WLS design - Pressio/pressio GitHub Wiki
Required Functions for WLS
variables:
- nts: width of time stencil, for forward euler nts = 2
- ns: number of time steps in the window
- K: ROM basis size
- N: FOM size
Evauate single residual
This computes the residual at a single step, and is the same as LSPG. Required inputs are:
- The nts states required for the time discretization, type = rom vectors
- The time instance (for non-autonomous functions), type=double
- The time step, type=double
Outputs/required storage is
- residual, FOM vector of size N
Evauate windowed residual
This computes the residual over the time window. Presumably this will use the "evaluate single residual" function. Required inputs are:
- The number of time steps, ns, to compute the residual over, type=int
- The nts + ns - 1 states required for the time discretization, type = rom vectors
- The time instances (for non-autonomous functions), type=vector of doubles
- The time steps, type = vector of doubles
Outputs/required storage is
- windowed residual, extended FOM vector of size N * ns
Evauate single Jacobian
This computes the Jacobian of a single step, and is the same as LSPG Required inputs are:
- The nts states required for the time discretization, type = rom vectors
- The time instance (for non-autonomous functions), type=double
- The time step, type=double
- The argument of the residual with which to compute the Jacobian of, type=int
Outputs/required storage is
- Jacobian, FOM matrix of size N * K
Evauate windowed Jacobian
This computes the Jacobian of over the time window. Presumably this will use the "evaluate single Jacobian" function. Required inputs are:
- The number of time steps, ns, to compute the residual over, type=int
- The nts + ns - 1 states required for the time discretization, type = rom vectors
- The time instance (for non-autonomous functions), type=double
- The time step, type=double
- The argument of the residual with which to compute the Jacobian of, type=int
Outputs/required storage is
- Jacobian, extended FOM sparse matrix of size N ns* K ns