Taylor moment expansion (TME) in Python
Please see the documentation of the package in https://tme.readthedocs.io.
Install
Install via pip install tme or python setup.py install (Please note that if you would like to use JaX, please
install jax by yourself beforehand).
Examples
import tme.base_jax as tme
import jax.numpy as jnp
from jax import jit, vmap
# 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, x[0]])
# Jit the 3-order TME mean and cov approximation functions
@jit
def tme_m_cov(x, dt):
return tme.mean_and_cov(x, dt, drift, dispersion, order=3)
# Compute E[X(t) | X(0)=x0]
x0 = jnp.array([0., -1])
ts = jnp.array([0.25, 0.5, 1.])
m_t, cov_t = vmap(tme_m_cov, in_axes=[None, 0])(x0, ts)
Inside folder examples, there are a few Jupyter notebooks showing how to use the TME method (in SymPy and JaX).
License
The GNU General Public License v3 or later
1 maintainer
Metadata
1 maintainer
Release files for tme 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
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| tme-0.2.0.tar.gz | 12.3 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| tme-0.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 23.1 kB
Release files / tme-0.2.0.tar.gz
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| Size | 12.3 kB |
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| Size | 10.7 kB |
| Tags | Python 3 |
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