小煜
ab91b120e6
- 添加Blender插件核心文件：__init__.py、ui.py、property.py、preference.py - 添加插件工具模块：g.py、loop.py、generate_loop.py、const.py、op.py - 添加翻译工具：utils/trans.py - 添加PuLP线性规划库及其依赖文件，包括CBC求解器二进制文件 - 添加.gitignore和VSCode配置文件
567 lines
22 KiB
Python
567 lines
22 KiB
Python
# PuLP : Python LP Modeler
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# Version 1.4.2
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# Copyright (c) 2002-2005, Jean-Sebastien Roy (js@jeannot.org)
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# Modifications Copyright (c) 2007- Stuart Anthony Mitchell (s.mitchell@auckland.ac.nz)
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# $Id:solvers.py 1791 2008-04-23 22:54:34Z smit023 $
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# Permission is hereby granted, free of charge, to any person obtaining a
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# copy of this software and associated documentation files (the
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# "Software"), to deal in the Software without restriction, including
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# without limitation the rights to use, copy, modify, merge, publish,
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# distribute, sublicense, and/or sell copies of the Software, and to
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# permit persons to whom the Software is furnished to do so, subject to
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# the following conditions:
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# The above copyright notice and this permission notice shall be included
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# in all copies or substantial portions of the Software.
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
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# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
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# IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
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# CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
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# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
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# SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."""
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from .core import LpSolver_CMD, LpSolver, subprocess, PulpSolverError, clock, log
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from .core import gurobi_path
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import os
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import sys
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from .. import constants
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import warnings
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# to import the gurobipy name into the module scope
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gp = None
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class GUROBI(LpSolver):
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"""
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The Gurobi LP/MIP solver (via its python interface)
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The Gurobi variables are available (after a solve) in var.solverVar
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Constraints in constraint.solverConstraint
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and the Model is in prob.solverModel
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"""
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name = "GUROBI"
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env = None
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try:
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sys.path.append(gurobi_path)
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# to import the name into the module scope
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global gp
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import gurobipy as gp
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except: # FIXME: Bug because gurobi returns
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# a gurobi exception on failed imports
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def available(self):
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"""True if the solver is available"""
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return False
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def actualSolve(self, lp, callback=None):
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"""Solve a well formulated lp problem"""
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raise PulpSolverError("GUROBI: Not Available")
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else:
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def __init__(
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self,
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mip=True,
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msg=True,
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timeLimit=None,
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epgap=None,
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gapRel=None,
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warmStart=False,
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logPath=None,
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env=None,
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envOptions=None,
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manageEnv=False,
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**solverParams,
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):
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"""
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:param bool mip: if False, assume LP even if integer variables
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:param bool msg: if False, no log is shown
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:param float timeLimit: maximum time for solver (in seconds)
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:param float gapRel: relative gap tolerance for the solver to stop (in fraction)
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:param bool warmStart: if True, the solver will use the current value of variables as a start
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:param str logPath: path to the log file
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:param float epgap: deprecated for gapRel
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:param gp.Env env: Gurobi environment to use. Default None.
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:param dict envOptions: environment options.
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:param bool manageEnv: if False, assume the environment is handled by the user.
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If ``manageEnv`` is set to True, the ``GUROBI`` object creates a
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local Gurobi environment and manages all associated Gurobi
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resources. Importantly, this enables Gurobi licenses to be freed
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and connections terminated when the ``.close()`` function is called
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(this function always disposes of the Gurobi model, and the
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environment)::
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solver = GUROBI(manageEnv=True)
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prob.solve(solver)
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solver.close() # Must be called to free Gurobi resources.
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# All Gurobi models and environments are freed
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``manageEnv=True`` is required when setting license or connection
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parameters. The ``envOptions`` argument is used to pass parameters
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to the Gurobi environment. For example, to connect to a Gurobi
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Cluster Manager::
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options = {
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"CSManager": "<url>",
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"CSAPIAccessID": "<access-id>",
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"CSAPISecret": "<api-key>",
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}
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solver = GUROBI(manageEnv=True, envOptions=options)
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solver.close()
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# Compute server connection terminated
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Alternatively, one can also pass a ``gp.Env`` object. In this case,
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to be safe, one should still call ``.close()`` to dispose of the
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model::
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with gp.Env(params=options) as env:
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# Pass environment as a parameter
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solver = GUROBI(env=env)
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prob.solve(solver)
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solver.close()
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# Still call `close` as this disposes the model which is required to correctly free env
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If ``manageEnv`` is set to False (the default), the ``GUROBI``
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object uses the global default Gurobi environment which will be
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freed once the object is deleted. In this case, one can still call
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``.close()`` to dispose of the model::
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solver = GUROBI()
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prob.solve(solver)
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# The global default environment and model remain active
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solver.close()
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# Only the global default environment remains active
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"""
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self.env = env
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self.env_options = envOptions if envOptions else {}
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self.manage_env = False if self.env is not None else manageEnv
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self.solver_params = solverParams
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self.model = None
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self.init_gurobi = False # whether env and model have been initialised
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if epgap is not None:
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warnings.warn("Parameter epgap is being depreciated for gapRel")
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if gapRel is not None:
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warnings.warn("Parameter gapRel and epgap passed, using gapRel")
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else:
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gapRel = epgap
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LpSolver.__init__(
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self,
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mip=mip,
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msg=msg,
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timeLimit=timeLimit,
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gapRel=gapRel,
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logPath=logPath,
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warmStart=warmStart,
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)
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# set the output of gurobi
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if not self.msg:
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if self.manage_env:
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self.env_options["OutputFlag"] = 0
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else:
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self.env_options["OutputFlag"] = 0
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self.solver_params["OutputFlag"] = 0
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def __del__(self):
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self.close()
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def close(self):
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"""
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Must be called when internal Gurobi model and/or environment
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requires disposing. The environment (default or otherwise) will be
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disposed only if ``manageEnv`` is set to True.
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"""
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if not self.init_gurobi:
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return
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self.model.dispose()
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if self.manage_env:
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self.env.dispose()
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def findSolutionValues(self, lp):
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model = lp.solverModel
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solutionStatus = model.Status
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GRB = gp.GRB
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# TODO: check status for Integer Feasible
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gurobiLpStatus = {
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GRB.OPTIMAL: constants.LpStatusOptimal,
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GRB.INFEASIBLE: constants.LpStatusInfeasible,
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GRB.INF_OR_UNBD: constants.LpStatusInfeasible,
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GRB.UNBOUNDED: constants.LpStatusUnbounded,
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GRB.ITERATION_LIMIT: constants.LpStatusNotSolved,
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GRB.NODE_LIMIT: constants.LpStatusNotSolved,
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GRB.TIME_LIMIT: constants.LpStatusNotSolved,
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GRB.SOLUTION_LIMIT: constants.LpStatusNotSolved,
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GRB.INTERRUPTED: constants.LpStatusNotSolved,
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GRB.NUMERIC: constants.LpStatusNotSolved,
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}
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if self.msg:
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print("Gurobi status=", solutionStatus)
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lp.resolveOK = True
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for var in lp._variables:
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var.isModified = False
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status = gurobiLpStatus.get(solutionStatus, constants.LpStatusUndefined)
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lp.assignStatus(status)
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if model.SolCount >= 1:
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# populate pulp solution values
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for var, value in zip(
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lp._variables, model.getAttr(GRB.Attr.X, model.getVars())
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):
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var.varValue = value
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# populate pulp constraints slack
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for constr, value in zip(
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lp.constraints.values(),
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model.getAttr(GRB.Attr.Slack, model.getConstrs()),
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):
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constr.slack = value
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# put pi and slack variables against the constraints
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if not model.IsMIP:
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for var, value in zip(
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lp._variables, model.getAttr(GRB.Attr.RC, model.getVars())
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):
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var.dj = value
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for constr, value in zip(
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lp.constraints.values(),
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model.getAttr(GRB.Attr.Pi, model.getConstrs()),
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):
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constr.pi = value
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return status
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def available(self):
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"""True if the solver is available"""
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try:
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with gp.Env(params=self.env_options):
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pass
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except gurobipy.GurobiError as e:
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warnings.warn(f"GUROBI error: {e}.")
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return False
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return True
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def initGurobi(self):
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if self.init_gurobi:
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return
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else:
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self.init_gurobi = True
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try:
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if self.manage_env:
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self.env = gp.Env(params=self.env_options)
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self.model = gp.Model(env=self.env)
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# Environment handled by user or default Env
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else:
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self.model = gp.Model(env=self.env)
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# Set solver parameters
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for param, value in self.solver_params.items():
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self.model.setParam(param, value)
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except gp.GurobiError as e:
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raise e
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def callSolver(self, lp, callback=None):
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"""Solves the problem with gurobi"""
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# solve the problem
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self.solveTime = -clock()
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lp.solverModel.optimize(callback=callback)
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self.solveTime += clock()
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def buildSolverModel(self, lp):
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"""
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Takes the pulp lp model and translates it into a gurobi model
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"""
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log.debug("create the gurobi model")
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self.initGurobi()
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self.model.ModelName = lp.name
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lp.solverModel = self.model
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log.debug("set the sense of the problem")
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if lp.sense == constants.LpMaximize:
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lp.solverModel.setAttr("ModelSense", -1)
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if self.timeLimit:
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lp.solverModel.setParam("TimeLimit", self.timeLimit)
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gapRel = self.optionsDict.get("gapRel")
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logPath = self.optionsDict.get("logPath")
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if gapRel:
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lp.solverModel.setParam("MIPGap", gapRel)
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if logPath:
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lp.solverModel.setParam("LogFile", logPath)
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log.debug("add the variables to the problem")
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lp.solverModel.update()
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nvars = lp.solverModel.NumVars
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for var in lp.variables():
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lowBound = var.lowBound
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if lowBound is None:
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lowBound = -gp.GRB.INFINITY
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upBound = var.upBound
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if upBound is None:
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upBound = gp.GRB.INFINITY
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obj = lp.objective.get(var, 0.0)
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varType = gp.GRB.CONTINUOUS
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if var.cat == constants.LpInteger and self.mip:
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varType = gp.GRB.INTEGER
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# only add variable once, ow new variable will be created.
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if not hasattr(var, "solverVar") or nvars == 0:
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var.solverVar = lp.solverModel.addVar(
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lowBound, upBound, vtype=varType, obj=obj, name=var.name
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)
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if self.optionsDict.get("warmStart", False):
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# Once lp.variables() has been used at least once in the building of the model.
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# we can use the lp._variables with the cache.
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for var in lp._variables:
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if var.varValue is not None:
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var.solverVar.start = var.varValue
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lp.solverModel.update()
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log.debug("add the Constraints to the problem")
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for name, constraint in lp.constraints.items():
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# build the expression
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expr = gp.LinExpr(
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list(constraint.values()), [v.solverVar for v in constraint.keys()]
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)
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if constraint.sense == constants.LpConstraintLE:
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constraint.solverConstraint = lp.solverModel.addConstr(
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expr <= -constraint.constant, name=name
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)
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elif constraint.sense == constants.LpConstraintGE:
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constraint.solverConstraint = lp.solverModel.addConstr(
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expr >= -constraint.constant, name=name
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)
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elif constraint.sense == constants.LpConstraintEQ:
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constraint.solverConstraint = lp.solverModel.addConstr(
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expr == -constraint.constant, name=name
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)
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else:
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raise PulpSolverError("Detected an invalid constraint type")
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lp.solverModel.update()
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def actualSolve(self, lp, callback=None):
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"""
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Solve a well formulated lp problem
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creates a gurobi model, variables and constraints and attaches
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them to the lp model which it then solves
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"""
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self.buildSolverModel(lp)
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# set the initial solution
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log.debug("Solve the Model using gurobi")
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self.callSolver(lp, callback=callback)
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# get the solution information
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solutionStatus = self.findSolutionValues(lp)
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for var in lp._variables:
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var.modified = False
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for constraint in lp.constraints.values():
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constraint.modified = False
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return solutionStatus
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def actualResolve(self, lp, callback=None):
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"""
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Solve a well formulated lp problem
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uses the old solver and modifies the rhs of the modified constraints
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"""
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log.debug("Resolve the Model using gurobi")
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for constraint in lp.constraints.values():
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if constraint.modified:
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constraint.solverConstraint.setAttr(
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gp.GRB.Attr.RHS, -constraint.constant
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)
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lp.solverModel.update()
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self.callSolver(lp, callback=callback)
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# get the solution information
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solutionStatus = self.findSolutionValues(lp)
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for var in lp._variables:
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var.modified = False
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for constraint in lp.constraints.values():
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constraint.modified = False
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return solutionStatus
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class GUROBI_CMD(LpSolver_CMD):
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"""The GUROBI_CMD solver"""
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name = "GUROBI_CMD"
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def __init__(
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self,
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mip=True,
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msg=True,
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timeLimit=None,
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gapRel=None,
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gapAbs=None,
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options=None,
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warmStart=False,
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keepFiles=False,
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path=None,
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threads=None,
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logPath=None,
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mip_start=False,
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):
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"""
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:param bool mip: if False, assume LP even if integer variables
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:param bool msg: if False, no log is shown
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:param float timeLimit: maximum time for solver (in seconds)
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:param float gapRel: relative gap tolerance for the solver to stop (in fraction)
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:param float gapAbs: absolute gap tolerance for the solver to stop
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:param int threads: sets the maximum number of threads
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:param list options: list of additional options to pass to solver
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:param bool warmStart: if True, the solver will use the current value of variables as a start
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:param bool keepFiles: if True, files are saved in the current directory and not deleted after solving
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:param str path: path to the solver binary
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:param str logPath: path to the log file
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:param bool mip_start: deprecated for warmStart
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"""
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if mip_start:
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warnings.warn("Parameter mip_start is being depreciated for warmStart")
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if warmStart:
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warnings.warn(
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"Parameter warmStart and mip_start passed, using warmStart"
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)
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else:
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warmStart = mip_start
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LpSolver_CMD.__init__(
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self,
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gapRel=gapRel,
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mip=mip,
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msg=msg,
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timeLimit=timeLimit,
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options=options,
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warmStart=warmStart,
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path=path,
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keepFiles=keepFiles,
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threads=threads,
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gapAbs=gapAbs,
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logPath=logPath,
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)
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def defaultPath(self):
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return self.executableExtension("gurobi_cl")
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def available(self):
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"""True if the solver is available"""
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if not self.executable(self.path):
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return False
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# we execute gurobi once to check the return code.
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# this is to test that the license is active
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result = subprocess.Popen(
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self.path, stdout=subprocess.PIPE, universal_newlines=True
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)
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out, err = result.communicate()
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if result.returncode == 0:
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# normal execution
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return True
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# error: we display the gurobi message
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warnings.warn(f"GUROBI error: {out}.")
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return False
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def actualSolve(self, lp):
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"""Solve a well formulated lp problem"""
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if not self.executable(self.path):
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raise PulpSolverError("PuLP: cannot execute " + self.path)
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tmpLp, tmpSol, tmpMst = self.create_tmp_files(lp.name, "lp", "sol", "mst")
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vs = lp.writeLP(tmpLp, writeSOS=1)
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try:
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os.remove(tmpSol)
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except:
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pass
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cmd = self.path
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options = self.options + self.getOptions()
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if self.timeLimit is not None:
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options.append(("TimeLimit", self.timeLimit))
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cmd += " " + " ".join([f"{key}={value}" for key, value in options])
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cmd += f" ResultFile={tmpSol}"
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if self.optionsDict.get("warmStart", False):
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self.writesol(filename=tmpMst, vs=vs)
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cmd += f" InputFile={tmpMst}"
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if lp.isMIP():
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if not self.mip:
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warnings.warn("GUROBI_CMD does not allow a problem to be relaxed")
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cmd += f" {tmpLp}"
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if self.msg:
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pipe = None
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else:
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pipe = open(os.devnull, "w")
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return_code = subprocess.call(cmd.split(), stdout=pipe, stderr=pipe)
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# Close the pipe now if we used it.
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if pipe is not None:
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pipe.close()
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if return_code != 0:
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raise PulpSolverError("PuLP: Error while trying to execute " + self.path)
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if not os.path.exists(tmpSol):
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# TODO: the status should be infeasible here, I think
|
|
status = constants.LpStatusNotSolved
|
|
values = reducedCosts = shadowPrices = slacks = None
|
|
else:
|
|
# TODO: the status should be infeasible here, I think
|
|
status, values, reducedCosts, shadowPrices, slacks = self.readsol(tmpSol)
|
|
self.delete_tmp_files(tmpLp, tmpMst, tmpSol, "gurobi.log")
|
|
if status != constants.LpStatusInfeasible:
|
|
lp.assignVarsVals(values)
|
|
lp.assignVarsDj(reducedCosts)
|
|
lp.assignConsPi(shadowPrices)
|
|
lp.assignConsSlack(slacks)
|
|
lp.assignStatus(status)
|
|
return status
|
|
|
|
def readsol(self, filename):
|
|
"""Read a Gurobi solution file"""
|
|
with open(filename) as my_file:
|
|
try:
|
|
next(my_file) # skip the objective value
|
|
except StopIteration:
|
|
# Empty file not solved
|
|
status = constants.LpStatusNotSolved
|
|
return status, {}, {}, {}, {}
|
|
# We have no idea what the status is assume optimal
|
|
# TODO: check status for Integer Feasible
|
|
status = constants.LpStatusOptimal
|
|
|
|
shadowPrices = {}
|
|
slacks = {}
|
|
shadowPrices = {}
|
|
slacks = {}
|
|
values = {}
|
|
reducedCosts = {}
|
|
for line in my_file:
|
|
if line[0] != "#": # skip comments
|
|
name, value = line.split()
|
|
values[name] = float(value)
|
|
return status, values, reducedCosts, shadowPrices, slacks
|
|
|
|
def writesol(self, filename, vs):
|
|
"""Writes a GUROBI solution file"""
|
|
|
|
values = [(v.name, v.value()) for v in vs if v.value() is not None]
|
|
rows = []
|
|
for name, value in values:
|
|
rows.append(f"{name} {value}")
|
|
with open(filename, "w") as f:
|
|
f.write("\n".join(rows))
|
|
return True
|
|
|
|
def getOptions(self):
|
|
# GUROBI parameters: http://www.gurobi.com/documentation/7.5/refman/parameters.html#sec:Parameters
|
|
params_eq = dict(
|
|
logPath="LogFile",
|
|
gapRel="MIPGap",
|
|
gapAbs="MIPGapAbs",
|
|
threads="Threads",
|
|
)
|
|
return [
|
|
(v, self.optionsDict[k])
|
|
for k, v in params_eq.items()
|
|
if k in self.optionsDict and self.optionsDict[k] is not None
|
|
]
|