A patch update so that users who had changed w_max
manually in their model will not get unhelpful error messages when
trying to use their model in the new version. General checking of
parameters is made more robust. In particular
validSpeciesParams()
has extra checks on consistency of
species parametersvalidParams()
checks that rate arrays contain finite
numeric valuesvalidSim()
checks that simulation results are finite
and truncates the simulation if they are not.newCommunityParams()
to set up
resource parameters differently since version 2.4.0 (#293)addSpecies()
now correctly preserves all
species_params
of the existing model.addSpecies()
no longer requires new species to grow to
maximum size, only maturity size is required.validGivenSpeciesParams()
validates the given
species parameters without adding defaults and
validSpeciesParams()
validates and returns a completed
species parameter dataframe.w_repro_max
giving the size at
which a species invests 100% of its energy into reproduction. Set to
w_max
by default.removeSpecies()
now also removes species parameters
that are not set for any of the remaining species.w_max
now also correctly updates
ft_mask
(#296).compareParams()
now also spells out differences in
given species parameters.getDiet()
now also includes the contribution of the
external encounter rate to the diet.setPredKernel()
now throws an error if some of the
required predation kernel parameters are NA.plotYieldGear()
one can select a subset of gears
with new gears
argument.valid_gears_arg()
to check the
gears
argument in functions that take a gears
argument.plotGrowthCurves()
.steadySingleSpecies()
no longer requires species to
grow to w_max
.matchGrowth()
now also rescales the external encounter
rate.setExtEncounter()
no longer resets the external
encounter rate to zero when called without the
ext_encounter
argument.plotBiomassObservedVsModel()
now plots the
ratio of modelled to observed biomass as default
(ratio = T
), as this is more useful visually to see how far
off modelled biomass is from observed biomass.time_modified
field is now updated correctly by
steadySingleSpecies()
, setColours()
and
setLinetypes()
.matchYields()
and
calibrateYield()
.This is a patch release made necessary by a change in CRAN’s requirement regarding the vignettes. It also includes a bug fix:
project()
and
projectToSteady(..., return_sim = TRUE)
now correctly
returns also the other components of the MizerSim object stored in
n_other
. #285This release introduces a change that requires you to upgrade your
old MizerParams and MizerSim objects with upgradeParams()
or upgradeSim()
.
Now the model can include an external encounter rate that represents
the rate at which a predator encounters food that is not explicitly
modelled. This encounter rate is set with setExtEncounter()
or ext_encounter<-()
and can be read with
getExtEncounter()
or ext_encounter()
. So this
is similar to how external mortality is handled.
You can now use given_species_params()
to see the
species parameter values that you have explicitly specified and
calculated_species_params()
to see the species parameter
values that mizer has calculated automatically or set to defaults. You
can continue to use species_params()
to get all species
parameters, irrespective of whether they were given or calculated.
You can still set parameter values with
species_params<-()
, but you can also use the stronger
given_species_params<-()
which not only sets the values
you give but also triggers a re-calculation of the calculated species
parameters. Using given_species_params<-()
is therefore
usually the better option.
There is now a three-part mizer course at https://mizer.course.sizespectrum.org with each part consisting of several tutorials, including code and exercises:
Part 1: Understand
You will gain an understanding of size spectra and their dynamics by
exploring simple example systems hands-on with mizer.
Part 2: Build
You will build your own multi-species mizer model for the Celtic sea,
following our example. You can also create a model for your own area of
interest.
Part 3: Use
You will explore the effects of changes in fishing and changes in
resource dynamics on the fish community and the fisheries yield. You
will run your own model scenarios.
effort
argument in
project()
is improved.h
of the maximum intake rate is
not given, it is now again given a default value. #282matchGrowth()
no longer gives an error when there is no
w_inf
column. #279This minor release was made necessary to keep mizer on CRAN after a unit test failed on macOS 13.3 with version 14.3 of the CLT toolchain.
This release introduces a change that requires you to upgrade your
old MizerParams and MizerSim objects with upgradeParams()
or upgradeSim()
.
For an explanation see blog post at https://blog.mizer.sizespectrum.org/posts/2022-11-30-dont-use-von-bertalanffy-growth-parameters/
The species parameter that specifies the size at which also the
largest fish stop growing is renamed from w_inf
to
w_max
. The parameter w_inf
is now reserved for
the von Bertalanffy asymptotic size parameter. If you upgrade your
existing MizerParams object with upgradeParams()
the
w_inf
column is copied over to the w_max
column automatically, but you may want to change the values yourself if
they do not currently reflect the maximum size of the species. Otherwise
the size distributions predicted by mizer will not match
observations.
The resource parameters kappa
and lambda
are now used to set the abundance of the resource in the steady state
rather than the carrying capacity, because the latter is not
observable.
While tuning the steady state using the steady()
function the resource abundance is now being kept fixed at the chosen
value. Then the resource dynamics can be switched on later with
setResource()
without changing the steady state. At that
stage you only choose either the resource intrinsic growth rate or the
resource carrying capacity and the other is determined by
setResource()
in such a way that the resource replenishes
at the same rate at which it is consumed. If you want to keep the old
behaviour and switch off this automatic balancing you have to add the
balance = FALSE
argument when calling
setResource()
.
You can also choose between semichemostat dynamics
resource_semichemostat()
or logistic dynamics
resource_logistic()
or you can write your own function
implementing more sophisticated resource dynamics.
The setParams()
function no longer includes the
arguments for setting the resource parameters. Instead you set these
separately with setResource()
.
As explained in the blog post at
https://blog.mizer.sizespectrum.org/posts/2022-11-30-dont-use-von-bertalanffy-growth-parameters/,
the von Bertalanffy curves fitted to size-at-age data are not suitable
for estimating the size-dependent growth rates in mizer. It is therefore
now recommended that instead of von Bertalanffy parameters you supply
the age at maturity in the age_mat
column of the species
parameter data frame. This is then used by mizer to calculate a default
for the maximum intake rate parameter h
if you do not
supply this.
In the past, whenever you changed any model parameters, you needed to
re-tune other parameters to keep the growth rates in line with
observations. There is now a new function matchGrowth()
that automatically scales the search volume, the maximum consumption
rate and the metabolic rate all by the same factor in order to achieve a
growth rate that allows individuals to reach their maturity size by
their maturity age while keeping the feeding level and the critical
feeding level unchanged. This function does not however preserve the
steady state, so you will need to also call steady()
after
matching the growth rates.
steadySingleSpecies()
that only balances
the size-spectrum dynamics while ignoring multi-species effects. In
other words, it calculates the steady-state size spectrum of each
species as it would be if the abundance of prey and predators could be
kept constant at their current values.plotGrowthCurves()
can now superimpose a scatterplot of
size-at-age data if you supply this via the new size_at_age
argument.calibrateNumber()
and
matchNumbers()
that are like
calibrateBiomass()
and matchBiomasses()
but
work with observed numbers instead of observed biomasses.age_mat()
to calculate the age at maturity
from the growth rate and the size at maturity.project()
now also works when called with a MizerSim
object with additional components.steady()
now preserves the RDD function in the
MizerParams object rather than always setting it to
“BevertonHoltRDD”.plotSpectra()
or
setInitialValues()
the user can now choose geometric
averaging with geometric_mean = TRUE
.w_mat25
species parameter is no longer filled in
automatically if it is not supplied. This makes it easier to change
w_mat
without having to change w_mat25
at the
same time.compareParams()
now also checks the validity of its
second argument.newTraitParams()
.info_level
argument in
newMultispeciesParams()
now leads to more messages.validSpeciesParams()
.
#136l2w()
and w2l()
for
converting between length-based and weight-based species parameters.
#258style
argument to plotDataFrame()
to
facilitate producing area plots.wrap_scale
argument to plotDataFrame()
to control scaling of axes in faceted plots.plotDiet()
can now show diets of several predator
species in a faceted plot. #267size
to linewidth
aesthetic to
avoid warnings in new version of ggplot2.compareParams()
says
so clearly.getReproductionLevel()
works as long as
R_max
is set. #252gear_params()
.defaults_edition()
. #186get_gamma_default()
ensures a
feeding level of f0
for larvae also if
interaction_resource
is not equal to 1. #238NS_params
set_species_default()
.
#268w_inf
no longer leads to error in
plyr::aaply()
. #269url
field in metadata.plotYieldObservedVsModel()
and
plotBiomassObservedVsModel()
. #266plotDiet()
restored after
change to ggplot2
package. #265mizerPredRate()
between the
argument t
and the function base::t()
.upgradeSim()
with a MizerSim object.getRequiredRDD()
renameSpecies()
no longer fails when linecolour and
linetype are of different lengths.setInitialValues()
can now average over a
time_range.getSSB()
, getBiomass()
,
getN()
, getYieldGear()
and
getYield()
can now be called with a MizerParams object as
well as with a MizerSim object. (#200)plotBiomassObservedVsModel()
and
plotYieldObservedVsModel()
contributed by @SamikDatta., together
with their plotly counterparts.calibrateBiomass()
, calibrateYield()
to set the model scale to agree with total observed biomass or total
observed yield. Uses the new scaleModel()
.matchBiomasses()
and matchYields()
will try to adjust the abundances of the species to produce the observed
biomasses or yields. See blog post at https://bit.ly/2YqXESV .params <- setReproduction(params, maturity = my_maturity)
one can simply use maturity(params) <- my_maturity
.
These are documented together with the setter functions. #213setMetadata()
to add information to a MizerParams
object describing the model, for example a title, a description, the
author or list of authors, a url and a doi. This will be particularly
useful for sharing your models with otherssaveParams()
for saving a MizerParams object to a
file and readParams()
for reading it back in. The resulting
files can be shared with others who want to run your model.getMetadata()
. This helps
you keep track of different versions of your model.steady()
now has a preserve
argument with
possible values erepro
, R_max
or
reproduction_level
to specify which quantity to preserve.
This means that one can continue to use steady()
also once
one has started to tune the density dependence in reproduction.
#208gear_params
are now set to “species,
gear”, so that one can access individual entries with for example
gear_params(NS_params)["Cod, Otter", "catchability"]
.
#212z0
argument of setExtMort()
has been
deprecated in favour of ext_mort
in order to avoid
confusion with the species parameter z0
.setColours()
and setLinetypes()
now issue
warnings when invalid values are given and ignores NAs.comment
arguments to the setter
functions have been removed. #214reset
argument which,
when set to TRUE
will recalculate the rates from the
species_, gear_ and resource_params even when custom values had been
set. #214species
argument to various functions, which is
checked with valid_species_arg()
, now does not throw an
error even when there is no valid species included. Only a warning is
issued. That means that for example
plotSpectra(NS_params, species = list(), total = TRUE)
is
now allowed.getComponent()
from the mizer extension mechanism now
returns NULL when asked for a non-existent component instead of giving
an error. This gives an easy way to check for the existence of a
component.inter
for the North Sea
model now has the alternative name NS_interaction
, with the
old name deprecated.addSpecies()
are now by default
given a reproduction level of 1/4 instead of 0, because at the low
densities at which they are introduced there would otherwise not be
enough density dependence to stabilise them.min_w
, max_w
,
min_l
and max_l
used in some summary functions
and processed by get_size_range_array()
accept vector
values setting different limits for different species.resource_rate
and the resource_capacity
as
arguments, which makes it easier to use them in extension packages.newMultispeciesParams()
, #199linecolour
or linetype
in the
species parameters now actually changes the linecolours and linetypes as
intended.getGrowthCurves()
and
plotted with plotGrowthCurves()
are now correct, and no
longer extend above the asymptotic size.plotGrowthCurves()
with
species_panel = TRUE
now respects the species
argument to only show growth curves for selected species, it works with
a MizerParams object as well as a MizerSim object, and it shows the
panels in the correct order. #201setBevertonHolt()
function has been expanded with
more arguments. It allows you to change the density dependence in
reproduction without changing the steady state of your model.getReproductionLevel()
function tells you at
what proportion of their maximum reproduction rate the species are
operating in your model.NS_sim
which holds a simulation of the North Sea
model.plotDataFrame()
allows easier creation of
plots.setInitialValues()
correctly preserves the gear names
on the initial effort. Thanks to Axel Rossberg.getFMort()
correctly passes the t
argument
on to any custom fishing mortality function you may have written.mizerPredMort()
suggested by Axel
Rossberg.plotSpectra()
now only shows those species in the
legend that are actually contained in the plot.initialNOther()
also works with MizerSim object.projectToSteady()
is called with
effort
, this effort is now also stored in the
initial_effort
slot.summary()
which is now using
sprintf()
for better formatting and also gives the
initial_effort.project_simple()
have been given
convenient defaults.projectToSteady()
.newSingleSpeciesParams()
for creating a
single species in a power-law background.animateSpectra()
creating an animated plot
of a simulation.addSpecies()
,
removeSpecies()
and renameSpecies()
.setComponent()
can now take any form, they no longer have
to be a named list.return_data
in the plot’s functions allows
to return the data frame used for the ggplot instead of the plot.steady()
no longer switches off the Beverton-Holt
density dependence. You can do this manually with
setBevertonHolt()
with R_factor = Inf
.getYield()
now also works with density-dependent
fishing mortality. Thanks to James Roger for discovering the
problem.gamma
argument now is no longer ignored in
newTraitParams()
but correctly overrides the
f0
argument. #188getFMort()
again works correctly when called with a
MizerSim object.resource_semichemostat()
no longer fail when at some
sizes both the resource growth rate and the resource mortality rate are
both zero.no_w
in newTraitParams()
is now always an integer.w_min_idx
should point to the start of the size
bin containing the egg size w_min
”.valid_species_arg()
is called with
species = NULL
and there are no background species then it
returns NULL
.getDiet()
and
plotDiet()
.projectToSteady()
to run the full dynamics
to steady state.distanceSSLogN()
and
distanceMaxRelRDI()
to measure distance between two
states.compareParams()
to compare two MizerParams
objects.constantEggRDI()
to allow keeping egg densities
fixed.customFunction()
to allow users to
overwrite mizer functions.plotGrowthCurves
as a panel of species with their
respective Von Bertalanffy curvesplotPredMort()
and
plotFMort
will stop displaying mortality values past the
species’ asymptotic size. The argumentall.sizes
allows you to continue to show these values.getFMort()
now passes time argument correctly.
#181validEffortArray()
now sets the dimnames correctly.
#173lifecycle
package to indicate status of some
functions and arguments as ‘experimental’ or ‘deprecated’.setFishing()
. #172species
argument in mizer
functions, via the new valid_species_arg()
function.
#170setInitialValues()
min_w_pp
is larger than
min_w
t
passed to dynamics functions has been
corrected.setReproduction()
now correctly sets the the total
proportion psi when the maturity proportion is changed.project()
has been simplified.
They are now either set by the arguments t_start
,
t_max
and t_save
or by the dimension names of
the effort
array.setRmax()
to setBevertonHolt()
and
allow it to work on an arbitrary MizerParams object. The old name
setRmax()
is still available as alias.mizerFMort()
now can also use the abundances and the
rates e_growth
and pred_mort
. This is useful
for example for implementing balanced harvesting.gear_params
is allowed to have zero rows.validGearParams()
the species name is used as gear
name in case gear_name
is NA.validGearParams()
ensures that all required arguments
of the selectivity function are supplied and checks validity of species
names.species_params()<-
suppresses warnings.steady()
fails because RDI is zero it gives a
meaningful error message.newCommunityParams()
now protects its zero investment
in reproduction with a comment.valid_species_arg()
checks
validity of species selection arguments.upgradeParams()
can now also upgrade old MizerParams
objects that do not have a consistent initial_effort
.validParams()
validates a
MizerParams object and automatically upgrades it with
upgradeParams()
if necessary.project()
or steady()
, #163.getRates()
to calculates all rates and
collects them in a list.steady()
with return_sim = TRUE
now
creates the MizerSim object the same way as project()
,
namely with the original values in the first time slot.species_params()
,
gear_params()
and resource_params()
.project()
.getRates()
functions by removing the
arguments that passed in other rates. Instead the required rates are now
always calculated within these functions.validGearParams()
handle NAs more gracefully and
check that there are no duplicates.upgradeParams()
works also on params objects that were
created with a development version of mizer.upgradeParams()
does a better job at guessing the value for
w_pp_cutoff
.getFeedingLevel()
, getPredMort()
,
setInitialValues()
and steady()
now work also
when model has extra components.plotFeedinglevel()
when called with
include_critical = TRUE
, see #162.species_params
is a tibble.params()
, effort()
and times()
to getParams()
,
getEffort()
and getTimes()
to avoid
conflicts.getDiet()
also takes into account possible
contributions by user-defined other components.project()
is called with
t_max < t_save
then t_save
is automatically
reduced so that the result at t_max
will get saved.project()
.project_simple()
that projects a
given number of time steps. This might be useful to extension
writers....
argument to project()
is passed on
to the dynamics and rate functions.steady()
runs faster by using
project_simple()
.summary()
now also works with non-default feeding
kernels. #159validSpeciesParams()
no longer fails when
w_mat25
is not specified. #160setInitialValues()
also works in a model with only a
single species. #161resource_params()<-
now works and has unit
tests.Some inconsistencies in the choice of names for parameters was removed by renaming
interaction_p
->
interaction_resource
r_resource
-> resource_rate
K_resource
-> resource_capacity
other_params()<-
and
other_params()
for setting and getting other parameters,
for example to be used in user-defined rate functions.setInitialValues()
also sets
initial_effort
. #157This is a major new release with many new features, an internal refactoring of the code and a new extension mechanism.
Nevertheless this version of mizer is almost fully backwards compatible with version 1.0 with the exception of bug fixes and the following breaking changes:
print_it
argument from plot functions.plotFeedingLevel()
now only plots the values within the
size range of each species. If for some reason you want the old plots
that show a feeding level also for sizes that the fish can never have,
you need to supply an argument all.sizes = TRUE
.RDD
argument in
setReproduction()
.sex_ratio
argument has been removed from
getRDI()
and getRDD()
.set_scaling_model()
function has been removed
because such models can now be set up with newTraitParams()
with the options perfect_scaling = TRUE
and
egg_size_scaling = TRUE
.display_frames()
,
addSpecies()
, setBackground()
and
retuneAbundance()
have been removed to the
“mizerExperimental” package
(https://sizespectrum.org/mizerExperimental/)project()
a progress bar is displayed by
default. You can turn this off with the option `progress_bar =
FALSE.The new functions
newCommunityParams()
newTraitParams()
newMultispeciesParams()
replace the old functions set_community_model()
,
set_trait_model()
and MizerParams()
, which are
now deprecated. The new functions choose better default values, in
particular for metabolic rate and maximum intake rate.
After setting up a mizer model, it is possible to change specific model parameters with the new functions
species_params<-()
resource_params<-()
gear_params<-()
setPredKernel()
setSearchVolume()
setInteraction()
setMaxIntakeRate()
setMetabolicRate()
setExtMort()
setReproduction()
setFishing()
setResource()
The new function setParams()
is a wrapper for all of the
above functions and is also used when setting up a new model with
newMultispeciesParams()
. (#51)
The documentation for these functions serves to explain the details of the mizer model.
Along with these setter functions there are accessor functions for
getting the parameter arrays: getPredKernel()
,
getSearchVolume()
, getInteraction()
,
getMaxIntakeRate()
, getMetabolicRate()
,
getExtMort()
, getMaturityProportion()
,
getReproductionProportion()
,
getCatchability()
, getSelectivity()
,
getResourceRate()
, getResourceCapacity()
,
getResourceParams()
,
getResourceDynamics()
,
setRmax()
.The MizerParams object now also contains the initial values for the
size spectra. This is particularly useful if the model has been tuned to
produce the observed steady state. The new function
steady()
finds a steady state for a model and sets it as
the initial value. The initial values can be accessed and changed via
functions initialN()
and initialNResource()
.
The initial values can be set to the final values of a previous
simulation with setInitialValues()
.
The MizerParams object now has a slot initial_effort
that specifies the initial fishing effort to which the steady state has
been calibrated.
Mizer now has an extension mechanism that allows other R packages to
be written to generalise the mizer model. See
setRateFunction()
and setComponent()
. This
mechanism is still experimental and may change as we gain experience in
writing extensions for mizer.
plotlyBiomass()
as the plotly version of
plotBiomass()
, and so on.plotGrowthCurves()
plots growth curves and compares
them to the von Bertalanffy growth curve.plotDiet()
plots the diet composition as a function
of predator size.highlight
argument to all plot functions that
display curves for multiple species. Displays highlighted species with
wider lines.plot()
method for MizerParams object to plot the
initial state.include_critical
in
plotFeedingLevel()
allows to show also the critical feeding
level.wlim
argument to plotSpectra()
in
analogy to the existing ylim
argument to limit the
w
range in the plot.setColours()
.solid
but this can be changed
via the setLinetypes()
function.box_pred_kernel()
implements a box-shaped kernel as
an alternative to the default lognormal_pred_kernel()
.power_law_pred_kernel()
implements a power-law
kernel with sigmoidal cutoffs at both ends. This is suitable for filter
feeders.setPredKernel()
). Mizer
automatically falls back on the old non-FFT code to handle this.
(#41)getPredKernel()
returns the full 3-dimensional
predation kernel array, even when this is not stored in MizerParams
object.Now it is finally possible to have several gears (or fleets)
targeting the same species. The information is set up via a new
gear_params()
data frame. See setFishing()
for
details.
w()
, w_full()
,
dw()
, dw_full()
.upgradeParams()
and upgradeSim()
can
upgrade objects from previous versions of mizer so they work with the
new version.getDiet()
calculates the diet of predators.
(#43)RickerRDD()
and
SheperdRDD()
for density-dependence in reproduction, as
well as noRDD()
and constantRDD()
.double_sigmoid_length()
allows modelling of escape of large individuals.sigmoidal_weight()
is
weight-based trawl selectivity function. (Ken H Andersen)getGrowthCurves()
calculates the growth curves
(size at age).mizerRates()
calculates all the rates needed in the
model and collects them in a list.times()
to extract the times at
which simulation results are saved in a MizerSim object.finalN()
,
finalNResource()
and finalNOther()
as well as
idxFinalT()
to access the values at the final time of a
simulation.getCriticalFeedingLevel()
returns the
critical feeding level for each species at each size.melt()
function from the reshape2
package which allows users to convert the arrays returned by mizer
functions into data frames that can be used for example in ggplot2 and
plotly.validSpeciesParams()
checks validity of species
parameter data frame and sets defaults for missing but required
parameters.n
, p
and
q
as well as the feeding level f0
can now be
set at the species level via columns in
species_params
.fc
can now be specified as a
species parameter and will be used to calculate the metabolic rate
parameter ks
if it is not supplied.project()
now shows a progress bar while a simulation
is running. Can be turned off with progress_bar = FALSE
argument.Inf
.resource_semichemostat()
.interaction_resource
column in the species parameter data
frame.w_mat25
column in the species parameter dataframe, which
gives the size at which 25% of the individuals of a species are
mature.m
column in the species parameter
data frame.project()
can now continue projection from last time
step of a previous simulation if the first argument is a MizerSim
object. The new append
argument then controls whether the
new results are appended to the old.newMultispeciesParams()
.n
,
n_pp
and n_other
arguments from the initial
values in the params
argument.perfect_scaling
argument allows
newTraitParams()
to produce a perfectly scale-invariant
model.ext_mort_prop
argument in
newTraitParams()
allows the inclusion of external
mortality.NS_params
with the North Sea model
MizerParams object.newMultispeciesParams()
.getmM2()
-> getPredMort()
plotM2
-> plotPredMort()
getM2background()
->
getResourceMort()
getZ()
-> getMort()
getESpawning()
-> getERepro()
MizerParams()
-> emptyParams()
or
set_multispecies_model()
r_max
to
R_max
.getSSB()
, the calculation of the spawning stock
biomass is done correctly using the maturity ogive instead of the
proportion of energy allocated to reproduction. (#47)getEncounter()
and getPredRate()
now set
names on the returned arrays.ylim
argument is not handled correctly in
plots.display_frame()
is now exported.plotGrowthCurves()
and getGrowthCurves()
also works when there is only a single speciest_start
argument in project()
is used
correctlyget_initial_n()
gets values for n
and
q
from params objectsummary()
of MizerParams object reflects the number of
non-empty resource bins. (@patricksykes)get_gamma_default()
, get_h_default()
and
get_ks_default()
, making it easier to change or extend
these in the future.set_species_param_default()
makes it
easier to set default values for species parameters.@inherit
functionality of roxygen2 to reduce
duplication in roxygen documentation.getPhiPrey()
is replaced by getEncounter()
which now returns the full encounter rate, including the contribution
from other components. Even in the absence of other components,
getEncounter()
differs from the old
getPhiPrey()
because it includes the search volume
factor.params
to refer to an argument of
class MizerParams, sim
to refer to an argument of class
MizerSim, and object
to an argument that can be
either.setClass()
to follow the new
guidelines, replacing representation
by class
and removing prototype
and validity
.shiny_progress
renamed to
progress_bar
because they control any type of progress
bar.outer()
instead of tapply()
where
possible to improve readability.hasArg()
and anyNA()
because they were not available in R 3.1@std_metab
and @activity
slots into
a single @metab
slot.@w_min_idx
out of @species_params
into its own slot.@maturity
to hold the maturity ogive.@pred_kernel
to hold predation kernel if it
has variable predator/prey ratio.@resource_dynamics
to allow user to specify
alternative resource dynamics.@gear_dynamics
to species to be targeted by
multiple gears.@ft_mask
that is used when calculating
predation rates using the Fourier transform method.@rates_funcs
to allow mizer extensions to
replace mizer rate functions with their own rate functions.@srr
we now have
the name of the function in @rate_funcs$RDD
, see #91.@other_dynamics
,
@other_params
, @other_encounter
,
@other_mort
and @initial_n_other
to allow
mizer extensions to add more ecosystem components.set_scaling_model()
, see section 12 in the vignette.PlotYield()
no longer fails when species names are
numbers or when a species abundance is zerototal
parameter to several plot functions to
add the curve for the total community (sum over all species and
resource)species
parameter to all plot functions to
allow for only a selection of species to be plotted@initial_n
and @initial_n_pp
slots to
MizerParams class.getPhiPrey()
and
getPredRate()
.getPhiPrey()
and
getPredRate()
.