import numpy as np import copy data=np.load("data.npz", allow_pickle=True) data=dict(data) size_database=len(data['database_labels']) for target_index in range(len(data['target_labels'])): CT=data['target_ncharges'][target_index] T=data['target_CMs'][target_index] I=[] for i in range(len(CT)): if CT[i] == 1: I.append(i) CT=np.delete(CT, I) T=np.delete(T, I, axis=0) T=np.delete(T,I,axis=1) data['target_ncharges'][target_index]=CT data['target_CMs'][target_index]=T for i in range(size_database): print(" ", i) M=data['database_CMs'][i] CM=data['database_ncharges'][i] m=len(CM) J=[] for j in range(m): if CM[j]==1: J.append(j) CM=np.delete(CM,J) M=np.delete(M,J,axis=0) M=np.delete(M,J,axis=1) data['database_CMs'][i]=M data['database_ncharges'][i]=CM labels='database_labels' ncharges='database_ncharges' CMs='database_CMs' np.savez("qm7_CM_data.npz", vitc_qm7_labels=data[labels], vitc_qm7_ncharges=data[ncharges], vitc_qm7_CMs=data[CMs], vitd_qm7_labels=data[labels], vitd_qm7_ncharges=data[ncharges], vitd_qm7_CMs=data[CMs], qm9_qm7_labels=data[labels], qm9_qm7_ncharges=data[ncharges], qm9_qm7_CMs=data[CMs])