def JPL_2014_May_light_blackbody_temperature(directory):
"""
Parameter directory is a string that is the path to the unzipped
contents of the file Log0522JAlSKIP20_bbT_sweep.zip, which is
posted on the SKIP wiki.
Return a dictionary with keys that are integers from 0 through 13
and values that are lists of 14 Resonators fitted to frequency
sweeps taken at blackbody temperatures from 4.2 K to 40 K in
ascending order. Each list contains data for a single detector.
The fits must include cable delay as a free parameter because it
has not been removed.
The frequency data in the files is in Hz and is converted to MHz
here to match our data.
The original data directory contains 150 sweeps, with indices
ranging from 203 through 352, taken at ten different temperatures
between 40 K and 4.2 K. There are 14 working resonators. Each
group of sweeps contains one sweep of the entire frequency range
then 14 sweeps of individual resonators in order of increasing
resonance frequency. Sweep 203 thus contains a sweep of the entire
band at the highest temperature of 40 K, and sweep 352 covers the
resonator with highest resonance frequency at the lowest
temperature of 4.2 K.
Note that each list in the returned dictionary contains sweeps in
order of increasing black body temperature.
"""
log = path.join(directory, 'Log0522JAlSKIP20_bbT_sweep.txt')
sweeps_per_group = 15
# Each element of sweep_number is the XX in trXX.txt
sweep_number, readout_power_dBm, bb_temp_K = np.loadtxt(log,
usecols=(0, 5, 9),
delimiter=' ',
skiprows=15,
unpack=True,
converters={0: lambda s: path.splitext(s)[0][2:]})
sweeps = read_all_sweeps(directory)
first_sweep = min(sweeps.keys())
resonators = dict([(n, []) for n in range(sweeps_per_group - 1)])
for n in range(len(sweeps)):
if (n % sweeps_per_group) == 0: # skip the first sweep in each group
continue
else:
r = Resonator(sweeps[n + first_sweep][0] / 1e6, sweeps[n + first_sweep][1], # Hz to MHz
guess = delayed_generic_guess, model = delayed_generic_s21)
r.T_bath = 0.2 # The device temperature, as listed in the header.
r.T_bb = bb_temp_K[n]
r.P_readout = readout_power_dBm[n]
resonators[(n % sweeps_per_group) - 1].insert(0, r) # Insert in ascending order
return resonators
def JPL_2013_August_dark_bath_temperature(directory):
"""
Return a list of Resonators from Peter's temperature sweeps of one
resonance.
"""
log = path.join(directory, 'Log0829LSKIP_T_sweep.txt')
numbers, temp_list = np.loadtxt(log,
usecols=(0, 9),
delimiter=' ',
skiprows=12,
unpack=True,
converters={0: lambda s: path.splitext(s)[0][2:]}) # extract XX from trXX.txt
sweeps = read_all_sweeps(directory)
resonators = []
for n, T_bath in zip(numbers, temp_list):
r = Resonator(sweeps[n][0], sweeps[n][1], guess = generic_guess, model = generic_s21)
r.T_bath = T_bath
resonators.append(r)
return resonators
def fit_sweep_data(sweep_data,
model=bifurcation_s21,
guess=bifurcation_guess,
delay_estimate=0):
resonators = []
for i in np.unique(sweep_data.sweep_indexes):
f, s21, errors = sweep_data.select_index(i)
s21 *= np.exp(2j * np.pi * delay_estimate * f)
resonators.append(
Resonator(f, s21, errors=errors, model=model, guess=guess))
return sorted(resonators, key=lambda r: r.f_0)
