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Functions13,519 in github.com/cvxpy/cvxpy

↓ 1 callersMethod__eq__
Equality : Creates a constraint ``self == other``.
cvxpy/expressions/expression.py:982
↓ 1 callersMethod__exit__
(self, exc_type, exc_val, exc_tb)
cvxpy/utilities/canonical.py:227
↓ 1 callersMethod__ge__
(self, other: ExpressionLike)
cvxpy/expressions/expression.py:997
↓ 1 callersMethod__gt__
(self, other: ExpressionLike)
cvxpy/expressions/expression.py:1000
↓ 1 callersMethod__init__
(self, x, y, z, alpha, constr_id=None)
cvxpy/constraints/power.py:42
↓ 1 callersMethod__init__
(self, expr, constr_id=None)
cvxpy/constraints/psd.py:52
↓ 1 callersMethod__init__
(self, expr, constr_id=None)
cvxpy/constraints/zero.py:31
↓ 1 callersMethod__init__
Atom representing :math:`x^T P x`.
cvxpy/atoms/quad_form.py:39
↓ 1 callersMethod__init__
(self, x, p: int = 2, axis: None | int | tuple[int, ...] = None, keepdims: bool = False, max_
cvxpy/atoms/pnorm.py:123
↓ 1 callersMethod__init__
(self, x)
cvxpy/atoms/elementwise/ceil.py:27
↓ 1 callersMethod__init__
(self, x, p, max_denom: int = 1024)
cvxpy/atoms/elementwise/power.py:172
↓ 1 callersMethod__init__
(self, arg)
cvxpy/atoms/elementwise/logic.py:94
↓ 1 callersMethod__init__
(self, arg_groups: Iterable[Expression])
cvxpy/atoms/affine/add_expr.py:36
↓ 1 callersMethod__init__
(self, expr, k: int = 0)
cvxpy/atoms/affine/diag.py:58
↓ 1 callersMethod__init__
(self, expr, key, orig_key=None)
cvxpy/atoms/affine/index.py:58
↓ 1 callersMethod__le__
Inequality : Creates an inequality constraint ``self <= other``.
cvxpy/expressions/expression.py:988
↓ 1 callersMethod__lt__
(self, other: ExpressionLike)
cvxpy/expressions/expression.py:993
↓ 1 callersMethod__next__
Make an alias for Python 3.x */
cvxpy/cvxcore/python/cvxcore_wrap.cxx:3441
↓ 1 callersMethod__radd__
Expression : Sum two expressions.
cvxpy/expressions/expression.py:780
↓ 1 callersMethod__rdiv__
Expression : Called for Number / Expression.
cvxpy/expressions/expression.py:870
↓ 1 callersMethod__repr__
Returns a string with information about the constraint.
cvxpy/constraints/zero.py:35
↓ 1 callersMethod__rlshift__
PSD : Creates a negative semidefinite inequality.
cvxpy/expressions/expression.py:919
↓ 1 callersMethod__rmul__
Expression : Called for Number * Expression.
cvxpy/expressions/expression.py:882
↓ 1 callersMethod__rpow__
Raise base to the power of this expression (base ** self). Uses the identity: a**x = exp(x * log(a)) Parameters ----------
cvxpy/expressions/expression.py:688
↓ 1 callersMethod__rrshift__
PSD : Creates a positive semidefinite inequality.
cvxpy/expressions/expression.py:907
↓ 1 callersMethod__rsub__
Expression : The difference of two expressions.
cvxpy/expressions/expression.py:796
↓ 1 callersMethod__str__
(self)
cvxpy/constraints/exponential.py:215
↓ 1 callersMethod__str__
(self)
cvxpy/constraints/exponential.py:343
↓ 1 callersMethod__str__
Returns a string showing the mathematical expression.
cvxpy/expressions/expression.py:185
↓ 1 callersMethod_add_constraints
Create a list of constraints.
cvxpy/reductions/solvers/conic_solvers/scip_conif.py:228
↓ 1 callersFunction_add_psd_bound_rows
Add finite variable bounds as explicit inequality rows. The rows are inserted right after the existing NonNeg (LEQ) block so the cone partiti
cvxpy/reductions/solvers/conic_solvers/copt_conif.py:19
↓ 1 callersMethod_affine_above_relevant
Whether canonicalize_tree result for ``expr`` depends on affine_above. Returns True when ``expr`` itself or any descendant could take the
cvxpy/reductions/dcp2cone/dcp2cone.py:275
↓ 1 callersFunction_as_expression
Cast scalars/arrays to ``Constant`` while leaving Expressions intact.
cvxpy/atoms/affine/stack.py:44
↓ 1 callersFunction_bisect
Bisect `problem` on the parameter `t`.
cvxpy/reductions/solvers/bisection.py:103
↓ 1 callersMethod_broadcast_batch_dims
Broadcast batch dimensions for ND matrix multiplication. For A @ B where A has shape (...a, m, k) and B has shape (...b, k, n),
cvxpy/atoms/affine/binary_operators.py:146
↓ 1 callersMethod_build_dualized_task
This function assumes "data" is formatted according to MOSEK.apply when the problem features no integer constraints. This dictionary
cvxpy/reductions/solvers/conic_solvers/mosek_conif.py:266
↓ 1 callersFunction_build_interleaved_param_matrix_mul
Build the stacked interleaved matrix for a batch-varying parametric mul (C @ X). For C (B, m, k) @ X (B, k, n) where C depends on Parameters
cvxpy/lin_ops/backends/scipy_backend.py:122
↓ 1 callersFunction_build_interleaved_param_matrix_rmul
Build the stacked interleaved matrix for a batch-varying parametric rmul (X @ C). For X (B, m, k) @ C (B, k, n) where C depends on Parameter
cvxpy/lin_ops/backends/scipy_backend.py:256
↓ 1 callersFunction_build_nlp_chain
Build the NLP reduction chain and return (SolvingChain, kwargs). Solver selection may mutate kwargs (e.g., Knitro algorithm, Uno preset).
cvxpy/reductions/solvers/nlp_solving_chain.py:27
↓ 1 callersFunction_build_pow_tree
Recursively build a balanced binary tree for PowConeND decomposition.
cvxpy/reductions/cone2cone/exact.py:69
↓ 1 callersMethod_build_slack_task
This function assumes "data" is formatted by MOSEK.apply, and is only intended when the problem has integer constraints. As of MOSEK
cvxpy/reductions/solvers/conic_solvers/mosek_conif.py:340
↓ 1 callersMethod_build_soc_lift_all
Build all SOC lifts aux_i + A[row,:]@x = b[row] in one CSR matrix. Returns ------- A_lift : csr_array or None Sha
cvxpy/reductions/solvers/conic_solvers/cuopt_conif.py:244
↓ 1 callersFunction_build_solving_chain
Build a reduction chain for a specific solver. The chain is assembled in three stages: 1. **Solver context** — ``SolverInfo`` is derived fro
cvxpy/reductions/solvers/solving_chain.py:105
↓ 1 callersMethod_build_working_problem
Assemble A_work and equality row bounds for eq/ineq + SOC lifts.
cvxpy/reductions/solvers/conic_solvers/cuopt_conif.py:309
↓ 1 callersFunction_cache_key
(args, kwargs)
cvxpy/utilities/performance_utils.py:48
↓ 1 callersMethod_canonicalize_tree
(self, expr)
cvxpy/reductions/dqcp2dcp/dqcp2dcp.py:122
↓ 1 callersMethod_chain_constraints
Raises an error due to chained constraints.
cvxpy/constraints/constraint.py:281
↓ 1 callersMethod_check_bound_feasibility
Check that promoted bounds are feasible. Validates: no -inf upper bounds, no +inf lower bounds, lb <= ub, no NaN, and structural zero
cvxpy/expressions/leaf.py:784
↓ 1 callersFunction_collect_x_duals_into_array
Collect x-component duals from leaf cones into pre-allocated array.
cvxpy/reductions/cone2cone/soc_dim3.py:256
↓ 1 callersFunction_compute_block_indices
Compute block indices for reducing along specified axes (Fortran order). Parameters ---------- shape : tuple Shape of input array
cvxpy/reductions/dcp2cone/canonicalizers/quad/quad_over_lin_canon.py:60
↓ 1 callersMethod_compute_cones
Compute both the QP-filtered and full cone sets. All QUAD_CANON_METHODS atoms canonicalize to SOC, so the only possible difference be
cvxpy/problems/problem_form.py:181
↓ 1 callersMethod_compute_conic_repr_of_set
(self)
cvxpy/transforms/suppfunc.py:185
↓ 1 callersMethod_compute_gp_cones
Compute cone sets for a DGP problem. DGP atoms map to different DCP atoms than their standard DCP canonicalization. For example, norm
cvxpy/problems/problem_form.py:284
↓ 1 callersFunction_constant_key
Key a Constant in one of three ways, in order of preference: 1. Small array (<= 64 elements): value hash. Catches the case where two struc
cvxpy/reductions/subexpr_cache.py:137
↓ 1 callersMethod_construct_dual_variables
(self, args)
cvxpy/constraints/constraint.py:129
↓ 1 callersFunction_contract_pair
Contract a pair of operands by elementwise multiplication and summation. This function performs the core contraction operation between two tensor
cvxpy/atoms/affine/einsum.py:349
↓ 1 callersMethod_convert_constraint
Convert a single constraint, following the conversion chain transitively. Returns a list of constraints in conversion order (for dual recover
cvxpy/reductions/cone2cone/exact.py:478
↓ 1 callersMethod_create_variables
Create a list of variables.
cvxpy/reductions/solvers/conic_solvers/scip_conif.py:205
↓ 1 callersMethod_define_data
Define data parts from the data reference.
cvxpy/reductions/solvers/conic_solvers/scip_conif.py:195
↓ 1 callersMethod_detect_boolean
Check if the original value has boolean dtype.
cvxpy/expressions/constants/constant.py:71
↓ 1 callersMethod_dual_cone
Implements the dual cone of the second-order cone See Pg 85 of the MOSEK modelling cookbook for more information
cvxpy/constraints/second_order.py:184
↓ 1 callersMethod_dual_cone
Method for modelling problems with the dual cone of `Cone` If the user simply calls the method without any arguments, then the dual c
cvxpy/constraints/cones.py:44
↓ 1 callersMethod_dual_cone
Implements the dual cone of the PSD cone See Pg 85 of the MOSEK modelling cookbook for more information
cvxpy/constraints/psd.py:111
↓ 1 callersMethod_dual_vars
Map the stacked ``[eq; ineq]`` dual vector to a CVXPY dual dict. Shared by the optimal duals and the infeasibility (Farkas) certificate,
cvxpy/reductions/solvers/conic_solvers/copt_conif.py:141
↓ 1 callersFunction_empty_float
Return a copy of an empty float64 array.
cvxpy/lin_ops/backends/coo_backend.py:41
↓ 1 callersMethod_ensure_valid_bounds
(self, value)
cvxpy/expressions/leaf.py:839
↓ 1 callersFunction_env_var_to_bool
(name: str, default: bool)
cvxpy/settings.py:115
↓ 1 callersFunction_extract_pow_duals
Extract W and z duals from raw 3D cone duals using tree structure.
cvxpy/reductions/cone2cone/exact.py:182
↓ 1 callersFunction_extract_pow_duals_recursive
Recursively extract W duals from the tree. For each node: - SingleVarNode: the variable's dual comes from the parent cone's x (row 0) o
cvxpy/reductions/cone2cone/exact.py:147
↓ 1 callersFunction_factorize
Draw a shape of exactly `ndim` positive dimensions whose product equals `size`. Algorithm: for each of the first ndim-1 slots, sample any di
cvxpy/tests/test_fuzz_reshape.py:68
↓ 1 callersFunction_fallback_solver
Last-resort: try every installed solver, warn, or raise.
cvxpy/reductions/solvers/solving_chain.py:68
↓ 1 callersFunction_find_bisection_interval
Finds an interval for bisection.
cvxpy/reductions/solvers/bisection.py:56
↓ 1 callersFunction_get_all_tree_cone_ids
Get all constraint IDs from a tree, including SpecialNode cases.
cvxpy/reductions/cone2cone/soc_dim3.py:397
↓ 1 callersMethod_get_convergence_info
(stats, candidate_type)
cvxpy/reductions/solvers/conic_solvers/pdlp_conif.py:184
↓ 1 callersMethod_get_cuopt_parameter_strings
(self)
cvxpy/reductions/solvers/conic_solvers/cuopt_conif.py:114
↓ 1 callersFunction_get_original_dim
Get the original dimension of a tree.
cvxpy/reductions/cone2cone/soc_dim3.py:357
↓ 1 callersFunction_get_path
Get the contraction path for the einsum operation. This function determines the order in which pairs of tensors should be contracted to minim
cvxpy/atoms/affine/einsum.py:222
↓ 1 callersFunction_get_root_t_dual
Get the t-component dual (lambda) from the root cone.
cvxpy/reductions/cone2cone/soc_dim3.py:321
↓ 1 callersMethod_get_solver_settings
(self, solver_opts, mip, verbose)
cvxpy/reductions/solvers/conic_solvers/cuopt_conif.py:189
↓ 1 callersFunction_get_squeezed_shape
( shape: tuple[int, ...], axis: int | tuple[int, ...] | None, )
cvxpy/atoms/affine/squeeze.py:42
↓ 1 callersMethod_get_status_lp
(self, cuopt_status)
cvxpy/reductions/solvers/conic_solvers/cuopt_conif.py:84
↓ 1 callersMethod_get_status_mip
(self, cuopt_status)
cvxpy/reductions/solvers/conic_solvers/cuopt_conif.py:72
↓ 1 callersMethod_get_sum_row_indices
Internal function that computes the row indices corresponding to the sum along a specified axis.
cvxpy/lin_ops/backends/scipy_backend.py:875
↓ 1 callersMethod_get_sum_row_map
Compute row mapping for axis-specific sum. Returns array where row_map[i] is the output row for input row i.
cvxpy/lin_ops/backends/coo_backend.py:1763
↓ 1 callersFunction_get_unsupported_cone_message
Get a descriptive message about unsupported cones.
cvxpy/reductions/solvers/qp_solvers/qp_solver.py:34
↓ 1 callersMethod_grad
Gives the (sub/super)gradient of the atom w.r.t. each argument. Matrix expressions are vectorized, so the gradient is a matrix. Args
cvxpy/atoms/atom.py:527
↓ 1 callersMethod_grad
Gives the (sub/super)gradient of elementwise multiply. For z = multiply(x, y), we have z[i] = x[i] * y[i]. Gradient is diagonal: grad
cvxpy/atoms/affine/binary_operators.py:425
↓ 1 callersMethod_grad_matrices
Compute gradient matrices for all batch elements. Returns an array of shape (*batch, n, n) where each (n, n) slice is the (sub)gradie
cvxpy/atoms/lambda_max.py:52
↓ 1 callersFunction_handle_solve_status
Map CPLEX MIP solution status codes to non-MIP status codes.
cvxpy/reductions/solvers/conic_solvers/cplex_conif.py:75
↓ 1 callersFunction_has_parametric_bounds
Check if any variable has an Expression (parametric) bound.
cvxpy/reductions/matrix_stuffing.py:122
↓ 1 callersFunction_hashable_value
Best-effort conversion of a ``get_data()`` entry to a hashable form.
cvxpy/reductions/subexpr_cache.py:205
↓ 1 callersMethod_infer_shape
(shape: tuple[int, ...], size: int)
cvxpy/atoms/affine/reshape.py:76
↓ 1 callersFunction_initial_reduction
Reduce operands with repeated indices by taking diagonal elements. This function handles the case where a subscript pattern contains repeated
cvxpy/atoms/affine/einsum.py:261
↓ 1 callersFunction_is_boolean_arg
Check if an argument is a valid boolean logic input.
cvxpy/atoms/elementwise/logic.py:24
↓ 1 callersFunction_is_internal_frame
Return True if *filename* belongs to cvxpy internals (not tests).
cvxpy/utilities/warn.py:34
↓ 1 callersFunction_lookup_by_name
Look up installed QP and conic instances for a solver name. Returns (qp_inst | None, conic_inst | None). GP mode suppresses QP.
cvxpy/reductions/solvers/solving_chain.py:51
↓ 1 callersMethod_lorentz_qcoo
COO for -x_0^2 + sum_{i>0} x_i^2 <= 0 (cuOpt Lorentz / CVXPY SOC).
cvxpy/reductions/solvers/conic_solvers/cuopt_conif.py:219
↓ 1 callersMethod_make_cache_key
Build a hashable structural key for an Expression subtree. Returns None if a safe key cannot be built, in which case the caller skips
cvxpy/reductions/dcp2cone/dcp2cone.py:250
↓ 1 callersMethod_max_ndim
The maximum number of dimensions of the sub-expression.
cvxpy/utilities/canonical.py:194
↓ 1 callersMethod_mul_interleaved
Batch-varying constant @ variable: use interleaved matrix structure. When the constant has batch dimensions (e.g., C(B,m,k) @ X(B,k,
cvxpy/lin_ops/backends/scipy_backend.py:580
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