CardamomOT.inference.proliferations
===================================

.. py:module:: CardamomOT.inference.proliferations

.. autoapi-nested-parse::

   Proliferation rate inference utilities for CardamomOT.

   Provides a lightweight MLP that maps protein levels to a net proliferation
   rate R = b - d (birth minus death), estimated from the row marginals of the
   optimal-transport coupling computed during trajectory inference.



Classes
-------

.. autoapisummary::

   CardamomOT.inference.proliferations.ProliferationMLP


Functions
---------

.. autoapisummary::

   CardamomOT.inference.proliferations.train_proliferation_mlp


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

.. py:class:: ProliferationMLP(n_proteins: int, hidden_size: int = 64)

   Bases: :py:obj:`torch.nn.Module`


   Two-hidden-layer MLP: protein levels → net proliferation rate R.


   .. py:method:: predict(prot: numpy.ndarray) -> numpy.ndarray

      prot: (N, n_proteins) → R values (N,).



.. py:function:: train_proliferation_mlp(prot: numpy.ndarray, R_opt: numpy.ndarray, ns: int = 1, hidden_size: int = 64, n_epochs: int = 300, lr: float = 0.001, batch_size: int = 256, verb: bool = True) -> ProliferationMLP

   Train a ProliferationMLP on (prot[:, ns:], R_opt) pairs.

   :param prot:
   :type prot: (N_total, G_tot) protein trajectory array (including stimulus dims).
   :param R_opt:
   :type R_opt: (N_total,) net proliferation rates from OT coupling marginals.
   :param ns:
   :type ns: number of stimulus dimensions to skip in prot.