# Index of values

 A add_identity [Sundials_Matrix.ArrayBand] Increment a square matrix by the identity matrix. add_identity [Sundials_Matrix.ArrayDense] Increments a square matrix by the identity matrix. add_tracing [Nvector_custom] add_tracing p ops modifies a set of Nvector_custom.nvector_ops so that a message, prefixed by p, is printed each time an operation is called. algebraic [Ida.VarId] The constant 0.0. array_nvec_ops [Nvector_array.ARRAY_NVECTOR] The set of nvector operations on an array. arrayband [Sundials_Matrix] By default, band n returns an n by n band matrix with all bandwidths equal to 2 and all values initialized to 0.0. arraydense [Sundials_Matrix] By default, arraydense n returns an n by n dense matrix with all elements initialized to 0.0. B backward_normal [Idas.Adjoint] Integrates a backward ODE system over an interval. backward_normal [Cvodes.Adjoint] Integrates a backward ODE system over an interval. backward_one_step [Idas.Adjoint] Like Idas.Adjoint.backward_normal but returns after one internal solver step. backward_one_step [Cvodes.Adjoint] Like Cvodes.Adjoint.backward_normal but returns after one internal solver step. band [Sundials_LinearSolver.Direct] Creates a direct linear solver on banded matrices. band [Sundials_Matrix] By default, band n returns an n by n band matrix with all bandwidths equal to 2 and all values initialized to 0.0. big_real [Sundials_Config] The largest value representable as a real. blit [Sundials_Matrix.ArrayBand] blit src dst copies the contents of src into dst. blit [Sundials_Matrix.ArrayDense] blit src dst copies the contents of src into dst. blit [Sundials_Matrix.Sparse] blit src dst copies the contents of src into dst. blit [Sundials_Matrix.Band] blit src dst copies the contents of src into dst. blit [Sundials_Matrix.Dense] blit src dst copies the contents of src into dst. blit [Sundials_Matrix] blit src dst copies the contents of src into dst. blit [Sundials.RootDirs] Copy the first array into the second one. blit [Sundials_RealArray2] Copy the first array into the second one. blit [Sundials_RealArray] Copy the first array into the second one. blit_some [Sundials.RootDirs] blit_some src isrc dst idst len copies len elements of src at offset isrc to dst at offset idst. blit_some [Sundials_RealArray] blit_some src isrc dst idst len copies len elements of src at offset isrc to dst at offset idst. C calc_ic [Idas.Adjoint] Computes the algebraic components of the initial state and the differential components of the derivative vectors for certain index-one problems. calc_ic_sens [Idas.Adjoint] Computes the algebraic components of the initial state and the differential components of the derivative vectors for certain index-one problems. calc_ic_y [Idas.Sensitivity] Identical to Ida.calc_ic_y, but with the possibility of filling s with the corrected sensitivity values. calc_ic_y [Ida] Computes the initial state vector for certain index-one problems. calc_ic_ya_yd' [Idas.Sensitivity] Identical to Ida.calc_ic_ya_yd', but with the possibility of filling s and s' with the corrected sensitivity and sensitivity derivative values. calc_ic_ya_yd' [Ida] Computes the algebraic components of the initial state and derivative vectors for certain index-one problems. check [Nvector] check v1 v2 checks v1 and v2 for compatibility. classical_gs [Sundials_LinearSolver.Iterative.Algorithms] Performs a classical Gram-Schmidt orthogonalization. clear_diagnostics [Arkode] Do not write step adaptivity or solver diagnostics of a file. clear_err_handler_fn [Arkode] Restores the default error handling function. clear_err_handler_fn [Ida] Restores the default error handling function. clear_err_handler_fn [Kinsol] Restores the default error handling function. clear_err_handler_fn [Cvode] Restores the default error handling function. clear_info_handler_fn [Kinsol] Restores the default information handling function. clear_jac_times [Idas.Adjoint.Spils] Remove a Jacobian-times-vector function and use the default implementation. clear_jac_times [Cvodes.Adjoint.Spils] Remove a Jacobian-times-vector function and use the default implementation. clear_jac_times [Arkode.Spils] Remove a Jacobian-times-vector function and use the default implementation. clear_jac_times [Ida.Spils] Remove a Jacobian-times-vector function and use the default implementation. clear_jac_times [Kinsol.Spils] Remove a Jacobian-times-vector function and use the default implementation. clear_jac_times [Cvode.Spils] Remove a Jacobian-times-vector function and use the default implementation. clear_postprocess_step_fn [Arkode] Clear the post processing step function. clear_stability_fn [Arkode] Clears the problem-dependent function that estimates a stable time step size for the explicit portion of the ODE system. clone [Nvector_parallel] Creates an nvector with a distinct underlying array but that shares the original global size and communicator. col [Sundials_RealArray2] col a j returns the jth column of a. communicator [Nvector_parallel] Returns the communicator used for the parallel nvector. copy [Sundials.RootDirs] copy n a returns an array with n elements, initialized from the contents of a. copy [Sundials.Roots] Creates a new array with the same contents as an existing one. copy [Sundials_RealArray2] Creates a new array with the same contents as an existing one. copy [Sundials_RealArray] Creates a new array with the same contents as an existing one. create [Sundials_Matrix.ArrayBand] create smu ml n returns an uninitialized n by n band matrix with storage upper bandwidth smu and lower half-bandwidth ml. create [Sundials_Matrix.ArrayDense] create m n returns an uninitialized m by n array dense matrix. create [Sundials_Matrix.Band] Returns an uninitialized band matrix with the given Sundials_Matrix.Band.dimensions. create [Sundials_Matrix.Dense] create m n returns an uninitialized m by n dense matrix. create [Sundials.RootDirs] create n returns an array with n elements each set to IncreasingOrDecreasing. create [Sundials.Roots] create n returns an array with n elements each set to NoRoot. create [Sundials_LintArray] create n returns an uninitialized array with n elements. create [Sundials_RealArray2] create nr nc returns an uninitialized array with nr rows and nc columns. create [Sundials_RealArray] create n returns an uninitialized array with n elements. D default_tolerances [Arkode] A default relative tolerance of 1.0e-4 and absolute tolerance of 1.0e-9. default_tolerances [Ida] A default relative tolerance of 1.0e-4 and absolute tolerance of 1.0e-8. default_tolerances [Cvode] A default relative tolerance of 1.0e-4 and absolute tolerance of 1.0e-8. dense [Sundials_LinearSolver.Direct] Creates a direct linear solver on dense matrices. dense [Sundials_Matrix] detected [Sundials.Roots] Returns true only if the specified element is either Rising or Falling. differential [Ida.VarId] The constant 1.0. dims [Sundials_Matrix.ArrayBand] Returns the dimensions of an array band matrix. dims [Sundials_Matrix.Sparse] nnz, np = dims m returns the allocated number of nonzeros nnz and of the number np of columns (for csc) or rows (for csr) in the matrix m. dims [Sundials_Matrix.Band] Returns the dimensions of a band matrix. E empty [Sundials_LintArray] An array with no elements. empty [Sundials_RealArray2] An array with no elements. empty [Sundials_RealArray] An array with no elements. exists [Sundials.Roots] true if any elements are equal to Rising or Falling. F falling [Sundials.Roots] Returns true only if the specified element is Falling. fill [Sundials.RootDirs] fill_all a x sets the values of a to x everywhere. fill [Sundials.Roots] fill a x sets all elements in a to x. fill [Sundials_RealArray2] fill a c sets all elements of a to the constant c. fill [Sundials_RealArray] fill a c sets all elements of a to the constant c. floata [Sundials.Util] Returns the bit-level representation of a float in hexadecimal as a string. flush [Sundials_Logfile] Flushes the given file. fold_left [Sundials_RealArray] fold_left f b a returns f (f (f b a.{0}) a.{1}) ...). fold_right [Sundials_RealArray] fold_right f b a returns (f ... (f a.{n-2} (f a.{n-1} b))). format_float [Sundials.Util] format_float fmt f formats f according to the format string fmt. forward_normal [Idas.Adjoint] Integrates the forward problem over an interval and saves checkpointing data. forward_normal [Cvodes.Adjoint] Integrates the forward problem over an interval and saves checkpointing data. forward_one_step [Idas.Adjoint] Integrates the forward problem over an interval and saves checkpointing data. forward_one_step [Cvodes.Adjoint] Integrates the forward problem over an interval and saves checkpointing data. from_band [Sundials_Matrix.Sparse] Creates a sparse matrix in the specified format from a band matrix by copying all values of magnitude greater than the given tolerance. from_dense [Sundials_Matrix.Sparse] Creates a sparse matrix in in the specified format from a dense matrix by copying all values of magnitude greater than the given tolerance. G gbtrf [Sundials_Matrix.ArrayBand] gbtrf a p performs the LU factorization of a with partial pivoting according to p. gbtrs [Sundials_Matrix.ArrayBand] gbtrs a p b finds the solution of ax = b using LU factorization. geq_zero [Sundials.Constraint] The constant 1.0. geqrf [Sundials_Matrix.ArrayDense] geqrf a beta work performs the QR factorization of a. get [Idas.Adjoint.Quadrature] Returns the backward quadrature solutions and time reached after a successful solver step. get [Idas.Adjoint] Fills the given vectors, yb and yb', with the solution of the backward DAE problem at the returned time, interpolating if necessary. get [Idas.Sensitivity.Quadrature] Returns the quadrature sensitivity solutions and time reached after a successful solver step. get [Idas.Sensitivity] Returns the sensitivity solution vectors after a successful solver step. get [Idas.Quadrature] Returns the quadrature solutions and time reached after a successful solver step. get [Cvodes.Adjoint.Quadrature] Returns the backward quadrature solutions and time reached after a successful solver step. get [Cvodes.Adjoint] Fills the given vector with the solution of the backward ODE problem at the returned time, interpolating if necessary. get [Cvodes.Sensitivity.Quadrature] Returns the quadrature sensitivity solutions and time reached after a successful solver step. get [Cvodes.Sensitivity] Returns the sensitivity solution vectors after a successful solver step. get [Cvodes.Quadrature] Returns the quadrature solutions and time reached after a successful solver step. get [Sundials_Matrix.ArrayBand] get a i j returns the value at row i and column j of a. get [Sundials_Matrix.ArrayDense] get a i j returns the value at row i and column j of a. get [Sundials_Matrix.Sparse] r, v = get a idx returns the row/column r and value v at the idxth position. get [Sundials_Matrix.Band] get a i j returns the value at row i and column j of a. get [Sundials_Matrix.Dense] get a i j returns the value at row i and column j of a. get [Sundials.RootDirs] get r i returns the ith element of r. get [Sundials.Roots] get r i returns the ith element of r. get [Sundials_RealArray2] get a i j returns the value at row i and column j of a. get1 [Idas.Sensitivity.Quadrature] Returns a single quadrature sensitivity vector after a successful solver step. get1 [Idas.Sensitivity] Returns a single sensitivity solution vector after a successful solver step. get1 [Cvodes.Sensitivity.Quadrature] Returns a single quadrature sensitivity vector after a successful solver step. get1 [Cvodes.Sensitivity] Returns a single sensitivity solution vector after a successful solver step. get_actual_init_step [Idas.Adjoint] Returns the the value of the integration step size used on the first step. get_actual_init_step [Cvodes.Adjoint] Returns the the value of the integration step size used on the first step. get_actual_init_step [Arkode] Returns the the value of the integration step size used on the first step. get_actual_init_step [Ida] Returns the the value of the integration step size used on the first step. get_actual_init_step [Cvode] Returns the the value of the integration step size used on the first step. get_cj [Idas.Adjoint.Alternate] Returns the current cj value. get_cj [Ida.Alternate] Returns the current cj value. get_cjratio [Idas.Adjoint.Alternate] Returns the current cjratio value. get_cjratio [Ida.Alternate] Returns the current cjratio value. get_col [Sundials_Matrix.Sparse] get_col a j returns the data index of column j. get_colval [Sundials_Matrix.Sparse] c = get_colval a idx returns the column c at the idxth position. get_current_butcher_tables [Arkode] Returns the explicit and implicit Butcher tables in use by the solver. get_current_order [Idas.Adjoint] Returns the integration method order to be used on the next internal step. get_current_order [Cvodes.Adjoint] Returns the integration method order to be used on the next internal step. get_current_order [Ida] Returns the integration method order to be used on the next internal step. get_current_order [Cvode] Returns the integration method order to be used on the next internal step. get_current_step [Idas.Adjoint] Returns the integration step size to be attempted on the next internal step. get_current_step [Cvodes.Adjoint] Returns the integration step size to be attempted on the next internal step. get_current_step [Arkode] Returns the integration step size to be attempted on the next internal step. get_current_step [Ida] Returns the integration step size to be attempted on the next internal step. get_current_step [Cvode] Returns the integration step size to be attempted on the next internal step. get_current_time [Idas.Adjoint] Returns the the current internal time reached by the solver. get_current_time [Cvodes.Adjoint] Returns the the current internal time reached by the solver. get_current_time [Arkode] Returns the the current internal time reached by the solver. get_current_time [Ida] Returns the the current internal time reached by the solver. get_current_time [Cvode] Returns the the current internal time reached by the solver. get_data [Sundials_Matrix.Sparse] v = get_data a idx returns the value v at the idxth position. get_dky [Idas.Adjoint] Returns the interpolated solution or derivatives. get_dky [Idas.Sensitivity.Quadrature] Returns the interpolated solution or derivatives of the quadrature sensitivity solution. get_dky [Idas.Sensitivity] Returns the interpolated solution or derivatives of the sensitivity solution vectors. get_dky [Idas.Quadrature] Returns the interpolated solution or derivatives of quadrature variables. get_dky [Cvodes.Adjoint] Returns the interpolated solution or derivatives. get_dky [Cvodes.Sensitivity.Quadrature] Returns the interpolated solution or derivatives of the quadrature sensitivity solution. get_dky [Cvodes.Sensitivity] Returns the interpolated solution or derivatives of the sensitivity solution vectors. get_dky [Cvodes.Quadrature] Returns the interpolated solution or derivatives of quadrature variables. get_dky [Arkode] Returns the interpolated solution or derivatives. get_dky [Ida] Returns the interpolated solution or derivatives. get_dky [Cvode] Returns the interpolated solution or derivatives. get_dky1 [Idas.Sensitivity.Quadrature] Returns the interpolated solution or derivatives of a single quadrature sensitivity solution vector. get_dky1 [Idas.Sensitivity] Returns the interpolated solution or derivatives of a single sensitivity solution vector. get_dky1 [Cvodes.Sensitivity.Quadrature] Returns the interpolated solution or derivatives of a single quadrature sensitivity solution vector. get_dky1 [Cvodes.Sensitivity] Returns the interpolated solution or derivatives of a single sensitivity solution vector. get_err_weights [Idas.Adjoint.Quadrature] Returns the quadrature error weights at the current time. get_err_weights [Idas.Adjoint] Returns the solution error weights at the current time. get_err_weights [Idas.Sensitivity.Quadrature] Returns the quadrature error weights at the current time. get_err_weights [Idas.Sensitivity] Returns the sensitivity error weights at the current time. get_err_weights [Idas.Quadrature] Returns the quadrature error weights at the current time. get_err_weights [Cvodes.Adjoint.Quadrature] Returns the quadrature error weights at the current time. get_err_weights [Cvodes.Adjoint] Returns the solution error weights at the current time. get_err_weights [Cvodes.Sensitivity.Quadrature] Returns the quadrature error weights at the current time. get_err_weights [Cvodes.Sensitivity] Returns the sensitivity error weights at the current time. get_err_weights [Cvodes.Quadrature] Returns the quadrature error weights at the current time. get_err_weights [Arkode] Returns the solution error weights at the current time. get_err_weights [Ida] Returns the solution error weights at the current time. get_err_weights [Cvode] Returns the solution error weights at the current time. get_est_local_errors [Idas.Adjoint] Returns the vector of estimated local errors. get_est_local_errors [Cvodes.Adjoint] Returns the vector of estimated local errors. get_est_local_errors [Arkode] Returns the vector of estimated local errors. get_est_local_errors [Ida] Returns the vector of estimated local errors. get_est_local_errors [Cvode] Returns the vector of estimated local errors. get_f_fscale [Kinsol.Alternate] Returns the internal f and fscale values. get_func_norm [Kinsol] Returns the scaled Euclidiean l2 norm of the nonlinear system function $F(u)$ evaluated at the current iterate. get_gammas [Cvodes.Adjoint.Alternate] Returns the current and previous gamma values. get_gammas [Arkode.Alternate] Returns the current and previous gamma values. get_gammas [Cvode.Alternate] Returns the current and previous gamma values. get_id [Sundials_Matrix] Return the internal type identifier of a matrix. get_integrator_stats [Idas.Adjoint] Returns the integrator statistics as a group. get_integrator_stats [Cvodes.Adjoint] Returns the integrator statistics as a group. get_integrator_stats [Arkode] Returns the integrator statistics as a group. get_integrator_stats [Ida] Returns the integrator statistics as a group. get_integrator_stats [Cvode] Returns the integrator statistics as a group. get_last_order [Idas.Adjoint] Returns the integration method order used during the last internal step. get_last_order [Cvodes.Adjoint] Returns the integration method order used during the last internal step. get_last_order [Ida] Returns the integration method order used during the last internal step. get_last_order [Cvode] Returns the integration method order used during the last internal step. get_last_step [Idas.Adjoint] Returns the integration step size taken on the last internal step. get_last_step [Cvodes.Adjoint] Returns the integration step size taken on the last internal step. get_last_step [Arkode] Returns the integration step size taken on the last successful internal step. get_last_step [Ida] Returns the integration step size taken on the last internal step. get_last_step [Cvode] Returns the integration step size taken on the last internal step. get_nonlin_solv_stats [Idas.Adjoint] Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails. get_nonlin_solv_stats [Idas.Sensitivity] Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails during sensitivity calculations. get_nonlin_solv_stats [Cvodes.Adjoint] Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails. get_nonlin_solv_stats [Cvodes.Sensitivity] Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails during sensitivity calculations. get_nonlin_solv_stats [Arkode] Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails. get_nonlin_solv_stats [Ida] Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails. get_nonlin_solv_stats [Cvode] Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails. get_num_acc_steps [Arkode] Returns the cumulative number of accuracy-limited steps taken by the solver. get_num_backtrack_ops [Ida] Returns the number of backtrack operations during Ida.calc_ic_ya_yd' or Ida.calc_ic_y. get_num_backtrack_ops [Kinsol] Returns the number of backtrack operations (step length adjustments) performed by the line search algorithm. get_num_beta_cond_fails [Kinsol] Returns the number of beta-condition failures. get_num_conv_fails [Idas.Adjoint.Spils] Returns the cumulative number of linear convergence failures. get_num_conv_fails [Cvodes.Adjoint.Spils] Returns the cumulative number of linear convergence failures. get_num_conv_fails [Arkode.Mass.Spils] Returns the cumulative number of linear convergence failures. get_num_conv_fails [Arkode.Spils] Returns the cumulative number of linear convergence failures. get_num_conv_fails [Ida.Spils] Returns the cumulative number of linear convergence failures. get_num_conv_fails [Kinsol.Spils] Returns the cumulative number of linear convergence failures. get_num_conv_fails [Cvode.Spils] Returns the cumulative number of linear convergence failures. get_num_err_test_fails [Idas.Adjoint.Quadrature] Returns the number of local error test failures due to quadrature variables. get_num_err_test_fails [Idas.Adjoint] Returns the number of local error test failures that have occurred. get_num_err_test_fails [Idas.Sensitivity.Quadrature] Returns the number of local error test failures due to quadrature variables. get_num_err_test_fails [Idas.Sensitivity] Returns the number of local error test failures for the sensitivity variables that have occurred. get_num_err_test_fails [Idas.Quadrature] Returns the number of local error test failures that have occurred due to quadrature variables. get_num_err_test_fails [Cvodes.Adjoint.Quadrature] Returns the number of local error test failures due to quadrature variables. get_num_err_test_fails [Cvodes.Adjoint] Returns the number of local error test failures that have occurred. get_num_err_test_fails [Cvodes.Sensitivity.Quadrature] Returns the number of local error test failures due to quadrature variables. get_num_err_test_fails [Cvodes.Sensitivity] Returns the number of local error test failures for the sensitivity variables that have occurred. get_num_err_test_fails [Cvodes.Quadrature] Returns the number of local error test failures that have occurred due to quadrature variables. get_num_err_test_fails [Arkode] Returns the number of local error test failures that have occurred. get_num_err_test_fails [Ida] Returns the number of local error test failures that have occurred. get_num_err_test_fails [Cvode] Returns the number of local error test failures that have occurred. get_num_exp_steps [Arkode] Returns the cumulative number of stability-limited steps taken by the solver. get_num_func_evals [Kinsol.Spils] Returns the number of calls to the system function for finite difference quotient Jacobian-vector product approximations. get_num_func_evals [Kinsol.Dls] Returns the number of calls made by a direct linear solver to the user system function for computing the difference quotient approximation to the Jacobian. get_num_func_evals [Kinsol] Returns the number of evaluations of the system function. get_num_g_evals [Arkode] Returns the cumulative number of calls made to the user-supplied root function g. get_num_g_evals [Ida] Returns the cumulative number of calls made to the user-supplied root function g. get_num_g_evals [Cvode] Returns the cumulative number of calls made to the user-supplied root function g. get_num_gfn_evals [Idas_bbd] Returns the number of calls to the right-hand side function due to finite difference banded Jacobian approximation in the setup function. get_num_gfn_evals [Ida_bbd] Returns the number of calls to the right-hand side function due to finite difference banded Jacobian approximation in the setup function. get_num_gfn_evals [Cvodes_bbd] Returns the number of calls to the right-hand side function due to finite difference banded Jacobian approximation in the setup function. get_num_gfn_evals [Cvode_bbd] Returns the number of calls to the right-hand side function due to finite difference banded Jacobian approximation in the setup function. get_num_gfn_evals [Arkode_bbd] Returns the number of calls to the right-hand side function due to finite difference banded Jacobian approximation in the setup function. get_num_gfn_evals [Kinsol_bbd] Returns the number of calls to the right-hand side function due to finite difference banded Jacobian approximation in the setup function. get_num_jac_evals [Idas.Adjoint.Dls] Returns the number of calls made by a direct linear solver to the Jacobian approximation function. get_num_jac_evals [Cvodes.Adjoint.Dls] Returns the number of calls made by a direct linear solver to the Jacobian approximation function. get_num_jac_evals [Arkode.Dls] Returns the number of calls made by a direct linear solver to the Jacobian approximation function. get_num_jac_evals [Ida.Dls] Returns the number of calls made by a direct linear solver to the Jacobian approximation function. get_num_jac_evals [Kinsol.Dls] Returns the number of calls made by a direct linear solver to the Jacobian approximation function. get_num_jac_evals [Cvode.Dls] Returns the number of calls made by a direct linear solver to the Jacobian approximation function. get_num_jtimes_evals [Idas.Adjoint.Spils] Returns the cumulative number of calls to the Jacobian-vector function. get_num_jtimes_evals [Cvodes.Adjoint.Spils] Returns the cumulative number of calls to the Jacobian-vector function. get_num_jtimes_evals [Arkode.Spils] Returns the cumulative number of calls to the Jacobian-vector function. get_num_jtimes_evals [Ida.Spils] Returns the cumulative number of calls to the Jacobian-vector function. get_num_jtimes_evals [Kinsol.Spils] Returns the cumulative number of calls to the Jacobian-vector function. get_num_jtimes_evals [Cvode.Spils] Returns the cumulative number of calls to the Jacobian-vector function. get_num_jtsetup_evals [Idas.Adjoint.Spils] Returns the cumulative number of calls to the Jacobian-vector setup function. get_num_jtsetup_evals [Cvodes.Adjoint.Spils] Returns the cumulative number of calls to the Jacobian-vector setup function. get_num_jtsetup_evals [Arkode.Spils] Returns the cumulative number of calls to the Jacobian-vector setup function. get_num_jtsetup_evals [Ida.Spils] Returns the cumulative number of calls to the Jacobian-vector setup function. get_num_jtsetup_evals [Cvode.Spils] Returns the cumulative number of calls to the Jacobian-vector setup function. get_num_lin_iters [Idas.Adjoint.Spils] Returns the cumulative number of linear iterations. get_num_lin_iters [Cvodes.Adjoint.Spils] Returns the cumulative number of linear iterations. get_num_lin_iters [Arkode.Mass.Spils] Returns the cumulative number of linear iterations. get_num_lin_iters [Arkode.Spils] Returns the cumulative number of linear iterations. get_num_lin_iters [Ida.Spils] Returns the cumulative number of linear iterations. get_num_lin_iters [Kinsol.Spils] Returns the cumulative number of linear iterations. get_num_lin_iters [Cvode.Spils] Returns the cumulative number of linear iterations. get_num_lin_solv_setups [Idas.Adjoint] Returns the number of calls made to the linear solver's setup function. get_num_lin_solv_setups [Idas.Sensitivity] Returns the number of calls made to the linear solver's setup function due to forward sensitivity calculations. get_num_lin_solv_setups [Cvodes.Adjoint] Returns the number of calls made to the linear solver's setup function. get_num_lin_solv_setups [Cvodes.Sensitivity] Returns the number of calls made to the linear solver's setup function due to forward sensitivity calculations. get_num_lin_solv_setups [Arkode] Returns the number of calls made to the linear solver's setup function. get_num_lin_solv_setups [Ida] Returns the number of calls made to the linear solver's setup function. get_num_lin_solv_setups [Cvode] Returns the number of calls made to the linear solver's setup function. get_num_mtimes_evals [Arkode.Mass.Spils] Returns the cumulative number of calls to the mass-matrix-vector product function (Arkode.Mass.Spils.mass_times_vec_fn). get_num_mtsetup_evals [Arkode.Mass.Spils] Returns the cumulative number of calls to the mass-matrix-vector setup function. get_num_mult [Arkode.Mass.Dls] Returns the number of calls made to the mass matrix-times-vector routine. get_num_nonlin_solv_conv_fails [Idas.Adjoint] Returns the number of nonlinear convergence failures that have occurred. get_num_nonlin_solv_conv_fails [Idas.Sensitivity] Returns the number of nonlinear convergence failures that have occurred during sensitivity calculations. get_num_nonlin_solv_conv_fails [Cvodes.Adjoint] Returns the number of nonlinear convergence failures that have occurred. get_num_nonlin_solv_conv_fails [Cvodes.Sensitivity] Returns the number of nonlinear convergence failures that have occurred during sensitivity calculations. get_num_nonlin_solv_conv_fails [Arkode] Returns the number of nonlinear convergence failures that have occurred. get_num_nonlin_solv_conv_fails [Ida] Returns the number of nonlinear convergence failures that have occurred. get_num_nonlin_solv_conv_fails [Cvode] Returns the number of nonlinear convergence failures that have occurred. get_num_nonlin_solv_iters [Idas.Adjoint] Returns the number of nonlinear (functional or Newton) iterations performed. get_num_nonlin_solv_iters [Idas.Sensitivity] Returns the number of nonlinear iterations performed for sensitivity calculations. get_num_nonlin_solv_iters [Cvodes.Adjoint] Returns the number of nonlinear (functional or Newton) iterations performed. get_num_nonlin_solv_iters [Cvodes.Sensitivity] Returns the number of nonlinear iterations performed for sensitivity calculations. get_num_nonlin_solv_iters [Arkode] Returns the number of nonlinear (functional or Newton) iterations performed. get_num_nonlin_solv_iters [Ida] Returns the number of nonlinear (functional or Newton) iterations performed. get_num_nonlin_solv_iters [Kinsol] Returns the number of nonlinear iterations. get_num_nonlin_solv_iters [Cvode] Returns the number of nonlinear (functional or Newton) iterations performed. get_num_prec_evals [Idas.Adjoint.Spils] Returns the number of calls to the setup function. get_num_prec_evals [Cvodes.Adjoint.Spils] Returns the cumulative number of calls to the setup function with jok=false. get_num_prec_evals [Arkode.Mass.Spils] Returns the cumulative number of calls to the setup function with jok=false. get_num_prec_evals [Arkode.Spils] Returns the cumulative number of calls to the setup function with jok=false. get_num_prec_evals [Ida.Spils] Returns the number of calls to the setup function. get_num_prec_evals [Kinsol.Spils] Returns the cumulative number of calls to the setup function. get_num_prec_evals [Cvode.Spils] Returns the cumulative number of calls to the setup function with jok=false. get_num_prec_solves [Idas.Adjoint.Spils] Returns the cumulative number of calls to the preconditioner solve function. get_num_prec_solves [Cvodes.Adjoint.Spils] Returns the cumulative number of calls to the preconditioner solve function. get_num_prec_solves [Arkode.Mass.Spils] Returns the cumulative number of calls to the preconditioner solve function. get_num_prec_solves [Arkode.Spils] Returns the cumulative number of calls to the preconditioner solve function. get_num_prec_solves [Ida.Spils] Returns the cumulative number of calls to the preconditioner solve function. get_num_prec_solves [Kinsol.Spils] Returns the cumulative number of calls to the preconditioner solve function. get_num_prec_solves [Cvode.Spils] Returns the cumulative number of calls to the preconditioner solve function. get_num_res_evals [Idas.Adjoint.Spils] Returns the number of calls to the residual callback for finite difference Jacobian-vector product approximation. get_num_res_evals [Idas.Adjoint.Dls] Returns the number of calls to the residual callback due to the finite difference Jacobian approximation. get_num_res_evals [Idas.Adjoint] Returns the number of calls to the backward residual function. get_num_res_evals [Idas.Sensitivity] Returns the number of calls to the sensitivity residual function. get_num_res_evals [Ida.Spils] Returns the number of calls to the residual callback for finite difference Jacobian-vector product approximation. get_num_res_evals [Ida.Dls] Returns the number of calls to the residual callback due to the finite difference Jacobian approximation. get_num_res_evals [Ida] Returns the number of calls to the residual function. get_num_res_evals_sens [Idas.Sensitivity] Returns the number of calls to the residual function due to the internal finite difference approximation of the sensitivity residual. get_num_rhs_evals [Idas.Adjoint.Quadrature] Returns the number of calls to the backward quadrature right-hand side function. get_num_rhs_evals [Idas.Sensitivity.Quadrature] Returns the number of calls to the quadrature right-hand side function. get_num_rhs_evals [Idas.Quadrature] Returns the number of calls to the quadrature function. get_num_rhs_evals [Cvodes.Adjoint.Quadrature] Returns the number of calls to the backward quadrature right-hand side function. get_num_rhs_evals [Cvodes.Adjoint.Spils.Banded] Returns the number of calls to the right-hand side callback for the difference banded Jacobian approximation. get_num_rhs_evals [Cvodes.Adjoint.Spils] Returns the number of calls to the right-hand side callback for finite difference Jacobian-vector product approximation. get_num_rhs_evals [Cvodes.Adjoint.Dls] Returns the number of calls to the right-hand side callback due to the finite difference Jacobian approximation. get_num_rhs_evals [Cvodes.Adjoint.Diag] Returns the number of calls made to the right-hand side function due to finite difference Jacobian approximation in the Diagonal linear solver. get_num_rhs_evals [Cvodes.Adjoint] Returns the number of calls to the backward right-hand side function. get_num_rhs_evals [Cvodes.Sensitivity.Quadrature] Returns the number of calls to the quadrature right-hand side function. get_num_rhs_evals [Cvodes.Sensitivity] Returns the number of calls to the sensitivity function. get_num_rhs_evals [Cvodes.Quadrature] Returns the number of calls to the quadrature function. get_num_rhs_evals [Arkode.Spils.Banded] Returns the number of calls to the right-hand side callback for the difference banded Jacobian approximation. get_num_rhs_evals [Arkode.Spils] Returns the number of calls to the right-hand side callback for finite difference Jacobian-vector product approximation. get_num_rhs_evals [Arkode.Dls] Returns the number of calls to the right-hand side callback due to the finite difference Jacobian approximation. get_num_rhs_evals [Arkode] Returns the number of calls to the right-hand side functions. get_num_rhs_evals [Cvode.Spils.Banded] Returns the number of calls to the right-hand side callback for the difference banded Jacobian approximation. get_num_rhs_evals [Cvode.Spils] Returns the number of calls to the right-hand side callback for finite difference Jacobian-vector product approximation. get_num_rhs_evals [Cvode.Dls] Returns the number of calls to the right-hand side callback due to the finite difference Jacobian approximation. get_num_rhs_evals [Cvode.Diag] Returns the number of calls made to the right-hand side function due to finite difference Jacobian approximation in the Diagonal linear solver. get_num_rhs_evals [Cvode] Returns the number of calls to the right-hand side function. get_num_rhs_evals_sens [Cvodes.Sensitivity] Returns the number of calls to the right-hand side function due to the internal finite difference approximation of the sensitivity equations. get_num_roots [Arkode] Returns the number of root functions. get_num_roots [Ida] Returns the number of root functions. get_num_roots [Cvode] Returns the number of root functions. get_num_setups [Arkode.Mass.Dls] Returns the number of calls made to the mass matrix solver setup routine. get_num_solves [Arkode.Mass.Dls] Returns the number of calls made to the mass matrix solver solve routine. get_num_stab_lim_order_reds [Cvodes.Adjoint] Returns the number of order reductions dictated by the BDF stability limit detection algorithm. get_num_stab_lim_order_reds [Cvode] Returns the number of order reductions dictated by the BDF stability limit detection algorithm. get_num_step_attempts [Arkode] Returns the cumulative number of steps attempted by the solver. get_num_steps [Idas.Adjoint] Returns the cumulative number of internal steps taken by the solver. get_num_steps [Cvodes.Adjoint] Returns the cumulative number of internal steps taken by the solver. get_num_steps [Arkode] Returns the cumulative number of internal steps taken by the solver. get_num_steps [Ida] Returns the cumulative number of internal solver steps. get_num_steps [Cvode] Returns the cumulative number of internal steps taken by the solver. get_num_stgr_nonlin_solv_conv_fails [Cvodes.Sensitivity] Returns the number of nonlinear convergence failures that have occurred for each sensitivity equation separately in the Staggered1 case. get_num_stgr_nonlin_solv_iters [Cvodes.Sensitivity] Returns the number of nonlinear (functional or Newton) iterations performed for each sensitivity equation separately in the Staggered1 case. get_ops [Sundials_Matrix] Return a record of matrix operations. get_root_info [Arkode] Fills an array showing which functions were found to have a root. get_root_info [Ida] Fills an array showing which functions were found to have a root. get_root_info [Cvode] Fills an array showing which functions were found to have a root. get_row [Sundials_Matrix.Sparse] get_row a j returns the data index of row j. get_rowval [Sundials_Matrix.Sparse] r = get_rowval a idx returns the row r at the idxth position. get_stats [Idas.Adjoint.Quadrature] Returns quadrature-related statistics. get_stats [Idas.Sensitivity.Quadrature] Returns quadrature-related statistics. get_stats [Idas.Sensitivity] Returns the sensitivity-related statistics as a group. get_stats [Idas.Quadrature] Returns quadrature-related statistics. get_stats [Cvodes.Adjoint.Quadrature] Returns quadrature-related statistics. get_stats [Cvodes.Sensitivity.Quadrature] Returns quadrature-related statistics. get_stats [Cvodes.Sensitivity] Returns the sensitivity-related statistics as a group. get_stats [Cvodes.Quadrature] Returns quadrature-related statistics. get_step_length [Kinsol] Returns the scaled Euclidiean l2 norm of the step used during the previous iteration. get_tol_scale_factor [Idas.Adjoint] Returns a suggested factor by which the user's tolerances should be scaled when too much accuracy has been requested for some internal step. get_tol_scale_factor [Cvodes.Adjoint] Returns a suggested factor by which the user's tolerances should be scaled when too much accuracy has been requested for some internal step. get_tol_scale_factor [Arkode] Returns a suggested factor by which the user's tolerances should be scaled when too much accuracy has been requested for some internal step. get_tol_scale_factor [Ida] Returns a suggested factor by which the user's tolerances should be scaled when too much accuracy has been requested for some internal step. get_tol_scale_factor [Cvode] Returns a suggested factor by which the user's tolerances should be scaled when too much accuracy has been requested for some internal step. get_u_uscale [Kinsol.Alternate] Returns the internal u and uscale values. get_work_space [Idas_bbd] Returns the sizes of the real and integer workspaces used by the BBD preconditioner. get_work_space [Ida_bbd] Returns the sizes of the real and integer workspaces used by the BBD preconditioner. get_work_space [Cvodes_bbd] Returns the sizes of the real and integer workspaces used by the BBD preconditioner. get_work_space [Cvode_bbd] Returns the sizes of the real and integer workspaces used by the BBD preconditioner. get_work_space [Arkode_bbd] Returns the sizes of the real and integer workspaces used by the BBD preconditioner. get_work_space [Kinsol_bbd] Returns the sizes of the real and integer workspaces used by the BBD preconditioner. get_work_space [Idas.Adjoint.Spils] Returns the sizes of the real and integer workspaces used by the linear solver. get_work_space [Idas.Adjoint.Dls] Returns the sizes of the real and integer workspaces used by a direct linear solver. get_work_space [Idas.Adjoint] Returns the real and integer workspace sizes. get_work_space [Cvodes.Adjoint.Spils.Banded] Returns the sizes of the real and integer workspaces used by the banded preconditioner module. get_work_space [Cvodes.Adjoint.Spils] Returns the sizes of the real and integer workspaces used by the spils linear solver. get_work_space [Cvodes.Adjoint.Dls] Returns the sizes of the real and integer workspaces used by a direct linear solver. get_work_space [Cvodes.Adjoint.Diag] Returns the sizes of the real and integer workspaces used by the Diagonal linear solver. get_work_space [Cvodes.Adjoint] Returns the real and integer workspace sizes. get_work_space [Arkode.Mass.Spils] Returns the sizes of the real and integer workspaces used by the spils linear solver. get_work_space [Arkode.Mass.Dls] Returns the sizes of the real and integer workspaces used by a direct linear mass matrix solver. get_work_space [Arkode.Spils.Banded] Returns the sizes of the real and integer workspaces used by the banded preconditioner module. get_work_space [Arkode.Spils] Returns the sizes of the real and integer workspaces used by the spils linear solver. get_work_space [Arkode.Dls] Returns the sizes of the real and integer workspaces used by a direct linear solver. get_work_space [Arkode] Returns the real and integer workspace sizes. get_work_space [Ida.Spils] Returns the sizes of the real and integer workspaces used by the spils linear solver. get_work_space [Ida.Dls] Returns the sizes of the real and integer workspaces used by a direct linear solver. get_work_space [Ida] Returns the sizes of the real and integer workspaces. get_work_space [Kinsol.Spils] Returns the sizes of the real and integer workspaces used by the spils linear solver. get_work_space [Kinsol.Dls] Returns the sizes of the real and integer workspaces used by a direct linear solver. get_work_space [Kinsol] Returns the sizes of the real and integer workspaces. get_work_space [Cvode.Spils.Banded] Returns the sizes of the real and integer workspaces used by the banded preconditioner module. get_work_space [Cvode.Spils] Returns the sizes of the real and integer workspaces used by the spils linear solver. get_work_space [Cvode.Dls] Returns the sizes of the real and integer workspaces used by a direct linear solver. get_work_space [Cvode.Diag] Returns the sizes of the real and integer workspaces used by the Diagonal linear solver. get_work_space [Cvode] Returns the real and integer workspace sizes. get_y [Idas.Adjoint] Fills the vector with the interpolated forward solution and its derivative at the given time during a backward simulation. get_y [Cvodes.Adjoint] Fills the vector with the interpolated forward solution at the given time during a backward simulation. getrf [Sundials_Matrix.ArrayDense] getrf a p performs the LU factorization of the square matrix a with partial pivoting according to p. getrs [Sundials_Matrix.ArrayDense] getrs a p b finds the solution of ax = b using an LU factorization found by Sundials_Matrix.ArrayDense.getrf. getrs' [Sundials_Matrix.ArrayDense] Like Sundials_Matrix.ArrayDense.getrs but stores b starting at a given offset. global_length [Nvector_parallel] Returns the number of global elements for a parallel nvector. gt_zero [Sundials.Constraint] The constant 2.0. I init [Idas.Adjoint.Quadrature] This function activates the integration of quadrature equations. init [Idas.Adjoint] Activates the forward-backward problem. init [Idas.Sensitivity.Quadrature] Activate the integration of quadrature sensitivities. init [Idas.Sensitivity] Activates the calculation of forward sensitivities. init [Idas.Quadrature] Activates the integration of quadrature equations. init [Cvodes.Adjoint.Quadrature] This function activates the integration of quadrature equations. init [Cvodes.Adjoint] Activates the forward-backward problem. init [Cvodes.Sensitivity.Quadrature] Activate the integration of quadrature sensitivities. init [Cvodes.Sensitivity] Activates the calculation of forward sensitivities. init [Cvodes.Quadrature] Activates the integration of quadrature equations. init [Arkode] Creates and initializes a session with the solver. init [Ida] Creates and initializes a session with the solver. init [Kinsol] Creates and initializes a session with the Kinsol solver. init [Cvode] Creates and initializes a session with the solver. init [Sundials.RootDirs] init n f returns an array with n elements, with element i set to f i. init [Sundials.Roots] init n f returns an array with n elements, with element i set to f i. init [Sundials_RealArray] init n f returns an array with n elements, with element i set to f i. init_backward [Idas.Adjoint] Creates and initializes a backward session attached to an existing (forward) session. init_backward [Cvodes.Adjoint] Creates and initializes a backward session attached to an existing (forward) session. int_of_root [Sundials.Roots] Returns 0 for NoRoot, 1 for Rising, and -1 for Falling. into_array [Sundials_RealArray] Copies into an existing float array. invalidate [Sundials_Matrix.Sparse] Called internally when the corresponding value in the underlying library ceases to exist. invalidate [Sundials_Matrix.Band] Called internally when the corresponding value in the underlying library ceases to exist. invalidate [Sundials_Matrix.Dense] Called internally when the corresponding value in the underlying library ceases to exist. is_csc [Sundials_Matrix.Sparse] Returns true iff the matrix format is CSC. iter [Sundials.Roots] iter f r successively applies f to each element in r. iter [Sundials_RealArray] iter f a successively applies f to the elements of a. iteri [Sundials.Roots] iteri f r successively applies f to the indexes and elements of r. iteri [Sundials_RealArray] iteri f a successively applies f to the indexes and values of a. K klu [Sundials_LinearSolver.Direct] Creates a direct linear solver on sparse matrices using KLU. klu_enabled [Sundials_Config] Indicates whether the KLU sparse linear solver is available. L lapack_band [Sundials_LinearSolver.Direct] Creates a direct linear solver on banded matrices using LAPACK. lapack_dense [Sundials_LinearSolver.Direct] Creates a direct linear solver on dense matrices using LAPACK. lapack_enabled [Sundials_Config] Indicates whether the interface was compiled with BLAS/LAPACK support. length [Sundials.RootDirs] Returns the length of an array length [Sundials.Roots] Returns the length of an array. length [Sundials_RealArray] Returns the length of an array. leq_zero [Sundials.Constraint] The constant -1.0. local_array [Nvector_parallel] local_array nv returns the local array a underlying the parallel nvector nv. local_length [Nvector_parallel] Returns the number of local elements for a parallel nvector. lt_zero [Sundials.Constraint] The constant -2.0. M make [Nvector_pthreads] make nthreads n iv creates a new Pthreads nvector with nthreads threads and n elements inialized to iv. make [Nvector_openmp] make nthreads n iv creates a new OpenMP nvector with nthreads threads and n elements inialized to iv. make [Nvector_parallel] make nl ng c iv creates a new parallel nvector with nl local elements, that is part of a global array with ng elements. make [Nvector_array.ARRAY_NVECTOR] make n x creates an nvector containing an array of n elements, each of which is equal to x. make [Nvector_serial] make n iv creates a new serial nvector with n elements, each initialized to iv. make [Sundials_LinearSolver.Iterative.Custom] Create an iterative linear solver given a set of operations and an internal state. make [Sundials_LinearSolver.Direct.Custom] Create a direct linear solver given a set of operations and an internal state. make [Sundials_LinearSolver.Direct.Superlumt] Creates a direct linear solver on sparse matrices using SuperLUMT. make [Sundials_LinearSolver.Direct.Klu] Creates a direct linear solver on sparse matrices using KLU. make [Sundials_Matrix.ArrayBand] make (smu, mu, ml) n v returns an n by n band matrix with storage upper bandwidth smu, upper bandwidth sm, lower half-bandwidth ml, and all elements initialized to v. make [Sundials_Matrix.ArrayDense] make m n x returns an m by n array dense matrix with elements set to x. make [Sundials_Matrix.Sparse] make fmt m n nnz returns an m by n sparse matrix in the specified format with a potential for nnz non-zero elements. make [Sundials_Matrix.Band] Returns a band matrix with the given Sundials_Matrix.Band.dimensions and all elements initialized to the given value. make [Sundials_Matrix.Dense] make m n x returns an m by n dense matrix with elements set to x. make [Sundials.RootDirs] make n x returns an array with n elements each set to x. make [Sundials.Roots] make n x returns an array with n elements each set to x. make [Sundials_LintArray] make n x returns an array with n elements each set to v. make [Sundials_RealArray2] make nr nc v returns an array with nr rows and nc columns, and with elements set to v. make [Sundials_RealArray] make n x returns an array with n elements each set to x. make_data [Sundials_RealArray2] make m n returns an uninitialized m by n array. make_wrap [Nvector_custom] make_wrap ops takes a set of operations on the data type 'd and yields a function for lifting values of type 'd into 'd nvectors which can be passed to a solver. map [Sundials_RealArray] map f a replaces each element a.{i} with f a.{i}. mapi [Sundials_RealArray] map f a replaces each element a.{i} with f i a.{i}. matvec [Sundials_Matrix.ArrayBand] The call matvec a x y computes the matrix-vector product $y = Ax$. matvec [Sundials_Matrix.ArrayDense] The call matvec a x y computes the matrix-vector product $y = Ax$. matvec [Sundials_Matrix.Sparse] The call matvec a x y computes the matrix-vector product $y = Ax$. matvec [Sundials_Matrix.Band] The call matvec a x y computes the matrix-vector product $y = Ax$. matvec [Sundials_Matrix.Dense] The call matvec a x y computes the matrix-vector product $y = Ax$. matvec [Sundials_Matrix] The call matvec a x y computes the matrix-vector product $y = Ax$. modified_gs [Sundials_LinearSolver.Iterative.Algorithms] Performs a modified Gram-Schmidt orthogonalization. mpi_enabled [Sundials_Config] Indicates whether the parallel nvectors and linear solvers are available. N n_vabs [Nvector.NVECTOR_OPS] n_vabs x z calculates z = abs(x). n_vaddconst [Nvector.NVECTOR_OPS] n_vaddconst x b z calculates z = x + b. n_vclone [Nvector.NVECTOR_OPS] Create a new, distinct vector from an existing one. n_vcompare [Nvector.NVECTOR_OPS] n_vcompare c x z calculates z(i) = if abs x(i) >= c then 1 else 0. n_vconst [Nvector.NVECTOR_OPS] n_vconst c z sets all of z to c. n_vconstrmask [Nvector.NVECTOR_OPS] n_vconstrmask c x m calculates m(i) = Pi x(i) returning the conjunction. n_vdiv [Nvector.NVECTOR_OPS] n_vdiv x y z calculates z = x / y (pointwise). n_vdotprod [Nvector.NVECTOR_OPS] n_vdotprod x y returns the dot product of x and y. n_vinv [Nvector.NVECTOR_OPS] n_vinv x z calculates z = 1/x (pointwise). n_vinvtest [Nvector.NVECTOR_OPS] n_vinvtest x z calculates z(i) = 1 / x(i) with prior testing for zero values. n_vl1norm [Nvector.NVECTOR_OPS] n_vl1norm x returns the l1 norm of x. n_vlinearsum [Nvector.NVECTOR_OPS] n_vlinearsum a x b y z calculates z = a*x + b*y. n_vmaxnorm [Nvector.NVECTOR_OPS] n_vmaxnorm x returns the maximum absolute value in x. n_vmin [Nvector.NVECTOR_OPS] n_vmin x returns the smallest element in x. n_vminquotient [Nvector.NVECTOR_OPS] n_vminquotient num denom returns the minimum of num(i) / denom(i). n_vprod [Nvector.NVECTOR_OPS] n_vprod x y z calculates z = x * y (pointwise). n_vscale [Nvector.NVECTOR_OPS] n_vscale c x z calculates z = c *. x. n_vspace [Nvector.NVECTOR_OPS] lrw, liw = n_vspace c returns the number of realtype words lrw and integer words liw required to store c. n_vwl2norm [Nvector.NVECTOR_OPS] n_vwl2norm x w returns the weighted (w) Euclidean l2 norm of x. n_vwrmsnorm [Nvector.NVECTOR_OPS] n_vwrmsnorm x w returns the weighted root-mean-square norm of x with weight vector w. n_vwrmsnormmask [Nvector.NVECTOR_OPS] n_vmaxnormmask x w id returns the weighted root-mean-square norm of x using only elements where the corresponding id is non-zero. no_roots [Arkode] A convenience value for signalling that there are no roots to monitor. no_roots [Ida] A convenience value for signalling that there are no roots to monitor. no_roots [Cvode] A convenience value for signalling that there are no roots to monitor. no_sens_params [Cvodes.Sensitivity] Empty pvals, plist, and pbar fields. num_threads [Nvector_pthreads] Returns the number of threads used within a Pthreads nvector. num_threads [Nvector_openmp] Returns the number of threads used within an OpenMP nvector. nvecopenmp_enabled [Sundials_Config] Indicates whether openmp-based nvectors are available. nvecpthreads_enabled [Sundials_Config] Indicates whether pthreads-based nvectors are available. O of_array [Sundials.RootDirs] Creates a new value from the contents of an array. of_array [Sundials.Roots] Creates a new value from the contents of an array. of_array [Sundials_RealArray] Creates an array by copying the contents of a float array. of_float [Ida.VarId] Map floating-point constants to id values. of_float [Sundials.Constraint] Map floating-point constants to constraint values. of_list [Sundials.RootDirs] Creates an array by copying the contents of a d list. of_list [Sundials.Roots] Creates an array by copying the contents of a r list. of_list [Sundials_RealArray] Creates an array by copying the contents of a float list. openfile [Sundials_Logfile] Opens the named file. ops [Sundials_Matrix.ArrayBand] Operations on array-based band matrices. ops [Sundials_Matrix.ArrayDense] Operations on array-based dense matrices. ops [Sundials_Matrix.Sparse] Operations on sparse matrices. ops [Sundials_Matrix.Band] ops [Sundials_Matrix.Dense] Operations on dense matrices. ormqr [Sundials_Matrix.ArrayDense] ormqr q beta v w work computes the product w = qv . P pcg [Sundials_LinearSolver.Iterative] Krylov iterative solver using the preconditioned conjugate gradient (PCG) method. potrf [Sundials_Matrix.ArrayDense] Performs Cholesky factorization of a real symmetric positive matrix. potrs [Sundials_Matrix.ArrayDense] potrs a b finds the solution of ax = b using the Cholesky factorization found by Sundials_Matrix.ArrayDense.potrf. pp [Nvector_pthreads] Pretty-print a Pthreads nvector using the Format module. pp [Nvector_openmp] Pretty-print an OpenMP nvector using the Format module. pp [Nvector_parallel] Pretty-print the local portion of a parallel nvector using the Format module. pp [Nvector_serial] Pretty-print a serial nvector using the Format module. pp [Sundials_Matrix.ArrayBand] Pretty-print a band matrix using the Format module. pp [Sundials_Matrix.ArrayDense] Pretty-print an array dense matrix using the Format module. pp [Sundials_Matrix.Sparse] Pretty-print a sparse matrix using the Format module. pp [Sundials_Matrix.Band] Pretty-print a band matrix using the Format module. pp [Sundials_Matrix.Dense] Pretty-print a dense matrix using the Format module. pp [Sundials.RootDirs] Pretty-print a root direction array using the Format module. pp [Sundials.Roots] Pretty-print a root array using the Format module. pp [Sundials_LintArray] Pretty-print an array using the Format module. pp [Sundials_RealArray2] Pretty-print an array using the Format module. pp [Sundials_RealArray] Pretty-print an array using the Format module. ppi [Sundials_Matrix.ArrayBand] Pretty-print an array band matrix using the Format module. ppi [Sundials_Matrix.Sparse] Pretty-print a sparse matrix using the Format module. ppi [Sundials_Matrix.Band] Pretty-print a band matrix using the Format module. ppi [Sundials_Matrix.Dense] Pretty-print a dense matrix using the Format module. ppi [Sundials.RootDirs] Pretty-print a root direction array using the Format module. ppi [Sundials.Roots] Pretty-print a root array using the Format module. ppi [Sundials_LintArray] Pretty-print an array using the Format module. ppi [Sundials_RealArray2] Pretty-print an array using the Format module. ppi [Sundials_RealArray] Pretty-print an array using the Format module. prec_both [Cvodes_bbd] Preconditioning from both sides using the Parallel Band-Block-Diagonal module. prec_both [Cvode_bbd] Preconditioning from both sides using the Parallel Band-Block-Diagonal module. prec_both [Arkode_bbd] Preconditioning from both sides using the Parallel Band-Block-Diagonal module. prec_both [Cvodes.Adjoint.Spils.Banded] Like Cvodes.Adjoint.Spils.Banded.prec_left but preconditions from both sides. prec_both [Cvodes.Adjoint.Spils] Left and right preconditioning with sensitivities. prec_both [Arkode.Mass.Spils] Left and right preconditioning. prec_both [Arkode.Spils.Banded] Like Arkode.Spils.Banded.prec_left but preconditions from both sides. prec_both [Arkode.Spils] Left and right preconditioning. prec_both [Cvode.Spils.Banded] Like Cvode.Spils.Banded.prec_left but preconditions from both sides. prec_both [Cvode.Spils] Left and right preconditioning. prec_both_with_sens [Cvodes.Adjoint.Spils] Left and right preconditioning without sensitivities. prec_left [Idas_bbd] Left preconditioning using the Parallel Band-Block-Diagonal module. prec_left [Ida_bbd] Left preconditioning using the Parallel Band-Block-Diagonal module. prec_left [Cvodes_bbd] Left preconditioning using the Parallel Band-Block-Diagonal module. prec_left [Cvode_bbd] Left preconditioning using the Parallel Band-Block-Diagonal module. prec_left [Arkode_bbd] Left preconditioning using the Parallel Band-Block-Diagonal module. prec_left [Idas.Adjoint.Spils] Left preconditioning without forward sensitivities. prec_left [Cvodes.Adjoint.Spils.Banded] A band matrix Cvodes.Adjoint.Spils.preconditioner based on difference quotients. prec_left [Cvodes.Adjoint.Spils] Left preconditioning without forward sensitivities. prec_left [Arkode.Mass.Spils] Left preconditioning. prec_left [Arkode.Spils.Banded] A band matrix Arkode.Spils.preconditioner based on difference quotients. prec_left [Arkode.Spils] Left preconditioning. prec_left [Ida.Spils] Left preconditioning. prec_left [Cvode.Spils.Banded] A band matrix Cvode.Spils.preconditioner based on difference quotients. prec_left [Cvode.Spils] Left preconditioning. prec_left_with_sens [Idas.Adjoint.Spils] Left preconditioning with forward sensitivities. prec_left_with_sens [Cvodes.Adjoint.Spils] Left preconditioning with forward sensitiviites. prec_none [Idas.Adjoint.Spils] No preconditioning. prec_none [Cvodes.Adjoint.Spils] No preconditioning. prec_none [Arkode.Mass.Spils] No preconditioning. prec_none [Arkode.Spils] No preconditioning. prec_none [Ida.Spils] No preconditioning. prec_none [Kinsol.Spils] No preconditioning. prec_none [Cvode.Spils] No preconditioning. prec_right [Cvodes_bbd] Right preconditioning using the Parallel Band-Block-Diagonal module. prec_right [Cvode_bbd] Right preconditioning using the Parallel Band-Block-Diagonal module. prec_right [Arkode_bbd] Right preconditioning using the Parallel Band-Block-Diagonal module. prec_right [Kinsol_bbd] Right preconditioning using the Parallel Band-Block-Diagonal module. prec_right [Cvodes.Adjoint.Spils.Banded] Like Cvodes.Adjoint.Spils.Banded.prec_left but preconditions from the right. prec_right [Cvodes.Adjoint.Spils] Right preconditioning with sensitivities. prec_right [Arkode.Mass.Spils] Right preconditioning. prec_right [Arkode.Spils.Banded] Like Arkode.Spils.Banded.prec_left but preconditions from the right. prec_right [Arkode.Spils] Right preconditioning. prec_right [Kinsol.Spils] Right preconditioning. prec_right [Cvode.Spils.Banded] Like Cvode.Spils.Banded.prec_left but preconditions from the right. prec_right [Cvode.Spils] Right preconditioning. prec_right_with_sens [Cvodes.Adjoint.Spils] Right preconditioning without sensitivities. print_band [Sundials_Matrix] Prints a band matrix to the given log file. print_dense [Sundials_Matrix] Prints a dense matrix to the given log file. print_integrator_stats [Idas.Adjoint] Prints the integrator statistics on the given channel. print_integrator_stats [Cvodes.Adjoint] Prints the integrator statistics on the given channel. print_integrator_stats [Arkode] Prints the integrator statistics on the given channel. print_integrator_stats [Ida] Prints the integrator statistics on the given channel. print_integrator_stats [Cvode] Prints the integrator statistics on the given channel. print_sparse [Sundials_Matrix] Prints a sparse matrix to the given log file. Q qr_fact [Sundials_LinearSolver.Iterative.Algorithms] Performs a QR factorization of a Hessenberg matrix. qr_sol [Sundials_LinearSolver.Iterative.Algorithms] Solve the linear least squares problem. R reinit [Idas_bbd] Reinitializes some BBD preconditioner parameters. reinit [Ida_bbd] Reinitializes some BBD preconditioner parameters. reinit [Cvodes_bbd] Reinitializes some BBD preconditioner parameters. reinit [Cvode_bbd] Reinitializes some BBD preconditioner parameters. reinit [Arkode_bbd] Reinitializes some BBD preconditioner parameters. reinit [Idas.Adjoint.Quadrature] This function reinitializes the integration of quadrature equations during the backward phase. reinit [Idas.Adjoint] Reinitializes the backward problem with new parameters and state values. reinit [Idas.Sensitivity.Quadrature] Reinitializes the quadrature sensitivity integration. reinit [Idas.Sensitivity] Reinitializes the forward sensitivity computation. reinit [Idas.Quadrature] Reinitializes the integration of quadrature equations. reinit [Cvodes.Adjoint.Quadrature] This function reinitializes the integration of quadrature equations during the backward phase. reinit [Cvodes.Adjoint] Reinitializes the backward problem with new parameters and state values. reinit [Cvodes.Sensitivity.Quadrature] Reinitializes the quadrature sensitivity integration. reinit [Cvodes.Sensitivity] Reinitializes the forward sensitivity computation. reinit [Cvodes.Quadrature] Reinitializes the integration of quadrature equations. reinit [Arkode] Reinitializes the solver with new parameters and state values. reinit [Ida] Reinitializes the solver with new parameters and state values. reinit [Cvode] Reinitializes the solver with new parameters and state values. reinit [Sundials_LinearSolver.Direct.Klu] Reinitializes memory and flags for a new factorization (symbolic and numeric) at the next solver setup call. reset [Sundials.Roots] Resets all elements to NoRoot. resize [Arkode] Change the number of equations and unknowns between integrator steps. resize [Sundials_Matrix.Sparse] Reallocates the underlying arrays to the given number of non-zero elements, or otherwise to the current number of non-zero elements . rising [Sundials.Roots] Returns true only if the specified element is Rising. S scale [Sundials_Matrix.ArrayBand] scale c a multiplies each element of the band matrix a by c. scale [Sundials_Matrix.ArrayDense] Multiplies each element by a constant. scale_add [Sundials_Matrix.ArrayBand] scale_add c a b calculates $A = cA + B$. scale_add [Sundials_Matrix.ArrayDense] scale_add c A B calculates $A = cA + B$. scale_add [Sundials_Matrix.Sparse] scale_add c A B calculates $A = cA + B$. scale_add [Sundials_Matrix.Band] scale_add c A B calculates $A = cA + B$. scale_add [Sundials_Matrix.Dense] scale_add c A B calculates $A = cA + B$. scale_add [Sundials_Matrix] scale_add c A B calculates $A = cA + B$. scale_addi [Sundials_Matrix.ArrayBand] scale_addi ml c A calculates $A = cA + I$. scale_addi [Sundials_Matrix.ArrayDense] scale_addi c A calculates $A = cA + I$. scale_addi [Sundials_Matrix.Sparse] scale_addi c A calculates $A = cA + I$. scale_addi [Sundials_Matrix.Band] scale_addi c A calculates $A = cA + I$. scale_addi [Sundials_Matrix.Dense] scale_addi c A calculates $A = cA + I$. scale_addi [Sundials_Matrix] scale_addi c A calculates $A = cA + I$. set [Sundials_Matrix.ArrayBand] set a i j v sets the value at row i and column j of a to v. set [Sundials_Matrix.ArrayDense] set a i j v sets the value at row i and column j of a to v. set [Sundials_Matrix.Sparse] set a idx i v sets the idxth row/column to i and its value to v. set [Sundials_Matrix.Band] set a i j v sets the value at row i and column j of a to v. set [Sundials_Matrix.Dense] set a i j v sets the value at row i and column j of a to v. set [Sundials.RootDirs] set r i v sets the ith element of r to v. set [Sundials.Roots] set r i v sets the ith element of r to v. set [Sundials_RealArray2] set a i j v sets the value at row i and column j of a to v. set_adaptivity_method [Arkode] Specifies the method and associated parameters used for time step adaptivity. set_all_root_directions [Arkode] Like Arkode.set_root_direction but specifies a single direction for all root functions. set_all_root_directions [Ida] Like Ida.set_root_direction but specifies a single direction for all root functions. set_all_root_directions [Cvode] Like Cvode.set_root_direction but specifies a single direction for all root functions. set_ark_table_num [Arkode] Use specific built-in Butcher tables for an ImEx system. set_ark_tables [Arkode] Specifies a customized Butcher table pair for the additive RK method. set_cfl_fraction [Arkode] Specifies the fraction of the estimated explicitly stable step to use. set_col [Sundials_Matrix.Sparse] set_col a j idx sets the data index of column j to idx. set_colval [Sundials_Matrix.Sparse] set_colval a idx i sets the idxth column to i. set_constraints [Ida] Specifies a vector defining inequality constraints for each component of the solution vector u. set_constraints [Kinsol] Specifies a vector defining inequality constraints for each component of the solution vector u. set_data [Sundials_Matrix.Sparse] set_data a idx v sets the value of the idxth row v. set_defaults [Arkode] Resets all optional input parameters to their default values. set_delta_gamma_max [Arkode] Specifies a scaled step size ratio tolerance beyond which the linear solver setup routine will be signalled. set_dense_order [Arkode] Specifies the order of accuracy for the polynomial interpolant used for dense output. set_diagnostics [Arkode] Write step adaptivity and solver diagnostics to the given file. set_dq_method [Idas.Sensitivity] Sets the difference quotient strategy when sensitivity equations are computed internally by the solver rather than via callback. set_dq_method [Cvodes.Sensitivity] Sets the difference quotient strategy when sensitivity equations are computed internally by the solver rather than via callback. set_eps_lin [Idas.Adjoint.Spils] Sets the factor by which the Krylov linear solver's convergence test constant is reduced from the Newton iteration test constant. set_eps_lin [Cvodes.Adjoint.Spils] Sets the factor by which the Krylov linear solver's convergence test constant is reduced from the Newton iteration test constant. set_eps_lin [Arkode.Mass.Spils] Sets the factor by which the Krylov linear solver's convergence test constant is reduced from the Newton iteration test constant. set_eps_lin [Arkode.Spils] Sets the factor by which the Krylov linear solver's convergence test constant is reduced from the Newton iteration test constant. set_eps_lin [Ida.Spils] Sets the factor by which the Krylov linear solver's convergence test constant is reduced from the Newton iteration test constant. set_eps_lin [Cvode.Spils] Sets the factor by which the Krylov linear solver's convergence test constant is reduced from the Newton iteration test constant. set_erk_table [Arkode] Specifies a customized Butcher table pair for the explicit portion of the system. set_erk_table_num [Arkode] Use specific built-in Butcher tables for an explicit integration of the problem. set_err_con [Idas.Sensitivity] Sets whether sensitivity variables are used in the error control mechanism. set_err_con [Cvodes.Sensitivity] Sets whether sensitivity variables are used in the error control mechanism. set_err_handler_fn [Arkode] Specifies a custom function for handling error messages. set_err_handler_fn [Ida] Specifies a custom function for handling error messages. set_err_handler_fn [Kinsol] Specifies a custom function for handling error messages. set_err_handler_fn [Cvode] Specifies a custom function for handling error messages. set_error_bias [Arkode] Specifies the bias to apply to the error estimates within accuracy-based adaptivity strategies. set_error_file [Arkode] Configure the default error handler to write messages to a file. set_error_file [Ida] Configure the default error handler to write messages to a file. set_error_file [Kinsol] Configure the default error handler to write messages to a file. set_error_file [Cvode] Configure the default error handler to write messages to a file. set_eta_choice [Kinsol] Specifies the method for computing the value of the eta coefficient used in the calculation of the linear solver convergence tolerance. set_explicit [Arkode] Disables the implicit portion of a problem. set_falling [Sundials.Roots] set_falling r i sets the ith element of r to Falling. set_fixed_point [Arkode] Solve the implicit portion of the problem using the accelerated fixed-point solver instead of the modified Newton iteration. set_fixed_step [Arkode] Disables time step adaptivity and fix the step size for all internal steps. set_fixed_step_bounds [Arkode] Specifies the step growth interval in which the step size will remain unchanged. set_func_norm_tol [Kinsol] Specifies the stopping tolerance on the scaled maximum norm. set_gs_type [Sundials_LinearSolver.Iterative] Sets the Gram-Schmidt orthogonalization to use. set_id [Idas.Adjoint] Class components of the state vector as either algebraic or differential. set_id [Ida] Class components of the state vector as either algebraic or differential. set_imex [Arkode] Enables both the implicit and explicit portions of a problem. set_implicit [Arkode] Disables the explicit portion of a problem. set_info_file [Kinsol] Write informational (non-error) messages to the given file. set_info_handler_fn [Kinsol] Specifies a custom function for handling informational (non-error) messages. set_init_setup [Kinsol] Specifies that an initial call to the preconditioner setup function should be made (the default). set_init_step [Idas.Adjoint] Specifies the initial step size. set_init_step [Cvodes.Adjoint] Specifies the initial step size. set_init_step [Arkode] Specifies the initial step size. set_init_step [Ida] Specifies the initial step size. set_init_step [Cvode] Specifies the initial step size. set_irk_table [Arkode] Specifies a customized Butcher table pair for the implicit portion of the system. set_irk_table_num [Arkode] Use specific built-in Butcher tables for an implicit integration of the problem. set_jac_times [Idas.Adjoint.Spils] Change the Jacobian-times-vector function. set_jac_times [Cvodes.Adjoint.Spils] Change the Jacobian-times-vector function. set_jac_times [Arkode.Spils] Change the Jacobian-times-vector function. set_jac_times [Ida.Spils] Change the Jacobian-times-vector function. set_jac_times [Kinsol.Spils] Change the Jacobian-times-vector function. set_jac_times [Cvode.Spils] Change the Jacobian-times-vector function. set_line_search_ic [Ida] Enables (true) or disables (false) the linesearch algorithm in the initial condition calculation. set_linear [Arkode] Specifies that the implicit portion of the problem is linear. set_max_backs_ic [Ida] Specifies the maximum number of linesearch backtracks allowed in any Newton iteration, when solving the initial conditions calculation problem. set_max_beta_fails [Kinsol] Specifies the maximum number of beta-condition failures in the line search algorithm. set_max_cfail_growth [Arkode] Specifies the maximum step size growth factor upon a convergence failure on a stage solve within a step. set_max_conv_fails [Arkode] Specifies the maximum number of nonlinear solver convergence failures permitted during one step. set_max_conv_fails [Ida] Specifies the maximum number of nonlinear solver convergence failures permitted during one step. set_max_conv_fails [Cvode] Specifies the maximum number of nonlinear solver convergence failures permitted during one step. set_max_efail_growth [Arkode] Specifies the maximum step size growth factor upon multiple successive accuracy-based error failures in the solver. set_max_err_test_fails [Arkode] Specifies the maximum number of error test failures permitted in attempting one step. set_max_err_test_fails [Ida] Specifies the maximum number of error test failures permitted in attempting one step. set_max_err_test_fails [Cvode] Specifies the maximum number of error test failures permitted in attempting one step. set_max_first_growth [Arkode] Specifies the maximum allowed step size change following the very first integration step. set_max_growth [Arkode] Specifies the maximum growth of the step size between consecutive time steps. set_max_hnil_warns [Arkode] Specifies the maximum number of messages warning that t + h = t on the next internal step. set_max_hnil_warns [Cvode] Specifies the maximum number of messages warning that t + h = t on the next internal step. set_max_newton_step [Kinsol] Specifies the maximum allowable scaled length of the Newton step. set_max_nonlin_iters [Idas.Sensitivity] Specifies the maximum number of nonlinear solver iterations for sensitivity variables permitted per step. set_max_nonlin_iters [Cvodes.Sensitivity] Sets the maximum number of nonlinear solver iterations for sensitivity variables permitted per step. set_max_nonlin_iters [Arkode] Specifies the maximum number of nonlinear solver iterations permitted per RK stage at each step. set_max_nonlin_iters [Ida] Specifies the maximum number of nonlinear solver iterations permitted per step. set_max_nonlin_iters [Cvode] Specifies the maximum number of nonlinear solver iterations permitted per step. set_max_num_iters_ic [Ida] Specifies the maximum number of Newton iterations allowed in any one attempt to calculate initial conditions. set_max_num_jacs_ic [Ida] Specifies the maximum number of approximate Jacobian or preconditioner evaluations allowed when the Newton iteration appears to be slowly converging. set_max_num_steps [Idas.Adjoint] Specifies the maximum number of steps taken in attempting to reach a given output time. set_max_num_steps [Cvodes.Adjoint] Specifies the maximum number of steps taken in attempting to reach a given output time. set_max_num_steps [Arkode] Specifies the maximum number of steps taken in attempting to reach a given output time. set_max_num_steps [Ida] Specifies the maximum number of steps taken in attempting to reach a given output time. set_max_num_steps [Cvode] Specifies the maximum number of steps taken in attempting to reach a given output time. set_max_num_steps_ic [Ida] Specifies the maximum number of steps taken in attempting to reach a given output time in the initial condition calculation. set_max_ord [Idas.Adjoint] Specifies the maximum order of the linear multistep method. set_max_ord [Cvodes.Adjoint] Specifies the maximum order of the linear multistep method. set_max_ord [Ida] Specifies the maximum order of the linear multistep method. set_max_ord [Cvode] Specifies the maximum order of the linear multistep method. set_max_restarts [Sundials_LinearSolver.Iterative] Sets the number of GMRES restarts to allow. set_max_setup_calls [Kinsol] Specifies the maximum number of nonlinear iterations between calls to the preconditioner setup function. set_max_step [Idas.Adjoint] Specifies an upper bound on the magnitude of the step size. set_max_step [Cvodes.Adjoint] Specifies an upper bound on the magnitude of the step size. set_max_step [Arkode] Specifies an upper bound on the magnitude of the step size. set_max_step [Ida] Specifies an upper bound on the magnitude of the step size. set_max_step [Cvode] Specifies an upper bound on the magnitude of the step size. set_max_steps_between_lset [Arkode] Specifies the frequency of calls to the linear solver setup routine. set_max_sub_setup_calls [Kinsol] Specifies the maximum number of nonlinear iterations between checks by the residual monitoring algorithm. set_maxl [Sundials_LinearSolver.Iterative] Updates the number of linear solver iterations to allow. set_min_eps [Kinsol] Specifies that the scaled linear residual tolerance (epsilon) is bounded from below. set_min_step [Cvodes.Adjoint] Specifies a lower bound on the magnitude of the step size. set_min_step [Arkode] Specifies a lower bound on the magnitude of the step size. set_min_step [Cvode] Specifies a lower bound on the magnitude of the step size. set_newton [Arkode] Solve the implicit portion of the problem using the modified Newton solver. set_no_inactive_root_warn [Arkode] Disables issuing a warning if some root function appears to be identically zero at the beginning of the integration. set_no_inactive_root_warn [Ida] Disables issuing a warning if some root function appears to be identically zero at the beginning of the integration. set_no_inactive_root_warn [Cvode] Disables issuing a warning if some root function appears to be identically zero at the beginning of the integration. set_no_init_setup [Kinsol] Specifies that an initial call to the preconditioner setup function should not be made. set_no_min_eps [Kinsol] Specifies that the scaled linear residual tolerance (epsilon) is not bounded from below. set_no_res_mon [Kinsol] Disables the nonlinear residual monitoring scheme that controls Jacobian updating. set_no_sensitivity [Idas.Adjoint] Cancels the storage of sensitivity checkpointing data during forward solution (with Idas.Adjoint.forward_normal or Idas.Adjoint.forward_one_step). set_no_sensitivity [Cvodes.Adjoint] Cancels the storage of sensitivity checkpointing data during forward solution (with Cvodes.Adjoint.forward_normal or Cvodes.Adjoint.forward_one_step). set_nonlin_conv_coef [Arkode] Specifies the safety factor used in the nonlinear convergence test. set_nonlin_conv_coef [Ida] Specifies the safety factor used in the nonlinear convergence test. set_nonlin_conv_coef [Cvode] Specifies the safety factor used in the nonlinear convergence test. set_nonlin_conv_coef_ic [Ida] Specifies the positive constant in the nonlinear convergence test of the initial condition calculation. set_nonlin_crdown [Arkode] Specifies the constant used in estimating the nonlinear solver convergence rate. set_nonlin_rdiv [Arkode] Specifies the nonlinear correction threshold beyond which the iteration will be declared divergent. set_nonlinear [Arkode] Specifies that the implicit portion of the problem is nonlinear. set_noroot [Sundials.Roots] set_noroot r i sets the ith element of r to NoRoot. set_optimal_params [Arkode] Sets all adaptivity and solver parameters to ‘best guess’ values. set_ordering [Sundials_LinearSolver.Direct.Superlumt] Sets the ordering algorithm used to minimize fill-in. set_ordering [Sundials_LinearSolver.Direct.Klu] Sets the ordering algorithm used to minimize fill-in. set_postprocess_step_fn [Arkode] Set a post processing step function. set_prec_type [Sundials_LinearSolver.Iterative] Change the preconditioning direction without modifying callback functions. set_preconditioner [Idas.Adjoint.Spils] Change the preconditioner functions without using forward sensitivities. set_preconditioner [Cvodes.Adjoint.Spils] Change the preconditioner functions without using forward sensitivities. set_preconditioner [Arkode.Mass.Spils] Change the preconditioner functions. set_preconditioner [Arkode.Spils] Change the preconditioner functions. set_preconditioner [Ida.Spils] Change the preconditioner functions. set_preconditioner [Kinsol.Spils] Change the preconditioner functions. set_preconditioner [Cvode.Spils] Change the preconditioner functions. set_preconditioner_with_sens [Idas.Adjoint.Spils] Change the preconditioner functions using forward sensitivities. set_preconditioner_with_sens [Cvodes.Adjoint.Spils] Change the preconditioner functions using forward sensitivities. set_predictor_method [Arkode] Specifies the method for predicting implicit solutions. set_print_level [Kinsol] Sets the level of verbosity of informational messages. set_rel_err_func [Kinsol] Specifies the relative error in computing $F(u)$, which is used in the difference quotient approximation of the Jacobian-vector product. set_res_mon [Kinsol] Enables the nonlinear residual monitoring scheme that controls Jacobian updating. set_res_mon_const_value [Kinsol] Specifies the constant value of omega when using residual monitoring. set_res_mon_params [Kinsol] Specifies the minimum and maximum values in the formula for omega. set_res_tolerance [Arkode] Sets the residual tolerance. set_rising [Sundials.Roots] set_rising r i sets the ith element of r to Rising. set_root_direction [Arkode] set_root_direction s dir specifies the direction of zero-crossings to be located and returned. set_root_direction [Ida] set_root_direction s dir specifies the direction of zero-crossings to be located and returned. set_root_direction [Cvode] set_root_direction s dir specifies the direction of zero-crossings to be located and returned. set_row [Sundials_Matrix.Sparse] set_row a j idx sets the data index of row j to idx. set_rowval [Sundials_Matrix.Sparse] set_rowval a idx i sets the idxth row to i. set_safety_factor [Arkode] Specifies the safety factor to be applied to the accuracy-based estimated step. set_scaled_step_tol [Kinsol] Specifies the stopping tolerance on the minimum scaled step length, which must be greater than zero. set_sfdotjp [Kinsol.Alternate] Sets the internal sfdotJp value. set_sjpnorm [Kinsol.Alternate] Sets the internal sJpnorm value. set_small_num_efails [Arkode] Specifies the threshold for “multiple” successive error failures before the factor from Arkode.set_max_efail_growth is applied. set_stab_lim_det [Cvodes.Adjoint] Indicates whether the BDF stability limit detection algorithm should be used. set_stab_lim_det [Cvode] Indicates whether the BDF stability limit detection algorithm should be used. set_stability_fn [Arkode] Sets a problem-dependent function to estimate a stable time step size for the explicit portion of the ODE system. set_step_tolerance_ic [Ida] Specifies a positive lower bound on the Newton step in the initial condition calculation. set_stop_time [Arkode] Limits the value of the independent variable t when solving. set_stop_time [Ida] Limits the value of the independent variable t when solving. set_stop_time [Cvode] Limits the value of the independent variable t when solving. set_suppress_alg [Idas.Adjoint] Indicates whether or not to ignore algebraic variables in the local error test. set_suppress_alg [Ida] Indicates whether or not to ignore algebraic variables in the local error test. set_sys_func [Kinsol] Changes the system function. set_times [Arkode.Mass.Spils] Change the mass matrix-times-vector function. set_to_zero [Sundials_Matrix.ArrayBand] Fills the matrix with zeros. set_to_zero [Sundials_Matrix.ArrayDense] Fills the matrix with zeros. set_to_zero [Sundials_Matrix.Sparse] Fills a matrix with zeros. set_to_zero [Sundials_Matrix.Band] Fills a matrix with zeros. set_to_zero [Sundials_Matrix.Dense] Fills a matrix with zeros. set_to_zero [Sundials_Matrix] Fills a matrix with zeros. set_tolerances [Idas.Adjoint.Quadrature] Specify how to use quadrature variables in step size control. set_tolerances [Idas.Sensitivity.Quadrature] Specify how to use quadrature sensitivities in step size control. set_tolerances [Idas.Sensitivity] Specify the integration tolerances for sensitivities. set_tolerances [Idas.Quadrature] Specify how to use quadrature variables in step size control. set_tolerances [Cvodes.Adjoint.Quadrature] Specify how to use quadrature variables in step size control. set_tolerances [Cvodes.Adjoint] Sets the integration tolerances for the backward problem. set_tolerances [Cvodes.Sensitivity.Quadrature] Specify how to use quadrature sensitivities in step size control. set_tolerances [Cvodes.Sensitivity] Sets the integration tolerances for sensitivities. set_tolerances [Cvodes.Quadrature] Specify how to use quadrature variables in step size control. set_tolerances [Arkode] Sets the integration tolerances. set_tolerances [Ida] Set the integration tolerances. set_tolerances [Cvode] Sets the integration tolerances. sformat [Sundials_Matrix.Sparse] Return the matrix format. size [Sundials_Matrix.ArrayBand] m, n = size a returns the numbers of rows m and columns n of a. size [Sundials_Matrix.ArrayDense] m, n = size a returns the numbers of columns m and rows n of a. size [Sundials_Matrix.Sparse] m, n = size a returns the numbers of columns m and rows n of a. size [Sundials_Matrix.Band] m, n = size a returns the numbers of rows m and columns n of a. size [Sundials_Matrix.Dense] m, n = size a returns the numbers of columns m and rows n of a. size [Sundials_RealArray2] nr, nc = size a returns the numbers of rows nr and columns nc of a small_real [Sundials_Config] The smallest value representable as a real. solve [Kinsol] Computes an approximate solution to a nonlinear system. solve_normal [Arkode] Integrates an ODE system over an interval. solve_normal [Ida] Integrates a DAE system over an interval. solve_normal [Cvode] Integrates an ODE system over an interval. solve_one_step [Arkode] Like Arkode.solve_normal but returns after one internal solver step. solve_one_step [Ida] Like Ida.solve_normal but returns after one internal solver step. solve_one_step [Cvode] Like Cvode.solve_normal but returns after one internal solver step. solver [Idas.Adjoint.Alternate] Creates a linear solver from a function returning a set of callbacks. solver [Idas.Adjoint.Spils] Create a Idas-specific linear solver from a generic iterative linear solver. solver [Idas.Adjoint.Dls] Create an Idas-specific linear solver from a Jacobian approximation function and a generic direct linear solver. solver [Cvodes.Adjoint.Alternate] Creates a linear solver from a function returning a set of callbacks. solver [Cvodes.Adjoint.Spils] Create a Cvodes-specific linear solver from a generic iterative linear solver. solver [Cvodes.Adjoint.Dls] Create a Cvodes-specific linear solver from a a Jacobian approximation function and a generic direct linear solver. solver [Cvodes.Adjoint.Diag] A linear solver based on Jacobian approximation by difference quotients. solver [Arkode.Mass.Alternate] Creates a mass matrix solver from a function returning a set of callbacks. solver [Arkode.Mass.Spils] Create an Arkode-specific mass linear solver from a generic iterative linear solver. solver [Arkode.Mass.Dls] Create an Arkode-specific mass linear solver from a mass-matrix constructor function and a generic dense linear solver. solver [Arkode.Alternate] Creates a linear solver from a function returning a set of callbacks. solver [Arkode.Spils] Create an Arkode-specific linear solver from a generic iterative linear solver. solver [Arkode.Dls] Create an Arkode-specific linear solver from a Jacobian approximation function and a generic direct linear solver. solver [Ida.Alternate] Creates a linear solver from a function returning a set of callbacks. solver [Ida.Spils] Create an Ida-specific linear solver from a generic iterative linear solver. solver [Ida.Dls] Create an Ida-specific linear solver from a Jacobian approximation function and a generic direct linear solver. solver [Kinsol.Alternate] Creates a linear solver from a function returning a set of callbacks. solver [Kinsol.Spils] Create a Cvode-specific linear solver from a generic iterative linear solver. solver [Kinsol.Dls] Create a Kinsol-specific linear solver from a Jacobian approximation function and a generic direct linear solver. solver [Cvode.Alternate] Creates a linear solver from a function returning a set of callbacks. solver [Cvode.Spils] Create a Cvode-specific linear solver from a generic iterative linear solver. solver [Cvode.Dls] Create a Cvode-specific linear solver from a Jacobian approximation function and generic direct linear solver. solver [Cvode.Diag] A linear solver based on Jacobian approximation by difference quotients. space [Sundials_Matrix.ArrayBand] lrw, liw = space a returns the storage requirements of a as lrw realtype words and liw integer words. space [Sundials_Matrix.ArrayDense] lrw, liw = space a returns the storage requirements of a as lrw realtype words and liw integer words. space [Sundials_Matrix.Sparse] lrw, liw = space a returns the storage requirements of a as lrw realtype words and liw integer words. space [Sundials_Matrix.Band] lrw, liw = space a returns the storage requirements of a as lrw realtype words and liw integer words. space [Sundials_Matrix.Dense] lrw, liw = space a returns the storage requirements of a as lrw realtype words and liw integer words. space [Sundials_Matrix] lrw, liw = space a returns the storage requirements of a as lrw realtype words and liw integer words. sparse_csc [Sundials_Matrix] By default, sparse_csc n returns an n by n sparse matrix in CSC format with the capacity for n / 10 non-zero elements and all elements initialized to 0.0. sparse_csr [Sundials_Matrix] As for Sundials_Matrix.sparse_csc but the returned matrix is in CSR format. spbcgs [Sundials_LinearSolver.Iterative] Krylov iterative solver using the scaled preconditioned biconjugate stabilized (Bi-CGStab) method. spfgmr [Sundials_LinearSolver.Iterative] Krylov iterative solver using the scaled preconditioned flexible generalized minimum residual (GMRES) method. spgmr [Sundials_LinearSolver.Iterative] Krylov iterative solver using the scaled preconditioned generalized minimum residual (GMRES) method. sptfqmr [Sundials_LinearSolver.Iterative] Krylov iterative with the scaled preconditioned transpose-free quasi-minimal residual (SPTFQMR) method. stderr [Sundials_Logfile] The stderr file. stdout [Sundials_Logfile] The stdout file. sub [Sundials_RealArray] Access a sub-array of the given array without copying. sundials_version [Sundials_Config] The major, minor, and patch version numbers of the underlying Sundials/C library. superlumt [Sundials_LinearSolver.Direct] Creates a direct linear solver on sparse matrices using SuperLUMT. superlumt_enabled [Sundials_Config] Indicates whether the SuperLU_MT sparse linear solver is available. T to_array [Sundials.RootDirs] Creates a new array from the contents of a given value. to_array [Sundials.Roots] Creates a new array from the contents of a given value. to_array [Sundials_RealArray] Copies into a new float array. to_float [Ida.VarId] Map id values to floating-point constants. to_float [Sundials.Constraint] Map constraint values to floating-point constants. to_list [Sundials.RootDirs] Copies into a list. to_list [Sundials.Roots] Copies into a list. to_list [Sundials_RealArray] Copies into a float list. toggle_off [Idas.Sensitivity] Deactivates forward sensitivity calculations without deallocating memory. toggle_off [Cvodes.Sensitivity] Deactivates forward sensitivity calculations without deallocating memory. U unconstrained [Sundials.Constraint] The constant 0.0. unit_roundoff [Sundials_Config] The difference bewteen 1.0 and the minimum real greater than 1.0. unwrap [Nvector_pthreads] Aliases Nvector.unwrap. unwrap [Nvector_openmp] Aliases Nvector.unwrap. unwrap [Nvector_parallel] Aliases Nvector.unwrap. unwrap [Nvector_array.ARRAY_NVECTOR] Returns the array underlying an nvector. unwrap [Nvector_serial] Aliases Nvector.unwrap. unwrap [Nvector] unwrap nv returns the data underlying the nvector nv. unwrap [Sundials_LinearSolver.Iterative.Custom] Return the internal state from an custom iterative linear solver. unwrap [Sundials_LinearSolver.Direct.Custom] Return the internal state from an custom direct linear solver. unwrap [Sundials_Matrix.ArrayBand] Direct access to the underlying storage array, which is accessed column first (unlike in Sundials_Matrix.ArrayBand.get). unwrap [Sundials_Matrix.ArrayDense] Direct access to the underlying storage array, which is accessed column first (unlike in Sundials_Matrix.ArrayDense.get). unwrap [Sundials_Matrix.Sparse] Direct access to the underlying sparse storage arrays. unwrap [Sundials_Matrix.Band] Direct access to the underlying storage array, which is accessed column first (unlike in Sundials_Matrix.Band.get). unwrap [Sundials_Matrix.Dense] Direct access to the underlying storage array, which is accessed column first (unlike in Sundials_Matrix.Dense.get). unwrap [Sundials_Matrix] Direct access to the underlying storage array, which is accessed column first (unlike in Sundials_Matrix.Dense.get, Sundials_Matrix.Band.get, and Sundials_Matrix.Sparse.get). unwrap [Sundials_RealArray2] Returns the Sundials_RealArray2.data array behind a matrix. update [Sundials_Matrix.ArrayBand] update a i j f sets the value at row i and column j of a to f v. update [Sundials_Matrix.ArrayDense] update a i j f sets the value at row i and column j of a to f v. update [Sundials_Matrix.Band] update a i j f sets the value at row i and column j of a to f v. update [Sundials_Matrix.Dense] update a i j f sets the value at row i and column j of a to f v. V version [Sundials_Config] W wrap [Nvector_pthreads] wrap nthreads a creates a new Pthreads nvector with nthreads threads over the elements of a. wrap [Nvector_openmp] wrap nthreads a creates a new OpenMP nvector with nthreads threads over the elements of a. wrap [Nvector_array.ARRAY_NVECTOR] Lifts an array to an nvector. wrap [Nvector_serial] wrap a creates a new serial nvector over the elements of a. wrap [Nvector.NVECTOR] Wrap data in an nvector. wrap [Sundials_RealArray2] Creates a new matrix from an existing Sundials_RealArray2.data array. wrap_arrayband [Sundials_Matrix] Creates an (array-based band) matrix by wrapping an existing array-based band matrix. wrap_arraydense [Sundials_Matrix] Creates an (array-based dense) matrix by wrapping an existing array-based dense matrix. wrap_band [Sundials_Matrix] Creates a (band) matrix by wrapping an existing band matrix. wrap_custom [Sundials_Matrix] Wrap a custom matrix value. wrap_dense [Sundials_Matrix] Creates a (dense) matrix by wrapping an existing dense matrix. wrap_sparse [Sundials_Matrix] Creates a (sparse) matrix by wrapping an existing sparse matrix.