How to use wradlib - 10 common examples

def get_membership_functions(filename):
    """Reads membership function parameters from wradlib-data file.

    Parameters
    ----------
    filename : filename
        Filename of wradlib-data file

    Returns
    -------
    msf : :class:`numpy:numpy.ndarray`
        Array of membership funcions with shape (hm-classes, observables,
        indep-ranges, 5)
    """
    gzip = util.import_optional('gzip')

    with gzip.open(filename, 'rb') as f:
        nclass = int(f.readline().decode().split(':')[1].strip())
        nobs = int(f.readline().decode().split(':')[1].strip())
        with warnings.catch_warnings():
            warnings.filterwarnings('ignore', category=UserWarning)
            data = np.genfromtxt(f, skip_header=10, autostrip=True,
                                 invalid_raise=False)

    data = np.reshape(data, (nobs, int(data.shape[0] / nobs), data.shape[1]))
    msf = np.reshape(data, (data.shape[0], nclass, int(data.shape[1] / nclass),
                            data.shape[2]))
    msf = np.swapaxes(msf, 0, 1)

    return msf

The algorithm is based on the paper of :cite:`Wang2009`.

    Parameters
    ----------
    phidp : :class:`numpy:numpy.ndarray`
        array of shape (...,nr) with nr being the number of range bins
    rho : :class:`numpy:numpy.ndarray`
        array of same shape as ``phidp``
    width : int
       Width of the analysis window
    copy : bool
       Leaves original ``phidp`` array unchanged if set to True
       (default: False)
    """
    # Check whether fast Fortran implementation is available
    speedup = util.import_optional("wradlib.speedup")

    shape = phidp.shape
    assert rho.shape == shape, "rho and phidp must have the same shape."

    phidp = phidp.reshape((-1, shape[-1]))
    if copy:
        phidp = phidp.copy()
    rho = rho.reshape((-1, shape[-1]))
    gradphi = util.gradient_from_smoothed(phidp)

    beams, rs = phidp.shape

    # Compute the standard deviation within windows of 9 range bins
    stdarr = np.zeros(phidp.shape, dtype=np.float32)
    for r in range(rs - 9):
        stdarr[..., r] = np.std(phidp[..., r:r + 9], -1)

def get_radolan_filehandle(fname):
    """Opens radolan file and returns file handle

    Parameters
    ----------
    fname : string
        filename

    Returns
    -------
    f : object
        filehandle
    """

    gzip = util.import_optional('gzip')

    # open file handle
    try:
        f = gzip.open(fname, 'rb')
        f.read(1)
    except IOError:
        f = open(fname, 'rb')
        f.read(1)

    # rewind file
    f.seek(0, 0)

    return f

def get_rb_blob_data(datastring, blobid):
    """ Read BLOB data from datastring and return it

    Parameters
    ----------
    datastring : string
        Blob Description String
    blobid : int
        Number of requested blob

    Returns
    -------
    data : string
        Content of blob
    """
    xmltodict = util.import_optional('xmltodict')

    start = 0
    search_string = '', start)
    xmlstring = datastring[start:end + 1]

    # cheat the xml parser by making xml well-known
    xmldict = xmltodict.parse(xmlstring.decode() + '')
    cmpr = get_rb_blob_attribute(xmldict, 'compression')
    size = int(get_rb_blob_attribute(xmldict, 'size'))
    data = datastring[end + 2:end + 2 + size]  # read blob data to string

    # decompress if necessary

Parameters
    ----------
    datastring : string
        Blob Description String

    blobid : int
        Number of requested blob

    Returns
    -------
    data : string
        Content of blob

    """
    xmltodict = util.import_optional('xmltodict')

    start = 0
    searchString = '', start)
    xmlstring = datastring[start:end + 1]

    # cheat the xml parser by making xml well-known
    xmldict = xmltodict.parse(xmlstring.decode() + '')
    cmpr = get_RB_blob_attribute(xmldict, 'compression')
    size = int(get_RB_blob_attribute(xmldict, 'size'))
    data = datastring[end + 2:end + 2 + size]  # read blob data to string

    # decompress if necessary

def decompress(data):
    """Decompression of data

    Parameters
    ----------
    data : string
        (from xml) data string containing compressed data.
    """
    zlib = util.import_optional('zlib')
    return zlib.decompress(data)

def decompress(data):
    """Decompression of data

    Parameters
    ----------
    data : string
        (from xml) data string containing compressed data.
    """
    zlib = util.import_optional('zlib')
    return zlib.decompress(data)

proj : osr spatial reference object
        GDAL OSR Spatial Reference Object describing projection

    Returns
    -------
    output :  :class:`numpy:numpy.ndarray`
        (num volume bins, 3)

    Examples
    --------
    See :ref:`/notebooks/workflow/recipe2.ipynb`.
    """
    # make sure that elevs is an array
    elevs = np.array([elevs]).ravel()
    # create polar grid
    el, az, r = util.meshgrid_n(elevs, azimuths, ranges)

    # get projected coordinates
    coords = georef.spherical_to_proj(r, az, el, sitecoords, proj=proj)
    coords = coords.reshape(-1, 3)

    return coords

python datetime.object.

    Parameters
    ----------
    name : string
        representing a DWD product name
    tz : timezone object
        (see pytz package or datetime module for explanation)
        in case the timezone of the data is not UTC
    opt : currently unused

    Returns
    -------
    time : timezone-aware datetime.datetime object
    """
    return _getTimestampFromFilename(name).replace(tzinfo=util.UTC())

def _get_valid_pairs(self, obs, raw):
        """INTERNAL: Helper method to identify valid obs-raw pairs
        """
        # checking input shape consistency
        self._check_shape(obs, raw)
        # radar values at gage locations
        rawatobs = self.get_raw_at_obs(raw, obs)
        # check where both gage and radar observations are valid
        ix = np.intersect1d(util._idvalid(obs, minval=self.minval),
                            util._idvalid(rawatobs, minval=self.minval))
        return rawatobs, ix