Metadata-Version: 1.2
Name: pxpy
Version: 1.0a56
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.
        Runs on Linux with GLIBC >= 2.28 and Windows 10.
        
        Inference
        =====================================================================
        * Loopy belief propagation
        * Junction tree
        * Stochastic Clenshaw-Curtis quadrature
        
        Sampling
        =====================================================================
        * Gibbs Sampling
        * Perturb+Map Sampling
        
        Parameter learning
        =====================================================================
        * Accelerated proximal gradient
        * built-in L1 / L2 regularization
        * Support for custom regularization
        
        Structure learning
        =====================================================================
        * Chow-Liu trees
        * Soft-thresolding
        * High-order clique structures
        
        Misc
        =====================================================================
        * Support for deep Boltzmann tree models (DBT)
        * Support for spatio-temporal compressible reparametrization (STRF)
        * Runs on x86_64 (linux, windows) and aarch64 (linux)
        * Graph drawing via graphviz
        * Discretization
        
        <https://randomfields.org>
        
        ---
        
        Alpha Changelog
        =====================================================================
        * 1.0a56: Improved: Numerical stability of discretization
        * 1.0a55: Added: Load/store of discretization models; aarch64 support (tested on Jetson TX1)
        * 1.0a54: Improved: Init speed
        * 1.0a53: Improved: Init speed
        * 1.0a52: Improved: Graph splitting; init speed
        * 1.0a51: Fixed: Multi-core normalization; Split-edge weight centering
        * 1.0a50: Improved: Support for external inference engines; Changed required GLIBC version to 2.29
        * 1.0a49: Fixed: External loader
        * 1.0a48: Added: Shell script "pxpy_environ" for populating various environment variables. Improved: multi-core support.
        * 1.0a47: Added: draw_neighbors(..). Improved: Discretization
        * 1.0a44: Improved: Discretization
        * 1.0a42: Improved: Updated some default values
        * 1.0a41: Improved: Fixed subtle bug in parameter initialization
        * 1.0a40: Added: Loading string data via genfromstrcsv(..) (built-in string<->int mapper)
        * 1.0a36: 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: >=3.8
