def cpmgT1( self, cpmg_freq, pulse1_us, pulse2_us, pulse1_dtcl, pulse2_dtcl, echo_spacing_us, scan_spacing_us, samples_per_echo, echoes_per_scan, init_adc_delay_compensation, number_of_iteration, ph_cycl_en, pulse180_t1_us, logsw, delay180_sta, delay180_sto, delay180_ste, ref_number_of_iteration, ref_twait_mult, data_folder, en_scan_fig, en_fig ):
# create t1 measurement folder
t1_meas_folder = datetime.now().strftime( '%Y_%m_%d_%H_%M_%S' ) + '_t1_meas'
os.mkdir( t1_meas_folder )
t1_meas_hist = 't1_meas_hist.txt' # the history file name for t1 measurement
self.fig_num = 1
self.fcpmg_to_fsys_mult = 16 # system_frequency/cpmg_frequency,set by fpga
self.t1_opt_mult = 1.6
# compute period for the system clock (which is multiplication of the cpmg
# freq)
t_sys = ( 1 / cpmg_freq ) / self.fcpmg_to_fsys_mult
# compute pulse180_t1 in integer values and round it to
# fcpmg_to_fsys_mult multiplication
pulse180_t1_int = np.round(
( pulse180_t1_us / t_sys ) / self.fcpmg_to_fsys_mult ) * self.fcpmg_to_fsys_mult
# process delay
if logsw:
delay180_t1_sw = np.logspace(
np.log10( delay180_sta ), np.log10( delay180_sto ), delay180_ste )
else:
delay180_t1_sw = np.linspace(
delay180_sta, delay180_sto, delay180_ste )
# make delay to be multiplication of fcpmg_to_fsys_mult
delay180_t1_sw_int = np.round( ( delay180_t1_sw / t_sys ) /
self.fcpmg_to_fsys_mult ) * self.fcpmg_to_fsys_mult
# compute the reference and do cpmg
ref_twait = ref_twait_mult * delay180_t1_sw_int[delay180_ste - 1]
ref_twait_int = np.round(
( ref_twait ) / self.fcpmg_to_fsys_mult ) * self.fcpmg_to_fsys_mult
self.cpmgSequence( cpmg_freq, pulse1_us, pulse2_us, pulse1_dtcl, pulse2_dtcl, echo_spacing_us, scan_spacing_us, samples_per_echo,
echoes_per_scan, init_adc_delay_compensation, ref_number_of_iteration, ph_cycl_en, pulse180_t1_int, ref_twait_int )
# process the data
meas_folder = parse_simple_info( data_folder, 'current_folder.txt' )
( a_ref, _, a0_ref, snr_ref, T2_ref, noise_ref, res_ref, theta_ref, data_filt_ref, echo_avg_ref, Df, _ ) = compute_iterate(
data_folder, meas_folder[0], 0, 0, 0, en_scan_fig )
# move the folder to t1 measurement folder and write history
shutil.move( meas_folder[0], t1_meas_folder )
write_text_append( t1_meas_folder, t1_meas_hist, meas_folder[0] )
# make the loop
a0_table = np.zeros( delay180_ste ) # normal format
a0_table_decay = np.zeros( delay180_ste ) # decay format
asum_table = np.zeros( delay180_ste ) # normal format
asum_table_decay = np.zeros( delay180_ste ) # decay format
for i in range( 0, delay180_ste ):
delay180_t1_int = delay180_t1_sw_int[i]
# do cpmg scan
self.cpmgSequence( cpmg_freq, pulse1_us, pulse2_us, pulse1_dtcl, pulse2_dtcl, echo_spacing_us, scan_spacing_us, samples_per_echo,
echoes_per_scan, init_adc_delay_compensation, number_of_iteration, ph_cycl_en, pulse180_t1_int, delay180_t1_int )
# process the data (note that a0 and T2 is based on single
# exponential fit)
meas_folder = parse_simple_info( data_folder, 'current_folder.txt' )
( a, _, a0, snr, T2, noise, res, theta, data_filt, echo_avg, Df, _ ) = compute_iterate(
data_folder, meas_folder[0], 1, theta_ref, echo_avg_ref, en_scan_fig )
# move the folder to t1 measurement folder and write history
shutil.move( meas_folder[0], t1_meas_folder )
write_text_append( t1_meas_folder, t1_meas_hist, meas_folder[0] )
# interscan data store
a0_table[i] = a0
a0_table_decay[i] = a0_ref - a0
asum_table[i] = np.mean( np.real( a ) )
asum_table_decay[i] = np.mean( np.real( a_ref ) ) - np.mean( np.real( a ) )
if en_fig:
print( 'Loading Figure' )
plt.ion()
fig = plt.figure( self.fig_num )
fig.clf()
ax = fig.add_subplot( 3, 1, 1 )
if logsw:
line1, = ax.semilogx(
delay180_t1_sw[0:i + 1] / 1000, asum_table[0:i + 1], 'r-' )
else:
line1, = ax.plot(
delay180_t1_sw[0:i + 1] / 1000, asum_table[0:i + 1], 'r-' )
# ax.set_xlim(-50, 0)
# ax.set_ylim(-50, 0)
ax.set_ylabel( 'Initial amplitude [a.u.]' )
ax.set_title( "T1 inversion recovery" )
ax.grid()
ax = fig.add_subplot( 3, 1, 2 )
if logsw:
line1, = ax.semilogx(
delay180_t1_sw[0:i + 1] / 1000, asum_table_decay[0:i + 1], 'r-' )
else:
line1, = ax.plot(
delay180_t1_sw[0:i + 1] / 1000, asum_table_decay[0:i + 1], 'r-' )
# ax.set_xlim(-50, 0)
# ax.set_ylim(-50, 0)
# ax.set_xlabel('Wait time [ms]')
ax.set_ylabel( 'Initial amplitude [a.u.]' )
ax.grid()
ax = fig.add_subplot( 3, 1, 3 )
ax.set_ylabel( 'Amplitude [a.u.]' )
ax.set_xlabel( 'Wait time [ms]' )
ax.grid()
fig.canvas.draw()
fig.canvas.flush_events()
print( 'Figure Loaded' )
# save t1 data to csv file to be processed
f = open( t1_meas_folder + '/' + 't1heel_in.csv', "w+" )
for i in range( 0, delay180_ste ):
f.write( "%f," % ( delay180_t1_sw[i] / 1000 ) ) # in milisecond
f.write( "%f\n" % ( a0_table_decay[i] ) )
f.close()
# process t1 data
self.doLaplaceInversion( t1_meas_folder + '/' + 't1heel_in.csv',
t1_meas_folder )
tvect, data = parse_csv_float2col(
t1_meas_folder, 't1heel_out.csv' )
i_peaks = signal.find_peaks_cwt( data, np.arange( 1, 10 ) )
t1_opt = tvect[max( i_peaks )]
'''
a_peaks = np.zeros(len(i_peaks))
for i in range(0, len(i_peaks)):
a_peaks[i] = data[i_peaks[i]]
# find tvect in which the largest peak is found
t1_opt = tvect[i_peaks[np.where(max(a_peaks))[0][0]]] # in second
'''
if en_fig:
ax = fig.add_subplot( 3, 1, 3 )
if logsw:
line1, = ax.semilogx( np.multiply( tvect, 1000 ), data, 'r-' )
else:
line1, = ax.plot( np.multiply( tvect, 1000 ), data, 'r-' )
ax.set_ylabel( 'Amplitude [a.u.]' )
ax.set_xlabel( 'Wait time [ms]' )
ax.grid()
fig.canvas.draw()
# copy the measurement history script
shutil.copy( 'measurement_history_matlab_script.txt', t1_meas_folder )
return delay180_t1_sw, a0_table, a0_ref, asum_table, t1_opt, t1_meas_folder
# turn off system
nmrObj.deassertControlSignal(nmrObj.RX1_1H_msk | nmrObj.RX1_1L_msk
| nmrObj.RX2_L_msk | nmrObj.RX2_H_msk
| nmrObj.RX_SEL1_msk | nmrObj.RX_FL_msk
| nmrObj.RX_FH_msk | nmrObj.PAMP_IN_SEL2_msk)
nmrObj.setMatchingNetwork(0, 0)
nmrObj.setPreampTuning(0, 0)
nmrObj.deassertControlSignal(nmrObj.PSU_15V_TX_P_EN_msk
| nmrObj.PSU_15V_TX_N_EN_msk
| nmrObj.PSU_5V_TX_N_EN_msk
| nmrObj.PSU_5V_ADC_EN_msk
| nmrObj.PSU_5V_ANA_P_EN_msk
| nmrObj.PSU_5V_ANA_N_EN_msk)
shutil.copy2(data_folder + '/' + meas_folder[0] + '/acqu.par', dst_path)
for kk in range(0, pulse_us_ste):
data_parser.write_text_append(dst_path, 'acqu.par',
'P90 = {}'.format(P90[kk]))
for kk in range(0, pulse_us_ste):
data_parser.write_text_append(dst_path, 'acqu.par',
'P180 = {}'.format(P180[kk]))
if en_fig:
fig.savefig(dst_path + '/' + datename + '_pulsesw.pdf')
pass
pass
Vvarac = 2.8
# (vbias vvarac)
nmrObj.setPreampTuning(Vbias, Vvarac) #-2.5, 2.8) # try -2.7, -1.8 if fail
nmrObj.setMatchingNetwork( 0, 0 )
nmrObj.setMatchingNetwork( 0, 0 )
while True:
nmrObj.assertControlSignal( nmrObj.RX1_1L_msk | nmrObj.RX2_L_msk | nmrObj.RX2_H_msk | nmrObj.RX_SEL1_msk |
nmrObj.RX_FL_msk )
nmrObj.assertControlSignal( nmrObj.PSU_15V_TX_P_EN_msk | nmrObj.PSU_15V_TX_N_EN_msk | nmrObj.PSU_5V_TX_N_EN_msk |
nmrObj.PSU_5V_ADC_EN_msk | nmrObj.PSU_5V_ANA_P_EN_msk |
nmrObj.PSU_5V_ANA_N_EN_msk )
time.sleep( 0.1 )
nmrObj.pamp_char ( sta_freq, sto_freq, spac_freq, samp_freq )
nmrObj.deassertAll()
meas_folder = parse_simple_info( data_parent_folder, 'current_folder.txt' )
# meas_folder[0] = "nmr_wobb_2018_06_25_12_44_48"
maxS21, maxS21_freq, _ = compute_gain( nmrObj, data_parent_folder, meas_folder[0], en_fig, fig_num )
print( 'maxS21={0:0.2f} maxS21_freq={1:0.2f}'.format(
maxS21, maxS21_freq ) )
dst_pat = ( data_parent_folder + '/' + meas_folder[0] + '/' )
data_parser.write_text_append(dst_pat, 'acqu.par', 'target_freq = {}'.format(target_freq))
data_parser.write_text_append(dst_pat, 'acqu.par', 'Vbias = {}'.format(Vbias))
data_parser.write_text_append(dst_pat, 'acqu.par', 'Vvarac = {}'.format(Vvarac))
def log_param(samples_per_echo, echoes_per_scan, scan_spacing_us, t2_opt,
t1_opt, t1t2, snr, folder):
write_text_append(folder, 'log_samples_per_echo', str(samples_per_echo))
write_text_append(folder, 'log_echoes_per_scan', str(echoes_per_scan))
write_text_append(folder, 'log_scan_spacing_us', str(scan_spacing_us))
write_text_append(folder, 'log_t2_opt', str(t2_opt))
write_text_append(folder, 'log_t1_opt', str(t1_opt))
write_text_append(folder, 'log_t1t2', str(t1t2))
write_text_append(folder, 'log_snr', str(snr))
t2_opt = tvectArray[max(i_peaks)] # in second
# adjust echoes_per_scan according to t2_opt
echoes_per_scan = np.round((t2_opt * 1e6 * t2_opt_mult) / echo_spacing_us)
t1_opt_echoes_per_scan = echoes_per_scan
print('num of echoes: %d' % echoes_per_scan)
print('t2Opt: %f' % t2_opt)
print('t2OptMult: %f' % t2_opt_mult)
plt.semilogx(tvect, dataArray)
plt.show()
# move the folder to t2t1 measurement folder and write history
shutil.move(meas_folder[0], t2t1_meas_folder)
write_text_append(t2t1_meas_folder, t2t1_meas_hist, meas_folder[0])
# log the parameters to file
log_param(samples_per_echo, echoes_per_scan, scan_spacing_us, t2_opt,
t1_opt, t1t2, snr, t2t1_meas_folder)
print('----- START T1 OPTIMIZATION -----')
en_fig = 0
# cpmg settings
scan_spacing_us = t2_opt * 13 * 10.0**6
number_of_iteration = 4 # number of averaging
pulse180_t1_us = pulse2_us
# sweep parameters
logsw = 1 # logsw specifies logsweep, or otherwise linsweep
ax = fig.add_subplot( 1, 1, 1 )
line1, = ax.plot( cpmg_freq_sw[0:i + 1], a_integ_table[0:i + 1], 'b-o' )
# ax.set_ylim(-50, 0)
# ax.set_xlabel('Frequency [MHz]')
# ax.set_ylabel('S11 [dB]')
# ax.set_title("Reflection Measurement (S11) Parameter")
ax.grid()
fig.canvas.draw()
# fig.canvas.flush_events()
# turn off system
nmrObj.deassertControlSignal(
nmrObj.RX1_1H_msk | nmrObj.RX1_1L_msk | nmrObj.RX2_L_msk | nmrObj.RX2_H_msk | nmrObj.RX_SEL1_msk | nmrObj.RX_FL_msk | nmrObj.RX_FH_msk | nmrObj.PAMP_IN_SEL2_msk )
nmrObj.setMatchingNetwork( 0, 0 )
nmrObj.setPreampTuning( 0, 0 )
nmrObj.deassertControlSignal( nmrObj.PSU_15V_TX_P_EN_msk | nmrObj.PSU_15V_TX_N_EN_msk | nmrObj.PSU_5V_TX_N_EN_msk |
nmrObj.PSU_5V_ADC_EN_msk | nmrObj.PSU_5V_ANA_P_EN_msk | nmrObj.PSU_5V_ANA_N_EN_msk )
shutil.copy2(data_folder + '/' + meas_folder[0] + '/acqu.par', dst_path)
for kk in range( 0, Freq_step ):
data_parser.write_text_append(dst_path, 'acqu.par', 'Freq = {}'.format(cpmg_freq_sw[kk]))
if en_fig:
fig.savefig( dst_path + '/' + datename + '_pulsesw.pdf' )
pass
pass
