sweep.vals = np.linspace(0.1, 1.1, 21)
sweep.num_steps = sweep.vals.size
#
daq = Nop("daq")
sweep.p = []
for step_num, v in enumerate(sweep.vals):
#
print("\nstep_num: {}".format(step_num))
#
amp = [v*1.5, v*1.77, 1.5, 1.5]
wx_programs.wx_set_and_amplitude_and_offset(amp=amp)
#
daq.daq_params, daq.rec_readout_vs_pats, daq.p_readout = daq_programs.run_daq(
num_patterns=seq.num_patterns, num_records_per_pattern=seq.num_records_per_pattern)
sweep.p.append(daq.p_readout)
wx_programs.wx_set_and_amplitude_and_offset()
sweep.p = np.array(sweep.p)
#
sweep.fit = []
for k in range(sweep.num_steps):
#.
popt, perr, _, _ = analysis.fit_sine_decay(seq.times, sweep.p[k][0])
sweep.fit.append(popt)
#
sweep.fit = np.array(sweep.fit)
for k in range(seq.num_avgs):
#
daq_params, _, p = daq_programs.run_daq(
num_patterns=seq.num_patterns, num_records_per_pattern=seq.num_records_per_pattern)
if k is 0:
p_readout = p
else:
p_readout += p
p_readout = p_readout/seq.num_avgs
p_post = analysis.p_readout_postselected(p_readout)
sweep.p.append(p_readout)
sweep.p_post.append(p_post)
daq = Nop("daq")
daq.daq_params = daq_params
wx_programs.wx_set_and_amplitude_and_offset()
sweep.p = np.array(sweep.p)
sweep.p_post = np.array(sweep.p_post)
#
for p in sweep.p:
daq_programs.make_readout_vs_patterns_plot(p)
#
sweep.fit = []
for k in range(sweep.num_steps):
#
x = seq.times
y = sweep.p_post[k][-1]