1 API Reference

1.1 Core Classes

Fundamental building blocks for optimization models

core.expressions.Variable A decision variable in an optimization problem.
BinaryVariable Create a binary (0/1) variable.
IntegerVariable Create an integer variable.
core.expressions.Constant A constant numerical value in an expression.
core.expressions.Expression Abstract base class for all symbolic expressions.

1.2 Vector & Matrix Variables

High-dimensional decision variables for scalable optimization

core.vectors.VectorVariable A vector of optimization variables.
core.variable_dict.VariableDict A dictionary-keyed collection of optimization variables.
core.vectors.VectorExpression A vector of expressions (result of vector arithmetic).
core.vectors.DotProduct Dot product of two vectors: x · y = x[0]y[0] + x[1]y[1] + … + x[n-1]*y[n-1].
core.vectors.L2Norm L2 (Euclidean) norm of a vector: ||x|| = sqrt(x[0]^2 + x[1]^2 + … + x[n-1]^2).
core.vectors.L1Norm L1 (Manhattan) norm of a vector: ||x||_1 = |x[0]| + |x[1]| + … + |x[n-1]|.
core.vectors.LinearCombination Linear combination of vector elements with constant coefficients.
core.matrices.MatrixVariable A 2D matrix of optimization variables.
core.matrices.ConstantMatrix Wrapper for constant dense or sparse matrices used in symbolic products.
core.matrices.QuadraticForm Quadratic form: x’ @ Q @ x where Q is a constant matrix.
core.matrices.MatrixVectorProduct Matrix-vector product: A @ x where A is a constant matrix.
core.matrices.FrobeniusNorm Frobenius norm of a matrix: ||A||_F = sqrt(sum of squared elements).

1.3 Parameters

Updatable constants for fast re-solves

core.parameters.Parameter An updatable constant for optimization problems.
core.parameters.VectorParameter A vector of parameters for array-valued constants.
core.parameters.MatrixParameter A matrix of parameters for array-valued constants.

1.4 Constraints

Equality and inequality constraints

constraints.Constraint Represents an optimization constraint.

1.5 Problem Definition

Building and solving optimization problems

problem.Problem An optimization problem with objective and constraints.
solution.Solution Result of solving an optimization problem.
solution.SolverStatus Status of an optimization solve.
solution.SolverProgress Snapshot of solver state passed to user callbacks during optimization.

1.6 Mathematical Functions

Transcendental and special functions for expressions

core.functions.sin Sine function.
core.functions.cos Cosine function.
core.functions.tan Tangent function.
core.functions.exp Exponential function (e^x).
core.functions.log Natural logarithm.
core.functions.log2 Base-2 logarithm.
core.functions.log10 Base-10 logarithm.
core.functions.sqrt Square root.
core.functions.abs_ Absolute value.
core.functions.sinh Hyperbolic sine.
core.functions.cosh Hyperbolic cosine.
core.functions.tanh Hyperbolic tangent.
core.functions.asin Inverse sine (arcsine).
core.functions.acos Inverse cosine (arccosine).
core.functions.atan Inverse tangent (arctangent).
core.functions.asinh Inverse hyperbolic sine.
core.functions.acosh Inverse hyperbolic cosine.
core.functions.atanh Inverse hyperbolic tangent.

1.7 Autodiff

Automatic differentiation internals

core.autodiff Automatic differentiation for symbolic expressions.