diagnostics.deSolve: Print Diagnostic Characteristics of ODE and DAE Solvers

In deSolve: Solvers for Initial Value Problems of Differential Equations ('ODE', 'DAE', 'DDE')

Print Diagnostic Characteristics of ODE and DAE Solvers

Description

Prints several diagnostics of the simulation to the screen, e.g. number of steps taken, the last step size, ...

Usage

## S3 method for class 'deSolve'
diagnostics(obj, Full = FALSE, ...)

Arguments

obj	is the output matrix as produced by one of the integration routines.
Full	when TRUE then all messages will be printed, including the ones that are not relevant for the solver. If FALSE, then only the relevant messages will be printed.
...	optional arguments allowing to extend diagnostics as a generic function.

Details

When the integration output is saved as a data.frame, then the required attributes are lost and method diagnostics will not work anymore.

Value

The integer and real vector with diagnostic values; for function lsodar also the root information.

See tables 2 and 3 in vignette("deSolve") for what these vectors contain.

Note: the number of function evaluations are *without* the extra calls performed to generate the ordinary output variables (if present).

Examples

## The famous Lorenz equations: chaos in the earth's atmosphere
## Lorenz 1963. J. Atmos. Sci. 20, 130-141.

chaos <- function(t, state, parameters) {
  with(as.list(c(state)), {

    dx     <- -8/3 * x + y * z
    dy     <- -10 * (y - z)
    dz     <- -x * y + 28 * y - z

    list(c(dx, dy, dz))
  })
}

state <- c(x = 1, y = 1, z = 1)
times <- seq(0, 50, 0.01)
out   <- vode(state, times, chaos, 0)
pairs(out, pch = ".")
diagnostics(out)

deSolve documentation built on Nov. 28, 2023, 1:11 a.m.