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Taylor moment expansion in Python.

Project description

Taylor moment expansion (TME) in Python

Please see the documentation of the package in


Install via pip install tme or python install.


import tme.base_jax as tme
from jax import jit

# Define SDE coefficients.
alp = 1.
def drift(x):
    return jnp.array([x[1],
                      x[0] * (alp - x[0] ** 2) - x[1]])

def dispersion(x):
    return jnp.array([[0.],

# Jit the 3-order TME mean and cov approximation functions
def tme_m_cov(x, dt):
    return tme.mean_and_cov(x=x, dt=dt,
                            a=drift, b=dispersion, Qw=jnp.eye(1),

# Compute E[X(t) | X(0)=x0]
x0 = jnp.array([0., -1])
t = 1.

m_t, cov_t = tme_m_cov(x0, t)

Inside folder examples, there are a few Jupyter notebooks showing how to use the TME method (in SymPy and JaX).


The GNU General Public License v3 or later

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