lumix.core.expressions.LXQuadraticExpression

class lumix.core.expressions.LXQuadraticExpression(linear_terms=<factory>, quadratic_terms=<factory>, constant=0.0)[source]

Quadratic expression: linear_terms + quadratic_terms + constant

Represents: 0.5 * x^T Q x + c^T x + constant

Example

# Portfolio variance: sum(w[i] * w[j] * cov[i,j]) # Plus linear returns: sum(return[i] * w[i]) quad_expr = LXQuadraticExpression() quad_expr.add_quadratic(w[0], w[1], cov[0,1]) quad_expr.linear_terms.add_term(w[0], returns[0])

Parameters:
__init__(linear_terms=<factory>, quadratic_terms=<factory>, constant=0.0)
Parameters:
Return type:

None

Methods

__init__([linear_terms, quadratic_terms, ...])

add_quadratic(var1, var2[, coeff])

Add quadratic term.

add_squared(var[, coeff])

Add x^2 term.

Attributes

constant

linear_terms

quadratic_terms

linear_terms: LXLinearExpression
quadratic_terms: List[LXQuadraticTerm]
constant: float = 0.0
__deepcopy__(memo)[source]

Custom deepcopy that handles linear and quadratic terms.

This method enables what-if analysis on quadratic expressions by: 1. Deep copying the linear expression component 2. Deep copying all quadratic terms 3. Preserving the expression structure

Parameters:

memo – Dictionary for tracking circular references during deepcopy

Returns:

Deep copy of this quadratic expression with all dependencies resolved

add_quadratic(var1, var2, coeff=1.0)[source]

Add quadratic term.

Parameters:
Return type:

Self

Returns:

Self for chaining

add_squared(var, coeff=1.0)[source]

Add x^2 term.

Parameters:
Return type:

Self

Returns:

Self for chaining

__add__(other)[source]

Enable: quad_expr + linear_expr or quad_expr + constant.

Parameters:

other (LXLinearExpression | float) – Linear expression or constant

Return type:

Self

Returns:

Self for chaining

__init__(linear_terms=<factory>, quadratic_terms=<factory>, constant=0.0)
Parameters:
Return type:

None