Index of types

Arguments for Arkode.Common.adaptivity_fns.

A function implementing a time step adaptivity algorithm that chooses an $h$ that satisfies the error tolerances.

Asymptotic error control algorithms.

Parameters for the standard adaptivity algorithms.

The type of a generic nvector.

Additive Butcher tables

Type argument representing the ARKStep time-stepping module.

Generic matrix with array-based band content.

Generic matrix with array-based dense content.

A function atimesfn v z computes the action of the system matrix on the vector v, storing the result in z.

A function atimesfn v z computes the action of the system matrix on the vector v, storing the result in z.

Generic matrix with Band content.

The range of nonzero entries in a band matrix.

The range of nonzero entries in a band matrix.

The range of nonzero entries in a band matrix.

The bandwidths for the difference quotient Jacobian operation.

The bandwidths for the difference quotient Jacobian operation.

The bandwidths for the difference quotient Jacobian operation.

The bandwidths for the difference quotient Jacobian operation.

The bandwidths for the difference quotient Jacobian operation.

The bandwidths for the difference quotient Jacobian operation.

These functions compute the quadrature equation right-hand side for the backward problem.

These functions compute the quadrature equation right-hand side for the backward problem.

Arguments common to Idas.Adjoint.Quadrature.bquadrhsfn_no_sens and Idas.Adjoint.Quadrature.bquadrhsfn_with_sens.

Arguments common to Cvodes.Adjoint.Quadrature.bquadrhsfn_no_sens and Cvodes.Adjoint.Quadrature.bquadrhsfn_with_sens.

Functions defining backward quadrature variables without forward sensitivities.

Functions defining backward quadrature variables without forward sensitivities.

Functions defining backward quadrature variables that depend on forward sensitivities.

Functions defining backward quadrature variables with forward sensitivities.

Functions that evaluate the right-hand side of a backward DAE system with or without forward sensitivities.

Arguments for backward functions.

Backward functions without forward sensitivities.

Backward functions with forward sensitivities.

Functions that evaluate the right-hand side of a backward ODE system with or without forward sensitivities.

Arguments common to Cvodes.Adjoint.brhsfn_no_sens and Cvodes.Adjoint.brhsfn_with_sens.

Backward functions without forward sensitivities.

Backward functions with forward sensitivities.

A backward session with the IDAS solver.

A backward session with the CVODES solver.

A callback function into the underlying library.

Functions that perform the interprocess communication necessary for the execution of Idas_bbd.local_fn.

Functions that perform the interprocess communication necessary for the execution of Ida_bbd.local_fn.

Functions that perform the interprocess communication necessary for the execution of Cvodes_bbd.local_fn.

Functions that perform the interprocess communication necessary for the execution of Cvode_bbd.local_fn.

Functions that perform the interprocess communication necessary for the execution of Arkode_bbd.local_fn.

Functions that perform the interprocess communication necessary for the execution of Kinsol_bbd.local_fn.

Represents an MPI communicator without introducing any unwanted dependencies on MPI.

Values returned by convergence tests.

A convergence test callback provided by an integrator.

A convergence test callback provided by an integrator with sensitivities.

A convergence test provided either by an integrator or a user program.

A function providing a convergence test.

Available coupling tables.

Compressed-sparse-column format.

Compressed-sparse-row format.

Distinguishes a user-supplied matrix from a standard one.

Values indicating which types of roots are sought.

Pthreads nvectors are based on bigarrays of floats.

OpenMP nvectors are based on bigarrays of floats.

The data in underlying nvectors is exposed as an array of wrapped values together with an MPI communicator.

The data in underlying nvectors is exposed as an array of wrapped values together with an MPI communicator and the sum of their lengths.

Parallel nvectors carry triples of a local bigarray of floats, a global length, and an MPI communicator.

The type of an array to be wrapped as an Nvector.t.

Type of the underlying array.

The data in underlying nvectors is exposed as an array of wrapped values paired with the sum of their lengths.

Serial nvectors are based on bigarrays of floats.

The data wrapped within an nvector.

An alias for two-dimensional Bigarrays of floating-point numbers.

Generic matrix with Dense content.

Band matrix dimensions.

Implicit Butcher tables

The operations required to implement a direct linear solver.

Workspaces with two temporary vectors.

Workspaces with two temporary vectors.

Workspaces with two temporary vectors.

A difference quotient strategy.

A difference quotient strategy.

Explicit Butcher tables

Type argument representing the ERKStep time-stepping module.

Information passed to registered error handler functions.

Functions that set the multiplicative error weights for use in the weighted RMS norm.

Functions that set the multiplicative error weights for use in the weighted RMS norm.

Functions that set the multiplicative error weights for use in the weighted RMS norm.

The eta parameter in the stopping criteria for the linear system solver.

The parameters gamma and alpha in the formula for the Eisenstat and Walker Choice 2 for eta.

The function efn t0 tout v advances the state vector v for the inner (fast) ODE system from time t0 to time tout.

The data necessary to computer the forcing term.

The function rhsfn t v f m updates f with the value of the full right-hand-side function of the inner (fast) ODE at time t and for dependent variable values v.

A flag indicating why the full RHS function has been called.

Represents generic nvector data.

Represents an nvector whose data must be accessed through a constructor in Nvector.gdata.

The type of Gram-Schmidt orthogonalization in iterative linear solvers.

Matrix internal type identifiers.

Array of row or column indices

Type of indexes into sparse matrices.

Summaries of integrator statistics.

Summaries of integrator statistics.

Used to specify the nterpolation method used for output values and implicit method predictors.

Specifies the type of interpolation to use between checkpoints.

Specifies the type of interpolation to use between checkpoints.

Callback functions that compute dense approximations to a Jacobian matrix.

Callback functions that compute dense approximations to a Jacobian matrix.

Callback functions that compute dense approximations to a Jacobian matrix.

Callback functions that compute dense approximations to a Jacobian matrix.

Callback functions that compute dense approximations to a Jacobian matrix.

Callback functions that compute approximations to a Jacobian matrix.

Callback functions that compute dense approximations to a Jacobian matrix without forward sensitivities.

Callback functions that compute dense approximations to a Jacobian matrix without forward sensitivities.

Callback functions that compute dense approximations to a Jacobian matrix with forward sensitivities.

Callback functions that compute dense approximations to a Jacobian matrix with forward sensitivities.

Callback functions that preprocess or evaluate Jacobian-related data needed by the jac_times_vec_fn.

Callback functions that preprocess or evaluate Jacobian-related data needed by the jac_times_vec_fn.

Callback functions that preprocess or evaluate Jacobian-related data needed by the jac_times_vec_fn.

Callback functions that preprocess or evaluate Jacobian-related data needed by the jac_times_vec_fn.

Callback functions that preprocess or evaluate Jacobian-related data needed by the jac_times_vec_fn.

Callback functions that preprocess or evaluate Jacobian-related data needed by the jac_times_vec_fn.

Callback functions that preprocess or evaluate Jacobian-related data needed by the jac_times_vec_fn.

Callback functions that compute the Jacobian times a vector.

Callback functions that compute the Jacobian times a vector.

Callback functions that compute the Jacobian times a vector.

Callback functions that compute the Jacobian times a vector.

Callback functions that compute (an approximation to) the Jacobian times a vector.

Callback functions that compute the Jacobian times a vector.

Callback functions that compute the Jacobian times a vector without forward sensitivities.

Callback functions that compute the Jacobian times a vector without forward sensitivities.

Callback functions that compute the Jacobian times a vector with forward sensitivities.

Callback functions that compute the Jacobian times a vector with forward sensitivities.

Arguments common to Jacobian callback functions.

Arguments common to Jacobian callback functions.

Arguments common to Jacobian callback functions.

Arguments common to Jacobian callback functions.

Arguments common to Jacobian callback functions.

Arguments common to Jacobian callback functions.

Represents the internal layout of a Pthreads nvector.

Represents the internal layout of an OpenMP nvector.

Represents the internal layout of an mpiplusx nvector.

Represents the internal layout of an mpimany-vector nvector.

Represents the internal layout of a parallel nvector.

Array nvectors are custom nvectors.

Represents an nvector manipulated by operations written in OCaml.

Represents the internal layout of a many-vector nvector.

Represents any nvector that can be treated as a serial nvector.

Classifies the internal structure of an nvector.

Linear solvers used in backward problems.

Linear solvers used in backward problems.

Linear solvers used by MRIStep.

Linear solvers used by ARKStep.

Linear solvers used by Ida.

Linear solvers used by Kinsol.

Linear solvers used by Cvode.

The identifier of a linear solver.

Summaries of linear solver statistics.

Broadly classifies the operations provided by a linear solver and its operating principle.

The linearity of the implicit portion of the problem.

Function to compute the linear system matrix $M_B = I - \gamma_B J_B$ or an approximation of it for the backward problem.

Function to compute the linear system matrix $A = M - \gamma J$ or an approximation of it.

Function to compute the linear system matrix $M = I - \gamma J$ or an approximation of it.

Function to compute the linear system matrix or an approximation to it without forward sensitivities.

Function to compute the linear system matrix or an approximation to it with forward sensitivities.

Choice of linear multistep method.

Functions that approximate backward residual functions using local computations only.

Approximates the right-hand side function using local computations only.

Functions that approximate backward right-hand side functions using local computations only.

Approximates the right-hand side function using local computations only.

Approximates the right-hand side function using local computations only.

Approximates the system function using local computations only.

A function to setup linear solves.

A function to solve linear systems.

Functions that compute a mass matrix (or an approximation of one).

Callback functions that preprocess or evaluate Jacobian-related data needed by the mass_times_vec_fn.

Callback functions that compute the mass matrix times a vector.

Generic operations that all matrix types must implement.

Lower-bandwidth.

Type argument representing the MRIStep time-stepping module.

Upper-bandwidth.

Internal data required to construct the current nonlinear implicit system within a nonlinear solver.

Internal data required to construct the current nonlinear implicit system within a nonlinear solver.

Internal data required to construct the current nonlinear implicit system within a nonlinear solver.

Internal data required to construct the current nonlinear implicit system within a nonlinear solver.

Internal data required to construct the current nonlinear implicit system within a nonlinear solver.

The problem specification expected by a nonlinear solver.

An alias for Nvector.t.

Vector type identifiers.

The set of operations required to define an nvector.

The operations required to implement an iterative linear solver.

The ordering algorithm used for reducing fill.

The ordering algorithm used for reducing fill.

Orthogonalization routines of the QR factorization portion of Anderson acceleration.

Alias for sessions based on parallel nvectors.

Alias for sessions based on parallel nvectors.

Alias for preconditioners based on parallel nvectors.

Alias for preconditioners based on parallel nvectors.

Alias for preconditioners based on parallel nvectors.

Alias for preconditioners based on parallel nvectors.

Alias for preconditioners based on parallel nvectors.

Alias for preconditioners based on parallel nvectors.

Alias for sessions based on parallel nvectors.

Alias for sessions based on parallel nvectors.

Alias for sessions based on parallel nvectors.

Alias for sessions based on parallel nvectors.

A function to be called after each inner integration.

A function to process the results of each timestep solution.

A function to be called before each inner integration.

Callback functions that preprocess or evaluate Jacobian-related data need by Idas.Adjoint.Spils.prec_solve_fn without forward sensitivities.

Callback functions that preprocess or evaluate Jacobian-related data needed by Cvodes.Adjoint.Spils.prec_solve_fn without forward sensitivities.

Callback functions that preprocess or evaluate mass matrix-related data needed by Arkode.ARKStep.Mass.Spils.prec_solve_fn.

Callback functions that preprocess or evaluate Jacobian-related data needed by Arkode.Spils.prec_solve_fn.

Callback functions that preprocess or evaluate Jacobian-related data need by Ida.Spils.prec_solve_fn.

Callback functions that preprocess or evaluate Jacobian-related data need by Kinsol.Spils.prec_solve_fn.

Callback functions that preprocess or evaluate Jacobian-related data needed by Cvode.Spils.prec_solve_fn.

Callback functions that preprocess or evaluate Jacobian-related data need by Idas.Adjoint.Spils.prec_solve_fn with forward sensitivities.

Callback functions that preprocess or evaluate Jacobian-related data needed by Cvodes.Adjoint.Spils.prec_solve_fn with forward sensitivities.

Arguments passed to the preconditioner solver function.

Arguments passed to the mass matrix preconditioner solver function.

Arguments passed to the preconditioner solver function.

Arguments passed to the preconditioner solver function.

Callback functions that solve a linear system involving a preconditioner matrix without forward sensitivities.

Callback functions that solve a linear system involving a preconditioner matrix without forward sensitivities.

Callback functions that solve a linear mass matrix system involving a preconditioner matrix.

Callback functions that solve a linear system involving a preconditioner matrix.

Callback functions that solve a linear system involving a preconditioner matrix.

Callback functions that solve a linear system involving a preconditioner matrix.

Callback functions that solve a linear system involving a preconditioner matrix.

Callback functions that solve a linear system involving a preconditioner matrix with forward sensitivities.

Callback functions that solve a linear system involving a preconditioner matrix with forward sensitivities.

Specifies a preconditioner and its callback functions.

Specifies a preconditioner, including the type of preconditioning (none, left, right, or both) and callback functions.

Specifies a preconditioner, including the type of preconditioning (none, left, right, or both) and callback functions.

Specifies a preconditioner, including the type of preconditioning (none, left, right, or both) and callback functions.

Specifies a preconditioner and its callback functions.

Specifies a preconditioner, including the type of preconditioning (none or right) and callback functions.

Specifies a preconditioner, including the type of preconditioning (none, left, right, or both) and callback functions.

The type of preconditioning in Krylov solvers.

Method choices for predicting implicit solutions.

Increasing levels of verbosity for informational messages.

The form of the initial value problem.

The form of the initial value problem.

A function to compute the projection of the solution and, if enabled, the error on the constraint manifold.

Functions that set up any problem data in preparation for calls to psolvefn.

Functions that set up any problem data in preparation for calls to psolvefn.

A function psolvefn r z tol lr that solves the preconditioner equation $Pz = r$ for the vector z such that $\left\lVert Pz - r \right\rVert_\mathrm{wrms} < \mathit{tol}$ .

A function psolvefn r z tol lr that solves the preconditioner equation $Pz = r$ for the vector z such that $\left\lVert Pz - r \right\rVert_\mathrm{wrms} < \mathit{tol}$ .

Functions defining quadrature variables.

Functions defining quadrature variables.

Functions defining quadrature sensitivities.

Functions defining quadrature sensitivities.

Arguments to Idas.Sensitivity.Quadrature.quadsensrhsfn.

Arguments to Cvodes.Sensitivity.Quadrature.quadsensrhsfn.

Values indicating the status of root functions.

Tolerance specification for calculations on mass matrix residuals.

Functions that compute the weighted RMS residual weights.

The function rfn tR vR rests the inner (fast) stepper state to time tR and dependent variable values vR.

Residual functions that define a DAE problem.

Called to resize a vector to match the dimensions of another.

Results of nonlinear solution attempts.

Right-hand side functions for calculating ODE derivatives.

Right-hand side functions for calculating ODE derivatives.

Called by the solver to calculate the values of root functions.

Called by the solver to calculate the values of root functions.

Called by the solver to calculate the values of root functions.

Specifies a sensitivity solution method.

Specifies a sensitivity solution method.

Specifies problem parameter information for sensitivity calculations.

Specifies problem parameter information for sensitivity calculations.

Summaries of sensitivity stats.

Summaries of sensitivity stats.

Sensitivity functions that calculate the residuals of all sensitivity equations.

Arguments to Idas.Sensitivity.sensresfn.

Specify a sensitivity function.

Sensitivity functions that calculate the right-hand side of a single sensitivity equation.

Sensitivity functions that calculate the right-hand sides of all sensitivity equations.

Common arguments to Cvodes.Sensitivity.sensrhsfn1 and Cvodes.Sensitivity.sensrhsfn_all.

The type of any nvector that can be used as a serial nvector.

Alias for backward sessions based on serial nvectors.

Alias for backward sessions based on serial nvectors.

Alias for linear solvers that are restricted to serial nvectors.

Alias for linear solvers that are restricted to serial nvectors.

Alias for linear solvers that are restricted to serial nvectors.

Alias for linear solvers that are restricted to serial nvectors.

Alias for linear solvers that are restricted to serial nvectors.

Alias for linear solvers that are restricted to serial nvectors.

Alias for linear solvers that are restricted to serial nvectors.

Alias for sessions based on serial nvectors.

Alias for sessions based on serial nvectors.

Alias for sessions based on serial nvectors.

Alias for sessions based on serial nvectors.

Alias for sessions based on serial nvectors.

Alias for sessions based on serial nvectors.

Alias for mass matrix solvers that are restricted to serial nvectors.

Alias for linear solvers that are restricted to serial nvectors.

Alias for Ida sessions.

Alias for Cvode sessions.

A session with the MRIStep time-stepping solver.

A session with the ERKStep time-stepping solver.

A session with the ARKStep time-stepping solver.

A session with the IDA solver.

A session with the KINSOL solver.

A session with the CVODE solver.

Matrix storage formats.

Storage upper-bandwidth.

Arguments passed to the preconditioner solver function.

Mass matrix solvers used by Arkode.

Values returned by the step functions.

Values returned by the step functions.

Values returned by the step functions.

Generic matrix with Sparse content.

A function that predicts the maximum stable step size for the explicit portions of an ImEx ODE system.

A function to be called after the predictor algorithm to update the predictor.

A function to be called after the predictor algorithm to update the predictor.

Distinguishes a library-supplied matrix from a custom one.

Summaries of integrator statistics.

Strategy used to solve the nonlinear system.

System function that defines nonlinear problem.

A function sysfn y fg mem to evaluate the nonlinear system $F(y)$ (for RootFind) or $G(y)$ (for FixedPoint).

The type of Pthreads nvectors.

The type of OpenMP nvectors.

The type of mpiplusx nvectors.

The type of mpimany-vector nvectors.

The type of parallel nvectors.

Represents a set of coupling coefficients.

Inner steppers are used to solve the auxiliary initial value problem of an MRIStep integrator's fast time-scale.

A butcher table.

For pattern-matching on constraints.

An alias for the nvector type.

The type scheme of custom nvectors.

The type of many-vector nvectors.

The type of serial nvectors.

An alias for the nvector type.

The vector type.

Represents an nvector of kind 'kind with underlying data of type 'data.

A senswrapper is an Nvector.nvector of Nvector.nvectors that cannot be created or manipulated from OCaml.

A generic nonlinear solver.

A linear solver.

A band matrix accessible directly through a Bigarray.

A dense matrix accessible directly through a Bigarray.

A sparse matrix.

A band matrix.

A dense matrix.

A generic matrix with a payload of type 'm.

For pattern-matching on constraints.

Arrays that communicate which zero-crossings are sought.

Arrays that communicate the occurrence of zero-crossings.

A context required to create Sundials values.

A Sundials profiler.

An open log file.

An immutable array.

A Bigarray of integers.

A two-dimensional matrix.

A Bigarray of floats.

Summaries of time-stepper statistics.

Summaries of time-stepper statistics.

Tolerances for calculating backward quadrature variables.

Tolerance specifications.

Tolerances for calculating quadrature sensitivities.

Tolerances for calculating sensitivities.

Tolerances for calculating quadrature variables.

Tolerances for calculating backward quadrature variables.

Tolerance specifications.

Tolerances for calculating quadrature sensitivities.

Tolerances for calculating sensitivities.

Tolerances for calculating quadrature variables.

Tolerance specifications.

Tolerance specifications.

Tolerance specifications.

Workspaces with three temporary vectors.

Workspaces with three temporary vectors.

Workspaces with three temporary vectors.

Workspaces with three temporary vectors.

Workspaces with three temporary vectors.