def plot(datapath, with_detuning=False, save=True):
plt.close('all')
###########################################
######## MEASUREMENT SPECS ################
###########################################
files = os.listdir(datapath)
for k in files:
if 'statics_and_parameters.npz' in k:
stats_params_file = k
if 'Spin_RO.npz' in k:
spin_ro_file = k
if 'SP_histogram.npz' in k:
sp_file = k
e = load(datapath + '\\' + stats_params_file)
f_drive = e['mw_center_freq']
mwpower = e['mw_power']
mw_min_freq = e['min_mw_freq']
mw_max_freq = e['max_mw_freq']
noof_datapoints = e['noof_datapoints']
###########################################
######## SPIN RO #########################
###########################################
f = load(datapath + '\\' + spin_ro_file)
raw_counts = f['counts']
repetitions = f['sweep_axis']
t = f['time']
tot_size = len(repetitions)
reps_per_point = tot_size / float(noof_datapoints)
idx = 0
counts_during_readout = zeros(noof_datapoints)
mw_freq = linspace(mw_min_freq, mw_max_freq, noof_datapoints)
counts_during_readout = sum(raw_counts, axis=1)
#########################################
############ FITTING ####################
#########################################
figure2 = plt.figure(2)
plt.plot(mw_freq / 1E9, counts_during_readout, 'sk')
plt.xlabel('MW frequency (GHz)')
plt.ylabel('Integrated counts')
plt.title('MW frequency sweep, driving $f$ ='+num2str(f_drive/1E6,1)+\
' MHz, power = '+num2str(mwpower,0)+' dBm')
#plt.text(0.1*(mw_max_freq+mw_min_freq),max(counts_during_readout),datapath)
if save:
figure2.savefig(datapath + '\\histogram_integrated.png')
x = 6.0
y = 8.0
figure3 = plt.figure(figsize=(x, y))
plt.pcolor(raw_counts, cmap='hot', antialiased=False)
plt.xlabel('Readout time (us)')
plt.ylabel('MW repetition number')
plt.title('Total histogram, integrated over repetitions')
plt.colorbar()
if save:
figure3.savefig(datapath + '\\histogram_counts_2d.png')
f.close()
###########################################
######## CHARGE RO ########################
###########################################
#g = load(datapath+'\\spin_control-0_ChargeRO_before.npz')
#h = load(datapath+'\\spin_control-0_ChargeRO_after.npz')
#g.close()
#h.close()
###########################################
######## SPIN PUMPING #####################
###########################################
v = load(datapath + '\\' + sp_file)
sp_counts = v['counts']
sp_time = v['time']
offset_guess = sp_counts[len(sp_counts) - 1]
init_amp_guess = sp_counts[2]
decay_guess = 10
figure4 = plt.figure(4)
fit.fit1d(sp_time / 1E3,
sp_counts,
common.fit_exp_decay_with_offset,
offset_guess,
init_amp_guess,
decay_guess,
do_plot=True,
do_print=True,
newfig=False,
plot_fitparams_xy=(0.5, 0.5))
plt.plot(sp_time / 1E3, sp_counts, 'sg')
plt.xlabel('Time ($\mu$s)')
plt.ylabel('Integrated counts')
plt.title('Spin pumping')
v.close()
if save:
figure4.savefig(datapath + '\\spin_pumping.png')
#Save a dat file for use in e.g. Origin with the rabi oscillation.
curr_date = '#' + time.ctime() + '\n'
col_names = '#Col0: MW length (ns)\tCol1: Integrated counts\n'
col_vals = str()
for k in arange(noof_datapoints):
col_vals += num2str(mw_len[k], 2) + '\t' + num2str(
counts_during_readout[k], 0) + '\n'
fo = open(datapath + '\\integrated_histogram.dat', "w")
for item in [curr_date, col_names, col_vals]:
fo.writelines(item)
fo.close()
return True
def plot(datapath, with_detuning = False, save = True):
plt.close('all')
###########################################
######## MEASUREMENT SPECS ################
###########################################
files = os.listdir(datapath)
for k in files:
if 'statics_and_parameters.npz' in k:
stats_params_file = k
if 'Spin_RO.npz' in k:
spin_ro_file = k
if 'SP_histogram.npz' in k:
sp_file = k
e = load(datapath+'\\'+stats_params_file)
f_drive = e['mw_center_freq']
mwpower = e['mw_power']
mw_min_freq = e['min_mw_freq']
mw_max_freq = e['max_mw_freq']
noof_datapoints = e['noof_datapoints']
###########################################
######## SPIN RO #########################
###########################################
f = load(datapath+'\\'+spin_ro_file)
raw_counts = f['counts']
repetitions = f['sweep_axis']
t = f['time']
tot_size = len(repetitions)
reps_per_point = tot_size/float(noof_datapoints)
idx = 0
counts_during_readout = zeros(noof_datapoints)
mw_freq = linspace(mw_min_freq,mw_max_freq,noof_datapoints)
counts_during_readout = sum(raw_counts, axis = 1)
#########################################
############ FITTING ####################
#########################################
figure2 = plt.figure(2)
plt.plot(mw_freq/1E9,counts_during_readout, 'sk')
plt.xlabel('MW frequency (GHz)')
plt.ylabel('Integrated counts')
plt.title('MW frequency sweep, driving $f$ ='+num2str(f_drive/1E6,1)+\
' MHz, power = '+num2str(mwpower,0)+' dBm')
#plt.text(0.1*(mw_max_freq+mw_min_freq),max(counts_during_readout),datapath)
if save:
figure2.savefig(datapath+'\\histogram_integrated.png')
x = 6.0
y = 8.0
figure3 = plt.figure(figsize=(x,y))
plt.pcolor(raw_counts, cmap = 'hot', antialiased=False)
plt.xlabel('Readout time (us)')
plt.ylabel('MW repetition number')
plt.title('Total histogram, integrated over repetitions')
plt.colorbar()
if save:
figure3.savefig(datapath+'\\histogram_counts_2d.png')
f.close()
###########################################
######## CHARGE RO ########################
###########################################
#g = load(datapath+'\\spin_control-0_ChargeRO_before.npz')
#h = load(datapath+'\\spin_control-0_ChargeRO_after.npz')
#g.close()
#h.close()
###########################################
######## SPIN PUMPING #####################
###########################################
v = load(datapath+'\\'+sp_file)
sp_counts = v['counts']
sp_time = v['time']
offset_guess = sp_counts[len(sp_counts)-1]
init_amp_guess = sp_counts[2]
decay_guess = 10
figure4 = plt.figure(4)
fit.fit1d(sp_time/1E3, sp_counts, common.fit_exp_decay_with_offset,
offset_guess, init_amp_guess, decay_guess,
do_plot = True, do_print = True, newfig = False,
plot_fitparams_xy = (0.5,0.5))
plt.plot(sp_time/1E3,sp_counts,'sg')
plt.xlabel('Time ($\mu$s)')
plt.ylabel('Integrated counts')
plt.title('Spin pumping')
v.close()
if save:
figure4.savefig(datapath+'\\spin_pumping.png')
#Save a dat file for use in e.g. Origin with the rabi oscillation.
curr_date = '#'+time.ctime()+'\n'
col_names = '#Col0: MW length (ns)\tCol1: Integrated counts\n'
col_vals = str()
for k in arange(noof_datapoints):
col_vals += num2str(mw_len[k],2)+'\t'+num2str(counts_during_readout[k],0)+'\n'
fo = open(datapath+'\\integrated_histogram.dat', "w")
for item in [curr_date, col_names, col_vals]:
fo.writelines(item)
fo.close()
return True
def plot(datapath, save = True):
###########################################
######## MEASUREMENT SPECS ################
###########################################
e = load(datapath+'\\spin_control-0_statics_and_parameters.npz')
f_drive = e['mw_drive_freq']
mwpower = e['mw_power']
mw_min_len = e['min_mw_length']
mw_max_len = e['max_mw_length']
noof_datapoints = e['noof_datapoints']
###########################################
######## SPIN RO #########################
###########################################
f = load(datapath+'\\spin_control-0_Spin_RO.npz')
raw_counts = f['counts']
repetitions = f['sweep_axis']
t = f['time']
tot_size = len(repetitions)
reps_per_point = tot_size/float(noof_datapoints)
idx = 0
counts_during_readout = zeros(noof_datapoints)
mw_len = linspace(mw_min_len,mw_max_len,noof_datapoints)
counts_during_readout = sum(raw_counts, axis = 1)
#########################################
############ FITTING ####################
#########################################
FFT = fft.fft(counts_during_readout)
N = int(noof_datapoints)
timestep = (mw_max_len-mw_min_len)/float(noof_datapoints-1)
freq = fft.fftfreq(N,d = timestep)
#Remove offset:
FFT[freq == 0] = 0
figure1 = plt.figure(1)
plt.bar(freq*1E3,abs(FFT), width = 0.4*1E3*(freq[1]-freq[0]), align = 'center')
plt.xlabel('Frequency (MHz)')
plt.ylabel('Amplitude')
plt.title('FFT (offset removed)')
if save:
figure1.savefig(datapath+'\\fft_signal_rabi.png')
freq_guess = freq[find_nearest(abs(FFT),abs(FFT).max())]
amp_guess = (counts_during_readout.max()+counts_during_readout.min())/2.0
offset_guess = counts_during_readout.min()+(counts_during_readout.max()+\
counts_during_readout.min())/2.0
phase_guess = 0
print 'freq_guess = ',freq_guess
fit.fit1d(mw_len, counts_during_readout, rabi.fit_rabi_simple,
freq_guess, amp_guess, offset_guess, phase_guess,
do_plot = True, do_print = True)
figure2 = plt.gcf()
plt.plot(mw_len,counts_during_readout, 'sk')
plt.xlabel('MW length (ns)')
plt.ylabel('Integrated counts')
plt.title('MW length sweep, driving $f$ ='+num2str(f_drive/1E6,1)+\
' MHz, power = '+num2str(mwpower,0)+' dBm')
plt.text(0.1*(mw_max_len+mw_min_len),max(counts_during_readout),datapath)
if save:
figure2.savefig(datapath+'\\histogram_integrated.png')
x = 6.0
y = 8.0
figure3 = plt.figure(figsize=(x,y))
plt.pcolor(raw_counts, cmap = 'hot', antialiased=False)
plt.xlabel('Readout time (us)')
plt.ylabel('MW repetition number')
plt.title('Total histogram, integrated over repetitions')
plt.colorbar()
if save:
figure3.savefig(datapath+'\\histogram_counts_2d.png')
f.close()
###########################################
######## CHARGE RO ########################
###########################################
#g = load(datapath+'\\spin_control-0_ChargeRO_before.npz')
#h = load(datapath+'\\spin_control-0_ChargeRO_after.npz')
#g.close()
#h.close()
###########################################
######## SPIN PUMPING #####################
###########################################
v = load(datapath+'\\spin_control-0_SP_histogram.npz')
sp_counts = v['counts']
sp_time = v['time']
offset_guess = sp_counts[len(sp_counts)-1]
init_amp_guess = sp_counts[2]
decay_guess = 10
figure4 = plt.figure(4)
fit.fit1d(sp_time/1E3, sp_counts, common.fit_exp_decay_with_offset,
offset_guess, init_amp_guess, decay_guess,
do_plot = True, do_print = True, newfig = False,
plot_fitparams_xy = (0.5,0.5))
plt.plot(sp_time/1E3,sp_counts,'sg')
plt.xlabel('Time ($\mu$s)')
plt.ylabel('Integrated counts')
plt.title('Spin pumping')
v.close()
if save:
figure4.savefig(datapath+'\\spin_pumping.png')
#Save a dat file for use in e.g. Origin with the rabi oscillation.
curr_date = '#'+time.ctime()+'\n'
col_names = '#Col0: MW length (ns)\tCol1: Integrated counts\n'
col_vals = str()
for k in arange(noof_datapoints):
col_vals += num2str(mw_len[k],2)+'\t'+num2str(counts_during_readout[k],0)+'\n'
fo = open(datapath+'\\integrated_histogram.dat', "w")
for item in [curr_date, col_names, col_vals]:
fo.writelines(item)
fo.close()
return True
