Index of values

A
add_identity [Sundials_Matrix.ArrayBand]

Increment a square matrix by the identity matrix.

add_identity [Sundials_Matrix.ArrayDense]

Increments a square matrix by the identity matrix.

add_tracing [Nvector_custom]

add_tracing p ops modifies a set of Nvector_custom.nvector_ops so that a message, prefixed by p, is printed each time an operation is called.

algebraic [Ida.VarId]

The constant 0.0.

array_nvec_ops [Nvector_array.ARRAY_NVECTOR]

The set of nvector operations on an array.

arrayband [Sundials_Matrix]

By default, band n returns an n by n band matrix with all bandwidths equal to 2 and all values initialized to 0.0.

arraydense [Sundials_Matrix]

By default, arraydense n returns an n by n dense matrix with all elements initialized to 0.0.

B
backward_normal [Idas.Adjoint]

Integrates a backward ODE system over an interval.

backward_normal [Cvodes.Adjoint]

Integrates a backward ODE system over an interval.

backward_one_step [Idas.Adjoint]

Like Idas.Adjoint.backward_normal but returns after one internal solver step.

backward_one_step [Cvodes.Adjoint]

Like Cvodes.Adjoint.backward_normal but returns after one internal solver step.

band [Sundials_LinearSolver.Direct]

Creates a direct linear solver on banded matrices.

band [Sundials_Matrix]

By default, band n returns an n by n band matrix with all bandwidths equal to 2 and all values initialized to 0.0.

big_real [Sundials_Config]

The largest value representable as a real.

blit [Sundials_Matrix.ArrayBand]

blit src dst copies the contents of src into dst.

blit [Sundials_Matrix.ArrayDense]

blit src dst copies the contents of src into dst.

blit [Sundials_Matrix.Sparse]

blit src dst copies the contents of src into dst.

blit [Sundials_Matrix.Band]

blit src dst copies the contents of src into dst.

blit [Sundials_Matrix.Dense]

blit src dst copies the contents of src into dst.

blit [Sundials_Matrix]

blit src dst copies the contents of src into dst.

blit [Sundials.RootDirs]

Copy the first array into the second one.

blit [Sundials_RealArray2]

Copy the first array into the second one.

blit [Sundials_RealArray]

Copy the first array into the second one.

blit_some [Sundials.RootDirs]

blit_some src isrc dst idst len copies len elements of src at offset isrc to dst at offset idst.

blit_some [Sundials_RealArray]

blit_some src isrc dst idst len copies len elements of src at offset isrc to dst at offset idst.

C
calc_ic [Idas.Adjoint]

Computes the algebraic components of the initial state and the differential components of the derivative vectors for certain index-one problems.

calc_ic_sens [Idas.Adjoint]

Computes the algebraic components of the initial state and the differential components of the derivative vectors for certain index-one problems.

calc_ic_y [Idas.Sensitivity]

Identical to Ida.calc_ic_y, but with the possibility of filling s with the corrected sensitivity values.

calc_ic_y [Ida]

Computes the initial state vector for certain index-one problems.

calc_ic_ya_yd' [Idas.Sensitivity]

Identical to Ida.calc_ic_ya_yd', but with the possibility of filling s and s' with the corrected sensitivity and sensitivity derivative values.

calc_ic_ya_yd' [Ida]

Computes the algebraic components of the initial state and derivative vectors for certain index-one problems.

check [Nvector]

check v1 v2 checks v1 and v2 for compatibility.

classical_gs [Sundials_LinearSolver.Iterative.Algorithms]

Performs a classical Gram-Schmidt orthogonalization.

clear_diagnostics [Arkode]

Do not write step adaptivity or solver diagnostics of a file.

clear_err_handler_fn [Arkode]

Restores the default error handling function.

clear_err_handler_fn [Ida]

Restores the default error handling function.

clear_err_handler_fn [Kinsol]

Restores the default error handling function.

clear_err_handler_fn [Cvode]

Restores the default error handling function.

clear_info_handler_fn [Kinsol]

Restores the default information handling function.

clear_jac_times [Idas.Adjoint.Spils]

Remove a Jacobian-times-vector function and use the default implementation.

clear_jac_times [Cvodes.Adjoint.Spils]

Remove a Jacobian-times-vector function and use the default implementation.

clear_jac_times [Arkode.Spils]

Remove a Jacobian-times-vector function and use the default implementation.

clear_jac_times [Ida.Spils]

Remove a Jacobian-times-vector function and use the default implementation.

clear_jac_times [Kinsol.Spils]

Remove a Jacobian-times-vector function and use the default implementation.

clear_jac_times [Cvode.Spils]

Remove a Jacobian-times-vector function and use the default implementation.

clear_postprocess_step_fn [Arkode]

Clear the post processing step function.

clear_stability_fn [Arkode]

Clears the problem-dependent function that estimates a stable time step size for the explicit portion of the ODE system.

clone [Nvector_parallel]

Creates an nvector with a distinct underlying array but that shares the original global size and communicator.

col [Sundials_RealArray2]

col a j returns the jth column of a.

communicator [Nvector_parallel]

Returns the communicator used for the parallel nvector.

copy [Sundials.RootDirs]

copy n a returns an array with n elements, initialized from the contents of a.

copy [Sundials.Roots]

Creates a new array with the same contents as an existing one.

copy [Sundials_RealArray2]

Creates a new array with the same contents as an existing one.

copy [Sundials_RealArray]

Creates a new array with the same contents as an existing one.

create [Sundials_Matrix.ArrayBand]

create smu ml n returns an uninitialized n by n band matrix with storage upper bandwidth smu and lower half-bandwidth ml.

create [Sundials_Matrix.ArrayDense]

create m n returns an uninitialized m by n array dense matrix.

create [Sundials_Matrix.Band]

Returns an uninitialized band matrix with the given Sundials_Matrix.Band.dimensions.

create [Sundials_Matrix.Dense]

create m n returns an uninitialized m by n dense matrix.

create [Sundials.RootDirs]

create n returns an array with n elements each set to IncreasingOrDecreasing.

create [Sundials.Roots]

create n returns an array with n elements each set to NoRoot.

create [Sundials_LintArray]

create n returns an uninitialized array with n elements.

create [Sundials_RealArray2]

create nr nc returns an uninitialized array with nr rows and nc columns.

create [Sundials_RealArray]

create n returns an uninitialized array with n elements.

D
default_tolerances [Arkode]

A default relative tolerance of 1.0e-4 and absolute tolerance of 1.0e-9.

default_tolerances [Ida]

A default relative tolerance of 1.0e-4 and absolute tolerance of 1.0e-8.

default_tolerances [Cvode]

A default relative tolerance of 1.0e-4 and absolute tolerance of 1.0e-8.

dense [Sundials_LinearSolver.Direct]

Creates a direct linear solver on dense matrices.

dense [Sundials_Matrix]
detected [Sundials.Roots]

Returns true only if the specified element is either Rising or Falling.

differential [Ida.VarId]

The constant 1.0.

dims [Sundials_Matrix.ArrayBand]

Returns the dimensions of an array band matrix.

dims [Sundials_Matrix.Sparse]

nnz, np = dims m returns the allocated number of nonzeros nnz and of the number np of columns (for csc) or rows (for csr) in the matrix m.

dims [Sundials_Matrix.Band]

Returns the dimensions of a band matrix.

E
empty [Sundials_LintArray]

An array with no elements.

empty [Sundials_RealArray2]

An array with no elements.

empty [Sundials_RealArray]

An array with no elements.

exists [Sundials.Roots]

true if any elements are equal to Rising or Falling.

F
falling [Sundials.Roots]

Returns true only if the specified element is Falling.

fill [Sundials.RootDirs]

fill_all a x sets the values of a to x everywhere.

fill [Sundials.Roots]

fill a x sets all elements in a to x.

fill [Sundials_RealArray2]

fill a c sets all elements of a to the constant c.

fill [Sundials_RealArray]

fill a c sets all elements of a to the constant c.

floata [Sundials.Util]

Returns the bit-level representation of a float in hexadecimal as a string.

flush [Sundials_Logfile]

Flushes the given file.

fold_left [Sundials_RealArray]

fold_left f b a returns f (f (f b a.{0}) a.{1}) ...).

fold_right [Sundials_RealArray]

fold_right f b a returns (f ... (f a.{n-2} (f a.{n-1} b))).

format_float [Sundials.Util]

format_float fmt f formats f according to the format string fmt.

forward_normal [Idas.Adjoint]

Integrates the forward problem over an interval and saves checkpointing data.

forward_normal [Cvodes.Adjoint]

Integrates the forward problem over an interval and saves checkpointing data.

forward_one_step [Idas.Adjoint]

Integrates the forward problem over an interval and saves checkpointing data.

forward_one_step [Cvodes.Adjoint]

Integrates the forward problem over an interval and saves checkpointing data.

from_band [Sundials_Matrix.Sparse]

Creates a sparse matrix in the specified format from a band matrix by copying all values of magnitude greater than the given tolerance.

from_dense [Sundials_Matrix.Sparse]

Creates a sparse matrix in in the specified format from a dense matrix by copying all values of magnitude greater than the given tolerance.

G
gbtrf [Sundials_Matrix.ArrayBand]

gbtrf a p performs the LU factorization of a with partial pivoting according to p.

gbtrs [Sundials_Matrix.ArrayBand]

gbtrs a p b finds the solution of ax = b using LU factorization.

geq_zero [Sundials.Constraint]

The constant 1.0.

geqrf [Sundials_Matrix.ArrayDense]

geqrf a beta work performs the QR factorization of a.

get [Idas.Adjoint.Quadrature]

Returns the backward quadrature solutions and time reached after a successful solver step.

get [Idas.Adjoint]

Fills the given vectors, yb and yb', with the solution of the backward DAE problem at the returned time, interpolating if necessary.

get [Idas.Sensitivity.Quadrature]

Returns the quadrature sensitivity solutions and time reached after a successful solver step.

get [Idas.Sensitivity]

Returns the sensitivity solution vectors after a successful solver step.

get [Idas.Quadrature]

Returns the quadrature solutions and time reached after a successful solver step.

get [Cvodes.Adjoint.Quadrature]

Returns the backward quadrature solutions and time reached after a successful solver step.

get [Cvodes.Adjoint]

Fills the given vector with the solution of the backward ODE problem at the returned time, interpolating if necessary.

get [Cvodes.Sensitivity.Quadrature]

Returns the quadrature sensitivity solutions and time reached after a successful solver step.

get [Cvodes.Sensitivity]

Returns the sensitivity solution vectors after a successful solver step.

get [Cvodes.Quadrature]

Returns the quadrature solutions and time reached after a successful solver step.

get [Sundials_Matrix.ArrayBand]

get a i j returns the value at row i and column j of a.

get [Sundials_Matrix.ArrayDense]

get a i j returns the value at row i and column j of a.

get [Sundials_Matrix.Sparse]

r, v = get a idx returns the row/column r and value v at the idxth position.

get [Sundials_Matrix.Band]

get a i j returns the value at row i and column j of a.

get [Sundials_Matrix.Dense]

get a i j returns the value at row i and column j of a.

get [Sundials.RootDirs]

get r i returns the ith element of r.

get [Sundials.Roots]

get r i returns the ith element of r.

get [Sundials_RealArray2]

get a i j returns the value at row i and column j of a.

get1 [Idas.Sensitivity.Quadrature]

Returns a single quadrature sensitivity vector after a successful solver step.

get1 [Idas.Sensitivity]

Returns a single sensitivity solution vector after a successful solver step.

get1 [Cvodes.Sensitivity.Quadrature]

Returns a single quadrature sensitivity vector after a successful solver step.

get1 [Cvodes.Sensitivity]

Returns a single sensitivity solution vector after a successful solver step.

get_actual_init_step [Idas.Adjoint]

Returns the the value of the integration step size used on the first step.

get_actual_init_step [Cvodes.Adjoint]

Returns the the value of the integration step size used on the first step.

get_actual_init_step [Arkode]

Returns the the value of the integration step size used on the first step.

get_actual_init_step [Ida]

Returns the the value of the integration step size used on the first step.

get_actual_init_step [Cvode]

Returns the the value of the integration step size used on the first step.

get_cj [Idas.Adjoint.Alternate]

Returns the current cj value.

get_cj [Ida.Alternate]

Returns the current cj value.

get_cjratio [Idas.Adjoint.Alternate]

Returns the current cjratio value.

get_cjratio [Ida.Alternate]

Returns the current cjratio value.

get_col [Sundials_Matrix.Sparse]

get_col a j returns the data index of column j.

get_colval [Sundials_Matrix.Sparse]

c = get_colval a idx returns the column c at the idxth position.

get_current_butcher_tables [Arkode]

Returns the explicit and implicit Butcher tables in use by the solver.

get_current_order [Idas.Adjoint]

Returns the integration method order to be used on the next internal step.

get_current_order [Cvodes.Adjoint]

Returns the integration method order to be used on the next internal step.

get_current_order [Ida]

Returns the integration method order to be used on the next internal step.

get_current_order [Cvode]

Returns the integration method order to be used on the next internal step.

get_current_step [Idas.Adjoint]

Returns the integration step size to be attempted on the next internal step.

get_current_step [Cvodes.Adjoint]

Returns the integration step size to be attempted on the next internal step.

get_current_step [Arkode]

Returns the integration step size to be attempted on the next internal step.

get_current_step [Ida]

Returns the integration step size to be attempted on the next internal step.

get_current_step [Cvode]

Returns the integration step size to be attempted on the next internal step.

get_current_time [Idas.Adjoint]

Returns the the current internal time reached by the solver.

get_current_time [Cvodes.Adjoint]

Returns the the current internal time reached by the solver.

get_current_time [Arkode]

Returns the the current internal time reached by the solver.

get_current_time [Ida]

Returns the the current internal time reached by the solver.

get_current_time [Cvode]

Returns the the current internal time reached by the solver.

get_data [Sundials_Matrix.Sparse]

v = get_data a idx returns the value v at the idxth position.

get_dky [Idas.Adjoint]

Returns the interpolated solution or derivatives.

get_dky [Idas.Sensitivity.Quadrature]

Returns the interpolated solution or derivatives of the quadrature sensitivity solution.

get_dky [Idas.Sensitivity]

Returns the interpolated solution or derivatives of the sensitivity solution vectors.

get_dky [Idas.Quadrature]

Returns the interpolated solution or derivatives of quadrature variables.

get_dky [Cvodes.Adjoint]

Returns the interpolated solution or derivatives.

get_dky [Cvodes.Sensitivity.Quadrature]

Returns the interpolated solution or derivatives of the quadrature sensitivity solution.

get_dky [Cvodes.Sensitivity]

Returns the interpolated solution or derivatives of the sensitivity solution vectors.

get_dky [Cvodes.Quadrature]

Returns the interpolated solution or derivatives of quadrature variables.

get_dky [Arkode]

Returns the interpolated solution or derivatives.

get_dky [Ida]

Returns the interpolated solution or derivatives.

get_dky [Cvode]

Returns the interpolated solution or derivatives.

get_dky1 [Idas.Sensitivity.Quadrature]

Returns the interpolated solution or derivatives of a single quadrature sensitivity solution vector.

get_dky1 [Idas.Sensitivity]

Returns the interpolated solution or derivatives of a single sensitivity solution vector.

get_dky1 [Cvodes.Sensitivity.Quadrature]

Returns the interpolated solution or derivatives of a single quadrature sensitivity solution vector.

get_dky1 [Cvodes.Sensitivity]

Returns the interpolated solution or derivatives of a single sensitivity solution vector.

get_err_weights [Idas.Adjoint.Quadrature]

Returns the quadrature error weights at the current time.

get_err_weights [Idas.Adjoint]

Returns the solution error weights at the current time.

get_err_weights [Idas.Sensitivity.Quadrature]

Returns the quadrature error weights at the current time.

get_err_weights [Idas.Sensitivity]

Returns the sensitivity error weights at the current time.

get_err_weights [Idas.Quadrature]

Returns the quadrature error weights at the current time.

get_err_weights [Cvodes.Adjoint.Quadrature]

Returns the quadrature error weights at the current time.

get_err_weights [Cvodes.Adjoint]

Returns the solution error weights at the current time.

get_err_weights [Cvodes.Sensitivity.Quadrature]

Returns the quadrature error weights at the current time.

get_err_weights [Cvodes.Sensitivity]

Returns the sensitivity error weights at the current time.

get_err_weights [Cvodes.Quadrature]

Returns the quadrature error weights at the current time.

get_err_weights [Arkode]

Returns the solution error weights at the current time.

get_err_weights [Ida]

Returns the solution error weights at the current time.

get_err_weights [Cvode]

Returns the solution error weights at the current time.

get_est_local_errors [Idas.Adjoint]

Returns the vector of estimated local errors.

get_est_local_errors [Cvodes.Adjoint]

Returns the vector of estimated local errors.

get_est_local_errors [Arkode]

Returns the vector of estimated local errors.

get_est_local_errors [Ida]

Returns the vector of estimated local errors.

get_est_local_errors [Cvode]

Returns the vector of estimated local errors.

get_f_fscale [Kinsol.Alternate]

Returns the internal f and fscale values.

get_func_norm [Kinsol]

Returns the scaled Euclidiean l2 norm of the nonlinear system function $F(u)$ evaluated at the current iterate.

get_gammas [Cvodes.Adjoint.Alternate]

Returns the current and previous gamma values.

get_gammas [Arkode.Alternate]

Returns the current and previous gamma values.

get_gammas [Cvode.Alternate]

Returns the current and previous gamma values.

get_id [Sundials_Matrix]

Return the internal type identifier of a matrix.

get_integrator_stats [Idas.Adjoint]

Returns the integrator statistics as a group.

get_integrator_stats [Cvodes.Adjoint]

Returns the integrator statistics as a group.

get_integrator_stats [Arkode]

Returns the integrator statistics as a group.

get_integrator_stats [Ida]

Returns the integrator statistics as a group.

get_integrator_stats [Cvode]

Returns the integrator statistics as a group.

get_last_order [Idas.Adjoint]

Returns the integration method order used during the last internal step.

get_last_order [Cvodes.Adjoint]

Returns the integration method order used during the last internal step.

get_last_order [Ida]

Returns the integration method order used during the last internal step.

get_last_order [Cvode]

Returns the integration method order used during the last internal step.

get_last_step [Idas.Adjoint]

Returns the integration step size taken on the last internal step.

get_last_step [Cvodes.Adjoint]

Returns the integration step size taken on the last internal step.

get_last_step [Arkode]

Returns the integration step size taken on the last successful internal step.

get_last_step [Ida]

Returns the integration step size taken on the last internal step.

get_last_step [Cvode]

Returns the integration step size taken on the last internal step.

get_nonlin_solv_stats [Idas.Adjoint]

Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails.

get_nonlin_solv_stats [Idas.Sensitivity]

Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails during sensitivity calculations.

get_nonlin_solv_stats [Cvodes.Adjoint]

Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails.

get_nonlin_solv_stats [Cvodes.Sensitivity]

Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails during sensitivity calculations.

get_nonlin_solv_stats [Arkode]

Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails.

get_nonlin_solv_stats [Ida]

Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails.

get_nonlin_solv_stats [Cvode]

Returns both the numbers of nonlinear iterations performed nniters and nonlinear convergence failures nncfails.

get_num_acc_steps [Arkode]

Returns the cumulative number of accuracy-limited steps taken by the solver.

get_num_backtrack_ops [Ida]

Returns the number of backtrack operations during Ida.calc_ic_ya_yd' or Ida.calc_ic_y.

get_num_backtrack_ops [Kinsol]

Returns the number of backtrack operations (step length adjustments) performed by the line search algorithm.

get_num_beta_cond_fails [Kinsol]

Returns the number of beta-condition failures.

get_num_conv_fails [Idas.Adjoint.Spils]

Returns the cumulative number of linear convergence failures.

get_num_conv_fails [Cvodes.Adjoint.Spils]

Returns the cumulative number of linear convergence failures.

get_num_conv_fails [Arkode.Mass.Spils]

Returns the cumulative number of linear convergence failures.

get_num_conv_fails [Arkode.Spils]

Returns the cumulative number of linear convergence failures.

get_num_conv_fails [Ida.Spils]

Returns the cumulative number of linear convergence failures.

get_num_conv_fails [Kinsol.Spils]

Returns the cumulative number of linear convergence failures.

get_num_conv_fails [Cvode.Spils]

Returns the cumulative number of linear convergence failures.

get_num_err_test_fails [Idas.Adjoint.Quadrature]

Returns the number of local error test failures due to quadrature variables.

get_num_err_test_fails [Idas.Adjoint]

Returns the number of local error test failures that have occurred.

get_num_err_test_fails [Idas.Sensitivity.Quadrature]

Returns the number of local error test failures due to quadrature variables.

get_num_err_test_fails [Idas.Sensitivity]

Returns the number of local error test failures for the sensitivity variables that have occurred.

get_num_err_test_fails [Idas.Quadrature]

Returns the number of local error test failures that have occurred due to quadrature variables.

get_num_err_test_fails [Cvodes.Adjoint.Quadrature]

Returns the number of local error test failures due to quadrature variables.

get_num_err_test_fails [Cvodes.Adjoint]

Returns the number of local error test failures that have occurred.

get_num_err_test_fails [Cvodes.Sensitivity.Quadrature]

Returns the number of local error test failures due to quadrature variables.

get_num_err_test_fails [Cvodes.Sensitivity]

Returns the number of local error test failures for the sensitivity variables that have occurred.

get_num_err_test_fails [Cvodes.Quadrature]

Returns the number of local error test failures that have occurred due to quadrature variables.

get_num_err_test_fails [Arkode]

Returns the number of local error test failures that have occurred.

get_num_err_test_fails [Ida]

Returns the number of local error test failures that have occurred.

get_num_err_test_fails [Cvode]

Returns the number of local error test failures that have occurred.

get_num_exp_steps [Arkode]

Returns the cumulative number of stability-limited steps taken by the solver.

get_num_func_evals [Kinsol.Spils]

Returns the number of calls to the system function for finite difference quotient Jacobian-vector product approximations.

get_num_func_evals [Kinsol.Dls]

Returns the number of calls made by a direct linear solver to the user system function for computing the difference quotient approximation to the Jacobian.

get_num_func_evals [Kinsol]

Returns the number of evaluations of the system function.

get_num_g_evals [Arkode]

Returns the cumulative number of calls made to the user-supplied root function g.

get_num_g_evals [Ida]

Returns the cumulative number of calls made to the user-supplied root function g.

get_num_g_evals [Cvode]

Returns the cumulative number of calls made to the user-supplied root function g.

get_num_gfn_evals [Idas_bbd]

Returns the number of calls to the right-hand side function due to finite difference banded Jacobian approximation in the setup function.

get_num_gfn_evals [Ida_bbd]

Returns the number of calls to the right-hand side function due to finite difference banded Jacobian approximation in the setup function.

get_num_gfn_evals [Cvodes_bbd]

Returns the number of calls to the right-hand side function due to finite difference banded Jacobian approximation in the setup function.

get_num_gfn_evals [Cvode_bbd]

Returns the number of calls to the right-hand side function due to finite difference banded Jacobian approximation in the setup function.

get_num_gfn_evals [Arkode_bbd]

Returns the number of calls to the right-hand side function due to finite difference banded Jacobian approximation in the setup function.

get_num_gfn_evals [Kinsol_bbd]

Returns the number of calls to the right-hand side function due to finite difference banded Jacobian approximation in the setup function.

get_num_jac_evals [Idas.Adjoint.Dls]

Returns the number of calls made by a direct linear solver to the Jacobian approximation function.

get_num_jac_evals [Cvodes.Adjoint.Dls]

Returns the number of calls made by a direct linear solver to the Jacobian approximation function.

get_num_jac_evals [Arkode.Dls]

Returns the number of calls made by a direct linear solver to the Jacobian approximation function.

get_num_jac_evals [Ida.Dls]

Returns the number of calls made by a direct linear solver to the Jacobian approximation function.

get_num_jac_evals [Kinsol.Dls]

Returns the number of calls made by a direct linear solver to the Jacobian approximation function.

get_num_jac_evals [Cvode.Dls]

Returns the number of calls made by a direct linear solver to the Jacobian approximation function.

get_num_jtimes_evals [Idas.Adjoint.Spils]

Returns the cumulative number of calls to the Jacobian-vector function.

get_num_jtimes_evals [Cvodes.Adjoint.Spils]

Returns the cumulative number of calls to the Jacobian-vector function.

get_num_jtimes_evals [Arkode.Spils]

Returns the cumulative number of calls to the Jacobian-vector function.

get_num_jtimes_evals [Ida.Spils]

Returns the cumulative number of calls to the Jacobian-vector function.

get_num_jtimes_evals [Kinsol.Spils]

Returns the cumulative number of calls to the Jacobian-vector function.

get_num_jtimes_evals [Cvode.Spils]

Returns the cumulative number of calls to the Jacobian-vector function.

get_num_jtsetup_evals [Idas.Adjoint.Spils]

Returns the cumulative number of calls to the Jacobian-vector setup function.

get_num_jtsetup_evals [Cvodes.Adjoint.Spils]

Returns the cumulative number of calls to the Jacobian-vector setup function.

get_num_jtsetup_evals [Arkode.Spils]

Returns the cumulative number of calls to the Jacobian-vector setup function.

get_num_jtsetup_evals [Ida.Spils]

Returns the cumulative number of calls to the Jacobian-vector setup function.

get_num_jtsetup_evals [Cvode.Spils]

Returns the cumulative number of calls to the Jacobian-vector setup function.

get_num_lin_iters [Idas.Adjoint.Spils]

Returns the cumulative number of linear iterations.

get_num_lin_iters [Cvodes.Adjoint.Spils]

Returns the cumulative number of linear iterations.

get_num_lin_iters [Arkode.Mass.Spils]

Returns the cumulative number of linear iterations.

get_num_lin_iters [Arkode.Spils]

Returns the cumulative number of linear iterations.

get_num_lin_iters [Ida.Spils]

Returns the cumulative number of linear iterations.

get_num_lin_iters [Kinsol.Spils]

Returns the cumulative number of linear iterations.

get_num_lin_iters [Cvode.Spils]

Returns the cumulative number of linear iterations.

get_num_lin_solv_setups [Idas.Adjoint]

Returns the number of calls made to the linear solver's setup function.

get_num_lin_solv_setups [Idas.Sensitivity]

Returns the number of calls made to the linear solver's setup function due to forward sensitivity calculations.

get_num_lin_solv_setups [Cvodes.Adjoint]

Returns the number of calls made to the linear solver's setup function.

get_num_lin_solv_setups [Cvodes.Sensitivity]

Returns the number of calls made to the linear solver's setup function due to forward sensitivity calculations.

get_num_lin_solv_setups [Arkode]

Returns the number of calls made to the linear solver's setup function.

get_num_lin_solv_setups [Ida]

Returns the number of calls made to the linear solver's setup function.

get_num_lin_solv_setups [Cvode]

Returns the number of calls made to the linear solver's setup function.

get_num_mtimes_evals [Arkode.Mass.Spils]

Returns the cumulative number of calls to the mass-matrix-vector product function (Arkode.Mass.Spils.mass_times_vec_fn).

get_num_mtsetup_evals [Arkode.Mass.Spils]

Returns the cumulative number of calls to the mass-matrix-vector setup function.

get_num_mult [Arkode.Mass.Dls]

Returns the number of calls made to the mass matrix-times-vector routine.

get_num_nonlin_solv_conv_fails [Idas.Adjoint]

Returns the number of nonlinear convergence failures that have occurred.

get_num_nonlin_solv_conv_fails [Idas.Sensitivity]

Returns the number of nonlinear convergence failures that have occurred during sensitivity calculations.

get_num_nonlin_solv_conv_fails [Cvodes.Adjoint]

Returns the number of nonlinear convergence failures that have occurred.

get_num_nonlin_solv_conv_fails [Cvodes.Sensitivity]

Returns the number of nonlinear convergence failures that have occurred during sensitivity calculations.

get_num_nonlin_solv_conv_fails [Arkode]

Returns the number of nonlinear convergence failures that have occurred.

get_num_nonlin_solv_conv_fails [Ida]

Returns the number of nonlinear convergence failures that have occurred.

get_num_nonlin_solv_conv_fails [Cvode]

Returns the number of nonlinear convergence failures that have occurred.

get_num_nonlin_solv_iters [Idas.Adjoint]

Returns the number of nonlinear (functional or Newton) iterations performed.

get_num_nonlin_solv_iters [Idas.Sensitivity]

Returns the number of nonlinear iterations performed for sensitivity calculations.

get_num_nonlin_solv_iters [Cvodes.Adjoint]

Returns the number of nonlinear (functional or Newton) iterations performed.

get_num_nonlin_solv_iters [Cvodes.Sensitivity]

Returns the number of nonlinear iterations performed for sensitivity calculations.

get_num_nonlin_solv_iters [Arkode]

Returns the number of nonlinear (functional or Newton) iterations performed.

get_num_nonlin_solv_iters [Ida]

Returns the number of nonlinear (functional or Newton) iterations performed.

get_num_nonlin_solv_iters [Kinsol]

Returns the number of nonlinear iterations.

get_num_nonlin_solv_iters [Cvode]

Returns the number of nonlinear (functional or Newton) iterations performed.

get_num_prec_evals [Idas.Adjoint.Spils]

Returns the number of calls to the setup function.

get_num_prec_evals [Cvodes.Adjoint.Spils]

Returns the cumulative number of calls to the setup function with jok=false.

get_num_prec_evals [Arkode.Mass.Spils]

Returns the cumulative number of calls to the setup function with jok=false.

get_num_prec_evals [Arkode.Spils]

Returns the cumulative number of calls to the setup function with jok=false.

get_num_prec_evals [Ida.Spils]

Returns the number of calls to the setup function.

get_num_prec_evals [Kinsol.Spils]

Returns the cumulative number of calls to the setup function.

get_num_prec_evals [Cvode.Spils]

Returns the cumulative number of calls to the setup function with jok=false.

get_num_prec_solves [Idas.Adjoint.Spils]

Returns the cumulative number of calls to the preconditioner solve function.

get_num_prec_solves [Cvodes.Adjoint.Spils]

Returns the cumulative number of calls to the preconditioner solve function.

get_num_prec_solves [Arkode.Mass.Spils]

Returns the cumulative number of calls to the preconditioner solve function.

get_num_prec_solves [Arkode.Spils]

Returns the cumulative number of calls to the preconditioner solve function.

get_num_prec_solves [Ida.Spils]

Returns the cumulative number of calls to the preconditioner solve function.

get_num_prec_solves [Kinsol.Spils]

Returns the cumulative number of calls to the preconditioner solve function.

get_num_prec_solves [Cvode.Spils]

Returns the cumulative number of calls to the preconditioner solve function.

get_num_res_evals [Idas.Adjoint.Spils]

Returns the number of calls to the residual callback for finite difference Jacobian-vector product approximation.

get_num_res_evals [Idas.Adjoint.Dls]

Returns the number of calls to the residual callback due to the finite difference Jacobian approximation.

get_num_res_evals [Idas.Adjoint]

Returns the number of calls to the backward residual function.

get_num_res_evals [Idas.Sensitivity]

Returns the number of calls to the sensitivity residual function.

get_num_res_evals [Ida.Spils]

Returns the number of calls to the residual callback for finite difference Jacobian-vector product approximation.

get_num_res_evals [Ida.Dls]

Returns the number of calls to the residual callback due to the finite difference Jacobian approximation.

get_num_res_evals [Ida]

Returns the number of calls to the residual function.

get_num_res_evals_sens [Idas.Sensitivity]

Returns the number of calls to the residual function due to the internal finite difference approximation of the sensitivity residual.

get_num_rhs_evals [Idas.Adjoint.Quadrature]

Returns the number of calls to the backward quadrature right-hand side function.

get_num_rhs_evals [Idas.Sensitivity.Quadrature]

Returns the number of calls to the quadrature right-hand side function.

get_num_rhs_evals [Idas.Quadrature]

Returns the number of calls to the quadrature function.

get_num_rhs_evals [Cvodes.Adjoint.Quadrature]

Returns the number of calls to the backward quadrature right-hand side function.

get_num_rhs_evals [Cvodes.Adjoint.Spils.Banded]

Returns the number of calls to the right-hand side callback for the difference banded Jacobian approximation.

get_num_rhs_evals [Cvodes.Adjoint.Spils]

Returns the number of calls to the right-hand side callback for finite difference Jacobian-vector product approximation.

get_num_rhs_evals [Cvodes.Adjoint.Dls]

Returns the number of calls to the right-hand side callback due to the finite difference Jacobian approximation.

get_num_rhs_evals [Cvodes.Adjoint.Diag]

Returns the number of calls made to the right-hand side function due to finite difference Jacobian approximation in the Diagonal linear solver.

get_num_rhs_evals [Cvodes.Adjoint]

Returns the number of calls to the backward right-hand side function.

get_num_rhs_evals [Cvodes.Sensitivity.Quadrature]

Returns the number of calls to the quadrature right-hand side function.

get_num_rhs_evals [Cvodes.Sensitivity]

Returns the number of calls to the sensitivity function.

get_num_rhs_evals [Cvodes.Quadrature]

Returns the number of calls to the quadrature function.

get_num_rhs_evals [Arkode.Spils.Banded]

Returns the number of calls to the right-hand side callback for the difference banded Jacobian approximation.

get_num_rhs_evals [Arkode.Spils]

Returns the number of calls to the right-hand side callback for finite difference Jacobian-vector product approximation.

get_num_rhs_evals [Arkode.Dls]

Returns the number of calls to the right-hand side callback due to the finite difference Jacobian approximation.

get_num_rhs_evals [Arkode]

Returns the number of calls to the right-hand side functions.

get_num_rhs_evals [Cvode.Spils.Banded]

Returns the number of calls to the right-hand side callback for the difference banded Jacobian approximation.

get_num_rhs_evals [Cvode.Spils]

Returns the number of calls to the right-hand side callback for finite difference Jacobian-vector product approximation.

get_num_rhs_evals [Cvode.Dls]

Returns the number of calls to the right-hand side callback due to the finite difference Jacobian approximation.

get_num_rhs_evals [Cvode.Diag]

Returns the number of calls made to the right-hand side function due to finite difference Jacobian approximation in the Diagonal linear solver.

get_num_rhs_evals [Cvode]

Returns the number of calls to the right-hand side function.

get_num_rhs_evals_sens [Cvodes.Sensitivity]

Returns the number of calls to the right-hand side function due to the internal finite difference approximation of the sensitivity equations.

get_num_roots [Arkode]

Returns the number of root functions.

get_num_roots [Ida]

Returns the number of root functions.

get_num_roots [Cvode]

Returns the number of root functions.

get_num_setups [Arkode.Mass.Dls]

Returns the number of calls made to the mass matrix solver setup routine.

get_num_solves [Arkode.Mass.Dls]

Returns the number of calls made to the mass matrix solver solve routine.

get_num_stab_lim_order_reds [Cvodes.Adjoint]

Returns the number of order reductions dictated by the BDF stability limit detection algorithm.

get_num_stab_lim_order_reds [Cvode]

Returns the number of order reductions dictated by the BDF stability limit detection algorithm.

get_num_step_attempts [Arkode]

Returns the cumulative number of steps attempted by the solver.

get_num_steps [Idas.Adjoint]

Returns the cumulative number of internal steps taken by the solver.

get_num_steps [Cvodes.Adjoint]

Returns the cumulative number of internal steps taken by the solver.

get_num_steps [Arkode]

Returns the cumulative number of internal steps taken by the solver.

get_num_steps [Ida]

Returns the cumulative number of internal solver steps.

get_num_steps [Cvode]

Returns the cumulative number of internal steps taken by the solver.

get_num_stgr_nonlin_solv_conv_fails [Cvodes.Sensitivity]

Returns the number of nonlinear convergence failures that have occurred for each sensitivity equation separately in the Staggered1 case.

get_num_stgr_nonlin_solv_iters [Cvodes.Sensitivity]

Returns the number of nonlinear (functional or Newton) iterations performed for each sensitivity equation separately in the Staggered1 case.

get_ops [Sundials_Matrix]

Return a record of matrix operations.

get_root_info [Arkode]

Fills an array showing which functions were found to have a root.

get_root_info [Ida]

Fills an array showing which functions were found to have a root.

get_root_info [Cvode]

Fills an array showing which functions were found to have a root.

get_row [Sundials_Matrix.Sparse]

get_row a j returns the data index of row j.

get_rowval [Sundials_Matrix.Sparse]

r = get_rowval a idx returns the row r at the idxth position.

get_stats [Idas.Adjoint.Quadrature]

Returns quadrature-related statistics.

get_stats [Idas.Sensitivity.Quadrature]

Returns quadrature-related statistics.

get_stats [Idas.Sensitivity]

Returns the sensitivity-related statistics as a group.

get_stats [Idas.Quadrature]

Returns quadrature-related statistics.

get_stats [Cvodes.Adjoint.Quadrature]

Returns quadrature-related statistics.

get_stats [Cvodes.Sensitivity.Quadrature]

Returns quadrature-related statistics.

get_stats [Cvodes.Sensitivity]

Returns the sensitivity-related statistics as a group.

get_stats [Cvodes.Quadrature]

Returns quadrature-related statistics.

get_step_length [Kinsol]

Returns the scaled Euclidiean l2 norm of the step used during the previous iteration.

get_tol_scale_factor [Idas.Adjoint]

Returns a suggested factor by which the user's tolerances should be scaled when too much accuracy has been requested for some internal step.

get_tol_scale_factor [Cvodes.Adjoint]

Returns a suggested factor by which the user's tolerances should be scaled when too much accuracy has been requested for some internal step.

get_tol_scale_factor [Arkode]

Returns a suggested factor by which the user's tolerances should be scaled when too much accuracy has been requested for some internal step.

get_tol_scale_factor [Ida]

Returns a suggested factor by which the user's tolerances should be scaled when too much accuracy has been requested for some internal step.

get_tol_scale_factor [Cvode]

Returns a suggested factor by which the user's tolerances should be scaled when too much accuracy has been requested for some internal step.

get_u_uscale [Kinsol.Alternate]

Returns the internal u and uscale values.

get_work_space [Idas_bbd]

Returns the sizes of the real and integer workspaces used by the BBD preconditioner.

get_work_space [Ida_bbd]

Returns the sizes of the real and integer workspaces used by the BBD preconditioner.

get_work_space [Cvodes_bbd]

Returns the sizes of the real and integer workspaces used by the BBD preconditioner.

get_work_space [Cvode_bbd]

Returns the sizes of the real and integer workspaces used by the BBD preconditioner.

get_work_space [Arkode_bbd]

Returns the sizes of the real and integer workspaces used by the BBD preconditioner.

get_work_space [Kinsol_bbd]

Returns the sizes of the real and integer workspaces used by the BBD preconditioner.

get_work_space [Idas.Adjoint.Spils]

Returns the sizes of the real and integer workspaces used by the linear solver.

get_work_space [Idas.Adjoint.Dls]

Returns the sizes of the real and integer workspaces used by a direct linear solver.

get_work_space [Idas.Adjoint]

Returns the real and integer workspace sizes.

get_work_space [Cvodes.Adjoint.Spils.Banded]

Returns the sizes of the real and integer workspaces used by the banded preconditioner module.

get_work_space [Cvodes.Adjoint.Spils]

Returns the sizes of the real and integer workspaces used by the spils linear solver.

get_work_space [Cvodes.Adjoint.Dls]

Returns the sizes of the real and integer workspaces used by a direct linear solver.

get_work_space [Cvodes.Adjoint.Diag]

Returns the sizes of the real and integer workspaces used by the Diagonal linear solver.

get_work_space [Cvodes.Adjoint]

Returns the real and integer workspace sizes.

get_work_space [Arkode.Mass.Spils]

Returns the sizes of the real and integer workspaces used by the spils linear solver.

get_work_space [Arkode.Mass.Dls]

Returns the sizes of the real and integer workspaces used by a direct linear mass matrix solver.

get_work_space [Arkode.Spils.Banded]

Returns the sizes of the real and integer workspaces used by the banded preconditioner module.

get_work_space [Arkode.Spils]

Returns the sizes of the real and integer workspaces used by the spils linear solver.

get_work_space [Arkode.Dls]

Returns the sizes of the real and integer workspaces used by a direct linear solver.

get_work_space [Arkode]

Returns the real and integer workspace sizes.

get_work_space [Ida.Spils]

Returns the sizes of the real and integer workspaces used by the spils linear solver.

get_work_space [Ida.Dls]

Returns the sizes of the real and integer workspaces used by a direct linear solver.

get_work_space [Ida]

Returns the sizes of the real and integer workspaces.

get_work_space [Kinsol.Spils]

Returns the sizes of the real and integer workspaces used by the spils linear solver.

get_work_space [Kinsol.Dls]

Returns the sizes of the real and integer workspaces used by a direct linear solver.

get_work_space [Kinsol]

Returns the sizes of the real and integer workspaces.

get_work_space [Cvode.Spils.Banded]

Returns the sizes of the real and integer workspaces used by the banded preconditioner module.

get_work_space [Cvode.Spils]

Returns the sizes of the real and integer workspaces used by the spils linear solver.

get_work_space [Cvode.Dls]

Returns the sizes of the real and integer workspaces used by a direct linear solver.

get_work_space [Cvode.Diag]

Returns the sizes of the real and integer workspaces used by the Diagonal linear solver.

get_work_space [Cvode]

Returns the real and integer workspace sizes.

get_y [Idas.Adjoint]

Fills the vector with the interpolated forward solution and its derivative at the given time during a backward simulation.

get_y [Cvodes.Adjoint]

Fills the vector with the interpolated forward solution at the given time during a backward simulation.

getrf [Sundials_Matrix.ArrayDense]

getrf a p performs the LU factorization of the square matrix a with partial pivoting according to p.

getrs [Sundials_Matrix.ArrayDense]

getrs a p b finds the solution of ax = b using an LU factorization found by Sundials_Matrix.ArrayDense.getrf.

getrs' [Sundials_Matrix.ArrayDense]

Like Sundials_Matrix.ArrayDense.getrs but stores b starting at a given offset.

global_length [Nvector_parallel]

Returns the number of global elements for a parallel nvector.

gt_zero [Sundials.Constraint]

The constant 2.0.

I
init [Idas.Adjoint.Quadrature]

This function activates the integration of quadrature equations.

init [Idas.Adjoint]

Activates the forward-backward problem.

init [Idas.Sensitivity.Quadrature]

Activate the integration of quadrature sensitivities.

init [Idas.Sensitivity]

Activates the calculation of forward sensitivities.

init [Idas.Quadrature]

Activates the integration of quadrature equations.

init [Cvodes.Adjoint.Quadrature]

This function activates the integration of quadrature equations.

init [Cvodes.Adjoint]

Activates the forward-backward problem.

init [Cvodes.Sensitivity.Quadrature]

Activate the integration of quadrature sensitivities.

init [Cvodes.Sensitivity]

Activates the calculation of forward sensitivities.

init [Cvodes.Quadrature]

Activates the integration of quadrature equations.

init [Arkode]

Creates and initializes a session with the solver.

init [Ida]

Creates and initializes a session with the solver.

init [Kinsol]

Creates and initializes a session with the Kinsol solver.

init [Cvode]

Creates and initializes a session with the solver.

init [Sundials.RootDirs]

init n f returns an array with n elements, with element i set to f i.

init [Sundials.Roots]

init n f returns an array with n elements, with element i set to f i.

init [Sundials_RealArray]

init n f returns an array with n elements, with element i set to f i.

init_backward [Idas.Adjoint]

Creates and initializes a backward session attached to an existing (forward) session.

init_backward [Cvodes.Adjoint]

Creates and initializes a backward session attached to an existing (forward) session.

int_of_root [Sundials.Roots]

Returns 0 for NoRoot, 1 for Rising, and -1 for Falling.

into_array [Sundials_RealArray]

Copies into an existing float array.

invalidate [Sundials_Matrix.Sparse]

Called internally when the corresponding value in the underlying library ceases to exist.

invalidate [Sundials_Matrix.Band]

Called internally when the corresponding value in the underlying library ceases to exist.

invalidate [Sundials_Matrix.Dense]

Called internally when the corresponding value in the underlying library ceases to exist.

is_csc [Sundials_Matrix.Sparse]

Returns true iff the matrix format is CSC.

iter [Sundials.Roots]

iter f r successively applies f to each element in r.

iter [Sundials_RealArray]

iter f a successively applies f to the elements of a.

iteri [Sundials.Roots]

iteri f r successively applies f to the indexes and elements of r.

iteri [Sundials_RealArray]

iteri f a successively applies f to the indexes and values of a.

K
klu [Sundials_LinearSolver.Direct]

Creates a direct linear solver on sparse matrices using KLU.

klu_enabled [Sundials_Config]

Indicates whether the KLU sparse linear solver is available.

L
lapack_band [Sundials_LinearSolver.Direct]

Creates a direct linear solver on banded matrices using LAPACK.

lapack_dense [Sundials_LinearSolver.Direct]

Creates a direct linear solver on dense matrices using LAPACK.

lapack_enabled [Sundials_Config]

Indicates whether the interface was compiled with BLAS/LAPACK support.

length [Sundials.RootDirs]

Returns the length of an array

length [Sundials.Roots]

Returns the length of an array.

length [Sundials_RealArray]

Returns the length of an array.

leq_zero [Sundials.Constraint]

The constant -1.0.

local_array [Nvector_parallel]

local_array nv returns the local array a underlying the parallel nvector nv.

local_length [Nvector_parallel]

Returns the number of local elements for a parallel nvector.

lt_zero [Sundials.Constraint]

The constant -2.0.

M
make [Nvector_pthreads]

make nthreads n iv creates a new Pthreads nvector with nthreads threads and n elements inialized to iv.

make [Nvector_openmp]

make nthreads n iv creates a new OpenMP nvector with nthreads threads and n elements inialized to iv.

make [Nvector_parallel]

make nl ng c iv creates a new parallel nvector with nl local elements, that is part of a global array with ng elements.

make [Nvector_array.ARRAY_NVECTOR]

make n x creates an nvector containing an array of n elements, each of which is equal to x.

make [Nvector_serial]

make n iv creates a new serial nvector with n elements, each initialized to iv.

make [Sundials_LinearSolver.Iterative.Custom]

Create an iterative linear solver given a set of operations and an internal state.

make [Sundials_LinearSolver.Direct.Custom]

Create a direct linear solver given a set of operations and an internal state.

make [Sundials_LinearSolver.Direct.Superlumt]

Creates a direct linear solver on sparse matrices using SuperLUMT.

make [Sundials_LinearSolver.Direct.Klu]

Creates a direct linear solver on sparse matrices using KLU.

make [Sundials_Matrix.ArrayBand]

make (smu, mu, ml) n v returns an n by n band matrix with storage upper bandwidth smu, upper bandwidth sm, lower half-bandwidth ml, and all elements initialized to v.

make [Sundials_Matrix.ArrayDense]

make m n x returns an m by n array dense matrix with elements set to x.

make [Sundials_Matrix.Sparse]

make fmt m n nnz returns an m by n sparse matrix in the specified format with a potential for nnz non-zero elements.

make [Sundials_Matrix.Band]

Returns a band matrix with the given Sundials_Matrix.Band.dimensions and all elements initialized to the given value.

make [Sundials_Matrix.Dense]

make m n x returns an m by n dense matrix with elements set to x.

make [Sundials.RootDirs]

make n x returns an array with n elements each set to x.

make [Sundials.Roots]

make n x returns an array with n elements each set to x.

make [Sundials_LintArray]

make n x returns an array with n elements each set to v.

make [Sundials_RealArray2]

make nr nc v returns an array with nr rows and nc columns, and with elements set to v.

make [Sundials_RealArray]

make n x returns an array with n elements each set to x.

make_data [Sundials_RealArray2]

make m n returns an uninitialized m by n array.

make_wrap [Nvector_custom]

make_wrap ops takes a set of operations on the data type 'd and yields a function for lifting values of type 'd into 'd nvectors which can be passed to a solver.

map [Sundials_RealArray]

map f a replaces each element a.{i} with f a.{i}.

mapi [Sundials_RealArray]

map f a replaces each element a.{i} with f i a.{i}.

matvec [Sundials_Matrix.ArrayBand]

The call matvec a x y computes the matrix-vector product $y = Ax$.

matvec [Sundials_Matrix.ArrayDense]

The call matvec a x y computes the matrix-vector product $y = Ax$.

matvec [Sundials_Matrix.Sparse]

The call matvec a x y computes the matrix-vector product $y = Ax$.

matvec [Sundials_Matrix.Band]

The call matvec a x y computes the matrix-vector product $y = Ax$.

matvec [Sundials_Matrix.Dense]

The call matvec a x y computes the matrix-vector product $y = Ax$.

matvec [Sundials_Matrix]

The call matvec a x y computes the matrix-vector product $y = Ax$.

modified_gs [Sundials_LinearSolver.Iterative.Algorithms]

Performs a modified Gram-Schmidt orthogonalization.

mpi_enabled [Sundials_Config]

Indicates whether the parallel nvectors and linear solvers are available.

N
n_vabs [Nvector.NVECTOR_OPS]

n_vabs x z calculates z = abs(x).

n_vaddconst [Nvector.NVECTOR_OPS]

n_vaddconst x b z calculates z = x + b.

n_vclone [Nvector.NVECTOR_OPS]

Create a new, distinct vector from an existing one.

n_vcompare [Nvector.NVECTOR_OPS]

n_vcompare c x z calculates z(i) = if abs x(i) >= c then 1 else 0.

n_vconst [Nvector.NVECTOR_OPS]

n_vconst c z sets all of z to c.

n_vconstrmask [Nvector.NVECTOR_OPS]

n_vconstrmask c x m calculates m(i) = Pi x(i) returning the conjunction.

n_vdiv [Nvector.NVECTOR_OPS]

n_vdiv x y z calculates z = x / y (pointwise).

n_vdotprod [Nvector.NVECTOR_OPS]

n_vdotprod x y returns the dot product of x and y.

n_vinv [Nvector.NVECTOR_OPS]

n_vinv x z calculates z = 1/x (pointwise).

n_vinvtest [Nvector.NVECTOR_OPS]

n_vinvtest x z calculates z(i) = 1 / x(i) with prior testing for zero values.

n_vl1norm [Nvector.NVECTOR_OPS]

n_vl1norm x returns the l1 norm of x.

n_vlinearsum [Nvector.NVECTOR_OPS]

n_vlinearsum a x b y z calculates z = a*x + b*y.

n_vmaxnorm [Nvector.NVECTOR_OPS]

n_vmaxnorm x returns the maximum absolute value in x.

n_vmin [Nvector.NVECTOR_OPS]

n_vmin x returns the smallest element in x.

n_vminquotient [Nvector.NVECTOR_OPS]

n_vminquotient num denom returns the minimum of num(i) / denom(i).

n_vprod [Nvector.NVECTOR_OPS]

n_vprod x y z calculates z = x * y (pointwise).

n_vscale [Nvector.NVECTOR_OPS]

n_vscale c x z calculates z = c *. x.

n_vspace [Nvector.NVECTOR_OPS]

lrw, liw = n_vspace c returns the number of realtype words lrw and integer words liw required to store c.

n_vwl2norm [Nvector.NVECTOR_OPS]

n_vwl2norm x w returns the weighted (w) Euclidean l2 norm of x.

n_vwrmsnorm [Nvector.NVECTOR_OPS]

n_vwrmsnorm x w returns the weighted root-mean-square norm of x with weight vector w.

n_vwrmsnormmask [Nvector.NVECTOR_OPS]

n_vmaxnormmask x w id returns the weighted root-mean-square norm of x using only elements where the corresponding id is non-zero.

no_roots [Arkode]

A convenience value for signalling that there are no roots to monitor.

no_roots [Ida]

A convenience value for signalling that there are no roots to monitor.

no_roots [Cvode]

A convenience value for signalling that there are no roots to monitor.

no_sens_params [Cvodes.Sensitivity]

Empty pvals, plist, and pbar fields.

num_threads [Nvector_pthreads]

Returns the number of threads used within a Pthreads nvector.

num_threads [Nvector_openmp]

Returns the number of threads used within an OpenMP nvector.

nvecopenmp_enabled [Sundials_Config]

Indicates whether openmp-based nvectors are available.

nvecpthreads_enabled [Sundials_Config]

Indicates whether pthreads-based nvectors are available.

O
of_array [Sundials.RootDirs]

Creates a new value from the contents of an array.

of_array [Sundials.Roots]

Creates a new value from the contents of an array.

of_array [Sundials_RealArray]

Creates an array by copying the contents of a float array.

of_float [Ida.VarId]

Map floating-point constants to id values.

of_float [Sundials.Constraint]

Map floating-point constants to constraint values.

of_list [Sundials.RootDirs]

Creates an array by copying the contents of a d list.

of_list [Sundials.Roots]

Creates an array by copying the contents of a r list.

of_list [Sundials_RealArray]

Creates an array by copying the contents of a float list.

openfile [Sundials_Logfile]

Opens the named file.

ops [Sundials_Matrix.ArrayBand]

Operations on array-based band matrices.

ops [Sundials_Matrix.ArrayDense]

Operations on array-based dense matrices.

ops [Sundials_Matrix.Sparse]

Operations on sparse matrices.

ops [Sundials_Matrix.Band]
ops [Sundials_Matrix.Dense]

Operations on dense matrices.

ormqr [Sundials_Matrix.ArrayDense]

ormqr q beta v w work computes the product w = qv .

P
pcg [Sundials_LinearSolver.Iterative]

Krylov iterative solver using the preconditioned conjugate gradient (PCG) method.

potrf [Sundials_Matrix.ArrayDense]

Performs Cholesky factorization of a real symmetric positive matrix.

potrs [Sundials_Matrix.ArrayDense]

potrs a b finds the solution of ax = b using the Cholesky factorization found by Sundials_Matrix.ArrayDense.potrf.

pp [Nvector_pthreads]

Pretty-print a Pthreads nvector using the Format module.

pp [Nvector_openmp]

Pretty-print an OpenMP nvector using the Format module.

pp [Nvector_parallel]

Pretty-print the local portion of a parallel nvector using the Format module.

pp [Nvector_serial]

Pretty-print a serial nvector using the Format module.

pp [Sundials_Matrix.ArrayBand]

Pretty-print a band matrix using the Format module.

pp [Sundials_Matrix.ArrayDense]

Pretty-print an array dense matrix using the Format module.

pp [Sundials_Matrix.Sparse]

Pretty-print a sparse matrix using the Format module.

pp [Sundials_Matrix.Band]

Pretty-print a band matrix using the Format module.

pp [Sundials_Matrix.Dense]

Pretty-print a dense matrix using the Format module.

pp [Sundials.RootDirs]

Pretty-print a root direction array using the Format module.

pp [Sundials.Roots]

Pretty-print a root array using the Format module.

pp [Sundials_LintArray]

Pretty-print an array using the Format module.

pp [Sundials_RealArray2]

Pretty-print an array using the Format module.

pp [Sundials_RealArray]

Pretty-print an array using the Format module.

ppi [Sundials_Matrix.ArrayBand]

Pretty-print an array band matrix using the Format module.

ppi [Sundials_Matrix.Sparse]

Pretty-print a sparse matrix using the Format module.

ppi [Sundials_Matrix.Band]

Pretty-print a band matrix using the Format module.

ppi [Sundials_Matrix.Dense]

Pretty-print a dense matrix using the Format module.

ppi [Sundials.RootDirs]

Pretty-print a root direction array using the Format module.

ppi [Sundials.Roots]

Pretty-print a root array using the Format module.

ppi [Sundials_LintArray]

Pretty-print an array using the Format module.

ppi [Sundials_RealArray2]

Pretty-print an array using the Format module.

ppi [Sundials_RealArray]

Pretty-print an array using the Format module.

prec_both [Cvodes_bbd]

Preconditioning from both sides using the Parallel Band-Block-Diagonal module.

prec_both [Cvode_bbd]

Preconditioning from both sides using the Parallel Band-Block-Diagonal module.

prec_both [Arkode_bbd]

Preconditioning from both sides using the Parallel Band-Block-Diagonal module.

prec_both [Cvodes.Adjoint.Spils.Banded]

Like Cvodes.Adjoint.Spils.Banded.prec_left but preconditions from both sides.

prec_both [Cvodes.Adjoint.Spils]

Left and right preconditioning with sensitivities.

prec_both [Arkode.Mass.Spils]

Left and right preconditioning.

prec_both [Arkode.Spils.Banded]

Like Arkode.Spils.Banded.prec_left but preconditions from both sides.

prec_both [Arkode.Spils]

Left and right preconditioning.

prec_both [Cvode.Spils.Banded]

Like Cvode.Spils.Banded.prec_left but preconditions from both sides.

prec_both [Cvode.Spils]

Left and right preconditioning.

prec_both_with_sens [Cvodes.Adjoint.Spils]

Left and right preconditioning without sensitivities.

prec_left [Idas_bbd]

Left preconditioning using the Parallel Band-Block-Diagonal module.

prec_left [Ida_bbd]

Left preconditioning using the Parallel Band-Block-Diagonal module.

prec_left [Cvodes_bbd]

Left preconditioning using the Parallel Band-Block-Diagonal module.

prec_left [Cvode_bbd]

Left preconditioning using the Parallel Band-Block-Diagonal module.

prec_left [Arkode_bbd]

Left preconditioning using the Parallel Band-Block-Diagonal module.

prec_left [Idas.Adjoint.Spils]

Left preconditioning without forward sensitivities.

prec_left [Cvodes.Adjoint.Spils.Banded]

A band matrix Cvodes.Adjoint.Spils.preconditioner based on difference quotients.

prec_left [Cvodes.Adjoint.Spils]

Left preconditioning without forward sensitivities.

prec_left [Arkode.Mass.Spils]

Left preconditioning.

prec_left [Arkode.Spils.Banded]

A band matrix Arkode.Spils.preconditioner based on difference quotients.

prec_left [Arkode.Spils]

Left preconditioning.

prec_left [Ida.Spils]

Left preconditioning.

prec_left [Cvode.Spils.Banded]

A band matrix Cvode.Spils.preconditioner based on difference quotients.

prec_left [Cvode.Spils]

Left preconditioning.

prec_left_with_sens [Idas.Adjoint.Spils]

Left preconditioning with forward sensitivities.

prec_left_with_sens [Cvodes.Adjoint.Spils]

Left preconditioning with forward sensitiviites.

prec_none [Idas.Adjoint.Spils]

No preconditioning.

prec_none [Cvodes.Adjoint.Spils]

No preconditioning.

prec_none [Arkode.Mass.Spils]

No preconditioning.

prec_none [Arkode.Spils]

No preconditioning.

prec_none [Ida.Spils]

No preconditioning.

prec_none [Kinsol.Spils]

No preconditioning.

prec_none [Cvode.Spils]

No preconditioning.

prec_right [Cvodes_bbd]

Right preconditioning using the Parallel Band-Block-Diagonal module.

prec_right [Cvode_bbd]

Right preconditioning using the Parallel Band-Block-Diagonal module.

prec_right [Arkode_bbd]

Right preconditioning using the Parallel Band-Block-Diagonal module.

prec_right [Kinsol_bbd]

Right preconditioning using the Parallel Band-Block-Diagonal module.

prec_right [Cvodes.Adjoint.Spils.Banded]

Like Cvodes.Adjoint.Spils.Banded.prec_left but preconditions from the right.

prec_right [Cvodes.Adjoint.Spils]

Right preconditioning with sensitivities.

prec_right [Arkode.Mass.Spils]

Right preconditioning.

prec_right [Arkode.Spils.Banded]

Like Arkode.Spils.Banded.prec_left but preconditions from the right.

prec_right [Arkode.Spils]

Right preconditioning.

prec_right [Kinsol.Spils]

Right preconditioning.

prec_right [Cvode.Spils.Banded]

Like Cvode.Spils.Banded.prec_left but preconditions from the right.

prec_right [Cvode.Spils]

Right preconditioning.

prec_right_with_sens [Cvodes.Adjoint.Spils]

Right preconditioning without sensitivities.

print_band [Sundials_Matrix]

Prints a band matrix to the given log file.

print_dense [Sundials_Matrix]

Prints a dense matrix to the given log file.

print_integrator_stats [Idas.Adjoint]

Prints the integrator statistics on the given channel.

print_integrator_stats [Cvodes.Adjoint]

Prints the integrator statistics on the given channel.

print_integrator_stats [Arkode]

Prints the integrator statistics on the given channel.

print_integrator_stats [Ida]

Prints the integrator statistics on the given channel.

print_integrator_stats [Cvode]

Prints the integrator statistics on the given channel.

print_sparse [Sundials_Matrix]

Prints a sparse matrix to the given log file.

Q
qr_fact [Sundials_LinearSolver.Iterative.Algorithms]

Performs a QR factorization of a Hessenberg matrix.

qr_sol [Sundials_LinearSolver.Iterative.Algorithms]

Solve the linear least squares problem.

R
reinit [Idas_bbd]

Reinitializes some BBD preconditioner parameters.

reinit [Ida_bbd]

Reinitializes some BBD preconditioner parameters.

reinit [Cvodes_bbd]

Reinitializes some BBD preconditioner parameters.

reinit [Cvode_bbd]

Reinitializes some BBD preconditioner parameters.

reinit [Arkode_bbd]

Reinitializes some BBD preconditioner parameters.

reinit [Idas.Adjoint.Quadrature]

This function reinitializes the integration of quadrature equations during the backward phase.

reinit [Idas.Adjoint]

Reinitializes the backward problem with new parameters and state values.

reinit [Idas.Sensitivity.Quadrature]

Reinitializes the quadrature sensitivity integration.

reinit [Idas.Sensitivity]

Reinitializes the forward sensitivity computation.

reinit [Idas.Quadrature]

Reinitializes the integration of quadrature equations.

reinit [Cvodes.Adjoint.Quadrature]

This function reinitializes the integration of quadrature equations during the backward phase.

reinit [Cvodes.Adjoint]

Reinitializes the backward problem with new parameters and state values.

reinit [Cvodes.Sensitivity.Quadrature]

Reinitializes the quadrature sensitivity integration.

reinit [Cvodes.Sensitivity]

Reinitializes the forward sensitivity computation.

reinit [Cvodes.Quadrature]

Reinitializes the integration of quadrature equations.

reinit [Arkode]

Reinitializes the solver with new parameters and state values.

reinit [Ida]

Reinitializes the solver with new parameters and state values.

reinit [Cvode]

Reinitializes the solver with new parameters and state values.

reinit [Sundials_LinearSolver.Direct.Klu]

Reinitializes memory and flags for a new factorization (symbolic and numeric) at the next solver setup call.

reset [Sundials.Roots]

Resets all elements to NoRoot.

resize [Arkode]

Change the number of equations and unknowns between integrator steps.

resize [Sundials_Matrix.Sparse]

Reallocates the underlying arrays to the given number of non-zero elements, or otherwise to the current number of non-zero elements .

rising [Sundials.Roots]

Returns true only if the specified element is Rising.

S
scale [Sundials_Matrix.ArrayBand]

scale c a multiplies each element of the band matrix a by c.

scale [Sundials_Matrix.ArrayDense]

Multiplies each element by a constant.

scale_add [Sundials_Matrix.ArrayBand]

scale_add c a b calculates $A = cA + B$.

scale_add [Sundials_Matrix.ArrayDense]

scale_add c A B calculates $A = cA + B$.

scale_add [Sundials_Matrix.Sparse]

scale_add c A B calculates $A = cA + B$.

scale_add [Sundials_Matrix.Band]

scale_add c A B calculates $A = cA + B$.

scale_add [Sundials_Matrix.Dense]

scale_add c A B calculates $A = cA + B$.

scale_add [Sundials_Matrix]

scale_add c A B calculates $A = cA + B$.

scale_addi [Sundials_Matrix.ArrayBand]

scale_addi ml c A calculates $A = cA + I$.

scale_addi [Sundials_Matrix.ArrayDense]

scale_addi c A calculates $A = cA + I$.

scale_addi [Sundials_Matrix.Sparse]

scale_addi c A calculates $A = cA + I$.

scale_addi [Sundials_Matrix.Band]

scale_addi c A calculates $A = cA + I$.

scale_addi [Sundials_Matrix.Dense]

scale_addi c A calculates $A = cA + I$.

scale_addi [Sundials_Matrix]

scale_addi c A calculates $A = cA + I$.

set [Sundials_Matrix.ArrayBand]

set a i j v sets the value at row i and column j of a to v.

set [Sundials_Matrix.ArrayDense]

set a i j v sets the value at row i and column j of a to v.

set [Sundials_Matrix.Sparse]

set a idx i v sets the idxth row/column to i and its value to v.

set [Sundials_Matrix.Band]

set a i j v sets the value at row i and column j of a to v.

set [Sundials_Matrix.Dense]

set a i j v sets the value at row i and column j of a to v.

set [Sundials.RootDirs]

set r i v sets the ith element of r to v.

set [Sundials.Roots]

set r i v sets the ith element of r to v.

set [Sundials_RealArray2]

set a i j v sets the value at row i and column j of a to v.

set_adaptivity_method [Arkode]

Specifies the method and associated parameters used for time step adaptivity.

set_all_root_directions [Arkode]

Like Arkode.set_root_direction but specifies a single direction for all root functions.

set_all_root_directions [Ida]

Like Ida.set_root_direction but specifies a single direction for all root functions.

set_all_root_directions [Cvode]

Like Cvode.set_root_direction but specifies a single direction for all root functions.

set_ark_table_num [Arkode]

Use specific built-in Butcher tables for an ImEx system.

set_ark_tables [Arkode]

Specifies a customized Butcher table pair for the additive RK method.

set_cfl_fraction [Arkode]

Specifies the fraction of the estimated explicitly stable step to use.

set_col [Sundials_Matrix.Sparse]

set_col a j idx sets the data index of column j to idx.

set_colval [Sundials_Matrix.Sparse]

set_colval a idx i sets the idxth column to i.

set_constraints [Ida]

Specifies a vector defining inequality constraints for each component of the solution vector u.

set_constraints [Kinsol]

Specifies a vector defining inequality constraints for each component of the solution vector u.

set_data [Sundials_Matrix.Sparse]

set_data a idx v sets the value of the idxth row v.

set_defaults [Arkode]

Resets all optional input parameters to their default values.

set_delta_gamma_max [Arkode]

Specifies a scaled step size ratio tolerance beyond which the linear solver setup routine will be signalled.

set_dense_order [Arkode]

Specifies the order of accuracy for the polynomial interpolant used for dense output.

set_diagnostics [Arkode]

Write step adaptivity and solver diagnostics to the given file.

set_dq_method [Idas.Sensitivity]

Sets the difference quotient strategy when sensitivity equations are computed internally by the solver rather than via callback.

set_dq_method [Cvodes.Sensitivity]

Sets the difference quotient strategy when sensitivity equations are computed internally by the solver rather than via callback.

set_eps_lin [Idas.Adjoint.Spils]

Sets the factor by which the Krylov linear solver's convergence test constant is reduced from the Newton iteration test constant.

set_eps_lin [Cvodes.Adjoint.Spils]

Sets the factor by which the Krylov linear solver's convergence test constant is reduced from the Newton iteration test constant.

set_eps_lin [Arkode.Mass.Spils]

Sets the factor by which the Krylov linear solver's convergence test constant is reduced from the Newton iteration test constant.

set_eps_lin [Arkode.Spils]

Sets the factor by which the Krylov linear solver's convergence test constant is reduced from the Newton iteration test constant.

set_eps_lin [Ida.Spils]

Sets the factor by which the Krylov linear solver's convergence test constant is reduced from the Newton iteration test constant.

set_eps_lin [Cvode.Spils]

Sets the factor by which the Krylov linear solver's convergence test constant is reduced from the Newton iteration test constant.

set_erk_table [Arkode]

Specifies a customized Butcher table pair for the explicit portion of the system.

set_erk_table_num [Arkode]

Use specific built-in Butcher tables for an explicit integration of the problem.

set_err_con [Idas.Sensitivity]

Sets whether sensitivity variables are used in the error control mechanism.

set_err_con [Cvodes.Sensitivity]

Sets whether sensitivity variables are used in the error control mechanism.

set_err_handler_fn [Arkode]

Specifies a custom function for handling error messages.

set_err_handler_fn [Ida]

Specifies a custom function for handling error messages.

set_err_handler_fn [Kinsol]

Specifies a custom function for handling error messages.

set_err_handler_fn [Cvode]

Specifies a custom function for handling error messages.

set_error_bias [Arkode]

Specifies the bias to apply to the error estimates within accuracy-based adaptivity strategies.

set_error_file [Arkode]

Configure the default error handler to write messages to a file.

set_error_file [Ida]

Configure the default error handler to write messages to a file.

set_error_file [Kinsol]

Configure the default error handler to write messages to a file.

set_error_file [Cvode]

Configure the default error handler to write messages to a file.

set_eta_choice [Kinsol]

Specifies the method for computing the value of the eta coefficient used in the calculation of the linear solver convergence tolerance.

set_explicit [Arkode]

Disables the implicit portion of a problem.

set_falling [Sundials.Roots]

set_falling r i sets the ith element of r to Falling.

set_fixed_point [Arkode]

Solve the implicit portion of the problem using the accelerated fixed-point solver instead of the modified Newton iteration.

set_fixed_step [Arkode]

Disables time step adaptivity and fix the step size for all internal steps.

set_fixed_step_bounds [Arkode]

Specifies the step growth interval in which the step size will remain unchanged.

set_func_norm_tol [Kinsol]

Specifies the stopping tolerance on the scaled maximum norm.

set_gs_type [Sundials_LinearSolver.Iterative]

Sets the Gram-Schmidt orthogonalization to use.

set_id [Idas.Adjoint]

Class components of the state vector as either algebraic or differential.

set_id [Ida]

Class components of the state vector as either algebraic or differential.

set_imex [Arkode]

Enables both the implicit and explicit portions of a problem.

set_implicit [Arkode]

Disables the explicit portion of a problem.

set_info_file [Kinsol]

Write informational (non-error) messages to the given file.

set_info_handler_fn [Kinsol]

Specifies a custom function for handling informational (non-error) messages.

set_init_setup [Kinsol]

Specifies that an initial call to the preconditioner setup function should be made (the default).

set_init_step [Idas.Adjoint]

Specifies the initial step size.

set_init_step [Cvodes.Adjoint]

Specifies the initial step size.

set_init_step [Arkode]

Specifies the initial step size.

set_init_step [Ida]

Specifies the initial step size.

set_init_step [Cvode]

Specifies the initial step size.

set_irk_table [Arkode]

Specifies a customized Butcher table pair for the implicit portion of the system.

set_irk_table_num [Arkode]

Use specific built-in Butcher tables for an implicit integration of the problem.

set_jac_times [Idas.Adjoint.Spils]

Change the Jacobian-times-vector function.

set_jac_times [Cvodes.Adjoint.Spils]

Change the Jacobian-times-vector function.

set_jac_times [Arkode.Spils]

Change the Jacobian-times-vector function.

set_jac_times [Ida.Spils]

Change the Jacobian-times-vector function.

set_jac_times [Kinsol.Spils]

Change the Jacobian-times-vector function.

set_jac_times [Cvode.Spils]

Change the Jacobian-times-vector function.

set_line_search_ic [Ida]

Enables (true) or disables (false) the linesearch algorithm in the initial condition calculation.

set_linear [Arkode]

Specifies that the implicit portion of the problem is linear.

set_max_backs_ic [Ida]

Specifies the maximum number of linesearch backtracks allowed in any Newton iteration, when solving the initial conditions calculation problem.

set_max_beta_fails [Kinsol]

Specifies the maximum number of beta-condition failures in the line search algorithm.

set_max_cfail_growth [Arkode]

Specifies the maximum step size growth factor upon a convergence failure on a stage solve within a step.

set_max_conv_fails [Arkode]

Specifies the maximum number of nonlinear solver convergence failures permitted during one step.

set_max_conv_fails [Ida]

Specifies the maximum number of nonlinear solver convergence failures permitted during one step.

set_max_conv_fails [Cvode]

Specifies the maximum number of nonlinear solver convergence failures permitted during one step.

set_max_efail_growth [Arkode]

Specifies the maximum step size growth factor upon multiple successive accuracy-based error failures in the solver.

set_max_err_test_fails [Arkode]

Specifies the maximum number of error test failures permitted in attempting one step.

set_max_err_test_fails [Ida]

Specifies the maximum number of error test failures permitted in attempting one step.

set_max_err_test_fails [Cvode]

Specifies the maximum number of error test failures permitted in attempting one step.

set_max_first_growth [Arkode]

Specifies the maximum allowed step size change following the very first integration step.

set_max_growth [Arkode]

Specifies the maximum growth of the step size between consecutive time steps.

set_max_hnil_warns [Arkode]

Specifies the maximum number of messages warning that t + h = t on the next internal step.

set_max_hnil_warns [Cvode]

Specifies the maximum number of messages warning that t + h = t on the next internal step.

set_max_newton_step [Kinsol]

Specifies the maximum allowable scaled length of the Newton step.

set_max_nonlin_iters [Idas.Sensitivity]

Specifies the maximum number of nonlinear solver iterations for sensitivity variables permitted per step.

set_max_nonlin_iters [Cvodes.Sensitivity]

Sets the maximum number of nonlinear solver iterations for sensitivity variables permitted per step.

set_max_nonlin_iters [Arkode]

Specifies the maximum number of nonlinear solver iterations permitted per RK stage at each step.

set_max_nonlin_iters [Ida]

Specifies the maximum number of nonlinear solver iterations permitted per step.

set_max_nonlin_iters [Cvode]

Specifies the maximum number of nonlinear solver iterations permitted per step.

set_max_num_iters_ic [Ida]

Specifies the maximum number of Newton iterations allowed in any one attempt to calculate initial conditions.

set_max_num_jacs_ic [Ida]

Specifies the maximum number of approximate Jacobian or preconditioner evaluations allowed when the Newton iteration appears to be slowly converging.

set_max_num_steps [Idas.Adjoint]

Specifies the maximum number of steps taken in attempting to reach a given output time.

set_max_num_steps [Cvodes.Adjoint]

Specifies the maximum number of steps taken in attempting to reach a given output time.

set_max_num_steps [Arkode]

Specifies the maximum number of steps taken in attempting to reach a given output time.

set_max_num_steps [Ida]

Specifies the maximum number of steps taken in attempting to reach a given output time.

set_max_num_steps [Cvode]

Specifies the maximum number of steps taken in attempting to reach a given output time.

set_max_num_steps_ic [Ida]

Specifies the maximum number of steps taken in attempting to reach a given output time in the initial condition calculation.

set_max_ord [Idas.Adjoint]

Specifies the maximum order of the linear multistep method.

set_max_ord [Cvodes.Adjoint]

Specifies the maximum order of the linear multistep method.

set_max_ord [Ida]

Specifies the maximum order of the linear multistep method.

set_max_ord [Cvode]

Specifies the maximum order of the linear multistep method.

set_max_restarts [Sundials_LinearSolver.Iterative]

Sets the number of GMRES restarts to allow.

set_max_setup_calls [Kinsol]

Specifies the maximum number of nonlinear iterations between calls to the preconditioner setup function.

set_max_step [Idas.Adjoint]

Specifies an upper bound on the magnitude of the step size.

set_max_step [Cvodes.Adjoint]

Specifies an upper bound on the magnitude of the step size.

set_max_step [Arkode]

Specifies an upper bound on the magnitude of the step size.

set_max_step [Ida]

Specifies an upper bound on the magnitude of the step size.

set_max_step [Cvode]

Specifies an upper bound on the magnitude of the step size.

set_max_steps_between_lset [Arkode]

Specifies the frequency of calls to the linear solver setup routine.

set_max_sub_setup_calls [Kinsol]

Specifies the maximum number of nonlinear iterations between checks by the residual monitoring algorithm.

set_maxl [Sundials_LinearSolver.Iterative]

Updates the number of linear solver iterations to allow.

set_min_eps [Kinsol]

Specifies that the scaled linear residual tolerance (epsilon) is bounded from below.

set_min_step [Cvodes.Adjoint]

Specifies a lower bound on the magnitude of the step size.

set_min_step [Arkode]

Specifies a lower bound on the magnitude of the step size.

set_min_step [Cvode]

Specifies a lower bound on the magnitude of the step size.

set_newton [Arkode]

Solve the implicit portion of the problem using the modified Newton solver.

set_no_inactive_root_warn [Arkode]

Disables issuing a warning if some root function appears to be identically zero at the beginning of the integration.

set_no_inactive_root_warn [Ida]

Disables issuing a warning if some root function appears to be identically zero at the beginning of the integration.

set_no_inactive_root_warn [Cvode]

Disables issuing a warning if some root function appears to be identically zero at the beginning of the integration.

set_no_init_setup [Kinsol]

Specifies that an initial call to the preconditioner setup function should not be made.

set_no_min_eps [Kinsol]

Specifies that the scaled linear residual tolerance (epsilon) is not bounded from below.

set_no_res_mon [Kinsol]

Disables the nonlinear residual monitoring scheme that controls Jacobian updating.

set_no_sensitivity [Idas.Adjoint]

Cancels the storage of sensitivity checkpointing data during forward solution (with Idas.Adjoint.forward_normal or Idas.Adjoint.forward_one_step).

set_no_sensitivity [Cvodes.Adjoint]

Cancels the storage of sensitivity checkpointing data during forward solution (with Cvodes.Adjoint.forward_normal or Cvodes.Adjoint.forward_one_step).

set_nonlin_conv_coef [Arkode]

Specifies the safety factor used in the nonlinear convergence test.

set_nonlin_conv_coef [Ida]

Specifies the safety factor used in the nonlinear convergence test.

set_nonlin_conv_coef [Cvode]

Specifies the safety factor used in the nonlinear convergence test.

set_nonlin_conv_coef_ic [Ida]

Specifies the positive constant in the nonlinear convergence test of the initial condition calculation.

set_nonlin_crdown [Arkode]

Specifies the constant used in estimating the nonlinear solver convergence rate.

set_nonlin_rdiv [Arkode]

Specifies the nonlinear correction threshold beyond which the iteration will be declared divergent.

set_nonlinear [Arkode]

Specifies that the implicit portion of the problem is nonlinear.

set_noroot [Sundials.Roots]

set_noroot r i sets the ith element of r to NoRoot.

set_optimal_params [Arkode]

Sets all adaptivity and solver parameters to ‘best guess’ values.

set_ordering [Sundials_LinearSolver.Direct.Superlumt]

Sets the ordering algorithm used to minimize fill-in.

set_ordering [Sundials_LinearSolver.Direct.Klu]

Sets the ordering algorithm used to minimize fill-in.

set_postprocess_step_fn [Arkode]

Set a post processing step function.

set_prec_type [Sundials_LinearSolver.Iterative]

Change the preconditioning direction without modifying callback functions.

set_preconditioner [Idas.Adjoint.Spils]

Change the preconditioner functions without using forward sensitivities.

set_preconditioner [Cvodes.Adjoint.Spils]

Change the preconditioner functions without using forward sensitivities.

set_preconditioner [Arkode.Mass.Spils]

Change the preconditioner functions.

set_preconditioner [Arkode.Spils]

Change the preconditioner functions.

set_preconditioner [Ida.Spils]

Change the preconditioner functions.

set_preconditioner [Kinsol.Spils]

Change the preconditioner functions.

set_preconditioner [Cvode.Spils]

Change the preconditioner functions.

set_preconditioner_with_sens [Idas.Adjoint.Spils]

Change the preconditioner functions using forward sensitivities.

set_preconditioner_with_sens [Cvodes.Adjoint.Spils]

Change the preconditioner functions using forward sensitivities.

set_predictor_method [Arkode]

Specifies the method for predicting implicit solutions.

set_print_level [Kinsol]

Sets the level of verbosity of informational messages.

set_rel_err_func [Kinsol]

Specifies the relative error in computing $F(u)$, which is used in the difference quotient approximation of the Jacobian-vector product.

set_res_mon [Kinsol]

Enables the nonlinear residual monitoring scheme that controls Jacobian updating.

set_res_mon_const_value [Kinsol]

Specifies the constant value of omega when using residual monitoring.

set_res_mon_params [Kinsol]

Specifies the minimum and maximum values in the formula for omega.

set_res_tolerance [Arkode]

Sets the residual tolerance.

set_rising [Sundials.Roots]

set_rising r i sets the ith element of r to Rising.

set_root_direction [Arkode]

set_root_direction s dir specifies the direction of zero-crossings to be located and returned.

set_root_direction [Ida]

set_root_direction s dir specifies the direction of zero-crossings to be located and returned.

set_root_direction [Cvode]

set_root_direction s dir specifies the direction of zero-crossings to be located and returned.

set_row [Sundials_Matrix.Sparse]

set_row a j idx sets the data index of row j to idx.

set_rowval [Sundials_Matrix.Sparse]

set_rowval a idx i sets the idxth row to i.

set_safety_factor [Arkode]

Specifies the safety factor to be applied to the accuracy-based estimated step.

set_scaled_step_tol [Kinsol]

Specifies the stopping tolerance on the minimum scaled step length, which must be greater than zero.

set_sfdotjp [Kinsol.Alternate]

Sets the internal sfdotJp value.

set_sjpnorm [Kinsol.Alternate]

Sets the internal sJpnorm value.

set_small_num_efails [Arkode]

Specifies the threshold for “multiple” successive error failures before the factor from Arkode.set_max_efail_growth is applied.

set_stab_lim_det [Cvodes.Adjoint]

Indicates whether the BDF stability limit detection algorithm should be used.

set_stab_lim_det [Cvode]

Indicates whether the BDF stability limit detection algorithm should be used.

set_stability_fn [Arkode]

Sets a problem-dependent function to estimate a stable time step size for the explicit portion of the ODE system.

set_step_tolerance_ic [Ida]

Specifies a positive lower bound on the Newton step in the initial condition calculation.

set_stop_time [Arkode]

Limits the value of the independent variable t when solving.

set_stop_time [Ida]

Limits the value of the independent variable t when solving.

set_stop_time [Cvode]

Limits the value of the independent variable t when solving.

set_suppress_alg [Idas.Adjoint]

Indicates whether or not to ignore algebraic variables in the local error test.

set_suppress_alg [Ida]

Indicates whether or not to ignore algebraic variables in the local error test.

set_sys_func [Kinsol]

Changes the system function.

set_times [Arkode.Mass.Spils]

Change the mass matrix-times-vector function.

set_to_zero [Sundials_Matrix.ArrayBand]

Fills the matrix with zeros.

set_to_zero [Sundials_Matrix.ArrayDense]

Fills the matrix with zeros.

set_to_zero [Sundials_Matrix.Sparse]

Fills a matrix with zeros.

set_to_zero [Sundials_Matrix.Band]

Fills a matrix with zeros.

set_to_zero [Sundials_Matrix.Dense]

Fills a matrix with zeros.

set_to_zero [Sundials_Matrix]

Fills a matrix with zeros.

set_tolerances [Idas.Adjoint.Quadrature]

Specify how to use quadrature variables in step size control.

set_tolerances [Idas.Sensitivity.Quadrature]

Specify how to use quadrature sensitivities in step size control.

set_tolerances [Idas.Sensitivity]

Specify the integration tolerances for sensitivities.

set_tolerances [Idas.Quadrature]

Specify how to use quadrature variables in step size control.

set_tolerances [Cvodes.Adjoint.Quadrature]

Specify how to use quadrature variables in step size control.

set_tolerances [Cvodes.Adjoint]

Sets the integration tolerances for the backward problem.

set_tolerances [Cvodes.Sensitivity.Quadrature]

Specify how to use quadrature sensitivities in step size control.

set_tolerances [Cvodes.Sensitivity]

Sets the integration tolerances for sensitivities.

set_tolerances [Cvodes.Quadrature]

Specify how to use quadrature variables in step size control.

set_tolerances [Arkode]

Sets the integration tolerances.

set_tolerances [Ida]

Set the integration tolerances.

set_tolerances [Cvode]

Sets the integration tolerances.

sformat [Sundials_Matrix.Sparse]

Return the matrix format.

size [Sundials_Matrix.ArrayBand]

m, n = size a returns the numbers of rows m and columns n of a.

size [Sundials_Matrix.ArrayDense]

m, n = size a returns the numbers of columns m and rows n of a.

size [Sundials_Matrix.Sparse]

m, n = size a returns the numbers of columns m and rows n of a.

size [Sundials_Matrix.Band]

m, n = size a returns the numbers of rows m and columns n of a.

size [Sundials_Matrix.Dense]

m, n = size a returns the numbers of columns m and rows n of a.

size [Sundials_RealArray2]

nr, nc = size a returns the numbers of rows nr and columns nc of a

small_real [Sundials_Config]

The smallest value representable as a real.

solve [Kinsol]

Computes an approximate solution to a nonlinear system.

solve_normal [Arkode]

Integrates an ODE system over an interval.

solve_normal [Ida]

Integrates a DAE system over an interval.

solve_normal [Cvode]

Integrates an ODE system over an interval.

solve_one_step [Arkode]

Like Arkode.solve_normal but returns after one internal solver step.

solve_one_step [Ida]

Like Ida.solve_normal but returns after one internal solver step.

solve_one_step [Cvode]

Like Cvode.solve_normal but returns after one internal solver step.

solver [Idas.Adjoint.Alternate]

Creates a linear solver from a function returning a set of callbacks.

solver [Idas.Adjoint.Spils]

Create a Idas-specific linear solver from a generic iterative linear solver.

solver [Idas.Adjoint.Dls]

Create an Idas-specific linear solver from a Jacobian approximation function and a generic direct linear solver.

solver [Cvodes.Adjoint.Alternate]

Creates a linear solver from a function returning a set of callbacks.

solver [Cvodes.Adjoint.Spils]

Create a Cvodes-specific linear solver from a generic iterative linear solver.

solver [Cvodes.Adjoint.Dls]

Create a Cvodes-specific linear solver from a a Jacobian approximation function and a generic direct linear solver.

solver [Cvodes.Adjoint.Diag]

A linear solver based on Jacobian approximation by difference quotients.

solver [Arkode.Mass.Alternate]

Creates a mass matrix solver from a function returning a set of callbacks.

solver [Arkode.Mass.Spils]

Create an Arkode-specific mass linear solver from a generic iterative linear solver.

solver [Arkode.Mass.Dls]

Create an Arkode-specific mass linear solver from a mass-matrix constructor function and a generic dense linear solver.

solver [Arkode.Alternate]

Creates a linear solver from a function returning a set of callbacks.

solver [Arkode.Spils]

Create an Arkode-specific linear solver from a generic iterative linear solver.

solver [Arkode.Dls]

Create an Arkode-specific linear solver from a Jacobian approximation function and a generic direct linear solver.

solver [Ida.Alternate]

Creates a linear solver from a function returning a set of callbacks.

solver [Ida.Spils]

Create an Ida-specific linear solver from a generic iterative linear solver.

solver [Ida.Dls]

Create an Ida-specific linear solver from a Jacobian approximation function and a generic direct linear solver.

solver [Kinsol.Alternate]

Creates a linear solver from a function returning a set of callbacks.

solver [Kinsol.Spils]

Create a Cvode-specific linear solver from a generic iterative linear solver.

solver [Kinsol.Dls]

Create a Kinsol-specific linear solver from a Jacobian approximation function and a generic direct linear solver.

solver [Cvode.Alternate]

Creates a linear solver from a function returning a set of callbacks.

solver [Cvode.Spils]

Create a Cvode-specific linear solver from a generic iterative linear solver.

solver [Cvode.Dls]

Create a Cvode-specific linear solver from a Jacobian approximation function and generic direct linear solver.

solver [Cvode.Diag]

A linear solver based on Jacobian approximation by difference quotients.

space [Sundials_Matrix.ArrayBand]

lrw, liw = space a returns the storage requirements of a as lrw realtype words and liw integer words.

space [Sundials_Matrix.ArrayDense]

lrw, liw = space a returns the storage requirements of a as lrw realtype words and liw integer words.

space [Sundials_Matrix.Sparse]

lrw, liw = space a returns the storage requirements of a as lrw realtype words and liw integer words.

space [Sundials_Matrix.Band]

lrw, liw = space a returns the storage requirements of a as lrw realtype words and liw integer words.

space [Sundials_Matrix.Dense]

lrw, liw = space a returns the storage requirements of a as lrw realtype words and liw integer words.

space [Sundials_Matrix]

lrw, liw = space a returns the storage requirements of a as lrw realtype words and liw integer words.

sparse_csc [Sundials_Matrix]

By default, sparse_csc n returns an n by n sparse matrix in CSC format with the capacity for n / 10 non-zero elements and all elements initialized to 0.0.

sparse_csr [Sundials_Matrix]

As for Sundials_Matrix.sparse_csc but the returned matrix is in CSR format.

spbcgs [Sundials_LinearSolver.Iterative]

Krylov iterative solver using the scaled preconditioned biconjugate stabilized (Bi-CGStab) method.

spfgmr [Sundials_LinearSolver.Iterative]

Krylov iterative solver using the scaled preconditioned flexible generalized minimum residual (GMRES) method.

spgmr [Sundials_LinearSolver.Iterative]

Krylov iterative solver using the scaled preconditioned generalized minimum residual (GMRES) method.

sptfqmr [Sundials_LinearSolver.Iterative]

Krylov iterative with the scaled preconditioned transpose-free quasi-minimal residual (SPTFQMR) method.

stderr [Sundials_Logfile]

The stderr file.

stdout [Sundials_Logfile]

The stdout file.

sub [Sundials_RealArray]

Access a sub-array of the given array without copying.

sundials_version [Sundials_Config]

The major, minor, and patch version numbers of the underlying Sundials/C library.

superlumt [Sundials_LinearSolver.Direct]

Creates a direct linear solver on sparse matrices using SuperLUMT.

superlumt_enabled [Sundials_Config]

Indicates whether the SuperLU_MT sparse linear solver is available.

T
to_array [Sundials.RootDirs]

Creates a new array from the contents of a given value.

to_array [Sundials.Roots]

Creates a new array from the contents of a given value.

to_array [Sundials_RealArray]

Copies into a new float array.

to_float [Ida.VarId]

Map id values to floating-point constants.

to_float [Sundials.Constraint]

Map constraint values to floating-point constants.

to_list [Sundials.RootDirs]

Copies into a list.

to_list [Sundials.Roots]

Copies into a list.

to_list [Sundials_RealArray]

Copies into a float list.

toggle_off [Idas.Sensitivity]

Deactivates forward sensitivity calculations without deallocating memory.

toggle_off [Cvodes.Sensitivity]

Deactivates forward sensitivity calculations without deallocating memory.

U
unconstrained [Sundials.Constraint]

The constant 0.0.

unit_roundoff [Sundials_Config]

The difference bewteen 1.0 and the minimum real greater than 1.0.

unwrap [Nvector_pthreads]

Aliases Nvector.unwrap.

unwrap [Nvector_openmp]

Aliases Nvector.unwrap.

unwrap [Nvector_parallel]

Aliases Nvector.unwrap.

unwrap [Nvector_array.ARRAY_NVECTOR]

Returns the array underlying an nvector.

unwrap [Nvector_serial]

Aliases Nvector.unwrap.

unwrap [Nvector]

unwrap nv returns the data underlying the nvector nv.

unwrap [Sundials_LinearSolver.Iterative.Custom]

Return the internal state from an custom iterative linear solver.

unwrap [Sundials_LinearSolver.Direct.Custom]

Return the internal state from an custom direct linear solver.

unwrap [Sundials_Matrix.ArrayBand]

Direct access to the underlying storage array, which is accessed column first (unlike in Sundials_Matrix.ArrayBand.get).

unwrap [Sundials_Matrix.ArrayDense]

Direct access to the underlying storage array, which is accessed column first (unlike in Sundials_Matrix.ArrayDense.get).

unwrap [Sundials_Matrix.Sparse]

Direct access to the underlying sparse storage arrays.

unwrap [Sundials_Matrix.Band]

Direct access to the underlying storage array, which is accessed column first (unlike in Sundials_Matrix.Band.get).

unwrap [Sundials_Matrix.Dense]

Direct access to the underlying storage array, which is accessed column first (unlike in Sundials_Matrix.Dense.get).

unwrap [Sundials_Matrix]

Direct access to the underlying storage array, which is accessed column first (unlike in Sundials_Matrix.Dense.get, Sundials_Matrix.Band.get, and Sundials_Matrix.Sparse.get).

unwrap [Sundials_RealArray2]

Returns the Sundials_RealArray2.data array behind a matrix.

update [Sundials_Matrix.ArrayBand]

update a i j f sets the value at row i and column j of a to f v.

update [Sundials_Matrix.ArrayDense]

update a i j f sets the value at row i and column j of a to f v.

update [Sundials_Matrix.Band]

update a i j f sets the value at row i and column j of a to f v.

update [Sundials_Matrix.Dense]

update a i j f sets the value at row i and column j of a to f v.

V
version [Sundials_Config]
W
wrap [Nvector_pthreads]

wrap nthreads a creates a new Pthreads nvector with nthreads threads over the elements of a.

wrap [Nvector_openmp]

wrap nthreads a creates a new OpenMP nvector with nthreads threads over the elements of a.

wrap [Nvector_array.ARRAY_NVECTOR]

Lifts an array to an nvector.

wrap [Nvector_serial]

wrap a creates a new serial nvector over the elements of a.

wrap [Nvector.NVECTOR]

Wrap data in an nvector.

wrap [Sundials_RealArray2]

Creates a new matrix from an existing Sundials_RealArray2.data array.

wrap_arrayband [Sundials_Matrix]

Creates an (array-based band) matrix by wrapping an existing array-based band matrix.

wrap_arraydense [Sundials_Matrix]

Creates an (array-based dense) matrix by wrapping an existing array-based dense matrix.

wrap_band [Sundials_Matrix]

Creates a (band) matrix by wrapping an existing band matrix.

wrap_custom [Sundials_Matrix]

Wrap a custom matrix value.

wrap_dense [Sundials_Matrix]

Creates a (dense) matrix by wrapping an existing dense matrix.

wrap_sparse [Sundials_Matrix]

Creates a (sparse) matrix by wrapping an existing sparse matrix.