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
This commit is contained in:
2026-03-03 19:24:57 +08:00
commit ab91b120e6
44 changed files with 17551 additions and 0 deletions

View File

@@ -0,0 +1,566 @@
# PuLP : Python LP Modeler
# Version 1.4.2
# Copyright (c) 2002-2005, Jean-Sebastien Roy (js@jeannot.org)
# Modifications Copyright (c) 2007- Stuart Anthony Mitchell (s.mitchell@auckland.ac.nz)
# $Id:solvers.py 1791 2008-04-23 22:54:34Z smit023 $
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the
# "Software"), to deal in the Software without restriction, including
# without limitation the rights to use, copy, modify, merge, publish,
# distribute, sublicense, and/or sell copies of the Software, and to
# permit persons to whom the Software is furnished to do so, subject to
# the following conditions:
# The above copyright notice and this permission notice shall be included
# in all copies or substantial portions of the Software.
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
# IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
# CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
# SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."""
from .core import LpSolver_CMD, LpSolver, subprocess, PulpSolverError, clock, log
from .core import gurobi_path
import os
import sys
from .. import constants
import warnings
# to import the gurobipy name into the module scope
gp = None
class GUROBI(LpSolver):
"""
The Gurobi LP/MIP solver (via its python interface)
The Gurobi variables are available (after a solve) in var.solverVar
Constraints in constraint.solverConstraint
and the Model is in prob.solverModel
"""
name = "GUROBI"
env = None
try:
sys.path.append(gurobi_path)
# to import the name into the module scope
global gp
import gurobipy as gp
except: # FIXME: Bug because gurobi returns
# a gurobi exception on failed imports
def available(self):
"""True if the solver is available"""
return False
def actualSolve(self, lp, callback=None):
"""Solve a well formulated lp problem"""
raise PulpSolverError("GUROBI: Not Available")
else:
def __init__(
self,
mip=True,
msg=True,
timeLimit=None,
epgap=None,
gapRel=None,
warmStart=False,
logPath=None,
env=None,
envOptions=None,
manageEnv=False,
**solverParams,
):
"""
:param bool mip: if False, assume LP even if integer variables
:param bool msg: if False, no log is shown
:param float timeLimit: maximum time for solver (in seconds)
:param float gapRel: relative gap tolerance for the solver to stop (in fraction)
:param bool warmStart: if True, the solver will use the current value of variables as a start
:param str logPath: path to the log file
:param float epgap: deprecated for gapRel
:param gp.Env env: Gurobi environment to use. Default None.
:param dict envOptions: environment options.
:param bool manageEnv: if False, assume the environment is handled by the user.
If ``manageEnv`` is set to True, the ``GUROBI`` object creates a
local Gurobi environment and manages all associated Gurobi
resources. Importantly, this enables Gurobi licenses to be freed
and connections terminated when the ``.close()`` function is called
(this function always disposes of the Gurobi model, and the
environment)::
solver = GUROBI(manageEnv=True)
prob.solve(solver)
solver.close() # Must be called to free Gurobi resources.
# All Gurobi models and environments are freed
``manageEnv=True`` is required when setting license or connection
parameters. The ``envOptions`` argument is used to pass parameters
to the Gurobi environment. For example, to connect to a Gurobi
Cluster Manager::
options = {
"CSManager": "<url>",
"CSAPIAccessID": "<access-id>",
"CSAPISecret": "<api-key>",
}
solver = GUROBI(manageEnv=True, envOptions=options)
solver.close()
# Compute server connection terminated
Alternatively, one can also pass a ``gp.Env`` object. In this case,
to be safe, one should still call ``.close()`` to dispose of the
model::
with gp.Env(params=options) as env:
# Pass environment as a parameter
solver = GUROBI(env=env)
prob.solve(solver)
solver.close()
# Still call `close` as this disposes the model which is required to correctly free env
If ``manageEnv`` is set to False (the default), the ``GUROBI``
object uses the global default Gurobi environment which will be
freed once the object is deleted. In this case, one can still call
``.close()`` to dispose of the model::
solver = GUROBI()
prob.solve(solver)
# The global default environment and model remain active
solver.close()
# Only the global default environment remains active
"""
self.env = env
self.env_options = envOptions if envOptions else {}
self.manage_env = False if self.env is not None else manageEnv
self.solver_params = solverParams
self.model = None
self.init_gurobi = False # whether env and model have been initialised
if epgap is not None:
warnings.warn("Parameter epgap is being depreciated for gapRel")
if gapRel is not None:
warnings.warn("Parameter gapRel and epgap passed, using gapRel")
else:
gapRel = epgap
LpSolver.__init__(
self,
mip=mip,
msg=msg,
timeLimit=timeLimit,
gapRel=gapRel,
logPath=logPath,
warmStart=warmStart,
)
# set the output of gurobi
if not self.msg:
if self.manage_env:
self.env_options["OutputFlag"] = 0
else:
self.env_options["OutputFlag"] = 0
self.solver_params["OutputFlag"] = 0
def __del__(self):
self.close()
def close(self):
"""
Must be called when internal Gurobi model and/or environment
requires disposing. The environment (default or otherwise) will be
disposed only if ``manageEnv`` is set to True.
"""
if not self.init_gurobi:
return
self.model.dispose()
if self.manage_env:
self.env.dispose()
def findSolutionValues(self, lp):
model = lp.solverModel
solutionStatus = model.Status
GRB = gp.GRB
# TODO: check status for Integer Feasible
gurobiLpStatus = {
GRB.OPTIMAL: constants.LpStatusOptimal,
GRB.INFEASIBLE: constants.LpStatusInfeasible,
GRB.INF_OR_UNBD: constants.LpStatusInfeasible,
GRB.UNBOUNDED: constants.LpStatusUnbounded,
GRB.ITERATION_LIMIT: constants.LpStatusNotSolved,
GRB.NODE_LIMIT: constants.LpStatusNotSolved,
GRB.TIME_LIMIT: constants.LpStatusNotSolved,
GRB.SOLUTION_LIMIT: constants.LpStatusNotSolved,
GRB.INTERRUPTED: constants.LpStatusNotSolved,
GRB.NUMERIC: constants.LpStatusNotSolved,
}
if self.msg:
print("Gurobi status=", solutionStatus)
lp.resolveOK = True
for var in lp._variables:
var.isModified = False
status = gurobiLpStatus.get(solutionStatus, constants.LpStatusUndefined)
lp.assignStatus(status)
if model.SolCount >= 1:
# populate pulp solution values
for var, value in zip(
lp._variables, model.getAttr(GRB.Attr.X, model.getVars())
):
var.varValue = value
# populate pulp constraints slack
for constr, value in zip(
lp.constraints.values(),
model.getAttr(GRB.Attr.Slack, model.getConstrs()),
):
constr.slack = value
# put pi and slack variables against the constraints
if not model.IsMIP:
for var, value in zip(
lp._variables, model.getAttr(GRB.Attr.RC, model.getVars())
):
var.dj = value
for constr, value in zip(
lp.constraints.values(),
model.getAttr(GRB.Attr.Pi, model.getConstrs()),
):
constr.pi = value
return status
def available(self):
"""True if the solver is available"""
try:
with gp.Env(params=self.env_options):
pass
except gurobipy.GurobiError as e:
warnings.warn(f"GUROBI error: {e}.")
return False
return True
def initGurobi(self):
if self.init_gurobi:
return
else:
self.init_gurobi = True
try:
if self.manage_env:
self.env = gp.Env(params=self.env_options)
self.model = gp.Model(env=self.env)
# Environment handled by user or default Env
else:
self.model = gp.Model(env=self.env)
# Set solver parameters
for param, value in self.solver_params.items():
self.model.setParam(param, value)
except gp.GurobiError as e:
raise e
def callSolver(self, lp, callback=None):
"""Solves the problem with gurobi"""
# solve the problem
self.solveTime = -clock()
lp.solverModel.optimize(callback=callback)
self.solveTime += clock()
def buildSolverModel(self, lp):
"""
Takes the pulp lp model and translates it into a gurobi model
"""
log.debug("create the gurobi model")
self.initGurobi()
self.model.ModelName = lp.name
lp.solverModel = self.model
log.debug("set the sense of the problem")
if lp.sense == constants.LpMaximize:
lp.solverModel.setAttr("ModelSense", -1)
if self.timeLimit:
lp.solverModel.setParam("TimeLimit", self.timeLimit)
gapRel = self.optionsDict.get("gapRel")
logPath = self.optionsDict.get("logPath")
if gapRel:
lp.solverModel.setParam("MIPGap", gapRel)
if logPath:
lp.solverModel.setParam("LogFile", logPath)
log.debug("add the variables to the problem")
lp.solverModel.update()
nvars = lp.solverModel.NumVars
for var in lp.variables():
lowBound = var.lowBound
if lowBound is None:
lowBound = -gp.GRB.INFINITY
upBound = var.upBound
if upBound is None:
upBound = gp.GRB.INFINITY
obj = lp.objective.get(var, 0.0)
varType = gp.GRB.CONTINUOUS
if var.cat == constants.LpInteger and self.mip:
varType = gp.GRB.INTEGER
# only add variable once, ow new variable will be created.
if not hasattr(var, "solverVar") or nvars == 0:
var.solverVar = lp.solverModel.addVar(
lowBound, upBound, vtype=varType, obj=obj, name=var.name
)
if self.optionsDict.get("warmStart", False):
# Once lp.variables() has been used at least once in the building of the model.
# we can use the lp._variables with the cache.
for var in lp._variables:
if var.varValue is not None:
var.solverVar.start = var.varValue
lp.solverModel.update()
log.debug("add the Constraints to the problem")
for name, constraint in lp.constraints.items():
# build the expression
expr = gp.LinExpr(
list(constraint.values()), [v.solverVar for v in constraint.keys()]
)
if constraint.sense == constants.LpConstraintLE:
constraint.solverConstraint = lp.solverModel.addConstr(
expr <= -constraint.constant, name=name
)
elif constraint.sense == constants.LpConstraintGE:
constraint.solverConstraint = lp.solverModel.addConstr(
expr >= -constraint.constant, name=name
)
elif constraint.sense == constants.LpConstraintEQ:
constraint.solverConstraint = lp.solverModel.addConstr(
expr == -constraint.constant, name=name
)
else:
raise PulpSolverError("Detected an invalid constraint type")
lp.solverModel.update()
def actualSolve(self, lp, callback=None):
"""
Solve a well formulated lp problem
creates a gurobi model, variables and constraints and attaches
them to the lp model which it then solves
"""
self.buildSolverModel(lp)
# set the initial solution
log.debug("Solve the Model using gurobi")
self.callSolver(lp, callback=callback)
# get the solution information
solutionStatus = self.findSolutionValues(lp)
for var in lp._variables:
var.modified = False
for constraint in lp.constraints.values():
constraint.modified = False
return solutionStatus
def actualResolve(self, lp, callback=None):
"""
Solve a well formulated lp problem
uses the old solver and modifies the rhs of the modified constraints
"""
log.debug("Resolve the Model using gurobi")
for constraint in lp.constraints.values():
if constraint.modified:
constraint.solverConstraint.setAttr(
gp.GRB.Attr.RHS, -constraint.constant
)
lp.solverModel.update()
self.callSolver(lp, callback=callback)
# get the solution information
solutionStatus = self.findSolutionValues(lp)
for var in lp._variables:
var.modified = False
for constraint in lp.constraints.values():
constraint.modified = False
return solutionStatus
class GUROBI_CMD(LpSolver_CMD):
"""The GUROBI_CMD solver"""
name = "GUROBI_CMD"
def __init__(
self,
mip=True,
msg=True,
timeLimit=None,
gapRel=None,
gapAbs=None,
options=None,
warmStart=False,
keepFiles=False,
path=None,
threads=None,
logPath=None,
mip_start=False,
):
"""
:param bool mip: if False, assume LP even if integer variables
:param bool msg: if False, no log is shown
:param float timeLimit: maximum time for solver (in seconds)
:param float gapRel: relative gap tolerance for the solver to stop (in fraction)
:param float gapAbs: absolute gap tolerance for the solver to stop
:param int threads: sets the maximum number of threads
:param list options: list of additional options to pass to solver
:param bool warmStart: if True, the solver will use the current value of variables as a start
:param bool keepFiles: if True, files are saved in the current directory and not deleted after solving
:param str path: path to the solver binary
:param str logPath: path to the log file
:param bool mip_start: deprecated for warmStart
"""
if mip_start:
warnings.warn("Parameter mip_start is being depreciated for warmStart")
if warmStart:
warnings.warn(
"Parameter warmStart and mip_start passed, using warmStart"
)
else:
warmStart = mip_start
LpSolver_CMD.__init__(
self,
gapRel=gapRel,
mip=mip,
msg=msg,
timeLimit=timeLimit,
options=options,
warmStart=warmStart,
path=path,
keepFiles=keepFiles,
threads=threads,
gapAbs=gapAbs,
logPath=logPath,
)
def defaultPath(self):
return self.executableExtension("gurobi_cl")
def available(self):
"""True if the solver is available"""
if not self.executable(self.path):
return False
# we execute gurobi once to check the return code.
# this is to test that the license is active
result = subprocess.Popen(
self.path, stdout=subprocess.PIPE, universal_newlines=True
)
out, err = result.communicate()
if result.returncode == 0:
# normal execution
return True
# error: we display the gurobi message
warnings.warn(f"GUROBI error: {out}.")
return False
def actualSolve(self, lp):
"""Solve a well formulated lp problem"""
if not self.executable(self.path):
raise PulpSolverError("PuLP: cannot execute " + self.path)
tmpLp, tmpSol, tmpMst = self.create_tmp_files(lp.name, "lp", "sol", "mst")
vs = lp.writeLP(tmpLp, writeSOS=1)
try:
os.remove(tmpSol)
except:
pass
cmd = self.path
options = self.options + self.getOptions()
if self.timeLimit is not None:
options.append(("TimeLimit", self.timeLimit))
cmd += " " + " ".join([f"{key}={value}" for key, value in options])
cmd += f" ResultFile={tmpSol}"
if self.optionsDict.get("warmStart", False):
self.writesol(filename=tmpMst, vs=vs)
cmd += f" InputFile={tmpMst}"
if lp.isMIP():
if not self.mip:
warnings.warn("GUROBI_CMD does not allow a problem to be relaxed")
cmd += f" {tmpLp}"
if self.msg:
pipe = None
else:
pipe = open(os.devnull, "w")
return_code = subprocess.call(cmd.split(), stdout=pipe, stderr=pipe)
# Close the pipe now if we used it.
if pipe is not None:
pipe.close()
if return_code != 0:
raise PulpSolverError("PuLP: Error while trying to execute " + self.path)
if not os.path.exists(tmpSol):
# 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
]