# $Id: batch.py,v 1.63 2013/02/15 19:15:41 samn Exp $
# execfile("runone.py") # loads sim
import sys
import os
import numpy
# from modindex import *
import multiprocessing
# from Queue import Queue
from conf import writeconf
# from IPython.core.debugger import Tracer
# debug_here = Tracer()
# if __name__ != "__main__":
# from neuron import h
# from network import net
# execfile("run.py")
# #from run import loadminrundat
liseed = [1234] # ,6912,9876,6789,3219,5936]
lwseed = [4321] # ,5012,9281,8130,6143,7131]
def appline (s,fn):
fp = open(fn,"a")
fp.write(s)
fp.write("\n")
fp.close()
batchf = "mybatch.sh"
def mycomm (s, fn=batchf):
appline(s,fn)
def mylog(s,fn="OLMbatchLong_13aug5B.log"):
appline(s,fn)
# runs batch modulating strength of NMDA synapses at OLM cells
# loops & calls ntebatchrun.py to run the sim/save data
def ntebatch(nlevels,startnum=0):
x = numpy.linspace(0,1,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for i1,r1 in enumerate(x):
#net.olm.set_r("somaNMDA",r1)
if y < startnum:
print ("skipping sim num ", y)
y += 1
continue
s = "./mod/x86_64/special -python ntebatchrun.py"
s += " "+str(iseed)+" "+str(wseed)+" "+str(r1)
print ("sim num = ", y, ", command = ", s)
y += 1
mylog(s)
os.system(s)
# load info about batch run into an NQS. returns the NQS
def ntebatchnq(nlevels=5):
from neuron import h
nq = h.NQS("id","simstr","iseed","wseed","OLMr")
nq.strdec("simstr")
x = numpy.linspace(0,1,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for i1,r1 in enumerate(x):
simstr = "11may20.05_iseed_"+str(iseed)+"_wseed_"+str(wseed)
simstr += "_OLMr_"+str(r1)
nq.append(y,simstr,iseed,wseed,r1)
y += 1
return nq
# runs batch modulating strength of NMDA synapses at different cell types/locations
# loops & calls nmbatchrun.py to run the sim/save data
def nmbatch(nlevels,startnum=0):
x = numpy.linspace(0,1,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for i1,r1 in enumerate(x):
#net.olm.set_r("somaNMDA",r1)
for i2, r2 in enumerate(x):
#net.bas.set_r("somaNMDA",r2)
for i3, r3 in enumerate(x):
#net.pyr.set_r("BdendNMDA",r3)
for i4, r4 in enumerate(x):
if y < startnum:
print ("skipping sim num ", y)
y += 1
continue
s = "./mod/x86_64/special -python nmbatchrun.py"
s += " "+str(iseed)+" "+str(wseed)+" "+str(r1)+" "+str(r2)+" "+str(r3)+" "+str(r4)
print ("sim num = ", y, ", command = ", s)
y += 1
mylog(s)
os.system(s)
#net.pyr.set_r("Adend3NMDA",r4)
# runs batch modulating level of Ih conductance at PYR,BAS cells together - maintaining OLM Ih conductance
# loops & calls ihbatchrun.py to run the sim/save data
def longihbatchPYRBAS (nlevels,startnum=0,qsz=25):
procs = []
q = Queue(qsz)
x,y = numpy.linspace(0,2,nlevels), 0
iseed, wseed = liseed[0], lwseed[0]
def myworker (scomm,num):
os.system(scomm) #worker function, invoked in a process.
for ih1 in x:
for ih2 in x:
if y < startnum:
print ("skipping sim num ", y)
y += 1
continue
s = "./mod/x86_64/special -python ihbatchrun.py"
s += " "+str(iseed)+" "+str(wseed)+" "+str(ih1)+" "+str(ih2)+" "+str(1.0)+" 1.0"
p = multiprocessing.Process(target=myworker,args=(s,2))
procs.append(p)
q.put(p,True) # put proc on q and wait for free slot
print ("sim num = ", y, ", command = ", s)
mylog(s)
p.start() # maybe have to put this before placing on q
y += 1
for p in procs: p.join() # Wait for all worker processes to finish
# runs batch modulating level of Ih conductance at OLM cells - maintaining PYR,BAS Ih conductance
# loops & calls ihbatchrun.py to run the sim/save data
def longihbatchOLM (nlevels,startnum=0,qsz=11):
procs = []
q = Queue(qsz)
x,y = numpy.linspace(0,2,nlevels), 0
iseed, wseed = liseed[0], lwseed[0]
def myworker (scomm,num):
os.system(scomm) #worker function, invoked in a process.
for ih1 in x:
if y < startnum:
print ("skipping sim num ", y)
y += 1
continue
s = "./mod/x86_64/special -python ihbatchrun.py"
s += " "+str(iseed)+" "+str(wseed)+" "+str(1.0)+" "+str(1.0)+" "+str(ih1)+" 1.0"
p = multiprocessing.Process(target=myworker,args=(s,2))
procs.append(p)
q.put(p,True) # put proc on q and wait for free slot
print ("sim num = ", y, ", command = ", s)
mylog(s)
p.start() # maybe have to put this before placing on q
y += 1
for p in procs: p.join() # Wait for all worker processes to finish
#
def getihsimstr (iseed,wseed,ihpyr,ihbas,iholm):
simstr = "12nov09.09_iseed_"+str(iseed)+"_wseed_"+str(wseed)
simstr += "_ihpyr_"+str(ihpyr)+"_ihbas_"+str(ihbas)+"_iholm_"+str(iholm)
return simstr
# return an NQS with concatenated vectors from longihbatcPYRBAS run
# only loads data <= savenums
def longihbatchPYRBASNQ (nlevels,savenums):
x,y = numpy.linspace(0,2,nlevels), 0
iseed, wseed = liseed[0], lwseed[0]
nq = h.NQS("id","simstr","iseed","wseed","ihpyr","ihbas","iholm","vlfp")
nq.strdec("simstr")
nq.odec("lfp")
for ih1 in x:
for ih2 in x:
simstr = getihsimstr(iseed,wseed,ih1,ih2,1.0)
fbase = "./data/lfp/" + simstr + "_"
vlfp = catlfp(fbase,savenums)
nq.append(y,simstr,iseed,wseed,ih1,ih2,1.0,vlfp)
y += 1
return nq
# runs batch modulating level of Ih conductance at PYR,BAS cells together - maintaining OLM Ih conductance
# loops & calls ihbatchrun.py to run the sim/save data
def ihbatchPYRBAS (nlevels,startnum=0):
x = numpy.linspace(0,2,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for r1 in x:
for r2 in x:
if r1 == 1.0 and r2 == 1.0:
continue # already ran all at baseline
elif r1 != r2:
continue # only running where they're equal
else:
xl = [[r1, r2, 1.0]]
#elif r1 == r2:
# continue # already ran same values of r1,r2
for xll in xl:
if y < startnum:
print ("skipping sim num ", y)
y += 1
continue
s = "./mod/x86_64/special -python ihbatchrun.py"
s += " "+str(iseed)+" "+str(wseed)+" "+str(xll[0])+" "+str(xll[1])+" "+str(xll[2])
print ("sim num = ", y, ", command = ", s)
y += 1
mylog(s)
os.system(s)
# mycomm(s)
# load info about batch run into an NQS. returns the NQS
def ihbatchPYRBASnq (nlevels):
from neuron import h
nq = h.NQS("id","simstr","iseed","wseed","ihpyr","ihbas","iholm")
nq.strdec("simstr")
x = numpy.linspace(0,2,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for r1 in x:
for r2 in x:
if r1 == 1.0 and r2 == 1.0:
continue # already ran all at baseline
else:
xl = [[r1, r2, 1.0]]
for xll in xl:
simstr = "12nov09.09_iseed_"+str(iseed)+"_wseed_"+str(wseed)
simstr += "_ihpyr_"+str(xll[0])+"_ihbas_"+str(xll[1])+"_iholm_"+str(xll[2])
nq.append(y,simstr,iseed,wseed,xll[0],xll[1],xll[2])
y += 1
return nq
# runs batch modulating level of ih conductance
# loops & calls ihbatchrun.py to run the sim/save data
def ihbatch (nlevels,startnum=0):
x = numpy.linspace(0,2,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for r1 in x:
if r1 == 1.0:
xl = [[1.0, 1.0, 1.0]] # skip dups
else:
xl = [[r1, r1, r1], [r1, 1.0, 1.0], [1.0, r1, 1.0], [1.0, 1.0, r1] ]
for xll in xl:
if y < startnum:
print ("skipping sim num ", y)
y += 1
continue
s = "./mod/x86_64/special -python ihbatchrun.py"
s += " "+str(iseed)+" "+str(wseed)+" "+str(xll[0])+" "+str(xll[1])+" "+str(xll[2])
print ("sim num = ", y, ", command = ", s)
y += 1
mylog(s)
os.system(s)
# load info about batch run into an NQS. returns the NQS
def ihbatchnq(nlevels):
from neuron import h
nq = h.NQS("id","simstr","iseed","wseed","ihpyr","ihbas","iholm")
nq.strdec("simstr")
x = numpy.linspace(0,2,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for r1 in x:
if r1 == 1.0:
xl = [[1.0, 1.0, 1.0]] # skip dups
else:
xl = [[r1, r1, r1], [r1, 1.0, 1.0], [1.0, r1, 1.0], [1.0, 1.0, r1] ]
for xll in xl:
simstr = "12nov09.09_iseed_"+str(iseed)+"_wseed_"+str(wseed)
simstr += "_ihpyr_"+str(xll[0])+"_ihbas_"+str(xll[1])+"_iholm_"+str(xll[2])
nq.append(y,simstr,iseed,wseed,xll[0],xll[1],xll[2])
y += 1
return nq
# load info about batch run into an NQS. returns the NQS (batch from 13aug1)
def newihbatchnq (nlevels):
nq = h.NQS("id","simstr","iseed","wseed","ihpyr","ihbas","iholm")
nq.strdec("simstr")
x = numpy.linspace(0,2,nlevels)
y = 0
liseed = [1234]; lwseed = [4321];
for iseed in liseed:
for wseed in lwseed:
for r1 in x:
if r1 == 1.0:
xl = [[1.0, 1.0, 1.0]] # skip dups
else:
xl = [[r1, r1, r1], [r1, 1.0, 1.0], [1.0, r1, 1.0], [1.0, 1.0, r1] ]
for xll in xl:
simstr = "13aug1_iseed_"+str(iseed)+"_wseed_"+str(wseed)
simstr += "_ihpyr_"+str(xll[0])+"_ihbas_"+str(xll[1])+"_iholm_"+str(xll[2])
nq.append(y,simstr,iseed,wseed,xll[0],xll[1],xll[2])
y += 1
for r1 in x:
for r2 in x:
if r1 == 1.0 and r2 == 1.0:
continue # already ran all at baseline
elif r1 != r2:
continue
else:
xl = [[r1, r2, 1.0]]
for xll in xl:
simstr = "13aug1_iseed_"+str(iseed)+"_wseed_"+str(wseed)
simstr += "_ihpyr_"+str(xll[0])+"_ihbas_"+str(xll[1])+"_iholm_"+str(xll[2])
nq.append(y,simstr,iseed,wseed,xll[0],xll[1],xll[2])
y += 1
return nq
# load info about batch run into an NQS. returns the NQS
def nmbatchnq(nlevels):
from neuron import h
nq = h.NQS("id","simstr","iseed","wseed","OLMr","BASr","PYRBr","PYRAr")
nq.strdec("simstr")
x = numpy.linspace(0,1,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for i1,r1 in enumerate(x):
for i2, r2 in enumerate(x):
for i3, r3 in enumerate(x):
for i4, r4 in enumerate(x):
simstr = "11jun22.02_iseed_"+str(iseed)+"_wseed_"+str(wseed)
simstr += "_OLMr_"+str(r1)+"_BASr_"+str(r2)+"_PYRBr_"+str(r3)+"_PYRAr_"+str(r4)
nq.append(y,simstr,iseed,wseed,r1,r2,r3,r4)
y += 1
return nq
def testit ():
# global h,net,loadminrundat
# from neuron import h
# from network import net
# from run import loadminrundat
print (h,net,loadminrundat)
# get cross-frequency coupling arrays - vlfp is a vector
def getcfc (vlfp):
v1 = h.Vector()
v1.copy(vlfp) # (vlfp,nsamp,vlfp.size()-1-nsamp)
v1.sub(v1.mean())
sampr = 1e3 / h.dt
from_t = 1
to_t = int( vlfp.size() / sampr - 1 )
phaseFreq,ampFreq,modArr = varModIndArr(v1, sampr, from_t, to_t, 4, 12, 25, 55, 1 , 1, 1)
return phaseFreq, ampFreq, modArr
# run CFC analysis on LFPs in nqb - save output to text files
def addCFCcol (nqb,datadir="./data/"):
global h
nqb.tog("DB")
if nqb.fi("fcfc") == -1:
nqb.resize("fcfc")
nqb.strdec("fcfc")
nqb.pad()
for i in range(int(nqb.v[0].size())):
print ("up to " + str(i) + " out of " + str(nqb.v[0].size()))
simstr = nqb.get("simstr",i).s
fcfc = "./data/cfc/" + simstr + "_cfc.txt"
if os.path.exists(fcfc):
print ("skipping ", fcfc, " already done.")
nqb.set("fcfc",i,fcfc)
continue
loadminrundat(simstr,datadir)
phaseFreq, ampFreq, modArr = getcfc(net.vlfp)
if i == 0:
numpy.savetxt("./data/cfc/phaseFreq.txt",phaseFreq)
numpy.savetxt("./data/cfc/ampFreq.txt",ampFreq)
numpy.savetxt(fcfc,modArr)
nqb.set("fcfc",i,fcfc)
# add a column to nqb with power spectra from h.matpmtm.
# skipms is milliseconds of signal to skip from beginning and end of LFP
# ty determines method to use for calculating power spectrum
def addnqpcol(nqb,skipms=200,ty=0,datadir="./data/"):
global h
nqb.tog("DB")
if nqb.fi("nqp") == -1:
nqb.resize("nqp")
nqb.odec("nqp")
nqb.pad()
hasvlfp = False
if nqb.fi("vlfp") != -1: hasvlfp = True
v1=h.Vector()
nsamp = skipms / h.dt # number of samples to skip from start,end
for i in range(int(nqb.v[0].size())):
print ("up to " + str(i) + " out of " + str(nqb.v[0].size()))
if hasvlfp:
v1.copy(nqb.get("vlfp",i).o[0])
else:
loadminrundat(nqb.get("simstr",i).s,datadir)
v1.copy(net.vlfp,nsamp,net.vlfp.size()-1-nsamp)
v1.sub(v1.mean())
if ty==0:
nqp=h.matpmtm(v1,1e3/h.dt)
elif ty==1:
nqp=h.pypmtm(v1,1e3/h.dt)
elif ty==2:
nqp=h.pypsd(v1,1e3/h.dt)
else:
nqp=h.nrnpsd(v1,1e3/h.dt)
nqb.set("nqp",i,nqp)
h.nqsdel(nqp)
# add columns to nqb with synchrony of each population (uses cvpsync in stats.hoc)
# skipms is milliseconds of signal to skip from beginning and end of sim
def addCVpcol (nqb,skipms=200,simdur=8e3,datadir="./data/"):
nqb.tog("DB")
if nqb.fi("pyrCVp") == -1:
for s in ["pyrCVp","basCVp","olmCVp","pyrbasCVp","pyrolmCVp","basolmCVp","allCVp"]: nqb.resize(s)
nqb.pad()
cdx = int(nqb.fi("pyrCVp")) # column index
for i in range(int(nqb.v[0].size())):
print ("up to " + str(i) + " out of " + str(nqb.v[0].size()))
loadminrundat(nqb.get("simstr",i).s,datadir)
net.snq.verbose=0
idx = cdx
for ty in range(7):
cvp = 0
if ty <= 2: # PYR then BAS then OLM
if net.snq.select("ty",ty,"t","[]",skipms,simdur-skipms) > 0:
cvp = h.cvpsync(net.snq.getcol("t"),net.cells[ty].n)
elif ty == 3: # PYR + BAS
if net.snq.select("ty","!=",2,"t","[]",skipms,simdur-skipms) > 0:
cvp = h.cvpsync(net.snq.getcol("t"),net.cells[0].n+net.cells[1].n)
elif ty == 4: # PYR + OLM
if net.snq.select("ty","!=",1,"t","[]",skipms,simdur-skipms) > 0:
cvp = h.cvpsync(net.snq.getcol("t"),net.cells[0].n+net.cells[2].n)
elif ty == 5: # BAS + OLM
if net.snq.select("ty","!=",0,"t","[]",skipms,simdur-skipms) > 0:
cvp = h.cvpsync(net.snq.getcol("t"),net.cells[1].n+net.cells[2].n)
elif ty == 6: # ALL
if net.snq.select("t","[]",skipms,simdur-skipms) > 0:
cvp = h.cvpsync(net.snq.getcol("t"),net.cells[0].n+net.cells[1].n+net.cells[2].n)
nqb.v[idx].x[i] = cvp
idx += 1
net.snq.verbose=1
# add columns to nqb with frequency of each population
# skipms is milliseconds of signal to skip from beginning and end of sim
def addHzcol (nqb,skipms=200,simdur=8e3,datadir="./data/"):
nqb.tog("DB")
if nqb.fi("pyrHz") == -1:
for s in ["pyrHz", "basHz", "olmHz"]: nqb.resize(s)
nqb.pad()
cdx = int(nqb.fi("pyrHz")) # column index
for i in range(int(nqb.v[0].size())):
print ("up to " + str(i) + " out of " + str(nqb.v[0].size()))
loadminrundat(nqb.get("simstr",i).s,datadir)
net.snq.verbose=0
idx = cdx
for ty in range(3):
nspks = net.snq.select("ty",ty,"t","[]",skipms,simdur-skipms)
hz = 1e3 * nspks / ( (simdur-2*skipms) * net.cells[ty].n ) # to hz
nqb.v[idx].x[i] = hz
idx += 1
net.snq.verbose=1
# runs a batch of sims of form baseline/washin/washout . during washin, OLM NMDA is turned off.
# at washout, it's turned back on.
def washbatch(nlevels,startnum=0):
x = numpy.linspace(0,1,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for r1 in x:
if y < startnum:
print ("skipping sim num ", y)
y += 1
continue
s = "./mod/x86_64/special -python washbatchrun.py"
s += " "+str(iseed)+" "+str(wseed)+" "+str(r1)
print ("sim num = ", y, ", command = ", s)
y += 1
mylog(s,"washbatch_10dec13.14.log")
os.system(s)
# load info about washbatch run into an NQS. returns the NQS
def washbatchnq(nlevels):
from neuron import h
nq = h.NQS("id","simstr","iseed","wseed","OLMr")
nq.strdec("simstr")
x = numpy.linspace(0,1,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for r1 in x:
simstr = "10dec14.10dec13.14_iseed_"+str(iseed)+"_wseed_"+str(wseed)
simstr += "_washOLMr_"+str(r1)
nq.append(y,simstr,iseed,wseed,r1)
y += 1
return nq
# addwashnqpcol -- add a column to nqb from washbatchnq with power spectra from h.matpmtm.
def addwashnqpcol(nqb):
from neuron import h
# from network import net
# from run import loadminrundat
nqb.tog("DB")
if nqb.fi("nqpbase") == -1:
nqb.resize("nqpbase") # baseline power spectra
nqb.odec("nqpbase")
nqb.resize("nqpwin") # washin power spectra
nqb.odec("nqpwin")
nqb.resize("nqpwout") # washout power spectra
nqb.odec("nqpwout")
nqb.pad()
cdx = int(nqb.fi("nqpbase")) # column id
vec=h.Vector()
dt = h.dt # time interval
sampr = 1e3/dt # sampling rate
vsidx = [2e3/dt,4e3/dt,6e3/dt] # start times for different periods
veidx = [4e3/dt,6e3/dt,8e3/dt] # end times for different periods
for i in range(int(nqb.v[0].size())):
simstr = nqb.get("simstr",i).s
print ("up to " + str(i) + " out of " + str(nqb.v[0].size()))
print ("\tsim = " , simstr)
loadminrundat(simstr) # load the sim data
j = cdx # j has column index into nqb
for k in range(len(vsidx)):
print ("interval=",k,vsidx[k],veidx[k])
vec.resize(0)
vec.copy(net.vlfp,vsidx[k],veidx[k]) # copy relevant portion of LFP
vec.sub(vec.mean()) # remove mean
nqp=h.matpmtm(vec,sampr) # get the power spectra
nqb.set(nqb.s[j].s,i,nqp) # save nqp in correct row,column of nqb
h.nqsdel(nqp) # free memory
j += 1 # increment column index
# runs a batch of sims where BAS cells are turned off
def basbatch(startnum=0):
y = 0
for iseed in liseed:
for wseed in lwseed:
if y < startnum:
print ("skipping sim num ", y)
y += 1
continue
s = "./mod/x86_64/special -python basbatchrun.py"
s += " "+str(iseed)+" "+str(wseed)
print ("sim num = ", y, ", command = ", s)
y += 1
mylog(s,"basbatch_10dec13.14.log")
os.system(s)
# load info about basbatch run into an NQS. returns the NQS
def basbatchnq():
from neuron import h
nq = h.NQS("id","simstr","iseed","wseed")
nq.strdec("simstr")
y = 0
for iseed in liseed:
for wseed in lwseed:
simstr = "10dec15.10dec13.14_iseed_"+str(iseed)+"_wseed_"+str(wseed)
simstr += "_BASoff_"
nq.append(y,simstr,iseed,wseed)
y += 1
return nq
# runs a batch of sims where OLM NMDA is off and different levels of current injection
# into the OLM cells is applied. calls currinjbatchrun.py to run sim & save data.
def currinjbatch(nlevels,startnum=0):
x = numpy.linspace(10,50,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for i1,r1 in enumerate(x):
if y < startnum:
print ("skipping sim num ", y)
y += 1
continue
s = "./mod/x86_64/special -python currinjbatchrun.py"
s += " "+str(iseed)+" "+str(wseed)+" "+str(r1)
print ("sim num = ", y, ", command = ", s)
y += 1
mylog(s,"currinjbatch_10dec13.14.log")
os.system(s)
# load info about currinjbatch run into an NQS. returns the NQS
def currinjbatchnq(nlevels):
from neuron import h
nq = h.NQS("id","simstr","iseed","wseed","incOLMInj")
nq.strdec("simstr")
x = numpy.linspace(10,50,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for ic in x:
simstr = "10dec14.10dec13.14_iseed_"+str(iseed)+"_wseed_"+str(wseed)
simstr += "_incOLMInj_"+str(ic)
nq.append(y,simstr,iseed,wseed,ic)
y += 1
return nq
# runs a batch of sims with 3 periods: baseline, washin, current injection (to replace washout)
# during washin, ALL OLM NMDA is off. during current injection different levels of current injection
# are sent into the OLM cells instead of washout. calls washinjbatchrun.py to run sim & save data.
def washinjbatch(nlevels,startnum=0):
x = numpy.linspace(0,50,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for i1,r1 in enumerate(x):
if y < startnum:
print ("skipping sim num ", y)
y += 1
continue
s = "./mod/x86_64/special -python washinjbatchrun.py"
s += " "+str(iseed)+" "+str(wseed)+" "+str(r1)
print ("sim num = ", y, ", command = ", s)
y += 1
mylog(s,"washinjbatch_10dec15.06.log")
os.system(s)
# load info about washinjbatch run into an NQS. returns the NQS
def washinjbatchnq(nlevels):
from neuron import h
nq = h.NQS("id","simstr","iseed","wseed","incOLMInj")
nq.strdec("simstr")
x = numpy.linspace(0,50,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for ic in x:
simstr = "10dec16.10dec15.06_iseed_"+str(iseed)+"_wseed_"+str(wseed)
simstr += "_washincOLMInj_"+str(ic*1e-3)
nq.append(y,simstr,iseed,wseed,ic)
y += 1
return nq
# runs a batch of sims varying the MSGain (medial septal weight gain)
# msbatchrun.py to run sim & save data.
def msbatch(nlevels,startnum=0):
x = numpy.linspace(0,1,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for i1,r1 in enumerate(x):
if y < startnum:
print ("skipping sim num ", y)
y += 1
continue
s = "./mod/x86_64/special -python msbatchrun.py"
s += " "+str(iseed)+" "+str(wseed)+" "+str(r1)
print ("sim num = ", y, ", command = ", s)
y += 1
mylog(s,"msbatch_11mar28.12.log")
os.system(s)
# load info about msbatch run into an NQS. returns the NQS
def msbatchnq(nlevels=5):
from neuron import h
nq = h.NQS("id","simstr","iseed","wseed","msgain")
nq.strdec("simstr")
x = numpy.linspace(0,1,nlevels)
y = 0
for iseed in liseed:
for wseed in lwseed:
for msgain in x:
simstr = "11mar28.12_iseed_"+str(iseed)+"_wseed_"+str(wseed)
simstr += "_msgain_"+str(msgain)
nq.append(y,simstr,iseed,wseed,msgain)
y += 1
return nq
# # append line s to filepath fn
# def appline (s,fn):
# '''append line s to filepath fn'''
# fp = open(fn,"a"); fp.write(s + "\n"); fp.close()
# append to the lists
def NewParam (lsec,lopt,lval,sec,opt,val):
'''append to the lists of params'''
lsec.append(sec); lopt.append(opt); lval.append(val)
# check that the batch dir exists
def checkdir (d):
'''check that the batch dir exists'''
try:
if not os.path.exists(d): os.mkdir(d)
return True
except:
print ("could not create directory :" + d)
return False
# run a batch using multiprocessing
# based on http://www.bryceboe.com/2011/01/28/the-python-multiprocessing-queue-and-large-objects/
# obtained from /u/samn/ca1d/batch.py
def batchRun (whichParams,blog,skip=[],qsz=10,bdir="./batchconfigFiles"):
'''run a batch using multiprocessing'''
if not checkdir(bdir): return False
jobs = multiprocessing.Queue()
lsec,lopt,lval,lconfigfilestr = whichParams()
def myworker (jobs):
while True:
scomm = jobs.get()
if scomm == None: break
print ("worker starting : " , scomm)
os.system(scomm) #worker function, invoked in a process.
for i in range(len(lsec)):
if i in skip: continue
cfgname = os.path.join(bdir, lconfigfilestr[i] + ".cfg")
writeconf(cfgname,sec=lsec[i],opt=lopt[i],val=lval[i])
cmd = "python runone.py " + cfgname
print (cmd, type(cmd))
appline(cmd,blog)
jobs.put(cmd)
workers = []
for i in range(qsz):
jobs.put(None)
tmp = multiprocessing.Process(target=myworker, args=(jobs,))
tmp.start()
workers.append(tmp)
for worker in workers: worker.join()
return jobs.empty()
# main...
if __name__ == "__main__":
na = len(sys.argv) # number of args
print (sys.argv)
if na < 2:
print ("Usage: python batch.py type[0=nmbatch,1=washbatch,2=currinjbatch,3=basbatch,4=washinj,5=msbatch,6=ntebatch,7=ihbatch],[nlevels,startnum]")
sys.exit(1)
ty = int(sys.argv[1])
print ("hello!!! ty is : " + str(ty))
if ty == 0:
print ("nmbatch")
bru = nmbatch
elif ty == 1:
print ("washbatch")
bru = washbatch
elif ty == 2:
print ("currinjbatch")
bru = currinjbatch
elif ty == 3:
print ("basbatch")
if na > 2:
startnum = int(sys.argv[2])
basbatch(startnum)
else:
basbatch()
sys.exit(0)
elif ty == 4:
print ("washinj")
bru = washinjbatch
elif ty == 5:
print ("msbatch")
bru = msbatch
elif ty == 6:
print ("ntebatch")
bru = ntebatch
elif ty == 7:
print ("ihbatch")
bru = ihbatch
elif ty == 8:
print ("ihbatchPYRBAS")
bru = ihbatchPYRBAS
elif ty == 9:
print ("longihbatchPYRBAS")
bru = longihbatchPYRBAS
elif ty == 10:
print ("longihbatchOLM")
bru = longihbatchOLM
else:
print (str(ty) + "is an unknown batch type!")
sys.exit(1)
nlevels = int(sys.argv[2])
if na > 3:
startnum = int(sys.argv[3])
bru(nlevels,startnum)
else:
bru(nlevels)
sys.exit(0)
