Welcome to NuCS’ documentation!

NuCS is a 100% Python library leveraging Numpy and Numba.

• Python is a powerful and flexible programing language that allows to express complex problems in a few lines of code.

• Numpy is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays.

• Numba translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. Numba-compiled numerical algorithms in Python can approach the speeds of C or FORTRAN.

Check out the Installation section for further information to get started with NuCS!

Note

This project is under active development.

Contents

• Installation
  • Install the NuCS package
  • Run some examples
    • Solve the 12-queens problem
    • Solve the Golomb ruler problem
  • Write your first model
    • Model the n-queens problem
• Variables
  • Decision variables
• Domains
  • Supported domains
    • Integer domains
    • Boolean domains
• Propagators (aka constraints)
  • Propagator functions
    • compute_domains function
    • get_triggers function
    • get_complexity function
  • Custom propagators
• Problems
  • The constructor of the Problem class
  • A concrete example: the 4-queens problem
• Consistency algorithms
  • Bound consistency algorithm
  • Bound consistency algorithm with shaving
  • Custom consistency algorithms
• Solvers
  • Solver arguments
  • Backtracking-based solver
    • Backtracking solver arguments
  • Multiprocessing-based solver
• Heuristics
  • Custom heuristics
• Statistics
• Logging
• Reference documentation
  • Consistency algorithms
  • Examples
  • Heuristics
    • Heuristics for selecting a variable
    • Heuristics for reducing the chosen domain
  • Problems
  • Propagators
  • Solvers
  • Statistics