def readout(): expt = expt_parameters.expt_parameters() seq = Nop("seq") msmt = Nop("measurement") # seq.comment = "ramsey_ge calibration" # seq.num_patterns = 51 # seq.sweep_time = 1000 # seq.num_records_per_pattern = 500 # seq.rabi_amp = 0.05 # seq.times = np.linspace(0., seq.sweep_time, seq.num_patterns)*1e-3 # steps=13 # # sweep = Nop("sweep") # sweep.comment = "rabi ssb freq near EP" # sweep.vals = np.linspace(-3, 3, steps)*1e-3 + 0.092 # ge ramsey ## sweep.vals = np.linspace(-0.5, 0.5, 3)*1e-3 + expt_cal.ssm.ef # pop_3state = [] # fpop=[] # # for idx, ssm_ef in enumerate(sweep.vals): # print(idx) # # black_nonHermitian.ramsey_ef(ssm_ef) # wx_programs.wx_set_and_amplitude_and_offset() # ## seq_experiments.rabi_ef_prep_f(seq.num_patterns, seq.sweep_time, seq.rabi_amp, rabi_ssb_freq) # daq_params, rec_readout_vs_pats, p_readout = daq_programs.run_daq( # num_patterns=seq.num_patterns, num_records_per_pattern=seq.num_records_per_pattern) # p_post = analysis.p_readout_postselected(p_readout) # pop_3state.append(p_readout) ## msmt.popt, msmt.perr, _, _ = analysis.fit_sine_decay(x, y, guess_vals=None) # x = seq.times # y = p_post[1] ## analysis.fit_sine_decay(x,y,) # fpop.append(p_post[1]) ## save_by_pickle((expt, seq, daq, msmt)) # plt.plot(seq.times, p_post[1]) # plt.ylim([0,4]) # plt.show() ## pop_3state = np.stack(pop_3state) # popdstack=np.dstack(pop_3state) # # pop3state_f=popdstack.reshape(seq.num_patterns*3,steps) # np.savetxt('popdstack', pop3state_f) # np.savetxt('fpop', fpop) # fig = plt.figure() # plt.imshow(fpop) ## plt.imshow(pop_3state[:,1,:]) # plt.show seq.comment = "t1 ge" seq.num_patterns = 51 seq.sweep_time = 1000 seq.num_records_per_pattern = 1000 seq.times = np.linspace(0., seq.sweep_time, seq.num_patterns) * 1e-3 # black_nonHermitian.ramsey_ef() wx_programs.wx_set_and_amplitude_and_offset() daq, msmt.rec_readout_vs_pats, msmt.p_readout = daq_programs.run_daq( num_patterns=seq.num_patterns, num_records_per_pattern=seq.num_records_per_pattern) # msmt.p_post = analysis.p_readout_postselected(msmt.p_readout) # msmt.p_post = analysis.p_readout_postselected(msmt.p_readout) # # x = seq.times # y = msmt.p_post[1] # plt.plot(x, y) # plt.ylim([0, 1]) # msmt.popt, msmt.perr, _, _ = analysis.fit_exp_decay(x, y, guess_vals=None) # msmt.popt, msmt.perr, _, _ = analysis.fit_sine_decay(x, y, guess_vals=None) # save_by_pickle((expt, seq, daq, msmt)) # test = [1, 2, 3] return msmt.p_readout
save_path = get_save_path() fname = save_path + ".pickle" print(fname) with open(fname, "wb") as open_file: pickle.dump(data_in, open_file) if __name__ == '__main__': seq = Nop("seq") expt_cal = seq_programs.get_expt_cal() # seq.comment = "rabi_ge, sweep wx amps" seq.num_patterns = 101 seq.num_records_per_pattern = 200 seq.sweep_time = 1000 seq.times = np.linspace(0., seq.sweep_time, seq.num_patterns)*1e-3 #seq_experiments.rabi_ge(seq.num_patterns, seq.sweep_time) # sweep = Nop("sweep") sweep.comment = "wx amps, ch1ch2" 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))
fname = path0 + "20200309_152452.pickle" with open(fname, "rb") as open_file: x = pickle.load(open_file) return x if __name__ == '__main__': expt = expt_parameters.expt_parameters() seq = Nop("seq") msmt = Nop("measurement") # seq.comment = "rabi_ef_prep_f, sweep rabi detuning" seq.num_patterns = 101 seq.sweep_time = 2000 seq.num_records_per_pattern = 200 seq.rabi_amp = 0.05 seq.times = np.linspace(0., seq.sweep_time, seq.num_patterns) * 1e-3 sweep = Nop("sweep") sweep.comment = "rabi ssb freq near EP" sweep.vals = np.linspace(-0.5, 0.5, 2) * 1e-3 + 0.092 # sweep.vals = np.linspace(-0.5, 0.5, 3)*1e-3 + expt_cal.ssm.ef pop_3state = [] for idx, rabi_ssb_freq in enumerate(sweep.vals): print(idx) seq_experiments.rabi_ef_prep_f(seq.num_patterns, seq.sweep_time, seq.rabi_amp, rabi_ssb_freq) daq_params, rec_readout_vs_pats, p_readout = daq_programs.run_daq( num_patterns=seq.num_patterns,