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