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int_encoder

class BinaryModel​

BinaryModel(coeff: 'dict[tuple[int, ...], float]', constant: 'float')

normalize (self, factor) -> -​

class IntegerBound​

IntegerBound

Attributes​

  • lower(int | float) : lower bound of integer decision variable
  • upper(int | float) : upper bound of integer decision variable

class SubstitutedExpression​

SubstitutedExpression(coeff: 'dict[tuple[int, ...], float]', constant: 'float', order: 'int')

add (self, other) -> -​

from_serializable (data) -> -​

is_constant (self) -> -​

mul (self, other) -> -​

power (self, exponent) -> -​

to_serializable (self) -> -​

class VariableMap​

VarialeMap

This class is used to manage the mapping between the label and the index of the decision variable.

Attributes​

  • var_map(dict[str, dict[tuple[int, ...], int]]) : label, subscripts -> index (int)
  • var_num(int) : number of variables
  • integer_bound(dict[str, dict[tuple[int, ...], IntegerBound]]) : bounds of integer decision variables.

add_cont_variable (self, label, subscripts, lower, upper) -> -​

Add an integer variable to the variable map.

add_int_variable (self, label, subscripts, lower, upper) -> -​

Add an integer variable to the variable map.

add_variable (self, label, subscripts) -> int​

Add a variable to the variable map.

Parameters​

  • label(str) : label of the variable
  • subscripts(tuple[int, ...]) : subscripts of the variable

Returns​

  • int : index of the variable in the variable map

from_serializable (data) -> -​

to_serializable (self) -> dict​

Convert to a serializable object.

Returns​

  • dict : serializable object

Examples​

varmap = VariableMap()
varmap.add_variable("x", (0, 0))
varmap.add_variable("x", (0, 1))
varmap.to_serializable()
# {
#    "class": "VariableMap",
#    "var_map": {
#        "x": {
#            "subscripts": [
#                [0, 0],
#                [0, 1]
#            ],
#            "index": [0, 1]
#        }
#    },
#    "var_num": 2,
#    "integer_bound": {}
# }