def get_rain_peaks(forecast_maps, max_ahead, xy, user_ahead=0, user_intensity=10):
timeframe = user_ahead
max_intensity = 0
peak_mins = 0
while timeframe <= max_ahead:
intensity = rvp_to_dbz(forecast_maps[timeframe][0][xy[0]][xy[1]])
if intensity > max_intensity:
peak_mins = timeframe
max_intensity = intensity
if intensity < user_intensity:
break
timeframe += 5
return max_intensity, peak_mins, timeframe-user_ahead
def test_rvp_to_dbz(self):
self.assertTrue(np.allclose(trafo.rvp_to_dbz(self.rvp), self.dbz))
def test_rvp_to_dbz(self):
assert np.allclose(trafo.rvp_to_dbz(self.rvp), self.dbz)
if interpolatedSpeed > 10:
logging.warn("%s: not pushing for client because of too high interpolated speed %f (orig=%f)" % (token, interpolatedSpeed, travelmodeSpeed))
continue
else:
logging.warn("interpolatedSpeed=%f < 20km/h -> OK" % interpolatedSpeed)
# XXX check lat/lon against the bounds of the dwd data here
# to avoid useless calculations here
# user position in grid
result = closest_node((lon, lat), linearized_grid)
xy = (int(result / gridsize), int(result % gridsize))
# get forecasted value from grid
data = forecast_maps[ahead]
reported_intensity = rvp_to_dbz(forecast_maps[ahead][0][xy[0]][xy[1]])
# also check timeframes BEFORE the configured ahead value
if reported_intensity < intensity:
timeframe = ahead - 5
while timeframe > 0:
previous_intensity = rvp_to_dbz(forecast_maps[timeframe][0][xy[0]][xy[1]])
if previous_intensity >= intensity:
logging.warn("%s: no match for old ahead value, but %d >= %d for lower ahead=%d!" % (token,
previous_intensity, intensity, timeframe))
reported_intensity = previous_intensity
ahead = timeframe
timeframe -= 5
logging.warn("%d >? %d" % (reported_intensity, intensity))
if reported_intensity >= intensity:
def test_rvp_to_dbz(self):
self.assertTrue(np.allclose(trafo.rvp_to_dbz(self.rvp), self.dbz))