{
"info": {
"author": "European Centre for Medium-Range Weather Forecasts (ECMWF)",
"author_email": "software.support@ecmwf.int",
"bugtrack_url": null,
"classifiers": [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.5",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: Implementation :: CPython",
"Programming Language :: Python :: Implementation :: PyPy"
],
"description": "\nPython interface to map GRIB files to the\n`Unidata's Common Data Model v4 `_\nfollowing the `CF Conventions `_.\nThe high level API is designed to support a GRIB engine for `xarray `_\nand it is inspired by `netCDF4-python `_\nand `h5netcdf `_.\nLow level access and decoding is performed via the\n`ECMWF ecCodes library `_.\n\nFeatures with development status **Beta**:\n\n- enables the ``engine='cfgrib'`` option to read GRIB files with *xarray*,\n- reads most GRIB 1 and 2 files including heterogeneous ones with ``cfgrib.open_datasets``,\n- supports all modern versions of Python 3.7, 3.6, 3.5 and PyPy3,\n- the 0.9.6.x series with support for Python 2 will stay active and receive critical bugfixes,\n- works on *Linux*, *MacOS* and *Windows*, the *ecCodes* C-library is the only binary dependency,\n- conda-forge package on all supported platforms,\n- PyPI package with no install time build (binds via *CFFI* ABI mode),\n- reads the data lazily and efficiently in terms of both memory usage and disk access,\n- allows larger-than-memory and distributed processing via *dask*,\n- supports translating coordinates to different data models and naming conventions,\n- supports writing the index of a GRIB file to disk, to save a full-file scan on open.\n\nWork in progress:\n\n- **Alpha** limited support for MULTI-FIELD messages, e.g. u-v components,\n see `#76 `_.\n- **Alpha** install a ``cfgrib`` utility that can convert a GRIB file ``to_netcdf``\n with a optional conversion to a specific coordinates data model,\n see `#40 `_.\n- **Alpha** support writing carefully-crafted ``xarray.Dataset``'s to a GRIB1 or GRIB2 file,\n see the *Advanced write usage* section below and\n `#18 `_.\n\nLimitations:\n\n- relies on *ecCodes* for the CF attributes of the data variables,\n- relies on *ecCodes* for anything related to coordinate systems / ``gridType``,\n see `#28 `_.\n\n\nInstallation\n============\n\nThe easiest way to install *cfgrib* and all its binary dependencies is via `Conda `_::\n\n $ conda install -c conda-forge cfgrib\n\nalternatively, if you install the binary dependencies yourself, you can install the\nPython package from *PyPI* with::\n\n $ pip install cfgrib\n\n\nBinary dependencies\n-------------------\n\nThe Python module depends on the ECMWF *ecCodes* binary library\nthat must be installed on the system and accessible as a shared library.\nSome Linux distributions ship a binary version that may be installed with the standard package manager.\nOn Ubuntu 18.04 use the command::\n\n $ sudo apt-get install libeccodes0\n\nOn a MacOS with HomeBrew use::\n\n $ brew install eccodes\n\nOr if you manage binary packages with *Conda* use::\n\n $ conda install -c conda-forge eccodes\n\nAs an alternative you may install the official source distribution\nby following the instructions at\nhttps://software.ecmwf.int/wiki/display/ECC/ecCodes+installation\n\nYou may run a simple selfcheck command to ensure that your system is set up correctly::\n\n $ python -m cfgrib selfcheck\n Found: ecCodes v2.12.0.\n Your system is ready.\n\n\nUsage\n=====\n\nFirst, you need a well-formed GRIB file, if you don't have one at hand you can download our\n`ERA5 on pressure levels sample `_::\n\n $ wget http://download.ecmwf.int/test-data/cfgrib/era5-levels-members.grib\n\n\nRead-only *xarray* GRIB engine\n------------------------------\n\nMost of *cfgrib* users want to open a GRIB file as a ``xarray.Dataset`` and\nneed to have *xarray>=0.12.0* installed::\n\n $ pip install xarray>=0.12.0\n\nIn a Python interpreter try:\n\n.. code-block: python\n\n>>> import xarray as xr\n>>> ds = xr.open_dataset('era5-levels-members.grib', engine='cfgrib')\n>>> ds\n\nDimensions: (isobaricInhPa: 2, latitude: 61, longitude: 120, number: 10, time: 4)\nCoordinates:\n * number (number) int64 0 1 2 3 4 5 6 7 8 9\n * time (time) datetime64[ns] 2017-01-01 ... 2017-01-02T12:00:00\n step timedelta64[ns] ...\n * isobaricInhPa (isobaricInhPa) int64 850 500\n * latitude (latitude) float64 90.0 87.0 84.0 81.0 ... -84.0 -87.0 -90.0\n * longitude (longitude) float64 0.0 3.0 6.0 9.0 ... 351.0 354.0 357.0\n valid_time (time) datetime64[ns] ...\nData variables:\n z (number, time, isobaricInhPa, latitude, longitude) float32 ...\n t (number, time, isobaricInhPa, latitude, longitude) float32 ...\nAttributes:\n GRIB_edition: 1\n GRIB_centre: ecmf\n GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: European Centre for Medium-Range Weather Forecasts\n history: ...\n\nThe *cfgrib* ``engine`` supports all read-only features of *xarray* like:\n\n* merge the content of several GRIB files into a single dataset using ``xarray.open_mfdataset``,\n* work with larger-than-memory datasets with `dask `_,\n* allow distributed processing with `dask.distributed `_.\n\nBy default *cfgrib* reads a limited set of ecCodes recognised *keys* from the GRIB files\nand exposes them as `Dataset` or `DataArray` attributes with the `GRIB_` prefix.\nIt is possible to have *cfgrib* read additional keys to the attributes by adding the\n`read_keys` dictionary key to the `backend_kwargs` with values the list of desired GRIB keys:\n\n.. code-block: python\n\n>>> ds = xr.open_dataset('era5-levels-members.grib', engine='cfgrib',\n... backend_kwargs={'read_keys': ['experimentVersionNumber']})\n>>> ds.t.attrs['GRIB_experimentVersionNumber']\n'0001'\n\n\nTranslate to a custom data model\n--------------------------------\n\nContrary to netCDF the GRIB data format is not self-describing and several details of the mapping\nto the *Unidata Common Data Model* are arbitrarily set by the software components decoding the format.\nDetails like names and units of the coordinates are particularly important because\n*xarray* broadcast and selection rules depend on them.\n``cf2cfm`` is a small coordinate translation module distributed with *cfgrib* that make it easy to\ntranslate CF compliant coordinates, like the one provided by *cfgrib*, to a user-defined\ncustom data model with set ``out_name``, ``units`` and ``stored_direction``.\n\nFor example to translate a *cfgrib* styled `xr.Dataset` to the classic *ECMWF* coordinate\nnaming conventions you can:\n\n.. code-block: python\n\n>>> import cf2cdm\n>>> ds = xr.open_dataset('era5-levels-members.grib', engine='cfgrib')\n>>> cf2cdm.translate_coords(ds, cf2cdm.ECMWF)\n\nDimensions: (latitude: 61, level: 2, longitude: 120, number: 10, time: 4)\nCoordinates:\n * number (number) int64 0 1 2 3 4 5 6 7 8 9\n * time (time) datetime64[ns] 2017-01-01 ... 2017-01-02T12:00:00\n step timedelta64[ns] ...\n * level (level) int64 850 500\n * latitude (latitude) float64 90.0 87.0 84.0 81.0 ... -84.0 -87.0 -90.0\n * longitude (longitude) float64 0.0 3.0 6.0 9.0 ... 348.0 351.0 354.0 357.0\n valid_time (time) datetime64[ns] ...\nData variables:\n z (number, time, level, latitude, longitude) float32 ...\n t (number, time, level, latitude, longitude) float32 ...\nAttributes:\n GRIB_edition: 1\n GRIB_centre: ecmf\n GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: European Centre for Medium-Range Weather Forecasts\n history: ...\n\nTo translate to the Common Data Model of the Climate Data Store use:\n\n.. code-block: python\n\n>>> import cf2cdm\n>>> cf2cdm.translate_coords(ds, cf2cdm.CDS)\n\nDimensions: (lat: 61, lon: 120, plev: 2, realization: 10, time: 4)\nCoordinates:\n * realization (realization) int64 0 1 2 3 4 5 6 7 8 9\n forecast_reference_time (time) datetime64[ns] 2017-01-01 ... 2017-01-02T12:00:00\n leadtime timedelta64[ns] ...\n * plev (plev) float64 8.5e+04 5e+04\n * lat (lat) float64 -90.0 -87.0 -84.0 ... 84.0 87.0 90.0\n * lon (lon) float64 0.0 3.0 6.0 9.0 ... 351.0 354.0 357.0\n * time (time) datetime64[ns] ...\nData variables:\n z (realization, time, plev, lat, lon) float32 ...\n t (realization, time, plev, lat, lon) float32 ...\nAttributes:\n GRIB_edition: 1\n GRIB_centre: ecmf\n GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: European Centre for Medium-Range Weather Forecasts\n history: ...\n\n\nFilter heterogeneous GRIB files\n-------------------------------\n\n``xr.open_dataset`` can open a GRIB file only if all the messages\nwith the same ``shortName`` can be represented as a single hypercube.\nFor example, a variable ``t`` cannot have both ``isobaricInhPa`` and ``hybrid`` ``typeOfLevel``'s,\nas this would result in multiple hypercubes for the same variable.\nOpening a non-conformant GRIB file will fail with a ``ValueError: multiple values for unique key...``\nerror message, see `#2 `_.\n\nFurthermore if different variables depend on the same coordinate, for example ``step``,\nthe values of the coordinate must match exactly.\nFor example, if variables ``t`` and ``z`` share the same ``step`` coordinate,\nthey must both have exactly the same set of steps.\nOpening a non-conformant GRIB file will fail with a ``ValueError: key present and new value is different...``\nerror message, see `#13 `_.\n\nIn most cases you can handle complex GRIB files containing heterogeneous messages by passing\nthe ``filter_by_keys`` key in ``backend_kwargs`` to select which GRIB messages belong to a\nwell formed set of hypercubes.\n\nFor example to open\n`US National Weather Service complex GRIB2 files `_\nyou can use:\n\n.. code-block: python\n\n>>> xr.open_dataset('nam.t00z.awp21100.tm00.grib2', engine='cfgrib',\n... backend_kwargs={'filter_by_keys': {'typeOfLevel': 'surface'}})\n\nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] ...\n step timedelta64[ns] ...\n surface int64 ...\n latitude (y, x) float64 ...\n longitude (y, x) float64 ...\n valid_time datetime64[ns] ...\nDimensions without coordinates: x, y\nData variables:\n gust (y, x) float32 ...\n sp (y, x) float32 ...\n orog (y, x) float32 ...\n tp (y, x) float32 ...\n acpcp (y, x) float32 ...\n csnow (y, x) float32 ...\n cicep (y, x) float32 ...\n cfrzr (y, x) float32 ...\n crain (y, x) float32 ...\n cape (y, x) float32 ...\n cin (y, x) float32 ...\n hpbl (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP...\n history: ...\n>>> xr.open_dataset('nam.t00z.awp21100.tm00.grib2', engine='cfgrib',\n... backend_kwargs={'filter_by_keys': {'typeOfLevel': 'heightAboveGround', 'level': 2}})\n\nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] ...\n step timedelta64[ns] ...\n heightAboveGround int64 ...\n latitude (y, x) float64 ...\n longitude (y, x) float64 ...\n valid_time datetime64[ns] ...\nDimensions without coordinates: x, y\nData variables:\n t2m (y, x) float32 ...\n r2 (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP...\n history: ...\n\n\nAutomatic filtering\n-------------------\n\n*cfgrib* also provides a function that automate the selection of appropriate ``filter_by_keys``\nand returns a list of all valid ``xarray.Dataset``'s in the GRIB file.\n\n.. code-block: python\n\n>>> import cfgrib\n>>> cfgrib.open_datasets('nam.t00z.awp21100.tm00.grib2')\n[\nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n cloudBase int64 0\n latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29\n longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6\n valid_time datetime64[ns] 2018-09-17\nDimensions without coordinates: x, y\nData variables:\n pres (y, x) float32 ...\n gh (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n cloudTop int64 0\n latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29\n longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6\n valid_time datetime64[ns] 2018-09-17\nDimensions without coordinates: x, y\nData variables:\n pres (y, x) float32 ...\n t (y, x) float32 ...\n gh (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n heightAboveGround int64 10\n latitude (y, x) float64 ...\n longitude (y, x) float64 ...\n valid_time datetime64[ns] ...\nDimensions without coordinates: x, y\nData variables:\n u10 (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n heightAboveGround int64 2\n latitude (y, x) float64 12.19 12.39 12.58 ... 57.68 57.49 57.29\n longitude (y, x) float64 226.5 227.2 227.9 ... 308.5 309.6 310.6\n valid_time datetime64[ns] 2018-09-17\nDimensions without coordinates: x, y\nData variables:\n t2m (y, x) float32 ...\n r2 (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (heightAboveGroundLayer: 2, x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n * heightAboveGroundLayer (heightAboveGroundLayer) int64 1000 3000\n latitude (y, x) float64 ...\n longitude (y, x) float64 ...\n valid_time datetime64[ns] ...\nDimensions without coordinates: x, y\nData variables:\n hlcy (heightAboveGroundLayer, y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (isobaricInhPa: 19, x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n * isobaricInhPa (isobaricInhPa) int64 1000 950 900 850 ... 250 200 150 100\n latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29\n longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6\n valid_time datetime64[ns] 2018-09-17\nDimensions without coordinates: x, y\nData variables:\n t (isobaricInhPa, y, x) float32 ...\n u (isobaricInhPa, y, x) float32 ...\n w (isobaricInhPa, y, x) float32 ...\n gh (isobaricInhPa, y, x) float32 ...\n r (isobaricInhPa, y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (isobaricInhPa: 5, x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n * isobaricInhPa (isobaricInhPa) int64 1000 850 700 500 250\n latitude (y, x) float64 ...\n longitude (y, x) float64 ...\n valid_time datetime64[ns] ...\nDimensions without coordinates: x, y\nData variables:\n absv (isobaricInhPa, y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n isothermZero int64 0\n latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29\n longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6\n valid_time datetime64[ns] 2018-09-17\nDimensions without coordinates: x, y\nData variables:\n gh (y, x) float32 ...\n r (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n maxWind int64 0\n latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29\n longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6\n valid_time datetime64[ns] 2018-09-17\nDimensions without coordinates: x, y\nData variables:\n pres (y, x) float32 ...\n u (y, x) float32 ...\n gh (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n meanSea int64 0\n latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29\n longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6\n valid_time datetime64[ns] 2018-09-17\nDimensions without coordinates: x, y\nData variables:\n prmsl (y, x) float32 ...\n mslet (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (pressureFromGroundLayer: 2, x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n * pressureFromGroundLayer (pressureFromGroundLayer) int64 9000 18000\n latitude (y, x) float64 12.19 12.39 12.58 ... 57.49 57.29\n longitude (y, x) float64 226.5 227.2 227.9 ... 309.6 310.6\n valid_time datetime64[ns] 2018-09-17\nDimensions without coordinates: x, y\nData variables:\n cape (pressureFromGroundLayer, y, x) float32 ...\n cin (pressureFromGroundLayer, y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (pressureFromGroundLayer: 5, x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n * pressureFromGroundLayer (pressureFromGroundLayer) int64 3000 6000 ... 15000\n latitude (y, x) float64 12.19 12.39 12.58 ... 57.49 57.29\n longitude (y, x) float64 226.5 227.2 227.9 ... 309.6 310.6\n valid_time datetime64[ns] 2018-09-17\nDimensions without coordinates: x, y\nData variables:\n t (pressureFromGroundLayer, y, x) float32 ...\n u (pressureFromGroundLayer, y, x) float32 ...\n r (pressureFromGroundLayer, y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n pressureFromGroundLayer int64 3000\n latitude (y, x) float64 ...\n longitude (y, x) float64 ...\n valid_time datetime64[ns] ...\nDimensions without coordinates: x, y\nData variables:\n pli (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n pressureFromGroundLayer int64 18000\n latitude (y, x) float64 ...\n longitude (y, x) float64 ...\n valid_time datetime64[ns] ...\nDimensions without coordinates: x, y\nData variables:\n 4lftx (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n surface int64 0\n latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29\n longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6\n valid_time datetime64[ns] 2018-09-17\nDimensions without coordinates: x, y\nData variables:\n cape (y, x) float32 ...\n sp (y, x) float32 ...\n acpcp (y, x) float32 ...\n cin (y, x) float32 ...\n orog (y, x) float32 ...\n tp (y, x) float32 ...\n crain (y, x) float32 ...\n cfrzr (y, x) float32 ...\n cicep (y, x) float32 ...\n csnow (y, x) float32 ...\n gust (y, x) float32 ...\n hpbl (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n tropopause int64 0\n latitude (y, x) float64 12.19 12.39 12.58 12.77 ... 57.68 57.49 57.29\n longitude (y, x) float64 226.5 227.2 227.9 228.7 ... 308.5 309.6 310.6\n valid_time datetime64[ns] 2018-09-17\nDimensions without coordinates: x, y\nData variables:\n pres (y, x) float32 ...\n t (y, x) float32 ...\n u (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP , \nDimensions: (x: 93, y: 65)\nCoordinates:\n time datetime64[ns] 2018-09-17\n step timedelta64[ns] 00:00:00\n level int64 0\n latitude (y, x) float64 ...\n longitude (y, x) float64 ...\n valid_time datetime64[ns] ...\nDimensions without coordinates: x, y\nData variables:\n pwat (y, x) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: kwbc\n GRIB_centreDescription: US National Weather Service - NCEP...\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: US National Weather Service - NCEP ]\n\n\nAdvanced usage\n==============\n\nWrite support\n=============\n\n**Please note that write support is Alpha.**\nOnly ``xarray.Dataset``'s in *canonical* form,\nthat is, with the coordinates names matching exactly the *cfgrib* coordinates,\ncan be saved at the moment:\n\n.. code-block: python\n\n>>> ds = xr.open_dataset('era5-levels-members.grib', engine='cfgrib')\n>>> ds\n\nDimensions: (isobaricInhPa: 2, latitude: 61, longitude: 120, number: 10, time: 4)\nCoordinates:\n * number (number) int64 0 1 2 3 4 5 6 7 8 9\n * time (time) datetime64[ns] 2017-01-01 ... 2017-01-02T12:00:00\n step timedelta64[ns] ...\n * isobaricInhPa (isobaricInhPa) int64 850 500\n * latitude (latitude) float64 90.0 87.0 84.0 81.0 ... -84.0 -87.0 -90.0\n * longitude (longitude) float64 0.0 3.0 6.0 9.0 ... 351.0 354.0 357.0\n valid_time (time) datetime64[ns] ...\nData variables:\n z (number, time, isobaricInhPa, latitude, longitude) float32 ...\n t (number, time, isobaricInhPa, latitude, longitude) float32 ...\nAttributes:\n GRIB_edition: 1\n GRIB_centre: ecmf\n GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: European Centre for Medium-Range Weather Forecasts\n history: ...\n>>> cfgrib.to_grib(ds, 'out1.grib', grib_keys={'edition': 2})\n>>> xr.open_dataset('out1.grib', engine='cfgrib')\n\nDimensions: (isobaricInhPa: 2, latitude: 61, longitude: 120, number: 10, time: 4)\nCoordinates:\n * number (number) int64 0 1 2 3 4 5 6 7 8 9\n * time (time) datetime64[ns] 2017-01-01 ... 2017-01-02T12:00:00\n step timedelta64[ns] ...\n * isobaricInhPa (isobaricInhPa) int64 850 500\n * latitude (latitude) float64 90.0 87.0 84.0 81.0 ... -84.0 -87.0 -90.0\n * longitude (longitude) float64 0.0 3.0 6.0 9.0 ... 351.0 354.0 357.0\n valid_time (time) datetime64[ns] ...\nData variables:\n z (number, time, isobaricInhPa, latitude, longitude) float32 ...\n t (number, time, isobaricInhPa, latitude, longitude) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: ecmf\n GRIB_centreDescription: European Centre for Medium-Range Weather Forecasts\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: European Centre for Medium-Range Weather Forecasts\n history: ...\n\nPer-variable GRIB keys can be set by setting the ``attrs`` variable with key prefixed by ``GRIB_``,\nfor example:\n\n.. code-block: python\n\n>>> import numpy as np\n>>> import xarray as xr\n>>> ds2 = xr.DataArray(\n... np.zeros((5, 6)) + 300.,\n... coords=[\n... np.linspace(90., -90., 5),\n... np.linspace(0., 360., 6, endpoint=False),\n... ],\n... dims=['latitude', 'longitude'],\n... ).to_dataset(name='skin_temperature')\n>>> ds2.skin_temperature.attrs['GRIB_shortName'] = 'skt'\n>>> cfgrib.to_grib(ds2, 'out2.grib')\n>>> xr.open_dataset('out2.grib', engine='cfgrib')\n\nDimensions: (latitude: 5, longitude: 6)\nCoordinates:\n time datetime64[ns] ...\n step timedelta64[ns] ...\n surface int64 ...\n * latitude (latitude) float64 90.0 45.0 0.0 -45.0 -90.0\n * longitude (longitude) float64 0.0 60.0 120.0 180.0 240.0 300.0\n valid_time datetime64[ns] ...\nData variables:\n skt (latitude, longitude) float32 ...\nAttributes:\n GRIB_edition: 2\n GRIB_centre: consensus\n GRIB_centreDescription: Consensus\n GRIB_subCentre: 0\n Conventions: CF-1.7\n institution: Consensus\n history: ...\n\nDataset / Variable API\n----------------------\n\nThe use of *xarray* is not mandatory and you can access the content of a GRIB file as\nan hypercube with the high level API in a Python interpreter:\n\n.. code-block: python\n\n>>> ds = cfgrib.open_file('era5-levels-members.grib')\n>>> ds.attributes['GRIB_edition']\n1\n>>> sorted(ds.dimensions.items())\n[('isobaricInhPa', 2), ('latitude', 61), ('longitude', 120), ('number', 10), ('time', 4)]\n>>> sorted(ds.variables)\n['isobaricInhPa', 'latitude', 'longitude', 'number', 'step', 't', 'time', 'valid_time', 'z']\n>>> var = ds.variables['t']\n>>> var.dimensions\n('number', 'time', 'isobaricInhPa', 'latitude', 'longitude')\n>>> var.data[:, :, :, :, :].mean()\n262.92133\n>>> ds = cfgrib.open_file('era5-levels-members.grib')\n>>> ds.attributes['GRIB_edition']\n1\n>>> sorted(ds.dimensions.items())\n[('isobaricInhPa', 2), ('latitude', 61), ('longitude', 120), ('number', 10), ('time', 4)]\n>>> sorted(ds.variables)\n['isobaricInhPa', 'latitude', 'longitude', 'number', 'step', 't', 'time', 'valid_time', 'z']\n>>> var = ds.variables['t']\n>>> var.dimensions\n('number', 'time', 'isobaricInhPa', 'latitude', 'longitude')\n>>> var.data[:, :, :, :, :].mean()\n262.92133\n\n\nGRIB index file\n---------------\n\nBy default *cfgrib* saves the index of the GRIB file to disk appending ``.idx``\nto the GRIB file name.\nIndex files are an **experimental** and completely optional feature, feel free to\nremove them and try again in case of problems. Index files saving can be disable passing\nadding ``indexpath=''`` to the ``backend_kwargs`` keyword argument.\n\n\nProject resources\n=================\n\n============= =========================================================\nDevelopment https://github.com/ecmwf/cfgrib\nDownload https://pypi.org/project/cfgrib\nUser support https://stackoverflow.com/search?q=cfgrib\nCode quality .. image:: https://api.travis-ci.org/ecmwf/cfgrib.svg?branch=master\n :target: https://travis-ci.org/ecmwf/cfgrib/branches\n :alt: Build Status on Travis CI\n .. image:: https://ci.appveyor.com/api/projects/status/github/ecmwf/cfgrib?svg=true&passingText=passing&failingText=failing&pendingText=pending\n :target: https://ci.appveyor.com/project/StephanSiemen/cfgrib\n :alt: Build Status on Appveyor\n .. image:: https://coveralls.io/repos/ecmwf/cfgrib/badge.svg?branch=master&service=github\n :target: https://coveralls.io/github/ecmwf/cfgrib\n :alt: Coverage Status on Coveralls\n============= =========================================================\n\n\nContributing\n============\n\nThe main repository is hosted on GitHub,\ntesting, bug reports and contributions are highly welcomed and appreciated:\n\nhttps://github.com/ecmwf/cfgrib\n\nPlease see the CONTRIBUTING.rst document for the best way to help.\n\nLead developer:\n\n- `Alessandro Amici `_ - `B-Open `_\n\nMain contributors:\n\n- Baudouin Raoult - `ECMWF `_\n- `Aureliana Barghini `_ - B-Open\n- `Iain Russell `_ - ECMWF\n- `Leonardo Barcaroli `_ - B-Open\n\nSee also the list of `contributors `_ who participated in this project.\n\n\nLicense\n=======\n\nCopyright 2017-2019 European Centre for Medium-Range Weather Forecasts (ECMWF).\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at: http://www.apache.org/licenses/LICENSE-2.0.\nUnless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \"AS IS\" BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License.\n\nChangelog for cfgrib\n====================\n\n0.9.7.2 (2019-09-24)\n--------------------\n\n- Add support to read additional keys from the GRIB files via `read_keys`, they\n appear in the variable `attrs` and you can `filter_by_keys` on them.\n This is a general solution for all issues where users know the name of the additional keys\n they are interested in.\n See: `#89 `_ and\n `#101 `_.\n\n\n0.9.7.1 (2019-07-08)\n--------------------\n\n- Fix a bytes-in-the-place-of-str bug when attempting to write a GRIB on Windows.\n See: `#91 `_.\n- Honor setting `indexpath` in `open_datasets`,\n See: `#93 `_.\n\n\n0.9.7 (2019-05-27)\n------------------\n\n- Much improved ``cfgrib.open_datasets`` heuristics now reads many more\n heterogeneous GRIB files. The function is now a supported API.\n See: `#63 `_,\n `#66 `_,\n `#73 `_ and\n `#75 `_.\n- Fix conda dependencies on Python 2 only package,\n See: `#78 `_.\n\n\n0.9.7rc1 (2019-05-14)\n---------------------\n\n- Drop support for Python 2, in line with *xarray* 0.12.0.\n The 0.9.6.x series will be supported long term for Python 2 users.\n See: `#69 `_.\n- Sync internal ecCodes bindings API to the one in eccodes-python.\n See: `#81 `_.\n- Source code has been formatted with ``black -S -l 99``.\n- Added initial support for spectral coordinates.\n\n\n0.9.6.2 (2019-04-15)\n--------------------\n\n- Improve merging of variables into a dataset.\n See: `#63 `_.\n\n\n0.9.6.1.post1 (2019-03-17)\n--------------------------\n\n- Fix an issue in the README format.\n\n\n0.9.6.1 (2019-03-17)\n--------------------\n\n- Fixed (for real) MULTI-FIELD messages,\n See: `#45 `_.\n- Added a protocol version to the index file. Old ``*.idx`` files must be removed.\n\n\n0.9.6.post1 (2019-03-07)\n------------------------\n\n- Fix an important typo in the README. See: `#64 `_.\n\n\n0.9.6 (2019-02-26)\n------------------\n\n- Add support for *Windows* by installing *ecCodes* via *conda*.\n See: `#7 `_.\n- Added *conda-forge* package.\n See: `#5 `_.\n\n\n0.9.5.7 (2019-02-24)\n--------------------\n\n- Fixed a serious bug in the computation of the suggested ``filter_by_keys`` for non-cubic\n GRIB files. As a result ``cfgrib.xarray_store.open_datasets`` was not finding all the\n variables in the files.\n See: `#54 `_.\n- Fixed a serious bug in variable naming that could drop or at worse mix the values of variables.\n Again see: `#54 `_.\n- Re-opened `#45 `_ as the fix was returning wrong data.\n Now we are back to dropping all variable in a MULTI-FIELD except the first.\n\n\n0.9.5.6 (2019-02-04)\n--------------------\n\n- Do not set explicit timezone in ``units`` to avoid crashing some versions of *xarray*.\n See: `#44 `_.\n\n\n0.9.5.5 (2019-02-02)\n--------------------\n\n- Enable ecCodes implicit MULTI-FIELD support by default, needed for NAM Products by NCEP.\n See: `#45 `_.\n- Added support for ``depthBelowLand`` coordinate.\n\n\n0.9.5.4 (2019-01-25)\n--------------------\n\n- Add support for building ``valid_time`` from a bad ``time-step`` hypercube.\n\n\n0.9.5.3 (2019-01-25)\n--------------------\n\n- Also convert is ``valid_time`` can index all times and steps in ``translate_coords``.\n\n\n0.9.5.2 (2019-01-24)\n--------------------\n\n- Set ``valid_time`` as preferred time dimension for the CDS data model.\n- Fall back to using the generic ``GRIB2`` *ecCodes* template when no better option is found.\n See: `#39 `_.\n\n\n0.9.5.1 (2018-12-27)\n--------------------\n\n- Fix the crash when using ``cf2cdm.translate_coords`` on datasets with non-dimension coordinates.\n See: `#41 `_.\n- Added a ``cfgrib`` script that can translate GRIB to netCDF.\n See: `#40 `_.\n\n\n0.9.5 (2018-12-20)\n------------------\n\n- Drop support for *xarray* versions prior to *v0.11* to reduce complexity.\n (This is really only v0.10.9).\n See: `#32 `_.\n- Declare the data as ``CF-1.7`` compliant via the ``Conventions`` global attribute.\n See: `#36 `_.\n- Tested larger-than-memory and distributed processing via *dask* and *dask.distributed*.\n See: `#33 `_.\n- Promote write support via ``cfgrib.to_grib`` to **Alpha**.\n See: `#18 `_.\n- Provide the ``cf2cdm.translate_coords`` utility function to translate the coordinates\n between CF-compliant data models, defined by ``out_name``, ``units`` and ``store_direction``.\n See: `#24 `_.\n- Provide ``cfgrib.__version__``.\n See: `#31 `_.\n- Raise with a better error message when users attempt to open a file that is not a GRIB.\n See: `#34 `_.\n- Make 2D grids for ``rotated_ll`` and ``rotated_gg`` ``gridType``'s.\n See: `#35 `_.\n\n\n0.9.4.1 (2018-11-08)\n--------------------\n\n- Fix formatting for PyPI page.\n\n\n0.9.4 (2018-11-08)\n------------------\n\n- Saves one index file per set of ``index_keys`` in a much more robust way.\n- Refactor CF-encoding and add the new ``encode_cf`` option to ``backend_kwargs``.\n See: `#23 `_.\n- Refactor error handling and the option to ignore errors (not well documented yet).\n See: `#13 `_.\n- Do not crash on ``gridType`` not fully supported by the installed *ecCodes*\n See: `#27 `_.\n- Several smaller bug fixes and performance improvements.\n\n\n0.9.3.1 (2018-10-28)\n--------------------\n\n- Assorted README fixes, in particular advertise index file support as alpha.\n\n\n0.9.3 (2018-10-28)\n------------------\n\n- Big performance improvement: add alpha support to save to and read from disk\n the GRIB index produced by the full-file scan at the first open.\n See: `#20 `_.\n\n\n0.9.2 (2018-10-22)\n------------------\n\n- Rename coordinate ``air_pressure`` to ``isobaricInhPa`` for consistency\n with all other vertical ``level`` coordinates.\n See: `#25 `_.\n\n\n0.9.1.post1 (2018-10-19)\n------------------------\n\n- Fix PyPI description.\n\n\n0.9.1 (2018-10-19)\n------------------\n\n- Change the usage of ``cfgrib.open_dataset`` to allign it with ``xarray.open_dataset``,\n in particular ``filter_by_key`` must be added into the ``backend_kwargs`` dictionary.\n See: `#21 `_.\n\n0.9.0 (2018-10-14)\n------------------\n\n- Beta release with read support.\n\n\n",
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