damaris-script-library/Scripts/CPMG/cpmg_res.py

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2015-06-26 12:17:24 +00:00
# -*- coding: iso-8859-1 -*-
from numpy import *
from scipy.signal import *
from scipy.optimize import *
from os import path, rename
def result():
measurement = MeasurementResult('Magnetization')
suffix = '' # output file name's suffix and...
counter = 1 # counter for arrayed experiments
# loop over the incoming results:
for timesignal in results:
if not isinstance(timesignal,ADC_Result):
continue
# read experiment parameters:
pars = timesignal.get_description_dictionary()
# rotate timesignal by 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
# get number of echoes:
num_echoes = pars['NECH']
# downsize accu to one point per echo:
echodecay = accu + 0
echodecay.x = resize(echodecay.x, int(num_echoes))
echodecay.y[0] = resize(echodecay.y[0], int(num_echoes))
echodecay.y[1] = resize(echodecay.y[1], int(num_echoes))
# specify noise level:
if not locals().get('noise'):
echo = accu.get_accu_by_index(0)
noise = 0.1*max(abs(echo.y[0]))
samples = abs(echo.y[0]) > noise
# set echo times and intensities:
for i in range(num_echoes):
# get ith echo:
echo = accu.get_accu_by_index(i)
# set echo timing:
echodecay.x[i] = i*2*pars['TAU']
# set echo value:
echodecay.y[0][i] = sum(echo.y[0][samples]) # the sum of echo points that exeed noise
echodecay.y[1][i] = sum(echo.y[1][samples])
#echodecay.y[0][i] = sum(echo.y[0]) # the sum of all echo points
#echodecay.y[1][i] = sum(echo.y[1])
#echodecay.y[0][i] = echo.y[0][echo.x.size/2] # a middle echo point
#echodecay.y[1][i] = echo.y[1][echo.x.size/2]
# compute a signal's phase:
phi0 = arctan2(echodecay.y[1][0], echodecay.y[0][0]) * 180 / pi
if not locals().get('ref'): ref = phi0
print 'phi0 = ', phi0
# rotate signal to maximize Re (optional):
#echodecay.phase(-phi0)
# provide echo decay to the display tab:
data['Echo Decay'] = echodecay
# fit a mono-exponential function to the echo decay:
[amplitude, rate] = fitfunc(echodecay.x, echodecay.y[0])
print '%s%02g' % ('Amplitude = ', amplitude)
print '%s%02g' % ('T2 [s] = ', 1./rate)
# provide the fit to the display tab:
fit = MeasurementResult('Mono-Exponential Fit')
for i, key in enumerate(echodecay.x):
fit[key] = echodecay.y[0][i]
fit.y = func([amplitude, rate], echodecay.x)
data[fit.get_title()] = fit
# 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 data recorded with different var_value's to the display tab:
data['Accumulation'+"/"+var_key+"=%e"%(var_value)] = accu
data['Echo Decay'+"/"+var_key+"=%e"%(var_value)] = echodecay
data[fit.get_title()+"/"+var_key+"=%e"%(var_value)] = fit
# measure a signal parameter vs. var_value:
measurement[var_value] = amplitude
#measurement[var_value] = sum(echodecay.y[0][:])
#measurement[var_value] = 1./rate
# provide measurement to the display tab:
data[measurement.get_title()] = measurement
# save accu if required:
outfile = pars.get('OUTFILE')
if outfile:
datadir = pars.get('DATADIR')
# write 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 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
# 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])
p0 = [amplitude, rate]
# 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)
pass