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wradlib Documentation, Release 0.1.1 3.5.4 wradlib.georef.polar2polyvert wradlib.georef.polar2polyvert(r, az, sitecoords) Generate 2-D polygon vertices directly from polar coordinates. This is an alternative to centroid2polyvert which does not use centroids, but generates the polygon vertices by simply connecting the corners of the radar bins. Both azimuth and range arrays are assumed to be equidistant and to contain only unique values. For further information refer to the documentation of polar2latlon. Parameters r : array array of ranges [m]; r defines the exterior boundaries of the range bins! (not the centroids). Thus, values must be positive! az : array array of azimuth angles containing values between 0° and 360°. The angles are assumed to describe the pointing direction fo the main beam lobe! The first angle can start at any values, but make sure the array is sorted continuously positively clockwise and the angles are equidistant. An angle if 0 degree is pointing north. sitecoords : a sequence of two floats the lat / lon coordinates of the radar location Returns output : a 3-d array of polygon vertices in lon/lat with shape(num_vertices, num_vertex_nodes, 2). The last dimension carries the longitudes on the first position, the latitudes on the second (lon: output[:,:,0], lat: output[:,:,1] Examples >>> import numpy as pl >>> import pylab as pl >>> import matplotlib as mpl >>> # define the polar coordinates and the site coordinates in lat/lon >>> r = np.array([50., 100., 150., 200.]) >>> az = np.array([0., 45., 90., 135., 180., 225., 270., 315., 360.]) >>> sitecoords = (48.0, 9.0) >>> polygons = polar2polyvert(r, az, sitecoords) >>> # plot the resulting mesh >>> fig = pl.figure() >>> ax = fig.add_subplot(111) >>> polycoll = mpl.collections.PolyCollection(vertices,closed=True, facecolors=None) >>> ax.add_collection(polycoll, autolim=True) >>> pl.axis(’tight’) >>> pl.show() 3.5.5 wradlib.georef.centroid2polyvert wradlib.georef.centroid2polyvert(centroid, delta) Calculates the 2-D Polygon vertices necessary to form a rectangular polygon around the centroid’s coordinates. The vertices order will be clockwise, as this is the convention used by ESRI’s shapefile format for a polygon. Parameters centroid : array_like 44 Chapter 3. Library Reference
wradlib Documentation, Release 0.1.1 list of 2-D coordinates of the center point of the rectangle delta : scalar or array symmetric distances of the vertices from the centroid in each direction. If delta is scalar, it is assumed to apply to both dimensions. Returns vertices : array an array with 5 vertices per centroid. Notes The function can currently only deal with 2-D data (If you come up with a higher dimensional version of ‘clockwise’ you’re welcome to add it). The data is then assumed to be organized within the centroid array with the last dimension being the 2-D coordinates of each point. Examples >>> centroid2polyvert([0., 1.], [0.5, 1.5]) array([[-0.5, -0.5], [-0.5, 2.5], [ 0.5, 2.5], [ 0.5, -0.5], [-0.5, -0.5]]) >>> centroid2polyvert(np.arange(4).reshape((2,2)), 0.5) array([[[-0.5, 0.5], [-0.5, 1.5], [ 0.5, 1.5], [ 0.5, 0.5], [-0.5, 0.5]], [[ 1.5, 2.5], [ 1.5, 3.5], [ 2.5, 3.5], [ 2.5, 2.5], [ 1.5, 2.5]]]) 3.5.6 wradlib.georef.project wradlib.georef.project(latc, lonc, projstr, inverse=False) Convert from latitude,longitude (based on WGS84) to coordinates in map projection This mainly serves as a convenience function to use proj.4 via pyproj. For proj.4 documentation visit http://proj.maptools.org. For pyproj documentation visit http://code.google.com/p/pyproj. See http://www.remotesensing.org/geotiff/proj_list for examples of key/value pairs defining different map projections. You can use wradlib.georef.create_projstr in order to create projection strings to be passed with argument projstr. However, the choice is still rather limited. Alternatively, you have to create or look up projection strings by yourself. See the Examples section for a quick start. Parameters latc : array of floats 3.5. Georeferencing 45
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