (LALInferenceVariables priorArgs, const char name, REAL8 xmin, REAL8 xmax, LALInferenceVariableType type)
	Add a log-uniform prior. More...

void	LALInferenceGetLogUniformPrior (LALInferenceVariables priorArgs, const char name, REAL8 xmin, REAL8 xmax)
	Get the xmin and xmax values of the log-uniform prior from the `priorArgs` list, given a name. More...

void	LALInferenceRemoveLogUniformPrior (LALInferenceVariables priorArgs, const char name)
	Function to remove the min and max values for the log-uniform prior from the `priorArgs`. More...

void	LALInferenceAddFermiDiracPrior (LALInferenceVariables priorArgs, const char name, REAL8 sigma, REAL8 r, LALInferenceVariableType type)
	Add a Fermi-Dirac prior. More...

void	LALInferenceGetFermiDiracPrior (LALInferenceVariables priorArgs, const char name, REAL8 sigma, REAL8 r)
	Get the r and sigma values of the Fermi-Dirac prior from the `priorArgs` list, given a name. More...

void	LALInferenceRemoveFermiDiracPrior (LALInferenceVariables priorArgs, const char name)
	Function to remove the r and sigma values for the Fermi-Dirac prior onto the `priorArgs`. More...

int	LALInferenceCheckMinMaxPrior (LALInferenceVariables priorArgs, const char name)
	Check for types of standard prior. More...

int	LALInferenceCheckGaussianPrior (LALInferenceVariables priorArgs, const char name)
	Check for a Gaussian prior (with a mean and variance) More...

int	LALInferenceCheckLogUniformPrior (LALInferenceVariables priorArgs, const char name)
	Check for a log-uniform prior (with xmin and xmax parameters) More...

int	LALInferenceCheckFermiDiracPrior (LALInferenceVariables priorArgs, const char name)
	Check for a Fermi-Dirac prior (with a r and sigma parameter) More...

void	LALInferenceAddCorrelatedPrior (LALInferenceVariables priorArgs, const char name, gsl_matrix *cor, REAL8 mu, REAL8 sigma, UINT4 idx)
	Function to add a correlation matrix and parameter index for a prior defined as part of a multivariate Gaussian distribution onto the `priorArgs`. More...

void	LALInferenceGetCorrelatedPrior (LALInferenceVariables priorArgs, const char name, gsl_matrix cor, gsl_matrix invcor, REAL8 mu, REAL8 sigma, UINT4 *idx)
	Get the correlation coefficient matrix and index for a parameter from the `priorArgs` list. More...

void	LALInferenceRemoveCorrelatedPrior (LALInferenceVariables *priorArgs)
	Remove the correlation coefficient matrix and index for a parameter from the `priorArgs` list. More...

int	LALInferenceCheckCorrelatedPrior (LALInferenceVariables priorArgs, const char name)
	Check for the existance of a correlation coefficient matrix and index for a parameter from the `priorArgs` list. More...

void	LALInferenceDrawFromPrior (LALInferenceVariables output, LALInferenceVariables priorArgs, gsl_rng *rdm)
	Draw variables from the prior ranges. More...

void	LALInferenceDrawNameFromPrior (LALInferenceVariables output, LALInferenceVariables priorArgs, char name, LALInferenceVariableType type, gsl_rng rdm)
	Draw an individual variable from its prior range. More...

UINT4	within_malmquist (LALInferenceRunState runState, LALInferenceVariables params, LALInferenceModel *model)

REAL8	LALInferenceAnalyticNullPrior (LALInferenceRunState runState, LALInferenceVariables params, LALInferenceModel *model)
	Prior that is 1 everywhere in component mass space. More...

UINT4	LALInferenceAnalyticCubeToPrior (LALInferenceRunState runState, LALInferenceVariables params, LALInferenceModel model, double Cube, void *context)
	Analytic null prior converted from hypercube. More...

REAL8	LALInferenceNullPrior (LALInferenceRunState runState, LALInferenceVariables params, LALInferenceModel *model)
	Prior that is 1 everywhere. More...

REAL8	LALInferenceComputePriorMassNorm (const double MMin, const double MMax, const double MTotMax, const double McMin, const double McMax, const double massRatioMin, const double massRatioMax, const char *massRatioName)
	Computes the numerical normalization of the mass prior \(p(\mathcal{M}) \sim \mathcal{M}^{-11/6}\) applying all cuts in the mass plane implied by the various component, total, and chirp mass limits, and the mass ratio limits. More...

REAL8	LALInferenceFlatBoundedPrior (LALInferenceRunState runState, LALInferenceVariables params)
	Prior that checks for minimum and maximum prior range specified in runState->priorArgs and returns 0.0 if sample lies inside the boundaries, -DBL_MAX otherwise. More...

UINT4	LALInferenceCubeToPSDScaleParams (LALInferenceVariables priorParams, LALInferenceVariables params, INT4 idx, double Cube, void *context)
	Utility CubeToPrior functions for psd-fit and both calibration models. More...

UINT4	LALInferenceCubeToConstantCalibrationPrior (LALInferenceRunState runState, LALInferenceVariables params, INT4 idx, double Cube, void *context)

REAL8	LALInferenceCubeToFlatPrior (double r, double x1, double x2)
	Prior that converts from a Cube parameter in [0,1] to the flat prior bounded by x1 and x2. More...

REAL8	LALInferenceCubeToLogFlatPrior (double r, double x1, double x2)
	Prior that converts from a Cube parameter in [0,1] to the flat in log prior bounded by x1 and x2. More...

REAL8	LALInferenceCubeToPowerPrior (double p, double r, double x1, double x2)
	Prior that converts from a Cube parameter in [0,1] to the power prior bounded by x1 and x2 with power p. More...

REAL8	LALInferenceCubeToGaussianPrior (double r, double mean, double sigma)
	Prior that converts from a Cube parameter in [0,1] to the Gaussian prior with given mean and standard deviation. More...

REAL8	LALInferenceCubeToSinPrior (double r, double x1, double x2)
	Prior that converts from a Cube parameter in [0,1] to the sine prior with given min (x1) and max (x2) values. More...

REAL8	LALInferenceSineGaussianPrior (LALInferenceRunState runState, LALInferenceVariables params, LALInferenceModel *model)

REAL8	LALInferenceFermiDiracPrior (LALInferenceVariables priorArgs, const char name, REAL8 value)
	Return the Fermi-Dirac distribution log prior. More...

REAL8	LALInferenceGMMPrior (LALInferenceVariables priorArgs, const char name, REAL8 value)
	Calculate the log probability for the Gaussian Mixture Model prior. More...

REAL8	LALInferenceLogUniformPrior (LALInferenceVariables priorArgs, const char name, REAL8 value)

Function Documentation

◆ LALInferenceInitCBCPrior()

void LALInferenceInitCBCPrior ( LALInferenceRunState * runState )

Initialize the prior based on command line arguments.

Definition at line 52 of file LALInferencePrior.c.

◆ LALInferenceInitLIBPrior()

void LALInferenceInitLIBPrior ( LALInferenceRunState * runState )

Initialize the LIB prior based on command line arguments.

Definition at line 177 of file LALInferencePrior.c.

◆ logGlitchAmplitudeDensity()

REAL8 logGlitchAmplitudeDensity	(	REAL8	A,
		REAL8	Q,
		REAL8	f
	)

Return the log Prior for the glitch amplitude.

Definition at line 305 of file LALInferencePrior.c.

◆ LALInferenceInspiralPrior()

REAL8 LALInferenceInspiralPrior	(	LALInferenceRunState *	runState,
		LALInferenceVariables *	params,
		LALInferenceModel *	model
	)

Return the logarithmic prior density of the variables specified, for the non-spinning/spinning inspiral signal case.

Definition at line 442 of file LALInferencePrior.c.

◆ LALInferenceInspiralCubeToPrior()

UINT4 LALInferenceInspiralCubeToPrior	(	LALInferenceRunState *	runState,
		LALInferenceVariables *	params,
		LALInferenceModel *	model,
		double *	Cube,
		void *	context
	)

Convert the hypercube parameter to physical parameters, for the non-spinning/spinning inspiral signal case.

Definition at line 707 of file LALInferencePrior.c.

◆ LALInferenceCyclicReflectiveBound()

void LALInferenceCyclicReflectiveBound	(	LALInferenceVariables *	parameter,
		LALInferenceVariables *	priorArgs
	)

Apply cyclic and reflective boundaries to parameter to bring it back within the allowed prior ranges that are specified in priorArgs.

LALInferenceCyclicReflectiveBound() should not be called after any multi-parameter update step in a jump proposal, as this violates detailed balance.

Parameters

parameter	[in] Pointer to an array of parameters
priorArgs	[in] Pointer to an array of prior ranges

Definition at line 1113 of file LALInferencePrior.c.

◆ LALInferenceRotateInitialPhase()

void LALInferenceRotateInitialPhase ( LALInferenceVariables * parameter )

Rotate initial phase if polarisation angle is cyclic around ranges.

If the polarisation angle parameter \(\psi\) is cyclic about its upper and lower ranges of \(-\pi/4\) to \(\pi/4\) then the transformation for crossing a boundary requires the initial phase parameter \(\phi_0\) to be rotated through \(\pi\) radians. The function assumes the value of \(\psi\) has been rescaled to be between 0 and \(2\pi\) - this is a requirement of the covariance matrix routine LALInferenceNScalcCVM function.

This is particularly relevant for pulsar analyses.

Parameters

parameter [in] Pointer to an array of parameters

Definition at line 1204 of file LALInferencePrior.c.

◆ LALInferenceInspiralSkyLocPrior()

REAL8 LALInferenceInspiralSkyLocPrior	(	LALInferenceRunState *	runState,
		LALInferenceVariables *	params,
		LALInferenceModel *	model
	)

Return the logarithmic prior density of the variables as specified for the sky localisation project (see: https://www.lsc-group.phys.uwm.edu/ligovirgo/cbcnote/SkyLocComparison#priors ), for the non-spinning/spinning inspiral signal case.

◆ LALInferenceInspiralSkyLocCubeToPrior()

UINT4 LALInferenceInspiralSkyLocCubeToPrior	(	LALInferenceRunState *	runState,
		LALInferenceVariables *	params,
		LALInferenceModel *	model,
		double *	Cube,
		void *	context
	)

Convert the hypercube parameter to physical parameters, for the prior density of the variables as specified for the sky localisation project (see: https://www.lsc-group.phys.uwm.edu/ligovirgo/cbcnote/SkyLocComparison#priors ), for the non-spinning/spinning inspiral signal case.

◆ LALInferenceAddMinMaxPrior()

void LALInferenceAddMinMaxPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		REAL8 *	min,
		REAL8 *	max,
		LALInferenceVariableType	type
	)

Function to add the minimum and maximum values for the uniform prior onto the priorArgs.

Definition at line 1934 of file LALInferencePrior.c.

◆ LALInferenceGetMinMaxPrior()

void LALInferenceGetMinMaxPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		REAL8 *	min,
		REAL8 *	max
	)

Get the minimum and maximum values of the uniform prior from the priorArgs list, given a name.

Definition at line 1974 of file LALInferencePrior.c.

◆ LALInferenceRemoveMinMaxPrior()

void LALInferenceRemoveMinMaxPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name
	)

Function to remove the minimum and maximum values for the uniform prior onto the priorArgs.

Definition at line 1950 of file LALInferencePrior.c.

◆ LALInferenceAddGaussianPrior()

void LALInferenceAddGaussianPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		REAL8 *	mu,
		REAL8 *	sigma,
		LALInferenceVariableType	type
	)

Function to add the mu and sigma values for the Gaussian prior onto the priorArgs.

Definition at line 2003 of file LALInferencePrior.c.

◆ LALInferenceGetGaussianPrior()

void LALInferenceGetGaussianPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		REAL8 *	mu,
		REAL8 *	sigma
	)

Get the mu and sigma values of the Gaussian prior from the priorArgs list, given a name.

Definition at line 2032 of file LALInferencePrior.c.

◆ LALInferenceRemoveGaussianPrior()

void LALInferenceRemoveGaussianPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name
	)

Function to remove the mu and sigma values for the Gaussian prior onto the priorArgs.

Definition at line 2018 of file LALInferencePrior.c.

◆ LALInferenceAddGMMPrior()

void LALInferenceAddGMMPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		REAL8Vector ***	mus,
		gsl_matrix ***	covs,
		REAL8Vector **	weights,
		REAL8Vector **	minrange,
		REAL8Vector **	maxrange
	)

Add a Gaussian Mixture Model prior.

Add a Gaussian Mixture Model prior defined by a number of multi-variate Gaussian modes, each with a specified set of means, standard deviations, covariance matrices and weights (where weights are the relative probabilities for each mode). The minumum and maximum allowed prior range for each parameter should also be supplied, although if the array pointers are NULL these ranges will default to +/-infinity.

The name input should be a colon separated list of all the parameters in the multivariate GMM, e.g. "H0:COSIOTA". The number of parameters in this list will be checked against the number of means supplied for each mode, and the shape of the covariances for each mode to make sure that they are consistent. If just one parameter is supplied (e.g. "H0") then this will just be a one-dimensional GMM.

Internally the function will convert the covariance matrices into correlation matrices and inverse correlation matrices for use later (provided they are positive-definite). This will avoid dynamic range/numerical precision issue with using covariances of parameters spanning a large range of values. The standard deviations of each parameter will also be extracted from the covariance matrices and stored, along with the determinants of the covariance matrices.

Definition at line 2203 of file LALInferencePrior.c.

◆ LALInferenceCheckGMMPrior()

int LALInferenceCheckGMMPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name
	)

Check for a Gaussian Mixture Model prior.

Check if the single parameter given by name has a Gaussian Mixture model prior. If the parameter was within a multivariate GMM prior then it will be found.

Definition at line 2424 of file LALInferencePrior.c.

◆ LALInferenceRemoveGMMPrior()

void LALInferenceRemoveGMMPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name
	)

Remove a Gaussian Mixture Model prior.

Definition at line 2485 of file LALInferencePrior.c.

◆ LALInferenceGetGMMPrior()

void LALInferenceGetGMMPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		REAL8Vector ***	mus,
		REAL8Vector ***	sigmas,
		gsl_matrix ***	cors,
		gsl_matrix ***	invcors,
		REAL8Vector **	weights,
		REAL8Vector **	minrange,
		REAL8Vector **	maxrange,
		REAL8Vector **	dets,
		UINT4 *	idx,
		CHAR **	fullname
	)

Get the parameters defining a Gaussian Mixture Model prior.

For a single parameter given by name it will check if that parameter has a GMM prior (even if it is within a multivariate GMM prior). Arrays of the following values for each GMM mode will be returned: means of each parameter; standard deviations of each parameter; a correlation matrix; and inverse correlation matrix; the weight (relative probability) of the mode; and, the determinant of the covariance matrix. The minimum and maximum ranges for each parameter are returned. The position (index) of the parameter name within a multivariate GMM will is returned. Finally, the combined name of the prior (i.e. including all parameters) is returned.

Definition at line 2341 of file LALInferencePrior.c.

◆ LALInferenceAddLogUniformPrior()

void LALInferenceAddLogUniformPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		REAL8 *	xmin,
		REAL8 *	xmax,
		LALInferenceVariableType	type
	)

Add a log-uniform prior.

Add a prior uniform in the log, i.e. PDF(x)~1/x

\[p(h|h_{\rm min}, h_{\rm max}, I) = \frac{1/h}{\log{(h_{\rm max}/h_{\rm min})}},\]

where \(h_{\rm min}\) and \(h_{\rm max}\) limit the domain of the PDF. The function has no support outside this range.

This function adds xmin and xmax values for the Fermi-Dirac prior to the priorArgs.

Definition at line 2626 of file LALInferencePrior.c.

◆ LALInferenceGetLogUniformPrior()

void LALInferenceGetLogUniformPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		REAL8 *	xmin,
		REAL8 *	xmax
	)

Get the xmin and xmax values of the log-uniform prior from the priorArgs list, given a name.

Definition at line 2663 of file LALInferencePrior.c.

◆ LALInferenceRemoveLogUniformPrior()

void LALInferenceRemoveLogUniformPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name
	)

Function to remove the min and max values for the log-uniform prior from the priorArgs.

Definition at line 2648 of file LALInferencePrior.c.

◆ LALInferenceAddFermiDiracPrior()

void LALInferenceAddFermiDiracPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		REAL8 *	sigma,
		REAL8 *	r,
		LALInferenceVariableType	type
	)

Add a Fermi-Dirac prior.

Add a prior defined by the Fermi-Dirac PDF

\[p(h|\sigma, r, I) = \frac{1}{\sigma\log{\left(1+e^{r} \right)}}\left(e^{((h/\sigma) - r)} + 1\right)^{-1},\]

where \(r = \mu/\sigma\) to give a more familiar form of the function.

This function adds sigma and r values for the Fermi-Dirac prior onto the priorArgs.

Definition at line 2561 of file LALInferencePrior.c.

◆ LALInferenceGetFermiDiracPrior()

void LALInferenceGetFermiDiracPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		REAL8 *	sigma,
		REAL8 *	r
	)

Get the r and sigma values of the Fermi-Dirac prior from the priorArgs list, given a name.

Definition at line 2589 of file LALInferencePrior.c.

◆ LALInferenceRemoveFermiDiracPrior()

void LALInferenceRemoveFermiDiracPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name
	)

Function to remove the r and sigma values for the Fermi-Dirac prior onto the priorArgs.

Definition at line 2576 of file LALInferencePrior.c.

◆ LALInferenceCheckMinMaxPrior()

int LALInferenceCheckMinMaxPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name
	)

Check for types of standard prior.

Check for a uniform prior (with minimum and maximum)

Definition at line 1963 of file LALInferencePrior.c.

◆ LALInferenceCheckGaussianPrior()

int LALInferenceCheckGaussianPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name
	)

Check for a Gaussian prior (with a mean and variance)

Definition at line 1993 of file LALInferencePrior.c.

◆ LALInferenceCheckLogUniformPrior()

int LALInferenceCheckLogUniformPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name
	)

Check for a log-uniform prior (with xmin and xmax parameters)

Definition at line 2612 of file LALInferencePrior.c.

◆ LALInferenceCheckFermiDiracPrior()

int LALInferenceCheckFermiDiracPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name
	)

Check for a Fermi-Dirac prior (with a r and sigma parameter)

Definition at line 2551 of file LALInferencePrior.c.

◆ LALInferenceAddCorrelatedPrior()

void LALInferenceAddCorrelatedPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		gsl_matrix **	cor,
		REAL8 *	mu,
		REAL8 *	sigma,
		UINT4 *	idx
	)

Function to add a correlation matrix and parameter index for a prior defined as part of a multivariate Gaussian distribution onto the priorArgs.

The correlation coefficient matrix must be a gsl_matrix and the index for the given parameter in the matrix must be supplied. The mean and standard deviation the named parameter must also be supplied.

Definition at line 2054 of file LALInferencePrior.c.

◆ LALInferenceGetCorrelatedPrior()

void LALInferenceGetCorrelatedPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		gsl_matrix **	cor,
		gsl_matrix **	invcor,
		REAL8 *	mu,
		REAL8 *	sigma,
		UINT4 *	idx
	)

Get the correlation coefficient matrix and index for a parameter from the priorArgs list.

Definition at line 2106 of file LALInferencePrior.c.

◆ LALInferenceRemoveCorrelatedPrior()

void LALInferenceRemoveCorrelatedPrior ( LALInferenceVariables * priorArgs )

Remove the correlation coefficient matrix and index for a parameter from the priorArgs list.

Definition at line 2146 of file LALInferencePrior.c.

◆ LALInferenceCheckCorrelatedPrior()

int LALInferenceCheckCorrelatedPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name
	)

Check for the existance of a correlation coefficient matrix and index for a parameter from the priorArgs list.

Definition at line 2176 of file LALInferencePrior.c.

◆ LALInferenceDrawFromPrior()

void LALInferenceDrawFromPrior	(	LALInferenceVariables *	output,
		LALInferenceVariables *	priorArgs,
		gsl_rng *	rdm
	)

Draw variables from the prior ranges.

Definition at line 2690 of file LALInferencePrior.c.

◆ LALInferenceDrawNameFromPrior()

void LALInferenceDrawNameFromPrior	(	LALInferenceVariables *	output,
		LALInferenceVariables *	priorArgs,
		char *	name,
		LALInferenceVariableType	type,
		gsl_rng *	rdm
	)

Draw an individual variable from its prior range.

Definition at line 2736 of file LALInferencePrior.c.

◆ within_malmquist()

UINT4 within_malmquist	(	LALInferenceRunState *	runState,
		LALInferenceVariables *	params,
		LALInferenceModel *	model
	)

Definition at line 2950 of file LALInferencePrior.c.

◆ LALInferenceAnalyticNullPrior()

REAL8 LALInferenceAnalyticNullPrior	(	LALInferenceRunState *	runState,
		LALInferenceVariables *	params,
		LALInferenceModel *	model
	)

Prior that is 1 everywhere in component mass space.

◆ LALInferenceAnalyticCubeToPrior()

UINT4 LALInferenceAnalyticCubeToPrior	(	LALInferenceRunState *	runState,
		LALInferenceVariables *	params,
		LALInferenceModel *	model,
		double *	Cube,
		void *	context
	)

Analytic null prior converted from hypercube.

◆ LALInferenceNullPrior()

REAL8 LALInferenceNullPrior	(	LALInferenceRunState *	runState,
		LALInferenceVariables *	params,
		LALInferenceModel *	model
	)

Prior that is 1 everywhere.

◆ LALInferenceComputePriorMassNorm()

REAL8 LALInferenceComputePriorMassNorm	(	const double	MMin,
		const double	MMax,
		const double	MTotMax,
		const double	McMin,
		const double	McMax,
		const double	massRatioMin,
		const double	massRatioMax,
		const char *	massRatioName
	)

Computes the numerical normalization of the mass prior \(p(\mathcal{M}) \sim \mathcal{M}^{-11/6}\) applying all cuts in the mass plane implied by the various component, total, and chirp mass limits, and the mass ratio limits.

Returns the integral of \(\mathcal{M}^{-11/6}\) over the allowed ranges in mass.

Definition at line 1880 of file LALInferencePrior.c.

◆ LALInferenceFlatBoundedPrior()

REAL8 LALInferenceFlatBoundedPrior	(	LALInferenceRunState *	runState,
		LALInferenceVariables *	params
	)

Prior that checks for minimum and maximum prior range specified in runState->priorArgs and returns 0.0 if sample lies inside the boundaries, -DBL_MAX otherwise.

Can be used with MinMaxPrior functions. Ignores variables which are not REAL8 or do not have min and max values set.

Definition at line 3218 of file LALInferencePrior.c.

◆ LALInferenceCubeToPSDScaleParams()

UINT4 LALInferenceCubeToPSDScaleParams	(	LALInferenceVariables *	priorParams,
		LALInferenceVariables *	params,
		INT4 *	idx,
		double *	Cube,
		void *	context
	)

Utility CubeToPrior functions for psd-fit and both calibration models.

◆ LALInferenceCubeToConstantCalibrationPrior()

UINT4 LALInferenceCubeToConstantCalibrationPrior	(	LALInferenceRunState *	runState,
		LALInferenceVariables *	params,
		INT4 *	idx,
		double *	Cube,
		void *	context
	)

◆ LALInferenceCubeToFlatPrior()

REAL8 LALInferenceCubeToFlatPrior	(	double	r,
		double	x1,
		double	x2
	)

Prior that converts from a Cube parameter in [0,1] to the flat prior bounded by x1 and x2.

Definition at line 3330 of file LALInferencePrior.c.

◆ LALInferenceCubeToLogFlatPrior()

REAL8 LALInferenceCubeToLogFlatPrior	(	double	r,
		double	x1,
		double	x2
	)

Prior that converts from a Cube parameter in [0,1] to the flat in log prior bounded by x1 and x2.

Definition at line 3339 of file LALInferencePrior.c.

◆ LALInferenceCubeToPowerPrior()

REAL8 LALInferenceCubeToPowerPrior	(	double	p,
		double	r,
		double	x1,
		double	x2
	)

Prior that converts from a Cube parameter in [0,1] to the power prior bounded by x1 and x2 with power p.

Definition at line 3351 of file LALInferencePrior.c.

◆ LALInferenceCubeToGaussianPrior()

REAL8 LALInferenceCubeToGaussianPrior	(	double	r,
		double	mean,
		double	sigma
	)

Prior that converts from a Cube parameter in [0,1] to the Gaussian prior with given mean and standard deviation.

Definition at line 3361 of file LALInferencePrior.c.

◆ LALInferenceCubeToSinPrior()

REAL8 LALInferenceCubeToSinPrior	(	double	r,
		double	x1,
		double	x2
	)

Prior that converts from a Cube parameter in [0,1] to the sine prior with given min (x1) and max (x2) values.

Definition at line 3370 of file LALInferencePrior.c.

◆ LALInferenceSineGaussianPrior()

REAL8 LALInferenceSineGaussianPrior	(	LALInferenceRunState *	runState,
		LALInferenceVariables *	params,
		LALInferenceModel *	model
	)

Definition at line 3295 of file LALInferencePrior.c.

◆ LALInferenceFermiDiracPrior()

REAL8 LALInferenceFermiDiracPrior	(	LALInferenceVariables *	priorArgs,
		const char *	name,
		REAL8	value
	)

Return the Fermi-Dirac distribution log prior.

The function returns the log of the prior for a Fermi-Dirac distribution