Replaces the six-step preamble every pipeline script used to repeat: open the store, read the points, read the predictor types, align the points to the store, read the raster resolution, and verify the store can serve this configuration.
Usage
dsm_load(
patch_dir,
points = NULL,
type_table = NULL,
windows = NULL,
cell_size = NULL,
raster_table = NULL,
target_col = NULL,
verbose = TRUE
)Arguments
- patch_dir
Directory written by the extraction step – or the
dsm_storedsm_prepare() returned, in which case nothing else is needed.- points
Point table, or a path to the CSV written by stage 01. NULL for a store written by dsm_prepare(), which carries its own copy.
- type_table
Predictor types, or a path to its CSV. NULL as above.
- windows
Windows to load. NULL loads every window the store has, which is the wrong default when the grid needs two of five – pass the windows the grid actually uses and the store reads only those. integer(0) loads none: the store's table alone, from which a fold cache reads each window it needs from its file (dsm_final()'s workers do).
- cell_size
Raster resolution in x/y units. NULL reads it from
raster_table, which is the only source that cannot drift.- raster_table
Path to raster_table_used.csv, for
cell_size.- target_col
Expected target column, for the store lock.
- verbose
Print the loaded data.
Value
A dsm_data object. $transform is the target transform the store
was built under – name, forward and inverse – or NULL when the store did
not record one.
Examples
ex <- example_landscape()
store <- dsm_prepare(ex$profiles, target = "soc_stock", raster_dir = ex$raster_dir,
windows = c(3, 7), out_dir = file.path(tempdir(), "landscape"),
percentage = "^clay_pct$", transform = "log1p", n_cores = 1,
overwrite = TRUE, verbose = FALSE)
dsm_load(store, windows = integer(0)) # the table alone: loading windows needs torch
#> Loading patch store: 160 points x 8 channels | windows none (the table only)
#> <dsm_data>
#> points : 160
#> channels : 8
#> windows : none loaded (the table only)
#> target : soc_stock
#> transform : log1p
#> cell size : 0.0025
#> <dsm_data>
#> points : 160
#> channels : 8
#> windows : none loaded (the table only)
#> target : soc_stock
#> transform : log1p
#> cell size : 0.0025