Metadata-Version: 1.2
Name: pxpy
Version: 1.0a34
Summary: discrete pairwise undirected graphical models
Home-page: https://www.randomfields.org/px
Author: Nico Piatkowski
Author-email: nico.piatkowski@gmail.com
License: UNKNOWN
Description: Copyright (c) 2020 Nico Piatkowski
        
        pxpy
        ====
        The python library for discrete pairwise undirected graphical models.
        
        Inference:
        * Loopy belief propagation (GPU support)
        * Junction tree
        * Stochastic Clenshaw-Curtis quadrature
        
        Sampling:
        * Gibbs Sampling
        * Perturb+Map Sampling
        
        Parameter learning:
        * Accelerated proximal gradient
        * built-in L1 / L2 regularization
        * Supports arbitrary custom regularization
        
        Structure learning:
        * Chow-Liu trees
        * Soft-thresolding
        * High-order clique structures
        
        Misc:
        * Support for spatio-temporal compressible reparametrization (STRF)
        * Runs on x86_64 (linux, windows), ARMv8 (linux), and MSP430 (bare metal)
        * Basic graph drawing via graphviz
        * Discretization
        
        <https://randomfields.org>
        
        Changelog
        =========
        * 1.0a30---1.0a34: Improved: Randomized clique search
        * 1.0a29: Added: Randomized clique search
        * 1.0a28: Improved: Handling NaN-values during discretization (now interpreted as missing)
        * 1.0a27: Improved: Accelerated structure estimation
        * 1.0a26: Improved: Progress computation. Added: Online entropy computation for large cliques
        * 1.0a25: Improved: Memory management
        * 1.0a24: Improved: Structure estimation, backend. Added: Third-order structure estimation; simple graphviz output
        * 1.0a23: Improved: Structure estimation
        * 1.0a22: Improved: Discretization engine, support for external inference engine. Added: default to 32bit computation (disable via env PX_USE64BIT)
        * 1.0a21: Improved: Support for external inference engine
        * 1.0a20: Added: Support for external inference engine (access via env PX_EXTINF)
        * 1.0a19: Improved: Manual model creation
        * 1.0a18: Added: Debug mode (linux only, enable via env PX_DEBUGMODE)
        * 1.0a17: Improved: API, tests, regularization. Added: AIC and BIC computation
        * 1.0a16: Improved: Memory management, access to optimizer state in optimization hooks. Added: Support for training resumption
        * 1.0a15: Improved: API
        * 1.0a14: Improved: Memory management
        * 1.0a13: Improved: Memory management (fixed leak in conditional sampling/marginals)
        * 1.0a12: Improved: Access to vertex and pairwise marginals
        * 1.0a11: Added: Access to single variable marginals
        * 1.0a10: Improved: Library build process
        * 1.0a9:  Added: Conditional sampling
        * 1.0a8:  Imroved: Maximum-a-posteriori (MAP) estimation. Added: Custom graph construction
        * 1.0a7:  Added: Conditional marginal inference, support for Ising/minimal statistics
        * 1.0a6:  Added: Manual model creation, support for training data with missing values (represented by pxpy.MISSING_VALUE)
        * 1.0a5:  Improved: Model management
        * 1.0a4:  Added: Model access in regularization and proximal hooks
        * 1.0a3:  Improved: GLIBC requirement, removed libgomp dependency
        * 1.0a2:  Added: Python 3.5 compatibility
        * 1.0a1:  Initial release
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: License :: Free for non-commercial use
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Microsoft :: Windows
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.5
