tidync-package: Tidy tools for NetCDF data.

Description Details Examples

Description

Provides easy to use idioms for working with NetCDF data for extraction, manipulation and visualization. NetCDF is Network Common Data Form https://www.unidata.ucar.edu/software/netcdf/.

Details

See print.tidync() for details on the printed version of a tidync object.

There is a family of functions "hyper_verb" around exploring and extracting data.

active report the currently active grid
activate active a grid
tidync core NetCDF source object for tidync functions
hyper_filter apply dimension expressions to specify array slices
hyper_array extracts a raw data array based on a NetCDF index
hyper_tbl_cube extracts data as a dplyr tbl_cube
hyper_tibble extracts data as a data frame with all dimension values
hyper_transforms extract the active (or all) dimension transforms
hyper_vars information on active variables
hyper_dims information on active dimensions
hyper_grids information on grids

The scheme generally processes dimension filters into NetCDF extraction indexes and these are always available to each function, and are expressed in printed output.

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
argofile <- system.file("extdata/argo/MD5903593_001.nc", package = "tidync")
argo <- tidync(argofile)
argo %>% active()
argo %>% activate("D3,D8") %>% hyper_array()
argo %>% hyper_filter(N_LEVELS = index < 4)
argo %>% hyper_tbl_cube()
argo %>% hyper_tibble(select_var = c("TEMP_QC"))
argo %>% hyper_transforms()
argo %>% hyper_vars()
argo %>% hyper_dims()
argo %>% hyper_grids()

tidync documentation built on July 1, 2020, 6:09 p.m.