Source code for heron.models.gw

"""
This module contains objects which provide the specifically-GW parts of waveform surrogate models.
"""
from elk.waveform import Waveform, Timeseries
import astropy.constants as c
from math import log

[docs]class HofTSurrogate(object):

    def _to_frequency(self, timeseries, *args):
        """Convert an elk timeseries output from heron into an elk frequency series output."""
        return timeseries.to_fseries(*args)

[docs]    def bilby(self, time, mass_1, mass_2, luminosity_distance):
        """
        Return a waveform from the GPR in a format expected by the Bilby ecosystem
        """

        times_b = time.copy()
        times_b -= self.t_min
    
        total_mass_cat = self.total_mass
        time_factor_cat = (c.c.value**3 / c.G.value)/(total_mass_cat*c.M_sun.value) #*1e4
        #h_factor = c.pc.value
        if mass_1 > mass_2:
            mass_ratio = mass_2/mass_1
        else:
            mass_ratio = mass_1/mass_2
        total_mass = (mass_1+mass_2)#*c.M_sun.value
    
        time_factor = (c.c.value**3 / c.G.value)/(total_mass*c.M_sun.value) 
    
        times_b *= (total_mass_cat / total_mass) #(time_factor/time_factor_cat)

        p = {'mass ratio': 1,
            'spin 1x': 0,  'spin 1y': 0,  'spin 1z': 0,
            'spin 2x': 0,  'spin 2y': 0,  'spin 2z': 0}
        p['mass ratio'] = mass_ratio
        
        mean = self.mean(p=p, times = times_b)
        return {"plus": mean[0].data / luminosity_distance , "cross": mean[1].data / luminosity_distance}
    
[docs]class BBHSurrogate(object):
    problem_dims = 8
    columns = {0: "time",
                    1: "mass ratio",
                    2: "spin 1x",
                    3: "spin 1y",
                    4: "spin 1z",
                    5: "spin 2x",
                    6: "spin 2y",
                    7: "spin 2z",
                    8: "h+",
                    9: "hx"
            }
    parameters = ("mass ratio", "spin 1x", "spin 1y", "spin 1z", "spin 2x", "spin 2y", "spin 2z")
    c_ind = {j:i for i,j in columns.items()}

[docs]class BBHNonSpinSurrogate(object):
    problem_dims = 2
    columns = {0: "time",
               1: "mass ratio",
               8: "h+",
               9: "hx"
    }
    parameters = ("mass ratio",)
    c_ind = {j:i for i,j in columns.items()}