PyStan provides a Python interface to Stan, a package for Bayesian inference using the No-U-Turn sampler, a variant of Hamiltonian Monte Carlo.
For more information on Stan and its modeling language, see the Stan User’s Guide and Reference Manual at http://mc-stan.org/.
Important links
HTML documentation: https://pystan.readthedocs.org
Issue tracker: https://github.com/stan-dev/pystan/issues
Source code repository: https://github.com/stan-dev/pystan
Stan: http://mc-stan.org/
Stan User’s Guide and Reference Manual (pdf) available at http://mc-stan.org
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Installation
NumPy and Cython (version 0.19 or greater) are required. matplotlib is optional.
PyStan and the required packages may be installed from the Python Package Index using pip.
pip install pystan
Alternatively, if Cython (version 0.19 or greater) and NumPy are already available, PyStan may be installed from source with the following commands
git clone --recursive https://github.com/stan-dev/pystan.git cd pystan python setup.py install
If you encounter an ImportError after compiling from source, try changing out of the source directory before attempting import pystan. On Linux and OS X cd /tmp will work.
Example
import pystan
import numpy as np
schools_code = """
data {
int<lower=0> J; // number of schools
real y[J]; // estimated treatment effects
real<lower=0> sigma[J]; // s.e. of effect estimates
}
parameters {
real mu;
real<lower=0> tau;
real eta[J];
}
transformed parameters {
real theta[J];
for (j in 1:J)
theta[j] <- mu + tau * eta[j];
}
model {
eta ~ normal(0, 1);
y ~ normal(theta, sigma);
}
"""
schools_dat = {'J': 8,
'y': [28, 8, -3, 7, -1, 1, 18, 12],
'sigma': [15, 10, 16, 11, 9, 11, 10, 18]}
fit = pystan.stan(model_code=schools_code, data=schools_dat,
iter=1000, chains=4)
print(fit)
eta = fit.extract(permuted=True)['eta']
np.mean(eta, axis=0)
# if matplotlib is installed (optional, not required), a visual summary and
# traceplot are available
fit.plot()
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Release files for pystan 2.5.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pystan-2.5.0.1.tar.gz | 11.4 MB | Details |
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pystan-2.5.0.1-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.whl | CPython 3.4 | CPython 3.4 pymalloc | macOS 10.6+ Intel (x86-64, i386), macOS 10.9+ x86-64, macOS 10.9+ Intel (x86-64, i386) | Details |
| pystan-2.5.0.1-cp33-cp33m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.whl | CPython 3.3 | CPython 3.3 pymalloc | macOS 10.9+ Intel (x86-64, i386), macOS 10.9+ x86-64, macOS 10.6+ Intel (x86-64, i386) | Details |
| pystan-2.5.0.1-cp27-none-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.whl | CPython 2.7 | none | macOS 10.9+ Intel (x86-64, i386), macOS 10.6+ Intel (x86-64, i386), macOS 10.9+ x86-64 | Details |
Total release size: 150.5 MB
Release files / pystan-2.5.0.1.tar.gz
| Download URL | pystan-2.5.0.1.tar.gz |
|---|---|
| Size | 11.4 MB |
| Tags | Source |
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Release files / pystan-2.5.0.1-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.whl
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|---|---|
| Size | 46.4 MB |
| Tags | CPython 3.4 CPython 3.4 pymalloc macOS 10.6+ Intel (x86-64, i386) macOS 10.9+ Intel (x86-64, i386) macOS 10.9+ x86-64 |
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Release files / pystan-2.5.0.1-cp33-cp33m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.whl
| Download URL | pystan-2.5.0.1-cp33-cp33m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.whl |
|---|---|
| Size | 46.4 MB |
| Tags | CPython 3.3 CPython 3.3 pymalloc macOS 10.6+ Intel (x86-64, i386) macOS 10.9+ Intel (x86-64, i386) macOS 10.9+ x86-64 |
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Release files / pystan-2.5.0.1-cp27-none-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.whl
| Download URL | pystan-2.5.0.1-cp27-none-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.whl |
|---|---|
| Size | 46.4 MB |
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