def time_sun_rise_set_transit_geometric_full_comparison(self, ndays):
dayofyear = self.times_daily.dayofyear
declination = solarposition.declination_spencer71(dayofyear)
equation_of_time = solarposition.equation_of_time_spencer71(dayofyear)
solarposition.sun_rise_set_transit_geometric(
self.times_daily, self.lat, self.lon, declination,
equation_of_time)
def test_sun_rise_set_transit_geometric(expected_rise_set_spa, golden_mst):
"""Test geometric calculations for sunrise, sunset, and transit times"""
times = expected_rise_set_spa.index
latitude = golden_mst.latitude
longitude = golden_mst.longitude
eot = solarposition.equation_of_time_spencer71(times.dayofyear) # minutes
decl = solarposition.declination_spencer71(times.dayofyear) # radians
sr, ss, st = solarposition.sun_rise_set_transit_geometric(
times,
latitude=latitude,
longitude=longitude,
declination=decl,
equation_of_time=eot)
# sunrise: 2015-01-02 07:26:39.763224487, 2015-08-02 05:04:35.688533801
# sunset: 2015-01-02 16:41:29.951096777, 2015-08-02 19:09:46.597355085
# transit: 2015-01-02 12:04:04.857160632, 2015-08-02 12:07:11.142944443
test_sunrise = solarposition._times_to_hours_after_local_midnight(sr)
test_sunset = solarposition._times_to_hours_after_local_midnight(ss)
test_transit = solarposition._times_to_hours_after_local_midnight(st)
# convert expected SPA sunrise, sunset, transit to local datetime indices
expected_sunrise = pd.DatetimeIndex(expected_rise_set_spa.sunrise.values,
tz='UTC').tz_convert(golden_mst.tz)
expected_sunset = pd.DatetimeIndex(expected_rise_set_spa.sunset.values,
tz='UTC').tz_convert(golden_mst.tz)
expected_transit = pd.DatetimeIndex(expected_rise_set_spa.transit.values,
tz='UTC').tz_convert(golden_mst.tz)
# convert expected times to hours since midnight as arrays of floats
expected_sunrise = solarposition._times_to_hours_after_local_midnight(
expected_sunrise)
expected_sunset = solarposition._times_to_hours_after_local_midnight(
expected_sunset)
expected_transit = solarposition._times_to_hours_after_local_midnight(
expected_transit)
# geometric time has about 4-6 minute error compared to SPA sunset/sunrise
expected_sunrise_error = np.array(
[0.07910089555555544, 0.06908014805555496]) # 4.8[min], 4.2[min]
expected_sunset_error = np.array(
[-0.1036246955555562, -0.06983406805555603]) # -6.2[min], -4.2[min]
expected_transit_error = np.array(
[-0.011150788888889096, 0.0036508177777765383]) # -40[sec], 13.3[sec]
assert np.allclose(test_sunrise,
expected_sunrise,
atol=np.abs(expected_sunrise_error).max())
assert np.allclose(test_sunset,
expected_sunset,
atol=np.abs(expected_sunset_error).max())
assert np.allclose(test_transit,
expected_transit,
atol=np.abs(expected_transit_error).max())
def test_sun_rise_set_transit_geometric(expected_rise_set_spa, golden_mst):
"""Test geometric calculations for sunrise, sunset, and transit times"""
times = expected_rise_set_spa.index
latitude = golden_mst.latitude
longitude = golden_mst.longitude
eot = solarposition.equation_of_time_spencer71(times.dayofyear) # minutes
decl = solarposition.declination_spencer71(times.dayofyear) # radians
sr, ss, st = solarposition.sun_rise_set_transit_geometric(
times, latitude=latitude, longitude=longitude, declination=decl,
equation_of_time=eot)
# sunrise: 2015-01-02 07:26:39.763224487, 2015-08-02 05:04:35.688533801
# sunset: 2015-01-02 16:41:29.951096777, 2015-08-02 19:09:46.597355085
# transit: 2015-01-02 12:04:04.857160632, 2015-08-02 12:07:11.142944443
test_sunrise = solarposition._times_to_hours_after_local_midnight(sr)
test_sunset = solarposition._times_to_hours_after_local_midnight(ss)
test_transit = solarposition._times_to_hours_after_local_midnight(st)
# convert expected SPA sunrise, sunset, transit to local datetime indices
expected_sunrise = pd.DatetimeIndex(expected_rise_set_spa.sunrise.values,
tz='UTC').tz_convert(golden_mst.tz)
expected_sunset = pd.DatetimeIndex(expected_rise_set_spa.sunset.values,
tz='UTC').tz_convert(golden_mst.tz)
expected_transit = pd.DatetimeIndex(expected_rise_set_spa.transit.values,
tz='UTC').tz_convert(golden_mst.tz)
# convert expected times to hours since midnight as arrays of floats
expected_sunrise = solarposition._times_to_hours_after_local_midnight(
expected_sunrise)
expected_sunset = solarposition._times_to_hours_after_local_midnight(
expected_sunset)
expected_transit = solarposition._times_to_hours_after_local_midnight(
expected_transit)
# geometric time has about 4-6 minute error compared to SPA sunset/sunrise
expected_sunrise_error = np.array(
[0.07910089555555544, 0.06908014805555496]) # 4.8[min], 4.2[min]
expected_sunset_error = np.array(
[-0.1036246955555562, -0.06983406805555603]) # -6.2[min], -4.2[min]
expected_transit_error = np.array(
[-0.011150788888889096, 0.0036508177777765383]) # -40[sec], 13.3[sec]
assert np.allclose(test_sunrise, expected_sunrise,
atol=np.abs(expected_sunrise_error).max())
assert np.allclose(test_sunset, expected_sunset,
atol=np.abs(expected_sunset_error).max())
assert np.allclose(test_transit, expected_transit,
atol=np.abs(expected_transit_error).max())
def get_sun_rise_set_transit(self, times, method='pyephem', **kwargs):
"""
Calculate sunrise, sunset and transit times.
Parameters
----------
times : DatetimeIndex
Must be localized to the Location
method : str, default 'pyephem'
'pyephem', 'spa', or 'geometric'
kwargs are passed to the relevant functions. See
solarposition.sun_rise_set_transit_<method> for details.
Returns
-------
result : DataFrame
Column names are: ``sunrise, sunset, transit``.
"""
if method == 'pyephem':
result = solarposition.sun_rise_set_transit_ephem(
times, self.latitude, self.longitude, **kwargs)
elif method == 'spa':
result = solarposition.sun_rise_set_transit_spa(
times, self.latitude, self.longitude, **kwargs)
elif method == 'geometric':
sr, ss, tr = solarposition.sun_rise_set_transit_geometric(
times, self.latitude, self.longitude, **kwargs)
result = pd.DataFrame(index=times,
data={
'sunrise': sr,
'sunset': ss,
'transit': tr
})
else:
raise ValueError('{} is not a valid method. Must be '
'one of pyephem, spa, geometric'.format(method))
return result
def get_sun_rise_set_transit(self, times, method='pyephem', **kwargs):
"""
Calculate sunrise, sunset and transit times.
Parameters
----------
times : DatetimeIndex
Must be localized to the Location
method : str, default 'pyephem'
'pyephem', 'spa', or 'geometric'
kwargs are passed to the relevant functions. See
solarposition.sun_rise_set_transit_<method> for details.
Returns
-------
result : DataFrame
Column names are: ``sunrise, sunset, transit``.
"""
if method == 'pyephem':
result = solarposition.sun_rise_set_transit_ephem(
times, self.latitude, self.longitude, **kwargs)
elif method == 'spa':
result = solarposition.sun_rise_set_transit_spa(
times, self.latitude, self.longitude, **kwargs)
elif method == 'geometric':
sr, ss, tr = solarposition.sun_rise_set_transit_geometric(
times, self.latitude, self.longitude, **kwargs)
result = pd.DataFrame(index=times,
data={'sunrise': sr,
'sunset': ss,
'transit': tr})
else:
raise ValueError('{} is not a valid method. Must be '
'one of pyephem, spa, geometric'
.format(method))
return result
