# TEMP # df_dft = df_dft.sample(n=3) # bulk_id_i = "64cg6j9any" # bulk_id_i = "zwvqnhbk7f" # bulk_id_i = "8p8evt9pcg" bulk_id_i = "b5cgvsb16w" # df_dft = df_dft.loc[[bulk_id_i]] # - # # Main loop # + from methods import get_df_xrd df_xrd_old = get_df_xrd() print("Number of rows in df_xrd:", df_xrd_old.shape[0]) # + # df_xrd_old.drop_duplicates( # + # assert False # + for i_cnt, (id_unique_i, row_i) in enumerate(df_dft.iterrows()): data_dict_i = dict() if verbose: print(40 * "=") print(str(i_cnt).zfill(3), "id_unique_i:", id_unique_i)
# verbose = False # bulk_id_i = "8ymh8qnl6o" # bulk_id_i = "8p8evt9pcg" # bulk_id_i = "8l919k6s7p" bulk_id_i = "64cg6j9any" # - # # Read Data # + df_dft = get_df_dft() print("df_dft.shape:", df_dft.shape[0]) from methods import get_df_xrd df_xrd = get_df_xrd() df_xrd = df_xrd.set_index("id_unique", drop=False) # + active="" # # # # + # ######################################################### row_i = df_dft.loc[bulk_id_i] # ######################################################### atoms_i = row_i.atoms atoms_stan_prim_i = row_i.atoms_stan_prim # #########################################################