Пример #1
0
def getderivedlabels(datafile):
    ch = channel.index(datafile, 'derived')
    chdict = {}
    for i in ch.chnumber:
        chdict[ch.cfgchname[ch.cfgchannumber == i][0]] = i

    return ch, chdict
Пример #2
0
 def __init__(self, datapdf, chlabel):
     ch=channel.index(datapdf, 'meg')
     chind=ch.channelindexhdr[ch.channelsortedlabels == chlabel]
     self.d=data.read(datapdf)
     self.d.getdata(0, self.d.pnts_in_file, chind)
     self.d.data_block=offset.correct(self.d.data_block)
     print self.d.data_block.shape
     self.p=pdf.read(datapdf)
     self.ext = 'pymtimef'
Пример #3
0
 def coilpower(self, event): # wxGlade: MyFrame.<event_handler>
     print "Event handler `coilpower'  "
     try:
         n = nearest(self.freq, 165)
     except AttributeError:
         print 'no power... running for you'
         self.pow,self.freq = functions.psd(self.datapdf)
     n = nearest(self.freq, 165)
     self.ch = channel.index(self.datapdf, 'meg')
     megcontour.display(self.pow[int(n[0]),:], self.ch.chanlocs)
Пример #4
0
 def badchannels(self, event): # wxGlade: MyFrame.<event_handler>
     print "Event handler `badchannels'  "
     try:
         bad = badchannels.calc(datapdf, self.pow, ch,thresh=5, chfreq='yes', freqarray=self.freq, maxhz=200,powernotch='yes', minhz=4)
     except NameError:
         print 'no power... running for you'
         self.pow,self.freq = functions.psd(self.datapdf)
         self.ch = channel.index(self.datapdf, 'meg')
         bad = badchannels.calc(self.datapdf, self.pow, self.ch, thresh=5, chfreq='yes', freqarray=self.freq, maxhz=200,powernotch='yes', minhz=4)
     figure(1,figsize=(5,10))
     subplot(2,1,1);plot(bad[3]);title('channel power ratio to family');
     subplot(2,1,2);megcontour.display(bad[3], self.ch.chanlocs)
Пример #5
0
def psd(datapdf):
    d = data.read(datapdf)
    nfft=256*2
    ch = channel.index(datapdf, 'meg')
    d.getdata(0, d.pnts_in_file, ch.channelindexhdr)
    data2anz = d.data_block
    #data2anz = result['attenddata']
    pow = zeros([(nfft/2)+1, size(data2anz,1)])
    comp = zeros([(nfft/2)+1, size(data2anz,1)], complex_)
    #fftreal = (zeros([(nfft/2)+1, size(attenddata,1)]))

    for eachch in range(0, size(data2anz,1)):
        p,f,i = spectral.psd(data2anz[:,eachch], NFFT=nfft, Fs=1/ d.hdr.header_data.sample_period)#, noverlap=200)#, detrend=matplotlib.pylab.detrend_mean)
        #p,f,i = spectral.psd(data[:,eachch], NFFT=nfft, Fs=1/ d.hdr.header_data.sample_period )
        pow[:,eachch] = p
        comp[:,eachch] = i
        #fftreal[:,eachch] = r
    logpow = 10*log10(pow)
    freq=f
    return logpow, freq
Пример #6
0
def getdata(datapath, chtype):
    ch = channel.index(datapath, chtype)
    d = data.read(datapath)
    labels = ch.chlabel[ch.channelsind]
    d.getdata(0, d.pnts_in_file, ch.channelsind)
    return d, labels