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caretSDM (version 1.1.0.1)

plot_occurrences: S3 Methods for plot and mapview

Description

This function creates different plots depending on the input.

Usage

plot_occurrences(i, spp_name = NULL, pa = TRUE)
plot_grid(i)
plot_predictors(i, variables_selected = NULL)
plot_scenarios(i, variables_selected = NULL, scenario = NULL)
plot_predictions(
  i,
  spp_name = NULL,
  scenario = NULL,
  id = NULL,
  ensemble = TRUE,
  ensemble_type = "mean_occ_prob"
)
mapview_grid(i)
mapview_occurrences(i, spp_name = NULL, pa = TRUE)
mapview_predictors(i, variables_selected = NULL)
mapview_scenarios(i, variables_selected = NULL, scenario = NULL)
mapview_predictions(
  i,
  spp_name = NULL,
  scenario = NULL,
  id = NULL,
  ensemble = TRUE,
  ensemble_type = "mean_occ_prob"
)

Value

The plot or mapview desired.

Arguments

i

Object to be plotted. Can be a input_sdm, but also occurrences or sdm_area.

spp_name

A character with species to be plotted. If NULL, the first species is plotted.

pa

Boolean. Should pseudoabsences be plotted together? (not implemented yet.)

variables_selected

A character vector with names of variables to be plotted.

scenario

description

id

The id of models to be plotted (only used when ensemble = FALSE). Possible values are row names of get_validation_metrics(i).

ensemble

Boolean. Should the ensemble be plotted (TRUE)? Otherwise a prediction will be plotted

ensemble_type

Character of the type of ensemble to be plotted. One of: "mean_occ_prob", "wmean_AUC" or "committee_avg"

Author

Luíz Fernando Esser (luizesser@gmail.com) https://luizfesser.wordpress.com

Details

We implemented a bestiary of plots to help visualizing the process and results. If you are not familiar with mapview, consider using it to better visualize maps.

See Also

WorldClim_data