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]