Plots

We collect here all plotting modules available in nucleardatapy.

astro_setupGW_fig

nucleardatapy.fig.astro_setupGW_fig.astro_setupGW_fig(pname, sources)

Plot Tidal deformabilities as a function of sources.

The plot is 1x1 with:

[0]: Tidal deformabilities versus sources.

Parameters:

• pname (str.) – name of the figure (*.png)

• sources (array of str.) – array of sources names.

astro_setupMR_fig

nucleardatapy.fig.astro_setupMR_fig.astro_setupMR_fig(pname, sources, sources_av)

Plot M-R constraints from observation measurements.

The plot is 1x1 with:

[0]: Masses versus radii.

Parameters:

• pname (str.) – name of the figure (*.png)

• sources (array of str.) – array of sources.

• sources_av (array of str.) – array of averaged sources.

astro_setupMasses_fig

nucleardatapy.fig.astro_setupMasses_fig.astro_setupMasses_fig(pname, sources)

Plot Masses for massives neutron stars as a function of sources.

The plot is 1x1 with:

[0]: masses versus sources.

Parameters:

• pname (str.) – name of the figure (*.png)

• sources (array of str.) – array of sources.

astro_setupMtov_fig

nucleardatapy.fig.astro_setupMtov_fig.astro_setupMtov_fig(pname, sources_lo_all, sources_lo_dist, sources_up1, sources_up2, sources_up3)

Plot the probability distribution functions associated to maximum masses.

Includes the observation uncertainty in the PDF by using error-function.

The plot is 1x1 with:

[0]: distribution of maximum mass versus maximum mass.

Parameters:

• pname (str.) – name of the figure (*.png)

• sources_lo_all (array of str.) – array of all sources (low boundaries).

• sources_lo_dist (array of str.) – array of sources considered for the distribution (low boundaries).

• sources_up1 (array of str.) – array of sources (up boundaries).

• sources_up2 (array of str.) – array of sources (up boundaries).

• sources_up3 (array of str.) – array of sources (up boundaries).

astro_setupMup_fig

nucleardatapy.fig.astro_setupMup_fig.astro_setupMup_fig(pname, sources)

Plot mass upper boundaries from GW measurements as a function of GW sources.

The plot is 1x1 with:

[0]: upper boundary for the mass versus sources.

Parameters:

• pname (str.) – name of the figure (*.png)

• sources (array of str.) – array of sources.

corr_setupEsymDen_fig

nucleardatapy.fig.corr_setupEsymDen_fig.corr_setupEsymDen_fig(pname, constraints, Ksym, origine)

Plot Esym or Esym,2 (depending on origine) as a function of the density.

The plot is 1x1 with:

[0]: upper boundary for the mass versus sources.

Parameters:

• pname (str.) – name of the figure (*.png)

• constraints (array of str.) – array of constraints to run on.

• Ksym (real number.) – Value (in MeV) of Ksym.

• origine (str.) – can be ‘finiteNuclei’ or ‘neutronStar’.

corr_setupEsymLsym_fig

nucleardatapy.fig.corr_setupEsymLsym_fig.corr_setupEsymLsym_fig(pname, constraints, origine)

Plot the correlation between Esym and Lsym.

The plot is 1x1 with:

[0]: Esym - Lsym correlation plot.

Parameters:

• pname (str.) – name of the figure (*.png)

• constraints (array of str.) – list of constraints to run on.

• origine (str.) – can be ‘finiteNuclei’ or ‘neutronStar’.

corr_setupKsatQsat_fig

nucleardatapy.fig.corr_setupKsatQsat_fig.corr_setupKsatQsat_fig(pname, constraints)

Plot the correlation between Ksat and Qsat.

The plot is 1x1 with:

[0]: Ksat - Qsat correlation plot

Parameters:

• pname (str.) – name of the figure (*.png)

• constraints (array of str.) – list of constraints to run on.

crust_setupCrust_fig

nucleardatapy.fig.crust_setupCrust_fig.crust_setupCrust_fig(pname, models)

Plot crust predictions for the models given in models.

The plot is 1x2 with:

[0]: internal energy per nucleon as a function of the density n. [1]: Z as a function of the density n.

Parameters:

• pname (str.) – name of the figure (*.png)

• models (str.) – list of different models.

eos_setupAMBeq_fig

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_cs2_lep_fig(pname, micro_mbs, pheno_models, band)

Plot the lepton contribution to the square of the sound speed in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_cs2_nuc_fig(pname, micro_mbs, pheno_models, band)

Plot the nucleon contribution to the square of the sound speed in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_cs2_tot_fig(pname, micro_mbs, pheno_models, band)

Plot the total (=nucleon+lepton) contribution to the square of the sound speed in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_e2a_lep_fig(pname, micro_mbs, pheno_models, band)

Plot the lepton contribution to the energy per nucleon in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_e2a_nuc_fig(pname, micro_mbs, pheno_models, band)

Plot the nucleon contribution to the energy per nucleon in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_e2a_tot_fig(pname, micro_mbs, pheno_models, band)

Plot the total (=nucleon+lepton) contribution to the energy per nucleon in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_eos_fig(pname, micro_mbs, pheno_models, band)

Plot the equation of state in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

Plot nuclear chart (N versus Z). The plot is 1x2 with: [0]: nuclear chart.

Parameters:

• pname (str.) – name of the figure (*.png)

• table (str.) – table.

• version (str.) – version of table to run on.

• theo_tables (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_pre_lep_fig(pname, micro_mbs, pheno_models, band)

Plot the lepton contribution to the pressure in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_pre_nuc_fig(pname, micro_mbs, pheno_models, band)

Plot the nucleon contribution to the pressure in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_pre_tot_fig(pname, micro_mbs, pheno_models, band)

Plot the total (=nucleon+lepton) contribution to the pressure in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_xe_fig(pname, micro_mbs, pheno_models, band)

Plot the electron fraction (=xe) in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_xmu_fig(pname, micro_mbs, pheno_models, band)

Plot the muon fraction (=xmu) in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMBeq_fig.eos_setupAMBeq_xp_fig(pname, micro_mbs, pheno_models, band)

Plot the proton fraction (=xp) in asymmetric matter at beta equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

eos_setupAMLeq_fig

nucleardatapy.fig.eos_setupAMLeq_fig.eos_setupAMLeq_xe_fig(pname, micro_mbs, pheno_models, band)

Plot the electron fraction (=xe) in asymmetric matter at lepton equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMLeq_fig.eos_setupAMLeq_xexmu_fig(pname, micro_mbs, pheno_models, band)

Plot the electron and muon fractions (=xe and xmu) in asymmetric matter at lepton equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAMLeq_fig.eos_setupAMLeq_xmu_fig(pname, micro_mbs, pheno_models, band)

Plot the muon fraction (=xmu) in asymmetric matter at lepton equilibrium.

The plot is 2x1 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

eos_setupAM_asy_lep_fig

nucleardatapy.fig.eos_setupAM_asy_lep_fig.eos_setupAM_cs2_asy_lep_fig(pname, micro_mbs, pheno_models, asy, band)

Plot the leptonic contribution to the square of the sound speed in asymmetric matter controlled by the variable asy (defined as (N-Z)/A).

The plot is 1x2 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• asy (real.) – asymmetry parameter defined as (N-Z)/A.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAM_asy_lep_fig.eos_setupAM_e2a_asy_lep_fig(pname, micro_mbs, pheno_models, asy, band)

Plot the leptonic contribution to the energy per nucleon in asymmetric matter controlled by the variable asy (defined as (N-Z)/A).

The plot is 1x2 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• asy (real.) – asymmetry parameter defined as (N-Z)/A.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAM_asy_lep_fig.eos_setupAM_pre_asy_lep_fig(pname, micro_mbs, pheno_models, asy, band)

Plot the leptonic contribution to the pressure in asymmetric matter controlled by the variable asy (defined as (N-Z)/A).

The plot is 1x2 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• asy (real.) – asymmetry parameter defined as (N-Z)/A.

• band (object.) – object instantiated on the reference band.

eos_setupAM_asy_nuc_fig

nucleardatapy.fig.eos_setupAM_asy_nuc_fig.eos_setupAM_cs2_asy_nuc_fig(pname, micro_mbs, pheno_models, asy, band)

Plot the nucleon contribution to the square of the sound speed in asymmetric matter controlled by the variable asy (defined as (N-Z)/A).

The plot is 1x2 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• asy (real.) – asymmetry parameter defined as (N-Z)/A.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAM_asy_nuc_fig.eos_setupAM_e2a_asy_nuc_fig(pname, micro_mbs, pheno_models, asy, band)

Plot the nucleon contribution to the energy per nucleon in asymmetric matter controlled by the variable asy (defined as (N-Z)/A).

The plot is 1x2 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• asy (real.) – asymmetry parameter defined as (N-Z)/A.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAM_asy_nuc_fig.eos_setupAM_pre_asy_nuc_fig(pname, micro_mbs, pheno_models, asy, band)

Plot the nucleon contribution to the pressure in asymmetric matter controlled by the variable asy (defined as (N-Z)/A).

The plot is 1x2 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• asy (real.) – asymmetry parameter defined as (N-Z)/A.

• band (object.) – object instantiated on the reference band.

eos_setupAM_asy_tot_fig

nucleardatapy.fig.eos_setupAM_asy_tot_fig.eos_setupAM_cs2_asy_tot_fig(pname, micro_mbs, pheno_models, asy, band)

Plot the total (nucleon+leptonic) contribution to the square of the sound speed in asymmetric matter controlled by the variable asy (defined as (N-Z)/A).

The plot is 1x2 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• asy (real.) – asymmetry parameter defined as (N-Z)/A.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAM_asy_tot_fig.eos_setupAM_e2a_asy_tot_fig(pname, micro_mbs, pheno_models, asy, band)

Plot the total (nucleon+leptonic) contribution to the energy per nucleon in asymmetric matter controlled by the variable asy (defined as (N-Z)/A).

The plot is 1x2 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• asy (real.) – asymmetry parameter defined as (N-Z)/A.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAM_asy_tot_fig.eos_setupAM_pre_asy_tot_fig(pname, micro_mbs, pheno_models, asy, band)

Plot the total (nucleon+leptonic) contribution to the pressure in asymmetric matter controlled by the variable asy (defined as (N-Z)/A).

The plot is 1x2 with:

[0]: microscopic models. [1]: phenomenologic models.

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• asy (real.) – asymmetry parameter defined as (N-Z)/A.

• band (object.) – object instantiated on the reference band.

eos_setupAM_fig

nucleardatapy.fig.eos_setupAM_fig.eos_setupAM_cs2_fig(pname, micro_mbs, pheno_models, band)

Plot the nucleon, lepton and total (nucleon+leptonic) contribution to the square of the sound speed in asymmetric matter.

The plot is 2x3 with:

[0,0]: microscopic models (nucleon). [0,1]: phenomenologic models (nucleon).

[1,0]: microscopic models (lepton). [1,1]: phenomenologic models (lepton).

[2,0]: microscopic models (total). [2,1]: phenomenologic models (total).

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAM_fig.eos_setupAM_e2a_fig(pname, micro_mbs, pheno_models, band)

Plot the nucleon, lepton and total (nucleon+leptonic) contribution to the energy per nucleon in asymmetric matter.

The plot is 2x3 with:

[0,0]: microscopic models (nucleon). [0,1]: phenomenologic models (nucleon).

[1,0]: microscopic models (lepton). [1,1]: phenomenologic models (lepton).

[2,0]: microscopic models (total). [2,1]: phenomenologic models (total).

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

nucleardatapy.fig.eos_setupAM_fig.eos_setupAM_pre_fig(pname, micro_mbs, pheno_models, band)

Plot the nucleon, lepton and total (nucleon+leptonic) contribution to the pressure in asymmetric matter.

The plot is 2x3 with:

[0,0]: microscopic models (nucleon). [0,1]: phenomenologic models (nucleon).

[1,0]: microscopic models (lepton). [1,1]: phenomenologic models (lepton).

[2,0]: microscopic models (total). [2,1]: phenomenologic models (total).

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (array of str.) – array with names of many-body framework for microscopic interactions.

• pheno_models (array of str.) – array of interaction names for phenomenologic interactions.

• band (object.) – object instantiated on the reference band.

eos_setupCC_fig

nucleardatapy.fig.eos_setupCC_fig.eos_setupCC_checkeos_fig(pname, band, crust_model, core_kind, core_model, core_param, connect, boundaries, emp)

Check the EoS with crust and core parts.

The plot is 1x1.

[0]: pressure and band to check visualy.

Parameters:

• pname (str.) – name of the figure (*.png)

• band (object.) – object instantiated on the reference band.

• crust_model (str.) – the name of the crust model.

• core_kind (str.) – the kind of the core model (‘micro’ or ‘pheno’).

• core_model (str.) – the name of the core model.

• core_param (str.) – the parameters of the core model.

• connect (str.) – The thermodynamic quantity employed to connect the crust and the core. Can be: ‘density’, ‘epsilon’ (energy density) or ‘pressure’.

• boundaries (array of real.) – array with lower and upper boundaries to consider. Connected to the variable connect. For instance boundaries = [ 0.016, 0.16 ] for ‘density’ (in units of fm-3), boundaries = [ 15.0, 150.0 ] for ‘epsilon’ (in units of MeV fm-3), or boundaries = [ 0.1, 1.0 ] for pressure (in units of MeV fm-3).

• emp (str.) – way to connect the crust and the core. Can be: ‘None’, ‘simple’, ‘Steiner’.

nucleardatapy.fig.eos_setupCC_fig.eos_setupCC_checkpre_fig(pname, band, crust_model, core_kind, core_model, core_param, connect, boundaries, emp)

Check the EoS with crust and core parts.

The plot is 1x1.

[0]: pressure and band to check visualy.

Parameters:

• pname (str.) – name of the figure (*.png)

• band (object.) – object instantiated on the reference band.

• crust_model (str.) – the name of the crust model.

• core_kind (str.) – the kind of the core model (‘micro’ or ‘pheno’).

• core_model (str.) – the name of the core model.

• core_param (str.) – the parameters of the core model.

• connect (str.) – The thermodynamic quantity employed to connect the crust and the core. Can be: ‘density’, ‘epsilon’ (energy density) or ‘pressure’.

• boundaries (array of real.) – array with lower and upper boundaries to consider. Connected to the variable connect. For instance boundaries = [ 0.016, 0.16 ] for ‘density’ (in units of fm-3), boundaries = [ 15.0, 150.0 ] for ‘epsilon’ (in units of MeV fm-3), or boundaries = [ 0.1, 1.0 ] for pressure (in units of MeV fm-3).

• emp (str.) – way to connect the crust and the core. Can be: ‘None’, ‘simple’, ‘Steiner’.

nucleardatapy.fig.eos_setupCC_fig.eos_setupCC_eos_fig(pname, band, crust_model, core_kind, core_model, core_param)

Plot the EoS with crust and core parts.

The plot is 1x1.

[0]: pressure as a function of the energy density.

Parameters:

• pname (str.) – name of the figure (*.png)

• band (object.) – object instantiated on the reference band.

• crust_model (str.) – the name of the crust model.

• core_kind (str.) – the kind of the core model (‘micro’ or ‘pheno’).

• core_model (str.) – the name of the core model.

• core_param (str.) – the parameters of the core model.

hnuc_setupChart_fig

nucleardatapy.fig.hnuc_setupChart_fig.hnuc_setupChart_fig(pname, tables1L, tables2L, tables1Xi)

Plot hyper-nuclear chart (N versus Z).

The plot is 1x1 with:

[0]: nuclear chart.

Parameters:

• pname (str.) – name of the figure (*.png)

• table1L (array of str.) – table.

• table2L (array of str.) – table.

• table1Xi (array of str.) – table.

hnuc_setupRE1LExp_fig

nucleardatapy.fig.hnuc_setupRE1LExp_fig.hnuc_setupRE1LExp_fig(pname, tables)

Plot the removal energies as a function of A^{-2/3}.

The plot is 1x1 with:

[0]: nuclear chart.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (str.) – table.

matter_all_fig

nucleardatapy.fig.matter_all_fig.matter_all_Esym_fig(pname, micro_mbs, pheno_models, band_check, band_plot)

Plot nucleonic symmetry energy.

The plot is 1x2 with:

[0]: Esym versus den (micro). [1]: Esym versus den (pheno).

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (str.) – many-body (mb) approach considered.

• pheno_models (array of str.) – models to run on.

• band_check (object.) – object instantiated on the reference band.

• band_plot (object.) – object instantiated on the reference band.

nucleardatapy.fig.matter_all_fig.matter_all_cs2_fig(pname, micro_mbs, pheno_models, band_check, matter)

Plot nucleonic sound speed in matter.

The plot is 1x2 with:

[0]: cs2 versus den (micro). [1]: cs2 versus den (pheno).

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (str.) – many-body (mb) approach considered.

• pheno_models (array of str.) – models to run on.

• band_check (object.) – object instantiated on the reference band.

• matter (str.) – can be ‘SM’ or ‘NM’.

nucleardatapy.fig.matter_all_fig.matter_all_e2a_fig(pname, micro_mbs, pheno_models, band_check, band_plot, matter)

Plot nucleonic energy per particle E/A in matter.

The plot is 1x2 with:

[0]: E/A versus den (micro). [1]: E/A versus den (pheno).

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (str.) – many-body (mb) approach considered.

• pheno_models (array of str.) – models to run on.

• band_check (object.) – object instantiated on the reference band.

• band_plot (object.) – object instantiated on the reference band.

• matter (str.) – can be ‘SM’ or ‘NM’.

nucleardatapy.fig.matter_all_fig.matter_all_eos_fig(pname, micro_mbs, pheno_models, band_check, matter)

Plot EoS in matter.

The plot is 1x2 with:

[0]: pre versus eps (micro). [1]: pre versus eps (pheno).

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (str.) – many-body (mb) approach considered.

• pheno_models (array of str.) – models to run on.

• band_check (object.) – object instantiated on the reference band.

• matter (str.) – can be ‘SM’ or ‘NM’.

nucleardatapy.fig.matter_all_fig.matter_all_pre_fig(pname, micro_mbs, pheno_models, band_check, matter)

Plot nucleonic pressure in matter.

The plot is 1x2 with:

[0]: pre versus den (micro). [1]: pre versus den (pheno).

Parameters:

• pname (str.) – name of the figure (*.png)

• micro_mbs (str.) – many-body (mb) approach considered.

• pheno_models (array of str.) – models to run on.

• band_check (object.) – object instantiated on the reference band.

• band_plot (object.) – object instantiated on the reference band.

• matter (str.) – can be ‘SM’ or ‘NM’.

matter_setupCheck_fig

nucleardatapy.fig.matter_setupCheck_fig.matter_setupCheck_fig(pname, mb, models, band, matter)

Check E/A from models in models and show the reference band.

The plot is 1x1 with:

[0]: E/A versus den.

Parameters:

• pname (str.) – name of the figure (*.png)

• mb (str.) – many-body (mb) approach considered.

• models (array of str.) – models to run on.

• band (object.) – object instantiated on the reference band.

• matter (str.) – can be ‘SM’ or ‘NM’.

matter_setupFFGLep_fig

nucleardatapy.fig.matter_setupFFGLep_fig.matter_setupFFGLep_fig(pname, den_el=None, den_mu1=None, den_mu2=None, den_mu3=None)

Plot leptonic FFG energy per particle E/A and pressure in NM and SM.

The plot is 2x1 with:

[0]: E/A versus den. [1]: pre versus den.

Parameters:

• pname (str.) – name of the figure (*.png)

• den_el (float or numpy vector of real numbers.) – electron densities.

• den_mu1 (float or numpy vector of real numbers.) – muon densities (set 1).

• den_mu2 (float or numpy vector of real numbers.) – muon densities (set 2).

• den_mu3 (float or numpy vector of real numbers.) – muon densities (set 3).

matter_setupFFGNuc_fig

nucleardatapy.fig.matter_setupFFGNuc_fig.matter_setupFFGNuc_EOS_fig(pname, mss=[1.0], den=array([0.01, 0.04777778, 0.08555556, 0.12333333, 0.16111111, 0.19888889, 0.23666667, 0.27444444, 0.31222222, 0.35]))

Plot nucleonic FFG EOS in NM and SM.

The plot is 2x1 with:

[0]: EOS (pre) versus energy density rho.

[1]: Sound speed c_s^2 versus energy density rho.

Parameters:

• pname (str.) – name of the figure (*.png)

• mss (float or numpy vector of real numbers.) – effective mass/bare mass of the nucleons.

• den (float or numpy vector of real numbers.) – density.

nucleardatapy.fig.matter_setupFFGNuc_fig.matter_setupFFGNuc_EP_fig(pname, mss=[1.0], den=array([0.01, 0.04777778, 0.08555556, 0.12333333, 0.16111111, 0.19888889, 0.23666667, 0.27444444, 0.31222222, 0.35]), kf=array([0.5, 0.66666667, 0.83333333, 1., 1.16666667, 1.33333333, 1.5, 1.66666667, 1.83333333, 2.]))

Plot nucleonic FFG energy per particle and pressure in NM and SM.

The plot is 2x2 with:

[0,0]: E/A versus den. [0,1]: E/A versus kfn.

[1,0]: pre versus den. [1,1]: pre versus kfn.

Parameters:

• pname (str.) – name of the figure (*.png)

• mss (float or numpy vector of real numbers.) – effective mass/bare mass of the nucleons.

• den (float or numpy vector of real numbers.) – densities.

• kf (float or numpy vector of real numbers.) – Fermi momenta.

matter_setupHIC_fig

nucleardatapy.fig.matter_setupHIC_fig.matter_setupHIC_fig(pname, inferences)

Plot the inferences from HIC.

The plot is 2x2 with:

[0,0]: pressure in SM versus den. [0,1]: E/A in SM versus den.

[1,0]: pressure in NM versus den. [1,1]: Esym versus den.

Parameters:

• pname (str.) – name of the figure (*.png)

• inferences (array of str.) – inferences for HIC.

matter_setupMicroEsym_fig

nucleardatapy.fig.matter_setupMicroEsym_fig.matter_setupMicroEsym_fig(pname, mbs, band)

Plot the symmetry energy esym for microscopic models.

The plot is 2x2 with:

[0,0]: esym function of the density. [0,1]: esym function of the Fermi momentum.

[0,0]: esym/esym,FFG function of the density. [0,1]: esym/esym,FFG function of the Fermi momentum.

Parameters:

• pname (str.) – name of the figure (*.png)

• mbs (array of str.) – list of many-body approaches.

• band (object.) – object instantiated on the reference band.

matter_setupMicro_LP_fig

nucleardatapy.fig.matter_setupMicro_LP_fig.matter_setupMicro_LP_fig(pname, models, matter='SM', ell=0)

Plot nucleonic energy per particle E/A in matter.

The plot is 2x2 in SM with:

[0,0]: F_ell versus den. [0,1]: G_ell versus den.

[1,0]: F’_ell’ versus den. [1,1]: G’_ell versus den.

Or the plot is 2x1 in NM with:

[0]: F_ell versus den. [1]: G_ell versus den.

Parameters:

• pname (str.) – name of the figure (*.png)

• models (array of str.) – models to run on.

• matter (str.) – can be ‘SM’ (default) or ‘NM’.

• ell (int.) – Value of the angular momentum L of the Landau residual parameter. Can be 0 (default) or 1.

matter_setupMicro_band_fig

nucleardatapy.fig.matter_setupMicro_band_fig.matter_setupMicro_band_fig(pname, models, den, matter)

Plot the reference band together with the models on wich it is constructed.

The plot is 1x2 with:

[0]: E versus den. [1]: E/EFFG versus den.

Parameters:

• pname (str.) – name of the figure (*.png)

• models (array of str.) – list of models to run on.

• den (array of reals.) – numpy array with densities to define the reference band.

• matter (str.) – chose between ‘SM’, ‘NM’ or ‘Esym’.

matter_setupMicro_effmass_fig

nucleardatapy.fig.matter_setupMicro_effmass_fig.matter_setupMicro_effmass_fig(pname, models, matter='NM')

Plot the effective mass as function of the density and Fermi momentum.

The plot is 1x2 with:

[0]: effmass(den). [1]: effmass(kF).

Parameters:

• pname (str.) – name of the figure (*.png)

• models (array of str.) – list of models to run on.

• matter (str.) – chose between ‘SM’ and ‘NM’ (default).

matter_setupMicro_err_NM_fig

nucleardatapy.fig.matter_setupMicro_err_NM_fig.matter_setupMicro_err_NM_fig(pname, models)

Plot uncertainties (err) estimated by different authors in NM.

The plot is 1x1 with:

[0]: uncertainty for E/A versus den.

Parameters:

• pname (str.) – name of the figure (*.png)

• models (array of str.) – array of models.

matter_setupMicro_fig

nucleardatapy.fig.matter_setupMicro_fig.matter_setupMicro_cs2_fig(pname, mb, models, band, matter)

Plot nucleonic pressure in matter.

The plot is 1x2 with:

[0]: cs2 versus den. [1]: cs2 versus kfn.

Parameters:

• pname (str.) – name of the figure (*.png)

• mb (str.) – many-body (mb) approach considered.

• models (array of str.) – models to run on.

• band (object.) – object instantiated on the reference band.

• matter (str.) – can be ‘SM’ or ‘NM’.

nucleardatapy.fig.matter_setupMicro_fig.matter_setupMicro_e2a_fig(pname, mb, models, band, matter)

Plot nucleonic energy per particle E/A in matter.

The plot is 2x2 with:

[0,0]: E/A versus den. [0,1]: E/A versus kfn.

[1,0]: E/E_NRFFG versus den. [1,1]: E/E_NRFFG versus kfn.

Parameters:

• pname (str.) – name of the figure (*.png)

• mb (str.) – many-body (mb) approach considered.

• models (array of str.) – models to run on.

• band (object.) – object instantiated on the reference band.

• matter (str.) – can be ‘SM’ or ‘NM’.

nucleardatapy.fig.matter_setupMicro_fig.matter_setupMicro_pre_fig(pname, mb, models, band, matter)

Plot nucleonic pressure in matter.

The plot is 2x2 with:

[0,0]: pre versus den. [0,1]: pre versus kfn.

[1,0]: pre/pre_NRFFG versus den. [1,1]: pre/pre_NRFFG versus kfn.

Parameters:

• pname (str.) – name of the figure (*.png)

• mb (str.) – many-body (mb) approach considered.

• models (array of str.) – models to run on.

• band (object.) – object instantiated on the reference band.

• matter (str.) – can be ‘SM’ or ‘NM’.

matter_setupMicro_gap_fig

nucleardatapy.fig.matter_setupMicro_gap_fig.matter_setupMicro_gap_1s0_fig(pname, models, matter='NM')

Plot the 1S0 pairing gap in matter.

The plot is 2x2 with:

[0,0]: gap versus den. [0,1]: gap versus kfn.

[1,0]: gap/EF versus den. [1,1]: gap/EF versus kfn.

Parameters:

• pname (str.) – name of the figure (*.png)

• models (array of str.) – models to run on.

• matter (str.) – can be ‘SM’ or ‘NM’ (default).

nucleardatapy.fig.matter_setupMicro_gap_fig.matter_setupMicro_gap_3pf2_fig(pname, models, matter='NM')

Plot the 3PF2 pairing gap in matter.

The plot is 2x2 with:

[0,0]: gap versus den. [0,1]: gap versus kfn.

[1,0]: gap/EF versus den. [1,1]: gap/EF versus kfn.

Parameters:

• pname (str.) – name of the figure (*.png)

• models (array of str.) – models to run on.

• matter (str.) – can be ‘SM’ or ‘NM’ (default).

matter_setupNEPStats_fig

nucleardatapy.fig.matter_setupNEPStats_fig.matter_setupNEPStats_fig(pname, models)

Plot the PDF for NEPs.

The plot is 5x2 with:

[0,0]: Esat. [0,1]: Esym.

[1,0]: nsat. [1,1]: Lsym.

[2,0]: Ksat. [2,1]: Ksym.

[3,0]: Qsat. [3,1]: Qsym.

[4,0]: m*sat/m. [4,1]: Delta m*sat/m.

Parameters:

• pname (str.) – name of the figure (*.png)

• models (array of str.) – models to run on.

matter_setupPhenoEsym_fig

nucleardatapy.fig.matter_setupPhenoEsym_fig.matter_setupPhenoEsym_fig(pname, models, band)

Plot the symmetry energy esym for phenomenologic models.

The plot is 2x2 with:

[0,0]: esym function of the density. [0,1]: esym function of the Fermi momentum.

[0,0]: esym/esym,FFG function of the density. [0,1]: esym/esym,FFG function of the Fermi momentum.

Parameters:

• pname (str.) – name of the figure (*.png)

• models (array of str.) – list of phenomenological models.

• band (object.) – object instantiated on the reference band.

matter_setupPheno_fig

nucleardatapy.fig.matter_setupPheno_fig.matter_setupPheno_cs2_fig(pname, model, band, matter)

Plot nucleonic sound speed in matter.

The plot is 1x2 with:

[0]: cs2 versus den. [1]: cs2 versus kfn.

Parameters:

• pname (str.) – name of the figure (*.png)

• model (str.) – class of model considered.

• band (object.) – object instantiated on the reference band.

• matter (str.) – can be ‘SM’ or ‘NM’.

nucleardatapy.fig.matter_setupPheno_fig.matter_setupPheno_e2a_fig(pname, model, band, matter)

Plot nucleonic internal energy per particle E/A in matter.

The plot is 2x2 with:

[0,0]: E/A versus den. [0,1]: E/A versus kfn.

[1,0]: E/E_NRFFG versus den. [1,1]: E/E_NRFFG versus kfn.

Parameters:

• pname (str.) – name of the figure (*.png)

• model (str.) – class of model considered.

• band (object.) – object instantiated on the reference band.

• matter (str.) – can be ‘SM’ or ‘NM’.

nucleardatapy.fig.matter_setupPheno_fig.matter_setupPheno_pre_fig(pname, model, band, matter)

Plot nucleonic pressure in matter.

The plot is 2x2 with:

[0,0]: pre versus den. [0,1]: pre versus kfn.

[1,0]: pre/pre_NRFFG versus den. [1,1]: pre/pre_NRFFG versus kfn.

Parameters:

• pname (str.) – name of the figure (*.png)

• model (str.) – class of model considered.

• band (object.) – object instantiated on the reference band.

• matter (str.) – can be ‘SM’ or ‘NM’.

nuc_setupBEExp_chart_fig

nucleardatapy.fig.nuc_setupBEExp_chart_fig.nuc_setupBEExp_chart_Rch_fig(pname, table, version, Rch_table)

Plot nuclear chart (N versus Z).

The plot is 1x1 with:

[0]: nuclear chart.

Parameters:

• pname (str.) – name of the figure (*.png)

• table (str.) – table.

• version (str.) – version of table to run on.

• Rch_table (str.) – table for Rch.

nucleardatapy.fig.nuc_setupBEExp_chart_fig.nuc_setupBEExp_chart_lt_fig(pname, table, version, theo_tables)

Plot nuclear chart (N versus Z).

The plot is 1x1 with:

[0]: nuclear chart.

Parameters:

• pname (str.) – name of the figure (*.png)

• table (str.) – table.

• version (str.) – version of table to run on.

• theo_tables (object.) – object instantiated on the reference band.

nucleardatapy.fig.nuc_setupBEExp_chart_fig.nuc_setupBEExp_chart_year_fig(pname, sYear, year_min, year_max)

Plot nuclear chart (N versus Z) for a range of discovery years.

The plot is 1x1 with:

[0]: nuclear chart.

Parameters:

• pname (str.) – name of the figure (*.png)

• sYear (object.) – select nuclei for given discovery years.

• year_min (real.) – lower range of the discovery years.

• year_max (real.) – upper range of the discovery years.

nuc_setupBEExp_fig

nucleardatapy.fig.nuc_setupBEExp_fig.nuc_setupBEExp_D3n_fig(pname, tables, versions, Zref=50)

Plot D3n (3-point formula for the odd-even mass staggering) from the data extracted from the nuclear chart.

The plot is 1x1 with:

[0]: show D3n as a function of N.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – tables.

• versions (array of str.) – versions of the tables.

• Zref (integer.) – Reference value for Z.

nucleardatapy.fig.nuc_setupBEExp_fig.nuc_setupBEExp_D3p_fig(pname, tables, versions, Nref=50)

Plot D3p (3-point formula for the odd-even mass staggering) from the data extracted from the nuclear chart.

The plot is 1x1 with:

[0]: show D3p as a function of Z.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – tables.

• versions (array of str.) – versions of the tables.

• Nref (integer.) – Reference value for N.

nucleardatapy.fig.nuc_setupBEExp_fig.nuc_setupBEExp_S2n_fig(pname, tables, versions, Zref=50)

Plot S2n from the data extracted from the nuclear chart.

The plot is 1x1 with:

[0]: show S2n as a function of N.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – tables.

• versions (array of str.) – versions of the tables.

• Zref (integer.) – Reference value for Z.

nucleardatapy.fig.nuc_setupBEExp_fig.nuc_setupBEExp_S2p_fig(pname, tables, versions, Nref=50)

Plot S2p from the data extracted from the nuclear chart.

The plot is 1x1 with:

[0]: show S2p as a function of Z.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – tables.

• versions (array of str.) – versions of the tables.

• Nref (integer.) – Reference value for N.

nucleardatapy.fig.nuc_setupBEExp_fig.nuc_setupBEExp_year_fig(pname, table, version)

Plot the histogram for the discovery year.

The plot is 1x2 with:

[0]: full range of years. [1]: last two decades.

Parameters:

• pname (str.) – name of the figure (*.png)

• table (str.) – table.

• version (str.) – version of table to run on.

nuc_setupBETheo_fig

nucleardatapy.fig.nuc_setupBETheo_fig.nuc_setupBETheo_D3n_fig(pname, tables, Zref=50)

Plot D3n (3-point formula for the odd-even mass staggering) from the data extracted from the theoretical mass table.

The plot is 1x1 with:

[0]: show D3n as a function of N.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – tables.

• versions (array of str.) – versions of the tables.

• Zref (integer.) – Reference value for Z.

nucleardatapy.fig.nuc_setupBETheo_fig.nuc_setupBETheo_D3p_fig(pname, tables, Nref=50)

Plot D3p (3-point formula for the odd-even mass staggering) from the data extracted from the theoretical mass table.

The plot is 1x1 with:

[0]: show D3p as a function of Z.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – tables.

• versions (array of str.) – versions of the tables.

• Nref (integer.) – Reference value for N.

nucleardatapy.fig.nuc_setupBETheo_fig.nuc_setupBETheo_S2n_fig(pname, tables, Zref=50)

Plot S2n from the data extracted from the theoretical mass table.

The plot is 1x1 with:

[0]: show S2n as a function of N.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – tables.

• versions (array of str.) – versions of the tables.

• Zref (integer.) – Reference value for Z.

nucleardatapy.fig.nuc_setupBETheo_fig.nuc_setupBETheo_S2p_fig(pname, tables, Nref=50)

Plot S2p from the data extracted from the theoretical mass table.

The plot is 1x1 with:

[0]: show S2p as a function of Z.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – tables.

• versions (array of str.) – versions of the tables.

• Nref (integer.) – Reference value for N.

nucleardatapy.fig.nuc_setupBETheo_fig.nuc_setupBETheo_diff_fig(pname, tables, table_ref='1995-DZ', Zref=50)

Plot the energy difference between theoretical mass tables with respect to table_ref.

The plot is 1x1 with:

[0]: show the energy difference as a function of N.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – tables.

• table_ref (str.) – reference table.

• Zref (integer.) – Reference value for Z.

nuc_setupISGMRExp_fig

nucleardatapy.fig.nuc_setupISGMRExp_fig.nuc_setupISGMRExp_fig(pname, tables)

Plot the experimental ISGMR energy from the tables.

The plot is 1x3 with:

[0]: for Zr. [1]: for Sn. [2]: for Pb.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – tables.

nuc_setupRchExp_fig

nucleardatapy.fig.nuc_setupRchExp_fig.nuc_setupRchExp_3Zref_fig(pname, tables)

Plot the experimental charge radii from the tables.The plot is 1x1 with:[0]: Rch as a function of N.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – tables.

nucleardatapy.fig.nuc_setupRchExp_fig.nuc_setupRchExp_fig(pname, tables)

Plot the experimental charge radii from the tables.

The plot is 1x1 with:

[0]: Rch as a function of N.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – tables.

nuc_setupRchTheo_fig

nucleardatapy.fig.nuc_setupRchTheo_fig.nuc_setupRchTheo_3Zref_fig(pname, tables, table_exp)

Plot the theoretical charge radii from the tables and compare to the experimental value.The plot is 1x1 with:[0]: Rch as a function of N.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – theoretical tables.

• table_exp (str.) – experimental table.

nucleardatapy.fig.nuc_setupRchTheo_fig.nuc_setupRchTheo_fig(pname, tables, table_exp)

Plot the theoretical charge radii from the tables and compare to the experimental value.

The plot is 1x1 with:

[0]: Rch as a function of N.

Parameters:

• pname (str.) – name of the figure (*.png)

• tables (array of str.) – theoretical tables.

• table_exp (str.) – experimental table.

nuc_setupRnpExp_fig

nucleardatapy.fig.nuc_setupRnpExp_fig.nuc_setupRnpExp_fig(pname=None, source=None)

Plot the experimental np radii (neutron skin).

The plot is 1x1 with:

[0]: Rch as a function of N.

Parameters:

• pname (str.) – name of the figure (*.png)

• source (str.) – experimental table.

nuc_setupRnpTheo_fig

nucleardatapy.fig.nuc_setupRnpTheo_fig.nuc_setupRnpTheo_fig(pname, source)

Plot the theoretical np radii (neutron skin).

The plot is 1x1 with:

[0]: Rch as a function of N.

Parameters:

• pname (str.) – name of the figure (*.png)

• source (str.) – experimental table.

nucleardatapy.fig.nuc_setupRnpTheo_fig.read_model_data(directory, source)