def store_map(new_to_map): fp_dataset_algo=open("mapping_dataset_algo","r") previously_mapped=pickle.load(fp_dataset_algo) fp_dataset_algo.close() algo_index=train_with_all.choose_best(new_to_map) best_chosen_new=algorithms_m[algo_index] temp=[] temp.append(new_to_map) temp.append(best_chosen_new) previously_mapped.append(temp) # Opening the same for updating purpose fp_dataset_algo_for_update=open("mapping_dataset_algo","w+") fp_dataset_algo_for_update.seek(0) pickle.dump(previously_mapped,fp_dataset_algo_for_update) fp_dataset_algo_for_update.close()
def store_map_main(): fp_sm=open("trained_databases","r") trained_dbs=pickle.load(fp_sm) print trained_dbs for i in range(len(trained_dbs)): algo_index=train_with_all.choose_best(trained_dbs[i]) best_chosen_algo.append(algorithms_m[algo_index]) print best_chosen_algo for i in range(len(trained_dbs)): temp=[] temp.append(trained_dbs[i]) temp.append(best_chosen_algo[i]) dataset_algo.append(temp) print dataset_algo fp_dataset_algo=open("mapping_dataset_algo","w+") pickle.dump(dataset_algo,fp_dataset_algo)