def main():
file = "comTraj.npz"
L, com_lipids, com_chol = trajIO.decompress(file)
com_lipids, com_chol = trajIO.translateZ(com_lipids, com_chol)
com_lipids = displacement.block_displacement(L, com_lipids)
com_chol = displacement.block_displacement(L, com_chol)
t = 28
lipids = com_lipids[t]
chol = com_chol[t]
lipids, trash = trajIO.layering(lipids)
chol, trash = trajIO.layering(chol)
total = np.concatenate((lipids, chol), axis=0)
total1 = iter.combine(lipids, chol)
cluster = percentages.cluster(total, [0.25, 0.25, 0.25, 0.25])
cluster1 = percentages.cluster(total1, [0.25, 0.25, 0.25, 0.25])
#edm = euclideanDist.edm(L[t],cluster[0])
#edm1 = euclideanDist.edm(L[t],cluster1[0])
#print(np.array_equiv(edm,edm1))
cutoff = 1.15
labels1 = dc.dbscan_wrapper(cluster[0], L[t], cutoff)
labels2 = iter.cluster_labels('upper', L[t], cluster1[0])
return labels1, labels2
def test_clusters(
): #not a complete testfunction but the function should nonetheless be accurate
file = "comTraj.npz"
L, com_lipids, com_chol = trajIO.decompress(file)
com_lipids = displacement.block_displacement(L, com_lipids)
Nlipids = com_lipids.shape[1]
clusters = jenks_clusters.clusters(com_lipids[40], 4)
return clusters
def s_test():
file = "comTraj.npz"
L,com_lipids,com_chol = trajIO.decompress(file)
control = displacement.block_displacement(L,com_lipids)
control = control[:,:,3]
test = com_lipids
test = displacement.s(L,com_lipids,0,list(range(1,46)))
test = displacement.s(L,test,46,np.asarray(list(range(1,46)))+46)
test = displacement.s(L,test,92,[93,94,95,96,97,98,99])
test = test[:,:,3]
for t in range(100):
boo = (test[t] == control[t])
print(boo.all())
def test_sort():
file = "comTraj.npz"
L, com_lipids, com_chol = trajIO.decompress(file)
com_lipids = displacement.block_displacement(L, com_lipids)
Nlipids = com_lipids.shape[1]
Nconf = com_lipids.shape[0]
for t in range(Nconf):
lipids = com_lipids[t][com_lipids[t][:, 3].argsort()]
curr = 0
for i in range(Nlipids):
if curr > lipids[i, 3]:
print("sorting messed up")
raise ValueError
else:
curr = lipids[i, 3]
return True
def linear_test():
file = "comTraj.npz"
L,com_lipids,com_chol = trajIO.decompress(file)
control = displacement.block_displacement(L,com_lipids)
control1 = control[:,:,3]
test = displacement.linear_displacement(L,control,0,100)
test1 = test[:,:,3]
print(test1.shape)
for t in range(46):
boo = (test1[t] == control1[t])
print(boo.all())
print("hi")
for t in [46,92]:
boo = (test1[t] != control1[t])
print(boo.all())
trajFileName, Nchol, c.NDIM, Nconf)
com_lipids, com_chol = trajIO.translateZ(com_lipids, com_chol)
Nlipids = com_lipids.shape[0]
else:
L, com_lipids, com_chol = trajIO.decompress(trajFileName)
com_lipids, com_chol = trajIO.translateZ(com_lipids, com_chol)
#parameters
del com_chol
cluster_sizes = [name]
name = str(cluster_sizes[0])
sys.stdout = open("norm" + name + ".txt", "w")
times = list(range(1, 46))
com_lipids = displacement.block_displacement(L, com_lipids)
#initialize output dict
normSizes = {}
for block in range(Nblock):
normSizes[block] = {}
for t in times:
normSizes[block][t] = {}
for layer in ['upper', 'lower']:
normSizes[block][t][layer] = {}
for size in cluster_sizes:
normSizes[block][t][layer][size] = [0 for i in range(size)]
for block in range(Nblock):
t = nlog
L, com_lipids, com_chol = trajIO.decompress(trajFileName)
Nchol = com_chol.shape[1]
Nchol = 0
Nlipids = com_lipids.shape[1]
Nblock = Nconf // nlog
com_lipids, com_chol = trajIO.translateZ(com_lipids, com_chol)
#parameters
cluster_sizes = [2, 5]
times = list(range(1, 46))
#calculating displacement
com_lipids = displacement.block_displacement(L, com_lipids)
if Nchol: com_chol = displacement.block_displacement(L, com_chol)
else: del com_chol
#cluster dict
clusters = {} #cluster[nblock][time][type][layer][cluster_size]
for block in range(Nblock):
clusters[block] = {}
for t in times:
clusters[block][t] = {}
clusters[block][t]['lipids'] = {}
if Nchol: clusters[block][t]['chol'] = {}
for layer in ['upper', 'lower']:
clusters[block][t]['lipids'][layer] = {}
if Nchol: clusters[block][t]['chol'][layer] = {}
L, com_lipids, com_chol = trajIO.decompress(trajFileName)
Nchol = com_chol.shape[1]
Nlipids = com_lipids.shape[1]
Nblock = Nconf // nlog
com_lipids, com_chol = trajIO.translateZ(com_lipids, com_chol)
del com_lipids
#parameters
cluster_sizes = [2, 3, 4, 5]
times = list(range(1, 46))
#calculating displacement
com_chol = displacement.block_displacement(L, com_chol)
#cluster dict
clusters = {} #cluster[nblock][time][type][layer][cluster_size]
for block in range(Nblock):
clusters[block] = {}
for t in times:
clusters[block][t] = {}
clusters[block][t]['chol'] = {}
for layer in ['upper', 'lower']:
clusters[block][t]['chol'][layer] = {}
for block in range(Nblock):
t = nlog
time = block * nlog + t
