A Tidy Approach to 'NetCDF' Data Exploration and Extraction

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().


tidync 0.1.1

  • Package improvements thanks to CRAN feedback, clarified Description and added more examples. Replaced cat and print() calls with message() and warning().

  • New class 'tidync_data' for output of 'hyper_array()', no underlying change to the object which is simply a list of arrays from each variable, and axis transforms stored in an attribute.

  • Old deprecated function 'axis_transforms()' now Defunct.

tidync 0.1.0

  • FIRST RELEASE, tidync benefitted greatly from the rOpenSci review process.

  • New function hyper_grids() to report available grid names.

  • A printing error of dimension value ranges is now fixed, thanks to James Goldie (#84).

  • Now supports 'NC_CHAR' type, by exploding these into the array size expected.

  • Breaking change: when using tidync$gridit's now expected that this must be tidyr::unnest()ed in order to expand out the grid list per variable, in line with https://github.com/hypertidy/ncmeta/issues/26.

  • The hyper_array function now stores the relevant transforms table as an attribute "transforms" so that objects can be constructed directly from the raw array output.

tidync 0.0.3

  • Function rename hyper_array now matches hyper_tibble indicating the form of the output (rather than the action used, was hyper_slice).

  • New utilities hyper_vars and hyper_dims for reporting on the currently active variables and dimensions and their hyper_filter status.

  • dependent on ncmeta >= 0.0.2, partly to avoid crashing on invalid source/file strings

  • removed hyper_index and incorporated that into hyper_filter, there's now only one delay-capable class which is "tidync"

tidync 0.0.2

  • hyper_filter now uses a selection idiom, to record the state of the axis rather than explicitly filter it. This means we can have more flexibility on what the axis transform tables can be used for, and removes some unwieldy handling code. All the available axes are on the object from first contact, which means we can program against the entire space in the source which will help for complex mapping scenarios.

  • hyper filter print now handles the case of char-type coordinate values by setting the min and max to NA_real_

  • various improvements and fixes for the print method for tidync

  • support coordinate-less dimensions has been added, there is new information in the print summary about which dimensions are a "coord_dim" and this results in the axis transform tables using the index as the 'coordinate value'

  • hyper_slice and hyper_tibble now return all variables that exist within a grid

  • This version sees a new model is applied where activation is on 'grids', effectively a 'space' composed of dimensions. In addition to the variables, dimension, attributes we add "grid" defined by a set of dimensions, and "axis" which is an instance of a particular dimension as used by a variable.

  • files without recognizable variables now gracefully handled, with help from ncmeta

tidync 0.0.1

  • imports ncdump > 0.0.3

  • Installed external example data from Unidata website

  • First working version now has 'tidync', and 'hyper_' family of functions.

  • Migrated from ncdump.

Reference manual

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0.2.4 by Michael Sumner, a year ago


Report a bug at https://github.com/ropensci/tidync/issues

Browse source code at https://github.com/cran/tidync

Authors: Michael Sumner [aut, cre] , Simon Wotherspoon [ctb] , Tomas Remenyi [ctb] , Ben Raymond [ctb] , Jakub Nowosad [ctb] , Tim Lucas [ctb] , Hadley Wickham [ctb]

Documentation:   PDF Manual  

GPL-3 license

Imports dplyr, forcats, magrittr, ncdf4, ncmeta, purrr, RNetCDF, rlang, tibble, tidyr

Suggests ggplot2, knitr, rmarkdown, testthat, covr, cubelyr

Suggested by heatwaveR.

See at CRAN