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Added SinSin STE for central line excitation

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Markus Rosenstihl
2025-09-24 10:55:13 +02:00
parent 7da97a4f26
commit ce79484157
5 changed files with 429 additions and 0 deletions
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Scripts/.idea/.gitignore generated vendored Normal file
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# Default ignored files
/shelf/
/workspace.xml
# Editor-based HTTP Client requests
/httpRequests/
# Datasource local storage ignored files
/dataSources/
/dataSources.local.xml

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<component name="ProjectDictionaryState">
<dictionary name="markusro" />
</component>

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="VcsDirectoryMappings">
<mapping directory="$PROJECT_DIR$/.." vcs="Git" />
</component>
</project>

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Scripts/Spin_Alignment_CentreEx/sinsin_centr_exp.py Normal file
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# -*- coding: iso-8859-1 -*-
from xml.etree import cElementTree as ET
import time
TXEnableDelay = 2e-6
TXEnableValue = 0b0001 # TTL line blanking RF amplifier (bit 0)
TXPulseValue = 0b0010 # TTL line triggering RF pulses (bit 1)
ADCSensitivity = 0.5 # voltage span for ADC
def experiment(): # SinSin-Stimulated Echos for central Anregung
# set up acquisition parameters:
pars = {}
# here: we want central line excitation, i.e. "long" pulses
pars['P90'] = 5.4e-6 # 90-degree pulse length (s),
pars['PFLIP'] = 90 # 2nd and 3rd pulse flip angles, i.e. 90 or 45
pars['SF'] = 95.2e6 # spectrometer frequency (Hz)
pars['O1'] =0 # offset from SF (Hz)
pars['SW'] = 5e6 # spectral window (Hz)
pars['SI'] = 8*1024 # number of acquisition points
pars['NS'] = 32*32*2#*3 # number of scans # multiple of 32
pars['DS'] = 0 # number of dummy scans
pars['RD'] = 0.1 # delay between scans (s) (Recycle Delay)
pars['TAU'] = 0.014*7 # delay between SatRec and experiment (s)
pars['D1'] = 20e-6 # delay after first pulse, or short tau (s)
pars['D2'] = 10e-6 # delay after second pulse, or long tau (s)
pars['D_PREAQ'] = 5e-6
pars['PHA'] =337 # receiver phase (degree)
### SatRec
pars['D3'] = 1e-5 # shortest SatRec delay
pars['D4'] = 1e-3 # longest SatRec delay
pars["NECH"] = 12 # numbe of saturation pulse
###
pars['DATADIR'] = '/home/fprak/Desktop/' # data directory
pars['OUTFILE'] = None # output file name
# specify a variable parameter (optional):
pars['tp'] = [20e-6,50e-6,90e-6,150e-6,300e-6]
pars['VAR_PAR'] = 'D2' # variable parameter name (a string)
start = 20e-6 # starting value
stop =0.3 # end value
steps = 21 # number of values
log_scale = True # log scale flag
stag_range = True # staggered range flag
# check parameters for safety:
if pars['PHA'] < 0:
pars['PHA'] = 360 + pars['PHA']
if pars['P90'] > 20e-6:
raise Exception("Pulse too long!!!")
# check whether a variable parameter is named:
var_key = pars.get('VAR_PAR')
if var_key == 'P90' and (start > 20e-6 or stop > 20e-6):
raise Exception("Pulse too long!!!")
# start the experiment:
if var_key:
# this is an arrayed experiment:
if log_scale:
array = log_range(start,stop,steps)
else:
array = lin_range(start,stop,steps)
if stag_range:
array = staggered_range(array, size = 3)
# estimate time by looping once over everything
duration = 0
for tp in pars["tp"]:
for index, var_par_value in enumerate(array):
# assign each var_key the corresponding var_value
pars[var_key] = var_par_value
# parse state tree
e_xml = ET.fromstring(spinal32_experiment(pars, 0).write_xml_string())
# sum up all time=x states
for a_state in e_xml.iter("state"):
duration += float(a_state.get("time"))*(pars['NS'] + pars['DS'])
t = time.localtime(duration)
print "\n\nINFO: Experiment will be finnished in: %id %ih %im" % (t.tm_mday-1, t.tm_hour-1, t.tm_min)
print "INFO: Experiment will be finnished at: %s\n\n" % (time.ctime(time.time() + duration))
# loop for a variable parameter:
for tp in pars['tp']:
pars['D1'] = tp
for index, pars[var_key] in enumerate(array):
print 'Arrayed experiment for '+var_key+': run = '+str(index+1)+\
' out of '+str(len(pars['tp'])*array.size)+': value = ' + str(tp) + ' / '+str(pars[var_key])
# loop for accumulation:
for run in xrange(pars['NS']+pars['DS']):
yield spinal32_experiment(pars, run)
synchronize()
else:
# estimate the experiment time:
seconds = (pars['D1']*2 + pars['D2'] + pars['RD']) * (pars['NS']+ pars['DS'])
m, s = divmod(seconds, 60)
h, m = divmod(m, 60)
print '%s%02d:%02d:%02d' % ('Experiment time estimated: ', h, m, s)
# loop for accumulation:
for run in xrange(pars['NS']+pars['DS']):
yield spinal32_experiment(pars, run)
# the pulse program:
def spinal32_experiment(pars, run):
e=Experiment()
dummy_scans = pars.get('DS')
if dummy_scans:
run -= dummy_scans
pars['PROG'] = 'spinalign_central_line_experiment'
# phase cycle by F. Qi et al. [JMR 169 (2004) 225-239] with 3rd-phase invertion
# Storek: SE+ + SE-
pars['PH1'] = [180, 180, 180, 180, 0, 0, 0, 0, 180, 180, 180, 180, 0, 0, 0, 0, 270, 270, 270, 270, 90,90,90,90, 270, 270, 270, 270, 90,90,90,90]
pars['PH3'] = [270, 270, 90, 90, 270, 270, 90, 90, 270, 270, 90, 90, 270, 270, 90, 90, 180, 180, 0, 0, 180, 180, 0, 0, 180, 180, 0, 0, 180, 180, 0, 0]
pars['PH4'] = [180, 0, 180, 0, 180, 0, 180, 0, 270, 90, 270, 90, 270, 90, 270, 90, 180, 0, 180, 0, 180, 0, 180, 0, 270, 90, 270, 90, 270, 90, 270, 90]
pars['PH2'] = [270, 90, 90, 270, 90, 270, 270, 90, 0, 180, 180, 0, 180, 0, 0, 180, 90, 270, 270, 90, 270, 90, 90, 270, 180, 0, 0, 180, 0, 180, 180, 0]
# read in variables:
P90 = pars['P90']
PMOD = pars["PFLIP"]/90.*pars['P90'] # modified flip angle
SF = pars['SF']
O1 = pars['O1']
RD = pars['RD']
D1 = pars['D1']
D2 = pars['D2']
D3 = pars['D3']
D4 = pars['D4']
D_PREAQ = pars['D_PREAQ']
TAU = pars['TAU']
NECH = pars['NECH']
PH1 = pars['PH1'][run%len(pars['PH1'])]
PH3 = pars['PH3'][run%len(pars['PH3'])]
PH4 = pars['PH4'][run%len(pars['PH4'])]
PH2 = pars['PH2'][run%len(pars['PH2'])]
PHA = pars['PHA']
# set sampling parameters:
SI = pars['SI']
SW = pars['SW']
# run the pulse program:
# saturation:
# set variable delay list for saturation pulses:
vdlist = log_range(D4, D3, NECH-1)
e.wait(RD) # relaxation delay between scans
e.set_frequency(SF+O1, phase=PH1) # set frequency and phase for saturation pulses
e.ttl_pulse(TXEnableDelay, value=TXEnableValue) # enable RF amplifier
e.ttl_pulse(P90, value=TXEnableValue|TXPulseValue) # apply 90-degree pulse
for delay in vdlist[::-1]:
e.wait(delay-P90-TXEnableDelay) # wait for next saturation pulse
e.ttl_pulse(TXEnableDelay, value=TXEnableValue) # enable RF amplifier
e.ttl_pulse(P90, value=TXEnableValue|TXPulseValue) # apply 90-degree pulse
# recovery:
e.set_phase(PH1)
e.wait(TAU-0.5e-6-TXEnableDelay) # wait for tau
e.ttl_pulse(TXEnableDelay, value=TXEnableValue)
e.ttl_pulse(P90, value=TXEnableValue|TXPulseValue) # 90-degree pulse
e.set_phase(PH3)
e.wait(D1-P90/2- PMOD/2-TXEnableDelay-0.5e-6) # 'short tau'
e.ttl_pulse(TXEnableDelay, value=TXEnableValue)
e.ttl_pulse(PMOD, value=TXEnableValue|TXPulseValue) # X-degree pulse
e.set_phase(PH4)
e.wait(D2-PMOD-TXEnableDelay-0.5e-6) # 'long tau'
e.ttl_pulse(TXEnableDelay, value=TXEnableValue)
e.ttl_pulse(PMOD, value=TXEnableValue|TXPulseValue) # X-degree pulse
e.set_phase(PHA)
e.wait(D1-PMOD/2-0.5e-6-D_PREAQ) # 'short tau'
e.record(SI, SW, sensitivity=ADCSensitivity) # acquisition
# write experiment parameters:
for key in pars.keys():
e.set_description(key, pars[key]) # acqusition parameters
e.set_description('run', run) # current scan
e.set_description('rec_phase', -PH2) # current receiver phase
return e

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Scripts/Spin_Alignment_CentreEx/sinsin_centr_res.py Normal file
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# -*- coding: iso-8859-1 -*-
from numpy import *
from scipy.signal import *
from scipy.optimize import *
from os import path, rename
d1s = []
def result():
measurement_range = [0.0, 10e-6]
suffix = '' # output file name's suffix and...
counter = 1 # counter for arrayed experiments
var_key = '' # variable parameter name
# loop over the incoming results:
for timesignal in results:
if not isinstance(timesignal,ADC_Result):
print 'Error during aquisition!'
if isinstance(timesignal, Error_Result):
print timesignal
raise IOError
continue
# read experiment parameters:
pars = timesignal.get_description_dictionary()
if not pars["D1"] in d1s:
measurement = MeasurementResult("Magnetization D1=%e"%(pars["D1"]))
d1s.append(pars["D1"])
# ---------------- digital filter ------------------
# get actual sampling rate of timesignal:
sampling_rate = timesignal.get_sampling_rate()
# get user-defined spectrum width:
spec_width = pars['SW']
# specify cutoff frequency, in relative units:
cutoff = spec_width / sampling_rate
if False: # no filter applied otherwise
# number of filter's coefficients:
numtaps = 29
# use firwin to create a lowpass FIR filter:
fir_coeff = firwin(numtaps, cutoff)
# downsize x according to user-defined spectral window:
skip = int(sampling_rate / spec_width)
timesignal.x = timesignal.x[::skip]
for i in range(2):
# apply the filter to ith channel:
timesignal.y[i] = lfilter(fir_coeff, 1.0, timesignal.y[i])
# zeroize first N-1 "corrupted" samples:
timesignal.y[i][:numtaps-1] = 0.0
# circular left shift of y:
timesignal.y[i] = roll(timesignal.y[i], -(numtaps-1))
# downsize y to user-defined number of samples (SI):
timesignal.y[i] = timesignal.y[i][::skip]
# update the sampling_rate attribute of the signal's:
timesignal.set_sampling_rate(spec_width)
# ----------------------------------------------------
# rotate timesignal according to current receiver's phase:
timesignal.phase(pars['rec_phase'])
# provide timesignal to the display tab:
data['Current scan'] = timesignal
# accumulate...
if not locals().get('accu'):
accu = Accumulation()
# skip dummy scans, if any:
if pars['run'] < 0: continue
# add up:
accu += timesignal
# provide accumulation to the display tab:
data['Accumulation'] = accu
# check how many scans are done:
if accu.n == pars['NS']: # accumulation is complete
# make a copy:
echo = accu + 0
# compute the initial phase of FID:
phi0 = arctan2(echo.y[1][0], echo.y[0][0]) * 180 / pi
if not 'ref' in locals(): ref = phi0
print 'phi0 = ', phi0
# rotate FID to maximize y[0][0]:
#echo.phase(-phi0)
# do FFT:
echo.exp_window(line_broadening=10)
spectrum = echo.fft(samples=2*pars['SI'])
# try zero-order phase correction:
spectrum.phase(-phi0)
# provide spectrum to the display tab:
data['Spectrum'] = spectrum
# check whether it is an arrayed experiment:
var_key = pars.get('VAR_PAR')
if var_key:
# get variable parameter's value:
var_value = pars.get(var_key)
# provide signal recorded with this var_value to the display tab:
data['Accumulation'+"/D1="+ "%e"%(pars["D1"]) + "/" + var_key+"=%e"%(var_value)] = accu
# measure signal intensity vs. var_value:
[start, stop] = accu.get_sampling_rate() * array(measurement_range)
measurement[var_value] = accu.y[0][int(start):int(stop)].mean()
# provide measurement to the display tab:
data[measurement.get_title()] = measurement
# update the file name suffix:
suffix = '_' + str(counter)
counter += 1
# save accu if required:
outfile = pars.get('OUTFILE')
if outfile:
datadir = pars.get('DATADIR')
# write raw data in Simpson format:
filename = datadir+outfile+suffix+'.dat'
if path.exists(filename):
rename(filename, datadir+'~'+outfile+suffix+'.dat')
accu.write_to_simpson(filename)
# write raw data in Tecmag format:
# filename = datadir+outfile+'.tnt'
# accu.write_to_tecmag(filename, nrecords=20)
# write parameters in a text file:
filename = datadir+outfile+suffix+'.par'
if path.exists(filename):
rename(filename, datadir+'~'+outfile+suffix+'.par')
fileobject = open(filename, 'w')
for key in sorted(pars.iterkeys()):
if key=='run': continue
if key=='rec_phase': continue
fileobject.write('%s%s%s'%(key,'=', pars[key]))
fileobject.write('\n')
fileobject.close()
# reset accumulation:
del accu
if var_key == 'D2':
# KWW fit:
xdata = measurement.get_xdata()
ydata = measurement.get_ydata()
[amplitude, rate, beta] = fitfunc(xdata, ydata)
print '%s%02g' % ('Amplitude = ', amplitude)
print '%s%02g' % ('T2 [s] = ', 1./rate)
print '%s%02g' % ('Beta = ', beta)
# update display for the fit:
measurement.y = func([amplitude, rate, beta], xdata)
data[measurement.get_title()] = measurement+0
# the fitting procedure:
def fitfunc(xdata, ydata):
# initialize variable parameters:
try:
# solve Az = b:
A = array((ones(xdata.size/2), xdata[0:xdata.size/2]))
b = log(abs(ydata[0:xdata.size/2]))
z = linalg.lstsq(transpose(A), b)
amplitude = exp(z[0][0])
rate = -z[0][1]
except:
amplitude = abs(ydata[0])
rate = 1./(xdata[-1] - xdata[0])
beta = 1
p0 = [amplitude, rate, beta]
# run least-squares optimization:
plsq = leastsq(residuals, p0, args=(xdata, ydata))
return plsq[0] # best-fit parameters
def residuals(p, xdata, ydata):
return ydata - func(p, xdata)
# here is the function to fit:
def func(p, xdata):
return p[0]*exp(-(p[1]*xdata)**p[2])
pass