diff options
Diffstat (limited to 'man')
| -rw-r--r-- | man/mkinpredict.Rd | 12 | ||||
| -rw-r--r-- | man/mmkin.Rd | 7 |
2 files changed, 8 insertions, 11 deletions
diff --git a/man/mkinpredict.Rd b/man/mkinpredict.Rd index d93c0753..ad749fa4 100644 --- a/man/mkinpredict.Rd +++ b/man/mkinpredict.Rd @@ -21,7 +21,6 @@ mkinpredict(x, odeparms, odeini, outtimes, ...) maxsteps = 20000L, map_output = TRUE, na_stop = TRUE, - call_lsoda = NULL, ... ) @@ -69,7 +68,8 @@ parent compound.} \link{mkinmod} model is used, even if is present.} \item{method.ode}{The solution method passed via \link{mkinpredict} to \link{ode}] in -case the solution type is "deSolve" and we are not using compiled code.} +case the solution type is "deSolve" and we are not using compiled code. +When using compiled code, only lsoda is supported.} \item{atol}{Absolute error tolerance, passed to the ode solver.} @@ -83,8 +83,6 @@ FALSE). Setting this to FALSE has no effect for analytical solutions, as these always return mapped output.} \item{na_stop}{Should it be an error if \link{ode} returns NaN values} - -\item{call_lsoda}{The address of the compiled function "call_lsoda"} } \value{ A matrix with the numeric solution in wide format @@ -111,11 +109,11 @@ mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20, mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20, solution_type = "analytical")[21,] mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20, - method = "lsoda")[21,] + method = "lsoda", use_compiled = FALSE)[21,] mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20, - method = "ode45")[21,] + method = "ode45", use_compiled = FALSE)[21,] mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20, - method = "rk4")[21,] + method = "rk4", use_compiled = FALSE)[21,] # rk4 is not as precise here # The number of output times used to make a lot of difference until the diff --git a/man/mmkin.Rd b/man/mmkin.Rd index 309761dd..438a237b 100644 --- a/man/mmkin.Rd +++ b/man/mmkin.Rd @@ -83,16 +83,15 @@ plot_sep(fits.0[[1, 1]]) # allow to plot the observed variables separately plot(fits.0[1, 1]) -# On Windows, we can use multiple cores by making a cluster using the parallel -# package, which gets loaded with mkin, and passing it to mmkin, e.g. -cl <- makePSOCKcluster(12) +# On Windows, we can use multiple cores by making a cluster first +cl <- parallel::makePSOCKcluster(12) f <- mmkin(c("SFO", "FOMC", "DFOP"), list(A = FOCUS_2006_A, B = FOCUS_2006_B, C = FOCUS_2006_C, D = FOCUS_2006_D), cluster = cl, quiet = TRUE) print(f) # We get false convergence for the FOMC fit to FOCUS_2006_A because this # dataset is really SFO, and the FOMC fit is overparameterised -stopCluster(cl) +parallel::stopCluster(cl) } } |