Module pywrapgraph
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# This file was automatically generated by SWIG (http://www.swig.org).
# Version 4.0.1
#
# Do not make changes to this file unless you know what you are doing--modify
# the SWIG interface file instead.
from sys import version_info as _swig_python_version_info
if _swig_python_version_info < (2, 7, 0):
raise RuntimeError("Python 2.7 or later required")
# Import the low-level C/C++ module
if __package__ or "." in __name__:
from . import _pywrapgraph
else:
import _pywrapgraph
try:
import builtins as __builtin__
except ImportError:
import __builtin__
def _swig_repr(self):
try:
strthis = "proxy of " + self.this.__repr__()
except __builtin__.Exception:
strthis = ""
return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,)
def _swig_setattr_nondynamic_instance_variable(set):
def set_instance_attr(self, name, value):
if name == "thisown":
self.this.own(value)
elif name == "this":
set(self, name, value)
elif hasattr(self, name) and isinstance(getattr(type(self), name), property):
set(self, name, value)
else:
raise AttributeError("You cannot add instance attributes to %s" % self)
return set_instance_attr
def _swig_setattr_nondynamic_class_variable(set):
def set_class_attr(cls, name, value):
if hasattr(cls, name) and not isinstance(getattr(cls, name), property):
set(cls, name, value)
else:
raise AttributeError("You cannot add class attributes to %s" % cls)
return set_class_attr
def _swig_add_metaclass(metaclass):
"""Class decorator for adding a metaclass to a SWIG wrapped class - a slimmed down version of six.add_metaclass"""
def wrapper(cls):
return metaclass(cls.__name__, cls.__bases__, cls.__dict__.copy())
return wrapper
class _SwigNonDynamicMeta(type):
"""Meta class to enforce nondynamic attributes (no new attributes) for a class"""
__setattr__ = _swig_setattr_nondynamic_class_variable(type.__setattr__)
class SimpleMaxFlow(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self):
_pywrapgraph.SimpleMaxFlow_swiginit(self, _pywrapgraph.new_SimpleMaxFlow())
def AddArcWithCapacity(self, tail: "operations_research::NodeIndex", head: "operations_research::NodeIndex", capacity: "operations_research::FlowQuantity") -> "operations_research::ArcIndex":
return _pywrapgraph.SimpleMaxFlow_AddArcWithCapacity(self, tail, head, capacity)
def NumNodes(self) -> "operations_research::NodeIndex":
return _pywrapgraph.SimpleMaxFlow_NumNodes(self)
def NumArcs(self) -> "operations_research::ArcIndex":
return _pywrapgraph.SimpleMaxFlow_NumArcs(self)
def Tail(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex":
return _pywrapgraph.SimpleMaxFlow_Tail(self, arc)
def Head(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex":
return _pywrapgraph.SimpleMaxFlow_Head(self, arc)
def Capacity(self, arc: "operations_research::ArcIndex") -> "operations_research::FlowQuantity":
return _pywrapgraph.SimpleMaxFlow_Capacity(self, arc)
OPTIMAL = _pywrapgraph.SimpleMaxFlow_OPTIMAL
POSSIBLE_OVERFLOW = _pywrapgraph.SimpleMaxFlow_POSSIBLE_OVERFLOW
BAD_INPUT = _pywrapgraph.SimpleMaxFlow_BAD_INPUT
BAD_RESULT = _pywrapgraph.SimpleMaxFlow_BAD_RESULT
def Solve(self, source: "operations_research::NodeIndex", sink: "operations_research::NodeIndex") -> "operations_research::SimpleMaxFlow::Status":
return _pywrapgraph.SimpleMaxFlow_Solve(self, source, sink)
def OptimalFlow(self) -> "operations_research::FlowQuantity":
return _pywrapgraph.SimpleMaxFlow_OptimalFlow(self)
def Flow(self, arc: "operations_research::ArcIndex") -> "operations_research::FlowQuantity":
return _pywrapgraph.SimpleMaxFlow_Flow(self, arc)
def GetSourceSideMinCut(self) -> "void":
return _pywrapgraph.SimpleMaxFlow_GetSourceSideMinCut(self)
def GetSinkSideMinCut(self) -> "void":
return _pywrapgraph.SimpleMaxFlow_GetSinkSideMinCut(self)
def SetArcCapacity(self, arc: "operations_research::ArcIndex", capacity: "operations_research::FlowQuantity") -> "void":
return _pywrapgraph.SimpleMaxFlow_SetArcCapacity(self, arc, capacity)
__swig_destroy__ = _pywrapgraph.delete_SimpleMaxFlow
# Register SimpleMaxFlow in _pywrapgraph:
_pywrapgraph.SimpleMaxFlow_swigregister(SimpleMaxFlow)
class MinCostFlowBase(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
NOT_SOLVED = _pywrapgraph.MinCostFlowBase_NOT_SOLVED
OPTIMAL = _pywrapgraph.MinCostFlowBase_OPTIMAL
FEASIBLE = _pywrapgraph.MinCostFlowBase_FEASIBLE
INFEASIBLE = _pywrapgraph.MinCostFlowBase_INFEASIBLE
UNBALANCED = _pywrapgraph.MinCostFlowBase_UNBALANCED
BAD_RESULT = _pywrapgraph.MinCostFlowBase_BAD_RESULT
BAD_COST_RANGE = _pywrapgraph.MinCostFlowBase_BAD_COST_RANGE
def __init__(self):
_pywrapgraph.MinCostFlowBase_swiginit(self, _pywrapgraph.new_MinCostFlowBase())
__swig_destroy__ = _pywrapgraph.delete_MinCostFlowBase
# Register MinCostFlowBase in _pywrapgraph:
_pywrapgraph.MinCostFlowBase_swigregister(MinCostFlowBase)
class SimpleMinCostFlow(MinCostFlowBase):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self):
_pywrapgraph.SimpleMinCostFlow_swiginit(self, _pywrapgraph.new_SimpleMinCostFlow())
def AddArcWithCapacityAndUnitCost(self, tail: "operations_research::NodeIndex", head: "operations_research::NodeIndex", capacity: "operations_research::FlowQuantity", unit_cost: "operations_research::CostValue") -> "operations_research::ArcIndex":
return _pywrapgraph.SimpleMinCostFlow_AddArcWithCapacityAndUnitCost(self, tail, head, capacity, unit_cost)
def SetNodeSupply(self, node: "operations_research::NodeIndex", supply: "operations_research::FlowQuantity") -> "void":
return _pywrapgraph.SimpleMinCostFlow_SetNodeSupply(self, node, supply)
def Solve(self) -> "operations_research::MinCostFlowBase::Status":
return _pywrapgraph.SimpleMinCostFlow_Solve(self)
def SolveMaxFlowWithMinCost(self) -> "operations_research::MinCostFlowBase::Status":
return _pywrapgraph.SimpleMinCostFlow_SolveMaxFlowWithMinCost(self)
def OptimalCost(self) -> "operations_research::CostValue":
return _pywrapgraph.SimpleMinCostFlow_OptimalCost(self)
def MaximumFlow(self) -> "operations_research::FlowQuantity":
return _pywrapgraph.SimpleMinCostFlow_MaximumFlow(self)
def Flow(self, arc: "operations_research::ArcIndex") -> "operations_research::FlowQuantity":
return _pywrapgraph.SimpleMinCostFlow_Flow(self, arc)
def NumNodes(self) -> "operations_research::NodeIndex":
return _pywrapgraph.SimpleMinCostFlow_NumNodes(self)
def NumArcs(self) -> "operations_research::ArcIndex":
return _pywrapgraph.SimpleMinCostFlow_NumArcs(self)
def Tail(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex":
return _pywrapgraph.SimpleMinCostFlow_Tail(self, arc)
def Head(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex":
return _pywrapgraph.SimpleMinCostFlow_Head(self, arc)
def Capacity(self, arc: "operations_research::ArcIndex") -> "operations_research::FlowQuantity":
return _pywrapgraph.SimpleMinCostFlow_Capacity(self, arc)
def Supply(self, node: "operations_research::NodeIndex") -> "operations_research::FlowQuantity":
return _pywrapgraph.SimpleMinCostFlow_Supply(self, node)
def UnitCost(self, arc: "operations_research::ArcIndex") -> "operations_research::CostValue":
return _pywrapgraph.SimpleMinCostFlow_UnitCost(self, arc)
__swig_destroy__ = _pywrapgraph.delete_SimpleMinCostFlow
# Register SimpleMinCostFlow in _pywrapgraph:
_pywrapgraph.SimpleMinCostFlow_swigregister(SimpleMinCostFlow)
class LinearSumAssignment(object):
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
__repr__ = _swig_repr
def __init__(self):
_pywrapgraph.LinearSumAssignment_swiginit(self, _pywrapgraph.new_LinearSumAssignment())
def AddArcWithCost(self, left_node: "operations_research::NodeIndex", right_node: "operations_research::NodeIndex", cost: "operations_research::CostValue") -> "operations_research::ArcIndex":
return _pywrapgraph.LinearSumAssignment_AddArcWithCost(self, left_node, right_node, cost)
def NumNodes(self) -> "operations_research::NodeIndex":
return _pywrapgraph.LinearSumAssignment_NumNodes(self)
def NumArcs(self) -> "operations_research::ArcIndex":
return _pywrapgraph.LinearSumAssignment_NumArcs(self)
def LeftNode(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex":
return _pywrapgraph.LinearSumAssignment_LeftNode(self, arc)
def RightNode(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex":
return _pywrapgraph.LinearSumAssignment_RightNode(self, arc)
def Cost(self, arc: "operations_research::ArcIndex") -> "operations_research::CostValue":
return _pywrapgraph.LinearSumAssignment_Cost(self, arc)
OPTIMAL = _pywrapgraph.LinearSumAssignment_OPTIMAL
INFEASIBLE = _pywrapgraph.LinearSumAssignment_INFEASIBLE
POSSIBLE_OVERFLOW = _pywrapgraph.LinearSumAssignment_POSSIBLE_OVERFLOW
def Solve(self) -> "operations_research::SimpleLinearSumAssignment::Status":
return _pywrapgraph.LinearSumAssignment_Solve(self)
def OptimalCost(self) -> "operations_research::CostValue":
return _pywrapgraph.LinearSumAssignment_OptimalCost(self)
def RightMate(self, left_node: "operations_research::NodeIndex") -> "operations_research::NodeIndex":
return _pywrapgraph.LinearSumAssignment_RightMate(self, left_node)
def AssignmentCost(self, left_node: "operations_research::NodeIndex") -> "operations_research::CostValue":
return _pywrapgraph.LinearSumAssignment_AssignmentCost(self, left_node)
__swig_destroy__ = _pywrapgraph.delete_LinearSumAssignment
# Register LinearSumAssignment in _pywrapgraph:
_pywrapgraph.LinearSumAssignment_swigregister(LinearSumAssignment)
def DijkstraShortestPath(node_count: "int", start_node: "int", end_node: "int", graph: "std::function< int64 (int,int) >", disconnected_distance: "int64") -> "std::vector< int > *":
return _pywrapgraph.DijkstraShortestPath(node_count, start_node, end_node, graph, disconnected_distance)
def BellmanFordShortestPath(node_count: "int", start_node: "int", end_node: "int", graph: "std::function< int64 (int,int) >", disconnected_distance: "int64") -> "std::vector< int > *":
return _pywrapgraph.BellmanFordShortestPath(node_count, start_node, end_node, graph, disconnected_distance)
def AStarShortestPath(node_count: "int", start_node: "int", end_node: "int", graph: "std::function< int64 (int,int) >", heuristic: "std::function< int64 (int) >", disconnected_distance: "int64") -> "std::vector< int > *":
return _pywrapgraph.AStarShortestPath(node_count, start_node, end_node, graph, heuristic, disconnected_distance)
Functions
def AStarShortestPath(node_count: int, start_node: int, end_node: int, graph: std::function< int64 (int,int) >, heuristic: std::function< int64 (int) >, disconnected_distance: int64) -> 'std::vector< int > *'
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def AStarShortestPath(node_count: "int", start_node: "int", end_node: "int", graph: "std::function< int64 (int,int) >", heuristic: "std::function< int64 (int) >", disconnected_distance: "int64") -> "std::vector< int > *": return _pywrapgraph.AStarShortestPath(node_count, start_node, end_node, graph, heuristic, disconnected_distance)
def BellmanFordShortestPath(node_count: int, start_node: int, end_node: int, graph: std::function< int64 (int,int) >, disconnected_distance: int64) -> 'std::vector< int > *'
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def BellmanFordShortestPath(node_count: "int", start_node: "int", end_node: "int", graph: "std::function< int64 (int,int) >", disconnected_distance: "int64") -> "std::vector< int > *": return _pywrapgraph.BellmanFordShortestPath(node_count, start_node, end_node, graph, disconnected_distance)
def DijkstraShortestPath(node_count: int, start_node: int, end_node: int, graph: std::function< int64 (int,int) >, disconnected_distance: int64) -> 'std::vector< int > *'
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def DijkstraShortestPath(node_count: "int", start_node: "int", end_node: "int", graph: "std::function< int64 (int,int) >", disconnected_distance: "int64") -> "std::vector< int > *": return _pywrapgraph.DijkstraShortestPath(node_count, start_node, end_node, graph, disconnected_distance)
AStarShortestPath
BellmanFordShortestPath
DijkstraShortestPath
Classes
class LinearSumAssignment
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class LinearSumAssignment(object): thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag") __repr__ = _swig_repr def __init__(self): _pywrapgraph.LinearSumAssignment_swiginit(self, _pywrapgraph.new_LinearSumAssignment()) def AddArcWithCost(self, left_node: "operations_research::NodeIndex", right_node: "operations_research::NodeIndex", cost: "operations_research::CostValue") -> "operations_research::ArcIndex": return _pywrapgraph.LinearSumAssignment_AddArcWithCost(self, left_node, right_node, cost) def NumNodes(self) -> "operations_research::NodeIndex": return _pywrapgraph.LinearSumAssignment_NumNodes(self) def NumArcs(self) -> "operations_research::ArcIndex": return _pywrapgraph.LinearSumAssignment_NumArcs(self) def LeftNode(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex": return _pywrapgraph.LinearSumAssignment_LeftNode(self, arc) def RightNode(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex": return _pywrapgraph.LinearSumAssignment_RightNode(self, arc) def Cost(self, arc: "operations_research::ArcIndex") -> "operations_research::CostValue": return _pywrapgraph.LinearSumAssignment_Cost(self, arc) OPTIMAL = _pywrapgraph.LinearSumAssignment_OPTIMAL INFEASIBLE = _pywrapgraph.LinearSumAssignment_INFEASIBLE POSSIBLE_OVERFLOW = _pywrapgraph.LinearSumAssignment_POSSIBLE_OVERFLOW def Solve(self) -> "operations_research::SimpleLinearSumAssignment::Status": return _pywrapgraph.LinearSumAssignment_Solve(self) def OptimalCost(self) -> "operations_research::CostValue": return _pywrapgraph.LinearSumAssignment_OptimalCost(self) def RightMate(self, left_node: "operations_research::NodeIndex") -> "operations_research::NodeIndex": return _pywrapgraph.LinearSumAssignment_RightMate(self, left_node) def AssignmentCost(self, left_node: "operations_research::NodeIndex") -> "operations_research::CostValue": return _pywrapgraph.LinearSumAssignment_AssignmentCost(self, left_node) __swig_destroy__ = _pywrapgraph.delete_LinearSumAssignment
Class variablesvar INFEASIBLE
var OPTIMAL
var POSSIBLE_OVERFLOW
INFEASIBLE
OPTIMAL
POSSIBLE_OVERFLOW
Instance variablesvar thisown
-
The membership flag
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thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
thisown
Methodsdef AddArcWithCost(self, left_node: operations_research::NodeIndex, right_node: operations_research::NodeIndex, cost: operations_research::CostValue) -> 'operations_research::ArcIndex'
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def AddArcWithCost(self, left_node: "operations_research::NodeIndex", right_node: "operations_research::NodeIndex", cost: "operations_research::CostValue") -> "operations_research::ArcIndex": return _pywrapgraph.LinearSumAssignment_AddArcWithCost(self, left_node, right_node, cost)
def AssignmentCost(self, left_node: operations_research::NodeIndex) -> 'operations_research::CostValue'
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def AssignmentCost(self, left_node: "operations_research::NodeIndex") -> "operations_research::CostValue": return _pywrapgraph.LinearSumAssignment_AssignmentCost(self, left_node)
def Cost(self, arc: operations_research::ArcIndex) -> 'operations_research::CostValue'
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def Cost(self, arc: "operations_research::ArcIndex") -> "operations_research::CostValue": return _pywrapgraph.LinearSumAssignment_Cost(self, arc)
def LeftNode(self, arc: operations_research::ArcIndex) -> 'operations_research::NodeIndex'
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def LeftNode(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex": return _pywrapgraph.LinearSumAssignment_LeftNode(self, arc)
def NumArcs(self) -> 'operations_research::ArcIndex'
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def NumArcs(self) -> "operations_research::ArcIndex": return _pywrapgraph.LinearSumAssignment_NumArcs(self)
def NumNodes(self) -> 'operations_research::NodeIndex'
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def NumNodes(self) -> "operations_research::NodeIndex": return _pywrapgraph.LinearSumAssignment_NumNodes(self)
def OptimalCost(self) -> 'operations_research::CostValue'
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def OptimalCost(self) -> "operations_research::CostValue": return _pywrapgraph.LinearSumAssignment_OptimalCost(self)
def RightMate(self, left_node: operations_research::NodeIndex) -> 'operations_research::NodeIndex'
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def RightMate(self, left_node: "operations_research::NodeIndex") -> "operations_research::NodeIndex": return _pywrapgraph.LinearSumAssignment_RightMate(self, left_node)
def RightNode(self, arc: operations_research::ArcIndex) -> 'operations_research::NodeIndex'
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def RightNode(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex": return _pywrapgraph.LinearSumAssignment_RightNode(self, arc)
def Solve(self) -> 'operations_research::SimpleLinearSumAssignment::Status'
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def Solve(self) -> "operations_research::SimpleLinearSumAssignment::Status": return _pywrapgraph.LinearSumAssignment_Solve(self)
AddArcWithCost
AssignmentCost
Cost
LeftNode
NumArcs
NumNodes
OptimalCost
RightMate
RightNode
Solve
class MinCostFlowBase
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class MinCostFlowBase(object): thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag") __repr__ = _swig_repr NOT_SOLVED = _pywrapgraph.MinCostFlowBase_NOT_SOLVED OPTIMAL = _pywrapgraph.MinCostFlowBase_OPTIMAL FEASIBLE = _pywrapgraph.MinCostFlowBase_FEASIBLE INFEASIBLE = _pywrapgraph.MinCostFlowBase_INFEASIBLE UNBALANCED = _pywrapgraph.MinCostFlowBase_UNBALANCED BAD_RESULT = _pywrapgraph.MinCostFlowBase_BAD_RESULT BAD_COST_RANGE = _pywrapgraph.MinCostFlowBase_BAD_COST_RANGE def __init__(self): _pywrapgraph.MinCostFlowBase_swiginit(self, _pywrapgraph.new_MinCostFlowBase()) __swig_destroy__ = _pywrapgraph.delete_MinCostFlowBase
SubclassesClass variablesvar BAD_COST_RANGE
var BAD_RESULT
var FEASIBLE
var INFEASIBLE
var NOT_SOLVED
var OPTIMAL
var UNBALANCED
BAD_COST_RANGE
BAD_RESULT
FEASIBLE
INFEASIBLE
NOT_SOLVED
OPTIMAL
UNBALANCED
Instance variablesvar thisown
-
The membership flag
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thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
thisown
class SimpleMaxFlow
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class SimpleMaxFlow(object): thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag") __repr__ = _swig_repr def __init__(self): _pywrapgraph.SimpleMaxFlow_swiginit(self, _pywrapgraph.new_SimpleMaxFlow()) def AddArcWithCapacity(self, tail: "operations_research::NodeIndex", head: "operations_research::NodeIndex", capacity: "operations_research::FlowQuantity") -> "operations_research::ArcIndex": return _pywrapgraph.SimpleMaxFlow_AddArcWithCapacity(self, tail, head, capacity) def NumNodes(self) -> "operations_research::NodeIndex": return _pywrapgraph.SimpleMaxFlow_NumNodes(self) def NumArcs(self) -> "operations_research::ArcIndex": return _pywrapgraph.SimpleMaxFlow_NumArcs(self) def Tail(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex": return _pywrapgraph.SimpleMaxFlow_Tail(self, arc) def Head(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex": return _pywrapgraph.SimpleMaxFlow_Head(self, arc) def Capacity(self, arc: "operations_research::ArcIndex") -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMaxFlow_Capacity(self, arc) OPTIMAL = _pywrapgraph.SimpleMaxFlow_OPTIMAL POSSIBLE_OVERFLOW = _pywrapgraph.SimpleMaxFlow_POSSIBLE_OVERFLOW BAD_INPUT = _pywrapgraph.SimpleMaxFlow_BAD_INPUT BAD_RESULT = _pywrapgraph.SimpleMaxFlow_BAD_RESULT def Solve(self, source: "operations_research::NodeIndex", sink: "operations_research::NodeIndex") -> "operations_research::SimpleMaxFlow::Status": return _pywrapgraph.SimpleMaxFlow_Solve(self, source, sink) def OptimalFlow(self) -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMaxFlow_OptimalFlow(self) def Flow(self, arc: "operations_research::ArcIndex") -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMaxFlow_Flow(self, arc) def GetSourceSideMinCut(self) -> "void": return _pywrapgraph.SimpleMaxFlow_GetSourceSideMinCut(self) def GetSinkSideMinCut(self) -> "void": return _pywrapgraph.SimpleMaxFlow_GetSinkSideMinCut(self) def SetArcCapacity(self, arc: "operations_research::ArcIndex", capacity: "operations_research::FlowQuantity") -> "void": return _pywrapgraph.SimpleMaxFlow_SetArcCapacity(self, arc, capacity) __swig_destroy__ = _pywrapgraph.delete_SimpleMaxFlow
Class variablesvar BAD_INPUT
var BAD_RESULT
var OPTIMAL
var POSSIBLE_OVERFLOW
BAD_INPUT
BAD_RESULT
OPTIMAL
POSSIBLE_OVERFLOW
Instance variablesvar thisown
-
The membership flag
Expand source code
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
thisown
Methodsdef AddArcWithCapacity(self, tail: operations_research::NodeIndex, head: operations_research::NodeIndex, capacity: operations_research::FlowQuantity) -> 'operations_research::ArcIndex'
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def AddArcWithCapacity(self, tail: "operations_research::NodeIndex", head: "operations_research::NodeIndex", capacity: "operations_research::FlowQuantity") -> "operations_research::ArcIndex": return _pywrapgraph.SimpleMaxFlow_AddArcWithCapacity(self, tail, head, capacity)
def Capacity(self, arc: operations_research::ArcIndex) -> 'operations_research::FlowQuantity'
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def Capacity(self, arc: "operations_research::ArcIndex") -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMaxFlow_Capacity(self, arc)
def Flow(self, arc: operations_research::ArcIndex) -> 'operations_research::FlowQuantity'
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def Flow(self, arc: "operations_research::ArcIndex") -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMaxFlow_Flow(self, arc)
def GetSinkSideMinCut(self) -> 'void'
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def GetSinkSideMinCut(self) -> "void": return _pywrapgraph.SimpleMaxFlow_GetSinkSideMinCut(self)
def GetSourceSideMinCut(self) -> 'void'
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def GetSourceSideMinCut(self) -> "void": return _pywrapgraph.SimpleMaxFlow_GetSourceSideMinCut(self)
def Head(self, arc: operations_research::ArcIndex) -> 'operations_research::NodeIndex'
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def Head(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex": return _pywrapgraph.SimpleMaxFlow_Head(self, arc)
def NumArcs(self) -> 'operations_research::ArcIndex'
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def NumArcs(self) -> "operations_research::ArcIndex": return _pywrapgraph.SimpleMaxFlow_NumArcs(self)
def NumNodes(self) -> 'operations_research::NodeIndex'
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def NumNodes(self) -> "operations_research::NodeIndex": return _pywrapgraph.SimpleMaxFlow_NumNodes(self)
def OptimalFlow(self) -> 'operations_research::FlowQuantity'
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def OptimalFlow(self) -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMaxFlow_OptimalFlow(self)
def SetArcCapacity(self, arc: operations_research::ArcIndex, capacity: operations_research::FlowQuantity) -> 'void'
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def SetArcCapacity(self, arc: "operations_research::ArcIndex", capacity: "operations_research::FlowQuantity") -> "void": return _pywrapgraph.SimpleMaxFlow_SetArcCapacity(self, arc, capacity)
def Solve(self, source: operations_research::NodeIndex, sink: operations_research::NodeIndex) -> 'operations_research::SimpleMaxFlow::Status'
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def Solve(self, source: "operations_research::NodeIndex", sink: "operations_research::NodeIndex") -> "operations_research::SimpleMaxFlow::Status": return _pywrapgraph.SimpleMaxFlow_Solve(self, source, sink)
def Tail(self, arc: operations_research::ArcIndex) -> 'operations_research::NodeIndex'
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def Tail(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex": return _pywrapgraph.SimpleMaxFlow_Tail(self, arc)
AddArcWithCapacity
Capacity
Flow
GetSinkSideMinCut
GetSourceSideMinCut
Head
NumArcs
NumNodes
OptimalFlow
SetArcCapacity
Solve
Tail
class SimpleMinCostFlow
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class SimpleMinCostFlow(MinCostFlowBase): thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag") __repr__ = _swig_repr def __init__(self): _pywrapgraph.SimpleMinCostFlow_swiginit(self, _pywrapgraph.new_SimpleMinCostFlow()) def AddArcWithCapacityAndUnitCost(self, tail: "operations_research::NodeIndex", head: "operations_research::NodeIndex", capacity: "operations_research::FlowQuantity", unit_cost: "operations_research::CostValue") -> "operations_research::ArcIndex": return _pywrapgraph.SimpleMinCostFlow_AddArcWithCapacityAndUnitCost(self, tail, head, capacity, unit_cost) def SetNodeSupply(self, node: "operations_research::NodeIndex", supply: "operations_research::FlowQuantity") -> "void": return _pywrapgraph.SimpleMinCostFlow_SetNodeSupply(self, node, supply) def Solve(self) -> "operations_research::MinCostFlowBase::Status": return _pywrapgraph.SimpleMinCostFlow_Solve(self) def SolveMaxFlowWithMinCost(self) -> "operations_research::MinCostFlowBase::Status": return _pywrapgraph.SimpleMinCostFlow_SolveMaxFlowWithMinCost(self) def OptimalCost(self) -> "operations_research::CostValue": return _pywrapgraph.SimpleMinCostFlow_OptimalCost(self) def MaximumFlow(self) -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMinCostFlow_MaximumFlow(self) def Flow(self, arc: "operations_research::ArcIndex") -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMinCostFlow_Flow(self, arc) def NumNodes(self) -> "operations_research::NodeIndex": return _pywrapgraph.SimpleMinCostFlow_NumNodes(self) def NumArcs(self) -> "operations_research::ArcIndex": return _pywrapgraph.SimpleMinCostFlow_NumArcs(self) def Tail(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex": return _pywrapgraph.SimpleMinCostFlow_Tail(self, arc) def Head(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex": return _pywrapgraph.SimpleMinCostFlow_Head(self, arc) def Capacity(self, arc: "operations_research::ArcIndex") -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMinCostFlow_Capacity(self, arc) def Supply(self, node: "operations_research::NodeIndex") -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMinCostFlow_Supply(self, node) def UnitCost(self, arc: "operations_research::ArcIndex") -> "operations_research::CostValue": return _pywrapgraph.SimpleMinCostFlow_UnitCost(self, arc) __swig_destroy__ = _pywrapgraph.delete_SimpleMinCostFlow
AncestorsMethodsdef AddArcWithCapacityAndUnitCost(self, tail: operations_research::NodeIndex, head: operations_research::NodeIndex, capacity: operations_research::FlowQuantity, unit_cost: operations_research::CostValue) -> 'operations_research::ArcIndex'
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def AddArcWithCapacityAndUnitCost(self, tail: "operations_research::NodeIndex", head: "operations_research::NodeIndex", capacity: "operations_research::FlowQuantity", unit_cost: "operations_research::CostValue") -> "operations_research::ArcIndex": return _pywrapgraph.SimpleMinCostFlow_AddArcWithCapacityAndUnitCost(self, tail, head, capacity, unit_cost)
def Capacity(self, arc: operations_research::ArcIndex) -> 'operations_research::FlowQuantity'
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def Capacity(self, arc: "operations_research::ArcIndex") -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMinCostFlow_Capacity(self, arc)
def Flow(self, arc: operations_research::ArcIndex) -> 'operations_research::FlowQuantity'
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def Flow(self, arc: "operations_research::ArcIndex") -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMinCostFlow_Flow(self, arc)
def Head(self, arc: operations_research::ArcIndex) -> 'operations_research::NodeIndex'
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def Head(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex": return _pywrapgraph.SimpleMinCostFlow_Head(self, arc)
def MaximumFlow(self) -> 'operations_research::FlowQuantity'
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def MaximumFlow(self) -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMinCostFlow_MaximumFlow(self)
def NumArcs(self) -> 'operations_research::ArcIndex'
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def NumArcs(self) -> "operations_research::ArcIndex": return _pywrapgraph.SimpleMinCostFlow_NumArcs(self)
def NumNodes(self) -> 'operations_research::NodeIndex'
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def NumNodes(self) -> "operations_research::NodeIndex": return _pywrapgraph.SimpleMinCostFlow_NumNodes(self)
def OptimalCost(self) -> 'operations_research::CostValue'
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def OptimalCost(self) -> "operations_research::CostValue": return _pywrapgraph.SimpleMinCostFlow_OptimalCost(self)
def SetNodeSupply(self, node: operations_research::NodeIndex, supply: operations_research::FlowQuantity) -> 'void'
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def SetNodeSupply(self, node: "operations_research::NodeIndex", supply: "operations_research::FlowQuantity") -> "void": return _pywrapgraph.SimpleMinCostFlow_SetNodeSupply(self, node, supply)
def Solve(self) -> 'operations_research::MinCostFlowBase::Status'
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def Solve(self) -> "operations_research::MinCostFlowBase::Status": return _pywrapgraph.SimpleMinCostFlow_Solve(self)
def SolveMaxFlowWithMinCost(self) -> 'operations_research::MinCostFlowBase::Status'
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def SolveMaxFlowWithMinCost(self) -> "operations_research::MinCostFlowBase::Status": return _pywrapgraph.SimpleMinCostFlow_SolveMaxFlowWithMinCost(self)
def Supply(self, node: operations_research::NodeIndex) -> 'operations_research::FlowQuantity'
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def Supply(self, node: "operations_research::NodeIndex") -> "operations_research::FlowQuantity": return _pywrapgraph.SimpleMinCostFlow_Supply(self, node)
def Tail(self, arc: operations_research::ArcIndex) -> 'operations_research::NodeIndex'
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def Tail(self, arc: "operations_research::ArcIndex") -> "operations_research::NodeIndex": return _pywrapgraph.SimpleMinCostFlow_Tail(self, arc)
def UnitCost(self, arc: operations_research::ArcIndex) -> 'operations_research::CostValue'
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def UnitCost(self, arc: "operations_research::ArcIndex") -> "operations_research::CostValue": return _pywrapgraph.SimpleMinCostFlow_UnitCost(self, arc)
AddArcWithCapacityAndUnitCost
Capacity
Flow
Head
MaximumFlow
NumArcs
NumNodes
OptimalCost
SetNodeSupply
Solve
SolveMaxFlowWithMinCost
Supply
Tail
UnitCost
Inherited members