Class AbstractModel

• Defined in File abstract_model.h

Inheritance Relationships

Derived Type

• public amici::Model (Class Model)

Class Documentation

class AbstractModel

Abstract base class of amici::Model defining functions that need to be implemented in an AMICI model.

Some functions have empty default implementations or throw. This class shall not have any data members.

Subclassed by amici::Model

Public Functions

virtual ~AbstractModel() = default

virtual std::unique_ptr<Solver> getSolver() = 0

Retrieves the solver object.

Returns:

The Solver instance

virtual void froot(realtype const t, AmiVector const &x, AmiVector const &dx, gsl::span<realtype> root) = 0

Root function.

Parameters:

• t – time

• x – state

• dx – time derivative of state (DAE only)

• root – array to which values of the root function will be written

virtual void fxdot(realtype const t, AmiVector const &x, AmiVector const &dx, AmiVector &xdot) = 0

Residual function.

Parameters:

• t – time

• x – state

• dx – time derivative of state (DAE only)

• xdot – array to which values of the residual function will be written

virtual void fsxdot(realtype const t, AmiVector const &x, AmiVector const &dx, int ip, AmiVector const &sx, AmiVector const &sdx, AmiVector &sxdot) = 0

Sensitivity Residual function.

Parameters:

• t – time

• x – state

• dx – time derivative of state (DAE only)

• ip – parameter index

• sx – sensitivity state

• sdx – time derivative of sensitivity state (DAE only)

• sxdot – array to which values of the sensitivity residual function will be written

virtual void fxBdot_ss(realtype const t, AmiVector const &xB, AmiVector const &dxB, AmiVector &xBdot) = 0

Residual function backward when running in steady state mode.

Parameters:

• t – time

• xB – adjoint state

• dxB – time derivative of state (DAE only)

• xBdot – array to which values of the residual function will be written

virtual void fJSparseB_ss(SUNMatrix JB) = 0

Sparse Jacobian function backward, steady state case.

Parameters:

JB – sparse matrix to which values of the Jacobian will be written

virtual void writeSteadystateJB(realtype const t, realtype cj, AmiVector const &x, AmiVector const &dx, AmiVector const &xB, AmiVector const &dxB, AmiVector const &xBdot) = 0

Computes the sparse backward Jacobian for steadystate integration and writes it to the model member.

Parameters:

• t – timepoint

• cj – scalar in Jacobian

• x – Vector with the states

• dx – Vector with the derivative states

• xB – Vector with the adjoint states

• dxB – Vector with the adjoint derivative states

• xBdot – Vector with the adjoint state right hand side

virtual void fJ(realtype const t, realtype cj, AmiVector const &x, AmiVector const &dx, AmiVector const &xdot, SUNMatrix J) = 0

Dense Jacobian function.

Parameters:

• t – time

• cj – scaling factor (inverse of timestep, DAE only)

• x – state

• dx – time derivative of state (DAE only)

• xdot – values of residual function (unused)

• J – dense matrix to which values of the jacobian will be written

virtual void fJB(realtype const t, realtype cj, AmiVector const &x, AmiVector const &dx, AmiVector const &xB, AmiVector const &dxB, AmiVector const &xBdot, SUNMatrix JB) = 0

Dense Jacobian function.

Parameters:

• t – time

• cj – scaling factor (inverse of timestep, DAE only)

• x – state

• dx – time derivative of state (DAE only)

• xB – Vector with the adjoint states

• dxB – Vector with the adjoint derivative states

• xBdot – Vector with the adjoint right hand side (unused)

• JB – dense matrix to which values of the jacobian will be written

virtual void fJSparse(realtype const t, realtype cj, AmiVector const &x, AmiVector const &dx, AmiVector const &xdot, SUNMatrix J) = 0

Sparse Jacobian function.

Parameters:

• t – time

• cj – scaling factor (inverse of timestep, DAE only)

• x – state

• dx – time derivative of state (DAE only)

• xdot – values of residual function (unused)

• J – sparse matrix to which values of the Jacobian will be written

virtual void fJSparseB(realtype const t, realtype cj, AmiVector const &x, AmiVector const &dx, AmiVector const &xB, AmiVector const &dxB, AmiVector const &xBdot, SUNMatrix JB) = 0

Sparse Jacobian function.

Parameters:

• t – time

• cj – scaling factor (inverse of timestep, DAE only)

• x – state

• dx – time derivative of state (DAE only)

• xB – Vector with the adjoint states

• dxB – Vector with the adjoint derivative states

• xBdot – Vector with the adjoint right hand side (unused)

• JB – dense matrix to which values of the jacobian will be written

virtual void fJDiag(realtype const t, AmiVector &Jdiag, realtype cj, AmiVector const &x, AmiVector const &dx) = 0

Diagonal Jacobian function.

Parameters:

• t – time

• Jdiag – array to which the diagonal of the Jacobian will be written

• cj – scaling factor (inverse of timestep, DAE only)

• x – state

• dx – time derivative of state (DAE only)

virtual void fdxdotdp(realtype const t, AmiVector const &x, AmiVector const &dx) = 0

Model-specific sparse implementation of explicit parameter derivative of right hand side.

Parameters:

• t – time

• x – state

• dx – time derivative of state (DAE only)

virtual void fJv(realtype const t, AmiVector const &x, AmiVector const &dx, AmiVector const &xdot, AmiVector const &v, AmiVector &nJv, realtype cj) = 0

Jacobian multiply function.

Parameters:

• t – time

• x – state

• dx – time derivative of state (DAE only)

• xdot – values of residual function (unused)

• v – multiplication vector (unused)

• nJv – array to which result of multiplication will be written

• cj – scaling factor (inverse of timestep, DAE only)

virtual std::string getAmiciVersion() const

Returns the AMICI version that was used to generate the model.

Returns:

AMICI version string

virtual std::string getAmiciCommit() const

Returns the AMICI commit that was used to generate the model.

Returns:

AMICI commit string

virtual void fx0(realtype *x0, realtype const t, realtype const *p, realtype const *k)

Model-specific implementation of fx0.

Parameters:

• x0 – initial state

• t – initial time

• p – parameter vector

• k – constant vector

virtual bool isFixedParameterStateReinitializationAllowed() const

Function indicating whether reinitialization of states depending on fixed parameters is permissible.

Returns:

flag indicating whether reinitialization of states depending on fixed parameters is permissible

virtual void fx0_fixedParameters(realtype *x0, realtype const t, realtype const *p, realtype const *k, gsl::span<int const> reinitialization_state_idxs)

Model-specific implementation of fx0_fixedParameters.

Parameters:

• x0 – initial state

• t – initial time

• p – parameter vector

• k – constant vector

• reinitialization_state_idxs – Indices of states to be reinitialized based on provided constants / fixed parameters.

virtual void fsx0_fixedParameters(realtype *sx0, realtype const t, realtype const *x0, realtype const *p, realtype const *k, int ip, gsl::span<int const> reinitialization_state_idxs)

Model-specific implementation of fsx0_fixedParameters.

Parameters:

• sx0 – initial state sensitivities

• t – initial time

• x0 – initial state

• p – parameter vector

• k – constant vector

• ip – sensitivity index

• reinitialization_state_idxs – Indices of states to be reinitialized based on provided constants / fixed parameters.

virtual void fsx0(realtype *sx0, realtype const t, realtype const *x0, realtype const *p, realtype const *k, int ip)

Model-specific implementation of fsx0.

Parameters:

• sx0 – initial state sensitivities

• t – initial time

• x0 – initial state

• p – parameter vector

• k – constant vector

• ip – sensitivity index

virtual void fdx0(AmiVector &x0, AmiVector &dx0)

Initial value for time derivative of states (only necessary for DAEs)

Parameters:

• x0 – Vector with the initial states

• dx0 – Vector to which the initial derivative states will be written (only DAE)

virtual void fstau(realtype *stau, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, realtype const *tcl, realtype const *sx, int ip, int ie)

Model-specific implementation of fstau.

Parameters:

• stau – total derivative of event timepoint

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

• tcl – total abundances for conservation laws

• sx – current state sensitivity

• ip – sensitivity index

• ie – event index

virtual void fy(realtype *y, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, realtype const *w)

Model-specific implementation of fy.

Parameters:

• y – model output at current timepoint

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

• w – repeating elements vector

virtual void fdydp(realtype *dydp, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, int ip, realtype const *w, realtype const *dwdp)

Model-specific implementation of fdydp (MATLAB-only)

Parameters:

• dydp – partial derivative of observables y w.r.t. model parameters p

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

• ip – parameter index w.r.t. which the derivative is requested

• w – repeating elements vector

• dwdp – Recurring terms in xdot, parameter derivative

virtual void fdydp(realtype *dydp, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, int ip, realtype const *w, realtype const *tcl, realtype const *dtcldp, realtype const *spl, realtype const *sspl)

Model-specific implementation of fdydp (Python)

Parameters:

• dydp – partial derivative of observables y w.r.t. model parameters p

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

• ip – parameter index w.r.t. which the derivative is requested

• w – repeating elements vector

• tcl – total abundances for conservation laws

• dtcldp – Sensitivities of total abundances for conservation laws

• spl – spline value vector

• sspl – sensitivities of spline values vector w.r.t. parameters \( p \)

virtual void fdydx(realtype *dydx, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, realtype const *w, realtype const *dwdx)

Model-specific implementation of fdydx.

Parameters:

• dydx – partial derivative of observables y w.r.t. model states x

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

• w – repeating elements vector

• dwdx – Recurring terms in xdot, state derivative

virtual void fz(realtype *z, int ie, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h)

Model-specific implementation of fz.

Parameters:

• z – value of event output

• ie – event index

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

virtual void fsz(realtype *sz, int ie, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, realtype const *sx, int ip)

Model-specific implementation of fsz.

Parameters:

• sz – Sensitivity of rz, total derivative

• ie – event index

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

• sx – current state sensitivity

• ip – sensitivity index

virtual void frz(realtype *rz, int ie, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h)

Model-specific implementation of frz.

Parameters:

• rz – value of root function at current timepoint (non-output events not included)

• ie – event index

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

virtual void fsrz(realtype *srz, int ie, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, realtype const *sx, int ip)

Model-specific implementation of fsrz.

Parameters:

• srz – Sensitivity of rz, total derivative

• ie – event index

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• sx – current state sensitivity

• h – Heaviside vector

• ip – sensitivity index

virtual void fdzdp(realtype *dzdp, int ie, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, int ip)

Model-specific implementation of fdzdp.

Parameters:

• dzdp – partial derivative of event-resolved output z w.r.t. model parameters p

• ie – event index

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

• ip – parameter index w.r.t. which the derivative is requested

virtual void fdzdx(realtype *dzdx, int ie, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h)

Model-specific implementation of fdzdx.

Parameters:

• dzdx – partial derivative of event-resolved output z w.r.t. model states x

• ie – event index

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

virtual void fdrzdp(realtype *drzdp, int ie, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, int ip)

Model-specific implementation of fdrzdp.

Parameters:

• drzdp – partial derivative of root output rz w.r.t. model parameters p

• ie – event index

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

• ip – parameter index w.r.t. which the derivative is requested

virtual void fdrzdx(realtype *drzdx, int ie, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h)

Model-specific implementation of fdrzdx.

Parameters:

• drzdx – partial derivative of root output rz w.r.t. model states x

• ie – event index

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

virtual void fdeltax(realtype *deltax, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, int ie, realtype const *xdot, realtype const *xdot_old)

Model-specific implementation of fdeltax.

Parameters:

• deltax – state update

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

• ie – event index

• xdot – new model right hand side

• xdot_old – previous model right hand side

virtual void fdeltasx(realtype *deltasx, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, realtype const *w, int ip, int ie, realtype const *xdot, realtype const *xdot_old, realtype const *sx, realtype const *stau, realtype const *tcl)

Model-specific implementation of fdeltasx.

Parameters:

• deltasx – sensitivity update

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

• w – repeating elements vector

• ip – sensitivity index

• ie – event index

• xdot – new model right hand side

• xdot_old – previous model right hand side

• sx – state sensitivity

• stau – event-time sensitivity

• tcl – total abundances for conservation laws

virtual void fdeltaxB(realtype *deltaxB, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, int ie, realtype const *xdot, realtype const *xdot_old, realtype const *xB)

Model-specific implementation of fdeltaxB.

Parameters:

• deltaxB – adjoint state update

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

• ie – event index

• xdot – new model right hand side

• xdot_old – previous model right hand side

• xB – current adjoint state

virtual void fdeltaqB(realtype *deltaqB, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, int ip, int ie, realtype const *xdot, realtype const *xdot_old, realtype const *xB)

Model-specific implementation of fdeltaqB.

Parameters:

• deltaqB – sensitivity update

• t – current time

• x – current state

• p – parameter vector

• k – constant vector

• h – Heaviside vector

• ip – sensitivity index

• ie – event index

• xdot – new model right hand side

• xdot_old – previous model right hand side

• xB – adjoint state

virtual void fsigmay(realtype *sigmay, realtype const t, realtype const *p, realtype const *k, realtype const *y)

Model-specific implementation of fsigmay.

Parameters:

• sigmay – standard deviation of measurements

• t – current time

• p – parameter vector

• k – constant vector

• y – model output at timepoint t

virtual void fdsigmaydp(realtype *dsigmaydp, realtype const t, realtype const *p, realtype const *k, realtype const *y, int ip)

Model-specific implementation of fdsigmaydp.

Parameters:

• dsigmaydp – partial derivative of standard deviation of measurements

• t – current time

• p – parameter vector

• k – constant vector

• y – model output at timepoint t

• ip – sensitivity index

virtual void fdsigmaydy(realtype *dsigmaydy, realtype const t, realtype const *p, realtype const *k, realtype const *y)

Model-specific implementation of fsigmay.

Parameters:

• dsigmaydy – partial derivative of standard deviation of measurements w.r.t. model outputs

• t – current time

• p – parameter vector

• k – constant vector

• y – model output at timepoint t

virtual void fsigmaz(realtype *sigmaz, realtype const t, realtype const *p, realtype const *k)

Model-specific implementation of fsigmaz.

Parameters:

• sigmaz – standard deviation of event measurements

• t – current time

• p – parameter vector

• k – constant vector

virtual void fdsigmazdp(realtype *dsigmazdp, realtype const t, realtype const *p, realtype const *k, int ip)

Model-specific implementation of fsigmaz.

Parameters:

• dsigmazdp – partial derivative of standard deviation of event measurements

• t – current time

• p – parameter vector

• k – constant vector

• ip – sensitivity index

virtual void fJy(realtype *nllh, int iy, realtype const *p, realtype const *k, realtype const *y, realtype const *sigmay, realtype const *my)

Model-specific implementation of fJy.

Parameters:

• nllh – negative log-likelihood for measurements y

• iy – output index

• p – parameter vector

• k – constant vector

• y – model output at timepoint

• sigmay – measurement standard deviation at timepoint

• my – measurements at timepoint

virtual void fJz(realtype *nllh, int iz, realtype const *p, realtype const *k, realtype const *z, realtype const *sigmaz, realtype const *mz)

Model-specific implementation of fJz.

Parameters:

• nllh – negative log-likelihood for event measurements z

• iz – event output index

• p – parameter vector

• k – constant vector

• z – model event output at timepoint

• sigmaz – event measurement standard deviation at timepoint

• mz – event measurements at timepoint

virtual void fJrz(realtype *nllh, int iz, realtype const *p, realtype const *k, realtype const *z, realtype const *sigmaz)

Model-specific implementation of fJrz.

Parameters:

• nllh – regularization for event measurements z

• iz – event output index

• p – parameter vector

• k – constant vector

• z – model event output at timepoint

• sigmaz – event measurement standard deviation at timepoint

virtual void fdJydy(realtype *dJydy, int iy, realtype const *p, realtype const *k, realtype const *y, realtype const *sigmay, realtype const *my)

Model-specific implementation of fdJydy.

Parameters:

• dJydy – partial derivative of time-resolved measurement negative log-likelihood Jy

• iy – output index

• p – parameter vector

• k – constant vector

• y – model output at timepoint

• sigmay – measurement standard deviation at timepoint

• my – measurement at timepoint

virtual void fdJydy_colptrs(SUNMatrixWrapper &dJydy, int index)

Model-specific implementation of fdJydy colptrs.

Parameters:

• dJydy – sparse matrix to which colptrs will be written

• index – ytrue index

virtual void fdJydy_rowvals(SUNMatrixWrapper &dJydy, int index)

Model-specific implementation of fdJydy rowvals.

Parameters:

• dJydy – sparse matrix to which rowvals will be written

• index – ytrue index

virtual void fdJydsigma(realtype *dJydsigma, int iy, realtype const *p, realtype const *k, realtype const *y, realtype const *sigmay, realtype const *my)

Model-specific implementation of fdJydsigma.

Parameters:

• dJydsigma – Sensitivity of time-resolved measurement negative log-likelihood Jy w.r.t. standard deviation sigmay

• iy – output index

• p – parameter vector

• k – constant vector

• y – model output at timepoint

• sigmay – measurement standard deviation at timepoint

• my – measurement at timepoint

virtual void fdJzdz(realtype *dJzdz, int iz, realtype const *p, realtype const *k, realtype const *z, realtype const *sigmaz, realtype const *mz)

Model-specific implementation of fdJzdz.

Parameters:

• dJzdz – partial derivative of event measurement negative log-likelihood Jz

• iz – event output index

• p – parameter vector

• k – constant vector

• z – model event output at timepoint

• sigmaz – event measurement standard deviation at timepoint

• mz – event measurement at timepoint

virtual void fdJzdsigma(realtype *dJzdsigma, int iz, realtype const *p, realtype const *k, realtype const *z, realtype const *sigmaz, realtype const *mz)

Model-specific implementation of fdJzdsigma.

Parameters:

• dJzdsigma – Sensitivity of event measurement negative log-likelihood Jz w.r.t. standard deviation sigmaz

• iz – event output index

• p – parameter vector

• k – constant vector

• z – model event output at timepoint

• sigmaz – event measurement standard deviation at timepoint

• mz – event measurement at timepoint

virtual void fdJrzdz(realtype *dJrzdz, int iz, realtype const *p, realtype const *k, realtype const *rz, realtype const *sigmaz)

Model-specific implementation of fdJrzdz.

Parameters:

• dJrzdz – partial derivative of event penalization Jrz

• iz – event output index

• p – parameter vector

• k – constant vector

• rz – model root output at timepoint

• sigmaz – event measurement standard deviation at timepoint

virtual void fdJrzdsigma(realtype *dJrzdsigma, int iz, realtype const *p, realtype const *k, realtype const *rz, realtype const *sigmaz)

Model-specific implementation of fdJrzdsigma.

Parameters:

• dJrzdsigma – Sensitivity of event penalization Jrz w.r.t. standard deviation sigmaz

• iz – event output index

• p – parameter vector

• k – constant vector

• rz – model root output at timepoint

• sigmaz – event measurement standard deviation at timepoint

virtual void fw(realtype *w, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, realtype const *tcl, realtype const *spl, bool include_static = true)

Model-specific implementation of fw.

Parameters:

• w – Recurring terms in xdot

• t – timepoint

• x – vector with the states

• p – parameter vector

• k – constants vector

• h – Heaviside vector

• tcl – total abundances for conservation laws

• spl – spline value vector

• include_static – Whether to (re-)evaluate only dynamic expressions (false) or also static expressions (true). Dynamic expressions are those that depend directly or indirectly on time, static expressions are those that don’t.

virtual void fdwdp(realtype *dwdp, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, realtype const *w, realtype const *tcl, realtype const *stcl, realtype const *spl, realtype const *sspl, bool include_static = true)

Model-specific sparse implementation of dwdp.

Parameters:

• dwdp – Recurring terms in xdot, parameter derivative

• t – timepoint

• x – vector with the states

• p – parameter vector

• k – constants vector

• h – Heaviside vector

• w – vector with helper variables

• tcl – total abundances for conservation laws

• stcl – sensitivities of total abundances for conservation laws

• spl – spline value vector

• sspl – sensitivities of spline values vector w.r.t. parameters \( p \)

• include_static – Whether to (re-)evaluate only dynamic expressions (false) or also static expressions (true). Dynamic expressions are those that depend directly or indirectly on time, static expressions are those that don’t.

virtual void fdwdp_colptrs(SUNMatrixWrapper &dwdp)

Model-specific implementation for dwdp, column pointers.

Parameters:

dwdp – sparse matrix to which colptrs will be written

virtual void fdwdp_rowvals(SUNMatrixWrapper &dwdp)

Model-specific implementation for dwdp, row values.

Parameters:

dwdp – sparse matrix to which rowvals will be written

virtual void fdwdx(realtype *dwdx, realtype const t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, realtype const *w, realtype const *tcl, realtype const *spl, bool include_static = true)

Model-specific implementation of dwdx, data part.

Parameters:

• dwdx – Recurring terms in xdot, state derivative

• t – timepoint

• x – vector with the states

• p – parameter vector

• k – constants vector

• h – Heaviside vector

• w – vector with helper variables

• tcl – total abundances for conservation laws

• spl – spline value vector

• include_static – Whether to (re-)evaluate only dynamic expressions (false) or also static expressions (true). Dynamic expressions are those that depend directly or indirectly on time, static expressions are those that don’t.

virtual void fdwdx_colptrs(SUNMatrixWrapper &dwdx)

Model-specific implementation for dwdx, column pointers.

Parameters:

dwdx – sparse matrix to which colptrs will be written

virtual void fdwdx_rowvals(SUNMatrixWrapper &dwdx)

Model-specific implementation for dwdx, row values.

Parameters:

dwdx – sparse matrix to which rowvals will be written

virtual void fdwdw(realtype *dwdw, realtype t, realtype const *x, realtype const *p, realtype const *k, realtype const *h, realtype const *w, realtype const *tcl, bool include_static = true)

Model-specific implementation of fdwdw, no w chainrule (Py)

Parameters:

• dwdw – partial derivative w wrt w

• t – timepoint

• x – Vector with the states

• p – parameter vector

• k – constants vector

• h – Heaviside vector

• w – vector with helper variables

• tcl – Total abundances for conservation laws

• include_static – Whether to (re-)evaluate only dynamic expressions (false) or also static expressions (true). Dynamic expressions are those that depend directly or indirectly on time, static expressions are those that don’t.

virtual void fdwdw_colptrs(SUNMatrixWrapper &dwdw)

Model-specific implementation of fdwdw, colptrs part.

Parameters:

dwdw – sparse matrix to which colptrs will be written

virtual void fdwdw_rowvals(SUNMatrixWrapper &dwdw)

Model-specific implementation of fdwdw, rowvals part.

Parameters:

dwdw – sparse matrix to which rowvals will be written

virtual void fdx_rdatadx_solver(realtype *dx_rdatadx_solver, realtype const *x, realtype const *tcl, realtype const *p, realtype const *k)

Compute dx_rdata / dx_solver.

Parameters:

• dx_rdatadx_solver – dx_rdata / dx_solver

• p – parameter vector

• k – constant vector

• x – State variables with conservation laws applied

• tcl – Total abundances for conservation laws

virtual void fdx_rdatadx_solver_colptrs(SUNMatrixWrapper &dxrdatadxsolver)

Model-specific implementation of fdx_rdatadx_solver, colptrs part.

Parameters:

dxrdatadxsolver – sparse matrix to which colptrs will be written

virtual void fdx_rdatadx_solver_rowvals(SUNMatrixWrapper &dxrdatadxsolver)

Model-specific implementation of fdx_rdatadx_solver, rowvals part.

Parameters:

dxrdatadxsolver – sparse matrix to which rowvals will be written

virtual void fdx_rdatadp(realtype *dx_rdatadp, realtype const *x, realtype const *tcl, realtype const *p, realtype const *k, int const ip)

Compute dx_rdata / dp.

Parameters:

• dx_rdatadp – dx_rdata / dp

• p – parameter vector

• k – constant vector

• x – State variables with conservation laws applied

• tcl – Total abundances for conservation laws

• ip – Sensitivity index

virtual void fdx_rdatadtcl(realtype *dx_rdatadtcl, realtype const *x, realtype const *tcl, realtype const *p, realtype const *k)

Compute dx_rdata / dtcl.

Parameters:

• dx_rdatadtcl – dx_rdata / dtcl

• p – parameter vector

• k – constant vector

• x – State variables with conservation laws applied

• tcl – Total abundances for conservation laws

virtual void fdx_rdatadtcl_colptrs(SUNMatrixWrapper &dx_rdatadtcl)

Model-specific implementation of fdx_rdatadtcl, colptrs part.

Parameters:

dx_rdatadtcl – sparse matrix to which colptrs will be written

virtual void fdx_rdatadtcl_rowvals(SUNMatrixWrapper &dx_rdatadtcl)

Model-specific implementation of fdx_rdatadtcl, rowvals part.

Parameters:

dx_rdatadtcl – sparse matrix to which rowvals will be written

virtual void fdtotal_cldp(realtype *dtotal_cldp, realtype const *x_rdata, realtype const *p, realtype const *k, int const ip)

Compute dtotal_cl / dp.

Parameters:

• dtotal_cldp – dtotal_cl / dp

• x_rdata – State variables with conservation laws applied

• p – parameter vector

• k – constant vector

• ip – Sensitivity index

virtual void fdtotal_cldx_rdata(realtype *dtotal_cldx_rdata, realtype const *x_rdata, realtype const *p, realtype const *k, realtype const *tcl)

Compute dtotal_cl / dx_rdata.

Parameters:

• dtotal_cldx_rdata – dtotal_cl / dx_rdata

• x_rdata – State variables with conservation laws applied

• p – parameter vector

• k – constant vector

• tcl – Total abundances for conservation laws

virtual void fdtotal_cldx_rdata_colptrs(SUNMatrixWrapper &dtotal_cldx_rdata)

Model-specific implementation of fdtotal_cldx_rdata, colptrs part.

Parameters:

dtotal_cldx_rdata – sparse matrix to which colptrs will be written

virtual void fdtotal_cldx_rdata_rowvals(SUNMatrixWrapper &dtotal_cldx_rdata)

Model-specific implementation of fdtotal_cldx_rdata, rowvals part.

Parameters:

dtotal_cldx_rdata – sparse matrix to which rowvals will be written

virtual std::vector<HermiteSpline> fcreate_splines(realtype const *p, realtype const *k)

Model-specific implementation of spline creation.

Parameters:

• p – parameter vector

• k – constants vector

Returns:

Vector of splines used in the model

virtual void fdspline_valuesdp(realtype *dspline_valuesdp, realtype const *p, realtype const *k, int const ip)

Model-specific implementation the parametric derivatives of spline node values.

Parameters:

• dspline_valuesdp – vector to which derivatives will be written

• p – parameter vector

• k – constants vector

• ip – Sensitivity index

virtual void fdspline_slopesdp(realtype *dspline_slopesdp, realtype const *p, realtype const *k, int const ip)

Model-specific implementation the parametric derivatives of slopevalues at spline nodes.

Parameters:

• dspline_slopesdp – vector to which derivatives will be written

• p – parameter vector

• k – constants vector

• ip – Sensitivity index