dshm_plot: Plotting prediction grid

In FilippoFranchini/dshm: Density surface modelling unsing Hurdle approach for zero inflation

Description

dshm_plot plots prediction grids, makes easier changing scale colours and intervals, provides the possibility to save the grid as a .shp file.

Usage

dshm_plot(prediction, grid, probability = FALSE, sightings = NULL,
  plot_title = NULL, scale_col = c("blue", "yellow", "red"),
  scale_lim = NULL, scale_val = NULL, cex = 1, saveRaster = FALSE,
  raster_name = NULL, resolution)

Arguments

prediction	Predictions for each grid cell in the prediction grid.
grid	Grid as SpatialPolygonsDataFrame.
probability	If TRUE colour label is Pr(Presence), if FALSE is Abundance. Default is FALSE.
sightings	sighting dataframe with at least three columns: x: sighting x coordinate. y: sighting y coordinate. size: sighting size.
plot_title	Title of the plot.
scale_col	Vector with colour scale values. Length should correspond to the length of 'scale_val'.
scale_lim	Vector for lower and upper limits of the colour scale.
scale_val	Vector for the scale values corresponding to colour transition as defined in 'scale_col'.
cex	Size of the pixels in the map (visualization purpose only, for true scaled spatial map save as raster).
saveRaster	If TRUE the map is saved as a raster file. Default is TRUE.
raster_name	Name of the saved raster.
resolution	Raster resolution.

Details

For more information about fitting Hurdle models, plotting model predictions and much more you can download the fitting_Hurldle.pdf tutorial.

Value

Prediction map and raster image (if saveRaster = TRUE).

Author(s)

Filippo Franchini [e-mail]

FilippoFranchini/dshm documentation built on April 25, 2020, 9:40 p.m.