Accumulate right hand Tensor into left hand by addition.

A problem is accepted if it is DGP.

A problem is accepted if it is a minimization and is DCP.

function: add_matrix_to_vectors * * This function adds a matrix to our sparse matrix triplet * representation, by using eigen's sparse matrix itera

Adds SOC constraint to the model using the data from mat and vec. Return tuple contains (QConstr, list of Constr, and list of variables).

Adds SOC constraint to the model using the data from mat and vec. Parameters ---------- model : GUROBI model The

Adds SOC constraint to the model using the data from mat and vec. Parameters ---------- model : CPLEX model The p

add_pointer. * Adds an existing pointer to the map and returns the virtual pointer id. */

Returns element-wise addition of two tensors of the same type.

* Adds Triplets for slices starting from the current axis. * * Parameters: triplet list, slices, dimensions, axis, row counter. * * Returns: new r

To use for operations with the adjoint of Q

* \internal * \brief Reallocates an aligned block of memory. * \throws std::bad_alloc on allocation failure */

Performs a symbolic decomposition on the sparcity of \a matrix. * * This function is particularly useful when solving for several problems

\returns the rotation angle */

Applies the reduction to a problem and returns an equivalent problem. Parameters ---------- problem : Problem The

Multiplies by Jacobian of parameter mapping. Assumes delA is sparse. Returns: A dictionary param.id -> dparam

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

Apply 'func' to each slice of the parameter representation.

Return the :math:`\\ell_\\infty` norm error from approximating the vector a_orig/sum(a_orig) with the weight vector w_approx. That i

Block diag of SciPy sparse matrices or linear operators.

Like at(), but the search is performed in the range [start,end) */

A list of the atom types present amongst this atom's arguments.

Returns bounds (lower, upper) of the expression based on argument bounds. Default implementation returns unbounded. Override in subclasses th

Broadcast bounds to a target shape. Handles sparse matrices: if a sparse bound already has the target shape, it is kept as-is; otherwise it i

Construct C++ LinOp tree from Python LinOp tree. Constructed C++ linOps are stored in the linPy_to_linC dict, which maps Python linOps to the

Build {param_id: C parameter capsule} mapping from InverseData.

Build {var_id: C variable capsule} mapping from InverseData.

Represent the atom as an affine objective and conic constraints.

Returns the graph implementation of the object. Change the ids of all the opt_vars. Returns ------- A tuple of (

Canonicalize an expression, w.r.t. canonicalized arguments. Args: expr: Expression to canonicalize. args: Arguments t

Canonicalize an expression, w.r.t. canonicalized arguments. Args: expr: Expression to canonicalize. args: Arguments t

Canonicalize an expression, w.r.t. canonicalized arguments. Parameters ---------- expr : The expression tree to canonicalize.

Canonicalize an expression, w.r.t. canonicalized arguments. Parameters ---------- expr : The expression tree to canonicalize.

Combine children with a balanced binary tree of adds. Tree depth is ceil(log2(N)) instead of N-1, which keeps the AD graph shallow when summi

Compare C-based gradient with numerical approximation using finite differences. The central-difference step is ~eps_machine**(1/3), which ba

Compare objective value from C implementation with Python implementation.

Can the solver solve the problem?

\returns a pointer to the SPQR workspace */

Return bibtex citation for the solver.

\sa MatrixBase::coeff() * \warning the coordinates must fit into the referenced triangular part */

Recursively collect variable names.

\returns the number of columns */

Compose variable ID mappings across all reductions. Returns a single ``{orig_var_id: [final_var_id, ...]}`` dict that accounts for ev