tidync-package | R Documentation |
Tidy tools for 'NetCDF' data sources. Explore the contents of a 'NetCDF' source (file or URL) presented as variables organized by grid with a database-like interface. The hyper_filter() interactive function translates the filter value or index expressions to array-slicing form. No data is read until explicitly requested, as a data frame or list of arrays via hyper_tibble() or hyper_array().
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/.
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.
The following options are available.
tidync.large.data.check = TRUE/FALSE | check for large data extraction (default TRUE ) |
tidync.silent = FALSE/TRUE | emit warnings,messages or be silent (default FALSE ) |
Maintainer: Michael Sumner mdsumner@gmail.com
Other contributors:
Simon Wotherspoon [contributor]
Tomas Remenyi [contributor]
Ben Raymond [contributor]
Jakub Nowosad [contributor]
Tim Lucas [contributor]
Hadley Wickham [contributor]
Adrian Odenweller [contributor]
Patrick Van Laake [contributor]
Fabian Bernhard [contributor]
Useful links:
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()
## some global options
getOption("tidync.large.data.check")
getOption("tidync.silent")
op <- options(tidync.silent = TRUE)
getOption("tidync.silent")
options(op)
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