Likelihood function definition module

Functions to define Likelihood functions from Astro observation and nuclear experiments

InferenceWorkflow.Likelihood.Jliklihood(theta, J_low, J_up)[source]

Computing likelihood from a hard cut constraint of J.

Parameters:

  • theta (array) – An array representing the parameters used to determine a RMF model in the

  • case (Lagrangian. In this)

  • parameters. (the RMF model is defined by 7)

  • K_low (float) – lower bound of this J constraint.

  • K_up (float) – upper bound of this J constraint.

Returns:

likelihood feed back for this given paramter set-up.

Return type:

likelihood (float)

InferenceWorkflow.Likelihood.Kliklihood(theta, K_low, K_up)[source]

Computing likelihood from a hard cut constraint of K.

Parameters:

  • theta (array) – An array representing the parameters used to determine a RMF model in the

  • case (Lagrangian. In this)

  • parameters. (the RMF model is defined by 7)

  • K_low (float) – lower bound of this K constraint.

  • K_up (float) – upper bound of this K constraint.

Returns:

likelihood feed back for this given paramter set-up.

Return type:

likelihood (float)

InferenceWorkflow.Likelihood.Lliklihood(theta, L_low, L_up)[source]

Computing likelihood from a hard cut constraint of L.

Parameters:

  • theta (array) – An array representing the parameters used to determine a RMF model in the

  • case (Lagrangian. In this)

  • parameters. (the RMF model is defined by 7)

  • K_low (float) – lower bound of this L constraint.

  • K_up (float) – upper bound of this L constraint.

Returns:

likelihood feed back for this given paramter set-up.

Return type:

likelihood (float)

InferenceWorkflow.Likelihood.MRlikihood_Gaussian(eps_total, pres_total, x, d1)[source]

Computing likelihood from a simulation gaussian distribution of MR measurement

Parameters:

  • eps_total (array) – the energy density of full EoS in MeV/fm3, times a G/c**2 factor

  • pres_total (array) – the pressure from full EoS model in MeV/fm3, times a G/c**4 factor

  • x (float array) – [Mvalue, Rvalue, Mwidth, Rwidth], Mvalue is the Mass center value of this

  • measurement (this Mass)

  • it (Rvalue is the Radius center of)

  • of (Mwidth is the 1-sigma width)

  • measurement

  • measurement. (Rwidth is the 1-sigma width of this radius)

  • d1 (float) – the sampled density of this measurement

Returns:

likelihood feed back for this given paramter set-up.

Return type:

likelihood (float)

InferenceWorkflow.Likelihood.MRlikihood_kernel(eps_total, pres_total, x, d1)[source]

Computing likelihood from a distribution of MR measurement

Parameters:

  • eps_total (array) – the energy density of full EoS in MeV/fm3, times a G/c**2 factor

  • pres_total (array) – the pressure from full EoS model in MeV/fm3, times a G/c**4 factor

  • x (kde.kernel) – the distribution kernel of MR measurement.

  • d1 (float) – the sampled density of this measurement

Returns:

likelihood feed back for this given paramter set-up.

Return type:

likelihood (float)

InferenceWorkflow.Likelihood.Masslikihood_Gaussian(eps_total, pres_total, x, d1)[source]

Computing likelihood from a simulation gaussian distribution of Mass measurement

Parameters:

  • eps_total (array) – the energy density of full EoS in MeV/fm3, times a G/c**2 factor

  • pres_total (array) – the pressure from full EoS model in MeV/fm3, times a G/c**4 factor

  • x (float array) – [Mvalue, Mwidth], Mvalue is the Mass center value of this

  • measurement (simulated)

  • measurement. (Mwidth is the 1-sigma width of this Mass)

  • d1 (float) – the sampled density of this measurement

Returns:

likelihood feed back for this given paramter set-up.

Return type:

likelihood (float)

InferenceWorkflow.Likelihood.TidalLikihood_kernel(eps_total, pres_total, x, d1)[source]

Computing likelihood from a distribution of Gravitational wave measurement

Parameters:

  • eps_total (array) – the energy density of full EoS in MeV/fm3, times a G/c**2 factor

  • pres_total (array) – the pressure from full EoS model in MeV/fm3, times a G/c**4 factor

  • x (kde.kernel) – containing kernelGW and chirp, kernelGW is the distribution kde.kernel

  • measurement (sampled from full GW)

  • mass (in [chrip)

  • M2/M1

  • M1 (tidal of)

  • sequence. (tidal of M2])

  • solely. (chrip mass is the sampling from chrip mass term in GW events)

  • d1 (float) – the sampled density of this measurement

Returns:

likelihood feed back for this given paramter set-up.

Return type:

likelihood (float)