feat: 初始化Easy Patch插件及依赖文件
- 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
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154
utils/pulp/apis/mipcl_api.py
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154
utils/pulp/apis/mipcl_api.py
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# 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, subprocess, PulpSolverError
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import os
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from .. import constants
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import warnings
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class MIPCL_CMD(LpSolver_CMD):
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"""The MIPCL_CMD solver"""
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name = "MIPCL_CMD"
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def __init__(
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self,
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path=None,
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keepFiles=False,
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mip=True,
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msg=True,
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options=None,
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timeLimit=None,
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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 list options: list of additional options to pass to solver
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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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"""
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LpSolver_CMD.__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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options=options,
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path=path,
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keepFiles=keepFiles,
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)
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def defaultPath(self):
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return self.executableExtension("mps_mipcl")
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def available(self):
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"""True if the solver is available"""
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return self.executable(self.path)
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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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tmpMps, tmpSol = self.create_tmp_files(lp.name, "mps", "sol")
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if lp.sense == constants.LpMaximize:
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# we swap the objectives
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# because it does not handle maximization.
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warnings.warn(
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"MIPCL_CMD does not allow maximization, "
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"we will minimize the inverse of the objective function."
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)
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lp += -lp.objective
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lp.checkDuplicateVars()
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lp.checkLengthVars(52)
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lp.writeMPS(tmpMps, mpsSense=lp.sense)
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# just to report duplicated variables:
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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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cmd += f" {tmpMps}"
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cmd += f" -solfile {tmpSol}"
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if self.timeLimit is not None:
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cmd += f" -time {self.timeLimit}"
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for option in self.options:
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cmd += " " + option
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if lp.isMIP():
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if not self.mip:
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warnings.warn("MIPCL_CMD cannot solve the relaxation of a problem")
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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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# We need to undo the objective swap before finishing
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if lp.sense == constants.LpMaximize:
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lp += -lp.objective
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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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status = constants.LpStatusNotSolved
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status_sol = constants.LpSolutionNoSolutionFound
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values = None
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else:
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status, values, status_sol = self.readsol(tmpSol)
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self.delete_tmp_files(tmpMps, tmpSol)
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lp.assignStatus(status, status_sol)
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if status not in [constants.LpStatusInfeasible, constants.LpStatusNotSolved]:
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lp.assignVarsVals(values)
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return status
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@staticmethod
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def readsol(filename):
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"""Read a MIPCL solution file"""
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with open(filename) as f:
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content = f.readlines()
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content = [l.strip() for l in content]
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values = {}
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if not len(content):
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return (
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constants.LpStatusNotSolved,
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values,
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constants.LpSolutionNoSolutionFound,
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)
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first_line = content[0]
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if first_line == "=infeas=":
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return constants.LpStatusInfeasible, values, constants.LpSolutionInfeasible
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objective, value = first_line.split()
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# this is a workaround.
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# Not sure if it always returns this limit when unbounded.
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if abs(float(value)) >= 9.999999995e10:
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return constants.LpStatusUnbounded, values, constants.LpSolutionUnbounded
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for line in content[1:]:
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name, value = line.split()
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values[name] = float(value)
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# I'm not sure how this solver announces the optimality
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# of a solution so we assume it is integer feasible
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return constants.LpStatusOptimal, values, constants.LpSolutionIntegerFeasible
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