def test_dec2dms(self):
self.assertEqual(dms_ex, dec2dms(dec_ex))
self.assertEqual(-dms_ex, dec2dms(-dec_ex))
def reducesetup(obslist, strict=False, zerodist=False, meanmulti=False):
"""
Takes a list of Observations from one setup and
means together FL, FR pairs of Observations.
:param obslist: List of Observations (i.e. from one InstSetup)
:param strict: If True, all single-face Obs are ignored. If False, all
single-face Obs are included and converted to Face Left
:param zerodist: If True, Obs with Slope Distance of Zero are included.
If False, these are ignored
:param meanmulti: If True, multiple rounds of observations are reduced
to a single FL-sense Observation
:return: a reduced list of Observations
"""
# Remove obs with sd_obs == 0
if not zerodist:
for ob in obslist:
if ob.sd_obs == 0:
obslist.remove(ob)
# Group obs numbers by to_id
uniqueto = []
for ob in obslist:
uniqueto.append(ob.to_id)
uniqueto = list(set(uniqueto))
# Sort Obs by to_id and face
meanedobs = []
for unique_id in uniqueto:
fl_list = []
fr_list = []
for ob in obslist:
if ob.to_id == unique_id and ob.face == 'FL':
fl_list.append(ob)
elif ob.to_id == unique_id and ob.face == 'FR':
fr_list.append(ob)
elif ob.to_id != unique_id and (ob.face == 'FL' or ob.face == 'FR'):
pass
else:
raise ValueError('Invalid Face')
obsdict = {unique_id: {'FL': fl_list, 'FR': fr_list}}
# Group Obs into FL, FR pairs and mean (Remove all non-paired obs)
if strict:
for key in obsdict:
pairedlist = list(zip(obsdict[key]['FL'], obsdict[key]['FR']))
for pair in pairedlist:
meanob = meanfaces(pair[0], pair[1])
meanedobs.append(meanob)
# Group Obs into FL, FR pairs and mean (Keep all non-paired obs)
elif not strict:
for key in obsdict:
pairedlist = list(itertools.zip_longest(obsdict[key]['FL'], obsdict[key]['FR'], fillvalue=None))
for pair in pairedlist:
meanob = meanfaces(pair[0], pair[1])
meanedobs.append(meanob)
# Mean multiple repeated measurements into a single FL observation
if meanmulti:
multiob = []
to_ids = set([i.to_id for i in meanedobs])
for id in to_ids:
matchedobs = []
for ob in meanedobs:
if ob.to_id == id:
matchedobs.append(ob)
ob1 = matchedobs[0]
repeat_hz = [ob.hz_obs.dec() for ob in matchedobs]
repeat_hz = sorted(repeat_hz)
repeat_va = [ob.va_obs.dec() for ob in matchedobs]
repeat_sd = [ob.sd_obs for ob in matchedobs]
# Finds where Horizontal Obseravtions are either side of 360, converts those on 360 side to negative
hz_diff = [j - i for i, j in zip(repeat_hz[:-1], repeat_hz[1:])]
bigjump = 1e100
for num, i in enumerate(hz_diff):
if i > 180:
bigjump = num
for num, ob in enumerate(repeat_hz):
if num > bigjump:
repeat_hz[num] = repeat_hz[num] - 360
# Mean Repeated Observations
mean_hz = mean(repeat_hz)
if mean_hz < 0:
mean_hz += 360
mean_va = mean(repeat_va)
mean_sd = mean(repeat_sd)
# Compute Standard Deviations for Observations
if len(repeat_hz) > 2:
hz_stdev = stdev(repeat_hz)
else:
hz_stdev = 0.0
if len(repeat_va) > 2:
va_stdev = stdev(repeat_va)
else:
va_stdev = 0.0
if len(repeat_sd) > 2:
sd_stdev = stdev(repeat_sd)
else:
sd_stdev = 0.0
# Compute number of rounds of observations completed
sum_rounds = 0
for ob in matchedobs:
sum_rounds += ob.rounds
# Output Meaned Observation
multiob.append(Observation(ob1.from_id,
id,
ob1.inst_height,
ob1.target_height,
ob1.face,
sum_rounds,
dec2dms(mean_hz),
dd2sec(hz_stdev),
dec2dms(mean_va),
dd2sec(va_stdev),
mean_sd,
sd_stdev))
meanedobs = multiob
# Order list of meaned obs
sorted_meanedobs = sorted(meanedobs, key=operator.attrgetter('hz_obs'))
return sorted_meanedobs