def record_sweep(roach, center_frequencies, offset_frequencies, attenuation, n_samples, suffix, interactive=False):
n_channels = center_frequencies.size
df = data_file.DataFile(suffix=suffix)
print("Writing data to " + df.filename)
print("Setting DAC attenuator to {:.1f} dB".format(attenuation))
roach.set_dac_attenuator(attenuation)
print("Sweep memory usage is {:.1f} MB of {:.1f} MB capacity.".format(
memory_usage_bytes(offset_frequencies.shape[0], n_samples) / 2 ** 20, EFFECTIVE_DRAM_CAPACITY / 2 ** 20))
measured_frequencies = sweeps.prepare_sweep(roach, center_frequencies, offset_frequencies, n_samples)
roach._sync()
time.sleep(0.2)
df.log_hw_state(roach)
if interactive:
raw_input("Hit enter to begin recording frequency sweep.")
else:
print("Recording frequency sweep.")
sweep_start_time = time.time()
sweep_data = sweeps.do_prepared_sweep(roach, nchan_per_step=n_channels, reads_per_step=8)
print("Elapsed time {:.0f} seconds. Writing to disk.".format(time.time() - sweep_start_time))
df.add_sweep(sweep_data)
df.sync()
resonators = fit_sweep_data(sweep_data)
fit_f0s = np.array([r.f_0 for r in resonators])
print("Initial frequencies in MHz are " + ', '.join(['{:.3f}'.format(f0) for f0 in center_frequencies]))
print("initial - fit [Hz]: " +
', '.join(['{:.0f}'.format(1e6 * delta_f) for delta_f in center_frequencies - fit_f0s]))
df.nc.close()
return df.filename, resonators
def record_sweeps_on_off(roach, nominal_frequencies, attenuation, n_samples, suffix):
df = data_file.DataFile(suffix=suffix)
roach.set_dac_attenuator(attenuation)
measured_frequencies = roach.set_tone_frequencies(nominal_frequencies, nsamp=n_samples)
df.log_hw_state(roach)
raw_input("Hit enter to begin sweep with compressor on.")
start1 = time.time()
sweep_data = sweeps.do_prepared_sweep(roach, nchan_per_step=nominal_frequencies.size, reads_per_step=8)
print("Sweep completed in {:.0f} seconds.".format(time.time() - start1))
df.add_sweep(sweep_data)
df.sync()
raw_input("Hit enter to begin sweep with compressor off.")
start2 = time.time()
sweep_data = sweeps.do_prepared_sweep(roach, nchan_per_step=nominal_frequencies.size, reads_per_step=8)
print("Sweep completed in {:.0f} seconds.".format(time.time() - start2))
df.add_sweep(sweep_data)
df.sync()
df.nc.close()
def sweep(roach, center_frequencies, sample_exponent, offset_frequencies=None, reads_per_step=2, transient_wait=0,
run=lambda: None):
n_samples = 2 ** sample_exponent
if offset_frequencies is None:
frequency_resolution = roach.fs / n_samples
offset_frequencies = frequency_resolution * offset_integers[sample_exponent]
sweeps.prepare_sweep(roach, center_frequencies, offset_frequencies, n_samples)
roach._sync()
time.sleep(transient_wait)
run()
sweep_data = sweeps.do_prepared_sweep(roach, nchan_per_step=len(center_frequencies), reads_per_step=reads_per_step)
return sweep_data
def record_sweeps_on_off(roach, nominal_frequencies, attenuation, n_samples,
suffix):
df = data_file.DataFile(suffix=suffix)
roach.set_dac_attenuator(attenuation)
measured_frequencies = roach.set_tone_frequencies(nominal_frequencies,
nsamp=n_samples)
df.log_hw_state(roach)
raw_input("Hit enter to begin sweep with compressor on.")
start1 = time.time()
sweep_data = sweeps.do_prepared_sweep(
roach, nchan_per_step=nominal_frequencies.size, reads_per_step=8)
print("Sweep completed in {:.0f} seconds.".format(time.time() - start1))
df.add_sweep(sweep_data)
df.sync()
raw_input("Hit enter to begin sweep with compressor off.")
start2 = time.time()
sweep_data = sweeps.do_prepared_sweep(
roach, nchan_per_step=nominal_frequencies.size, reads_per_step=8)
print("Sweep completed in {:.0f} seconds.".format(time.time() - start2))
df.add_sweep(sweep_data)
df.sync()
df.nc.close()
def record_sweep(roach,
center_frequencies,
offset_frequencies,
attenuation,
n_samples,
suffix,
interactive=False):
n_channels = center_frequencies.size
df = data_file.DataFile(suffix=suffix)
print("Writing data to " + df.filename)
print("Setting DAC attenuator to {:.1f} dB".format(attenuation))
roach.set_dac_attenuator(attenuation)
print("Sweep memory usage is {:.1f} MB of {:.1f} MB capacity.".format(
memory_usage_bytes(offset_frequencies.shape[0], n_samples) / 2**20,
EFFECTIVE_DRAM_CAPACITY / 2**20))
measured_frequencies = sweeps.prepare_sweep(roach, center_frequencies,
offset_frequencies, n_samples)
roach._sync()
time.sleep(0.2)
df.log_hw_state(roach)
if interactive:
raw_input("Hit enter to begin recording frequency sweep.")
else:
print("Recording frequency sweep.")
sweep_start_time = time.time()
sweep_data = sweeps.do_prepared_sweep(roach,
nchan_per_step=n_channels,
reads_per_step=8)
print("Elapsed time {:.0f} seconds. Writing to disk.".format(
time.time() - sweep_start_time))
df.add_sweep(sweep_data)
df.sync()
resonators = fit_sweep_data(sweep_data)
fit_f0s = np.array([r.f_0 for r in resonators])
print("Initial frequencies in MHz are " +
', '.join(['{:.3f}'.format(f0) for f0 in center_frequencies]))
print("initial - fit [Hz]: " + ', '.join([
'{:.0f}'.format(1e6 * delta_f)
for delta_f in center_frequencies - fit_f0s
]))
df.nc.close()
return df.filename, resonators
def sweep(roach,
center_frequencies,
sample_exponent,
offset_frequencies=None,
reads_per_step=2,
transient_wait=0,
run=lambda: None):
n_samples = 2**sample_exponent
if offset_frequencies is None:
frequency_resolution = roach.fs / n_samples
offset_frequencies = frequency_resolution * offset_integers[
sample_exponent]
sweeps.prepare_sweep(roach, center_frequencies, offset_frequencies,
n_samples)
roach._sync()
time.sleep(transient_wait)
run()
sweep_data = sweeps.do_prepared_sweep(
roach,
nchan_per_step=len(center_frequencies),
reads_per_step=reads_per_step)
return sweep_data
def mmw_source_sweep_and_stream(df, roach, lockin, approximate_stream_time, overwrite_last, f_mmw_source,
sweep_modulation_rate, stream_modulation_rate, measurement_modulation_rate,
roach_wait=10, lockin_wait=5, verbose=True):
f_sweep_modulation = roach.set_modulation_output(sweep_modulation_rate)
if verbose:
print("Sweep modulation state {}: frequency {:.2f} Hz.".format(sweep_modulation_rate, f_sweep_modulation))
df.log_hw_state(roach)
sweep = sweeps.do_prepared_sweep(roach, nchan_per_step=roach.tone_bins.shape[0], reads_per_step=2)
df.add_sweep(sweep)
df.sync()
f_fit = np.array([r.f_0 for r in fit_sweep_data(sweep)])
f_measurement_modulation = roach.set_modulation_output(measurement_modulation_rate)
f_stream_measured = roach.add_tone_freqs(f_fit, overwrite_last=overwrite_last) # Use this delay for settling
if verbose:
print("Stream tone separations [MHz]: {}".format(np.diff(sorted(f_stream_measured))))
time.sleep(lockin_wait)
x, y, r, theta = lockin.get_data()
if verbose:
print("Lock-in measured {:.4g} V at frequency {:.2f} Hz.".format(x, f_measurement_modulation))
f_stream_modulation = roach.set_modulation_output(stream_modulation_rate)
if verbose:
print("Modulation state {} for {:.0f} second stream: frequency {:.2f} Hz.".format(stream_modulation_rate,
approximate_stream_time,
f_stream_modulation))
# After 2015-05-05, select_fft_bins is no longer necessary since select_bank now selects FFT bins too.
roach.select_bank(roach.fft_bins.shape[0] - 1)
roach._sync()
time.sleep(roach_wait) # The above commands somehow create a transient that takes about 5 seconds to decay.
df.log_hw_state(roach)
start_time = time.time()
stream, addresses = roach.get_data_seconds(approximate_stream_time, pow2=True)
df.add_timestream_data(stream, roach, start_time, mmw_source_freq=f_mmw_source,
mmw_source_modulation_freq=f_stream_modulation, zbd_voltage=x)
df.sync()
return sweep, stream
offsets = offset_bins * 512.0 / nsamp
measured_freqs = sweeps.prepare_sweep(ri,
f0binned,
offsets,
nsamp=nsamp)
print "loaded waveforms in", (time.time() - start), "seconds"
delay = -31.3
print "median delay is ", delay
df = data_file.DataFile(suffix=suffix)
df.nc.mmw_atten_turns = mmw_atten_turns
df.log_hw_state(ri)
sweep_data = sweeps.do_prepared_sweep(ri,
nchan_per_step=atonce,
reads_per_step=2)
df.add_sweep(sweep_data)
meas_cfs = []
idxs = []
for m in range(len(f0s)):
fr, s21, errors = sweep_data.select_by_freq(f0s[m])
thiscf = f0s[m]
s21 = s21 * np.exp(2j * np.pi * delay * fr)
res = fit_best_resonator(
fr, s21, errors=errors) #Resonator(fr,s21,errors=errors)
fmin = fr[np.abs(s21).argmin()]
print "s21 fmin", fmin, "original guess", thiscf, "this fit", res.f_0
if use_fmin:
meas_cfs.append(fmin)
else:
def sweep_fit_timestream(roach,
center_frequencies,
offset_frequencies,
sweep_n_samples,
timestream_n_samples,
attenuation,
suffix,
time_in_seconds,
interactive=False,
coarse_multiplier=3):
df = data_file.DataFile(suffix=suffix)
print("Writing data to " + df.filename)
print("Setting DAC attenuator to {:.1f} dB".format(attenuation))
roach.set_dac_attenuator(attenuation)
print("Sweep memory usage is {:.1f} MB of {:.1f} MB capacity.".format(
memory_usage_bytes(offset_frequencies.shape[0], sweep_n_samples) /
2**20, EFFECTIVE_DRAM_CAPACITY / 2**20))
# Do a preliminary sweep to make sure the main sweeps are centered properly.
sweeps.prepare_sweep(roach, center_frequencies,
coarse_multiplier * offset_frequencies,
sweep_n_samples)
roach._sync()
time.sleep(0.2)
if interactive:
raw_input("Hit enter to record preliminary frequency sweep.")
else:
print("Recording preliminary frequency sweep.")
coarse_sweep_data = sweeps.do_prepared_sweep(
roach, nchan_per_step=center_frequencies.size, reads_per_step=8)
coarse_resonators = fit_sweep_data(coarse_sweep_data)
coarse_f0s = np.array([r.f_0 for r in coarse_resonators])
fine_center_frequencies = round_frequencies(coarse_f0s, roach.fs,
sweep_n_samples)
# Now do the actual sweep and save it.
sweeps.prepare_sweep(roach, fine_center_frequencies, offset_frequencies,
sweep_n_samples)
roach._sync()
time.sleep(0.2)
df.log_hw_state(roach)
if interactive:
raw_input("Hit enter to begin recording frequency sweep.")
else:
print("Recording frequency sweep.")
sweep_start_time = time.time()
sweep_data = sweeps.do_prepared_sweep(
roach, nchan_per_step=center_frequencies.size, reads_per_step=8)
print("Elapsed time {:.0f} seconds. Writing to disk.".format(
time.time() - sweep_start_time))
df.add_sweep(sweep_data)
df.sync()
resonators = fit_sweep_data(sweep_data)
fine_f0s = np.array([r.f_0 for r in resonators])
print("Initial frequencies in MHz are " +
', '.join(['{:.3f}'.format(f0) for f0 in center_frequencies]))
print("initial - fit [Hz]: " + ', '.join([
'{:.0f}'.format(1e6 * delta_f)
for delta_f in center_frequencies - fine_f0s
]))
timestream_measured_frequencies = roach.set_tone_frequencies(
fine_f0s, nsamp=timestream_n_samples)
roach.select_fft_bins(np.arange(roach.tone_bins.shape[1]))
roach._sync()
time.sleep(0.2)
df.log_hw_state(roach)
print("measured - fit [Hz]: " + ', '.join([
'{:.0f}'.format(1e6 * delta_f)
for delta_f in timestream_measured_frequencies - fine_f0s
]))
# This delay was added because the above lines cause some kind of transient signal that takes about three seconds
# to decay. This was showing up at the beginning of the timestreams with interactive=False.
minimum_wait = 5
wait_start_time = time.time()
if interactive:
raw_input(
"Hit enter to begin recording {:.0f} second timestream.".format(
time_in_seconds))
else:
print("Recording {:.0f} second timestream.".format(time_in_seconds))
while time.time() - wait_start_time < minimum_wait:
time.sleep(0.1)
timestream_start_time = time.time()
data, address = roach.get_data_seconds(time_in_seconds,
demod=True,
pow2=True)
print("Elapsed time {:.0f} seconds. Writing to disk.".format(
time.time() - timestream_start_time))
df.add_timestream_data(data, roach, timestream_start_time)
df.sync()
df.nc.close()
return df.filename
def mmw_source_sweep_and_stream(df,
roach,
lockin,
approximate_stream_time,
overwrite_last,
f_mmw_source,
sweep_modulation_rate,
stream_modulation_rate,
measurement_modulation_rate,
roach_wait=10,
lockin_wait=5,
verbose=True):
f_sweep_modulation = roach.set_modulation_output(sweep_modulation_rate)
if verbose:
print("Sweep modulation state {}: frequency {:.2f} Hz.".format(
sweep_modulation_rate, f_sweep_modulation))
df.log_hw_state(roach)
sweep = sweeps.do_prepared_sweep(roach,
nchan_per_step=roach.tone_bins.shape[0],
reads_per_step=2)
df.add_sweep(sweep)
df.sync()
f_fit = np.array([r.f_0 for r in fit_sweep_data(sweep)])
f_measurement_modulation = roach.set_modulation_output(
measurement_modulation_rate)
f_stream_measured = roach.add_tone_freqs(
f_fit, overwrite_last=overwrite_last) # Use this delay for settling
if verbose:
print("Stream tone separations [MHz]: {}".format(
np.diff(sorted(f_stream_measured))))
time.sleep(lockin_wait)
x, y, r, theta = lockin.get_data()
if verbose:
print("Lock-in measured {:.4g} V at frequency {:.2f} Hz.".format(
x, f_measurement_modulation))
f_stream_modulation = roach.set_modulation_output(stream_modulation_rate)
if verbose:
print(
"Modulation state {} for {:.0f} second stream: frequency {:.2f} Hz."
.format(stream_modulation_rate, approximate_stream_time,
f_stream_modulation))
# After 2015-05-05, select_fft_bins is no longer necessary since select_bank now selects FFT bins too.
roach.select_bank(roach.fft_bins.shape[0] - 1)
roach._sync()
time.sleep(
roach_wait
) # The above commands somehow create a transient that takes about 5 seconds to decay.
df.log_hw_state(roach)
start_time = time.time()
stream, addresses = roach.get_data_seconds(approximate_stream_time,
pow2=True)
df.add_timestream_data(stream,
roach,
start_time,
mmw_source_freq=f_mmw_source,
mmw_source_modulation_freq=f_stream_modulation,
zbd_voltage=x)
df.sync()
return sweep, stream
def sweeps_and_streams(f_initial,
attenuations,
suffix='',
coarse_exponent=19,
fine_exponent=21,
long_stream_time=30,
short_stream_time=4,
roach_wait=10):
roach = baseband.RoachBaseband()
f_modulation = roach.set_modulation_output('high')
n_coarse_samples = 2**coarse_exponent
n_fine_samples = 2**fine_exponent
coarse_frequency_resolution = roach.fs / n_coarse_samples
fine_frequency_resolution = roach.fs / n_fine_samples
coarse_offset_integers = offset_integers[coarse_exponent]
fine_offset_integers = offset_integers[fine_exponent]
f_coarse_offset = coarse_frequency_resolution * coarse_offset_integers
f_fine_offset = fine_frequency_resolution * fine_offset_integers
start_time = time.time()
df = data_file.DataFile(suffix=suffix)
maximum_attenuation = max(attenuations)
print(
"Setting DAC attenuator to maximum requested attenuation of {:.1f} dB."
.format(maximum_attenuation))
roach.set_dac_attenuator(maximum_attenuation)
# At the lowest readout power, record a coarse sweep and a short stream
sweeps.prepare_sweep(roach, f_initial, f_coarse_offset, n_coarse_samples)
df.log_hw_state(roach)
coarse_sweep_data = sweeps.do_prepared_sweep(
roach, nchan_per_step=roach.tone_bins.shape[0], reads_per_step=2)
df.add_sweep(coarse_sweep_data)
df.sync()
coarse_f_fit = np.array([r.f_0 for r in fit_sweep_data(coarse_sweep_data)])
print("coarse - initial [Hz]: " + ', '.join(
['{:.0f}'.format(1e6 * diff) for diff in coarse_f_fit - f_initial]))
roach.add_tone_freqs(coarse_f_fit, overwrite_last=True)
roach.select_bank(roach.fft_bins.shape[0] - 1)
roach._sync()
time.sleep(
roach_wait
) # The above commands somehow create a transient that takes about 5 seconds to decay.
df.log_hw_state(roach)
stream_start_time = time.time()
stream, addresses = roach.get_data_seconds(short_stream_time, pow2=True)
df.add_timestream_data(stream,
roach,
stream_start_time,
mmw_source_modulation_freq=f_modulation)
df.sync()
# Use these frequencies for all subsequent sweeps, and add an additional waveform for each stream.
print("\nSetting fine sweep frequencies.")
sweeps.prepare_sweep(roach, coarse_f_fit, f_fine_offset, n_fine_samples)
for k, attenuation in enumerate(attenuations):
print("\nMeasurement {} of {}: DAC attenuator at {:.1f} dB.".format(
k + 1, len(attenuations), attenuation))
roach.set_dac_attenuator(attenuation)
fine_sweep_data = sweeps.do_prepared_sweep(
roach, nchan_per_step=roach.tone_bins.shape[0], reads_per_step=2)
df.add_sweep(fine_sweep_data)
df.sync()
fine_f_fit = np.array([r.f_0 for r in fit_sweep_data(fine_sweep_data)])
print("fine - coarse [Hz]: " + ', '.join([
'{:.0f}'.format(1e6 * diff) for diff in fine_f_fit - coarse_f_fit
]))
f_stream = roach.add_tone_freqs(
coarse_f_fit, overwrite_last=k > 0) # Overwrite after the first
print("stream detuning [ppm]: " + ', '.join(
['{:.0f}'.format(1e6 * x) for x in (f_stream / fine_f_fit - 1)]))
roach.select_bank(roach.fft_bins.shape[0] - 1)
roach._sync()
time.sleep(
roach_wait
) # The above commands somehow create a transient that takes about 5 seconds to decay.
df.log_hw_state(roach)
stream_start_time = time.time()
stream, addresses = roach.get_data_seconds(long_stream_time, pow2=True)
df.add_timestream_data(stream,
roach,
stream_start_time,
mmw_source_modulation_freq=f_modulation)
df.sync()
df.close()
print("Completed in {:.0f} minutes: {}".format(
(time.time() - start_time) / 60, df.filename))
if temp > 0.348:
break
time.sleep(300)
time.sleep(600)
start = time.time()
use_fmin = False
attenlist = [39]
for atten in attenlist:
hittite.off()
print "setting attenuator to",atten
ri.set_dac_attenuator(atten)
measured_freqs = sweeps.prepare_sweep(ri,f0binned,offsets,nsamp=nsamp)
print "loaded waveforms in", (time.time()-start),"seconds"
sweep_data = sweeps.do_prepared_sweep(ri, nchan_per_step=atonce, reads_per_step=4)
orig_sweep_data = sweep_data
meas_cfs = []
idxs = []
delays = []
for m in range(len(f0s)):
fr,s21,errors = sweep_data.select_by_freq(f0s[m])
thiscf = f0s[m]
res = fit_best_resonator(fr[1:-1],s21[1:-1],errors=errors[1:-1]) #Resonator(fr,s21,errors=errors)
delay = res.delay
delays.append(delay)
s21 = s21*np.exp(2j*np.pi*res.delay*fr)
res = fit_best_resonator(fr,s21,errors=errors)
fmin = fr[np.abs(s21).argmin()]
print "s21 fmin", fmin, "original guess",thiscf,"this fit", res.f_0, "delay",delay,"resid delay",res.delay
if use_fmin:
break
time.sleep(300)
time.sleep(600)
start = time.time()
use_fmin = False
attenlist = [39]
for atten in attenlist:
hittite.off()
print "setting attenuator to", atten
ri.set_dac_attenuator(atten)
measured_freqs = sweeps.prepare_sweep(ri, f0binned, offsets, nsamp=nsamp)
print "loaded waveforms in", (time.time() - start), "seconds"
sweep_data = sweeps.do_prepared_sweep(ri,
nchan_per_step=atonce,
reads_per_step=4)
orig_sweep_data = sweep_data
meas_cfs = []
idxs = []
delays = []
for m in range(len(f0s)):
fr, s21, errors = sweep_data.select_by_freq(f0s[m])
thiscf = f0s[m]
res = fit_best_resonator(
fr[1:-1], s21[1:-1],
errors=errors[1:-1]) #Resonator(fr,s21,errors=errors)
delay = res.delay
delays.append(delay)
s21 = s21 * np.exp(2j * np.pi * res.delay * fr)
res = fit_best_resonator(fr, s21, errors=errors)
f0binned = np.round(f0s * nsamp / 512.0) * 512.0 / nsamp
offset_bins = np.arange(-(nstep + 1), (nstep + 1)) * step
offsets = offset_bins * 512.0 / nsamp
measured_freqs = sweeps.prepare_sweep(ri, f0binned, offsets, nsamp=nsamp)
print "loaded waveforms in", (time.time() - start), "seconds"
delay = -31.3
print "median delay is ", delay
df = data_file.DataFile(suffix=suffix)
df.nc.mmw_atten_turns = mmw_atten_turns
df.log_hw_state(ri)
sweep_data = sweeps.do_prepared_sweep(ri, nchan_per_step=atonce, reads_per_step=2)
df.add_sweep(sweep_data)
meas_cfs = []
idxs = []
for m in range(len(f0s)):
fr, s21, errors = sweep_data.select_by_freq(f0s[m])
thiscf = f0s[m]
s21 = s21 * np.exp(2j * np.pi * delay * fr)
res = fit_best_resonator(fr, s21, errors=errors) #Resonator(fr,s21,errors=errors)
fmin = fr[np.abs(s21).argmin()]
print "s21 fmin", fmin, "original guess", thiscf, "this fit", res.f_0
if use_fmin:
meas_cfs.append(fmin)
else:
if abs(res.f_0 - thiscf) > 2:
if abs(fmin - thiscf) > 2:
def sweeps_and_streams(f_initial, attenuations, suffix='', coarse_exponent=19, fine_exponent=21, long_stream_time=30,
short_stream_time=4, roach_wait=10):
roach = baseband.RoachBaseband()
f_modulation = roach.set_modulation_output('high')
n_coarse_samples = 2 ** coarse_exponent
n_fine_samples = 2 ** fine_exponent
coarse_frequency_resolution = roach.fs / n_coarse_samples
fine_frequency_resolution = roach.fs / n_fine_samples
coarse_offset_integers = offset_integers[coarse_exponent]
fine_offset_integers = offset_integers[fine_exponent]
f_coarse_offset = coarse_frequency_resolution * coarse_offset_integers
f_fine_offset = fine_frequency_resolution * fine_offset_integers
start_time = time.time()
df = data_file.DataFile(suffix=suffix)
maximum_attenuation = max(attenuations)
print("Setting DAC attenuator to maximum requested attenuation of {:.1f} dB.".format(maximum_attenuation))
roach.set_dac_attenuator(maximum_attenuation)
# At the lowest readout power, record a coarse sweep and a short stream
sweeps.prepare_sweep(roach, f_initial, f_coarse_offset, n_coarse_samples)
df.log_hw_state(roach)
coarse_sweep_data = sweeps.do_prepared_sweep(roach, nchan_per_step=roach.tone_bins.shape[0], reads_per_step=2)
df.add_sweep(coarse_sweep_data)
df.sync()
coarse_f_fit = np.array([r.f_0 for r in fit_sweep_data(coarse_sweep_data)])
print("coarse - initial [Hz]: " + ', '.join(['{:.0f}'.format(1e6 * diff) for diff in coarse_f_fit - f_initial]))
roach.add_tone_freqs(coarse_f_fit, overwrite_last=True)
roach.select_bank(roach.fft_bins.shape[0] - 1)
roach._sync()
time.sleep(roach_wait) # The above commands somehow create a transient that takes about 5 seconds to decay.
df.log_hw_state(roach)
stream_start_time = time.time()
stream, addresses = roach.get_data_seconds(short_stream_time, pow2=True)
df.add_timestream_data(stream, roach, stream_start_time, mmw_source_modulation_freq=f_modulation)
df.sync()
# Use these frequencies for all subsequent sweeps, and add an additional waveform for each stream.
print("\nSetting fine sweep frequencies.")
sweeps.prepare_sweep(roach, coarse_f_fit, f_fine_offset, n_fine_samples)
for k, attenuation in enumerate(attenuations):
print("\nMeasurement {} of {}: DAC attenuator at {:.1f} dB.".format(k + 1, len(attenuations), attenuation))
roach.set_dac_attenuator(attenuation)
fine_sweep_data = sweeps.do_prepared_sweep(roach, nchan_per_step=roach.tone_bins.shape[0], reads_per_step=2)
df.add_sweep(fine_sweep_data)
df.sync()
fine_f_fit = np.array([r.f_0 for r in fit_sweep_data(fine_sweep_data)])
print("fine - coarse [Hz]: " + ', '.join(['{:.0f}'.format(1e6 * diff) for diff in fine_f_fit - coarse_f_fit]))
f_stream = roach.add_tone_freqs(coarse_f_fit, overwrite_last=k>0) # Overwrite after the first
print("stream detuning [ppm]: " + ', '.join(['{:.0f}'.format(1e6 * x) for x in (f_stream / fine_f_fit - 1)]))
roach.select_bank(roach.fft_bins.shape[0] - 1)
roach._sync()
time.sleep(roach_wait) # The above commands somehow create a transient that takes about 5 seconds to decay.
df.log_hw_state(roach)
stream_start_time = time.time()
stream, addresses = roach.get_data_seconds(long_stream_time, pow2=True)
df.add_timestream_data(stream, roach, stream_start_time, mmw_source_modulation_freq=f_modulation)
df.sync()
df.close()
print("Completed in {:.0f} minutes: {}".format((time.time() - start_time) / 60, df.filename))
def sweep_fit_timestream(roach, center_frequencies, offset_frequencies, sweep_n_samples, timestream_n_samples,
attenuation, suffix,
time_in_seconds, interactive=False, coarse_multiplier=3):
df = data_file.DataFile(suffix=suffix)
print("Writing data to " + df.filename)
print("Setting DAC attenuator to {:.1f} dB".format(attenuation))
roach.set_dac_attenuator(attenuation)
print("Sweep memory usage is {:.1f} MB of {:.1f} MB capacity.".format(
memory_usage_bytes(offset_frequencies.shape[0], sweep_n_samples) / 2 ** 20, EFFECTIVE_DRAM_CAPACITY / 2 ** 20))
# Do a preliminary sweep to make sure the main sweeps are centered properly.
sweeps.prepare_sweep(roach, center_frequencies, coarse_multiplier * offset_frequencies, sweep_n_samples)
roach._sync()
time.sleep(0.2)
if interactive:
raw_input("Hit enter to record preliminary frequency sweep.")
else:
print("Recording preliminary frequency sweep.")
coarse_sweep_data = sweeps.do_prepared_sweep(roach, nchan_per_step=center_frequencies.size, reads_per_step=8)
coarse_resonators = fit_sweep_data(coarse_sweep_data)
coarse_f0s = np.array([r.f_0 for r in coarse_resonators])
fine_center_frequencies = round_frequencies(coarse_f0s, roach.fs, sweep_n_samples)
# Now do the actual sweep and save it.
sweeps.prepare_sweep(roach, fine_center_frequencies, offset_frequencies, sweep_n_samples)
roach._sync()
time.sleep(0.2)
df.log_hw_state(roach)
if interactive:
raw_input("Hit enter to begin recording frequency sweep.")
else:
print("Recording frequency sweep.")
sweep_start_time = time.time()
sweep_data = sweeps.do_prepared_sweep(roach, nchan_per_step=center_frequencies.size, reads_per_step=8)
print("Elapsed time {:.0f} seconds. Writing to disk.".format(time.time() - sweep_start_time))
df.add_sweep(sweep_data)
df.sync()
resonators = fit_sweep_data(sweep_data)
fine_f0s = np.array([r.f_0 for r in resonators])
print("Initial frequencies in MHz are " + ', '.join(['{:.3f}'.format(f0) for f0 in center_frequencies]))
print("initial - fit [Hz]: " +
', '.join(['{:.0f}'.format(1e6 * delta_f) for delta_f in center_frequencies - fine_f0s]))
timestream_measured_frequencies = roach.set_tone_frequencies(fine_f0s, nsamp=timestream_n_samples)
roach.select_fft_bins(np.arange(roach.tone_bins.shape[1]))
roach._sync()
time.sleep(0.2)
df.log_hw_state(roach)
print("measured - fit [Hz]: " +
', '.join(['{:.0f}'.format(1e6 * delta_f) for delta_f in timestream_measured_frequencies - fine_f0s]))
# This delay was added because the above lines cause some kind of transient signal that takes about three seconds
# to decay. This was showing up at the beginning of the timestreams with interactive=False.
minimum_wait = 5
wait_start_time = time.time()
if interactive:
raw_input("Hit enter to begin recording {:.0f} second timestream.".format(time_in_seconds))
else:
print("Recording {:.0f} second timestream.".format(time_in_seconds))
while time.time() - wait_start_time < minimum_wait:
time.sleep(0.1)
timestream_start_time = time.time()
data, address = roach.get_data_seconds(time_in_seconds, demod=True, pow2=True)
print("Elapsed time {:.0f} seconds. Writing to disk.".format(time.time() - timestream_start_time))
df.add_timestream_data(data, roach, timestream_start_time)
df.sync()
df.nc.close()
return df.filename
