lineage.states.stateCommon
==========================

.. py:module:: lineage.states.stateCommon

.. autoapi-nested-parse::

   Common utilities used between states regardless of distribution.



Attributes
----------

.. autoapisummary::

   lineage.states.stateCommon.arr_type
   lineage.states.stateCommon._addr_gammaincc
   lineage.states.stateCommon.gammaincc
   lineage.states.stateCommon._addr_gammaln
   lineage.states.stateCommon.gammaln
   lineage.states.stateCommon._addr_psi
   lineage.states.stateCommon.psi


Functions
---------

.. autoapisummary::

   lineage.states.stateCommon.censor_lineage_gamma
   lineage.states.stateCommon.censor_lineage_gaphs
   lineage.states.stateCommon.bern_estimator
   lineage.states.stateCommon.gamma_LL
   lineage.states.stateCommon.gamma_LL_grad
   lineage.states.stateCommon.trigamma
   lineage.states.stateCommon.pava_increasing
   lineage.states.stateCommon.gamma_mle_closed_form
   lineage.states.stateCommon.gamma_estimator


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

.. py:data:: arr_type

.. py:function:: censor_lineage_gamma(tree, obs, states, censor_condition, desired_experiment_time = 2000000000000.0)

   Applies temporal and fate censorship to Gamma distribution lineages using arrays.


.. py:function:: censor_lineage_gaphs(tree, obs, states, censor_condition, desired_experiment_time = 2000000000000.0)

   Applies temporal and fate censorship to 2-phase GaPhs lineages using arrays.


.. py:function:: bern_estimator(bern_obs, gammas)

   A weighted estimator for a Bernoulli distribution.


.. py:data:: _addr_gammaincc

.. py:data:: gammaincc

.. py:data:: _addr_gammaln

.. py:data:: gammaln

.. py:data:: _addr_psi

.. py:data:: psi

.. py:function:: gamma_LL(logX, gamma_obs, time_cen, gammas, param_idx)

   Log-likelihood for the optionally censored Gamma distribution.
   The logX is the log transform of the parameters, in case of atonce estimation, it is [shape, scale1, scale2, scale3, scale4].


.. py:function:: gamma_LL_grad(logX, gamma_obs, time_cen, gammas, param_idx)

   Analytical gradient of gamma_LL with respect to logX.


.. py:function:: trigamma(x)

   Asymptotic expansion for polygamma(1, x).


.. py:function:: pava_increasing(y, w)

   Pool Adjacent Violators Algorithm for increasing monotonicity: y[0] <= y[1] <= ... <= y[K-1].


.. py:function:: gamma_mle_closed_form(gamma_obs, gammas, param_idx, K, constrained=True)

   1D profile likelihood solver using Minka initialization and Newton-Raphson.


.. py:function:: gamma_estimator(gamma_obs, time_cen, gammas, param_idx, x0, phase)

   This is a weighted estimator for the parameters of the Gamma distribution,
   estimating shared shape and separate scale parameters across drug concentrations.