del sys.argv[1]
if option == '-p1':
p1 = float(sys.argv[1].replace(',', '.'))
del sys.argv[1]
elif option == '-p2':
p2 = float(sys.argv[1].replace(',', '.'))
del sys.argv[1]
elif option == '-p3':
p3 = str(sys.argv[1])
del sys.argv[1]
else:
print 'Options invalides :', option, '->', sys.argv[0]
main = '/home/mathieuG/SearchForPatt/%s' % p3
typ2 = '_pC'
mkdir(main + typ2)
dir1S = main + '/Cand_S/'
dir1X = main + '/Cand_X/'
dir2S = main + typ2 + '/Cand_S/'
dir2X = main + typ2 + '/Cand_X/'
mkdir(dir2S)
mkdir(dir2X)
sim_coef = 0.9
#endFName = '_P_%.2f_f0_%.2f.npy' %(p1,p2)
endFName = '_P_%.2f_G_%.2f.npy' % (p1, p2)
fileName = 'patterns' + endFName
############################################################################################'
# **Main**
if not adressExists(dir2X + fileName):
tic()
# **Parameters**
while len(sys.argv) > 1:
option = sys.argv[1]; del sys.argv[1]
if option == '-G': G = float(sys.argv[1].replace(',','.')); del sys.argv[1]
elif option == '-sx': sx = float(sys.argv[1].replace(',','.')); del sys.argv[1]
elif option == '-sT': sT = float(sys.argv[1].replace(',','.')); del sys.argv[1]
elif option == '-dir': dir_= str(sys.argv[1]); del sys.argv[1]
else:
print 'Options invalides :',option,'->',sys.argv[0]
mdir = '/home/mathieuG/TCS/%s' %dir_
name = 'G_%.2f_sx_%.3f_sT_%.3f.npy' %(G, sx, sT)
dir_DFC = mdir + '/DFC_998/'
dir_TC = mdir + '/TC_998/'
try:
mkdir(dir_DFC)
except:
pass
############################################################################################'
# **Main**
if not adressExists(dir_DFC + name):
TC = data2array(dir_TC + name)
FCs = windowedFCs(TC, window=6000, jump=100)
DFC = windowedCorrelations(FCs)
array2data(DFC, dir_DFC + name)
S = sortBy(patts.mean(1) - patts.mean(), inverse=1)[0]
C1, freq = preClustering(patts[S], sim_coef=sim_coef, sim_func=similarity_Euclidean)
C2, freq = preClustering(patts[S][C1], freq=freq, sim_coef=sim_coef, sim_func=fPearsonCorrelation)
SC, freq = sortBy(freq, inverse=1)
array2data(pattsx[S][C1][C2][SC], dir_prix + '/patterns_' + endDir)
array2data(pattsA[S][C1][C2][SC], dir_priA + '/patterns_' + endDir)
array2data(freq, dir_priT + '/tendances_' + endDir)
os.system('rm ' + dir_prix + '/allPatt_' + endDir)
os.system('rm ' + dir_priA + '/allPatt_' + endDir)
return len(pattsx[S][C1][C2][SC])
############################################################################################'
# **Main**
dir_sub = '/dP_G_%.3f_r_%i.npy' %(G, revert)
if not adressExists(dir_priC + dir_sub):
mkdir(dir_prix)
mkdir(dir_priA)
mkdir(dir_priT)
mkdir(dir_priC)
if revert: x = [0.95, 2.00]
else: x = [0.00, 1.05]
dx = paramExplo(funcNbofAttr, nb=[7,1], ax='x', x=x, y=[G], revert=revert)
array2data(dx, dir_priC + dir_sub)
# **Parameters**
while len(sys.argv) > 1:
option = sys.argv[1]
del sys.argv[1]
if option == '-p1':
p1 = float(sys.argv[1].replace(',', '.'))
del sys.argv[1]
elif option == '-p2':
p2 = float(sys.argv[1].replace(',', '.'))
del sys.argv[1]
else:
print 'Options invalides :', option, '->', sys.argv[0]
dir_priA = './withG_SG/Cand_S'
dir_prix = './withG_SG/Cand_X'
mkdir(dir_priA)
mkdir(dir_prix)
#dir_sub = '/patterns_P_%.2f_f0_%.2f.npy' %(p1,p2)
dir_sub = '/patterns_P_%.2f_G_%.2f.npy' % (p1, p2)
############################################################################################'
# **Main**
multi_dens = arange(0.02, 0.981, 0.03) # (33)
all_pattx = zeros((3300, 998))
all_pattA = zeros((3300, 998))
conn = {'connAd': Pdir('Connectomes/SC_FB_D_998_0.npy'), 'normType': '1'}
noise = {'colors': None}
model = {
elif option == '-sT':
sT = float(sys.argv[1].replace(',', '.'))
del sys.argv[1]
elif option == '-dir':
dir_ = str(sys.argv[1])
del sys.argv[1]
else:
print 'Options invalides :', option, '->', sys.argv[0]
mdir = '/home/mathieuG/TCS/%s' % dir_
name = 'P_%.2f_sigmax_%.2f.npy' % (P, sx)
dir_FC = mdir + '/FC_998'
dir_TC = mdir + '/TC_998'
try:
mkdir(dir_FC)
mkdir(dir_TC)
except:
pass
############################################################################################'
# **Main**
if not adressExists(dir_TC + '/TC_998_' + name):
conn = {
'connAd': "/home/mathieuG/Connectomes/Hagmann/SC_D_998_0.npy",
'normC': 1.
}
model = {
'model': 'HopfieldBasedDynamic',