maxent_call: maxent_call: Call maxent from R

In luismurao/ntbox: From Getting Biodiversity Data to Evaluating Species Distribution Models in a Friendly GUI Environment

maxent_call: Call maxent from R

Description

maxent_call Allows the user to introduce all the arguments that can be passed to MaxEnt. It also allows running MaxEnt from R.

Usage

maxent_call(
  maxentjar_path,
  run_fromR = TRUE,
  wait = TRUE,
  features,
  memory_assigned = 2000,
  environmentallayers,
  samplesfile,
  testsamplesfile = NULL,
  outputdirectory = NULL,
  projectionlayers = NULL,
  responsecurves = FALSE,
  pictures = TRUE,
  jackknife = FALSE,
  outputformat = "cloglog",
  randomseed = FALSE,
  logscale = TRUE,
  warnings = TRUE,
  askoverwrite = FALSE,
  skipifexists = FALSE,
  removeduplicates = TRUE,
  writeclampgrid = FALSE,
  writemess = FALSE,
  randomtestpoints = 0,
  betamultiplier = 1,
  maximumbackground = 10000,
  biasfile = "",
  biastype = 3,
  replicates = NULL,
  replicatetype = "crossvalidate",
  perspeciesresults = FALSE,
  writebackgroundpredictions = FALSE,
  responsecurvesexponent = FALSE,
  addsamplestobackground = TRUE,
  addallsamplestobackground = FALSE,
  autorun = TRUE,
  writeplotdata = FALSE,
  fadebyclamping = FALSE,
  extrapolate = FALSE,
  visible = FALSE,
  autofeature = FALSE,
  doclamp = FALSE,
  outputgrids = TRUE,
  plots = TRUE,
  appendtoresultsfile = FALSE,
  maximumiterations = 500,
  convergencethreshold = 1e-05,
  adjustsampleradius = 0,
  threads = 1,
  lq2lqptthreshold = 80,
  l2lqthreshold = 10,
  hingethreshold = 15,
  beta_threshold = -1,
  beta_categorical = -1,
  beta_lqp = -1,
  beta_hinge = -1,
  logfile = "maxent.log",
  cache = TRUE,
  defaultprevalence = 0.5,
  applythresholdrule = NULL,
  togglelayertype = NULL,
  togglespeciesselected = NULL,
  togglelayerselected = NULL,
  verbose = FALSE,
  allowpartialdata = FALSE,
  prefixes = TRUE,
  nodata = -9999
)

Arguments

maxentjar_path	Path to maxent.jar
run_fromR	Logical If TRUE, maxent will be executed from the current R session.
wait	Logical If TRUE, R will wait until maxent fishes to run the model. Default TRUE.
features	A vector with features classes to fit the maxent model. Use "l" for "linear","q" for "quadratic", "p" for "product", "h" for "hinge"and "t" for "threshold".
memory_assigned	A numeric value representing the RAM memory assigned to the process.
environmentallayers	Path to the directory containing environmental layers. Environmental variables can be in a directory containing one file per variable, or all together in a .csv file in SWD format. Please enter a directory name or file name.
samplesfile	Path to the file containing presence locations for one or more species.
testsamplesfile	Path to the file containing test locations.
outputdirectory	Path to the directory where model results will be written. if it is NULL the results will be written in the working directory.
projectionlayers	Path to the directory containing the projection layer.
responsecurves	Logical if TRUE creates graphs showing how predicted relative probability of occurrence depends on the value of each environmental variable.
pictures	Logical if TRUE creates a .png image for each output grid.
jackknife	Logical if TRUE measures the importance of each environmental variable by training with each environmental variable first omitted, then used in isolation.
outputformat	A character vector describing the type of output format to be written in model results. Representation of probabilities used in writing output grids. Possible output formats are cloglog, logistic, cumulative, and raw.
randomseed	Logical if TRUE, a different random seed will be used for each run, so a different random test/train partition will be made and a different random subset of the background will be used, if applicable.
logscale	Logical If TRUE, all pictures of models will use a logarithmic scale for color-coding.
warnings	Logical If TRUE, pops up windows to warn about potential problems with input data. Regardless of this setting, warnings are always printed to the log file.
askoverwrite	Logical if TRUE, the output files that already exist will be overwritten.
skipifexists	Logical if TRUE, skips the species without remaking the model.
removeduplicates	Logical if TRUE, removes duplicate presence records.
writeclampgrid	Logical if TRUE, writes clamp grid when projecting.
writemess	Logical if TRUE, does MESS analysis when projecting
randomtestpoints	Numeric. Percentage of presence localities to be randomly set aside as test points used to compute AUC, omission, etc.
betamultiplier	Numeric. Regularization multiplier. A higher number gives a more spread-out distribution.
maximumbackground	Numeric. Max number of background points.
biasfile	Path to the bias file. Sampling is assumed to be biased according to the sampling distribution given in this grid file. Values in this file must not be zero or negative.
biastype	Default 3. See https://groups.google.com/forum/#!topic/maxent/bZYdlYmDG4s for details.
replicates	Numeric. The number of replicate runs to do when cross-validating, bootstrapping, or doing sampling with replacement runs.
replicatetype	Character vector. Possible values are crossvalidate, bootstrap, and subsample. If replicates > 1, do multiple runs of this type: Crossvalidate: samples divided into replicates folds; each fold in turn used for test data. Bootstrap: replicate sample sets chosen by sampling with replacement. Subsample: replicate sample sets chosen by removing random test percentage without replacement to be used for evaluation.
perspeciesresults	Logical, if TRUE write separate maxentResults file for each species.
writebackgroundpredictions	Logical if TRUE, will write .csv file with predictions at background points.
responsecurvesexponent	Logical if TRUE, shows exponent in response curves.
addsamplestobackground	Logical if TRUE adds samples to background.
addallsamplestobackground	Logical if TRUE adds all samples to background.
autorun	Logical if TRUE starts running as soon as the program starts up.
writeplotdata	Logical if TRUE writes plot data.
fadebyclamping	Logical if TRUE reduces prediction at each point in projections by the difference between clamped and non-clamped output at that point.
extrapolate	Logical, If TRUE predicts to regions of environmental space outside the limits encountered during training
visible	Logical If TRUE makes the Maxent user interface visible.
autofeature	Logical If TRUE Automatically selects which feature classes to use, based on the number of training samples
doclamp	Logical If TRUE applies clamping when projecting
outputgrids	Logical If TRUE writes output grids. Turning this off when doing replicate runs causes only the summary grids (average, std deviation, etc.) to be written, not those for the individual runs.
plots	Logical If TRUE writes various plots for inclusion in .html output.
appendtoresultsfile	Logical If FALSE, maxentResults.csv file is reinitialized before each run.
maximumiterations	Numeric. Stop training after this many iterations of the optimization algorithm.
convergencethreshold	Numeric. Stop training when they drop in log loss per iteration drops below this number.
adjustsampleradius	Numeric. Add this number of pixels to the radius of white/purple dots for samples on pictures of predictions. Negative values reduce the size of dots.
threads	Numeric. The number of processor threads to use. Matching this number to the number of cores on your computer speeds up some operations, especially variable jackknifing.
lq2lqptthreshold	Numeric. The number of samples at which product and threshold features start being used.
l2lqthreshold	Numeric. The number of samples at which quadratic features start being used.
hingethreshold	Numeric. The number of samples at which hinge features start being used.
beta_threshold	Numeric. Regularization parameter to be applied to all threshold features; negative value enables automatic setting.
beta_categorical	Numeric. Regularization parameter to be applied to all categorical features; negative value enables automatic setting.
beta_lqp	Numeric. Regularization parameter to be applied to all linear, quadratic, and product features; negative value enables automatic setting.
beta_hinge	Numeric. Regularization parameter to be applied to all hinge features; negative value enables automatic setting.
logfile	Filename to be used for writing debugging information about a run in the output directory.
cache	Logical If TRUE makes a .mxe cached version of ascii files, for faster access.
defaultprevalence	Numeric. Default prevalence of the species: the probability of presence at ordinary occurrence points. See Elith et al., Diversity and Distributions, 2011 for details.
applythresholdrule	Apply a threshold rule, generating a binary output grid in addition to the regular prediction grid. Use the full name of the threshold rule in Maxent's html output as the argument. For example, 'applyThresholdRule=Fixed cumulative value 1'.
togglelayertype	Toggle selection of environmental layers whose names begin with this prefix (default: all selected).
togglespeciesselected	String Toggle selection of species whose names begin with this prefix (default: all selected)
togglelayerselected	String. Toggle selection of environmental layers whose names begin with this prefix (default: all selected)
verbose	Logical If TRUE gives a detailed diagnostics for debugging.
allowpartialdata	Logical If TRUE During model training, allow the use of samples that have nodata values for one or more environmental variables..
prefixes	Logical If TRUE during model training, allow the use of samples that have nodata values for one or more environmental variables.
nodata	Numeric. Default nodata value.

Details

The documentation of the parameters of this function are based on maxent´s help. For detailed documentation of the parameter that can be passed to maxent go to https://github.com/mrmaxent/Maxent/blob/master/density/parameters.csv.

Value

A character vector with maxent's parametrization.

Examples

## Not run: 
environmentallayers <- system.file("extdata",
                                   package = "ntbox")
maxent_path <- "~/Downloads/maxent"
outputdirectory <- "~/Downloads/"
occ_data_path <- system.file("extdata",
                            "cardon_occs.csv",
                            package = "ntbox")
maxent_parm <- maxent_call(maxentjar_path = maxent_path,run_fromR=TRUE,
                          environmentallayers = environmentallayers,
                          samplesfile=occ_data_path,
                          betamultiplier = .1,
                          features=c("l","q","p"),
                          outputdirectory = outputdirectory)
print(maxent_parm)

## End(Not run)

luismurao/ntbox documentation built on Nov. 22, 2024, 4 a.m.