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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"
)

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"

Value

The plot or mapview desired.

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

Author

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