| project | R Documentation |
Runs the size spectrum model simulation. The function returns an object of type MizerSim that can then be explored with a range of summary_functions, indicator_functions and plotting_functions.
project(
object,
effort,
t_max = 100,
dt = 0.1,
t_save = 1,
t_start = 0,
initial_n,
initial_n_pp,
append = TRUE,
progress_bar = TRUE,
callback = NULL,
method = c("euler", "predictor_corrector", "tr_bdf2"),
check_steady = FALSE,
...
)
An object of class MizerSim.
The spatial discretisation of the growth (advection) term is controlled by
the flux entry of the second_order_w slot of the params object, not by
an argument to project(). With the default ("upwind") the first-order
upwind flux is used. Setting it to "van_leer" (for example with
second_order_w(params) <- TRUE) switches on a flux-limited (van Leer, TVD)
deferred correction that removes the leading numerical diffusion
\approx g\,w\,\log\beta of the upwind flux while keeping the density
update a tridiagonal solve and preserving positivity. The correction is most
useful on coarse logarithmic grids and pairs naturally with the second-order
time methods. Because it changes the discrete steady state, the choice lives
in the params object alongside the steady state rather than being a per-run
argument. See second_order_w().
All three methods are semi-implicit: the densities are solved for implicitly, but the rates that build the transport operator are frozen at values computed from earlier states. The second-order methods gain their extra order by evaluating the rates twice — at the start of the step and from a provisional prediction of its end — and averaging. That average is only second order if the rates vary smoothly along the trajectory.
A custom rate function registered with setRateFunction() that depends
discontinuously on the abundances therefore defeats all three methods alike,
including the L-stable "tr_bdf2", whose damping applies to the frozen
linear operator and not to the rates. The result is a trajectory that keeps
changing as dt is refined. See the Discontinuous rate functions
article for the symptoms and the remedy.
The effort argument specifies the level of fishing effort during the
simulation. If it is not supplied, the initial effort stored in the params
object is used. The effort can be specified in four different ways:
A single numeric value. This specifies the effort of all fishing gears which is constant through time (i.e. all the gears have the same constant effort).
A named vector whose names match with existing gear names.
The values in the vector specify the constant fishing effort for those
fishing gears, i.e. the effort is constant through time. The
effort for gears that are not included in the effort vector is set to the
default effort value, which is 1 in defaults edition 2 and later and 0 in
earlier defaults editions. Missing (NA) effort entries are replaced in
the same way.
A numerical vector which has the same length as the number of fishing gears. The values in the vector specify the constant fishing effort of each of the fishing gears, with the ordering assumed to be the same as in the MizerParams object.
A numerical array with dimensions time x gear. This specifies the
fishing effort of each gear at each time step. The first dimension, time,
must be named numerically and increasing. The second dimension of the array
must be named and the names must correspond to the gear names in the
MizerParams object. The value for the effort for a particular time
is used during the interval from that time to the next time in the array.
If effort is specified as an array then the smallest time in the array is
used as the initial time for the simulation. Otherwise the initial time is
set to the final time of the previous simulation if object is a
MizerSim object or to t_start otherwise.
When an effort array is provided, the t_max argument can be used to
extend the simulation beyond the last time specified in the effort array.
In this case, the effort values from the last time in the array will be
used for the extended period. The t_save argument can be used to specify
the frequency at which simulation results are saved. If t_save is not
supplied, the results will be saved at the times specified in the effort
array. If both t_max and t_save are provided with an effort array,
effort values will be interpolated (using step function) or extrapolated
(using the last known value) as needed for the new time points. The
t_start argument continues to be ignored when an effort array is supplied.
Note that if t_max or t_save are specified, the time grid for the
simulation is resampled based on t_save. This means that if the time
points in the effort array are irregular and do not align with the new
grid, those specific time points may be lost and the effort values at the
new grid points will be calculated via interpolation.
If the object argument is of class MizerSim then the initial
values for the simulation are taken from the final values in the
MizerSim object and the corresponding arguments to this function will
be ignored.
params <- NS_params
# With constant fishing effort for all gears for 20 time steps
sim <- project(params, t_max = 20, effort = 0.5)
# With constant fishing effort which is different for each gear
effort <- c(Industrial = 0, Pelagic = 1, Beam = 0.5, Otter = 0.5)
sim <- project(params, t_max = 20, effort = effort)
# With fishing effort that varies through time for each gear
gear_names <- c("Industrial", "Pelagic", "Beam", "Otter")
times <- seq(from = 1, to = 10, by = 1)
effort_array <- array(NA,
dim = c(length(times), length(gear_names)),
dimnames = list(time = times, gear = gear_names)
)
effort_array[, "Industrial"] <- 0.5
effort_array[, "Pelagic"] <- seq(from = 1, to = 2, length = length(times))
effort_array[, "Beam"] <- seq(from = 1, to = 0, length = length(times))
effort_array[, "Otter"] <- seq(from = 1, to = 0.5, length = length(times))
sim <- project(params, effort = effort_array)
# Extend a simulation beyond the effort array times
# Effort values from the final time are used for the extension
sim <- project(params, effort = effort_array, t_max = 15)
# Control save times with an effort array using t_save
sim <- project(params, effort = effort_array, t_save = 2)
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