\returns the number of rows of the represented matrix. */

\returns an expression of the transposed of the factored matrix. * * A typical usage is to solve for the transposed problem A^T x = b:

Sets all coefficients to zero. */

Apply the derivative of the solution map to perturbations in the Parameters This method applies the derivative of the solution map to perturb

Extract constant data from a LinOp node. Parameters ---------- lin_op : LinOp A LinOp node, typically "*

Horizontal concatenation of an arbitrary number of Expressions. Parameters ---------- arg_list : list of Expression The Expressio

Is the composition non-increasing in argument idx?

Is the expression affine?

Project value onto the attribute set of the leaf. A sensible idiom is ``leaf.value = leaf.project(val)``. Parameters -------

The sum of the squares of the entries. Parameters ---------- expr : Expression The expression to take the sum of squares of.

Returns A, b after applying parameters (and reshaping). Args: id_to_param_value: (optional) dict mapping parameter ids to values.

Converts elementwise gradient into a diagonal matrix for Atom._grad() Args: value: A scalar or NumPy matrix. Returns:

Is the Leaf imaginary?

Equivalent to `cp.mean(self, axis, keepdims)`.

Resizes the sparse vector to \a rows x \a cols * * This method is provided for compatibility with matrices. * For a column vector, \

str: The sign of the expression.

Convert to stacked sparse matrix (for compatibility).

Leaf nodes are not quadratic terms.

The Indicator is constant if all constraints have constant args.

Factory function for elementwise power. Parameters ---------- x : Expression The base expression, OR a positive constant if p is

Reduces the owned problem to an equivalent problem. Returns ------- Problem or dict An equivalent problem, encode

Preallocates \a reserveSize non zeros. * * Precondition: the matrix must be in compressed mode. */

Swaps the content of two sparse matrices of the same type. * This is a fast operation that simply swaps the underlying pointers and parameters.

Returns the numeric value of the expression. Returns: A numpy matrix or a scalar.

Constructs a read-write Map to a sparse matrix of size \a rows x \a cols, containing \a nnz non-zero coefficients, * stored as a sparse format a

Assert P = scale * (M1 @ M1.T - M2 @ M2.T) within tolerance.

Compute the gradient of a solution with respect to Parameters. This method differentiates through the solution map of the problem, ob

\returns a const expression of the diagonal coefficients. */

Is problem a linear program? A problem is an LP if: - It is DCP - The objective is piecewise linear (PWL expressions lineariz

Is problem a quadratic program? A problem is a QP if: - It is DCP - The objective is quadratic or piecewise-affine (QPWA)

\returns a view of the upper triangular matrix U */

Returns the string representation of the function call.

Whether the objective contains a quadratic term.

\returns the inner-stride of the underlying dense matrix * \sa DenseCoeffsBase::innerStride() */

Is the expression constant?

Is the expression convex?

Returns the parameters in the problem.

Promote a scalar expression to a vector/matrix. Parameters ---------- expr : Expression The expression to promote. shape : t

Promote view by repeating along axis 0 (rows)

\sa MatrixBase::setIdentity() */