Welcome to iconarray’s documentation!

Contents

Welcome to iconarray’s documentation!#

The iconarray python package contains various modules to facilitate working with ICON data with xarray or other xarray based tools (such as psyplot - a plotting package). iconarray was developed together with icon-vis.

Getting started

New to iconarray? Check out the getting started guide. This instructs you how to create your conda environment, and using iconarray at CSCS.

API reference#

This page provides an auto-generated summary of iconarray’s API.

Core functions#

`crop`	functionality to crop both ICON grids and datasets on any grid location.
`crop.Crop`(grid, lon_bnds, lat_bnds[, ...])	Cut the domain of an ICON grid and data to a region specified by a lat/lon retangle.
`latlonhash`	Functionality to locate ICON grid indices associated to lat/lon grid coordinates via hashing the indices in a Cartesian grid.
`latlonhash.Icon2latlon`(grid[, scale_factor])	Creates a field in a Cartesian lat/lon grid whose elements contain the ICON grid indices of the element whose lat/lon coordinates are contained within the cartesian element.
`utilities`	The utilities.py module contains various functions useful for analysing or plotting (ICON) data using xarray.
`utilities.ind_from_latlon`(lon_array, ...[, ...])	Find the indices of the n closest cells in a grid, relative to a given latitude/longitude point.
`utilities.show_data_vars`(ds)	Print a table with variables in dataset.
`interpolate`	The functions in interpolate.py are used to facilitate the interpolation of ICON vector data to a regular grid, or a coarser ICON grid, for the purpose of vectorplots, e.g., wind plots.
`interpolate.remap_ICON_to_regulargrid`(...[, ...])	REMAP ICON data to regular grid using Fieldextra.
`interpolate.remap_ICON_to_ICON`(data_file, ...)	Remap ICON data to another ICON grid using Fieldextra.

Backend functions#

`grid`	The grid module contains functions relating to the grid information for ICON data, such as merging ICON data with the grid data to provide one merged dataset.
`grid.combine_grid_information`(file, grid_file)	Combine grid information.
`grid.get_cell_dim_name`(ds, grid)	Get name of dimension in ICON data xarray dataset which identifies the cell dimension.
`grid.get_edge_dim_name`(ds, grid)	Get name of dimension in ICON data xarray dataset which identifies the edge dimension.
`grid.get_time_coord_name`(ds)	Get name of time coordinate in xarray dataset which has attribute standard_name = 'time' and datatype of datetime.
`grid.add_cell_data`(ds, grid)	Add clon, clat, clon_bnds, and clat_bnds coordinates from the grid file to the dataset.
`grid.add_edge_data`(ds, grid)	Add elon, elat, elon_bnds, and elat_bnds and other edge related coordinates from the grid file to the dataset.
`grid.open_dataset`(file[, variable, ...])	Open either NETCDF or GRIB file.

Plotting functions#

`formatoptions`
`formatoptions.borders`	Formatoption that adds internal land borders on mapplot, mapvector, and mapcombined plots created by psyplot.
`formatoptions.lakes`	Formatoption that adds lakes to mapplot, mapvector, and mapcombined plots created by psyplot.
`formatoptions.rivers`	Formatoption that adds rivers to mapplot, mapvector, and mapcombined plots created by psyplot.
`config`	This module config.py contains the public function read_config which parses configuration file for plotting scripts in icon-vis.

Utility functions#

`get_data`	This script/module contains the function get_example_data which downloads example ICON data from FTP server (NETCDF, GRIB and Grid files).
`get_data.get_example_data`()	Download example ICON data from FTP server (NETCDF, GRIB and Grid files) to current directory.

Indices and tables#