GWForge.population.pdb_external
===============================

.. py:module:: GWForge.population.pdb_external

.. autoapi-nested-parse::

   Power Law + Dip + Break models. None are reviewed.



Classes
-------

.. autoapisummary::

   GWForge.population.pdb_external.NotchFilterBinnedPairingMassDistribution


Functions
---------

.. autoapisummary::

   GWForge.population.pdb_external.power_law_dip_break_1d


Module Contents
---------------

.. py:function:: power_law_dip_break_1d(mass, A, A2, NSmin, NSmax, BHmin, BHmax, UPPERmin, UPPERmax, n0, n1, n2, n3, n4, n5, alpha_1, alpha_2, alpha_dip, mu1, sig1, mix1, mu2, sig2, mix2, absolute_mmin, absolute_mmax)

   The one-dimensional mass distribution considered in Fishbach, Essick, Holz. Does
   Matter Matter? ApJ Lett 899, 1 (2020) : arXiv:2006.13178

   .. math::
       p(m|\lambda) = n(m|\gamma_{\text{low}}, \gamma_{\text{high}}, A) \times
           l(m|m_{\text{max}}, \eta) \\
                \times \begin{cases}
                        & m^{\alpha_1} \text{ if } m < \gamma_{\text{low}} \\
                        & m^{\alpha_2} \text{ if } m > \gamma_{\text{low}} \\
                        & 0 \text{ otherwise }
                \end{cases}.

   where $l(m|m_{\text{max}}, \eta)$ is the low pass filter with powerlaw $\eta$
   applied at mass $m_{\text{max}}$,
   $n(m|\gamma_{\text{low}}, \gamma_{\text{high}}, A)$ is the notch
   filter with depth $A$ applied between $\gamma_{\text{low}}$ and
   $\gamma_{\text{high}}$, and
   $\lambda$ is the subset of hyperparameters $\{ \gamma_{\text{low}},
   \gamma_{\text{high}}, A, \alpha_1, \alpha_2, m_{\text{min}}, m_{\
   text{max}}\}$.

   :param mass: Mass to evaluate probability at (:math:`m`).
   :type mass: array-like
   :param alpha_1: Powerlaw exponent for compact objects below NSmax (:math:`\alpha_1`).
   :type alpha_1: float
   :param alpha_2: Powerlaw exponent for compact objects above BHmin (:math:`\alpha_2`).
   :type alpha_2: float
   :param alpha_dip: Powerlaw exponent for compact objects between NSmax and BHmin (:math: `\alpha_d`).
   :type alpha_dip: float
   :param NSmin: Minimum compact object mass (:math:`m_\min`).
   :type NSmin: float
   :param NSmax: Mass at which the notch filter starts for the lower mass gap (:math:`\gamma_{low1}`).
   :type NSmax: float
   :param BHmin: Mass at which the notch filter ends for the lower mass gap (:math:`\gamma_{high1}`).
   :type BHmin: float
   :param BHmax: Maximum mass in the powerlaw distributed component (:math:`m_\max`).
   :type BHmax: float
   :param A: depth of the dip between NSmax and BHmin (A).
   :type A: float
   :param UPPERmin: Mass at which the notch filter starts for the upper mass gap (:math:`\gamma_{low2}`).
   :type UPPERmin: float
   :param UPPERmax: Mass at which the notch filter ends for the upper mass gap (:math:`\gamma_{high2}`).
   :type UPPERmax: float
   :param mu1: Location of the upper peak where an overdensity of merging compact objects is observed (:math:`\mu_{peak1}`)..
   :type mu1: float
   :param sig1: Width of the upper peak where an overdensity of merging compact objects is observed (:math:`\sigma_{peak1}`)..
   :type sig1: float
   :param mix1: Mixing fraction of the first gaussian peak with the powerlaw + notches (:math: `c_1`)
   :type mix1: float
   :param mu2: Location of the lower peak where an overdensity of merging compact objects is observed (:math:`\mu_{peak2}`)..
   :type mu2: float
   :param sig2: Width of the lower peak where an overdensity of merging compact objects is observed (:math:`\mu_{peak2}`)..
   :type sig2: float
   :param mix2: Mixing fraction of the second gaussian peak with the powerlaw + notches (:math: `c_2`)
   :type mix2: float
   :param absolute_mmin: The minimum limit for the truncated normal distribution.
   :type absolute_mmin: float
   :param absolute_mmax: The maximum limit for the truncated normal distribution.
   :type absolute_mmax: float
   :param n{0: Exponents to set the sharpness of the low mass cutoff and high mass cutoff, respectively (:math:`\eta_i`).
   :type n{0: float
   :param 5}: Exponents to set the sharpness of the low mass cutoff and high mass cutoff, respectively (:math:`\eta_i`).
   :type 5}: float
   :param n{1: Exponents to set the sharpness of the lower edge and upper edge of the lower mass gap, respectively (:math:`\eta_i`).
   :type n{1: float
   :param 2}: Exponents to set the sharpness of the lower edge and upper edge of the lower mass gap, respectively (:math:`\eta_i`).
   :type 2}: float
   :param n{3: Exponents to set the sharpness of the lower edge and upper edge of the upper mass gap, respectively (:math:`\eta_i`).
   :type n{3: float
   :param 4}: Exponents to set the sharpness of the lower edge and upper edge of the upper mass gap, respectively (:math:`\eta_i`).
   :type 4}: float


.. py:class:: NotchFilterBinnedPairingMassDistribution(mmin=0.5, mmax=350.0)

   Bases: :py:obj:`_NotchFilterPairingMassDistribution`


   2D "Power Law + Dip + Break" Model with a pairing function that depends on m2.


   .. py:method:: pairing(dataset, beta_pair_1, beta_pair_2, mbreak)