initial check-in
This commit is contained in:
Markus Rosenstihl
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# -*- coding: iso-8859-1 -*-
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TXEnableDelay = 2e-6
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TXEnableValue = 0b0001 # TTL line blanking RF amplifier (bit 0)
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TXPulseValue = 0b0010 # TTL line triggering RF pulses (bit 1)
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ADCSensitivity = 2 # voltage span for ADC
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def experiment(): # saturation-recovery with soild-echo detection
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# set up acquisition parameters:
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pars = {}
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pars['P90'] = 2.3e-6 # 90-degree pulse length (s)
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pars['SF'] = 46.7e6 # spectrometer frequency (Hz)
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pars['O1'] = 5.6e3 # offset from SF (Hz)
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pars['SW'] = 10e6 # spectral window (Hz)
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pars['SI'] = 1*1024 # number of acquisition points
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pars['NS'] = 16 # number of scans
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pars['DS'] = 0 # number of dummy scans
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pars['TAU'] = 1 # delay for recovery (s)
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pars['D3'] = 20e-6 # echo delay (s)
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pars['D4'] = 0 # echo pre-aquisition delay (s)
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pars['PHA'] = -30 # receiver phase (degree)
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# -*- these ain't variable: -*-
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pars['NECH'] = 40 # number of saturation pulses
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pars['D1'] = 100e-3 # starting interval in saturation sequence (s)
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pars['D2'] = 1e-4 # end interval in saturation sequence (s)
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pars['DATADIR'] = '/home/fprak/Students/' # data directory
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pars['OUTFILE'] = None # output file name
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# specify a variable parameter (optional):
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pars['VAR_PAR'] = 'TAU' # variable parameter name (a string)
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start = 1e-4 # starting value
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stop = 1e-0 # end value
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steps = 10 # number of values
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log_scale = True # log scale flag
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stag_range = True # staggered range flag
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# check parameters for safety:
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if pars['PHA'] < 0:
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pars['PHA'] = 360 + pars['PHA']
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if pars['P90'] > 20e-6:
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raise Exception("pulse too long!!!")
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# check whether a variable parameter is named:
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var_key = pars.get('VAR_PAR')
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if var_key == 'P90' and (start > 20e-6 or stop > 20e-6):
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raise Exception("Pulse too long!!!")
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if pars['NS']%8 != 0:
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pars['NS'] = int(round(pars['NS'] / 8) + 1) * 8
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print 'Number of scans changed to ',pars['NS'],' due to phase cycling'
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if pars['D1'] < pars['D2']:
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raise Exception("D1 must be greater than D2!")
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sat_length = sum(log_range(pars['D1'],pars['D2'],pars['NECH']))
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if sat_length > 1.:
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raise Exception("saturation sequence too long!!!")
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# start the experiment:
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if var_key:
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# this is an arrayed experiment:
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if log_scale:
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array = log_range(start, stop, steps)
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else:
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array = lin_range(start, stop, steps)
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if stag_range:
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array = staggered_range(array, size = 2)
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# estimate the experiment time:
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if var_key == 'TAU':
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seconds = ((sat_length + pars['D3']*2) * steps + sum(array)) * (pars['NS'] + pars['DS'])
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elif var_key == 'D3':
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seconds = ((sat_length + pars['TAU']) * steps + sum(array)*2) * (pars['NS'] + pars['DS'])
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else:
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seconds = (sat_length + pars['TAU'] + pars['D3']*2) * steps * (pars['NS']+ pars['DS'])
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m, s = divmod(seconds, 60)
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h, m = divmod(m, 60)
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print '%s%02d:%02d:%02d' % ('Experiment time estimated: ', h, m, s)
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# loop for a variable parameter:
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for index, pars[var_key] in enumerate(array):
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print 'Arrayed experiment for '+var_key+': run = '+str(index+1)+\
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' out of '+str(array.size)+': value = '+str(pars[var_key])
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# loop for accumulation:
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for run in xrange(pars['NS']+pars['DS']):
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yield satrec2_experiment(pars, run)
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synchronize()
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else:
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# estimate the experiment time:
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seconds = (sat_length + pars['TAU'] + pars['D3']*2) * (pars['NS']+ pars['DS'])
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m, s = divmod(seconds, 60)
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h, m = divmod(m, 60)
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print '%s%02d:%02d:%02d' % ('Experiment time estimated: ', h, m, s)
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# loop for accumulation:
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for run in xrange(pars['NS']+pars['DS']):
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yield satrec2_experiment(pars, run)
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# the pulse program:
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def satrec2_experiment(pars, run):
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e=Experiment()
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dummy_scans = pars.get('DS')
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if dummy_scans:
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run -= dummy_scans
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pars['PROG'] = 'satrec2_experiment'
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# phase lists:
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pars['PH1'] = [ 0] # saturation pulses
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pars['PH3'] = [ 0, 180, 0, 180, 90, 270, 90, 270] # 1st 90-degree pulse
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pars['PH4'] = [90, 90, 270, 270, 0, 0, 180, 180] # 2nd 90-degree pulse
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pars['PH2'] = [ 0, 180, 0, 180, 90, 270, 90, 270] # receiver
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# read in variables:
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P90 = pars['P90']
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SF = pars['SF']
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O1 = pars['O1']
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NECH = pars['NECH']
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D1 = pars['D1']
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D2 = pars['D2']
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D3 = pars['D3']
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D4 = pars['D4']
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TAU = pars['TAU']
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PH1 = pars['PH1'][run%len(pars['PH1'])]
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PH3 = pars['PH3'][run%len(pars['PH3'])]
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PH4 = pars['PH4'][run%len(pars['PH4'])]
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PH2 = pars['PH2'][run%len(pars['PH2'])]
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PHA = pars['PHA']
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# set variable delay list for saturation pulses:
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vdlist = log_range(D2, D1, NECH-1)
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# set sampling parameters:
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SI = pars['SI']
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SW = pars['SW']
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while SW <= 10e6 and SI < 256*1024:
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SI *= 2
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SW *= 2
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# the pulse sequence:
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# saturation:
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e.set_frequency(SF+O1, phase=PH1) # set frequency and phase for saturation pulses
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e.ttl_pulse(TXEnableDelay, value=TXEnableValue) # enable RF amplifier
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e.ttl_pulse(P90, value=TXEnableValue|TXPulseValue) # apply 90-degree pulse
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for delay in vdlist[::-1]:
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e.wait(delay-P90-TXEnableDelay) # wait for next saturation pulse
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e.ttl_pulse(TXEnableDelay, value=TXEnableValue) # enable RF amplifier
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e.ttl_pulse(P90, value=TXEnableValue|TXPulseValue) # apply 90-degree pulse
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# recovery:
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e.wait(TAU) # wait for tau
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e.set_phase(PH3) # set phase for next pulse
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# echo detection:
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e.ttl_pulse(TXEnableDelay, value=TXEnableValue) # enable RF amplifier
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e.ttl_pulse(P90, value=TXEnableValue|TXPulseValue) # apply 90-degree pulse
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e.wait(D3-P90/2-TXEnableDelay) # echo delay
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e.set_phase(PH4) # set phase for next pulse
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e.ttl_pulse(TXEnableDelay, value=TXEnableValue) # enable RF amplifier
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e.ttl_pulse(P90, value=TXEnableValue|TXPulseValue) # apply 90-degree pulse
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e.set_phase(PHA) # set phase for receiver
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e.wait(D3-P90/2+D4) # echo delay
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e.record(SI, SW, sensitivity=ADCSensitivity) # acquisition
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# write experiment attributes:
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for key in pars.keys():
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e.set_description(key, pars[key]) # pulse sequence parameters
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e.set_description('run', run) # current scan
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e.set_description('rec_phase', -PH2) # current receiver phase
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return e
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@ -0,0 +1,208 @@
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# -*- coding: iso-8859-1 -*-
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from numpy import *
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from scipy.signal import *
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from scipy.optimize import *
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from os import path, rename
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def result():
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measurement = MeasurementResult('Magnetization')
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measurement_range = [0.0, 10e-6]
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measurement_ranging = False
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suffix = '' # output file name's suffix and...
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counter = 1 # counter for arrayed experiments
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var_key = '' # variable parameter name
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# loop over the incoming results:
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for timesignal in results:
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if not isinstance(timesignal,ADC_Result):
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continue
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# read experiment parameters:
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pars = timesignal.get_description_dictionary()
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# ---------------- digital filter ------------------
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# get actual sampling rate of timesignal:
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sampling_rate = timesignal.get_sampling_rate()
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# get user-defined spectrum width:
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spec_width = pars['SW']
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# specify cutoff frequency, in relative units:
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cutoff = spec_width / sampling_rate
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if cutoff < 1: # no filter applied otherwise
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# number of filter's coefficients:
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numtaps = 29
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# use firwin to create a lowpass FIR filter:
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fir_coeff = firwin(numtaps, cutoff)
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# downsize x according to user-defined spectral window:
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skip = int(sampling_rate / spec_width)
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timesignal.x = timesignal.x[::skip]
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for i in range(2):
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# apply the filter to ith channel:
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timesignal.y[i] = lfilter(fir_coeff, 1.0, timesignal.y[i])
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# zeroize first N-1 "corrupted" samples:
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timesignal.y[i][:numtaps-1] = 0.0
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# circular left shift of y:
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timesignal.y[i] = roll(timesignal.y[i], -(numtaps-1))
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# downsize y to user-defined number of samples (SI):
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timesignal.y[i] = timesignal.y[i][::skip]
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# update the sampling_rate attribute of the signal's:
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timesignal.set_sampling_rate(spec_width)
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# ----------------------------------------------------
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# rotate timesignal according to current receiver's phase:
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timesignal.phase(pars['rec_phase'])
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# provide timesignal to the display tab:
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data['Current Scan'] = timesignal
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# accumulate...
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if not locals().get('accu'):
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accu = Accumulation()
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# skip dummy scans, if any:
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if pars['run'] < 0: continue
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# add up:
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accu += timesignal
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# provide accumulation to the display tab:
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data['Accumulation'] = accu
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# check how many scans are done:
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if accu.n == pars['NS']: # accumulation is complete
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# make a copy:
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fid = accu + 0
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# compute the initial phase of FID:
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phi0 = arctan2(fid.y[1][0], fid.y[0][0]) * 180 / pi
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if not locals().get('ref'): ref = phi0
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print 'phi0 = ', phi0
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# rotate FID to maximize Re (optional):
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#fid.phase(-phi0)
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# do FFT:
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fid.exp_window(line_broadening=10)
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spectrum = fid.fft(samples=2*pars['SI'])
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# try zero-order phase correction:
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spectrum.phase(-phi0)
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# provide spectrum to the display tab:
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data['Spectrum'] = spectrum
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# check whether it is an arrayed experiment:
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var_key = pars.get('VAR_PAR')
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if var_key:
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# get variable parameter's value:
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var_value = pars.get(var_key)
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# provide signal recorded with this var_value to the display tab:
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data['Accumulation'+"/"+var_key+"=%e"%(var_value)] = accu
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# measure signal intensity vs. var_value:
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if measurement_ranging == True:
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[start, stop] = accu.get_sampling_rate() * array(measurement_range)
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measurement[var_value] = sum(accu.y[0][int(start):int(stop)])
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else:
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measurement[var_value] = sum(accu.y[0][0:31])
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# provide measurement to the display tab:
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data[measurement.get_title()] = measurement
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# update the file name suffix:
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suffix = '_' + str(counter)
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counter += 1
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# save accu if required:
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outfile = pars.get('OUTFILE')
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if outfile:
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datadir = pars.get('DATADIR')
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# write raw data in Simpson format:
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filename = datadir+outfile+suffix+'.dat'
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if path.exists(filename):
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rename(filename, datadir+'~'+outfile+suffix+'.dat')
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accu.write_to_simpson(filename)
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# write raw data in Tecmag format:
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# filename = datadir+outfile+'.tnt'
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# accu.write_to_tecmag(filename, nrecords=20)
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# write parameters in a text file:
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filename = datadir+outfile+suffix+'.par'
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if path.exists(filename):
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rename(filename, datadir+'~'+outfile+suffix+'.par')
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fileobject = open(filename, 'w')
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for key in sorted(pars.iterkeys()):
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if key=='run': continue
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if key=='rec_phase': continue
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fileobject.write('%s%s%s'%(key,'=', pars[key]))
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fileobject.write('\n')
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fileobject.close()
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# reset accumulation:
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del accu
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if var_key == 'TAU':
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# mono-exponential recovery fit:
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xdata = measurement.get_xdata()
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ydata = measurement.get_ydata()
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[amplitude, rate, offset] = fitfunc(xdata, ydata)
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print '%s%02g' % ('Amplitude = ', amplitude)
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print '%s%02g' % ('T1 [s] = ', 1./rate)
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# update display for the fit:
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measurement.y = func([amplitude, rate, offset], xdata)
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data[measurement.get_title()] = measurement
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# the fitting procedure:
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def fitfunc(xdata, ydata):
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# initialize variable parameters:
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try:
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# solve Az = b:
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A = array((ones(xdata.size/2), xdata[0:xdata.size/2]))
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b = log(abs(mean(ydata[-2:]) - ydata[0:xdata.size/2]))
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z = linalg.lstsq(transpose(A), b)
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amplitude = exp(z[0][0])
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rate = -z[0][1]
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except:
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amplitude = abs(ydata[-1] - ydata[0])
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rate = 1./(xdata[-1] - xdata[0])
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offset = min(ydata)
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p0 = [amplitude, rate, offset]
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# run least-squares optimization:
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plsq = leastsq(residuals, p0, args=(xdata, ydata))
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return plsq[0] # best-fit parameters
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def residuals(p, xdata, ydata):
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return ydata - func(p, xdata)
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# here is the function to fit:
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def func(p, xdata):
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return p[0]*(1-exp(-p[1]*xdata)) + p[2]
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pass
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Reference in New Issue
Block a user