This function creates different plots depending on the input.
plot_occurrences(i, spp_name = NULL, pa = TRUE, pa_id = 1)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"
)
plot_background(i, variables_selected = NULL)
plot_niche(
i,
spp_name = NULL,
variables_selected = NULL,
scenario = NULL,
id = NULL,
ensemble = TRUE,
ensemble_type = "mean_occ_prob",
raster = FALSE
)
The plot or mapview desired.
Object to be plotted. Can be a input_sdm, but also occurrences or
sdm_area.
A character with species to be plotted. If NULL, the first species is plotted.
Boolean. Should pseudoabsences be plotted together? (not implemented yet.)
The id of pseudoabsences to be plotted (only used when pa = TRUE). Possible
values are numeric values from 1 to number of PA sets.
A character vector with names of variables to be plotted.
description
The id of models to be plotted (only used when ensemble = FALSE). Possible
values are row names of get_validation_metrics(i).
Boolean. Should the ensemble be plotted (TRUE)? Otherwise a prediction will be plotted
Character of the type of ensemble to be plotted. One of: "mean_occ_prob", "wmean_AUC" or "committee_avg"
Should the niche be extrapolated to a raster covering all possibe values in the environmental space?
Luíz Fernando Esser (luizesser@gmail.com) https://luizfesser.wordpress.com
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.
WorldClim_data