tidync-package: Tidy tools for NetCDF data.

In r-gris/tidync: A Tidy Approach to 'NetCDF' Data Exploration and Extraction

Tidy tools for NetCDF data.

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

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()

r-gris/tidync documentation built on April 5, 2022, 10:55 a.m.