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Create Predictor Metadata Table

Source: R/pred_meta_t.R
pred_meta_t.Rd

Construct and validate pred_meta_t objects, which are used to store predictor metadata.

Usage

as_pred_meta_t(x)

create_pred_meta_t(pred_spec)

# S3 method for class 'pred_meta_t'
print(x, ...)

Arguments

x

An object that is accepted by data.table::setDT()

pred_spec

A list of predictor specifications, schema: see examples

...

passed to data.table::print.data.table()

Value

A data.table of class "pred_meta_t" with columns:

  • id_pred: Unique ID for each predictor

  • name: Name for use in code and queries

  • pretty_name: Name for plots/output

  • description: Long description / operationalisation

  • orig_format: Original format description

  • sources: Sources, a data.frame with cols url and md5sum

  • unit: SI-compatible unit (nullable for categorical)

  • factor_levels: Map of factor levels (nullable)

Methods (by generic)

  • print(pred_meta_t): Print an pred_meta_t object, passing params to data.table print

Functions

  • create_pred_meta_t(): Creates a pred_meta_t table from intervention specifications

Examples

create_pred_meta_t(list(
   noise = list(
     unit = "dBa",
     pretty_name = "Maximum noise exposure",
     orig_format = "10m*10m raster",
     description = "daytime & nighttime road & rail noise exposure",
     sources = list(
       list(
         url = "https://data.geo.admin.ch/ch.bafu.laerm-strassenlaerm_tag/laerm-strassenlaerm_tag/laerm-strassenlaerm_tag_2056.tif",
         md5sum = "a4b9f1c04ee63824f18852bfd1eecbdd"
       ),
       list(
         url = "https://data.geo.admin.ch/ch.bafu.laerm-bahnlaerm_nacht/laerm-bahnlaerm_nacht/laerm-bahnlaerm_nacht_2056.tif",
         md5sum = "4b782128495b5af8467e2259bd57def2"
       )
     )
   ),
   distance_to_lake = list(
     unit = "m",
     pretty_name = "Distance to closest lake",
     orig_format = "vector",
     description = "Derived from swissTLM3D",
     sources = list(list(
       url = "https://data.geo.admin.ch/ch.swisstopo.swisstlm3d/swisstlm3d_2025-03/swisstlm3d_2025-03_2056_5728.gpkg.zip",
       md5sum = "ecb3bcfbf6316c6e7542e20de24f61b7"
     ))
   )
 ))
#> Predictor Metadata Table
#> Number of predictors: 2
#>                name              pretty_name
#>              <char>                   <char>
#> 1:            noise   Maximum noise exposure
#> 2: distance_to_lake Distance to closest lake
#> 5 variables not shown: [description <char>, orig_format <char>, sources <list>, unit <char>, factor_levels <list>]