Reading SNOwGLoBES-Format Model Files

Demonstrate how snewpy can read files in the tabular .dat input format used by SNOwGLoBES and plot the data.

Note: These files only contain time-integrated fluences, not the full information that is available in all other models. Accordingly, much of the functionality of snewpy is not available for these files.

At the moment the class only reads the NoOsc files inside the tarfiles.

from snewpy.models.ccsn import SNOwGLoBES

import matplotlib as mpl
import matplotlib.pyplot as plt

mpl.rc('font', size=14)

Plotting Functions

Two functions are provided:

1. One to plot the spectrum (number flux, actually fluence) at a given time.

2. One to plot the fluence in 2D vs. energy and time.

def plot_spectrum(snmodel, time=0.):
    """Plot spectrum (count/cm2) from SNOwGLoBES model at a given time.
    """
    fig, axes = plt.subplots(2,3, figsize=(14,8), sharex=True, sharey=True,
                             gridspec_kw={'wspace':0, 'hspace':0})

    for ax, (flavor, fl) in zip(axes.flatten(), snmodel.get_fluence(time).items()):
        ax.plot(snmodel.energy, fl, label=flavor)
        ax.legend()
        ax.grid(ls=':')

    axes[0,0].set(ylabel='fluence [cm$^{-2}$ (0.2 MeV)$^{-1}$]')
    axes[1,0].set(xlabel='energy [MeV]', xlim=(-0.5,10.5))
    fig.tight_layout()
    return fig

def plot_fluence(snmodel, log=False):
    """Plot the fluence (count/cm2) vs energy and time.
    """
    fig, axes = plt.subplots(2,3, figsize=(14,8), sharex=True, sharey=True,
                             gridspec_kw={'wspace':0, 'hspace':0})

    if log:
        norm = mpl.colors.LogNorm(vmin=1., vmax=snmodel.fmax)
    else:
        norm = mpl.colors.Normalize(vmin=0., vmax=snmodel.fmax)

    for ax, (flavor, fl) in zip(axes.flatten(), snmodel.flux.items()):
        im = ax.imshow(fl, extent=[snmodel.time[0], snmodel.time[-1], snmodel.energy[0], snmodel.energy[-1]],
                       origin='lower', cmap='Blues', norm=norm,
                       aspect='auto')
        ax.text(0.8,0.9, flavor, fontsize=12, transform=ax.transAxes)
        ax.grid(ls=':')

    axes[0,0].set(xlim=(snmodel.time[0], snmodel.time[-1]),
                  ylim=(0,10), ylabel='energy [MeV]')
    axes[1,0].set(xlabel='time [s]')

    fig.tight_layout()
    fig.subplots_adjust(right=0.8)
    cb_ax = fig.add_axes([0.82, 0.1, 0.02, 0.85])
    cb = fig.colorbar(im, cax=cb_ax)
    cb.set_label('fluence [cm$^{-2}$ (0.2 MeV)$^{-1}$]')

PISN Models

Plot the spectrum at \(t=0\) and the total fluence for some of the PISN models.

150\(M_{\odot}\) Progenitor, Helm EOS

sn1 = SNOwGLoBES('../../models/PISN/PISN_150Msun_EOS=Helm_NeutrinoFlux.tar.bz2')

fig = plot_fluence(sn1)

fig = plot_fluence(sn1, log=True)

fig = plot_spectrum(sn1, time=0.)

150\(M_\odot\) Progenitor, SFHo EOS

sn2 = SNOwGLoBES('../../models/PISN/PISN_150Msun_EOS=SFHo_NeutrinoFlux.tar.bz2')

fig = plot_fluence(sn2)

fig = plot_fluence(sn2, log=True)

fig = plot_spectrum(sn2, time=0.)

250\(M_\odot\) Progenitor, Helm EOS

sn3 = SNOwGLoBES('../../models/PISN/PISN_250Msun_EOS=Helm_NeutrinoFlux.tar.bz2')

fig = plot_fluence(sn3)

fig = plot_fluence(sn3, log=True)

fig = plot_spectrum(sn3, time=0.)

250\(M_\odot\) Progenitor, SFHo EOS

sn4 = SNOwGLoBES('../../models/PISN/PISN_250Msun_EOS=SFHo_NeutrinoFlux.tar.bz2')

fig = plot_fluence(sn4)

fig = plot_fluence(sn4, log=True)

fig = plot_spectrum(sn4, time=0.)

Type Ia Models

GCD

sn5 = SNOwGLoBES('../../models/Type_Ia/GCD_NeutrinoFlux.tar.bz2')

fig = plot_fluence(sn5)

fig = plot_fluence(sn5, log=True)

fig = plot_spectrum(sn5, time=0.5)

DDT

sn6 = SNOwGLoBES('../../models/Type_Ia/DDT_NeutrinoFlux.tar.bz2')

fig = plot_fluence(sn6)

fig = plot_fluence(sn6, log=True)

fig = plot_spectrum(sn6, time=0.5)

Nakazato CCSN Model

Load the Nakazato CCSN model written to SNOwGLoBES format using the generate_* functions in snewpy.snowglobes.

Note that the Nakazato SNOwGLoBES tarball is not uploaded to GitHub. If you want to repeat this, generate it yourself the converter.

sn7 = SNOwGLoBES('../../models/Nakazato_2013/nakazato-LS220-BH-z0.004-s30.0.SNOformat.tar.bz2')

WARNING: OverflowError converting to FloatType in column NuMu, possibly resulting in degraded precision. [astropy.io.ascii.fastbasic]
WARNING:astropy:OverflowError converting to FloatType in column NuMu, possibly resulting in degraded precision.
WARNING: OverflowError converting to FloatType in column NuTau, possibly resulting in degraded precision. [astropy.io.ascii.fastbasic]
WARNING:astropy:OverflowError converting to FloatType in column NuTau, possibly resulting in degraded precision.
WARNING: OverflowError converting to FloatType in column aNuMu, possibly resulting in degraded precision. [astropy.io.ascii.fastbasic]
WARNING:astropy:OverflowError converting to FloatType in column aNuMu, possibly resulting in degraded precision.
WARNING: OverflowError converting to FloatType in column aNuTau, possibly resulting in degraded precision. [astropy.io.ascii.fastbasic]
WARNING:astropy:OverflowError converting to FloatType in column aNuTau, possibly resulting in degraded precision.

fig = plot_fluence(sn7)

fig = plot_fluence(sn7, log=True)

fig = plot_spectrum(sn7, time=0)