def read_mff_data(filePath, indType, startInd, lastInd, hdr):
import numpy as np
from mff.mff_getSummaryInfo import mff_getSummaryInfo
from mff.blockSample2BlockAndSample import blockSample2BlockAndSample
from mff.read_signalN import read_signalN
if hdr != None:
summaryInfo = hdr['orig']
else:
summaryInfo = mff_getSummaryInfo(filePath)
##------------------------------------------------------------------------------
blockNumSamps = summaryInfo['blockNumSamps']
if indType == 'sample':
[startBlockNum, startSamp] = blockSample2BlockAndSample(startInd-1, blockNumSamps)
[lastBlockNum, lastSamp] = blockSample2BlockAndSample(lastInd, blockNumSamps)
blocksInEpoch = range(startBlockNum, lastBlockNum+1)
elif indType == 'epoch':
blocksInEpoch = []
for i in range(startInd-1, lastInd):
blocksInd = range(summaryInfo['epochFirstBlocks'][i]-1,summaryInfo['epochLastBlocks'][i])
blocksInEpoch.extend(blocksInd)
else:
print("Error: indType must to be either 'epoch' or 'sample'")
##--------------------------------------------------------------------------------
dataeeg = read_signalN(filePath, 'signal1.bin', blocksInEpoch)
if summaryInfo['pibFilename'] != []:
datapib = read_signalN(filePath, summaryInfo['pibFilename'], blocksInEpoch)
datalist = []
for i in range(len(dataeeg)):
dataI = np.concatenate((dataeeg[i], datapib[i]), axis=0)
datalist.append(dataI)
else:
datalist = dataeeg
##--------------------------------------------------------------------------------
if indType == 'sample':
if startBlockNum == lastBlockNum :
data = datalist[0][:, startSamp:lastSamp]
elif lastBlockNum-startBlockNum == 1:
datalistS = datalist[0][:,startSamp:]
datalistL = datalist[1][:,:lastSamp]
data = np.concatenate((datalistS, datalistL), axis=1)
else:
datalistS = datalist[0][:,startSamp:]
for j in range(1, len(datalist)-1):
datalistJ = datalist[j]
datalistS = np.concatenate((datalistS, datalistJ), axis=1)
datalistL = datalist[-1][:,:lastSamp]
data = np.concatenate((datalistS, datalistL), axis=1)
elif indType == 'epoch':
if len(datalist) > 1:
if len(set(blockNumSamps)) > 1 :
data = datalist[0]
for j in range(1,len(datalist)):
datalistj = datalist[j]
data = np.concatenate((data, datalistj), axis=1)
else :
data = np.zeros((datalist[0].shape[0], datalist[0].shape[1], len(datalist)))
for j in range(len(datalist)):
data[:,:,j] = datalist[j]
else:
data = datalist[0]
else:
print("Error: indType must to be either 'epoch' or 'sample'")
return data
def read_mff_header(filePath):
# import numpy as np
from xml.dom.minidom import parse
from mff.mff_getSummaryInfo import mff_getSummaryInfo
##---------------------------------------------------------------------------
summaryInfo = mff_getSummaryInfo(filePath)
##---------------------------------------------------------------------------
# Pull header info from the summary info.
nSamplesPre = 0
if summaryInfo['epochType'] =='seg':
nSamples = summaryInfo['epochNumSamps'][0];
nTrials = len(summaryInfo['epochNumSamps'])
# nTrials = summaryInfo['blocks']
# if Time0 is the same for all segments...
if len(set(summaryInfo['epochTime0'])) == 1 :
nSamplesPre = summaryInfo['epochTime0'][0]
else :
nSamples = sum(summaryInfo['epochNumSamps'])
nTrials = 1
##---------------------------------------------------------------------------
# Add the sensor info.
sensorLayoutfile = filePath+'/sensorLayout.xml'
sensorLayoutObj = parse(sensorLayoutfile)
sensors = sensorLayoutObj.getElementsByTagName('sensor')
label = []
chantype = []
chanunit = []
tmpLabel = []
nChans = 0
for sensor in sensors:
sensortype = int(sensor.getElementsByTagName('type')[0].firstChild.data)
if sensortype == 0 or sensortype == 1 :
if sensor.getElementsByTagName('name')[0].firstChild == None:
sn = sensor.getElementsByTagName('number')[0].firstChild.data.encode()
tmpLabel = 'E'+ sn.decode()
# tmpLabel = 'E'+ sensor.getElementsByTagName('number')[0].firstChild.data.encode()
else:
sn = sensor.getElementsByTagName('name')[0].firstChild.data.encode()
tmpLabel = sn.decode()
label.append(tmpLabel)
chantype.append('eeg')
chanunit.append('uV')
nChans = nChans + 1
if nChans != summaryInfo['nChans']:
print("Error. Should never occur.")
##----------------------------------------------------------------------------
if summaryInfo['pibNChans'] > 0 :
pnsSetfile = filePath + '/pnsSet.xml'
pnsSetObj = parse(pnsSetfile)
pnsSensors = pnsSetObj.getElementsByTagName('sensor')
for p in range(summaryInfo['pibNChans']):
tmpLabel = 'pib' + str(p+1)
label.append(tmpLabel)
pnsSensorObj = pnsSensors[p]
chantype.append(pnsSensorObj.getElementsByTagName('name')[0].firstChild.data.encode())
chanunit.append(pnsSensorObj.getElementsByTagName('unit')[0].firstChild.data.encode())
nChans = nChans + summaryInfo['pibNChans']
##-------------------------------------------------------------------------------
header = {'Fs':summaryInfo['sampRate'], 'nChans':nChans,
'nSamplesPre':nSamplesPre, 'nSamples':nSamples,'nTrials':nTrials,'label':label,'chantype':chantype, 'chanunit':chanunit, 'orig':summaryInfo }
return header
def read_mff_event(filePath, hdr):
import numpy as np
from xml.dom.minidom import parse
import os.path
from mff.mff_micros2Sample import mff_micros2Sample
import glob
import os
from mff.mff_getSummaryInfo import mff_getSummaryInfo
from mff.ns2pyTime import ns2pyTime
from mff.mff_micros2Sample import mff_micros2Sample
from mff.samples2EpochSample import samples2EpochSample
if hdr == None :
summaryInfo = mff_getSummaryInfo(filePath)
else:
summaryInfo = hdr['orig']
# Pull the information about the epochs out of the summary info
epochBeginSamps = summaryInfo['epochBeginSamps']
epochNumSamps = summaryInfo['epochNumSamps']
epochFirstBlocks = summaryInfo['epochFirstBlocks']
epochLastBlocks = summaryInfo['epochLastBlocks']
infofile = filePath+'/info.xml'
infotime = parse(infofile)
beginTime = infotime.getElementsByTagName('recordTime')[0].firstChild.data.encode()
bTime = ns2pyTime(beginTime)
numEpochs = len(epochBeginSamps)
events = []
eventInds = np.zeros((numEpochs,2), dtype='i')
eventInd = 0
for p in range(numEpochs):
origp = [0, 0, 'metadata',{}]
eventp = ['break '+ summaryInfo['epochType'],
summaryInfo['epochBeginSamps'][p],
summaryInfo['epochLabels'][p], [],
summaryInfo['epochNumSamps'][p], [], origp ]
events.append(eventp)
eventInds[eventInd,:] = [eventp[1], eventInd]
eventInd = eventInd+1
for file in glob.glob(filePath+"/Events_*.xml"):
eventsfile = file
eventsListObj = parse(eventsfile)
trackname = eventsListObj.getElementsByTagName('name')[0].firstChild.data.encode()
eventsList = eventsListObj.getElementsByTagName('event')
numEvents = eventsList.length
for p in range(numEvents):
theEvent= eventsList[p]
eventTime = theEvent.getElementsByTagName('beginTime')[0].firstChild.data.encode()
eTime = ns2pyTime(eventTime)
eventTimeInMicros = (eTime-bTime).microseconds
out = mff_micros2Sample(eventTimeInMicros,summaryInfo['sampRate'])
eventTimeInSamples = int(out[0])
sampleRemainder = int(out[1])
eventTimeInEpochSamples= samples2EpochSample(eventTimeInSamples, epochBeginSamps, epochNumSamps)
if eventTimeInEpochSamples >= 0:
keylist = theEvent.getElementsByTagName('key')
eventkeycount = len(keylist)
keyp = []
for q in range(eventkeycount):
theKey = keylist[q]
theKeyCode = theKey.getElementsByTagName('keyCode')[0].firstChild.data.encode()
theKeyData = theKey.getElementsByTagName('data')[0].firstChild.data.encode()
theKeyData1 = theKey.getElementsByTagName('data')
theKeyData0 = theKeyData1[0] # print theKeyData0.toxml()
a = theKeyData0.attributes["dataType"]
theKeyDatatype = a.value.encode()
theKeyq = [theKeyCode, int(theKeyData), theKeyDatatype,'']
keyp.append(theKeyq)
duration = int(theEvent.getElementsByTagName('duration')[0].firstChild.data.encode())
out = mff_micros2Sample(duration, summaryInfo['sampRate'])
origp =[sampleRemainder, int(out[1]), trackname, keyp]
eventp=[theEvent.getElementsByTagName('code')[0].firstChild.data.encode(),eventTimeInEpochSamples,0, [], int(out[0]), [], origp]
events.append(eventp)
eventIndp = np.array([eventp[1], eventInd], dtype='i').reshape((1,2))
eventInds = np.concatenate((eventInds,eventIndp), axis=0)
eventInd = eventInd+1
eventInds0 = eventInds[eventInds[:,0].argsort()]
sortedEvents = events
for p in range(eventInd):
nextEventInd = eventInds0[p,1]
sortedEvents[p] = events[nextEventInd]
events = sortedEvents
return events
def read_mff_event(filePath, hdr):
import numpy as np
from xml.dom.minidom import parse
import os.path
from mff.mff_micros2Sample import mff_micros2Sample
import glob
import os
from mff.mff_getSummaryInfo import mff_getSummaryInfo
from mff.ns2pyTime import ns2pyTime
from mff.mff_micros2Sample import mff_micros2Sample
from mff.samples2EpochSample import samples2EpochSample
if hdr == None:
summaryInfo = mff_getSummaryInfo(filePath)
else:
summaryInfo = hdr['orig']
# Pull the information about the epochs out of the summary info
epochBeginSamps = summaryInfo['epochBeginSamps']
epochNumSamps = summaryInfo['epochNumSamps']
epochFirstBlocks = summaryInfo['epochFirstBlocks']
epochLastBlocks = summaryInfo['epochLastBlocks']
infofile = filePath + '/info.xml'
infotime = parse(infofile)
beginTime = infotime.getElementsByTagName(
'recordTime')[0].firstChild.data.encode()
bTime = ns2pyTime(beginTime)
numEpochs = len(epochBeginSamps)
events = []
eventInds = np.zeros((numEpochs, 2), dtype='i')
eventInd = 0
for p in range(numEpochs):
origp = [0, 0, 'metadata', {}]
eventp = [
'break ' + summaryInfo['epochType'],
summaryInfo['epochBeginSamps'][p], summaryInfo['epochLabels'][p],
[], summaryInfo['epochNumSamps'][p], [], origp
]
events.append(eventp)
eventInds[eventInd, :] = [eventp[1], eventInd]
eventInd = eventInd + 1
for file in glob.glob(filePath + "/Events_*.xml"):
eventsfile = file
eventsListObj = parse(eventsfile)
trackname = eventsListObj.getElementsByTagName(
'name')[0].firstChild.data.encode()
eventsList = eventsListObj.getElementsByTagName('event')
numEvents = eventsList.length
for p in range(numEvents):
theEvent = eventsList[p]
eventTime = theEvent.getElementsByTagName(
'beginTime')[0].firstChild.data.encode()
eTime = ns2pyTime(eventTime)
eventTimeInMicros = (eTime - bTime).microseconds
out = mff_micros2Sample(eventTimeInMicros, summaryInfo['sampRate'])
eventTimeInSamples = int(out[0])
sampleRemainder = int(out[1])
eventTimeInEpochSamples = samples2EpochSample(eventTimeInSamples,
epochBeginSamps,
epochNumSamps)
if eventTimeInEpochSamples >= 0:
keylist = theEvent.getElementsByTagName('key')
eventkeycount = len(keylist)
keyp = []
for q in range(eventkeycount):
theKey = keylist[q]
theKeyCode = theKey.getElementsByTagName(
'keyCode')[0].firstChild.data.encode()
theKeyData = theKey.getElementsByTagName(
'data')[0].firstChild.data.encode()
theKeyData1 = theKey.getElementsByTagName('data')
theKeyData0 = theKeyData1[0] # print theKeyData0.toxml()
a = theKeyData0.attributes["dataType"]
theKeyDatatype = a.value.encode()
theKeyq = [theKeyCode, int(theKeyData), theKeyDatatype, '']
keyp.append(theKeyq)
duration = int(
theEvent.getElementsByTagName('duration')
[0].firstChild.data.encode())
out = mff_micros2Sample(duration, summaryInfo['sampRate'])
origp = [sampleRemainder, int(out[1]), trackname, keyp]
eventp = [
theEvent.getElementsByTagName('code')
[0].firstChild.data.encode(), eventTimeInEpochSamples, 0, [],
int(out[0]), [], origp
]
events.append(eventp)
eventIndp = np.array([eventp[1], eventInd], dtype='i').reshape(
(1, 2))
eventInds = np.concatenate((eventInds, eventIndp), axis=0)
eventInd = eventInd + 1
eventInds0 = eventInds[eventInds[:, 0].argsort()]
sortedEvents = events
for p in range(eventInd):
nextEventInd = eventInds0[p, 1]
sortedEvents[p] = events[nextEventInd]
events = sortedEvents
return events
def read_mff_data(filePath, indType, startInd, lastInd, hdr):
import numpy as np
from mff.mff_getSummaryInfo import mff_getSummaryInfo
from mff.blockSample2BlockAndSample import blockSample2BlockAndSample
from mff.read_signalN import read_signalN
if hdr != None:
summaryInfo = hdr['orig']
else:
summaryInfo = mff_getSummaryInfo(filePath)
##------------------------------------------------------------------------------
blockNumSamps = summaryInfo['blockNumSamps']
if indType == 'sample':
[startBlockNum,
startSamp] = blockSample2BlockAndSample(startInd - 1, blockNumSamps)
[lastBlockNum,
lastSamp] = blockSample2BlockAndSample(lastInd, blockNumSamps)
blocksInEpoch = range(startBlockNum, lastBlockNum + 1)
elif indType == 'epoch':
blocksInEpoch = []
for i in range(startInd - 1, lastInd):
blocksInd = range(summaryInfo['epochFirstBlocks'][i] - 1,
summaryInfo['epochLastBlocks'][i])
blocksInEpoch.extend(blocksInd)
else:
print("Error: indType must to be either 'epoch' or 'sample'")
##--------------------------------------------------------------------------------
dataeeg = read_signalN(filePath, 'signal1.bin', blocksInEpoch)
if summaryInfo['pibFilename'] != []:
datapib = read_signalN(filePath, summaryInfo['pibFilename'],
blocksInEpoch)
datalist = []
for i in range(len(dataeeg)):
dataI = np.concatenate((dataeeg[i], datapib[i]), axis=0)
datalist.append(dataI)
else:
datalist = dataeeg
##--------------------------------------------------------------------------------
if indType == 'sample':
if startBlockNum == lastBlockNum:
data = datalist[0][:, startSamp:lastSamp]
elif lastBlockNum - startBlockNum == 1:
datalistS = datalist[0][:, startSamp:]
datalistL = datalist[1][:, :lastSamp]
data = np.concatenate((datalistS, datalistL), axis=1)
else:
datalistS = datalist[0][:, startSamp:]
for j in range(1, len(datalist) - 1):
datalistJ = datalist[j]
datalistS = np.concatenate((datalistS, datalistJ), axis=1)
datalistL = datalist[-1][:, :lastSamp]
data = np.concatenate((datalistS, datalistL), axis=1)
elif indType == 'epoch':
if len(datalist) > 1:
if len(set(blockNumSamps)) > 1:
data = datalist[0]
for j in range(1, len(datalist)):
datalistj = datalist[j]
data = np.concatenate((data, datalistj), axis=1)
else:
data = np.zeros((datalist[0].shape[0], datalist[0].shape[1],
len(datalist)))
for j in range(len(datalist)):
data[:, :, j] = datalist[j]
else:
data = datalist[0]
else:
print("Error: indType must to be either 'epoch' or 'sample'")
return data