Metadata-Version: 1.1
Name: cog-suspect
Version: 1.0.4
Summary: Special Structure Detection for Pyomo
Home-page: https://github.com/cog-imperial/suspect
Author: Francesco Ceccon
Author-email: francesco@ceccon.me
License: Apache 2.0
Description: Special Structure Detection for Pyomo
        =====================================
        
        |DOI|_ |travis|_ |codecov|_
        
        .. |DOI| image:: https://zenodo.org/badge/127118649.svg
        .. _DOI: https://zenodo.org/badge/latestdoi/127118649
        .. |travis| image:: https://travis-ci.org/cog-imperial/suspect.svg?branch=master
        .. _travis: https://travis-ci.org/cog-imperial/suspect
        .. |codecov| image:: https://codecov.io/gh/cog-imperial/suspect/branch/master/graph/badge.svg
        .. _codecov: https://codecov.io/gh/cog-imperial/suspect
        
        
        This library implements methods to:
        
        * Detect convex and concave expressions
        * Detect increasing and decreasing expressions
        * Detect linear, quadratic and polynomial expressions
        * Tighten expression bounds
        
        
        Documentation
        -------------
        
        Documentation is available at https://cog-imperial.github.io/suspect/
        
        
        Installation
        ------------
        
        SUSPECT requires Python 3.5 or later. We recommend installing SUSPECT in
        a virtual environment
        
        To create the virtual environment run::
        
            $ python3 -m venv myenv
            $ source myenv/bin/activate
        
        Then you are ready to clone and install SUSPECT::
        
            $ git clone https://github.com/cog-imperial/suspect.git
            $ cd suspect
            $ pip install -r requirements.txt
            $ pip install .
        
        
        Command Line Usage
        ------------------
        
        The package contains an utility to display structure information about
        a single problem.
        
        You can run the utility as::
        
            model_summary.py -p /path/to/problem.osil
        
        or, if you want to check variables bounds include the solution::
        
            model_summary.py -p /path/to/problem.osil -s /path/to/problem.sol
        
        The repository also includes a `Dockerfile` to simplify running the utility in
        batch mode in a cloud environment. Refer to the `batch` folder for more information.
        
        
        Library Usage
        -------------
        
        .. code-block:: python
        
            from suspect import (
        	    set_pyomo4_expression_tree,
        	    detect_special_structure,
            )
            import pyomo.environ as aml
        
        
            set_pyomo4_expression_tree()
        
        
            model = aml.ConcreteModel()
            model.x = aml.Var()
            model.y = aml.Var()
        
            model.obj = aml.Objective(expr=(model.y - model.x)**3)
            model.c1 = aml.Constraint(expr=model.y - model.x >= 0)
        
            info = detect_special_structure(model)
        
            # try info.variables, info.objectives, and info.constraints
            print(info.objectives['obj'])
        
        
        License
        -------
        
        Copyright 2018 Francesco Ceccon
        
        Licensed under the Apache License, Version 2.0 (the "License");
        you may not use this file except in compliance with the License.
        You may obtain a copy of the License at::
        
            http://www.apache.org/licenses/LICENSE-2.0
        
        Unless required by applicable law or agreed to in writing, software
        distributed under the License is distributed on an "AS IS" BASIS,
        WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
        See the License for the specific language governing permissions and
        limitations under the License.
        
        
        Changelog
        =========
        
        1.0.4
        -----
        
        * First public release. Yay!
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Mathematics
