Пример #1
0
    try:
        file_trig_times = f["trigger_times"][:]
    except:
        file_trig_times = None
    if use_old_reco:
        file_reco_labels = f["reco_labels"][:]
    f.close()
    del f
   
    if file_labels.shape[0] == 0:
        print("Empty file...skipping...")
        continue
    
    # Applying cuts
    type_mask = CutMask(file_labels)
    vertex_mask = VertexMask(file_labels,azimuth_index=azimuth_index,track_index=track_index,max_track=track_max)
    vertex_cut = np.logical_and(vertex_mask[start_cut], vertex_mask[end_cut])
    mask = np.logical_and(type_mask[cut_name], vertex_cut)
    mask = np.array(mask,dtype=bool)

    energy = file_labels[:,0]
    keep_index = [False]*len(energy)
    print("Total events this file: %i"%len(energy))

    # Check how many events already in each bin, save if under max
    for index,e in enumerate(energy):
        if e > emax:
            continue
        if e < emin:
            continue
Пример #2
0
        Y_train[:, 0] = np.log10(Y_train[:, 0])
        Y_validate[:, 0] = np.log10(Y_validate[:, 0])

    if chop_energy:
        cut_train = Y_train[:, 0] < ecut / 100.
        cut_validate = Y_validate[:, 0] < ecut / 100.
        Y_train = Y_train[cut_train]
        X_train_DC = X_train_DC[cut_train]
        X_train_IC = X_train_IC[cut_train]
        Y_validate = Y_validate[cut_validate]
        X_validate_DC = X_validate_DC[cut_validate]
        X_validate_IC = X_validate_IC[cut_validate]

    if vertex_cut:
        vertex_mask_train = VertexMask(Y_train,
                                       azimuth_index=7,
                                       track_index=2,
                                       max_track=200.)
        cut_train = vertex_mask_train["start_IC19"]
        vertex_mask_val = VertexMask(Y_validate,
                                     azimuth_index=7,
                                     track_index=2,
                                     max_track=200.)
        cut_validate = vertex_mask_val["start_IC19"]
        print("Removing %i events from train, %i events from validate" %
              ((len(cut_train) - sum(cut_train)),
               (len(cut_validate) - sum(cut_validate))))
        Y_train = Y_train[cut_train]
        X_train_DC = X_train_DC[cut_train]
        X_train_IC = X_train_IC[cut_train]
        Y_validate = Y_validate[cut_validate]
        X_validate_DC = X_validate_DC[cut_validate]