pxpy 1.0a52

discrete pairwise undirected graphical models

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 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), ARMv8 (linux), and MSP430 * Graph drawing via graphviz * Discretization

<https://randomfields.org>

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## Alpha Changelog * 1.0a52: Improved: Graph splitting; startup 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