def test_pyephem_htoea(self):
""" Check celestial.horizontal_to_equatorial_astropy """
# This is the transform inputs
eq = [(-39.34633914878846, -112.2277168069694, 1295503840,
3.8662384455822716, -0.31222454326513827),
(53.13143508448587, -49.24074935964933, 985619982,
3.901575896592809, -0.3926720112815971),
(48.02031016860923, -157.4023812557098, 1126251396,
3.366278312183976, -1.3610394240813288)]
# result of pyephem hor->eq/zenaz-> eq
efemeq = [(5.620508199785029, -0.3651173667585858),
(5.244630787139936, -0.7866376569183651),
(2.276751381056623, -1.0406498066785745)]
htoea_test = []
# Produce horizontal_to_equatorial_astropy results
for latitude, longitude, gps, az, alt in eq:
result = celestial.horizontal_to_equatorial_astropy(
latitude, longitude, gps, [(az, alt)])
htoea_test.extend(result)
# Check if all inputs are correct
# Test horizontal_to_equatorial_astropy
np.testing.assert_almost_equal(efemeq, htoea_test, 4)
def test_pyephem_htoea(self):
""" Check celestial.horizontal_to_equatorial_astropy """
# This is the transform inputs
eq = [(-39.34633914878846, -112.2277168069694, 1295503840,
3.8662384455822716, -0.31222454326513827),
(53.13143508448587, -49.24074935964933, 985619982,
3.901575896592809, -0.3926720112815971),
(48.02031016860923, -157.4023812557098, 1126251396,
3.366278312183976, -1.3610394240813288)]
# result of pyephem hor->eq/zenaz-> eq
efemeq = [(5.620508199785029, -0.3651173667585858),
(5.244630787139936, -0.7866376569183651),
(2.276751381056623, -1.0406498066785745)]
htoea_test = []
# Produce horizontal_to_equatorial_astropy results
for latitude, longitude, gps, az, alt in eq:
result = celestial.horizontal_to_equatorial_astropy(
latitude, longitude, gps, [(az, alt)])
htoea_test.extend(result)
# Check if all inputs are correct
# Test horizontal_to_equatorial_astropy
np.testing.assert_almost_equal(efemeq, htoea_test, 4)
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 pyephem_comp():
"""
This function compares the values from transformations done by our
new astropy functions with the pyephem numbers. It generates
correlation graphs between the new and old functions
and histograms of the frequency of errors. Most errors do not much
exceed 10 arcsec. There is complete correlation
i.e. visually all points are on the same 1:1 line.
These comparisons are done on the basis of 100 randomly generated
points
:return: None
Ethan van Woerkom is responsible for the benchmarking functions;
refer to him for when something is unclear
"""
# Set up randoms equatorial J2000 bodies
# that we will convert the RAs/Decs of.
eq = [] # random frames to use
for i in range(100):
eq.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)))
efemeq = [] # store pyephem transformations to equatorial
altaz = [] # store pyephem transformations to altaz (horizontal)
htoea = [] # store astropy transformations to equatorial
etoha = [] # store astropy transformations to horizontal (altaz)
for latitude, longitude, utc, ra, dec in eq:
# Calculate altaz
# Set observer for each case
obs = ephem.Observer()
obs.lat = str(latitude)
obs.lon = str(longitude)
obs.date = datetime.datetime.utcfromtimestamp(utc)
obs.pressure = 0 # Crucial to prevent refraction correction!
# Set body for each case
coord = ephem.FixedBody()
coord._ra = ra
coord._dec = dec
# Do calculation and add to list, it is necessary
# to force the coords into radians
coord.compute(obs)
altaz.append((float(coord.az), float(coord.alt)))
# Also calculate efemeq using eq
result = obs.radec_of(ra, dec) # This is of course not ra,dec but
# actually az, alt.
efemeq.append((float(result[0]), float(result[1])))
# Produce horizontal_to_equatorial_astropy results
for latitude, longitude, utc, az, alt in eq:
result = celestial.horizontal_to_equatorial_astropy(latitude, longitude, utc, [(az, alt)])
htoea.extend(result)
# Produce equatorial_to_horizontal_astropy results
for latitude, longitude, utc, ra, dec in eq:
result = celestial.equatorial_to_horizontal_astropy(latitude, longitude, utc, [(ra, dec)])
etoha.extend(result)
altdecrange = [-0.5 * np.pi, 0.5 * np.pi]
azrarange = [0, 2 * np.pi]
plt.figure(1)
plt.suptitle('RA/Dec correlation Altaz->(Astropy/Pyephem)->RA,DEC')
# Create RA correlation subplot
plt.subplot(211)
plt.title('RA')
plt.axis(azrarange * 2)
plt.xlabel('Pyephem RA (rad)')
plt.ylabel('Astropy RA (rad)')
# Plot RA correlation and trendline
plt.plot([co[0] for co in efemeq], [co[0] for co in htoea], 'b.', azrarange, azrarange, '-')
# DEC correlation subplot
plt.subplot(212)
plt.title('DEC')
plt.axis(altdecrange*2)
plt.xlabel('Pyephem DEC (rad)')
plt.ylabel('Astropy DEC (rad)')
# Plot DEC correlation and trendline
plt.plot([co[1] for co in efemeq], [co[1] for co in htoea], 'r.', altdecrange, altdecrange, '-')
# Formatting
plt.tight_layout()
plt.subplots_adjust(top=0.85)
# Make RA error histogram
plt.figure(2)
plt.title('RA Error Altaz->(Astropy/Pyephem)->RA,DEC')
nieuw = (np.array(htoea) - np.array(efemeq))
# Get differences in arcsec
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist([co[0] for co in nieuw], bins=20)
plt.ylabel('Counts')
plt.xlabel('Error (arcsec)')
# Make DEC error histogram
plt.figure(3)
plt.title('DEC Error Altaz->(Astropy/Pyephem)->RA,DEC')
plt.hist([co[1] for co in nieuw], bins=20)
plt.ylabel('Counts')
plt.xlabel('Error (arcsec)')
# Altaz comparison plot
plt.figure(4)
plt.suptitle('Alt/Az correlation RA,DEC->(pyephem/astropy)->Altaz')
# Altitude
plt.subplot(211)
plt.title('Altitude')
plt.axis(altdecrange*2)
plt.xlabel('Pyephem Altitude (rad)')
plt.ylabel('Astropy Altitude (rad')
# Plot with trendline
plt.plot([co[1] for co in altaz], [co[1] for co in etoha], 'b.', altdecrange, altdecrange, '-')
# Azimuth
plt.subplot(212)
plt.title('Azimuth')
plt.axis(azrarange*2)
plt.xlabel('Pyephem Azimuth (rad)')
plt.ylabel('Astropy Azimuth (rad)')
plt.plot([co[0] for co in altaz], [co[0] for co in etoha], 'r.', azrarange, azrarange, '-')
# Formatting
plt.tight_layout()
plt.subplots_adjust(top=0.85)
# Alt error histogram
plt.figure(5)
plt.title('Altitude Error RA,DEC->(pyephem/astropy)->Altaz')
nieuw = (np.array(etoha) - np.array(altaz))
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist([co[1] for co in nieuw], bins=20)
plt.ylabel('Counts')
plt.xlabel('Error (arcsec)')
# Az error histogram
plt.figure(6)
plt.title('Azimuth Error RA,DEC->(pyephem/astropy)->Altaz')
plt.hist([co[0] for co in nieuw], bins=20)
plt.ylabel('Counts')
plt.xlabel('Error (arcsec)')
# Make histograms of differences using the absolute distance in arcsec
# these graphs have no wrapping issues
plt.figure(7)
nieuw = np.array([angle_between_horizontal(altaz[i][0], altaz[i][1], etoha[i][0], etoha[i][1])
for i in range(len(etoha))])
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist(nieuw, bins=20)
plt.title('Alt+Azi Error RA,DEC->(pyephem/astropy)->Altaz')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
plt.figure(8)
nieuw = np.array([angle_between_horizontal(efemeq[i][0], efemeq[i][1], htoea[i][0], htoea[i][1])
for i in range(len(htoea))])
# Take difference and convert to arcsec
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist(nieuw, bins=20)
plt.title('RA+DEC Error Altaz->(pyephem/astropy)->RA,DEC')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
# Done; output
plt.show()
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
def pyephem_comp():
"""
This function compares the values from transformations done by our
new astropy functions with the pyephem numbers. It generates
correlation graphs between the new and old functions
and histograms of the frequency of errors. Most errors do not much
exceed 10 arcsec. There is complete correlation
i.e. visually all points are on the same 1:1 line.
These comparisons are done on the basis of 100 randomly generated
points
:return: None
Ethan van Woerkom is responsible for the benchmarking functions;
refer to him for when something is unclear
"""
# Set up randoms equatorial J2000 bodies
# that we will convert the RAs/Decs of.
eq = [] # random frames to use
for i in range(100):
eq.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)))
efemeq = [] # store pyephem transformations to equatorial
altaz = [] # store pyephem transformations to altaz (horizontal)
htoea = [] # store astropy transformations to equatorial
etoha = [] # store astropy transformations to horizontal (altaz)
for latitude, longitude, utc, ra, dec in eq:
# Calculate altaz
# Set observer for each case
obs = ephem.Observer()
obs.lat = str(latitude)
obs.lon = str(longitude)
obs.date = datetime.datetime.utcfromtimestamp(utc)
obs.pressure = 0 # Crucial to prevent refraction correction!
# Set body for each case
coord = ephem.FixedBody()
coord._ra = ra
coord._dec = dec
# Do calculation and add to list, it is necessary
# to force the coords into radians
coord.compute(obs)
altaz.append((float(coord.az), float(coord.alt)))
# Also calculate efemeq using eq
result = obs.radec_of(ra, dec) # This is of course not ra,dec but
# actually az, alt.
efemeq.append((float(result[0]), float(result[1])))
# Produce horizontal_to_equatorial_astropy results
for latitude, longitude, utc, az, alt in eq:
result = celestial.horizontal_to_equatorial_astropy(
latitude, longitude, utc, [(az, alt)])
htoea.extend(result)
# Produce equatorial_to_horizontal_astropy results
for latitude, longitude, utc, ra, dec in eq:
result = celestial.equatorial_to_horizontal_astropy(
latitude, longitude, utc, [(ra, dec)])
etoha.extend(result)
altdecrange = [-0.5 * np.pi, 0.5 * np.pi]
azrarange = [0, 2 * np.pi]
plt.figure(1)
plt.suptitle('RA/Dec correlation Altaz->(Astropy/Pyephem)->RA,DEC')
# Create RA correlation subplot
plt.subplot(211)
plt.title('RA')
plt.axis(azrarange * 2)
plt.xlabel('Pyephem RA (rad)')
plt.ylabel('Astropy RA (rad)')
# Plot RA correlation and trendline
plt.plot([co[0] for co in efemeq], [co[0] for co in htoea], 'b.',
azrarange, azrarange, '-')
# DEC correlation subplot
plt.subplot(212)
plt.title('DEC')
plt.axis(altdecrange * 2)
plt.xlabel('Pyephem DEC (rad)')
plt.ylabel('Astropy DEC (rad)')
# Plot DEC correlation and trendline
plt.plot([co[1] for co in efemeq], [co[1] for co in htoea], 'r.',
altdecrange, altdecrange, '-')
# Formatting
plt.tight_layout()
plt.subplots_adjust(top=0.85)
# Make RA error histogram
plt.figure(2)
plt.title('RA Error Altaz->(Astropy/Pyephem)->RA,DEC')
nieuw = (np.array(htoea) - np.array(efemeq))
# Get differences in arcsec
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist([co[0] for co in nieuw], bins=20)
plt.ylabel('Counts')
plt.xlabel('Error (arcsec)')
# Make DEC error histogram
plt.figure(3)
plt.title('DEC Error Altaz->(Astropy/Pyephem)->RA,DEC')
plt.hist([co[1] for co in nieuw], bins=20)
plt.ylabel('Counts')
plt.xlabel('Error (arcsec)')
# Altaz comparison plot
plt.figure(4)
plt.suptitle('Alt/Az correlation RA,DEC->(pyephem/astropy)->Altaz')
# Altitude
plt.subplot(211)
plt.title('Altitude')
plt.axis(altdecrange * 2)
plt.xlabel('Pyephem Altitude (rad)')
plt.ylabel('Astropy Altitude (rad')
# Plot with trendline
plt.plot([co[1] for co in altaz], [co[1] for co in etoha], 'b.',
altdecrange, altdecrange, '-')
# Azimuth
plt.subplot(212)
plt.title('Azimuth')
plt.axis(azrarange * 2)
plt.xlabel('Pyephem Azimuth (rad)')
plt.ylabel('Astropy Azimuth (rad)')
plt.plot([co[0] for co in altaz], [co[0] for co in etoha], 'r.',
azrarange, azrarange, '-')
# Formatting
plt.tight_layout()
plt.subplots_adjust(top=0.85)
# Alt error histogram
plt.figure(5)
plt.title('Altitude Error RA,DEC->(pyephem/astropy)->Altaz')
nieuw = (np.array(etoha) - np.array(altaz))
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist([co[1] for co in nieuw], bins=20)
plt.ylabel('Counts')
plt.xlabel('Error (arcsec)')
# Az error histogram
plt.figure(6)
plt.title('Azimuth Error RA,DEC->(pyephem/astropy)->Altaz')
plt.hist([co[0] for co in nieuw], bins=20)
plt.ylabel('Counts')
plt.xlabel('Error (arcsec)')
# Make histograms of differences using the absolute distance in arcsec
# these graphs have no wrapping issues
plt.figure(7)
nieuw = np.array([
angle_between_horizontal(altaz[i][0], altaz[i][1], etoha[i][0],
etoha[i][1]) for i in range(len(etoha))
])
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist(nieuw, bins=20)
plt.title('Alt+Azi Error RA,DEC->(pyephem/astropy)->Altaz')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
plt.figure(8)
nieuw = np.array([
angle_between_horizontal(efemeq[i][0], efemeq[i][1], htoea[i][0],
htoea[i][1]) for i in range(len(htoea))
])
# Take difference and convert to arcsec
nieuw *= 360 * 3600 / (2 * np.pi)
plt.hist(nieuw, bins=20)
plt.title('RA+DEC Error Altaz->(pyephem/astropy)->RA,DEC')
plt.xlabel('Error (arcsec)')
plt.ylabel('Counts')
# Done; output
plt.show()