Raw Data I/O

Please have a look at the tutorial Data Input - Data Output for an introduction on how to deal with different file formats.

Xarray backends

Reading radar data into xarray Datasets using xarray.open_dataset and xarray.open_mfdataset.

Former available backends have been ported to xradar-package.

RadolanBackendEntrypoint

Xarray BackendEntrypoint for RADOLAN data.

class wradlib.io.backends.RadolanBackendEntrypoint

Bases: BackendEntrypoint

Xarray BackendEntrypoint for RADOLAN data.

description: ClassVar[str] = 'Open RADOLAN in Xarray'

url: ClassVar[str] = 'https://docs.wradlib.org/en/stable/notebooks/fileio/backends/radolan_backend.html'

open_dataset(filename_or_obj, *, mask_and_scale=True, decode_times=True, concat_characters=True, decode_coords=True, drop_variables=None, use_cftime=None, decode_timedelta=None, fillmissing=False, copy=False, ancillary=False)

Backend open_dataset method used by Xarray in open_dataset.

Digital Elevation Model Data I/O

Provide surface/terrain elevation information from SRTM data

download_srtm	Download NASA SRTM elevation data Only available with login/password
get_srtm	Get NASA SRTM elevation data
get_srtm_tile_names	Get NASA SRTM elevation data tile names

wradlib.io.dem.download_srtm(filename, destination, *, resolution=3, session=None)

Download NASA SRTM elevation data Only available with login/password

Parameters:

• filename (str) – srtm file to download

• destination (str) – output filename

Keyword Arguments:

• resolution (int) – resolution of SRTM data (1, 3 or 30)

• session (object) – session object to use

wradlib.io.dem.get_srtm(extent, *, resolution=3, merge=True, session=None)

Get NASA SRTM elevation data

Parameters:

• extent (list) – list containing lonmin, lonmax, latmin, latmax

• resolution (int) – resolution of SRTM data (1, 3 or 30)

• merge (bool) – True to merge the tiles in one dataset

• session (object) – session object to use

Returns:

dataset (osgeo.gdal.Dataset) – gdal.Dataset Raster dataset containing elevation information

wradlib.io.dem.get_srtm_tile_names(extent)

Get NASA SRTM elevation data tile names

Parameters:

extent (list) – list containing lonmin, lonmax, latmin, latmax

Returns:

out (list) – list of tile names

GDAL Raster/Vector Data I/O

open_vector	Open vector file, return gdal.Dataset and OGR.Layer
open_raster	Open raster file, return gdal.Dataset
read_safnwc	Read MSG SAFNWC hdf5 file into a gdal georeferenced object
gdal_create_dataset	Creates GDAL.DataSet object.
write_raster_dataset	Write raster dataset to file format
VectorSource	DataSource class for handling ogr/gdal vector data

wradlib.io.gdal.open_vector(filename, *, driver=None, layer=0)

Open vector file, return gdal.Dataset and OGR.Layer

Warning

dataset and layer have to live in the same context, if dataset is deleted all layer references will get lost

Parameters:

• filename (str) – vector file name

• driver (str) – gdal driver string

• layer (int or str)

Returns:

• dataset (osgeo.gdal.Dataset) – gdal.Dataset

• layer (osgeo.ogr.Layer) – ogr.Layer

wradlib.io.gdal.open_raster(filename, *, driver=None)

Open raster file, return gdal.Dataset

Parameters:

• filename (str) – raster file name

• driver (str) – gdal driver string

Returns:

dataset (osgeo.gdal.Dataset) – gdal.Dataset

wradlib.io.gdal.read_safnwc(filename)

Read MSG SAFNWC hdf5 file into a gdal georeferenced object

Parameters:

filename (str) – satellite file name

Returns:

ds (osgeo.gdal.Dataset) – gdal.DataSet with satellite data

wradlib.io.gdal.gdal_create_dataset(drv, name, cols=0, rows=0, bands=0, *, gdal_type=None, remove=False)

Creates GDAL.DataSet object.

Parameters:

• drv (str) – GDAL driver string

• name (str) – path to filename

• cols (int) – number of columns

• rows (int) – number of rows

• bands (int) – number of raster bands

• gdal_type (gdal:osgeo.ogr.DataType) – raster data type, e.g. gdal.GDT_Float32

• remove (bool) – if True, existing gdal.Dataset will be removed before creation

Returns:

out (osgeo.gdal.Dataset) – gdal.Dataset

wradlib.io.gdal.write_raster_dataset(fpath, dataset, *, driver='GTiff', **kwargs)

Write raster dataset to file format

Parameters:

• fpath (str) – A file path - should have file extension corresponding to format.

• dataset (osgeo.gdal.Dataset) – gdal.Dataset gdal raster dataset

• driver (str, optional) – gdal raster format driver string, defaults to “GTiff”

Keyword Arguments:

• options (list, optional) – Option strings for the corresponding format. Defaults to

• remove (bool, optional) – if True, existing gdal.Dataset will be removed before creation, defaults to False

Note

For format and options refer to formats_list.

Examples

See Export a dataset in GIS-compatible format.

class wradlib.io.gdal.VectorSource(data=None, trg_crs=None, name='layer', source=0, **kwargs)

Bases: object

DataSource class for handling ogr/gdal vector data

DataSource handles creates in-memory (vector) ogr DataSource object with one layer for point or polygon geometries.

Parameters:

• data (sequence or str) – sequence of source points (shape Nx2) or polygons (shape NxMx2) or Vector File (GDAL/OGR) filename containing source points/polygons

• trg_crs (osgeo.osr.SpatialReference) – GDAL OSR SRS describing target CRS the source data should be projected to

Keyword Arguments:

• name (str) – Layer Name, defaults to “layer”.

• source (int) – Number of layer to load, if multiple layers in source shape file.

• mode (str) – Return type of class access functions/properties. Can be either of “numpy”, “geo” and “ogr”, defaults to “numpy”.

• src_crs (osgeo.osr.SpatialReference) – GDAL OGR SRS describing projection source in which data is provided in.

Warning

Writing shapefiles with the wrong locale settings can have impact on the type of the decimal. If problem arise use LC_NUMERIC=C in your environment.

Examples

See Vector Source.

close()

property mode

property ds

Returns VectorSource

property extent

property crs

property data

Returns VectorSource geometries as numpy arrays

Note

This may be slow, because it extracts all source polygons

property geo

Returns VectorSource geometries as GeoPandas Dataframe

get_data_by_idx(idx, *, mode=None)

Returns DataSource geometries from given index

Parameters:

• idx (sequence) – sequence of int indices

• mode (str, optional) – return type (“numpy”, “geo”, “ogr”), defaults to “numpy”

get_data_by_att(attr=None, value=None, mode=None)

Returns DataSource geometries filtered by given attribute/value

Keyword Arguments:

• attr (str) – attribute name

• value (str) – attribute value

• mode (str) – return type (“numpy”, “geo”, “ogr”), defaults to “numpy”

get_data_by_geom(geom=None, mode=None)

Returns DataSource geometries filtered by given geometry

Keyword Arguments:

• geom (osgeo.ogr.Geometry | geopandas.GeoDataFrame) – OGR.Geometry object or geopandas.GeoDataFrame containing the Geometry

• mode (str) – return type (“numpy”, “geo”, “ogr”), defaults to “numpy”

dump_vector(filename, *, driver='ESRI Shapefile', remove=True)

Output layer to OGR Vector File

Parameters:

• filename (str) – path to shape-filename

• driver (str, optional) – driver string, defaults to “ESRI SHapefile”

• remove (bool, optional) – if True removes existing output file, defaults to True

load_vector(filename, *, source=0, driver='ESRI Shapefile')

Read Layer from OGR Vector File

Parameters:

• filename (str) – path to shape-filename

• source (int or str, optional) – number or name of wanted layer, defaults to 0

• driver (str, optional) – driver string, defaults to “ESRI Shapefile”

dump_raster(filename, *, driver='GTiff', attr=None, pixel_size=1.0, **kwargs)

Output layer to GDAL Rasterfile

Parameters:

• filename (str) – path to shape-filename

• driver (str, optional) – GDAL Raster Driver, defaults to “GTiff”.

• attr (str, optional) – attribute to burn into raster, defaults to None.

• pixel_size (float, optional) – pixel Size in source units

Keyword Arguments:

• remove (bool, optional) – if True removes existing output file. Defaults to True.

• silent (bool, optional) – If True no ProgressBar is shown. Defaults to False.

set_attribute(name, values, *, reset_filter=False)

Add/Set given Attribute with given values

Parameters:

• name (str) – Attribute Name

• values (numpy.ndarray) – Values to fill in attributes.

• reset_filter (bool, optional) – reset any layer filter (spatial/attribute), defaults to False.

get_attributes(attrs, *, filt=None)

Return attributes

Parameters:

• attrs (list) – Attribute Names to retrieve

• filt (tuple, optional) – (attname, value) for Attribute Filter, defaults to None

get_geom_properties(props, *, filt=None)

Return geometry properties

Parameters:

• props (list) – Property Names to retrieve

• filt (tuple, optional) – (attname, value) for Attribute Filter, defaults to None.

get_attrs_and_props(*, attrs=None, props=None, filt=None)

Return properties and attributes

Keyword Arguments:

• attrs (list) – Attribute Names to retrieve

• props (list) – Property Names to retrieve

• filt (tuple) – (attname, value) for Attribute Filter

HDF Data I/O

Former available xarray based code has been ported to xradar-package.

open_gpm_dataset	Reads GPM files version V07A.
read_generic_hdf5	Reads hdf5 files according to their structure
read_opera_hdf5	Reads hdf5 files according to OPERA conventions
read_gamic_hdf5	Data reader for hdf5 files produced by the commercial GAMIC Enigma V3 MURAN software
to_hdf5	Quick storage of one <data> array and a <metadata> dict in an hdf5 file
from_hdf5	Loading data from hdf5 files that was stored by to_hdf5
read_gpm	Reads GPM files for matching with GR
read_trmm	Reads TRMM files for matching with GR

wradlib.io.hdf.open_gpm_dataset(filename, group)

Reads GPM files version V07A.

Parameters:

• filename (str) – path of the GPM file

• group (str) – name of group

Returns:

ds (xarray.Dataset) – xarray.Dataset representation of GPM file with requested group.

wradlib.io.hdf.read_generic_hdf5(fname)

Reads hdf5 files according to their structure

In contrast to other file readers under wradlib.io, this function will not return a two item tuple with (data, metadata). Instead, this function returns ONE dictionary that contains all the file contents - both data and metadata. The keys of the output dictionary conform to the Group/Subgroup directory branches of the original file.

Parameters:

fname (str or file-like) – a hdf5 file path or file-like object

Returns:

output (dict) – a dictionary that contains both data and metadata according to the original hdf5 file structure

Examples

See Reading HDF5 files with a generic reader.

wradlib.io.hdf.read_opera_hdf5(fname)

Reads hdf5 files according to OPERA conventions

Please refer to the OPERA data model documentation [B1] in order to understand how an hdf5 file is organized that conforms to the OPERA ODIM_H5 conventions.

In contrast to other file readers under wradlib.io, this function will not return a two item tuple with (data, metadata). Instead, this function returns ONE dictionary that contains all the file contents - both data and metadata. The keys of the output dictionary conform to the Group/Subgroup directory branches of the original file. If the end member of a branch (or path) is “data”, then the corresponding item of output dictionary is a numpy array with actual data.

Any other end member (either how, where, and what) will contain the meta information applying to the corresponding level of the file hierarchy.

Parameters:

fname (str or file-like) – a hdf5 file path or file-like object

Returns:

output (dict) – a dictionary that contains both data and metadata according to the original hdf5 file structure

wradlib.io.hdf.read_gamic_hdf5(filename, *, wanted_elevations=None, wanted_moments=None)

Data reader for hdf5 files produced by the commercial GAMIC Enigma V3 MURAN software

See GAMIC homepage for further info (https://www.gamic.com).

Parameters:

• filename (str or file-like) – path of the gamic hdf5 file or file-like object

• wanted_elevations (sequence) – sequence of strings of elevation_angle(s) of scan (only needed for PPI)

• wanted_moments (sequence) – sequence of strings of moment name(s)

Returns:

• data (dict) – dictionary of scan and moment data (numpy arrays)

• attrs (dict) – dictionary of attributes

Examples

See GAMIC HDF5.

wradlib.io.hdf.to_hdf5(fpath, data, *, mode='w', metadata=None, dataset='data', compression='gzip')

Quick storage of one <data> array and a <metadata> dict in an hdf5 file

This is more efficient than pickle, cPickle or numpy.save. The data is stored in a subgroup named data (i.e. file[“data”]). See from_hdf5 for retrieving stored data.

Parameters:

• fpath (str or file-like) – path to the hdf5 file or file-like object

• data (numpy.ndarray)

• mode (str) – file open mode, defaults to “w” (create, truncate if exists)

• metadata (dict) – dictionary of data’s attributes

• dataset (str) – describing dataset

• compression (str) – h5py-compression type {“gzip”|”szip”|”lzf”}, see h5py-documentation for details

wradlib.io.hdf.from_hdf5(fpath, *, dataset='data')

Loading data from hdf5 files that was stored by to_hdf5

Parameters:

• fpath (str or file-like) – path to the hdf5 file or file-like object

• dataset (str) – name of the Dataset in which the data is stored

wradlib.io.hdf.read_gpm(filename, *, bbox=None)

Reads GPM files for matching with GR

Parameters:

• filename (str) – path of the GPM file

• bbox (dict) – dictionary with bounding box coordinates (lon, lat), defaults to None

Returns:

gpm_data (dict) – dictionary of gpm data

Examples

See Match spaceborn SR (GPM/TRMM) with ground radars GR.

wradlib.io.hdf.read_trmm(filename1, filename2, *, bbox=None)

Reads TRMM files for matching with GR

Parameters:

• filename1 (str) – path of the TRMM 2A23 file

• filename2 (str) – path of the TRMM 2A25 file

• bbox (dict) – dictionary with bounding box coordinates (lon, lat), defaults to None

Returns:

trmm_data (dict) – dictionary of trmm data

Examples

See Match spaceborn SR (GPM/TRMM) with ground radars GR.

IRIS/Sigmet Data I/O

Reads data from Vaisala’s IRIS data formats. Former available code was ported to xradar-package and is imported from there.

IRIS (Vaisala Sigmet Interactive Radar Information System)

See M211318EN-F Programming Guide ftp://ftp.sigmet.com/outgoing/manuals/

Reading sweep data can be skipped by setting loaddata=False. By default, the data is decoded on the fly. Using rawdata=True the data will be kept undecoded.

read_iris	Read Iris file and return dictionary.
IrisProductFile	Class for retrieving data from Sigmet IRIS Product files.
IrisCartesianProductFile	Class for retrieving data from Sigmet IRIS Cartesian Product files.

wradlib.io.iris.read_iris(filename, *, loaddata=True, rawdata=False, debug=False, **kwargs)

Read Iris file and return dictionary.

Parameters:

• filename (str or file-like) – Filename of data file or file-like object.

• loaddata (bool or dict) – If true, retrieves whole data section from file. If false, retrievs only ingest_data_headers, but no data. If dict, retrieves according to given dict:

  loaddata = {'moment': ['DB_DBZ', 'DB_VEL'],
              'sweep': [1, 3, 9]}
  

• rawdata (bool) – If true, returns raw unconverted/undecoded data.

• debug (bool) – If true, print debug messages.

Returns:

data (dict) – Ordered Dictionary with data and metadata retrieved from file.

Examples

See Vaisala Sigmet IRIS.

class wradlib.io.iris.IrisProductFile(filename, **kwargs)

Bases: IrisRecordFile

Class for retrieving data from Sigmet IRIS Product files.

product_identifier = ['CATCH', 'FCAST', 'NDOP', 'SLINE', 'TDWR', 'TRACK', 'VAD', 'VVP', 'WARN', 'WIND', 'STATUS']

property data

property protect_setup

get_protect_setup()

get_results(results, num, structure)

get_data()

Retrieves cartesian data from file.

class wradlib.io.iris.IrisCartesianProductFile(irisfile, **kwargs)

Bases: IrisRecordFile

Class for retrieving data from Sigmet IRIS Cartesian Product files.

product_identifier = ['MAX', 'TOPS', 'HMAX', 'BASE', 'THICK', 'PPI', 'RHI', 'CAPPI', 'RAINN', 'RAIN1', 'CROSS', 'SHEAR', 'SRI', 'RTI', 'VIL', 'LAYER', 'BEAM', 'MLHGT']

property data

fix_ext_header(ext)

get_extended_header()

get_image(header)

Retrieve cartesian image.

Parameters:

header (dict) – header dictionary

Returns:

data (numpy.ndarray) – 3D array of cartesian data

get_data()

Retrieves cartesian data from file.

decode_data(data, prod)

Decode data according given prod-dict.

Parameters:

• data (numpy.ndarray) – data to decode

• prod (dict) – dictionary holding decoding information

Returns:

data (numpy.ndarray) – decoded data

Miscellaneous Data I/O

write_polygon_to_text	Writes Polygons to a Text file which can be interpreted by ESRI ArcGIS's "Create Features from Text File (Samples)" tool.
to_pickle	Pickle object <obj> to file <fpath>
from_pickle	Return pickled object from file <fpath>
get_radiosonde	Download radiosonde data from internet.
get_membership_functions	Reads membership function parameters from wradlib-data file.

wradlib.io.misc.write_polygon_to_text(fname, polygons)

Writes Polygons to a Text file which can be interpreted by ESRI ArcGIS’s “Create Features from Text File (Samples)” tool.

This is (yet) only a convenience function with limited functionality. E.g. interior rings are not yet supported.

Parameters:

• fname (str) – name of the file to save the vertex data to

• polygons (list) – list of lists of polygon vertices. Each vertex itself is a list of 3 coordinate values and an additional value. The third coordinate and the fourth value may be nan.

Returns:

None

Note

As Polygons are closed shapes, the first and the last vertex of each polygon must be the same!

Examples

Writes two triangle Polygons to a text file::

poly1 = [[0.,0.,0.,0.],[0.,1.,0.,1.],[1.,1.,0.,2.],[0.,0.,0.,0.]] poly2 = [[0.,0.,0.,0.],[0.,1.,0.,1.],[1.,1.,0.,2.],[0.,0.,0.,0.]] polygons = [poly1, poly2] write_polygon_to_text(‘polygons.txt’, polygons)

The resulting text file will look like this::

Polygon 0 0 0 0.000000 0.000000 0.000000 0.000000 1 0.000000 1.000000 0.000000 1.000000 2 1.000000 1.000000 0.000000 2.000000 3 0.000000 0.000000 0.000000 0.000000 1 0 0 0.000000 0.000000 0.000000 0.000000 1 0.000000 1.000000 0.000000 1.000000 2 1.000000 1.000000 0.000000 2.000000 3 0.000000 0.000000 0.000000 0.000000 END

wradlib.io.misc.to_pickle(fpath, obj)

Pickle object <obj> to file <fpath>

wradlib.io.misc.from_pickle(fpath)

Return pickled object from file <fpath>

wradlib.io.misc.get_radiosonde(wmoid, date, *, cols=None)

Download radiosonde data from internet.

Based on http://weather.uwyo.edu/upperair/sounding.html.

Parameters:

• wmoid (int) – WMO radiosonde ID

• date (datetime.datetime) – Date and Time

• cols (tuple, optional) – tuple of int or strings describing the columns to consider, defaults to None (all columns)

Returns:

• data (numpy.ndarray) – Structured array of radiosonde data

• meta (dict) – radiosonde metadata

wradlib.io.misc.get_membership_functions(filename)

Reads membership function parameters from wradlib-data file.

Parameters:

filename (str) – Filename of wradlib-data file

Returns:

msf (numpy.ndarray) – Array of membership funcions with shape (hm-classes, observables, indep-ranges, 5)

NetCDF Data I/O

Former available xarray based code has been ported to xradar-package.

read_edge_netcdf	Data reader for netCDF files exported by the EDGE radar software
read_generic_netcdf	Reads netcdf files and returns a dictionary with corresponding structure.

wradlib.io.netcdf.read_edge_netcdf(filename, *, enforce_equidist=False)

Data reader for netCDF files exported by the EDGE radar software

The corresponding NetCDF files from the EDGE software typically contain only one variable (e.g. reflectivity) for one elevation angle (sweep). The elevation angle is specified in the attributes keyword “Elevation”. Please note that the radar might not return data with equidistant azimuth angles. In case you need equidistant azimuth angles, please set enforce_equidist to True.

Parameters:

• filename (str or file-like) – path of the netCDF file or file-like object

• enforce_equidist (bool) – Set True if the values of the azimuth angles should be forced to be equidistant; default value is False

Returns:

output (tuple) – Array of image data (dBZ), dictionary of attributes

wradlib.io.netcdf.read_generic_netcdf(fname)

Reads netcdf files and returns a dictionary with corresponding structure.

In contrast to other file readers under wradlib.io, this function will not return a two item tuple with (data, metadata). Instead, this function returns ONE dictionary that contains all the file contents - both data and metadata. The keys of the output dictionary conform to the Group/Subgroup directory branches of the original file. Please see the examples below on how to browse through a return object. The most important keys are the “dimensions” which define the shape of the data arrays, and the “variables” which contain the actual data and typically also the data that define the dimensions (e.g. sweeps, azimuths, ranges). These keys should be present in any netcdf file.

Note

The returned dictionary could be quite big, depending on the content of the file.

Parameters:

fname (str or file-like) – a netcdf file path or file-like object

Returns:

out (dict) – an ordered dictionary that contains both data and metadata according to the original netcdf file structure

Examples

See Reading NetCDF.

RADOLAN and DX Data I/O

Reading DX and RADOLAN data from German Weather Service

Warning

Additionally to the binary composite formats DWD also provides data in ASCII format, which have a very limited header and need to extract product and datetime from the filename. Use on your own risk.

open_radolan_dataset	Open and decode a RADOLAN dataset from a file or file-like object.
open_radolan_mfdataset	Open multiple RADOLAN files as a single dataset.
read_dx	Data reader for German Weather Service DX product raw radar data files.
read_radolan_composite	Read quantitative radar composite format of the German Weather Service
get_radolan_filehandle	Opens radolan file and returns file handle
read_radolan_header	Reads radolan ASCII header and returns it as string
parse_dwd_composite_header	Parses the ASCII header of a DWD quantitative composite file
read_radolan_binary_array	Read binary data from file given by filehandle
decode_radolan_runlength_array	Decodes the binary runlength coded section from DWD composite file and return decoded numpy array with correct shape

wradlib.io.radolan.open_radolan_dataset(filename_or_obj, **kwargs)

Open and decode a RADOLAN dataset from a file or file-like object.

Parameters:

filename_or_obj (str, Path, file-like or DataStore) – Strings and Path objects are interpreted as a path to a local or remote file.

Keyword Arguments:

• fillmissing (bool) – Fill truncated data, defaults to False.

• copy (bool) – Create copies instead of views into the data, defaults to False.

• ancillary (bool, tuple of str) – If True, resturns ancillary masks (“secondary”, “nodatamask”, “cluttermask”) as additional data variables. Can be specified as tuple of strings. Defaults to False.

• **kwargs (dict, optional) – Additional arguments passed on to xarray.open_dataset.

Returns:

dataset (xarray.Dataset)

wradlib.io.radolan.open_radolan_mfdataset(paths, **kwargs)

Open multiple RADOLAN files as a single dataset.

Needs dask-package to be installed.

Parameters:

paths (str or sequence) – Either a string glob in the form "path/to/my/files/*" or an explicit list of files to open. Paths can be given as strings or as pathlib Paths.

Keyword Arguments:

• fillmissing (bool) – Fill truncated data, defaults to False.

• copy (bool) – Create copies instead of views into the data, defaults to False.

• ancillary (bool, tuple of str) – If True, resturns ancillary masks (“secondary”, “nodatamask”, “cluttermask”) as additional data variables. Can be specified as tuple of strings. Defaults to False.

• **kwargs (dict, optional) – Additional arguments passed on to xarray.open_mfdataset.

Returns:

dataset (xarray.Dataset)

wradlib.io.radolan.read_dx(filename)

Data reader for German Weather Service DX product raw radar data files.

This product uses a simple algorithm to compress zero values to reduce data file size.

Notes

While the format appears to be well-defined, there have been reports on DX- files that seem to produce errors. e.g. while one file usually contains a 360 degree by 128 1km range bins, there are files, that contain 361 beams. Also, while usually azimuths are stored monotonously in ascending order, this is not guaranteed by the format. This routine does not (yet) check for this and directly returns the data in the order found in the file. If you are in doubt, check the ‘azim’ attribute. Be aware that this function does no extensive checking on its output. If e.g. beams contain different numbers of range bins, the resulting data will not be a 2-D array but a 1-D array of objects, which will most probably break calling code. It was decided to leave the handling of these (hopefully) rare events to the user, who might still be able to retrieve some reasonable data, instead of raising an exception, making it impossible to get any data from a file containing errors.

Parameters:

filename (str or file-like) – filename of binary file of DX raw data or file-like object

Returns:

• data (numpy.ndarray) – Array of image data [dBZ]; shape (360,128)

• attributes (dict) – dictionary of attributes - currently implemented keys:

  • ’azim’ - azimuths array of shape (360, )

  • ’elev’ - elevations (1 per azimuth); array of shape (360, )

  • ’clutter’ - clutter mask; boolean array of same shape as data; corresponds to bit 15 set in each dataset.

  • ’bytes’- the total product length (including header). Apparently, this value may be off by one byte for unknown reasons

  • ’version’- a product version string - use unknown

  • ’cluttermap’ - number of the (DWD internal) cluttermap used

  • ’dopplerfilter’ - number of the dopplerfilter used (DWD internal)

  • ’statfilter’ - number of a statistical filter used (DWD internal)

  • ’elevprofile’ - as stated in the format description, this list indicates the elevations in the eight 45 degree sectors. These sectors need not start at 0 degrees north, so it is advised to explicitly evaluate the elev attribute, if elevation information is needed.

  • ’message’ - additional text stored in the header.

Examples

See Handling DX Radar Data (German Weather Service).

wradlib.io.radolan.read_radolan_composite(f, *, missing=-9999, loaddata=True, fillmissing=False)

Read quantitative radar composite format of the German Weather Service

The quantitative composite format of the DWD (German Weather Service) was established in the course of the RADOLAN project and includes several file types, e.g. RX, RO, RK, RZ, RP, RT, RC, RI, RG, PC, PG and many, many more. (see format description on the RADOLAN project homepage [DWD, 2009]). At the moment, the national RADOLAN composite is a 900 x 900 grid with 1 km resolution and in polar-stereographic projection. There are other grid resolutions for different composites (e.g. PC, PG)

Note

DWD also provides data in ASCII format, which have a very limited header and need to extract product and datetime from the filename. Use on your own risk.

Added in version 1.17.

Warning

This function already evaluates and applies the so-called PR factor which is specified in the header section of the RADOLAN files. The raw values in an RY file are in the unit 0.01 mm/5min, while read_radolan_composite returns values in mm/5min (e.g. factor 100 higher). The factor is also returned as part of attrs dictionary under keyword “precision”.

Note

You might also use wradlib.io.radolan.open_radolan_dataset or xarray.open_dataset with keyword engine=’radolan’ to import into xarray Dataset.

Parameters:

• f (str or file-like) – path to the composite file or file-like object

• missing (int) – value assigned to no-data cells

• loaddata (bool) – True | False, If False function returns (None, attrs)

• fillmissing (bool) – If True fills truncated values with “missing”. Defaults to False. Does not work for run-length encoded files (“PC” and “PG).

Returns:

output (tuple) –

tuple of two items (data, attrs):

• data : numpy.ndarray of shape (number of rows, number of columns) or xarray.Dataset

• attrs : dict of metadata information from the file header

Examples

See RADOLAN data formats.

wradlib.io.radolan.get_radolan_filehandle(fname)

Opens radolan file and returns file handle

Parameters:

fname (str or file-like) – filename or file-like object

Returns:

f (object) – file handle

wradlib.io.radolan.read_radolan_header(fid)

Reads radolan ASCII header and returns it as string

Parameters:

fid (object) – file handle

Returns:

header (str)

wradlib.io.radolan.parse_dwd_composite_header(header)

Parses the ASCII header of a DWD quantitative composite file

Parameters:

header (str) – (ASCII header)

Returns:

output (dict) – of metadata retrieved from file header

wradlib.io.radolan.read_radolan_binary_array(fid, size, *, raise_on_error=True)

Read binary data from file given by filehandle

Parameters:

• fid (object) – file handle

• size (int) – number of bytes to read

• raise_on_error (bool) – If True, raise IOError if data is truncated.

Returns:

binarr (bytes) – binary data

wradlib.io.radolan.decode_radolan_runlength_array(binarr, attrs)

Decodes the binary runlength coded section from DWD composite file and return decoded numpy array with correct shape

Parameters:

• binarr (str) – Buffer

• attrs (dict) – Attribute dict of file header

Returns:

arr (numpy.ndarray) – Array of decoded values

Rainbow Data I/O

Reads data from Leonardo’s Rainbow5 data formats. Former available code was ported to xradar-package and is imported from there.

read_rainbow reads all data and metadata into a dictionary. Reading sweep data can be skipped by setting loaddata=False.

read_rainbow

Reads Rainbow files according to their structure

wradlib.io.rainbow.read_rainbow(filename, *, loaddata=True)

Reads Rainbow files according to their structure

In contrast to other file readers under wradlib.io, this function will not return a two item tuple with (data, metadata). Instead, this function returns ONE dictionary that contains all the file contents - both data and metadata. The keys of the output dictionary conform to the XML outline in the original data file. The radar data will be extracted from the data blobs, converted and added to the dict with key ‘data’ at the place where the @blobid was pointing from.

Parameters:

• filename (str or file-like) – a rainbow file path or file-like object of rainbow file

• loaddata (bool) – Defaults to True. If False function returns only metadata.

Returns:

rbdict (dict) – a dictionary that contains both data and metadata according to the original rainbow file structure

Examples

See Leonardo Rainbow.

Xarray based Data I/O

Note

The Xarray backend code has been moved to xradar-package.

WradlibVariable

Minimal variable wrapper.

class wradlib.io.xarray.WradlibVariable(dims, data, attrs)

Bases: object

Minimal variable wrapper.

property dimensions

property data

property attributes

class wradlib.io.IrisCartesianProductFile(irisfile, **kwargs)

Bases: IrisRecordFile

Class for retrieving data from Sigmet IRIS Cartesian Product files.

product_identifier = ['MAX', 'TOPS', 'HMAX', 'BASE', 'THICK', 'PPI', 'RHI', 'CAPPI', 'RAINN', 'RAIN1', 'CROSS', 'SHEAR', 'SRI', 'RTI', 'VIL', 'LAYER', 'BEAM', 'MLHGT']

property data

fix_ext_header(ext)

get_extended_header()

get_image(header)

Retrieve cartesian image.

Parameters:

header (dict) – header dictionary

Returns:

data (numpy.ndarray) – 3D array of cartesian data

get_data()

Retrieves cartesian data from file.

decode_data(data, prod)

Decode data according given prod-dict.

Parameters:

• data (numpy.ndarray) – data to decode

• prod (dict) – dictionary holding decoding information

Returns:

data (numpy.ndarray) – decoded data

class wradlib.io.IrisProductFile(filename, **kwargs)

Bases: IrisRecordFile

Class for retrieving data from Sigmet IRIS Product files.

product_identifier = ['CATCH', 'FCAST', 'NDOP', 'SLINE', 'TDWR', 'TRACK', 'VAD', 'VVP', 'WARN', 'WIND', 'STATUS']

property data

property protect_setup

get_protect_setup()

get_results(results, num, structure)

get_data()

Retrieves cartesian data from file.

class wradlib.io.RadolanBackendEntrypoint

Bases: BackendEntrypoint

Xarray BackendEntrypoint for RADOLAN data.

description: ClassVar[str] = 'Open RADOLAN in Xarray'

url: ClassVar[str] = 'https://docs.wradlib.org/en/stable/notebooks/fileio/backends/radolan_backend.html'

open_dataset(filename_or_obj, *, mask_and_scale=True, decode_times=True, concat_characters=True, decode_coords=True, drop_variables=None, use_cftime=None, decode_timedelta=None, fillmissing=False, copy=False, ancillary=False)

Backend open_dataset method used by Xarray in open_dataset.

class wradlib.io.VectorSource(data=None, trg_crs=None, name='layer', source=0, **kwargs)

Bases: object

DataSource class for handling ogr/gdal vector data

DataSource handles creates in-memory (vector) ogr DataSource object with one layer for point or polygon geometries.

Parameters:

• data (sequence or str) – sequence of source points (shape Nx2) or polygons (shape NxMx2) or Vector File (GDAL/OGR) filename containing source points/polygons

• trg_crs (osgeo.osr.SpatialReference) – GDAL OSR SRS describing target CRS the source data should be projected to

Keyword Arguments:

• name (str) – Layer Name, defaults to “layer”.

• source (int) – Number of layer to load, if multiple layers in source shape file.

• mode (str) – Return type of class access functions/properties. Can be either of “numpy”, “geo” and “ogr”, defaults to “numpy”.

• src_crs (osgeo.osr.SpatialReference) – GDAL OGR SRS describing projection source in which data is provided in.

Warning

Writing shapefiles with the wrong locale settings can have impact on the type of the decimal. If problem arise use LC_NUMERIC=C in your environment.

Examples

See Vector Source.

close()

property mode

property ds

Returns VectorSource

property extent

property crs

property data

Returns VectorSource geometries as numpy arrays

Note

This may be slow, because it extracts all source polygons

property geo

Returns VectorSource geometries as GeoPandas Dataframe

get_data_by_idx(idx, *, mode=None)

Returns DataSource geometries from given index

Parameters:

• idx (sequence) – sequence of int indices

• mode (str, optional) – return type (“numpy”, “geo”, “ogr”), defaults to “numpy”

get_data_by_att(attr=None, value=None, mode=None)

Returns DataSource geometries filtered by given attribute/value

Keyword Arguments:

• attr (str) – attribute name

• value (str) – attribute value

• mode (str) – return type (“numpy”, “geo”, “ogr”), defaults to “numpy”

get_data_by_geom(geom=None, mode=None)

Returns DataSource geometries filtered by given geometry

Keyword Arguments:

• geom (osgeo.ogr.Geometry | geopandas.GeoDataFrame) – OGR.Geometry object or geopandas.GeoDataFrame containing the Geometry

• mode (str) – return type (“numpy”, “geo”, “ogr”), defaults to “numpy”

dump_vector(filename, *, driver='ESRI Shapefile', remove=True)

Output layer to OGR Vector File

Parameters:

• filename (str) – path to shape-filename

• driver (str, optional) – driver string, defaults to “ESRI SHapefile”

• remove (bool, optional) – if True removes existing output file, defaults to True

load_vector(filename, *, source=0, driver='ESRI Shapefile')

Read Layer from OGR Vector File

Parameters:

• filename (str) – path to shape-filename

• source (int or str, optional) – number or name of wanted layer, defaults to 0

• driver (str, optional) – driver string, defaults to “ESRI Shapefile”

dump_raster(filename, *, driver='GTiff', attr=None, pixel_size=1.0, **kwargs)

Output layer to GDAL Rasterfile

Parameters:

• filename (str) – path to shape-filename

• driver (str, optional) – GDAL Raster Driver, defaults to “GTiff”.

• attr (str, optional) – attribute to burn into raster, defaults to None.

• pixel_size (float, optional) – pixel Size in source units

Keyword Arguments:

• remove (bool, optional) – if True removes existing output file. Defaults to True.

• silent (bool, optional) – If True no ProgressBar is shown. Defaults to False.

set_attribute(name, values, *, reset_filter=False)

Add/Set given Attribute with given values

Parameters:

• name (str) – Attribute Name

• values (numpy.ndarray) – Values to fill in attributes.

• reset_filter (bool, optional) – reset any layer filter (spatial/attribute), defaults to False.

get_attributes(attrs, *, filt=None)

Return attributes

Parameters:

• attrs (list) – Attribute Names to retrieve

• filt (tuple, optional) – (attname, value) for Attribute Filter, defaults to None

get_geom_properties(props, *, filt=None)

Return geometry properties

Parameters:

• props (list) – Property Names to retrieve

• filt (tuple, optional) – (attname, value) for Attribute Filter, defaults to None.

get_attrs_and_props(*, attrs=None, props=None, filt=None)

Return properties and attributes

Keyword Arguments:

• attrs (list) – Attribute Names to retrieve

• props (list) – Property Names to retrieve

• filt (tuple) – (attname, value) for Attribute Filter

class wradlib.io.WradlibVariable(dims, data, attrs)

Bases: object

Minimal variable wrapper.

property dimensions

property data

property attributes

wradlib.io.decode_radolan_runlength_array(binarr, attrs)

Decodes the binary runlength coded section from DWD composite file and return decoded numpy array with correct shape

Parameters:

• binarr (str) – Buffer

• attrs (dict) – Attribute dict of file header

Returns:

arr (numpy.ndarray) – Array of decoded values

wradlib.io.download_srtm(filename, destination, *, resolution=3, session=None)

Download NASA SRTM elevation data Only available with login/password

Parameters:

• filename (str) – srtm file to download

• destination (str) – output filename

Keyword Arguments:

• resolution (int) – resolution of SRTM data (1, 3 or 30)

• session (object) – session object to use

wradlib.io.from_hdf5(fpath, *, dataset='data')

Loading data from hdf5 files that was stored by to_hdf5

Parameters:

• fpath (str or file-like) – path to the hdf5 file or file-like object

• dataset (str) – name of the Dataset in which the data is stored

wradlib.io.from_pickle(fpath)

Return pickled object from file <fpath>

wradlib.io.gdal_create_dataset(drv, name, cols=0, rows=0, bands=0, *, gdal_type=None, remove=False)

Creates GDAL.DataSet object.

Parameters:

• drv (str) – GDAL driver string

• name (str) – path to filename

• cols (int) – number of columns

• rows (int) – number of rows

• bands (int) – number of raster bands

• gdal_type (gdal:osgeo.ogr.DataType) – raster data type, e.g. gdal.GDT_Float32

• remove (bool) – if True, existing gdal.Dataset will be removed before creation

Returns:

out (osgeo.gdal.Dataset) – gdal.Dataset

wradlib.io.get_membership_functions(filename)

Reads membership function parameters from wradlib-data file.

Parameters:

filename (str) – Filename of wradlib-data file

Returns:

msf (numpy.ndarray) – Array of membership funcions with shape (hm-classes, observables, indep-ranges, 5)

wradlib.io.get_radiosonde(wmoid, date, *, cols=None)

Download radiosonde data from internet.

Based on http://weather.uwyo.edu/upperair/sounding.html.

Parameters:

• wmoid (int) – WMO radiosonde ID

• date (datetime.datetime) – Date and Time

• cols (tuple, optional) – tuple of int or strings describing the columns to consider, defaults to None (all columns)

Returns:

• data (numpy.ndarray) – Structured array of radiosonde data

• meta (dict) – radiosonde metadata

wradlib.io.get_radolan_filehandle(fname)

Opens radolan file and returns file handle

Parameters:

fname (str or file-like) – filename or file-like object

Returns:

f (object) – file handle

wradlib.io.get_srtm(extent, *, resolution=3, merge=True, session=None)

Get NASA SRTM elevation data

Parameters:

• extent (list) – list containing lonmin, lonmax, latmin, latmax

• resolution (int) – resolution of SRTM data (1, 3 or 30)

• merge (bool) – True to merge the tiles in one dataset

• session (object) – session object to use

Returns:

dataset (osgeo.gdal.Dataset) – gdal.Dataset Raster dataset containing elevation information

wradlib.io.get_srtm_tile_names(extent)

Get NASA SRTM elevation data tile names

Parameters:

extent (list) – list containing lonmin, lonmax, latmin, latmax

Returns:

out (list) – list of tile names

wradlib.io.open_gpm_dataset(filename, group)

Reads GPM files version V07A.

Parameters:

• filename (str) – path of the GPM file

• group (str) – name of group

Returns:

ds (xarray.Dataset) – xarray.Dataset representation of GPM file with requested group.

wradlib.io.open_radolan_dataset(filename_or_obj, **kwargs)

Open and decode a RADOLAN dataset from a file or file-like object.

Parameters:

filename_or_obj (str, Path, file-like or DataStore) – Strings and Path objects are interpreted as a path to a local or remote file.

Keyword Arguments:

• fillmissing (bool) – Fill truncated data, defaults to False.

• copy (bool) – Create copies instead of views into the data, defaults to False.

• ancillary (bool, tuple of str) – If True, resturns ancillary masks (“secondary”, “nodatamask”, “cluttermask”) as additional data variables. Can be specified as tuple of strings. Defaults to False.

• **kwargs (dict, optional) – Additional arguments passed on to xarray.open_dataset.

Returns:

dataset (xarray.Dataset)

wradlib.io.open_radolan_mfdataset(paths, **kwargs)

Open multiple RADOLAN files as a single dataset.

Needs dask-package to be installed.

Parameters:

paths (str or sequence) – Either a string glob in the form "path/to/my/files/*" or an explicit list of files to open. Paths can be given as strings or as pathlib Paths.

Keyword Arguments:

• fillmissing (bool) – Fill truncated data, defaults to False.

• copy (bool) – Create copies instead of views into the data, defaults to False.

• ancillary (bool, tuple of str) – If True, resturns ancillary masks (“secondary”, “nodatamask”, “cluttermask”) as additional data variables. Can be specified as tuple of strings. Defaults to False.

• **kwargs (dict, optional) – Additional arguments passed on to xarray.open_mfdataset.

Returns:

dataset (xarray.Dataset)

wradlib.io.open_raster(filename, *, driver=None)

Open raster file, return gdal.Dataset

Parameters:

• filename (str) – raster file name

• driver (str) – gdal driver string

Returns:

dataset (osgeo.gdal.Dataset) – gdal.Dataset

wradlib.io.open_vector(filename, *, driver=None, layer=0)

Open vector file, return gdal.Dataset and OGR.Layer

Warning

dataset and layer have to live in the same context, if dataset is deleted all layer references will get lost

Parameters:

• filename (str) – vector file name

• driver (str) – gdal driver string

• layer (int or str)

Returns:

• dataset (osgeo.gdal.Dataset) – gdal.Dataset

• layer (osgeo.ogr.Layer) – ogr.Layer

wradlib.io.parse_dwd_composite_header(header)

Parses the ASCII header of a DWD quantitative composite file

Parameters:

header (str) – (ASCII header)

Returns:

output (dict) – of metadata retrieved from file header

wradlib.io.read_dx(filename)

Data reader for German Weather Service DX product raw radar data files.

This product uses a simple algorithm to compress zero values to reduce data file size.

Notes

While the format appears to be well-defined, there have been reports on DX- files that seem to produce errors. e.g. while one file usually contains a 360 degree by 128 1km range bins, there are files, that contain 361 beams. Also, while usually azimuths are stored monotonously in ascending order, this is not guaranteed by the format. This routine does not (yet) check for this and directly returns the data in the order found in the file. If you are in doubt, check the ‘azim’ attribute. Be aware that this function does no extensive checking on its output. If e.g. beams contain different numbers of range bins, the resulting data will not be a 2-D array but a 1-D array of objects, which will most probably break calling code. It was decided to leave the handling of these (hopefully) rare events to the user, who might still be able to retrieve some reasonable data, instead of raising an exception, making it impossible to get any data from a file containing errors.

Parameters:

filename (str or file-like) – filename of binary file of DX raw data or file-like object

Returns:

• data (numpy.ndarray) – Array of image data [dBZ]; shape (360,128)

• attributes (dict) – dictionary of attributes - currently implemented keys:

  • ’azim’ - azimuths array of shape (360, )

  • ’elev’ - elevations (1 per azimuth); array of shape (360, )

  • ’clutter’ - clutter mask; boolean array of same shape as data; corresponds to bit 15 set in each dataset.

  • ’bytes’- the total product length (including header). Apparently, this value may be off by one byte for unknown reasons

  • ’version’- a product version string - use unknown

  • ’cluttermap’ - number of the (DWD internal) cluttermap used

  • ’dopplerfilter’ - number of the dopplerfilter used (DWD internal)

  • ’statfilter’ - number of a statistical filter used (DWD internal)

  • ’elevprofile’ - as stated in the format description, this list indicates the elevations in the eight 45 degree sectors. These sectors need not start at 0 degrees north, so it is advised to explicitly evaluate the elev attribute, if elevation information is needed.

  • ’message’ - additional text stored in the header.

Examples

See Handling DX Radar Data (German Weather Service).

wradlib.io.read_edge_netcdf(filename, *, enforce_equidist=False)

Data reader for netCDF files exported by the EDGE radar software

The corresponding NetCDF files from the EDGE software typically contain only one variable (e.g. reflectivity) for one elevation angle (sweep). The elevation angle is specified in the attributes keyword “Elevation”. Please note that the radar might not return data with equidistant azimuth angles. In case you need equidistant azimuth angles, please set enforce_equidist to True.

Parameters:

• filename (str or file-like) – path of the netCDF file or file-like object

• enforce_equidist (bool) – Set True if the values of the azimuth angles should be forced to be equidistant; default value is False

Returns:

output (tuple) – Array of image data (dBZ), dictionary of attributes

wradlib.io.read_gamic_hdf5(filename, *, wanted_elevations=None, wanted_moments=None)

Data reader for hdf5 files produced by the commercial GAMIC Enigma V3 MURAN software

See GAMIC homepage for further info (https://www.gamic.com).

Parameters:

• filename (str or file-like) – path of the gamic hdf5 file or file-like object

• wanted_elevations (sequence) – sequence of strings of elevation_angle(s) of scan (only needed for PPI)

• wanted_moments (sequence) – sequence of strings of moment name(s)

Returns:

• data (dict) – dictionary of scan and moment data (numpy arrays)

• attrs (dict) – dictionary of attributes

Examples

See GAMIC HDF5.

wradlib.io.read_generic_hdf5(fname)

Reads hdf5 files according to their structure

In contrast to other file readers under wradlib.io, this function will not return a two item tuple with (data, metadata). Instead, this function returns ONE dictionary that contains all the file contents - both data and metadata. The keys of the output dictionary conform to the Group/Subgroup directory branches of the original file.

Parameters:

fname (str or file-like) – a hdf5 file path or file-like object

Returns:

output (dict) – a dictionary that contains both data and metadata according to the original hdf5 file structure

Examples

See Reading HDF5 files with a generic reader.

wradlib.io.read_generic_netcdf(fname)

Reads netcdf files and returns a dictionary with corresponding structure.

In contrast to other file readers under wradlib.io, this function will not return a two item tuple with (data, metadata). Instead, this function returns ONE dictionary that contains all the file contents - both data and metadata. The keys of the output dictionary conform to the Group/Subgroup directory branches of the original file. Please see the examples below on how to browse through a return object. The most important keys are the “dimensions” which define the shape of the data arrays, and the “variables” which contain the actual data and typically also the data that define the dimensions (e.g. sweeps, azimuths, ranges). These keys should be present in any netcdf file.

Note

The returned dictionary could be quite big, depending on the content of the file.

Parameters:

fname (str or file-like) – a netcdf file path or file-like object

Returns:

out (dict) – an ordered dictionary that contains both data and metadata according to the original netcdf file structure

Examples

See Reading NetCDF.

wradlib.io.read_gpm(filename, *, bbox=None)

Reads GPM files for matching with GR

Parameters:

• filename (str) – path of the GPM file

• bbox (dict) – dictionary with bounding box coordinates (lon, lat), defaults to None

Returns:

gpm_data (dict) – dictionary of gpm data

Examples

See Match spaceborn SR (GPM/TRMM) with ground radars GR.

wradlib.io.read_iris(filename, *, loaddata=True, rawdata=False, debug=False, **kwargs)

Read Iris file and return dictionary.

Parameters:

• filename (str or file-like) – Filename of data file or file-like object.

• loaddata (bool or dict) – If true, retrieves whole data section from file. If false, retrievs only ingest_data_headers, but no data. If dict, retrieves according to given dict:

  loaddata = {'moment': ['DB_DBZ', 'DB_VEL'],
              'sweep': [1, 3, 9]}
  

• rawdata (bool) – If true, returns raw unconverted/undecoded data.

• debug (bool) – If true, print debug messages.

Returns:

data (dict) – Ordered Dictionary with data and metadata retrieved from file.

Examples

See Vaisala Sigmet IRIS.

wradlib.io.read_opera_hdf5(fname)

Reads hdf5 files according to OPERA conventions

Please refer to the OPERA data model documentation [B1] in order to understand how an hdf5 file is organized that conforms to the OPERA ODIM_H5 conventions.

In contrast to other file readers under wradlib.io, this function will not return a two item tuple with (data, metadata). Instead, this function returns ONE dictionary that contains all the file contents - both data and metadata. The keys of the output dictionary conform to the Group/Subgroup directory branches of the original file. If the end member of a branch (or path) is “data”, then the corresponding item of output dictionary is a numpy array with actual data.

Any other end member (either how, where, and what) will contain the meta information applying to the corresponding level of the file hierarchy.

Parameters:

fname (str or file-like) – a hdf5 file path or file-like object

Returns:

output (dict) – a dictionary that contains both data and metadata according to the original hdf5 file structure

wradlib.io.read_radolan_binary_array(fid, size, *, raise_on_error=True)

Read binary data from file given by filehandle

Parameters:

• fid (object) – file handle

• size (int) – number of bytes to read

• raise_on_error (bool) – If True, raise IOError if data is truncated.

Returns:

binarr (bytes) – binary data

wradlib.io.read_radolan_composite(f, *, missing=-9999, loaddata=True, fillmissing=False)

Read quantitative radar composite format of the German Weather Service

The quantitative composite format of the DWD (German Weather Service) was established in the course of the RADOLAN project and includes several file types, e.g. RX, RO, RK, RZ, RP, RT, RC, RI, RG, PC, PG and many, many more. (see format description on the RADOLAN project homepage [DWD, 2009]). At the moment, the national RADOLAN composite is a 900 x 900 grid with 1 km resolution and in polar-stereographic projection. There are other grid resolutions for different composites (e.g. PC, PG)

Note

DWD also provides data in ASCII format, which have a very limited header and need to extract product and datetime from the filename. Use on your own risk.

Added in version 1.17.

Warning

This function already evaluates and applies the so-called PR factor which is specified in the header section of the RADOLAN files. The raw values in an RY file are in the unit 0.01 mm/5min, while read_radolan_composite returns values in mm/5min (e.g. factor 100 higher). The factor is also returned as part of attrs dictionary under keyword “precision”.

Note

You might also use wradlib.io.radolan.open_radolan_dataset or xarray.open_dataset with keyword engine=’radolan’ to import into xarray Dataset.

Parameters:

• f (str or file-like) – path to the composite file or file-like object

• missing (int) – value assigned to no-data cells

• loaddata (bool) – True | False, If False function returns (None, attrs)

• fillmissing (bool) – If True fills truncated values with “missing”. Defaults to False. Does not work for run-length encoded files (“PC” and “PG).

Returns:

output (tuple) –

tuple of two items (data, attrs):

• data : numpy.ndarray of shape (number of rows, number of columns) or xarray.Dataset

• attrs : dict of metadata information from the file header

Examples

See RADOLAN data formats.

wradlib.io.read_radolan_header(fid)

Reads radolan ASCII header and returns it as string

Parameters:

fid (object) – file handle

Returns:

header (str)

wradlib.io.read_rainbow(filename, *, loaddata=True)

Reads Rainbow files according to their structure

In contrast to other file readers under wradlib.io, this function will not return a two item tuple with (data, metadata). Instead, this function returns ONE dictionary that contains all the file contents - both data and metadata. The keys of the output dictionary conform to the XML outline in the original data file. The radar data will be extracted from the data blobs, converted and added to the dict with key ‘data’ at the place where the @blobid was pointing from.

Parameters:

• filename (str or file-like) – a rainbow file path or file-like object of rainbow file

• loaddata (bool) – Defaults to True. If False function returns only metadata.

Returns:

rbdict (dict) – a dictionary that contains both data and metadata according to the original rainbow file structure

Examples

See Leonardo Rainbow.

wradlib.io.read_safnwc(filename)

Read MSG SAFNWC hdf5 file into a gdal georeferenced object

Parameters:

filename (str) – satellite file name

Returns:

ds (osgeo.gdal.Dataset) – gdal.DataSet with satellite data

wradlib.io.read_trmm(filename1, filename2, *, bbox=None)

Reads TRMM files for matching with GR

Parameters:

• filename1 (str) – path of the TRMM 2A23 file

• filename2 (str) – path of the TRMM 2A25 file

• bbox (dict) – dictionary with bounding box coordinates (lon, lat), defaults to None

Returns:

trmm_data (dict) – dictionary of trmm data

Examples

See Match spaceborn SR (GPM/TRMM) with ground radars GR.

wradlib.io.to_hdf5(fpath, data, *, mode='w', metadata=None, dataset='data', compression='gzip')

Quick storage of one <data> array and a <metadata> dict in an hdf5 file

This is more efficient than pickle, cPickle or numpy.save. The data is stored in a subgroup named data (i.e. file[“data”]). See from_hdf5 for retrieving stored data.

Parameters:

• fpath (str or file-like) – path to the hdf5 file or file-like object

• data (numpy.ndarray)

• mode (str) – file open mode, defaults to “w” (create, truncate if exists)

• metadata (dict) – dictionary of data’s attributes

• dataset (str) – describing dataset

• compression (str) – h5py-compression type {“gzip”|”szip”|”lzf”}, see h5py-documentation for details

wradlib.io.to_pickle(fpath, obj)

Pickle object <obj> to file <fpath>

wradlib.io.write_polygon_to_text(fname, polygons)

Writes Polygons to a Text file which can be interpreted by ESRI ArcGIS’s “Create Features from Text File (Samples)” tool.

This is (yet) only a convenience function with limited functionality. E.g. interior rings are not yet supported.

Parameters:

• fname (str) – name of the file to save the vertex data to

• polygons (list) – list of lists of polygon vertices. Each vertex itself is a list of 3 coordinate values and an additional value. The third coordinate and the fourth value may be nan.

Returns:

None

Note

As Polygons are closed shapes, the first and the last vertex of each polygon must be the same!

Examples

Writes two triangle Polygons to a text file::

poly1 = [[0.,0.,0.,0.],[0.,1.,0.,1.],[1.,1.,0.,2.],[0.,0.,0.,0.]] poly2 = [[0.,0.,0.,0.],[0.,1.,0.,1.],[1.,1.,0.,2.],[0.,0.,0.,0.]] polygons = [poly1, poly2] write_polygon_to_text(‘polygons.txt’, polygons)

The resulting text file will look like this::

Polygon 0 0 0 0.000000 0.000000 0.000000 0.000000 1 0.000000 1.000000 0.000000 1.000000 2 1.000000 1.000000 0.000000 2.000000 3 0.000000 0.000000 0.000000 0.000000 1 0 0 0.000000 0.000000 0.000000 0.000000 1 0.000000 1.000000 0.000000 1.000000 2 1.000000 1.000000 0.000000 2.000000 3 0.000000 0.000000 0.000000 0.000000 END

wradlib.io.write_raster_dataset(fpath, dataset, *, driver='GTiff', **kwargs)

Write raster dataset to file format

Parameters:

• fpath (str) – A file path - should have file extension corresponding to format.

• dataset (osgeo.gdal.Dataset) – gdal.Dataset gdal raster dataset

• driver (str, optional) – gdal raster format driver string, defaults to “GTiff”

Keyword Arguments:

• options (list, optional) – Option strings for the corresponding format. Defaults to

• remove (bool, optional) – if True, existing gdal.Dataset will be removed before creation, defaults to False

Note

For format and options refer to formats_list.

Examples

See Export a dataset in GIS-compatible format.