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New solution

Source: R/class_Solution.R
new_solution.Rd

Create a new Solution object.

Usage

new_solution(
  name,
  variable,
  visible,
  invisible = NA_real_,
  loaded = TRUE,
  parameters,
  statistics,
  theme_results,
  weight_results,
  include_results,
  exclude_results,
  id = uuid::UUIDgenerate(),
  hidden = FALSE,
  downloadable = TRUE,
  pane = paste(uuid::UUIDgenerate(), variable$index, sep = "-")
)

Arguments

name

character name for new solution.

variable

Variable object with the solution.

visible

logical should the solution be visible on a map?

invisible

numeric date/time. A time stamp date given to when a loaded layer is first turned invisible. This is used to keep track of loaded invisible layers to offload once the cache threshold has been reached. Defaults to NA_real_.

loaded

logical The initial loaded value. This is used to determine if the feature is loaded (or not) or not the map. Defaults to FALSE.

parameters

list of Parameter objects.

statistics

list of Statistic objects.

theme_results

list of ThemeResults objects.

weight_results

list of WeightResults objects.

include_results

list of IncludeResults objects.

exclude_results

list of ExcludeResults objects.

id

character unique identifier. Defaults to a random identifier (uuid::UUIDgenerate()).

hidden

logical should the solution be hidden from map?

downloadable

logical can the solution be downloaded?

pane

character unique map pane identifier. Defaults to a random identifier (uuid::UUIDgenerate()) concatenated with layer index.

Examples

# find data file paths
f1 <- system.file(
  "extdata", "projects", "sim_raster", "sim_raster_spatial.tif",
  package = "wheretowork"
)
f2 <- system.file(
  "extdata",  "projects", "sim_raster", "sim_raster_attribute.csv.gz",
  package = "wheretowork"
)
f3 <- system.file(
  "extdata",  "projects", "sim_raster", "sim_raster_boundary.csv.gz",
  package = "wheretowork"
)

# create new dataset
d <- new_dataset(f1, f2, f3)

# create variables
v1 <- new_variable_from_auto(dataset = d, index = 1)
v2 <- new_variable_from_auto(dataset = d, index = 2)

# create features using variables
f1 <- new_feature(
  name = "Possum", variable = v2,
  goal = 0.2, status = FALSE, current = 0.5, id = "F1"
)

# create themes using the features
t1 <- new_theme("Species", f1, id = "T1")

# create a feature results object to store results for the feature
fr1 <- new_feature_results(f1, held = 0.8)

# create a theme results object to store results for the feature
tr1 <- new_theme_results(t1, fr1)

# create parameters
p1 <- new_parameter(name = "Spatial clustering")
p2 <- new_parameter(name = "Optimality gap")

# create a new solution
s <- new_solution(
  name = "solution001",
  variable = v2,
  visible = TRUE,
  parameters = list(p1, p2),
  statistics = list(),
  theme_results = list(tr1),
  weight_results = list(),
  include_results = list(),
  exclude_results = list(),
  id = "solution1",
  hidden = FALSE,
  downloadable = TRUE
)