A grid is a discretized space, defined by a set of dimensions. These are the spaces used
by one or more variables in a source. Traditional summaries are organized by variable, but
when organized by space or grid we can treat multiple variables together using standard
database techniques.
Usage
nc_grids(x, ...)
# S3 method for class 'character'
nc_grids(x, ...)
# S3 method for class 'NetCDF'
nc_grids(x, ...)
# S3 method for class 'tidync'
nc_grids(x, ...)Value
data frame of grid information, one row per grid, with columns 'grid' (a label of the dimensions in the grid), 'ndims', 'variables' (a nested data frame of the variables defined on the grid), 'nvars'
Details
Each data source has a set of dimensions available for use by variables. Each grid is an n-dimensional space available for use by 0, 1 or more variables. A grid only really exists if variable is defined for it, and 'grid' is an implicit entity not an explicit part of the NetCDF API definition. The Unidata pages refer to "shape", which is more or less what we mean by "grid".
Examples
f <- system.file("extdata", "S2008001.L3m_DAY_CHL_chlor_a_9km.nc", package = "ncmeta")
nc_grids(f)
#> # A tibble: 4 × 4
#> grid ndims variables nvars
#> <chr> <int> <list> <int>
#> 1 D1,D0 2 <tibble [1 × 1]> 1
#> 2 D3,D2 2 <tibble [1 × 1]> 1
#> 3 D0 1 <tibble [1 × 1]> 1
#> 4 D1 1 <tibble [1 × 1]> 1