wradlib Documentation - Bitbucket

wradlib Documentation, Release 0.1.1
Notes
The shape of elevations and ranges may differ in which case numpy’s broadcasting rules will apply and the
shape of output will be that of the broadcast arrays. See the numpy documentation on how broadcasting works.
References
[Doviak1993]
3.7.3 wradlib.qual.pulse_volume
wradlib.qual.pulse_volume(ranges, h, theta)
Calculates the sampling volume of the radar beam per bin depending on range and aperture.
We assume a cone frustum which has the volume V=(pi/3)*h*(R**2 + R*r + r**2). R and r are the radii
of the two frustum surface circles. Assuming that the pulse width is small compared to the range, we get
R=r=tan(theta*pi/180)*range. Thus, the pulse volume simpy becomes a the volume of a cylinder with V=pi * h
* range**2 * tan(theta*pi/180)**2
Parameters ranges : array
h : float
the distances of each bin from the radar [m]
pulse width (which corresponds to the range resolution [m])
theta : float
the aperture angle (beam width) of the radar beam [degree]
Returns output : volume of radar bins at each range in ranges [m**3]
3.8 Composition
Combine data from different radar locations on one common set of locations
extract_circle
togrid
compose_ko
compose_weighted
Extract the indices of coords which fall within a circle
Interpolate data from a radar location to the composite grid or set of locations
Composes grids according to quality information using quality information as a knockout criterion.
Composes grids according to quality information using a weighted averaging approach.
3.8.1 wradlib.comp.extract_circle
wradlib.comp.extract_circle(center, radius, coords)
Extract the indices of coords which fall within a circle defined by center and radius
Parameters center : float
radius : float
coords : array of float with shape (numpoints,2)
Returns output : 1-darray of integers
3.8. Composition 53