def test_utc_to_lst_gmst(self):
self.assertEqual(clock.utc_to_lst(datetime.datetime(2010, 12, 25), 0),
clock.utc_to_gmst(datetime.datetime(2010, 12, 25)))
# Perhaps not perfect test, a few seconds of uncertainty exist..
self.assertAlmostEqual(
clock.utc_to_lst(datetime.datetime(2010, 12, 25), 0),
clock.time_to_decimal(datetime.time(6, 13, 35, 852535)))
def test_utc_to_lst_at_longitudes(self):
self.assertAlmostEqual(clock.utc_to_lst(datetime.datetime(2010, 12, 25), 90),
clock.time_to_decimal(datetime.time(12, 13, 35, 852535)))
self.assertAlmostEqual(clock.utc_to_lst(datetime.datetime(2010, 12, 25), 180),
clock.time_to_decimal(datetime.time(18, 13, 35, 852535)))
self.assertAlmostEqual(clock.utc_to_lst(datetime.datetime(2010, 12, 25), 5),
clock.time_to_decimal(datetime.time(6, 33, 35, 852535)))
def test_utc_to_lst_gmst(self):
self.assertEqual(
clock.utc_to_lst(datetime.datetime(2010, 12, 25), 0), clock.utc_to_gmst(datetime.datetime(2010, 12, 25))
)
# Perhaps not perfect test, a few seconds of uncertainty exist..
self.assertAlmostEqual(
clock.utc_to_lst(datetime.datetime(2010, 12, 25), 0),
clock.time_to_decimal(datetime.time(6, 13, 35, 852535)),
)
def oldvsnew_diagram():
"""
Visual accuracy comparisons of old and new transformations.
Compares the correlations between the transformations:
equatorial_to_horizontal and equatorial_to_zenith_azimuth_astropy
horizontal_to_equatorial and horizontal_to_zenith_azimuth_astropy
Makes a histogram of the error differences
between these two functions as well.
The errors seem to be in the order of 1000 arcsec
:return: None
Ethan van Woerkom is responsible for the benchmarking functions;
refer to him for when something is unclear
"""
# make random frames, in correct angle range and from utc time 2000-2020
frames = []
# boxes for the four different transformation results
etoha = []
etoh = []
htoe = []
htoea = []
straight = lambda x : x # straight trendline function
# Create the data sets for eq to az
for i in range(100):
frames.append((r.uniform(-90, 90),
r.uniform(-180,180),
r.randint(946684800,1577836800),
r.uniform(0, 2 * np.pi),
r.uniform(-0.5 * np.pi, 0.5 * np.pi)))
for i in frames:
etoha.append(celestial.equatorial_to_zenithazimuth_astropy(i[0], i[1], i[2], [(i[3], i[4])])[0])
etoh.append(celestial.equatorial_to_zenithazimuth(i[0], i[1], clock.utc_to_gps(i[2]), i[3], i[4]))
# Data sets for hor to eq
for i in frames:
htoe.append(celestial.horizontal_to_equatorial(i[0],
clock.utc_to_lst(datetime.datetime.utcfromtimestamp(i[2]), i[1]), i[4], i[3]))
htoea.extend(celestial.horizontal_to_equatorial_astropy(i[0], i[1], i[2], [(i[3], i[4])]))
# Make figs eq -> zenaz
plt.figure(1)
plt.suptitle('Zen/Az correlation in rads (equatorial_to_zenithazimuth)')
zenrange = [0, np.pi]
plt.subplot(211)
plt.title('Zenith')
plt.axis(zenrange*2)
plt.xlabel('New (Astropy)')
plt.ylabel('Old')
# Make figure and add 1:1 trendline
plt.plot([co[0] for co in etoha], [co[0] for co in etoh], 'r.', zenrange, straight(zenrange), '-')
plt.subplot(212)
plt.title('Azimuth')
azrange = [-np.pi, np.pi]
plt.axis(azrange*2)
plt.xlabel('New (Astropy)')
plt.ylabel('Old')
# Make figure and add 1:1 trendline
plt.plot([co[1] for co in etoha], [co[1] for co in etoh], 'b.', azrange, straight(azrange), '-')
plt.tight_layout() # Prevent titles merging
plt.subplots_adjust(top=0.85)
# Make histogram of differences
plt.figure(2)
# Take diff. and convert to arcsec
nieuw = (np.array(etoh) - np.array(etoha))
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist([i[0] for i in nieuw], bins=20)
plt.title('Zenith Old-New Error (equatorial_to_zenithazimuth)')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
plt.figure(3)
plt.hist([i[1] for i in nieuw], bins=20)
plt.title('Azimuth Old-New Error (equatorial_to_zenithazimuth)')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
# Make histogram of differences using the absolute distance in arcsec
# this graph has no wrapping issues
plt.figure(7)
nieuw = np.array([angle_between(etoh[i][0], etoh[i][1], etoha[i][0], etoha[i][1])
for i in range(len(etoh))])
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist(nieuw, bins=20)
plt.title('ZEN+AZ Old-New Error (equatorial_to_zenithazimuth)')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
# Make figs hor - > eq
plt.figure(4)
plt.suptitle('RA/DEC correlation in rads (horizontal_to_equatorial)')
altrange = [-0.5 * np.pi, 0.5 * np.pi]
plt.subplot(211)
plt.title('Declination')
plt.axis(altrange * 2)
plt.xlabel('New (Astropy)')
plt.ylabel('Old')
# Make figure and add 1:1 trendline
plt.plot([co[1] for co in htoea], [co[1] for co in htoe], 'r.', altrange, straight(altrange), '-')
plt.subplot(212)
plt.title('Right Ascension')
azrange = [0, 2 * np.pi]
plt.axis(azrange * 2)
plt.xlabel('New (Astropy)')
plt.ylabel('Old')
# Make figure and add 1:1 trendline
plt.plot([co[0] for co in htoea], [co[0] for co in htoe], 'b.', azrange, straight(azrange), '-')
plt.tight_layout() # Prevent titles merging
plt.subplots_adjust(top=0.85)
# Make histogram of differences
plt.figure(5)
# Take diff. and convert to arcsec
nieuw = (np.array(htoe) - np.array(htoea))
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist([i[1] for i in nieuw], bins=20)
plt.title('Declination Old-New Error (horizontal_to_equatorial)')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
plt.figure(6)
# Take diff. and convert to arcsec
nieuw = (np.array(htoe) - np.array(htoea))
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist([i[0] for i in nieuw], bins=20)
plt.title('Right Ascension Old-New Error (horizontal_to_equatorial)')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
# Make histogram of differences using the absolute distance in arcsec
# this graph has no wrapping issues
plt.figure(8)
nieuw = np.array([angle_between_horizontal(htoe[i][0], htoe[i][1], htoea[i][0], htoea[i][1])
for i in range(len(htoe))])
# Take diff. and convert to arcsec
nieuw /= 2 / np.pi * 360 * 3600
plt.hist(nieuw, bins=20)
plt.title('RA+DEC Old-New Error (horizontal_to_equatorial)')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
plt.show()
return
def oldvsnew_diagram():
"""
Visual accuracy comparisons of old and new transformations.
Compares the correlations between the transformations:
equatorial_to_horizontal and equatorial_to_zenith_azimuth_astropy
horizontal_to_equatorial and horizontal_to_zenith_azimuth_astropy
Makes a histogram of the error differences
between these two functions as well.
The errors seem to be in the order of 1000 arcsec
:return: None
Ethan van Woerkom is responsible for the benchmarking functions;
refer to him for when something is unclear
"""
# make random frames, in correct angle range and from utc time 2000-2020
frames = []
# boxes for the four different transformation results
etoha = []
etoh = []
htoe = []
htoea = []
straight = lambda x: x # straight trendline function
# Create the data sets for eq to az
for i in range(100):
frames.append(
(r.uniform(-90,
90), r.uniform(-180,
180), r.randint(946684800, 1577836800),
r.uniform(0, 2 * np.pi), r.uniform(-0.5 * np.pi, 0.5 * np.pi)))
for i in frames:
etoha.append(
celestial.equatorial_to_zenithazimuth_astropy(
i[0], i[1], i[2], [(i[3], i[4])])[0])
etoh.append(
celestial.equatorial_to_zenithazimuth(i[0], i[1],
clock.utc_to_gps(i[2]), i[3],
i[4]))
# Data sets for hor to eq
for i in frames:
htoe.append(
celestial.horizontal_to_equatorial(
i[0],
clock.utc_to_lst(datetime.datetime.utcfromtimestamp(i[2]),
i[1]), i[4], i[3]))
htoea.extend(
celestial.horizontal_to_equatorial_astropy(i[0], i[1], i[2],
[(i[3], i[4])]))
# Make figs eq -> zenaz
plt.figure(1)
plt.suptitle('Zen/Az correlation in rads (equatorial_to_zenithazimuth)')
zenrange = [0, np.pi]
plt.subplot(211)
plt.title('Zenith')
plt.axis(zenrange * 2)
plt.xlabel('New (Astropy)')
plt.ylabel('Old')
# Make figure and add 1:1 trendline
plt.plot([co[0] for co in etoha], [co[0] for co in etoh], 'r.', zenrange,
straight(zenrange), '-')
plt.subplot(212)
plt.title('Azimuth')
azrange = [-np.pi, np.pi]
plt.axis(azrange * 2)
plt.xlabel('New (Astropy)')
plt.ylabel('Old')
# Make figure and add 1:1 trendline
plt.plot([co[1] for co in etoha], [co[1] for co in etoh], 'b.', azrange,
straight(azrange), '-')
plt.tight_layout() # Prevent titles merging
plt.subplots_adjust(top=0.85)
# Make histogram of differences
plt.figure(2)
# Take diff. and convert to arcsec
nieuw = (np.array(etoh) - np.array(etoha))
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist([i[0] for i in nieuw], bins=20)
plt.title('Zenith Old-New Error (equatorial_to_zenithazimuth)')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
plt.figure(3)
plt.hist([i[1] for i in nieuw], bins=20)
plt.title('Azimuth Old-New Error (equatorial_to_zenithazimuth)')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
# Make histogram of differences using the absolute distance in arcsec
# this graph has no wrapping issues
plt.figure(7)
nieuw = np.array([
angle_between(etoh[i][0], etoh[i][1], etoha[i][0], etoha[i][1])
for i in range(len(etoh))
])
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist(nieuw, bins=20)
plt.title('ZEN+AZ Old-New Error (equatorial_to_zenithazimuth)')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
# Make figs hor - > eq
plt.figure(4)
plt.suptitle('RA/DEC correlation in rads (horizontal_to_equatorial)')
altrange = [-0.5 * np.pi, 0.5 * np.pi]
plt.subplot(211)
plt.title('Declination')
plt.axis(altrange * 2)
plt.xlabel('New (Astropy)')
plt.ylabel('Old')
# Make figure and add 1:1 trendline
plt.plot([co[1] for co in htoea], [co[1] for co in htoe], 'r.', altrange,
straight(altrange), '-')
plt.subplot(212)
plt.title('Right Ascension')
azrange = [0, 2 * np.pi]
plt.axis(azrange * 2)
plt.xlabel('New (Astropy)')
plt.ylabel('Old')
# Make figure and add 1:1 trendline
plt.plot([co[0] for co in htoea], [co[0] for co in htoe], 'b.', azrange,
straight(azrange), '-')
plt.tight_layout() # Prevent titles merging
plt.subplots_adjust(top=0.85)
# Make histogram of differences
plt.figure(5)
# Take diff. and convert to arcsec
nieuw = (np.array(htoe) - np.array(htoea))
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist([i[1] for i in nieuw], bins=20)
plt.title('Declination Old-New Error (horizontal_to_equatorial)')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
plt.figure(6)
# Take diff. and convert to arcsec
nieuw = (np.array(htoe) - np.array(htoea))
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist([i[0] for i in nieuw], bins=20)
plt.title('Right Ascension Old-New Error (horizontal_to_equatorial)')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
# Make histogram of differences using the absolute distance in arcsec
# this graph has no wrapping issues
plt.figure(8)
nieuw = np.array([
angle_between_horizontal(htoe[i][0], htoe[i][1], htoea[i][0],
htoea[i][1]) for i in range(len(htoe))
])
# Take diff. and convert to arcsec
nieuw = nieuw / 2 / np.pi * 360 * 3600
plt.hist(nieuw, bins=20)
plt.title('RA+DEC Old-New Error (horizontal_to_equatorial)')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
plt.show()
return
