Summary
- Version:
1.2.1
- Author:
Keurfon Luu
- Web site:
- Copyright:
This document has been placed in the public domain.
- License:
StochOPy is released under the MIT License.
NOTE: StochOPy has been implemented in the frame of my Ph. D. thesis. If you find any error or bug, or if you have any suggestion, please don’t hesitate to contact me.
Features
StochOPy provides routines for sampling of a model parameter space:
Pure Monte-Carlo
Metropolis-Hastings algorithm
Hamiltonian (Hybrid) Monte-Carlo [1,2]
or optimization of an objective function:
Differential Evolution [3]
Particle Swarm Optimization [4,5]
Competitive Particle Swarm Optimization [6]
Covariance Matrix Adaptation - Evolution Strategy [7]
Installation
The recommended way to install StochOPy is through pip (internet required):
pip install stochopyOtherwise, download and extract the package, then run:
python setup.py installUsage
First, import StochOPy and define an objective function (here Rosenbrock):
import numpy as np
from stochopy import MonteCarlo, Evolutionary
f = lambda x: 100*np.sum((x[1:]-x[:-1]**2)**2)+np.sum((1-x[:-1])**2)You can define the search space boundaries if necessary:
n_dim = 2
lower = np.full(n_dim, -5.12)
upper = np.full(n_dim, 5.12)Initialize the Monte-Carlo sampler:
max_iter = 1000
mc = MonteCarlo(f, lower = lower, upper = upper, max_iter = max_iter)Now, you can start sampling with the simple method ‘sample’:
mc.sample(sampler = "hamiltonian", stepsize = 0.005, n_leap = 20, xstart = [ 2., 2. ])Note that sampler can be set to “pure” or “hastings” too. The models sampled and their corresponding energies are stored in:
print(mc.models)
print(mc.energy)Optimization is just as easy:
n_dim = 10
lower = np.full(n_dim, -5.12)
upper = np.full(n_dim, 5.12)
popsize = 4 + np.floor(3.*np.log(n_dim))
ea = Evolutionary(f, lower = lower, upper = upper, popsize = popsize, max_iter = max_iter)
xopt, gfit = ea.optimize(solver = "cmaes")
print(xopt)
print(gfit)References
1 maintainer
Release files for stochopy 1.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| stochopy-1.2.1.tar.gz | 29.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| stochopy-1.2.1-py3.5.egg | Legacy Egg format | - | - | Details |
Total release size: 64.9 kB
Release files / stochopy-1.2.1.tar.gz
| Download URL | stochopy-1.2.1.tar.gz |
|---|---|
| Size | 29.0 kB |
| Tags | Source |
|
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Release files / stochopy-1.2.1-py3.5.egg
| Download URL | stochopy-1.2.1-py3.5.egg |
|---|---|
| Size | 35.8 kB |
| Tags | Egg |
|
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