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tidync (version 0.4.0)

tidync-package: tidync: A Tidy Approach to 'NetCDF' Data Exploration and Extraction

Description

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/.

Arguments

Author

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]

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.

activereport the currently active grid
activateactive a grid
tidynccore NetCDF source object for tidync functions
hyper_filterapply dimension expressions to specify array slices
hyper_arrayextracts a raw data array based on a NetCDF index
hyper_tbl_cubeextracts data as a dplyr tbl_cube
hyper_tibbleextracts data as a data frame with all dimension values
hyper_transformsextract the active (or all) dimension transforms
hyper_varsinformation on active variables
hyper_dimsinformation on active dimensions
hyper_gridsinformation 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/FALSEcheck for large data extraction (default TRUE)
tidync.silent = FALSE/TRUEemit warnings,messages or be silent (default FALSE)

See Also

Examples

Run this code
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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