def blend(color1: Color, color2: Color) -> Color:
"""Blends two colors together
Args:
color1 (:class:`~pigment.Color`): The first color
color2 (:class:`~pigment.Color`): The second color
Returns:
:class:`~pigment.Color`
"""
colors = (color1.rgb, color2.rgb)
return Color(*(round(sqrt(average([c[i]**2 for c in colors])))
for i in range(3)))
def check(self, i1: float, i2: float, exp: float):
"""Checks the inputs for a case with an expected output and prints a helpful message upon failure."""
average_found = average(i1, i2)
self.assertEqual(average_found, exp, f"Error: Average of {i1} and {i2} was found to be {average_found}, not {exp}")
def test_average_six(self):
self.check(-6, 6, 0)
self.assertEqual(average(-6, 6), 0)
def test_average(values, expected):
result = average(*values)
assert result == approx(expected)
assert type(result) == type(expected)
def test_average_one_value(value):
result = average(value)
assert result == approx(value)
assert type(result) == type(value)
def test_average_no_values():
with raises(ZeroDivisionError):
average()
def record_pointing(d, s, l, b, point, file_name='raw/'+time.strftime("%m-%d-%Y_%H%M%S"),
int_time=150, repoint_freq=30):
"""Records data from a point on the sky for a specified integration time.
Spectra for an observation at two different LO frequencies and a separate
10 second observation with the noise diode on are saved in the specified
files.
Args:
d (dish.Dish): an interface to the Leuschner dish
s (dish_synth.Synth): an interface to the synthesizer used to set the LO
frequency
file_name (String, optional): file name prefix to save the data
int_time (float, optional): integration time (in seconds).
"""
logger = logging.getLogger('leuschner')
logger.debug('Recording data')
status = 0
# lets us keep data from this pointing in unique directory,
# since each time we point we will have different noise/background spectrums
record_id = time.strftime("%m-%d-%Y_%H%M%S")
# Compute number of spectra to record (integration time/3)
num_spec = int(int_time*3)
num_spec_noise = 5 * 3
OBS.date = ephem.now()
point.compute(OBS)
d.point(np.rad2deg(point.alt), np.rad2deg(point.az))
# Take measurement with noise diode off at the higher LO frequency (ON frequency)
s.set_freq(LO_ON)
s.set_amp(10.0)
d.noise_off()
try:
takespec.takeSpec(file_name+'_ON', numSpec=num_spec)
except IOError:
logger.error('%s not saved or averaged.' % (file_name+'_ON'))
status = -1
else:
# Only want to average if the takespec was successful!
averager.average(file_name+'_ON0.log', lo=LO_ON, l=l, b=b, record_id=record_id)
# Take 10 second measurement with the noise diode on at the ON frequency
d.noise_on()
try:
takespec.takeSpec(file_name+'_ON_noise', numSpec=num_spec_noise)
except IOError:
logger.error('%s not saved or averaged.' % (file_name+'_ON_noise'))
status = -1
else:
averager.average(file_name+'_ON_noise0.log', lo=LO_ON, l=l, b=b, record_id=record_id, noise=True)
# repoint for the second half of the measurement
OBS.date = ephem.now()
point.compute(OBS)
d.point(np.rad2deg(point.alt), np.rad2deg(point.az))
# Take 10 second measurement with the noise diode on at the OFF frequency
s.set_freq(LO_OFF)
s.set_amp(10.0)
try:
takespec.takeSpec(file_name+'_OFF_noise', numSpec=num_spec_noise)
except IOError:
logger.error('%s not saved or averaged.' % (file_name+'_OFF_noise'))
status = -1
else:
averager.average(file_name+'_OFF_noise0.log', lo=LO_OFF, l=l, b=b, record_id=record_id, noise=True)
d.noise_off()
# Take measurement with noise diode off at the lower LO frequency (OFF frequency)
s.set_freq(LO_OFF)
s.set_amp(10.0)
d.noise_off()
try:
takespec.takeSpec(file_name+'_OFF', numSpec=num_spec)
except IOError:
logger.error('%s not saved or averaged.' % (file_name+'_OFF'))
status = -1
else:
averager.average(file_name+'_OFF0.log', lo=LO_OFF, l=l, b=b, record_id=record_id)
logger.debug('Finished recording data')
print 'Print Stat'
print stat
print 'Print Syst names'
trimsnames = map(str.strip, snames)
print trimsnames
#initialization (optional information)
averager.avin.initvariables()
averager.avin.setoutputfolder('./TOutP')
averager.avin.initeration = 5
averager.avin.setsnames(snames)
#perform averaging
dataAv, statAv, systAv = averager.average(data, stat, syst)
#print output information
print averager.avout.pulldata
print averager.avout.pullsyst
print averager.avout.shiftsyst
print averager.avout.squeezesyst
print averager.avout.chi2
print averager.avout.ndof
#plotting
# Averaged data
# rotate initial arrays of data and stat uncertainty