from pylab import *
import scipy.io
from os.path import exists
import os
import mytools
import calcconds
def boxoff(ax):
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.get_xaxis().tick_bottom()
ax.get_yaxis().tick_left()
def ltdltpcurve(blocked='GluR1,GluR1_memb,GluR2,GluR2_memb,Cax0.5,0.5,1.5,1.5,1.0', T = 100, Caflux = 150.0, Lflux = 5.0, Gluflux = 10.0, altered = '_k1x1.0', freqs = [0.5, 1.0, 2.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 22.0, 25.0, 30.0, 40.0, 50.0, 75.0, 100.0, 200.0, 300.0, 500.0],dodraw = True):
if dodraw:
close("all")
f,axarr = subplots(3,4)
for iay in range(0,3):
for iax in range(0,4):
axarr[iay,iax].set_position([0.08+0.25*iax,0.77-0.27*iay,0.17,0.21])
Nstims = [int(T*x) for x in freqs]
tposts = [20, 30, 40, 0] #min after stimulus onset
condposts = []
condposts_abs = []
GluR1posts = []
GluR1S831posts = []
GluR2posts = []
addition = ''
for ifreq in range(0,len(freqs)):
freq = freqs[ifreq]
Nstim = Nstims[ifreq]
filename = addition+'nrn_tstop27000000_tol1e-06_'+blocked+altered+'_onset24040000.0_n'+str(Nstim)+'_freq'+str(freq)+'_dur3.0_flux'+str(Caflux)+'_Lflux'+str(Lflux)+'_Gluflux'+str(Gluflux)+'_AChflux'+str(Gluflux)+'_Ntrains1_trainT1000.0.mat'
if ifreq == 0 and not exists(filename) and not exists(filename+'.mat') and (exists('muts/'+filename) or exists('muts/'+filename+'.mat')): #do this only once to save i/o, the same should apply to either all freqs or none
addition = 'muts/'
filename = 'muts/'+filename
if exists(filename):
print('Loading '+filename)
conds, times = calcconds.calcconds_nrn(filename)
#print("max(conds) = "+str(max(conds))+", min(conds) = "+str(min(conds)))
minabs = [min(abs(times-(24040000+x*60*1000))) for x in tposts]
its = [[it for it in range(0,len(times)) if times[it]-(24040000+tposts[ipost]*60*1000) == minabs[ipost]][0] for ipost in range(0,len(tposts))]
condposts.append([conds[its[ipost]]/conds[0] for ipost in range(0,len(tposts))])
condposts_abs.append([conds[its[ipost]] for ipost in range(0,len(tposts))])
A = scipy.io.loadmat(filename)
iGluR1 = [i for i in range(0,len(A['headers'])) if 'GluR1_memb' in A['headers'][i]]
iGluR1S831 = [i for i in range(0,len(A['headers'])) if 'GluR1_memb' in A['headers'][i] and 'S831' in A['headers'][i]]
iGluR2 = [i for i in range(0,len(A['headers'])) if 'GluR2_memb' in A['headers'][i]]
GluR1s = [sum([A['DATA'][i][it] for i in iGluR1]) for it in range(0,len(times))]
GluR1S831s = [sum([A['DATA'][i][it] for i in iGluR1S831]) for it in range(0,len(times))]
GluR2s = [sum([A['DATA'][i][it] for i in iGluR2]) for it in range(0,len(times))]
GluR1posts.append([GluR1s[its[ipost]] for ipost in range(0,len(tposts))])
GluR1S831posts.append([GluR1S831s[its[ipost]] for ipost in range(0,len(tposts))])
GluR2posts.append([GluR2s[its[ipost]] for ipost in range(0,len(tposts))])
else:
print(filename+' not found')
condposts.append(list(nan*ones([len(tposts),])))
condposts_abs.append(list(nan*ones([len(tposts),])))
GluR1posts.append(list(nan*ones([len(tposts),])))
GluR1S831posts.append(list(nan*ones([len(tposts),])))
GluR2posts.append(list(nan*ones([len(tposts),])))
return [condposts, condposts_abs, GluR1posts, GluR2posts, GluR1S831posts]
def ltdltpcurves_many(blockeds=['GluR1,GluR1_memb,GluR2,GluR2_memb,Cax0.5,0.5,1.5,1.5,1.0'], T = 100, Caflux = 150.0, Lflux = 5.0, Gluflux = 10.0, altereds = ['_k1x1.0'], freqs = [0.5, 1.0, 2.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 22.0, 25.0, 30.0, 40.0, 50.0, 75.0, 100.0, 200.0, 300.0, 500.0],dodraw = True, epsfilename = '', givenlabels = [], givencolors = []):
tposts = [20, 30, 40] #min after stimulus onset
if len(blockeds) == 1 and len(altereds) == 1:
return ltdltpcurve(blockeds[0], T, Caflux, Lflux, Gluflux, altereds[0], freqs, dodraw)
else:
DATAS = []
print("blockeds="+str(blockeds))
labels = []
if len(blockeds) > 1 and len(altereds) == 1:
for iexp in range(0,len(blockeds)):
DATA = ltdltpcurve(blockeds[iexp], T, Caflux, Lflux, Gluflux, altereds[0], freqs, False)
DATAS.append(DATA[:])
labels.append('blocked-'+str(iexp))
elif len(blockeds) == 1 and len(altereds) > 1:
for iexp in range(0,len(altereds)):
DATA = ltdltpcurve(blockeds[0], T, Caflux, Lflux, Gluflux, altereds[iexp], freqs, False)
DATAS.append(DATA[:])
labels.append('altered-'+str(iexp))
elif len(blockeds) == len(altereds):
for iexp in range(0,len(blockeds)):
DATA = ltdltpcurve(blockeds[iexp], T, Caflux, Lflux, Gluflux, altereds[iexp], freqs, False)
DATAS.append(DATA[:])
labels.append('blocked-'+str(iexp))
else:
for iexp in range(0,len(blockeds)):
for iexp2 in range(0,len(altereds)):
DATA = ltdltpcurve(blockeds[iexp], T, Caflux, Lflux, Gluflux, altereds[iexp2], freqs, False)
DATAS.append(DATA[:])
labels.append('blocked-'+str(iexp)+'_altered-'+str(iexp2))
return DATAS
#BLOCKEDS=( 'DAG' 'Gi' 'Gs' 'MGluR' 'PP1' 'PDE4' 'PP2A' 'PKA' 'PKC' 'PLC' 'NCX' 'PP2B' 'Ng' 'DAG' 'Gi' 'Gs' 'MGluR' 'PP1' 'PDE4' 'PP2A' 'PKA' 'PKC' 'PLC' 'NCX' 'PP2B' 'Ng' )
#BLOCKEDCOEFFS=( 0.98 0.97 0.98 1.09 0.94 1.03 1.02 0.97 0.93 0.91 0.99 1.03 0.92 0.73 0.97 1.0 0.76 0.92 0.92 0.9 0.89 0.86 0.78 0.8 0.84 0.98 )
T = 100
Lflux = 5.0
Gluflux = 10.0
blockeds0 = ['Calbin,CalbinC,DAGK,Gi,MGluR,NCX,Ng,PDE4,PKC,PP1', 'Calbin,CalbinC,DAGK,Gi,MGluR,NCX,Ng,PDE4,PKC,PP1', 'CK,DAGK,Gqabg,PKA', 'DAGK,PKA,PKC,PLA2,PP1', 'CK,Calbin,CalbinC,DAGK,Gi,Gqabg,MGluR,NCX,Ng,PDE4,PKA,PKC,PP1', 'Calbin,CalbinC,DAGK,Gi,MGluR,NCX,Ng,PDE4,PKA,PKC,PLA2,PP1', 'Calbin,CalbinC,DAGK,Gi,Ng,PDE4,PKC', 'DAGK,Gi,Ng,PDE4,PP1', 'CK,DAGK,Gqabg,PKA', 'DAGK,PKA,PKC,PLA2,PP1', 'CK,Calbin,CalbinC,DAGK,Gi,Gqabg,Ng,PDE4,PKA,PKC', 'DAGK,Gi,Ng,PDE4,PKA,PKC,PLA2,PP1', 'DAGK,MGluR,NCX,PDE4,PP1', 'MGluR', 'CK,DAGK,Gqabg,PKA', 'DAGK,PKA,PKC,PLA2,PP1', 'CK,DAGK,Gqabg,MGluR,NCX,PDE4,PKA,PP1', 'DAGK,MGluR,PKA,PKC,PLA2,PP1', 'DAGK,PDE4', 'CK,DAGK,Gqabg,PKA', 'DAGK,PKA,PKC,PLA2,PP1', 'CK,DAGK,Gqabg,PDE4,PKA', 'DAGK,PKA,PKC,PLA2,PP1']
blockedcoeffs0 = [[0.967,0.967,0.974,0.979,1.062,1.090,0.973,1.054,0.994,1.066], [1.025,1.025,0.988,0.968,1.093,1.042,0.941,0.967,0.984,0.986], [0.905,1.140,1.109,1.079], [1.158,1.055,1.056,0.864,0.897], [0.905,0.967,0.967,1.029,0.979,1.109,1.062,1.090,0.973,1.054,1.079,0.994,1.066], [1.025,1.025,1.045,0.968,1.093,1.042,0.941,0.967,1.055,1.020,0.864,0.942], [0.985,0.985,0.924,0.971,0.962,1.012,0.996], [0.992,0.984,0.944,0.977,0.992], [0.959,1.072,1.063,1.048], [1.134,1.039,1.037,0.933,0.940], [0.959,0.985,0.985,0.998,0.971,1.063,0.962,1.012,1.048,0.996], [1.039,0.984,0.944,0.977,1.039,1.037,0.933,0.966], [0.918,1.062,1.090,1.054,1.066], [1.093], [0.905,1.140,1.109,1.079], [1.158,1.055,1.056,0.864,0.897], [0.905,1.029,1.109,1.062,1.090,1.054,1.079,1.066], [1.158,1.093,1.055,1.056,0.864,0.897], [0.924,1.012], [0.959,1.072,1.063,1.048], [1.134,1.039,1.037,0.933,0.940], [0.959,0.998,1.063,1.012,1.048], [1.134,1.039,1.037,0.933,0.940]]
geneparams = ['sig0,imp0\n,GWAS,PFC','sig0,imp0\n,GWAS,ACC','sig0,imp0\n,CommonMind,PFC','sig0,imp0\n,CommonMind,ACC','sig0,imp0\n,Both,PFC','sig0,imp0\n,Both,ACC','sig0,imp1,\nGWAS,PFC','sig0,imp1,\nGWAS,ACC','sig0,imp1,\nCommonMind,PFC','sig0,imp1,\nCommonMind,ACC','sig0,imp1,\nBoth,PFC','sig0,imp1,\nBoth,ACC','sig1,imp0\n,GWAS,PFC','sig1,imp0\n,GWAS,ACC','sig1,imp0\n,CommonMind,PFC','sig1,imp0\n,CommonMind,ACC','sig1,imp0\n,Both,PFC','sig1,imp0\n,Both,ACC','sig1,imp1,\nGWAS,PFC','sig1,imp1,\nCommonMind,PFC','sig1,imp1,\nCommonMind,ACC','sig1,imp1,\nBoth,PFC','sig1,imp1,\nBoth,ACC']
icombs = [10,11]
#cols = ['#BBBBBB','#666666', '#AA0000', '#FF2222','#FF00FF','#006600','#660066','#00FF00','#AAAA00','#FFFF00','#FF9B00','#000066','#770077','#00FF00']
cols = ['#BBBBBB','#666666', '#AA0000', '#FF2222','#FF00FF','#888800','#FF00FF','#888800','#FF00FF','#888800','#FF00FF','#888800','#FF00FF','#888800','#FF00FF','#888800','#FF00FF','#888800','#FF00FF','#888800']
#cols = ['#00CC00','#6666FF']
f,axs = subplots(2,6)
axinsets = []
for iax in range(0,6):
for iay in range(0,2):
axs[iay,iax].set_position([0.08+0.15*iax,0.68-0.3*iay,0.15,0.22])
for tick in axs[iay,iax].xaxis.get_major_ticks()+axs[iay,iax].yaxis.get_major_ticks():
tick.label.set_fontsize(4)
for axis in ['top','bottom','left','right']:
axs[iay,iax].spines[axis].set_linewidth(0.3)
for iay in range(0,2):
for iax in range(0,6):
axinsets.append(f.add_axes([0.19+0.15*iax,0.69-0.3*iay,0.025,0.1]))
for tick in axinsets[-1].xaxis.get_major_ticks()+axinsets[-1].yaxis.get_major_ticks():
tick.label.set_fontsize(4)
for axis in ['top','bottom','left','right']:
axinsets[-1].spines[axis].set_linewidth(0.3)
axinsets[-1].set_xticks([])
boxoff(axinsets[-1])
axarr = axs.reshape(prod(axs.shape),).tolist()
for i in [1,2,3,4,5,7,8,9,10,11]:
axarr[i].set_yticklabels([])
for i in [6,7,8,9,10,11]:
axarr[i].set_xlabel('$f$ (Hz)',fontsize=6)
for i in [0,6]:
axarr[i].set_ylabel('Syn. cond. (fold change)',fontsize=6)
GluRCoeffs = ['0.5,0.5,1.5,1.5']
myfreqs = [0.001]+[1.0*i for i in range(1,21)]
min10 = [inf,inf,inf]
max10 = [-inf,-inf,-inf]
min20 = [inf,inf,inf]
max20 = [-inf,-inf,-inf]
contr10 = [-inf,-inf,-inf]
contr20 = [-inf,-inf,-inf]
#blockeds_orig = ['Calbin,CalbinC','DAGK','Gi','MGluR','Gqabg','PKC','PLA2','CK','Ng','NCX','PDE4','PKA','PP1','CMcomb','CMcomb']
#blockeds_orig = ['PKA', 'PP1', 'PLA2', 'PDE4', 'PKC', 'CK', 'Ng', 'NCX', 'Gqabg', 'MGluR', 'Calbin,CalbinC','DAGK','Gi', 'CMcomb', 'CMcomb']
blockeds_orig = ['PKA', 'PP1', 'PLA2', 'PDE4', 'PKC', 'CK', 'Ng', 'Gqabg', 'Calbin,CalbinC','DAGK','Gi', 'CMcomb']
blockedTitles = ['PKA', 'PP1', 'PLA2', 'PDE4', 'PKC', 'CaMKII', 'Neurogranin', 'Gq', 'Calbindin','DAGK','Gi', 'Combinations']
Caflux = 150.0
for iglur in range(0,len(GluRCoeffs)):
DATAS_0_CONTROL = ltdltpcurves_many(['GluR1,GluR1_memb,GluR2,GluR2_memb,Cax'+GluRCoeffs[iglur]+',1.0'], T, Caflux, Lflux, Gluflux, [''], freqs = myfreqs, dodraw = False)
#print(str(DATAS_0_CONTROL))
minmaxes = []
#blockeds = ['DAG','Gi','MGluR','Gs','PLC','PKC','PP2A','Ng','PKA','NCX','PDE4','PP2B','PP1']
#blockedTitles = ['DAG','Gi','mGluR','Gs','PLC','PKC','PP2A','Ng','PKA','NCX','PDE4','PP2B','PP1']
#blockedCoeffs = [[0.98,0.97,1.09,0.98,0.91,0.93,1.02,0.92,0.97,0.99,1.03,1.03,0.94],[0.73,0.97,0.76,1.0,0.78,0.86,0.9,0.98,0.89,0.8,0.92,0.84,0.92]]
for iicomb in range(0,len(icombs)):
icomb = icombs[iicomb]
blockeds = blockeds0[icomb].split(',')
blockedcoeffs = [str(x) for x in blockedcoeffs0[icomb]]
for i in range(0,len(blockeds)-1):
if blockeds[i] == 'Calbin' and blockeds[i+1] == 'CalbinC':
blockeds = blockeds[0:i]+['Calbin,CalbinC']+blockeds[i+2:]
blockedcoeffs = blockedcoeffs[0:i]+[blockedcoeffs[i]+','+blockedcoeffs[i+1]]+blockedcoeffs[i+2:]
break
for iblocked in range(0,len(blockeds)):
coeff = blockedcoeffs[iblocked]
iax = [i for i in range(0,len(blockeds_orig)) if blockeds_orig[i] == blockeds[iblocked]][0]
blocked_base = 'GluR1,GluR1_memb,GluR2,GluR2_memb,'+blockeds[iblocked]+'x'+GluRCoeffs[iglur]+','+coeff
DATAS_0 = ltdltpcurves_many([blocked_base], T, Caflux, Lflux, Gluflux, [''], freqs = myfreqs, dodraw = False)
#print(str(DATAS_0))
if DATAS_0[0][10][1] < min10[iglur]:
min10[iglur] = DATAS_0[0][10][1]
if DATAS_0[0][10][1] > max10[iglur]:
max10[iglur] = DATAS_0[0][10][1]
if DATAS_0[0][20][1] < min20[iglur]:
min20[iglur] = DATAS_0[0][20][1]
if DATAS_0[0][20][1] > max20[iglur]:
max20[iglur] = DATAS_0[0][20][1]
axarr[iax].plot(myfreqs,[DATAS_0[0][i][1] for i in range(0,len(DATAS_0[0]))],'b.-', lw=0.3, ms=1.0, mew=1.0, color=cols[icomb], label = blockeds[iblocked])
print('icomb '+str(icomb)+' iblocked '+str(iblocked)+' ('+blockeds_orig[iax]+') plotted in iax '+str(iax)+', max='+str(max([DATAS_0[0][i][1] for i in range(0,len(DATAS_0[0]))]))+
'LTP amplitude changed by '+str((max([DATAS_0[0][i][1] for i in range(0,len(DATAS_0[0]))])-1)/(max([DATAS_0_CONTROL[0][i][1] for i in range(0,len(DATAS_0_CONTROL[0]))])-1)*100-100)+'% , col='+cols[icomb])
minmaxes.append([min([DATAS_0[0][i][1] for i in range(0,len(DATAS_0[0]))]),max([DATAS_0[0][i][1] for i in range(0,len(DATAS_0[0]))])])
#if iglur == 0:
axinsets[iax].bar(icomb-min(icombs),DATAS_0[1][0][-1],color=cols[icomb])
# #print("DATAS_0[0][0][0] = "+str(DATAS_0[0][0][0])+", DATAS_0[0][0][1] = "+str(DATAS_0[0][0][1]))
axarr[iax].plot(myfreqs,[DATAS_0_CONTROL[0][i][1] for i in range(0,len(DATAS_0_CONTROL[0]))],'b.--', lw=0.3, ms=1.0, mew=1.0, color='#000000', label = 'Control')
print('control iblocked '+str(iblocked)+' plotted in iax '+str(iax)+', max='+str(max([DATAS_0_CONTROL[0][i][1] for i in range(0,len(DATAS_0_CONTROL[0]))])))
axarr[iax].set_xlim([10,20])
axarr[iax].set_ylim([1.4,2.6])
axinsets[iax].bar(-1,DATAS_0_CONTROL[1][0][-1],color='#000000')
axinsets[iax].set_xlim([-1.5,1.5])
axinsets[iax].set_ylim([0,43])
contr10[iglur] = DATAS_0_CONTROL[0][10][1]
contr20[iglur] = DATAS_0_CONTROL[0][20][1]
axarr[iax].set_title(blockedTitles[iax],fontsize=7)
if coeff.find(',') > -1:
coeff = coeff.split(',')[0]
if coeff[0] == '0':
mystr = '-'+'{:.1f}'.format((1-float(coeff))*100)+'%'
else:
mystr = '+'+'{:.1f}'.format((float(coeff)-1)*100)+'%'
axarr[iax].text(11.0,1.47+0.1*iicomb,mystr,fontsize=6,ha='left',va='bottom',color=cols[icomb])
for iblocked in range(len(blockeds_orig)-1,len(blockeds_orig)):
blockedSet = [10,11]
for iicoeff in range(0,len(blockedSet)):
#blocked_base = 'GluR1,GluR1_memb,GluR2,GluR2_memb,PDE1A,Cax0.5,0.5,1.5,1.5,0.8,1.0'
iblockedCoeff = blockedSet[iicoeff]
blockedCoeffs = [0.5,0.8,1.2,1.5,4,5,6,7,8,9,10,11,12,13]
coeff = blockedCoeffs[iblockedCoeff]
Nsamespecies = blockeds_orig[iblocked].count(',')+1
blocked_base = 'GluR1,GluR1_memb,GluR2,GluR2_memb,'+blockeds_orig[iblocked]+'x'+GluRCoeffs[iglur]+','+','.join([str(coeff) for i in range(0,Nsamespecies)])
DATAS_0 = ltdltpcurves_many([blocked_base], T, Caflux, Lflux, Gluflux, [''], freqs = myfreqs, dodraw = False)
axarr[iblocked].plot(myfreqs,[DATAS_0[0][i][1] for i in range(0,len(DATAS_0[0]))],'b.-', lw=0.3, ms=1.0, mew=1.0, color=cols[iblockedCoeff], label = blockeds_orig[iblocked])
axinsets[iblocked].bar(-1+2*iicoeff if iblocked < len(blockeds)-1 else iicoeff,DATAS_0[1][0][-1],color=cols[iblockedCoeff])
print('baseline = '+str(DATAS_0[1][0][-1])+', max = '+str(max([DATAS_0[0][i][1] for i in range(0,len(DATAS_0[0]))])))
axarr[iblocked].plot(myfreqs,[DATAS_0_CONTROL[0][i][1] for i in range(0,len(DATAS_0_CONTROL[0]))],'b.-', lw=0.3, ms=1.0, mew=1.0, color='#000000', label = 'Control')
axarr[iblocked].set_xlim([10,20])
axarr[iblocked].set_ylim([1.4,2.6])
axinsets[iblocked].bar(0 if iblocked < len(blockeds)-1 else -1,DATAS_0_CONTROL[1][0][-1],color='#000000')
print('baseline = '+str(DATAS_0_CONTROL[1][0][-1])+', max = '+str(max([DATAS_0_CONTROL[0][i][1] for i in range(0,len(DATAS_0_CONTROL[0]))])))
axinsets[iblocked].set_xlim([-1.5,1.5])
axinsets[iblocked].set_ylim([0,43])
axarr[iblocked].set_title('Combinations',fontsize=7)
#axarr[1,iglur].set_xlabel(GluRCoeffs[iglur],fontsize=7)
print(str(min10)+","+str(max10)+","+str(min20)+","+str(max20))
print("control: "+str(contr10)+",2"+str(contr20))
print("minmaxes = "+str(minmaxes))
#axarr[0,1].legend(fontsize=5)
for i in [0,1,2,3,4,6,7,8,9,10]:
axarr[i].set_xticks([10,15])
for i in range(0,12):
points = axarr[i+(i==13)].get_position().get_points()
#if i not in [3,9]:
f.text(points[0,0]+0.007,points[1,1]-0.024,chr(ord('A')+i),fontsize=10)
#for iax in [3,9]:
# axarr[iax].set_visible(False)
# axinsets[iax].set_visible(False)
f.savefig('fig_ltdltpcurves_CMmut_all.eps')