Updated docstrings to inform users that ODE solution may be slow. (#5965)

Author: dmburt

pymc/ode/__init__.py

@@ -1,4 +1,11 @@
-"""This submodule contains tools used to perform inference on ordinary differential equations."""
+"""
+This submodule contains tools used to perform inference on ordinary differential equations.
+
+Due to the nature of the model (as well as included solvers), ODE solution may perform slowly.
+Another library based on PyMC--sunode--has implemented Adams' method and BDF (backward differentation formula) using the very fast SUNDIALS suite of ODE and PDE solvers.
+It is much faster than the ``pm.ode`` implementation.
+More information about ``sunode`` is available at: https://github.com/aseyboldt/sunode.
+"""
 #   Copyright 2020 The PyMC Developers
 #
 #   Licensed under the Apache License, Version 2.0 (the "License");

pymc/ode/ode.py

@@ -34,6 +34,9 @@ class DifferentialEquation(Op):
     r"""
     Specify an ordinary differential equation
 
+    Due to the nature of the model (as well as included solvers), the process of ODE solution may perform slowly.  A faster alternative library based on PyMC--sunode--has implemented Adams' method and BDF (backward differentation formula).  More information about sunode is available at: https://github.com/aseyboldt/sunode.
+
+
     .. math::
         \dfrac{dy}{dt} = f(y,t,p) \quad y(t_0) = y_0
 
@@ -64,6 +67,7 @@ def odefunc(y, t, p):
         times = np.arange(0.5, 5, 0.5)
 
         ode_model = DifferentialEquation(func=odefunc, times=times, n_states=1, n_theta=1, t0=0)
+
     """
     _itypes = [
         TensorType(floatX, (False,)),  # y0 as 1D floatX vector