Revision 92ceb3989677a4abea76f8a76427d9a7d6add5b1 authored by heisterm on 18 February 2014, 08:18:27 UTC, committed by heisterm on 18 February 2014, 08:18:27 UTC
The function was changed in a way that we now check for each target time interval whether source and target time specs are consistent. If they are not, the target value for that target interval will be NaN. Bfore that change, the entire target series was set to NaN if the specs for only one target interval was inconsistent.
1 parent cad11e3
qual.py
#-------------------------------------------------------------------------------
# Name: qual
# Purpose:
#
# Authors: Maik Heistermann, Stephan Jacobi and Thomas Pfaff
#
# Created: 26.10.2011
# Copyright: (c) Maik Heistermann, Stephan Jacobi and Thomas Pfaff 2011
# Licence: The MIT License
#-------------------------------------------------------------------------------
#!/usr/bin/env python
"""
Data Quality
^^^^^^^^^^^^
This module will serve two purposes:
#. provide routines to create simple radar data quality related fields.
#. provide routines to decide which radar pixel to choose based on the
competing information in different quality fields.
Data is supposed to be stored in 'aligned' arrays. Aligned here means that
all fields are structured such that in each field the data for a certain index
is representative for the same physical target.
Therefore no assumptions are made on the dimensions or shape of the input
fields except that they exhibit the numpy ndarray interface.
.. autosummary::
:nosignatures:
:toctree: generated/
beam_height_ft
beam_height_ft_doviak
pulse_volume
"""
import numpy as np
def beam_height_ft(ranges, elevations, degrees=True, re=6371000):
"""Calculates the height of a radar beam above the antenna according to
the 4/3 (four-thirds -> ft) effective Earth radius model.
The formula was taken from [Collier1996]_.
Parameters
----------
ranges : array
the distances of each bin from the radar [m]
elevations : array
the elevation angles of each bin from the radar [degrees or radians]
degrees : bool
if True (the default) elevation angles are given in degrees and will
be converted to radians before calculation. If False no transformation
will be done and elevations has to be given in radians.
re : float
earth radius [m]
Returns
-------
output : height of the beam [m]
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
----------
.. [Collier1996] Collier, C.G., 1996.
Applications of weather radar systems: A guide to uses of radar data in
meteorology and hydrology 2nd edition, New York: John Wiley and Sons.
"""
if degrees:
elev = np.deg2rad(elevations)
else:
elev = elevations
return ((ranges**2*np.cos(elev)**2)/(2*(4./3.)*re))+ranges*np.sin(elev)
def beam_height_ft_doviak(ranges, elevations, degrees=True, re=6371000):
"""Calculates the height of a radar beam above the antenna according to \
the 4/3 (four-thirds -> ft) effective Earth radius model.
The formula was taken from [Doviak1993]_.
Parameters
----------
ranges : array
the distances of each bin from the radar [m]
elevations : array
the elevation angles of each bin from the radar [degrees or radians]
degrees : bool
if True (the default) elevation angles are assumed to be given in
degrees and will
be converted to radians before calculation. If False no transformation
will be done and `elevations` has to be given in radians.
re : float
earth radius [m]
Returns
-------
output : height of the beam [m]
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] Doviak, R.J. & Zrnic, D.S., 1993.
Doppler radar and weather observations 2nd ed.,
San Diego: Academic Press.
"""
if degrees:
elev = np.deg2rad(elevations)
else:
elev = elevations
reft = (4./3.)*re
return np.sqrt(ranges**2 + reft**2 + 2*ranges*reft*np.sin(elev)) - reft
def 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
the distances of each bin from the radar [m]
h : float
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]
"""
return np.pi * h * (ranges**2) * (np.tan( np.radians(theta) ))**2
if __name__ == '__main__':
print 'wradlib: Calling module <qual> as main...'
Computing file changes ...
