def readNtwFile(self):
"""
read network file
"""
filename = os.path.join(self.filePath, self.fileName)
with open(filename) as f:
self.text = f.read()
print("Reading network file : ", filename)
# extract useful lines from the the text
lineArr = util.cleanupFileText(self.text)
i = 0
while i < len(lineArr):
line = lineArr[i]
if len(line) < 2:
i = i + 1
continue
if line[0] == "LIST_NEURONS:":
i = self.extractNeurons(i + 1, lineArr)
elif line[0] == "CHEMSYN:":
i = self.extractChemSynapses(i + 1, lineArr)
elif line[0] == "ELCTRCPL:":
i = self.extractElecSynapses(i + 1, lineArr)
elif line[0] == "MODULSYN:":
i = self.extractModularySynapses(i + 1, lineArr)
else:
i = i + 1
def readModByRegulatorFile(self):
"""
read fBR file
"""
filename = os.path.join(self.filePath, self.fileName)
print("FBR FIle", filename)
with open(filename) as f:
self.text = f.read()
print("Reading fBR file : ", filename)
lineArr = util.cleanupFileText(self.text)
i = 0
while i < len(lineArr):
line = lineArr[i]
if len(line) < 2:
i = i + 1
continue
if re.search("^fBR", line[0]) is not None:
self.fBRType = self.extractfBR(i + 1, lineArr)
if re.search("^BR", line[0]) is not None:
self.BRType, self.BR_a = self.extractBR(i + 1, lineArr)
i = i + 1
pass
def readSMFile(self):
"""
read .sm file
"""
filename = os.path.join(self.filePath, self.fileName)
with open(filename) as f:
self.text = f.read()
print("Reading second messenger file : ", filename)
lineArr = util.cleanupFileText(self.text)
i = 0
while i < len(lineArr):
line = lineArr[i]
if len(line) < 2:
i = i + 1
continue
if re.search("^Csm", line[0]) is not None:
self.smType, self.iv, self.tau = self.extractSM(
i + 1, lineArr)
if re.search("^xCsm", line[0]) is not None:
self.xCsmType = lineArr[i + 1][0]
i = i + 1
pass
def readfATFile(self):
"""
read SNNAP time dependent activation function of chemical synapse
"""
fileName = os.path.join(self.filePath,self.fAtFileName)
with open(fileName) as f:
self.text = f.read()
# extract useful lines from the the text
lineArr = util.cleanupFileText(self.text)
i=0
while i < len(lineArr):
line = lineArr[i]
if re.search("^fAt", line[0]) is not None:
self.fATType = lineArr[i+1][0]
if self.fATType in ['3', '5', '6']:
self.fAT_a = self.findNextFeature(i+1, lineArr, feature="a")
#self.fAT_b = self.findNextFeature(i+1, lineArr, feature="b")
if self.fATType in ['3', '4', '5']:
self.fAT_b = self.findNextFeature(i+1, lineArr, feature="b")
if re.search("^At", line[0]) is not None:
self.extractAt(i, lineArr)
i = i+1
def readVDGFile(self):
filename = os.path.join(self.filePath,self.fileName)
with open(filename) as f:
self.text = f.read()
print("Reading .vdg file : ", filename)
lineArr = util.cleanupFileText(self.text)
i = 0
while i< len(lineArr):
line = lineArr[i]
if re.search("^Ivd", line[0]) is not None:
self.extractIvd(i+1, lineArr)
i = i+1
return
def readNeuronFile(self):
"""
read .neu file
"""
filename = os.path.join(self.filePath, self.fileName)
with open(filename) as f:
self.text = f.read()
print("Reading neuron file : ", filename)
lineArr = util.cleanupFileText(self.text)
i = 0
while i < len(lineArr):
line = lineArr[i]
if len(line) < 2:
i = i + 1
continue
if re.search("THRESHOLD", line[0]) is not None:
self.treshold = self.extractNeuronsFeature(i + 1, line[0])
elif re.search("SPIKDUR", line[0]) is not None:
self.spikeDur = self.extractNeuronsFeature(i + 1, line[0])
elif re.search("VMINIT", line[0]) is not None:
self.vmInit = self.extractNeuronsFeature(i + 1, line[0])
elif re.search("CM", line[0]) is not None:
self.cm = self.extractNeuronsFeature(i + 1, line[0])
elif re.search("^MEM_AREA", line[0]) is not None:
self.memAreaType = lineArr[i + 1][0]
elif line[0] == "CONDUCTANCES:":
i = self.extractConductance(i + 1, lineArr)
elif line[0] == "LIST_ION:":
i = self.extractIonPools(i + 1, lineArr)
elif line[0] == "LIST_SM:":
i = self.extractSMPools(i + 1, lineArr)
elif line[0] == "CURRENT_TO_ION:":
i = self.extractCurr2Ions(i + 1, lineArr)
elif line[0] == "COND_BY_ION:":
i = self.extractConductanceByIon(i + 1, lineArr)
elif line[0] == "COND_BY_SM:":
i = self.extractConductanceBySM(i + 1, lineArr)
i = i + 1
def readTrtFile(self):
filename = os.path.join(self.filePath, self.fileName)
with open(filename) as f:
self.text = f.read()
print "Reading treatment file : ", filename
lineArr = util.cleanupFileText(self.text)
i = 0
while i < len(lineArr):
line = lineArr[i]
if len(line) < 2:
i = i + 1
continue
if re.search("CURNT_INJ", line[0]) is not None:
self.extractCurntInj(i, lineArr)
i = i + 1
def read_BFile(self):
filename = os.path.join(self.filePath,self.B)
with open(filename) as f:
self.text = f.read()
print("Reading .B file : ", filename)
lineArr = util.cleanupFileText(self.text)
i = 0
while i< len(lineArr):
line = lineArr[i]
if re.search("^B", line[0]) is not None:
self.BType, self.B_IV = self.extractActivation_timeConst(i+1, lineArr)
if re.search("^ssB", line[0]) is not None:
self.ssBType, self.ssB_h, self.ssB_s, self.ssB_p, self.ssB_Bn = self.extractSteadyState(i+1, lineArr, 0)
if self.BType == "2" and re.search("^tB", line[0]) is not None:
self.tBType, self.tB_tx, self.tB_tn, self.tB_h1, self.tB_h2, self.tB_s1, self.tB_s2, self.tB_p1, self.tB_p2 = self.extractTimeConstant(i+1, lineArr)
i = i+1
return
def readXtFile(self):
"""
read .Xt file
"""
fileName = os.path.join(self.filePath,self.XtFileName)
with open(fileName) as f:
self.text = f.read()
# extract useful lines from the the text
lineArr = util.cleanupFileText(self.text)
i=0
while i < len(lineArr):
line = lineArr[i]
if re.search("^Xt", line[0]) is not None:
self.XtType = lineArr[i+1][0]
if self.XtType == "3":
self.extractPSM(i+1, lineArr)
i = i+1
def read_AFile(self):
filename = os.path.join(self.filePath,self.A)
with open(filename) as f:
self.text = f.read()
print "Reading .A file : ", filename
lineArr = util.cleanupFileText(self.text)
i = 0
while i< len(lineArr):
line = lineArr[i]
if re.search("^A", line[0]) is not None:
self.AType, self.A_IV = self.extractActivation_timeConst(i+1, lineArr)
if re.search("^ssA", line[0]) is not None:
self.ssAType, self.ssA_h, self.ssA_s, self.ssA_p, self.ssA_An = self.extractSteadyState(i+1, lineArr, 1)
if re.search("^tA", line[0]) is not None:
self.tAType, self.tA_tx, self.tA_tn, self.tA_h1, self.tA_h2, self.tA_s1, self.tA_s2, self.tA_p1, self.tA_p2 = self.extractTimeConstant(i+1, lineArr)
i = i+1
return
def read_hFile(self):
filename = os.path.join(self.filePath,self.h)
with open(filename) as f:
self.text = f.read()
print("Reading .h file : ", filename)
lineArr = util.cleanupFileText(self.text)
i = 0
while i< len(lineArr):
line = lineArr[i]
if re.search("^h", line[0]) is not None:
self.hType, self.h_IV, self.h_L = self.extractActivation_rateConst(i+1, lineArr)
if re.search("^ah", line[0]) is not None:
self.ahType, self.ah_A, self.ah_B, self.ah_C, self.ah_D = self.extractRateParameter(i+1, lineArr)
if re.search("^bh", line[0]) is not None:
self.bhType, self.bh_A, self.bh_B, self.bh_C, self.bh_D = self.extractRateParameter(i+1, lineArr)
i = i+1
return
def read_mFile(self):
filename = os.path.join(self.filePath,self.m)
with open(filename) as f:
self.text = f.read()
print "Reading .m file : ", filename
lineArr = util.cleanupFileText(self.text)
i = 0
while i< len(lineArr):
line = lineArr[i]
if re.search("^m", line[0]) is not None:
self.mType, self.m_IV, self.m_L = self.extractActivation_rateConst(i+1, lineArr)
if re.search("^am", line[0]) is not None:
self.amType, self.am_A, self.am_B, self.am_C, self.am_D = self.extractRateParameter(i+1, lineArr)
if re.search("^bm", line[0]) is not None:
self.bmType, self.bm_A, self.bm_B, self.bm_C, self.bm_D = self.extractRateParameter(i+1, lineArr)
i = i+1
return
def readCSFile(self):
"""
read SNNAP chemical synapse (.cs) file
"""
fileName = os.path.join(self.filePath,self.fileName)
with open(fileName) as f:
self.text = f.read()
print("Reading chemical synapse file : ", fileName)
# extract useful lines from the the text
lineArr = util.cleanupFileText(self.text)
i=0
while i < len(lineArr):
line = lineArr[i]
if len(line) < 2:
i = i+1
continue
if re.search("Ics", line[0]) is not None:
self.extractCS(i+1, lineArr)
i = i+1
def readSimFile(self, filePath, fileName):
"""
read simulation file
"""
fileName = os.path.join(filePath,fileName)
with open(fileName) as f:
self.text = f.read()
print("Reading simulaiton file : ", fileName)
# extract useful lines from the the text
lineArr = util.cleanupFileText(self.text)
i = 0
while i < len(lineArr):
l = lineArr[i]
# get 1st word fo the line
word1 = l[0][:-1]
if word1 in self.parameters.keys():
i = self.extractParam(i, lineArr, word1)
else:
i = i+1
def readESFile(self):
"""
read electrical coupling file
"""
filename = os.path.join(self.filePath, self.fileName)
with open(filename) as f:
self.text = f.read()
print("Reading electrical coupling file : ", filename)
# extract useful lines from the the text
lineArr = util.cleanupFileText(self.text)
i = 0
while i < len(lineArr):
line = lineArr[i]
if len(lineArr[i]) > 1:
if not re.search("G1", lineArr[i][1]) is None:
self.g1 = lineArr[i][0]
if not re.search("G2", lineArr[i][1]) is None:
self.g2 = lineArr[i][0]
i = i + 1
return
def readNeuronFile(self):
"""
read .neu file
"""
filename = os.path.join(self.filePath,self.fileName)
with open(filename) as f:
self.text = f.read()
print "Reading neuron file : ", filename
lineArr = util.cleanupFileText(self.text)
i = 0
while i< len(lineArr):
line = lineArr[i]
if len(line) < 2:
i = i+1
continue
if re.search("THRESHOLD", line[0]) is not None:
self.treshold = self.extractNeuronsFeature(i+1, line[0])
elif re.search("SPIKDUR", line[0]) is not None:
self.spikeDur = self.extractNeuronsFeature(i+1, line[0])
elif re.search("VMINIT", line[0]) is not None:
self.vmInit = self.extractNeuronsFeature(i+1, line[0])
elif re.search("CM", line[0]) is not None:
self.cm = self.extractNeuronsFeature(i+1, line[0])
elif re.search("^MEM_AREA", line[0]) is not None:
self.memAreaType = lineArr[i+1][0]
elif re.search("Name of conductance", line[1]) is not None:
self.extractConductance(i, lineArr)
i = i+1
def readIonFile(self):
"""
read .ion file
"""
filename = os.path.join(self.filePath, self.fileName)
with open(filename) as f:
self.text = f.read()
print("Reading ion file : ", filename)
lineArr = util.cleanupFileText(self.text)
i = 0
while i < len(lineArr):
line = lineArr[i]
if len(line) < 2:
i = i + 1
continue
if re.search("Cion", line[0]) is not None:
self.cionType, self.k1, self.k2 = self.extractIon(
i + 1, lineArr)
i = i + 1
pass
