orloge 1.0.0

Orloge

What and why

The idea of this project is to permit a fast and easy parsing of the log files from different solvers, specifically 'operations research' (OR) logs.

There exist bigger, and more robust libraries. In particular, IPET. The trouble I had was that it deals with too many benchmarking and GUI things and I wanted something simple I could modify and build on top.

In any case, a lot of the ideas and parsing strings were obtained or adapted from IPET, to whom I am graceful.

The supported solvers for the time being are: GUROBI, CPLEX and CBC. Specially the two first ones.

How

The basic idea is just to provide a unique interface function like the following:

import orloge as ol
ol.get_info_solver(path_to_solver_log, solver_name)

This returns a python dictionary with a lot of information from the log (see Examples below).

Installation

pip install orloge

or, for the development version:

pip install https://github.com/pchtsp/orloge/archive/master.zip

Testing

Run the command

 python3 -m unittest tests.SolverTest

if the output says OK, all tests were passed.

Reference

Main parameters

The most common parameters to extract are: best_bound, best_solution and time. These three parameters are obtained at the end of the solving process and summarize the best relaxed objective value obtained, the best integer objective value obtained and the time it took to do the solving.

Cuts

The cuts information can be accessed by the cuts_info key. It offers the best known bound after the cut phase has ended, the best solution (if any) after the cuts and the number of cuts made of each type.

Matrix

There are two matrices that are provided. The matrix key returns the number of variables, constraints and non-zero values before the pre-processing of the solver. The matrix_post key returns these same values after the pre-processing has been done.

Progress

The progress key returns a list of dataclass instances, one per row of the progress table the solver printed while solving. Each row carries the time, gap, best bound, best solution, iterations, nodes, among other columns. The set of columns can vary between solvers, but the names are normalized so the same name always means the same thing: CBC rows are MIPProgressRow, GUROBI rows are GUROBIProgressRow, and CPLEX rows are CPLEXProgressRow (both subclass MIPProgressRow, adding their own extra columns); CPSAT rows are the unrelated CPSATProgressRow. Numeric columns are parsed to int/float and become None when a value can't be trusted as a real number — except Objective and CutsBestBound, which can instead hold a short status string (e.g. "infeasible", "cutoff", "Cuts: 5") when the solver printed an annotation instead of a number on that row.

Status

The status is given in several ways. First, a raw string extraction is returned in status. Then, a normalized one using codes is given via sol_code and status_code keys. sol_code gives information about the quality of the solution obtained. status_code gives details about the status of the solver after finishing (mainly, the reason it stopped).

Other

There is also information about the pre-solving phase, the first bound and the first solution. Also, there's information about the time it took to solve the root node.

Examples

import orloge as ol
ol.get_info_solver('tests/data/cbc298-app1-2.out', 'CBC')

Would produce the following:

{'best_bound': -96.111283,
 'best_solution': None,
 'cut_info': {},
 'first_relaxed': -210.09571,
 'first_solution': None,
 'gap': None,
 'matrix': {'constraints': 53467, 'nonzeros': 199175, 'variables': 26871},
 'matrix_post': {'constraints': 26555, 'nonzeros': 195875, 'variables': 13265},
 'nodes': 31867,
 'presolve': None,
 'progress': [MIPProgressRow(Node=0, NodesLeft=1, BestInteger=1e+50, CutsBestBound=-210.09571, Time=32.83),
              MIPProgressRow(Node=100, NodesLeft=11, BestInteger=1e+50, CutsBestBound=-210.09571, Time=124.49),
              ...
              # 319 rows total
              ],
 'rootTime': None,
 'sol_code': 0,
 'solver': 'CBC',
 'status': 'Stopped on time limit',
 'status_code': -4,
 'time': 7132.49,
 'version': '2.9.8'}

And another example, this time using GUROBI:

import orloge as ol
ol.get_info_solver('tests/data/gurobi700-app1-2.out', 'GUROBI')

Creates the following output:

{'best_bound': -41.0,
 'best_solution': -41.0,
 'cut_info': {'best_bound': -167.97894,
              'best_solution': -41.0,
              'cuts': {'Clique': 1,
                       'Gomory': 16,
                       'Implied bound': 23,
                       'MIR': 22},
              'time': 21.0},
 'first_relaxed': -178.94318,
 'first_solution': {'Node': 0, 'NodesLeft': 0, 'BestInteger': -41.0, 'CutsBestBound': -178.94318},
 'gap': 0,
 'matrix': {'constraints': 53467, 'nonzeros': 199175, 'variables': 26871},
 'matrix_post': {'constraints': 35616, 'nonzeros': 149085, 'variables': 22010},
 'nodes': 526.0,
 'presolve': {'cols': 4861, 'rows': 17851, 'time': 3.4},
 'progress': [GUROBIProgressRow(Node=0, NodesLeft=0, BestInteger=-41.0, CutsBestBound=-178.94318, Time=4.0,
                                 Objective=-178.94318, Depth=0, IInf=282, Gap=336.0, ItpNode=None),
              GUROBIProgressRow(Node=0, NodesLeft=0, BestInteger=-41.0, CutsBestBound=-171.91701, Time=15.0,
                                 Objective=-171.91701, Depth=0, IInf=268, Gap=319.0, ItpNode=None),
              ...
              # 26 rows total
              ],
 'rootTime': 0.7,
 'sol_code': 1,
 'solver': 'GUROBI',
 'status': 'Optimal solution found',
 'status_code': 1,
 'time': 46.67,
 'version': '7.0.0'}

Parsing the complete progress table helps anyone who later wants to analyze the raw solution process. I've tried to use the status codes and solution codes present in PuLP.