Metadata-Version: 2.1
Name: myopenopt
Version: 0.0.3
Summary: `myopenopt` is a package for myopenopt.
Home-page: https://github.com/SaitoTsutomu/myopenopt
Author: Mikio Kubo
Author-email: kubomikio@gmail.com
Requires-Python: >=3.7.0,<3.8.0
Classifier: Development Status :: 1 - Planning
Classifier: License :: OSI Approved :: Python Software Foundation License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Requires-Dist: FuncDesigner (>=0.5629,<0.5630)
Requires-Dist: openopt (>=0.5629,<0.5630)
Description-Content-Type: text/x-rst

Myopenopt is a wrapper module for openopt. It supports to call openopt using the same functions and classes as in Gurobi, a commercial mixed integer optimization solver.
For more details, see the Gurobi HP http://www.gurobi.com/.
::

    from myopenopt import *
    model = Model("sample", mtype='NLP')
    x1 = model.addVar(vtype="C", name="x1")
    x2 = model.addVar(vtype="C", name="x2")
    x3 = model.addVar(vtype="C", ub=10, name="x3")
    model.update()
    c1 = model.addConstr(x1**2 + 2*x2**2 <= x3**2, name="C1")
    c2 = model.addConstr(x3 <= 30, name="C2")
    c3 = model.addConstr(quicksum([x1, x2, x3]) <= 20, name="C3" )
    model.setObjective(15*x1 + 18*x2 + 30*x3, GRB.MAXIMIZE)
    print(model)
    model.optimize(solver="ralg")
    print("Result =", model.Status)
    for v in model.getVars():
        print(v.VarName, v.X)

Requirements
------------
* Python 3.7 and openopt, FuncDesigner

Features
--------
* nothing

Setup
-----
::

   Add compiler path(ex. C:\Anaconda3\MinGW\bin)
   $ pip install openopt
   $ pip install FuncDesigner
   $ pip install myopenopt

History
-------
0.0.1 (2015-5-4)
~~~~~~~~~~~~~~~~~~
* first release

