def getnonzerosind(datafile, chdict, ch): d = data.read(datafile) d.getdata(0, d.pnts_in_file, ch.chindex) gofdata = d.data_block[:,ch.chnumber == chdict['GoF']]; #use the GOF channel, as if it is zero there shouldn't be any dipole at this point ind = nonzero(gofdata[:,0]) return ind, d
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'
def __init__(self, datapdf): if os.path.isfile(datapdf)==True: print('reading pdf', os.path.abspath(datapdf)) self.data = data.read(datapdf) print('reading pdf header', os.path.abspath(datapdf)) self.hdr=header.read(datapdf); #reading withing data module if os.path.isfile(os.path.dirname(datapdf)+'/config')==True: print('found config file in same dir. Reading config') self.cfg=config.read(os.path.dirname(datapdf)+'/config'); if os.path.isfile(os.path.dirname(datapdf)+'/hs_file')==True: print('found headshape file in same dir. Reading headshape') self.hs=headshape.read(os.path.dirname(datapdf)+'/hs_file'); #self.results = self.__class__ else: print('no file found')
def psd(datapdf): d = data.read(result["path"]) nfft = 256 * 2 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
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
def setparams(self, datatemplate, trig=None): #since header written at end, need to provide data template of same acquisiiton '''c=chunk(datapdf) c.setparams(datatemplate,trigchannel) ex. c.setparams(datafilename, 'TRIGGER') or 'RESPONSE' ''' self.trig=trig if self.trig==None: print 'no triggers will be detected, so no realtime averaging and such' else: print 'setting detection of channel',self.trig #for debugging using fidpos as positions to seek in file #090324 fix conf = read(datatemplate) #conf=config(datatemplate) self.step=conf.time_slice_size self.numch=conf.total_chans self.dataprecision=conf.dataprecision '''set data parameters''' print 'test' self.timelist.append(time.time()) self.data_blockall=zeros((1,self.numch))
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