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
