def getNetworkMeansBtw(networkAvg, netw1, other_netw, numRuns):
allMeans=np.zeros(len(other_netw))
allSTDs=np.zeros(len(other_netw))
i=0
for net in other_netw:
netw1btwnetw_mean=getNetworkBtw(networkAvg, netw1, net, numRuns)
allMeans[i]=np.mean(netw1btwnetw_mean)
allSTDs[i]=np.std(netw1btwnetw_mean)
i=i+1
return allMeans, allSTDs
objSelCoher=getNetworkWithin(networkAvg, objSel)
#Average over last two dimensions....
earlyVentCoher_mean=stats.nanmean(earlyVentCoher.reshape([numRuns,len(earlyVent)*len(earlyVent)]), axis=1)
earlyDorsCoher_mean=stats.nanmean(earlyDorsCoher.reshape([numRuns,len(earlyDors)*len(earlyDors)]), axis=1)
parietalCoher_mean=stats.nanmean(parietalCoher.reshape([numRuns,len(parietal)*len(parietal)]), axis=1)
objSelCoher_mean=stats.nanmean(objSelCoher.reshape([numRuns,len(objSel)*len(objSel)]), axis=1)
#Correlation means and STDs across all RUNs correlation/coherence values.
allMeansWithin= (stats.nanmean(earlyVentCoher_mean), stats.nanmean(earlyDorsCoher_mean), stats.nanmean(parietalCoher_mean), stats.nanmean(objSelCoher_mean))
allSTDWithin=(stats.nanstd(earlyVentCoher_mean), stats.nanstd(earlyDorsCoher_mean), stats.nanstd(parietalCoher_mean), stats.nanstd(objSelCoher_mean))
# Get network btw
#Early Visual
EVbtwED_mean=getNetworkBtw(networkAvg, earlyVent, earlyDors, numRuns); EVbtwEDavg=np.mean(EVbtwED_mean); EVbtwEDstd=np.std(EVbtwED_mean)
EVbtwPar_mean=getNetworkBtw(networkAvg, earlyVent, parietal, numRuns); EVbtwParavg=np.mean(EVbtwPar_mean); EVbtwParstd=np.std(EVbtwPar_mean)
EVbtwObjSel_mean=getNetworkBtw(networkAvg, earlyVent, objSel, numRuns); EVbtwObjSelavg=np.mean(EVbtwObjSel_mean); EVbtwObjSelstd=np.std(EVbtwObjSel_mean)
# Early Dorsal
EDbtwEV_mean=getNetworkBtw(networkAvg, earlyDors, earlyVent, numRuns); EDbtwEVavg=np.mean(EDbtwEV_mean); EDbtwEVstd=np.std(EDbtwEV_mean)
EDbtwPar_mean=getNetworkBtw(networkAvg, earlyDors, parietal, numRuns); EDbtwParavg=np.mean(EDbtwPar_mean); EDbtwParstd=np.std(EDbtwPar_mean)
EDbtwObjSel_mean=getNetworkBtw(networkAvg, earlyDors, objSel, numRuns); EDbtwObjSelavg=np.mean(EDbtwObjSel_mean); EDbtwObjSelstd=np.std(EDbtwObjSel_mean)
# Parietal
ParbtwEV_mean=getNetworkBtw(networkAvg, parietal, earlyVent, numRuns); ParbtwEVavg=np.mean(ParbtwEV_mean); ParbtwEVstd=np.std(ParbtwEV_mean)
ParbtwED_mean=getNetworkBtw(networkAvg, parietal, earlyDors, numRuns); ParbtwEDavg=np.mean(ParbtwED_mean); ParbtwEDstd=np.std(ParbtwED_mean)
ParbtwObjSel_mean=getNetworkBtw(networkAvg, parietal, objSel, numRuns); ParbtwObjSelavg=np.mean(ParbtwObjSel_mean); ParbtwObjSelstd=np.std(ParbtwObjSel_mean)
# Object Selective
ObjSelbtwEV_mean=getNetworkBtw(networkAvg, objSel, earlyVent, numRuns); ObjSelbtwEVavg=np.mean(ObjSelbtwEV_mean); ObjSelbtwEVstd=np.std(ObjSelbtwEV_mean)