removed op_ from all experiments
This commit is contained in:
Markus Rosenstihl
170
Scripts/EXSY_2H/exsy2h_res.py
Normal file
170
Scripts/EXSY_2H/exsy2h_res.py
Normal file
@@ -0,0 +1,170 @@
|
||||
# -*- coding: iso-8859-1 -*-
|
||||
|
||||
from numpy import *
|
||||
from scipy.signal import *
|
||||
from scipy.optimize import *
|
||||
from scipy.fftpack import fft, ifft
|
||||
from os import path, rename
|
||||
|
||||
def result():
|
||||
|
||||
measurement = MeasurementResult('Magnetization')
|
||||
|
||||
measurement_range = [0.0, 10e-6]
|
||||
measurement_ranging = False
|
||||
|
||||
suffix = '' # output file name's suffix and...
|
||||
counter = 0 # counter for arrayed 2D experiments
|
||||
# npts = 0
|
||||
|
||||
# loop over the incoming results:
|
||||
for timesignal in results:
|
||||
if not isinstance(timesignal,ADC_Result):
|
||||
continue
|
||||
|
||||
# read experiment parameters:
|
||||
pars = timesignal.get_description_dictionary()
|
||||
|
||||
# ---------------- 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 cutoff < 1: # otherwise no filter applied
|
||||
|
||||
# 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 whether accumulation is complete:
|
||||
# ------------------------------------------------------------------------------------
|
||||
# The hypercomplex technique implies recording two data sets for each t1 value.
|
||||
# One dataset (a cosine-modulated signal) is stored in odd records as Re, while
|
||||
# the other dataset (a sine-modulated signal) in even records as Im, totally 2*SI1
|
||||
# records. Henceforth, accu represents one such a record.
|
||||
# ------------------------------------------------------------------------------------
|
||||
if accu.n == pars['NS']:
|
||||
# compute the initial phase of FID:
|
||||
phi0 = arctan2(accu.y[1][0], accu.y[0][0]) * 180 / pi
|
||||
if not 'ref' in locals(): ref = phi0
|
||||
print 'phi0 = ', phi0
|
||||
|
||||
# rotate every other record by 90<39> so that States algorithm is applicable:
|
||||
rec = (accu.job_id/accu.n)%(2*pars['SI1']) + 1
|
||||
if rec%2 == 0:
|
||||
accu.phase(90)
|
||||
coeff = 1.5
|
||||
accu.y[0] *= coeff # XY-balancing
|
||||
accu.y[1] *= coeff
|
||||
|
||||
else: # baseline correction )))))
|
||||
tmp = fft(accu.y[0]+1j*accu.y[1])
|
||||
[start, stop] = len(accu.y[0])*array([0.4, 0.6])
|
||||
tmp -= mean(tmp.real[start:stop])
|
||||
tmp = ifft(tmp)
|
||||
accu.y[0] = tmp.real
|
||||
accu.y[1] = tmp.imag
|
||||
|
||||
# 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'+"/"+var_key+"=%e"%(var_value)] = accu
|
||||
|
||||
# measure signal intensity vs. var_value:
|
||||
if measurement_ranging == True:
|
||||
[start, stop] = accu.get_sampling_rate() * array(measurement_range)
|
||||
measurement[var_value] = sum(accu.y[0][int(start):int(stop)])
|
||||
|
||||
else:
|
||||
# measurement[var_value] = sum(accu.y[0][0:31])
|
||||
measurement[var_value+counter*1e-6] = sum(accu.y[0][0:31])
|
||||
|
||||
# provide measurement to the display tab:
|
||||
data[measurement.get_title()] = measurement
|
||||
|
||||
# update the file name suffix:
|
||||
counter2D = counter/(2*pars['SI1'])+1
|
||||
suffix = '_' + str(counter2D)
|
||||
counter += 1
|
||||
|
||||
# save accu if required:
|
||||
outfile = pars.get('OUTFILE')
|
||||
if outfile:
|
||||
datadir = pars.get('DATADIR')
|
||||
|
||||
# write raw data in Tecmag format:
|
||||
filename = datadir+outfile+suffix+'.tnt'
|
||||
accu.write_to_tecmag(filename,\
|
||||
nrecords=2*pars['SI1'],\
|
||||
frequency=pars['SW']+pars['O1'])
|
||||
|
||||
# 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
|
||||
|
||||
pass
|
||||
Reference in New Issue
Block a user