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clmodel.py
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clmodel.py
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##################################
#
# clmodel.py
# Copyright (C) Louisiana State University, Health Sciences Center
# Written by 2011-2013 Ruben Tikidji-Hamburyan <rth@nisms.krinc.ru>
#
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or (at
# your option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE, GOOD TITLE or
# NON INFRINGEMENT. See the GNU General Public License for more
# details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
#
###################################
import sys, csv
import random as rnd
from datetime import time
import clprc, clrprc, clpopulation, clneurons, clconnection, clnoisyneurons, clrepeaters
class clmodel:
class file:
def __init__(self,attr={}):
self.format, self.watch, self.name, self.connections = "excel","last period","data.csv", "on"
#### Test for implicit attributes:
for atr in attr.keys():
if atr == "format": continue
if atr == "watch": continue
if atr == "name": continue
if atr == "connections": continue
sys.stderr.write("Unexpected attribute \'%s\'for tag <output>\nABORT\n\n"%atr)
sys.exit(1)
if attr.get("format"):
self.format = attr["format"]
if attr.get("watch"):
self.watch = attr["watch"]
if attr.get("name"):
self.name = attr["name"]
if attr.get("connections"):
self.connections = attr["connections"]
if self.format == "xml":
if self.name[-4:] != ".xml" :
self.name += ".xml"
self.__fd = open(self.name,"w")
self.__fd.write("<?xml version=\"1.0\" encoding=\"utf-8\" ?>\n")
self.__fd.write("<!--Automatically generated by uniPRCsim-->\n")
self.__fd.write("<!-- Version 0.01.01 (preAlpha) -->\n")
self.__fd.write("<data watch=\"%s\">\n"%self.watch)
elif self.format == "data":
if self.name[-4:] != ".dat" :
self.name += ".dat"
self.__fd = open(self.name,"w")
self.__fd.write("###Automatically generated by uniPRCsim###\n")
self.__fd.write("### Version 0.01.01 (preAlpha) ###\n")
self.__fd.write("### Watch % 18s ###\n"%self.watch)
else:
if self.name[-4:] != ".csv" :
self.name += ".csv"
self.__hfd = open(self.name,"w")
self.__fd = csv.writer(self.__hfd, dialect=self.format)
self.__fd.writerow(["###Automatically generated by uniPRCsim###"])
self.__fd.writerow(["### Version 0.01.01 (preAlpha) ###"])
self.__fd.writerow(["### Watch % 18s ###"%self.watch])
def writeheader(self,body,attr={}):
if self.format == "xml":
line = "<header "
for atr in attr.items():
line += "%s=\"%s\" "%atr
line += ">"
for bdy in body:
line += "%s,"%bdy
line = line[:-1] + "</header>\n"
self.__fd.write(line)
elif self.format == "data":
line=""
if attr.get("time",0):
line += "time"
del attr["time"]
for atr in attr.items():
if atr[0] == "time" : continue
line +=" "+atr[0]
for bdy in body:
line +=" "+bdy
self.__fd.write(line+"\n")
else:
line=[]
if attr.get("time",0):
line.append("time")
del attr["time"]
for atr in attr.items():
if atr[0] == "time" : continue
line.append(atr[0])
for bdy in body:
line.append(bdy)
self.__fd.writerow(line)
def write(self, body,attr={}):
if self.format == "xml":
line = "<sample "
for atr in attr.items():
line += "%s=\"%s\" "%atr
line += ">"
if self.watch == "spikes":
for bdy in body:
line += "%d,"%bdy
else:
for bdy in body:
line += "%g,"%bdy
line = line[:-1] + "</sample>\n"
self.__fd.write(line)
elif self.format == "data":
line=""
if attr.get("time",0):
line="%7.5f"%attr["time"]
del attr["time"]
for atr in attr.items():
if atr[0] == "time" : continue
line += " %7.5f"%atr[1]
if self.watch == "spikes":
for bdy in body:
line += " %d"%bdy
else:
for bdy in body:
line += " %g"%bdy
self.__fd.write(line+"\n")
else:
line=[]
if attr.get("time",-1) >= 0:
line.append(attr["time"])
del attr["time"]
for atr in attr.items():
if atr[0] == "time" : continue
line.append(atr[1])
for bdy in body:
line.append(bdy)
self.__fd.writerow(line)
def close(self):
if self.format == "xml":
self.__fd.write("</data>")
self.__fd.close()
elif self.format == "data":
self.__fd.close()
else:
self.__hfd.close()
def __init__(self, mode="STD", attr={}):
if(not attr.get("version", 0) ) or attr["version"] != "0.1":
if mode == "STD":
sys.stderr.write("Wrong model forman\nABORT\n\n");
sys.exit(1)
else:
self.error = "Wrong model forman\nABORT\n\n"
return
self.object = "model"
self.objlst={}
self.workobj=None
self.maxspikes=-1
self.elapsed_time=0
self.timetospike=0
self.runer_flg = 1
self.cnt = 0
self.name = "collapse"
self.tos_accomul=0
self.hideout = 1
self.mode = mode
self.error = None
if attr.get("name"):
self.name = attr["name"]
def startpoint(self,object,attr):
if self.workobj == None and object == "simulation":
if attr.get("maxspikes"):
self.maxspikes = float( attr["maxspikes"] )
if attr.get("SEED"):
rnd.seed( float( attr["SEED"] ) )
else:
rnd.seed(time.microsecond)
self.workobj = "simulation"
return
elif self.workobj == None and object == "output":
if not self.objlst.get("outputs",0):
self.objlst["outputs"]=[]
self.objlst["outputs"].append(clmodel.file(attr))
self.workobj = "output"
return
elif self.workobj == None and object == "prc":
self.workobj = clprc.clprc(object,attr)
if not self.objlst.get("prc", 0):
self.objlst["prc"]={}
self.objlst["prc"][self.workobj.name]= self.workobj
elif self.workobj == None and object == "rprc":
self.workobj = clrprc.clrprc(find=self.find,attr=attr)
if not self.objlst.get("prc", 0):
self.objlst["prc"]={}
self.objlst["prc"][self.workobj.name]= self.workobj
elif self.workobj == None and object == "population":
self.workobj = clpopulation.clpopulation(attr=attr)
if not self.objlst.get("neurons", 0):
self.objlst["neurons"]={}
self.objlst["neurons"][self.workobj.name]= self.workobj
elif self.workobj == None and object == "neurons":
self.workobj = clneurons.clneurons(attr=attr)
if not self.objlst.get("neurons", 0):
self.objlst["neurons"]={}
self.objlst["neurons"][self.workobj.name]= self.workobj
elif self.workobj == None and object == "noisyneurons":
self.workobj = clnoisyneurons.clnoisyneurons(attr=attr)
if not self.objlst.get("neurons", 0):
self.objlst["neurons"]={}
self.objlst["neurons"][self.workobj.name]= self.workobj
#DB>>
elif self.workobj == None and object == "repeaters":
self.workobj = clrepeaters.clrepeaters(attr=attr)
if not self.objlst.get("neurons", 0):
self.objlst["neurons"]={}
self.objlst["neurons"][self.workobj.name]= self.workobj
#<<DB
elif self.workobj == None and object == "connection":
self.workobj = clconnection.clconnection(find=self.find,attr=attr)
if not self.objlst.get("connections", 0):
self.objlst["connections"]={}
self.objlst["connections"][self.workobj.name]= self.workobj
elif self.workobj != None:
self.workobj.startpoint(object,attr)
else:
if self.mode == "STD":
sys.stderr.write("Unexpected tag <%s> in <model> expression\nABORT\n\n"%object);
sys.exit(1)
else:
self.error ="Unexpected tag <%s> in <model> expression\nABORT\n\n"%object
def stoppoint(self,object):
if self.workobj != None and self.workobj == "simulation" and object == "simulation":
self.workobj = None
elif self.workobj != None and self.workobj == "output" and object == "output":
self.workobj = None
return
elif self.workobj != None and object == "rprc":
self.workobj = None
elif self.workobj != None and self.workobj.object == object:
self.workobj = None
elif self.workobj != None:
self.workobj.stoppoint(object)
else:
sys.stderr.write("Unexpected close tag <%s> in <model> expression\nABORT\n\n"%object);
sys.exit(1)
def find(self,object="",name=""):
if object == "" :
for objs in self.objlst.items():
return self.find(objs[0],name)
elif self.objlst.get(object) and self.objlst[object].get(name):
return self.objlst[object][name]
else:
if self.mode == "STD":
sys.stderr.write("FATAL ERROR: Cannot find object <%s name \"%s\" >\nABORT\n\n"%(object, name) );
sys.exit(1)
else:
self.error ="FATAL ERROR: Cannot find object <%s name \"%s\" >\nABORT\n\n"%(object, name)
def write(self):
lines=["<model name=\"%s\" version=\"0.1\" >"%self.name]
for i in self.objlst["prc"].items():
map(lambda x: lines.append("\t"+x), i[1].write() )
for i in self.objlst["neurons"].items():
map(lambda x: lines.append("\t"+x), i[1].write() )
for i in self.objlst["connections"].items():
map(lambda x: lines.append("\t"+x), i[1].write() )
lines.append("</model>")
return lines
def run(self):
neuronlst = self.objlst["neurons"]
neuronlst = [ x[1] for x in neuronlst.items() ]
connectlst = self.objlst["connections"]
connectlst = [ x[1] for x in connectlst.items() ]
self.print_header(neuronlst,connectlst)
self.timetospike = 1e19
for tos in reduce(lambda y,x:y+x.timetospike,neuronlst + connectlst ,[]):
if tos < self.timetospike:
self.timetospike = tos
self.cnt = 0
self.runer_flg = 1
while ( self.cnt < self.maxspikes or self.maxspikes < 0 ) and self.runer_flg:
if self.hideout: self.cnt += 1
for idx in neuronlst :idx.calculate(self)
for idx in connectlst:idx.calculate(self)
# for idx in xrange( len(neuronlst) ):
# neuronlst[idx].calculate(self)
# for idx in xrange( len(connectlst) ):
# connectlst[idx].calculate(self)
self.timetospike = min(reduce(lambda y,x:y+x.timetospike,neuronlst + connectlst ,[]))
# self.timetospike = 1e19
# for tos in reduce(lambda y,x:y+x.timetospike,neuronlst + connectlst ,[]):
# if tos < self.timetospike:
# self.timetospike = tos
if self.timetospike < 0.0 :
#print reduce(lambda y,x:y+x.timetospike,neuronlst + connectlst ,[])
if self.mode == "STD":
sys.stderr.write("At t=%g Minimal Time To Spike less then ZERO!\nABORT\n\n"%self.elapsed_time)
sys.exit(1)
else:
self.runer_flg = 0
self.error = "\nMinimal Time To Spike less then ZERO!\nABORT\nt = %g\n\n"%self.elapsed_time
break
self.print_preupdate(neuronlst,connectlst)
self.elapsed_time += self.timetospike
for idx in neuronlst : idx.update(self)
for idx in connectlst: idx.update(self)
self.print_postupdate(neuronlst,connectlst)
if self.runer_flg == 0: return
for fl in self.objlst["outputs"]:
if fl.watch != "last period":
fl.close()
else:
wrd = []
for item in neuronlst:
for ph in item.neurons:
wrd.append(ph[2])
fl.write(wrd)
fl.close()
self.runer_flg = 0
def print_header(self,neuronlst,connectlst):
for fl in self.objlst["outputs"]:
#print fl.name," ",fl.watch," ",fl.format," "
wrd=[]
if fl.watch == "time to spike" or fl.watch == "spikes":
if fl.connections != "off":
for item in neuronlst+connectlst:
wrd += item.getnames()
else:
for item in neuronlst:
wrd += item.getnames()
else:
for item in neuronlst:
wrd += item.getnames()
fl.writeheader(wrd,attr={"time":1.0,"mintos":0})
def print_preupdate(self,neuronlst,connectlst):
for fl in self.objlst["outputs"]:
#print fl.name," ",fl.watch," ",fl.format," "
wrd=[]
if fl.connections == "off" and (not self.hideout):continue
if fl.watch == "last period" or fl.watch == "spikes" :
continue
elif fl.watch == "time to spike":
if fl.connections == "off":
for item in neuronlst:
for tos in item.timetospike:
wrd.append(tos)
else:
for item in neuronlst+connectlst:
for tos in item.timetospike:
wrd.append(tos)
elif fl.watch == "phases":
for item in neuronlst:
for ph in item.neurons:
wrd.append(ph[0])
if fl.connections == "on":
for item in connectlst:
for ph in item.fifo:
if len(ph) > 0:
wrd.append(ph[0])
else:
wrd.append(1e19)
elif fl.watch == "second correction":
for item in neuronlst:
for ph in item.neurons:
wrd.append(ph[1])
elif fl.watch == "periods":
for item in neuronlst:
for ph in item.neurons:
wrd.append(ph[2])
elif fl.watch == "intrinsic period" :
for item in neuronlst:
if item.object != "noisyneurons":
wrd += [ item.period for x in xrange(item.number) ]
else :
wrd += item.periods
# print fl.name," ",fl.watch," ",fl.format," ",wrd
fl.write(wrd,attr={"time":self.elapsed_time,"mintos":self.timetospike+self.tos_accomul})
def print_postupdate(self,neuronlst,connectlst):
self.hideout = reduce(lambda x,y:x+y,reduce(lambda x,y:x+y.op,neuronlst,[]),0)
# print "TOS %g Hide %d Comulation %g"%(self.timetospike,self.hideout,self.tos_accomul)
for fl in self.objlst["outputs"]:
wrd = []
if fl.connections == "off" and (not self.hideout):continue
if fl.watch == "last period" or fl.watch == "time to spike":
continue
if fl.watch == "phases" or fl.watch == "second correction":
continue
if fl.watch == "periods" or fl.watch == "intrinsic period" :
continue
if fl.connections == "off":
for item in neuronlst:
for op in item.op:
wrd.append(op)
else:
for item in neuronlst+connectlst:
for op in item.op:
wrd.append(op)
fl.write(wrd,attr={"time":self.elapsed_time,"mintos":self.timetospike+self.tos_accomul})
if self.hideout:
self.tos_accomul = 0.0
else:
self.tos_accomul += self.timetospike