EvalWorkspace class — EvalWorkspace • SticsREval

Manage the evaluation workspace

Methods

Public methods

EvalWorkspace$new()
EvalWorkspace$save_sim()
EvalWorkspace$save_obs()
EvalWorkspace$get_species()
EvalWorkspace$get_species_usm()
EvalWorkspace$get_sim()
EvalWorkspace$get_obs()
EvalWorkspace$save_stats()
EvalWorkspace$save_global_stats()
EvalWorkspace$get_stats()
EvalWorkspace$get_global_stats()
EvalWorkspace$save_rmse_per_usm()
EvalWorkspace$get_rmse_per_usm()
EvalWorkspace$save_deteriorated_usm()
EvalWorkspace$get_deteriorated_usm()
EvalWorkspace$save_species_comparison()
EvalWorkspace$save_global_comparison()
EvalWorkspace$get_species_comparison()
EvalWorkspace$get_global_comparison()
EvalWorkspace$save_metadata()
EvalWorkspace$add_evaluated_version()
EvalWorkspace$get_all_versions()
EvalWorkspace$get_stics_version()
EvalWorkspace$with_version()
EvalWorkspace$set_version()
EvalWorkspace$get_version()
EvalWorkspace$remove_init_obs()
EvalWorkspace$clone()

`EvalWorkspace$new()`

Create an evaluation workspace manager

Usage

EvalWorkspace$new(data_dir, version = NULL)

Arguments

data_dir: Path to the evaluation workspace
version: Optional, the version of STICS to use for the data extraction. If not defined the last evaluated version will be used.

`EvalWorkspace$save_sim()`

Save simulations

Usage

EvalWorkspace$save_sim(sim, usms_species)

Arguments

sim: the list of simulations
usms_species: a dataframe which associates a USM to its species

`EvalWorkspace$save_obs()`

Save observations

Usage

EvalWorkspace$save_obs(obs, usms_species)

Arguments

obs: the list of observations
usms_species: a dataframe which associates a USM to its species

`EvalWorkspace$get_species()`

Returns the list of species

Usage

EvalWorkspace$get_species()

Returns

a list of species as character list

`EvalWorkspace$get_species_usm()`

Returns the list of USMs of a species

Usage

EvalWorkspace$get_species_usm(species, usms = NULL)

Arguments

species: the species to search for
usms: Optional, filter the USMs returned by the function

Returns

a list of USMs as a character list

`EvalWorkspace$get_sim()`

Return the simulation

Usage

EvalWorkspace$get_sim(
  species = NULL,
  usms = NULL,
  var2exclude = NULL,
  collect = TRUE
)

Arguments

species: Optional, if defined filter the simulations with this species
usms: Optional, if defined filter the simulations with these USMs
var2exclude: Optional, if defined remove the variables from the returned simulations
collect: Optional, if TRUE a dataframe will be returned, otherwise the lazy arrow data object will be returned

Returns

a dataframe if collect is TRUE, a lazy arrow data object

`EvalWorkspace$get_obs()`

Return the observation

Usage

EvalWorkspace$get_obs(
  species = NULL,
  usms = NULL,
  var2exclude = NULL,
  collect = TRUE
)

Arguments

species: Optional, if defined filter the observations with this species
usms: Optional, if defined filter the observations with these USMs
var2exclude: Optional, if defined remove the variables from the returned observations
collect: Optional, if TRUE a dataframe will be returned, otherwise the lazy arrow data object will be returned

Returns

a dataframe if collect is TRUE, a lazy arrow data object

`EvalWorkspace$save_stats()`

Save a species statistics

Usage

EvalWorkspace$save_stats(species, stats)

Arguments

species: the species
stats: the statistics as a dataframe

`EvalWorkspace$save_global_stats()`

Save global statistics

Usage

EvalWorkspace$save_global_stats(stats)

Arguments

stats: the global statistics as a dataframe

`EvalWorkspace$get_stats()`

Return statistics for a species

Usage

EvalWorkspace$get_stats(species, collect = FALSE)

Arguments

species: the species
collect: Optional, if TRUE returns a dataframe, otherwise a lazy arrow data object will be returned

Returns

the statistics, as a dataframe if collect is TRUE, a lazy arrow data object otherwise

`EvalWorkspace$get_global_stats()`

Return global statistics

Usage

EvalWorkspace$get_global_stats(collect = FALSE)

Arguments

collect: Optional, if TRUE returns a dataframe, otherwise a lazy arrow data object will be returned

Returns

the global statistics, as a dataframe if collect is TRUE, a lazy arrow data object otherwise

`EvalWorkspace$save_rmse_per_usm()`

Save the RMSE per USM

Usage

EvalWorkspace$save_rmse_per_usm(species, rmse_per_usm)

Arguments

species: the species
rmse_per_usm: the RMSE per USMs

`EvalWorkspace$get_rmse_per_usm()`

Return the RMSE per USM for a species

Usage

EvalWorkspace$get_rmse_per_usm(
  species = NULL,
  collect = FALSE,
  usms = NULL,
  var2exclude = NULL
)

Arguments

species: Optional, the species
collect: Optional, if TRUE a dataframe will be returned, otherwise a lazy arrow data object will be returned
usms: Optional, if defined filter the RMSE per USM with these USMs
var2exclude: Optional, if defined remove the variables from the returned RMSE per USM

Returns

the RMSE per USM for a species, as a dataframe if collect is TRUE, a lazy arrow data object otherwise

`EvalWorkspace$save_deteriorated_usm()`

Save the deteriorated USM

Usage

EvalWorkspace$save_deteriorated_usm(deteriorated)

Arguments

deteriorated: the deteriorated USM object

`EvalWorkspace$get_deteriorated_usm()`

Get the deteriorated USM comparison for a species

Usage

EvalWorkspace$get_deteriorated_usm(species, percentage)

Arguments

species: the species
percentage: the percentage

Returns

a DeterioratedUSMComparison object

`EvalWorkspace$save_species_comparison()`

Save the species comparison

Usage

EvalWorkspace$save_species_comparison(spec_comparison)

Arguments

spec_comparison: the species comparison object

`EvalWorkspace$save_global_comparison()`

Save the global comparison

Usage

EvalWorkspace$save_global_comparison(spec_comparison)

Arguments

spec_comparison: the global comparison object

`EvalWorkspace$get_species_comparison()`

Get the species comparison for a species

Usage

EvalWorkspace$get_species_comparison(species, percentage)

Arguments

species: the species
percentage: the percentage

Returns

an RmseComparison object

`EvalWorkspace$get_global_comparison()`

Get the global comparison

Usage

EvalWorkspace$get_global_comparison(percentage)

Arguments

percentage: the percentage

Returns

an RmseComparison object

`EvalWorkspace$save_metadata()`

Save the metadata

Usage

EvalWorkspace$save_metadata(metadata)

Arguments

metadata: the metadata dataframe

`EvalWorkspace$add_evaluated_version()`

Add an evaluated version to the metadata

Usage

EvalWorkspace$add_evaluated_version(version)

Arguments

version: the STICS version

`EvalWorkspace$get_all_versions()`

Get all evaluated versions

Usage

EvalWorkspace$get_all_versions()

Returns

a list of versions

`EvalWorkspace$get_stics_version()`

Get the last evaluated STICS version

Usage

EvalWorkspace$get_stics_version()

Returns

the STICS version

`EvalWorkspace$with_version()`

Create a new EvalWorkspace with a specific version

Usage

EvalWorkspace$with_version(version)

Arguments

version: the version

Returns

an EvalWorkspace object

`EvalWorkspace$set_version()`

Set the version of the evaluation workspace

Usage

EvalWorkspace$set_version(v)

Arguments

v: the version to set

`EvalWorkspace$get_version()`

Get the current version of the evaluation workspace

Usage

EvalWorkspace$get_version()

Returns

the current version of the evaluation workspace

`EvalWorkspace$remove_init_obs()`

Remove the initial observations (HR_1 to HR_5, AZnit_1 to AZnit_5, resmes and azomes) from the observations dataset This function is used to remove the initial observations from the dataset, which are not relevant for the evaluation and can bias the results. The initial observations are defined as the observations of the first date of each situation (USM) for the variables HR_1 to HR_5 and AZnit_1 to AZnit_5, resmes and azomes. This function will replace the initial observations by NA in the dataset.

Usage

EvalWorkspace$remove_init_obs()

`EvalWorkspace$clone()`

The objects of this class are cloneable with this method.

Usage

EvalWorkspace$clone(deep = FALSE)

Arguments

deep: Whether to make a deep clone.

Examples

if (FALSE) { # \dontrun{
ws <- EvalWorkspace$new(
  data_dir = "/path/to/eval_workspace"
)
} # }