import matplotlib
matplotlib.use('Agg')
import numpy
from pylab import *
import mytools
import pickle
import time
import sys
import random
from os.path import exists
random.seed(1)
v0 = -80
ca0 = 0.0001
proximalpoint = 400
distalpoint = 620
BACdt = 5.0
fs = 8
ITERS = 30
tstop = 11000.0
import mutation_stuff
MT = mutation_stuff.getMT()
defVals = mutation_stuff.getdefvals()
keyList = defVals.keys()
for idefval in range(0,len(keyList)):
if type(defVals[keyList[idefval]]) is not list:
defVals[keyList[idefval]] = [defVals[keyList[idefval]], defVals[keyList[idefval]]] #make the dictionary values [somatic, apical]
updatedVars = ['somatic','apical','basal'] # the possible classes of segments that defVals may apply to
whichDefVal = [0,1,0] # use the defVal[0] for somatic and basal segments and defVal[1] for apical segments
unpicklefile = open('scalings_cs.sav', 'r')
unpickledlist = pickle.load(unpicklefile)
unpicklefile.close()
theseCoeffsAllAll = unpickledlist[0]
theseMutValsAllAll = unpickledlist[2]
lensToStart = [100.0 + x*50 for x in range(0,16)]
for istartdist in range(0,len(lensToStart)):
startdist = lensToStart[istartdist]
unpicklefile = open('synlocs'+str(startdist)+'.sav', 'r')
unpickledlist = pickle.load(unpicklefile)
unpicklefile.close()
Nsyns = unpickledlist[0]
synlocsAll = unpickledlist[3]
startdist = int(startdist)
maxLens = [1300,1185]
gsAllAll = []
for icell in range(0,7):
synlocs = synlocsAll[0]
gsAll = []
theseCoeffsAll = theseCoeffsAllAll[icell]
coeffCoeffs = [[0.25,0],[0.125,0],[0.5,0],[0.5,1.0/3],[0.5,2.0/3],[0.5,1.0],[-0.25,0],[-0.125,0],[-0.5,0]]
counter = -1
for igene in range(0,len(MT)):
gsThisGene = []
for imut in range(0,len(MT[igene])):
gsThisMut = []
nVals = len(MT[igene][imut])*[0]
thesemutvars = []
theseCoeffs = theseCoeffsAll[igene][imut]
for imutvar in range(0,len(MT[igene][imut])):
thesemutvars.append(MT[igene][imut][imutvar][0])
if type(MT[igene][imut][imutvar][1]) is int or type(MT[igene][imut][imutvar][1]) is float:
MT[igene][imut][imutvar][1] = [MT[igene][imut][imutvar][1]]
nVals[imutvar] = len(MT[igene][imut][imutvar][1])
cumprodnVals = cumprod(nVals)
allmutvars = cumprodnVals[len(MT[igene][imut])-1]*[thesemutvars]
allmutvals = []
for iallmutval in range(0,cumprodnVals[len(MT[igene][imut])-1]):
allmutvals.append([0]*len(thesemutvars))
for iallmutval in range(0,cumprodnVals[len(MT[igene][imut])-1]):
for imutvar in range(0,len(MT[igene][imut])):
if imutvar==0:
allmutvals[iallmutval][imutvar] = MT[igene][imut][imutvar][1][iallmutval%nVals[imutvar]]
else:
allmutvals[iallmutval][imutvar] = MT[igene][imut][imutvar][1][(iallmutval/cumprodnVals[imutvar-1])%nVals[imutvar]]
for iallmutval in range(0,cumprodnVals[len(MT[igene][imut])-1]):
counter = counter + 1
gsThisMutVal = []
if exists('thresholddistalamp'+str(startdist)+'_cs'+str(icell)+'_'+str(counter)+'.sav'):
print 'thresholddistalamp'+str(startdist)+'_cs'+str(icell)+'_'+str(counter)+'.sav exists'
unpicklefile = open('thresholddistalamp'+str(startdist)+'_cs'+str(icell)+'_'+str(counter)+'.sav', 'r')
unpickledlist = pickle.load(unpicklefile)
unpicklefile.close()
gsThisMutVal = unpickledlist[1]
#picklelist = [theseCoeffsAll,gsThisMutVal,MT]
#file = open('thresholddistalamp'+str(startdist)+'_cs'+str(icell)+'_'+str(counter)+'.sav', 'w')
#pickle.dump(picklelist,file)
#file.close()
gsThisMut.append(gsThisMutVal[:])
gsThisGene.append(gsThisMut[:])
gsAll.append(gsThisGene[:])
gsAllAll.append(gsAll[:])
picklelist = [theseCoeffsAllAll,gsAllAll,MT]
file = open('thresholddistalamp'+str(startdist)+'.sav', 'w')
pickle.dump(picklelist,file)
file.close()
#picklelist = [theseCoeffsAllAll,gsThisAllAll,MT]
#file = open('thresholddistalamp'+str(startdist)+'_cs'+str(icell)+'_'+str(counter)+'.sav', 'w')
#pickle.dump(picklelist,file)
#file.close()