wradlib Documentation - Bitbucket

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wradlib Documentation, Release 0.1.1 index array referring to the coords array 3.8.2 wradlib.comp.togrid wradlib.comp.togrid(src, trg, radius, center, data, interpol, *args, **kwargs) Interpolate data from a radar location to the composite grid or set of locations Parameters src : ndarray of float of shape (numpoints, ndim) cartesian x / y coordinates of the radar bins trg : ndarray of float of shape (numpoints, ndim) cartesian x / y coordinates of the composite radius : float the radius of the radar circle (same units as src and trg) center : array of float the location coordinates of the radar data : ndarray of float the data that should be transferred to composite interpol : an interpolation class name from wradlib.ipol - e.g. Nearest or Idw Returns output : ndarray of float data of the radar circle which is interpolated on the composite grid 3.8.3 wradlib.comp.compose_ko wradlib.comp.compose_ko(radargrids, qualitygrids) Composes grids according to quality information using quality information as a knockout criterion. The value of the composed pixel is taken from the radargrid whose quality grid has the highest value. Parameters radargrids : list of arrays radar data to be composited. Each item in the list corresponds to the data of one radar location. All items must have the same shape. qualitygrids : list of arrays quality data to decide upon which radar site will contribute its pixel to the composite. Then length of this list must be the same as that of radargrids. All items must have the same shape and be aligned with the items in radargrids. Returns composite : array 3.8.4 wradlib.comp.compose_weighted wradlib.comp.compose_weighted(radargrids, qualitygrids) Composes grids according to quality information using a weighted averaging approach. The value of the composed pixel is the weighted average of all radar pixels with the quality values being the weights. 54 Chapter 3. Library Reference
wradlib Documentation, Release 0.1.1 Parameters radargrids : list of arrays qualitygrids : list of arrays Returns composite : array See Also: compose_ko for more description about the shape of the input arrays 3.9 Clutter Identification filter_gabella Clutter identification filter developed by Gabella [Gabella2002] . filter_gabella_a First part of the Gabella filter looking for large reflectivity filter_gabella_b Second part of the Gabella filter comparing area to circumference of histo_cut Histogram based clutter identification. 3.9.1 wradlib.clutter.filter_gabella wradlib.clutter.filter_gabella(img, wsize=5, thrsnorain=0.0, tr1=6.0, n_p=8, tr2=1.3) Clutter identification filter developed by Gabella [Gabella2002] . This is a two-part identification algorithm using echo continuity and minimum echo area to distinguish between meteorological (rain) and non- meteorological echos (ground clutter etc.) See Also: Parameters img : array_like wsize : int thrsnorain : float tr1 : float n_p : int thr2 : float Returns output : array boolean array with pixels identified as clutter set to True. filter_gabella_a the first part of the filter filter_gabella_b the second part of the filter References [Gabella2002] Examples TODO: provide a correct example here 3.9. Clutter Identification 55
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