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Fixing power-law + peak model and adding a chi_eff distribution to gwpopulation.py #54

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Fixing power-law + peak model and adding a chi_eff distribution to gwpopulation.py #54

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9 changes: 8 additions & 1 deletion gwinferno/models/gwpopulation/gwpopulation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,10 @@ def plpeak_primary_ratio_pdf(m1, q, alpha, beta, mmin, mmax, mpp, sigpp, lam):


def plpeak_primary_pdf(m1, alpha, mmin, mmax, mpp, sigpp, lam):
return (1 - lam) * powerlaw_pdf(m1, -alpha, mmin, mmax) + lam * truncnorm_pdf(m1, mpp, sigpp, mmin, mmax)

# we need to normalize powerlaw_pdf for the mixture model. truncnorm_pdf is already normalized
pl_norm = (1 - alpha) / (jnp.power(mmax, 1 - alpha) - jnp.power(mmin, 1 - alpha))
return (1 - lam) * powerlaw_pdf(m1, -alpha, mmin, mmax) * (pl_norm) + lam * truncnorm_pdf(m1, mpp, sigpp, mmin, mmax)


"""
Expand All @@ -51,6 +54,10 @@ def plpeak_primary_pdf(m1, alpha, mmin, mmax, mpp, sigpp, lam):
"""


def chi_eff_truncnorm(chi_eff, mu_x=0, log_sig_x=0.5):
return truncnorm_pdf(chi_eff, mu_x, jnp.exp(log_sig_x), -1, 1)


def beta_spin_magnitude(a, alpha, beta, amax=1):
return betadist(a, alpha, beta, scale=amax)

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