Index of values


A
add [Sls.SparseMatrix]
Adds two matrices.
add_identity [Sls.SparseMatrix]
Increments a square matrix by the identity matrix.
add_identity [Dls.ArrayBandMatrix]
Increment a square matrix by the identity matrix.
add_identity [Dls.BandMatrix]
Increment a square matrix by the identity matrix.
add_identity [Dls.ArrayDenseMatrix]
Increments a square matrix by the identity matrix.
add_identity [Dls.DenseMatrix]
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.

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 [Idas.Adjoint.Dls]
A direct linear solver on banded matrices.
band [Cvodes.Adjoint.Dls]
A direct linear solver on banded matrices.
band [Arkode.Dls.Mass]
A direct linear solver for mass matrix linear systems on banded matrices.
band [Arkode.Dls]
A direct linear solver on banded matrices.
band [Ida.Dls]
A direct linear solver on banded matrices.
band [Kinsol.Dls]
A direct linear solver on banded matrices.
band [Cvode.Dls]
A direct linear solver on banded matrices.
big_real [Sundials]
The largest value representable as a real.
blit [Sls.SparseMatrix]
blit src dst copies the contents of src into dst.
blit [Dls.ArrayBandMatrix]
blit src dst src_smu dst_smu copy_mu copy_ml copies the contents of src into dst.
blit [Dls.BandMatrix]
blit src dst copymu copyml copies the contents of src into dst.
blit [Dls.ArrayDenseMatrix]
blit src dst copies the contents of src into dst.
blit [Dls.DenseMatrix]
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 [Spils]
Performs a classical Gram-Schmidt orthogonalization.
clear_band_jac_fn [Idas.Adjoint.Dls]
Remove a banded Jacobian function and use the default implementation.
clear_band_jac_fn [Cvodes.Adjoint.Dls]
Remove a banded Jacobian function and use the default implementation.
clear_band_jac_fn [Arkode.Dls]
Remove a banded Jacobian function and use the default implementation.
clear_band_jac_fn [Ida.Dls]
Remove a banded Jacobian function and use the default implementation.
clear_band_jac_fn [Kinsol.Dls]
Remove a banded Jacobian function and use the default implementation.
clear_band_jac_fn [Cvode.Dls]
Remove a banded Jacobian function and use the default implementation.
clear_dense_jac_fn [Idas.Adjoint.Dls]
Remove a dense Jacobian function and use the default implementation.
clear_dense_jac_fn [Cvodes.Adjoint.Dls]
Remove a dense Jacobian function and use the default implementation.
clear_dense_jac_fn [Arkode.Dls]
Remove a dense Jacobian function and use the default implementation.
clear_dense_jac_fn [Ida.Dls]
Remove a dense Jacobian function and use the default implementation.
clear_dense_jac_fn [Kinsol.Dls]
Remove a dense Jacobian function and use the default implementation.
clear_dense_jac_fn [Cvode.Dls]
Remove a dense Jacobian function and use the default implementation.
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_vec_fn [Idas.Adjoint.Spils]
Remove a Jacobian-times-vector function and use the default implementation.
clear_jac_times_vec_fn [Cvodes.Adjoint.Spils]
Remove a Jacobian-times-vector function and use the default implementation.
clear_jac_times_vec_fn [Arkode.Spils]
Remove a Jacobian-times-vector function and use the default implementation.
clear_jac_times_vec_fn [Ida.Spils]
Remove a Jacobian-times-vector function and use the default implementation.
clear_jac_times_vec_fn [Kinsol.Spils]
Remove a Jacobian-times-vector function and use the default implementation.
clear_jac_times_vec_fn [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 [Dls.ArrayBandMatrix]
create n smu ml returns an n by n band matrix with storage upper bandwidth smu and lower half-bandwidth ml.
create [Dls.BandMatrix]
Returns an uninitialized band matrix with the given Dls.BandMatrix.dimensions.
create [Dls.ArrayDenseMatrix]
create m n returns an uninitialized m by n dense matrix.
create [Dls.DenseMatrix]
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.
create_csc [Sls.SparseMatrix]
create m n nnz returns an uninitialized m by n sparse matrix in compressed-sparse-column format with a potential for nnz non-zero elements.
create_csr [Sls.SparseMatrix]
create m n nnz returns an uninitialized m by n sparse matrix in compressed-sparse-row format with a potential for nnz non-zero elements.
csc_from_band [Sls.SparseMatrix]
Create a sparse matrix from a banded one.
csc_from_dense [Sls.SparseMatrix]
Create a compressed-sparse-column matrix from a dense one.
csr_from_band [Sls.SparseMatrix]
Create a sparse matrix from a banded one.
csr_from_dense [Sls.SparseMatrix]
Create a compressed-sparse-row matrix from a dense one.

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 [Idas.Adjoint.Dls]
A direct linear solver on dense matrices.
dense [Cvodes.Adjoint.Dls]
A direct linear solver on dense matrices.
dense [Arkode.Dls.Mass]
A direct linear solver for mass matrix linear systems.
dense [Arkode.Dls]
A direct linear solver on dense matrices.
dense [Ida.Dls]
A direct linear solver on dense matrices.
dense [Kinsol.Dls]
A direct linear solver on dense matrices.
dense [Cvode.Dls]
A direct linear solver on dense matrices.
detected [Sundials.Roots]
Returns true only if the specified element is either Rising or Falling.
differential [Ida.VarId]
The constant 1.0.

E
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.RealArray]
fill a c sets all elements of a to the constant c.
floata [Sundials]
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]
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.

G
gbtrf [Dls.ArrayBandMatrix]
gbtrf a smu mu ml p performs the LU factorization of a with partial pivoting according to p.
gbtrf [Dls.BandMatrix]
gbtrf a p performs the LU factorization of a with partial pivoting according to p.
gbtrs [Dls.ArrayBandMatrix]
gbtrs a smu ml p b finds the solution of ax = b using LU factorization.
gbtrs [Dls.BandMatrix]
gbtrs a p b finds the solution of ax = b using an LU factorization found by Dls.BandMatrix.gbtrf.
geq_zero [Sundials.Constraint]
The constant 1.0.
geqrf [Dls.ArrayDenseMatrix]
geqrf a beta work performs the QR factorization of a.
geqrf [Dls.DenseMatrix]
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 [Sls.SparseMatrix]
r, v = get a idx returns the row/column r and value v at the idxth position.
get [Dls.ArrayBandMatrix]
get a smu i j returns the value at row i and column j of a.
get [Dls.BandMatrix]
get a i j returns the value at row i and column j of a.
get [Dls.ArrayDenseMatrix]
get a i j returns the value at row i and column j of a.
get [Dls.DenseMatrix]
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 [Ida.Alternate]
Returns the current cj value.
get_cjratio [Ida.Alternate]
Returns the current cjratio value.
get_col [Sls.SparseMatrix]
get_col a j returns the data index of column j.
get_colval [Sls.SparseMatrix]
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 [Sls.SparseMatrix]
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 [Arkode.Alternate]
Returns the current and previous gamma values.
get_gammas [Cvode.Alternate]
Returns the current and previous gamma values.
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.Spils.Mass]
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_evals [Arkode.Sls.Superlumt.Mass]
Returns the number of calls made by a sparse linear solver to the mass matrix approximation function.
get_num_evals [Arkode.Sls.Klu.Mass]
Returns the number of calls made by a sparse linear solver to the mass matrix approximation function.
get_num_evals [Arkode.Dls.Mass]
Returns the number of calls made by a direct linear solver to the mass matrix construction routine.
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 Jacobian approximation function.
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.Sls.Superlumt]
Returns the number of calls made by a sparse linear solver to the Jacobian approximation function.
get_num_jac_evals [Idas.Adjoint.Sls.Klu]
Returns the number of calls made by a sparse linear solver to the Jacobian approximation 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.Sls.Superlumt]
Returns the number of calls made by a sparse linear solver to the Jacobian approximation function.
get_num_jac_evals [Cvodes.Adjoint.Sls.Klu]
Returns the number of calls made by a sparse 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.Sls.Superlumt]
Returns the number of calls made by a sparse linear solver to the Jacobian approximation function.
get_num_jac_evals [Arkode.Sls.Klu]
Returns the number of calls made by a sparse 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.Sls.Superlumt]
Returns the number of calls made by a sparse linear solver to the Jacobian approximation function.
get_num_jac_evals [Ida.Sls.Klu]
Returns the number of calls made by a sparse 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.Sls.Superlumt]
Returns the number of calls made by a sparse linear solver to the Jacobian approximation function.
get_num_jac_evals [Kinsol.Sls.Klu]
Returns the number of calls made by a sparse 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.Sls.Superlumt]
Returns the number of calls made by a sparse linear solver to the Jacobian approximation function.
get_num_jac_evals [Cvode.Sls.Klu]
Returns the number of calls made by a sparse 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_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.Spils.Mass]
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_mass_solves [Arkode]
Returns the number of calls made to the mass matrix solver.
get_num_mtimes_evals [Arkode.Spils.Mass]
Returns the cumulative number of calls to the mass-matrix-vector product function (Arkode.Spils.Mass.times_vec_fn).
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.Spils.Mass]
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.Spils.Mass]
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_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_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 [Sls.SparseMatrix]
get_row a j returns the data index of row j.
get_rowval [Sls.SparseMatrix]
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.Spils.Mass]
Returns the sizes of the real and integer workspaces used by the spils linear 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.Mass]
Returns the sizes of the real and integer workspaces used by a direct linear mass matrix 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 [Dls.ArrayDenseMatrix]
getrf a p performs the LU factorization of the square matrix a with partial pivoting according to p.
getrf [Dls.DenseMatrix]
getrf a p performs the LU factorization of the square matrix a with partial pivoting according to p.
getrs [Dls.ArrayDenseMatrix]
getrs a p b finds the solution of ax = b using an LU factorization found by Dls.ArrayDenseMatrix.getrf.
getrs [Dls.DenseMatrix]
getrs a p b finds the solution of ax = b using an LU factorization found by Dls.DenseMatrix.getrf.
getrs' [Dls.ArrayDenseMatrix]
Like Dls.ArrayDenseMatrix.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 [Sls.SparseMatrix]
Called internally when the corresponding value in the underlying library ceases to exist.
invalidate [Dls.BandMatrix]
Called internally when the corresponding value in the underlying library ceases to exist.
invalidate [Dls.DenseMatrix]
Called internally when the corresponding value in the underlying library ceases to exist.
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_enabled [Sundials]
Indicates whether the KLU sparse linear solver is available.

L
lapack_band [Idas.Adjoint.Dls]
A direct linear solver on banded matrices using LAPACK.
lapack_band [Cvodes.Adjoint.Dls]
A direct linear solver on banded matrices using LAPACK.
lapack_band [Arkode.Dls.Mass]
A direct linear solver for mass matrix linear systems on banded matrices using LAPACK.
lapack_band [Arkode.Dls]
A direct linear solver on banded matrices using LAPACK.
lapack_band [Ida.Dls]
A direct linear solver on banded matrices using LAPACK.
lapack_band [Kinsol.Dls]
A direct linear solver on banded matrices using LAPACK.
lapack_band [Cvode.Dls]
A direct linear solver on banded matrices using LAPACK.
lapack_dense [Idas.Adjoint.Dls]
A direct linear solver on dense matrices using LAPACK.
lapack_dense [Cvodes.Adjoint.Dls]
A direct linear solver on dense matrices using LAPACK.
lapack_dense [Arkode.Dls.Mass]
A direct linear solver for mass matrix linear systems using LAPACK.
lapack_dense [Arkode.Dls]
A direct linear solver on dense matrices using LAPACK.
lapack_dense [Ida.Dls]
A direct linear solver on dense matrices using LAPACK.
lapack_dense [Kinsol.Dls]
A direct linear solver on dense matrices using LAPACK.
lapack_dense [Cvode.Dls]
A direct linear solver on dense matrices using LAPACK.
lapack_enabled [Sundials]
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 [Arkode.Alternate.Mass]
Creates a mass matrix solver from a function returning a set of callbacks.
make [Arkode.Alternate]
Creates a linear solver from a function returning a set of callbacks.
make [Ida.Alternate]
Creates a linear solver from a function returning a set of callbacks.
make [Kinsol.Alternate]
Creates a linear solver from a function returning a set of callbacks.
make [Cvode.Alternate]
Creates a linear solver from a function returning a set of callbacks.
make [Nvector_serial]
make n iv creates a new serial nvector with n elements, each initialized to iv.
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 [Spils.PCG]
make lmax temp returns a solver session.
make [Spils.SPTFQMR]
make lmax temp returns a solver session.
make [Spils.SPBCG]
make lmax temp returns a solver session.
make [Spils.SPFGMR]
make lmax temp returns a solver session.
make [Spils.SPGMR]
make lmax temp returns a solver session.
make [Dls.BandMatrix]
Returns a band matrix with the given Dls.BandMatrix.dimensions and all elements initialized to the given value.
make [Dls.ArrayDenseMatrix]
make m n x returns an m by n dense matrix with elements set to x.
make [Dls.DenseMatrix]
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_csc [Sls.SparseMatrix]
make m n nnz returns an m by n sparse matrix in compressed-sparse-column format with a potential for nnz non-zero elements.
make_csr [Sls.SparseMatrix]
make m n nnz returns an m by n sparse matrix in compressed-sparse-row format with a potential for nnz non-zero elements.
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 [Sls.SparseMatrix]
matvec a x y computes the matrix-vector product y = A*x.
matvec [Dls.ArrayBandMatrix]
Compute the matrix-vector product $y = Ax$.
matvec [Dls.BandMatrix]
Compute the matrix-vector product $y = Ax$.
matvec [Dls.ArrayDenseMatrix]
Compute the matrix-vector product $y = Ax$.
matvec [Dls.DenseMatrix]
Compute the matrix-vector product $y = Ax$.
modified_gs [Spils]
Performs a modified Gram-Schmidt orthogonalization.
mpi_enabled [Sundials]
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_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]
Indicates whether openmp-based nvectors are available.
nvecpthreads_enabled [Sundials]
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.
ormqr [Dls.ArrayDenseMatrix]
ormqr q beta v w work computes the product w = qv .
ormqr [Dls.DenseMatrix]
ormqr q beta v w work computes the product w = qv .

P
pcg [Arkode.Spils.Mass]
Krylov iterative solver using the preconditioned conjugate gradient (PCG) method.
pcg [Arkode.Spils]
Krylov iterative solver using the preconditioned conjugate gradient (PCG) method.
potrf [Dls.ArrayDenseMatrix]
Performs Cholesky factorization of a real symmetric positive matrix.
potrf [Dls.DenseMatrix]
Performs Cholesky factorization of a real symmetric positive matrix.
potrs [Dls.ArrayDenseMatrix]
potrs a b finds the solution of ax = b using the Cholesky factorization found by Dls.ArrayDenseMatrix.potrf.
potrs [Dls.DenseMatrix]
potrs a b finds the solution of ax = b using the Cholesky factorization found by Dls.DenseMatrix.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 [Sls.SparseMatrix]
Pretty-print a sparse matrix using the Format module.
pp [Dls.BandMatrix]
Pretty-print a band matrix using the Format module.
pp [Dls.DenseMatrix]
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 [Dls.BandMatrix]
Pretty-print a band matrix using the Format module.
ppi [Dls.DenseMatrix]
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.Spils.Mass]
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.Spils.Mass]
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.Spils.Mass]
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.Spils.Mass]
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 [Sls.SparseMatrix]
Prints a sparse matrix to stdout.
print [Dls.BandMatrix]
Prints a band matrix to stdout.
print [Dls.DenseMatrix]
Prints a dense matrix to stdout.
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.

Q
qr_fact [Spils]
Performs a QR factorization of a Hessenberg matrix.
qr_sol [Spils]
Solve the linear least squares problem.

R
realloc [Sls.SparseMatrix]
Reallocates enoughs space for the given number of non-zero values.
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.Sls.Klu]
Reinitializes the Jacobian matrix memory and flags.
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.Sls.Klu]
Reinitializes the Jacobian matrix memory and flags.
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.Sls.Klu.Mass]
Reinitializes the mass matrix memory and flags.
reinit [Arkode.Sls.Klu]
Reinitializes the Jacobian matrix memory and flags.
reinit [Arkode]
Reinitializes the solver with new parameters and state values.
reinit [Ida.Sls.Klu]
Reinitializes the Jacobian matrix memory and flags.
reinit [Ida]
Reinitializes the solver with new parameters and state values.
reinit [Kinsol.Sls.Klu]
Reinitializes the Jacobian matrix memory and flags.
reinit [Cvode.Sls.Klu]
Reinitializes the Jacobian matrix memory and flags.
reinit [Cvode]
Reinitializes the solver with new parameters and state values.
reset [Sundials.Roots]
Resets all elements to NoRoot.
resize [Arkode]
Change the number of equations and unknowns between integrator steps.
rising [Sundials.Roots]
Returns true only if the specified element is Rising.

S
scale [Sls.SparseMatrix]
Multiplies each element by a constant.
scale [Dls.ArrayBandMatrix]
scale c a smu mu ml multiplies each element of the band matrix a by c.
scale [Dls.BandMatrix]
Multiplies each element by a constant.
scale [Dls.ArrayDenseMatrix]
Multiplies each element by a constant.
scale [Dls.DenseMatrix]
Multiplies each element by a constant.
set [Sls.SparseMatrix]
set a idx i v sets the idxth row/column to i and its value to v.
set [Dls.ArrayBandMatrix]
set a smu i j v sets the value at row i and column j of a to v.
set [Dls.BandMatrix]
set a i j v sets the value at row i and column j of a to v.
set [Dls.ArrayDenseMatrix]
set a i j v sets the value at row i and column j of a to v.
set [Dls.DenseMatrix]
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_band_fn [Arkode.Dls.Mass]
Change the band mass matrix function.
set_band_jac_fn [Idas.Adjoint.Dls]
Change the band Jacobian function.
set_band_jac_fn [Cvodes.Adjoint.Dls]
Change the band Jacobian function.
set_band_jac_fn [Arkode.Dls]
Change the band Jacobian function.
set_band_jac_fn [Ida.Dls]
Change the band Jacobian function.
set_band_jac_fn [Kinsol.Dls]
Change the band Jacobian function.
set_band_jac_fn [Cvode.Dls]
Change the band Jacobian function.
set_cfl_fraction [Arkode]
Specifies the fraction of the estimated explicitly stable step to use.
set_col [Sls.SparseMatrix]
set_col a j idx sets the data index of column j to idx.
set_colval [Sls.SparseMatrix]
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 [Sls.SparseMatrix]
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_fn [Arkode.Dls.Mass]
Change the dense mass matrix function.
set_dense_jac_fn [Idas.Adjoint.Dls]
Change the dense Jacobian function.
set_dense_jac_fn [Cvodes.Adjoint.Dls]
Change the dense Jacobian function.
set_dense_jac_fn [Arkode.Dls]
Change the dense Jacobian function.
set_dense_jac_fn [Ida.Dls]
Change the dense Jacobian function.
set_dense_jac_fn [Kinsol.Dls]
Change the dense Jacobian function.
set_dense_jac_fn [Cvode.Dls]
Change the dense Jacobian function.
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.Spils.Mass]
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 [Idas.Adjoint.Spils]
Sets the Gram-Schmidt orthogonalization to be used with the Spgmr Idas.Adjoint.linear_solver.
set_gs_type [Cvodes.Adjoint.Spils]
Sets the Gram-Schmidt orthogonalization to be used with the Spgmr Cvodes.Adjoint.linear_solver.
set_gs_type [Arkode.Spils.Mass]
Sets the Gram-Schmidt orthogonalization to be used with the Spgmr or Spfgmr Arkode.linear_solver.
set_gs_type [Arkode.Spils]
Sets the Gram-Schmidt orthogonalization to be used with the Spgmr or Spfgmr Arkode.linear_solver.
set_gs_type [Ida.Spils]
Sets the Gram-Schmidt orthogonalization to be used with the Spgmr Ida.linear_solver.
set_gs_type [Cvode.Spils]
Sets the Gram-Schmidt orthogonalization to be used with the Spgmr Cvode.linear_solver.
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_vec_fn [Idas.Adjoint.Spils]
Change the Jacobian-times-vector function.
set_jac_times_vec_fn [Cvodes.Adjoint.Spils]
Change the Jacobian-times-vector function.
set_jac_times_vec_fn [Arkode.Spils]
Change the Jacobian-times-vector function.
set_jac_times_vec_fn [Ida.Spils]
Change the Jacobian-times-vector function.
set_jac_times_vec_fn [Kinsol.Spils]
Change the Jacobian-times-vector function.
set_jac_times_vec_fn [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_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 [Idas.Adjoint.Spils]
Resets the maximum Krylov subspace dimension for the Bi-CGStab and TFQMR methods.
set_maxl [Cvodes.Adjoint.Spils]
Resets the maximum Krylov subspace dimension for the Bi-CGStab and TFQMR methods.
set_maxl [Arkode.Spils.Mass]
Resets the maximum Krylov subspace dimension for the Bi-CGStab, TFQMR, or PCG methods.
set_maxl [Arkode.Spils]
Resets the maximum Krylov subspace dimension for the Bi-CGStab, TFQMR, or PCG methods.
set_maxl [Ida.Spils]
Resets the maximum Krylov subspace dimension for the Bi-CGStab and TFQMR methods.
set_maxl [Cvode.Spils]
Resets the maximum Krylov subspace dimension for the Bi-CGStab and TFQMR methods.
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 [Idas.Adjoint.Sls.Superlumt]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Idas.Adjoint.Sls.Klu]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Cvodes.Adjoint.Sls.Superlumt]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Cvodes.Adjoint.Sls.Klu]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Arkode.Sls.Superlumt.Mass]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Arkode.Sls.Superlumt]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Arkode.Sls.Klu.Mass]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Arkode.Sls.Klu]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Ida.Sls.Superlumt]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Ida.Sls.Klu]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Kinsol.Sls.Superlumt]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Kinsol.Sls.Klu]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Cvode.Sls.Superlumt]
Sets the ordering algorithm used to minimize fill-in.
set_ordering [Cvode.Sls.Klu]
Sets the ordering algorithm used to minimize fill-in.
set_postprocess_step_fn [Arkode]
Set a post processing step function.
set_prec_type [Cvodes.Adjoint.Spils]
Change the preconditioning direction without modifying callback functions.
set_prec_type [Arkode.Spils.Mass]
Change the preconditioning direction without modifying callback functions.
set_prec_type [Arkode.Spils]
Change the preconditioning direction without modifying callback functions.
set_prec_type [Cvode.Spils]
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.Spils.Mass]
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 [Sls.SparseMatrix]
set_row a j idx sets the data index of row j to idx.
set_rowval [Sls.SparseMatrix]
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_vec_fn [Arkode.Spils.Mass]
Change the mass matrix-times-vector function.
set_to_zero [Sls.SparseMatrix]
Fills a matrix with zeros.
set_to_zero [Dls.BandMatrix]
Fills a matrix with zeros.
set_to_zero [Dls.ArrayDenseMatrix]
Fills the matrix with zeros.
set_to_zero [Dls.DenseMatrix]
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.
size [Sls.SparseMatrix]
m, n, nnz = size a returns the numbers of columns m, rows n, and the maximum number of non-zero elements of a.
size [Dls.BandMatrix]
Returns the dimensions of a band matrix.
size [Dls.DenseMatrix]
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]
The smallest value representable as a real.
solve [Kinsol]
Computes an approximate solution to a nonlinear system.
solve [Spils.PCG]
Solves the linear system Ax = b using the PCG iterative method.
solve [Spils.SPTFQMR]
Solves the linear system Ax = b using the SPTFQMR iterative method.
solve [Spils.SPBCG]
Solves the linear system Ax = b using the SPBCG iterative method.
solve [Spils.SPFGMR]
Solves the linear system Ax = b using the SPFGMR iterative method.
solve [Spils.SPGMR]
Solves the linear system Ax = b using the SPGMR iterative method.
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 [Cvodes.Adjoint.Diag]
A linear solver based on Jacobian approximation by difference quotients.
solver [Cvode.Diag]
A linear solver based on Jacobian approximation by difference quotients.
solver_csc [Idas.Adjoint.Sls.Superlumt]
A direct linear solver on compressed-sparse-column matrices.
solver_csc [Idas.Adjoint.Sls.Klu]
A direct linear solver on compressed-sparse-column matrices.
solver_csc [Cvodes.Adjoint.Sls.Superlumt]
A direct linear solver on compressed-sparse-column matrices.
solver_csc [Cvodes.Adjoint.Sls.Klu]
A direct linear solver on compressed-sparse-column matrices.
solver_csc [Arkode.Sls.Superlumt.Mass]
A direct linear solver on compressed-sparse-column matrices.
solver_csc [Arkode.Sls.Superlumt]
A direct linear solver on compressed-sparse-column matrices.
solver_csc [Arkode.Sls.Klu.Mass]
A direct linear solver on compressed-sparse-column matrices.
solver_csc [Arkode.Sls.Klu]
A direct linear solver on compressed-sparse-column matrices.
solver_csc [Ida.Sls.Superlumt]
A direct linear solver on compresed-sparse-column matrices.
solver_csc [Ida.Sls.Klu]
A direct linear solver on compressed-sparse-column matrices.
solver_csc [Kinsol.Sls.Superlumt]
A direct linear solver on compressed-sparse-column matrices.
solver_csc [Kinsol.Sls.Klu]
A direct linear solver on compressed-sparse-column matrices.
solver_csc [Cvode.Sls.Superlumt]
A direct linear solver on compressed-sparse-column matrices.
solver_csc [Cvode.Sls.Klu]
A direct linear solver on compressed-sparse-column matrices.
solver_csr [Idas.Adjoint.Sls.Klu]
A direct linear solver on compressed-sparse-row matrices.
solver_csr [Cvodes.Adjoint.Sls.Klu]
A direct linear solver on compressed-sparse-row matrices.
solver_csr [Arkode.Sls.Klu.Mass]
A direct linear solver on compressed-sparse-row matrices.
solver_csr [Arkode.Sls.Klu]
A direct linear solver on compressed-sparse-row matrices.
solver_csr [Ida.Sls.Klu]
A direct linear solver on compressed-sparse-row matrices.
solver_csr [Kinsol.Sls.Klu]
A direct linear solver on compressed-sparse-row matrices.
solver_csr [Cvode.Sls.Klu]
A direct linear solver on compressed-sparse-row matrices.
spbcg [Idas.Adjoint.Spils]
Krylov iterative solver using the scaled preconditioned biconjugate stabilized (Bi-CGStab) method.
spbcg [Cvodes.Adjoint.Spils]
Krylov iterative solver using the scaled preconditioned biconjugate stabilized (Bi-CGStab) method.
spbcg [Arkode.Spils.Mass]
Krylov iterative solver using the scaled preconditioned biconjugate stabilized (Bi-CGStab) method.
spbcg [Arkode.Spils]
Krylov iterative solver using the scaled preconditioned biconjugate stabilized (Bi-CGStab) method.
spbcg [Ida.Spils]
Krylov iterative solver using the scaled preconditioned biconjugate stabilized (Bi-CGStab) method.
spbcg [Kinsol.Spils]
Krylov iterative solver using the scaled preconditioned biconjugate stabilized (Bi-CGStab) method.
spbcg [Cvode.Spils]
Krylov iterative solver using the scaled preconditioned biconjugate stabilized (Bi-CGStab) method.
spfgmr [Arkode.Spils.Mass]
Krylov iterative solver using the scaled preconditioned flexible generalized minimum residual (GMRES) method.
spfgmr [Arkode.Spils]
Krylov iterative solver using the scaled preconditioned flexible generalized minimum residual (GMRES) method.
spfgmr [Kinsol.Spils]
Krylov iterative solver using the scaled preconditioned flexible generalized minimum residual (GMRES) method.
spgmr [Idas.Adjoint.Spils]
Krylov iterative solver using the scaled preconditioned generalized minimum residual (GMRES) method.
spgmr [Cvodes.Adjoint.Spils]
Krylov iterative solver using the scaled preconditioned generalized minimum residual (GMRES) method.
spgmr [Arkode.Spils.Mass]
Krylov iterative solver using the scaled preconditioned generalized minimum residual (GMRES) method.
spgmr [Arkode.Spils]
Krylov iterative solver using the scaled preconditioned generalized minimum residual (GMRES) method.
spgmr [Ida.Spils]
Krylov iterative solver using the scaled preconditioned generalized minimum residual (GMRES) method.
spgmr [Kinsol.Spils]
Krylov iterative solver using the scaled preconditioned generalized minimum residual (GMRES) method.
spgmr [Cvode.Spils]
Krylov iterative solver using the scaled preconditioned generalized minimum residual (GMRES) method.
sptfqmr [Idas.Adjoint.Spils]
Krylov iterative with the scaled preconditioned transpose-free quasi-minimal residual (SPTFQMR) method.
sptfqmr [Cvodes.Adjoint.Spils]
Krylov iterative with the scaled preconditioned transpose-free quasi-minimal residual (SPTFQMR) method.
sptfqmr [Arkode.Spils.Mass]
Krylov iterative with the scaled preconditioned transpose-free quasi-minimal residual (SPTFQMR) method.
sptfqmr [Arkode.Spils]
Krylov iterative with the scaled preconditioned transpose-free quasi-minimal residual (SPTFQMR) method.
sptfqmr [Ida.Spils]
Krylov iterative with the scaled preconditioned transpose-free quasi-minimal residual (SPTFQMR) method.
sptfqmr [Kinsol.Spils]
Krylov iterative with the scaled preconditioned transpose-free quasi-minimal residual (SPTFQMR) method.
sptfqmr [Cvode.Spils]
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]
The major, minor, and patch version numbers of the underlying Sundials/C library.
superlumt_enabled [Sundials]
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]
The difference bewteen 1.0 and the minimum real greater than 1.0.
unsafe_unwrap [Dls.BandMatrix]
Potentially unsafe access to the underlying storage.
unsafe_unwrap [Dls.DenseMatrix]
Potentially unsafe access to the underlying storage.
unwrap [Nvector_pthreads]
Aliases Nvector.unwrap.
unwrap [Nvector_openmp]
Aliases Nvector.unwrap.
unwrap [Nvector_parallel]
Aliases Nvector.unwrap.
unwrap [Nvector_serial]
Aliases Nvector.unwrap.
unwrap [Nvector_array.ARRAY_NVECTOR]
Returns the array underlying an nvector.
unwrap [Nvector]
unwrap nv returns the data underlying the nvector nv.
unwrap [Sundials.RealArray2]
Returns the Sundials.RealArray2.data array behind a matrix.
update [Dls.ArrayBandMatrix]
update a smu i j f sets the value at row i and column j of a to f v.
update [Dls.BandMatrix]
update a i j f sets the value at row i and column j of a to f v.
update [Dls.ArrayDenseMatrix]
update a i j f sets the value at row i and column j of a to f v.
update [Dls.DenseMatrix]
update a i j f sets the value at row i and column j of a to f v.

V
version [Sundials]
The major, minor, patch, and binding version numbers of Sundials/ML.

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_serial]
wrap a creates a new serial nvector over the elements of a.
wrap [Nvector_array.ARRAY_NVECTOR]
Lifts an array to an nvector.
wrap [Nvector.NVECTOR]
Wrap data in an nvector.
wrap [Sundials.RealArray2]
Creates a new matrix from an existing Sundials.RealArray2.data array.