将新数据添加到 HDF5 文件中会导致一个空数组

Adding new data into HDF5 file results an empty array

在玩 Python 的 HDF5 包时,我发现了一个奇怪的行为。我想在 table 中插入更多数据。但不知何故我无法让它正常工作。正如您从源代码中看到的那样,我使用 fromRow = hf["X"].shape[0] 获取键 'X' 中的最后一行数据,然后写入 tempArray2。结果为空 table.

import h5py

tempArray1 = [[0.9293237924575806, -0.32789671421051025, 0.18110771477222443], [0.9293237924575806, -0.32789671421051025, 0.18110771477222443], [0.9293237924575806, -0.32789671421051025, 0.18110771477222443], [0.9293237924575806, -0.32789671421051025, 0.18110771477222443], [0.9293237924575806, -0.32789671421051025, 0.18110771477222443], [0.9293237924575806, -0.32789671421051025, 0.18110771477222443], [0.9293237924575806, -0.32789671421051025, 0.18110771477222443], [0.9293237924575806, -0.32789671421051025, 0.18110771477222443], [0.9293237924575806, -0.32789671421051025, 0.18110771477222443], [0.9293237924575806, -0.32789671421051025, 0.18110771477222443]]
tempArray2 = [[3.1387749004352372e-06, 8.120089097236803e+27, -1.645612730013634e-14], [3.1387749004352372e-06, 8.120089097236803e+27, -1.645612730013634e-14], [3.1387749004352372e-06, 8.120089097236803e+27, -1.645612730013634e-14], [3.1387749004352372e-06, 8.120089097236803e+27, -1.645612730013634e-14], [3.1387749004352372e-06, 8.120089097236803e+27, -1.645612730013634e-14], [3.1387749004352372e-06, 8.120089097236803e+27, -1.645612730013634e-14], [3.1387749004352372e-06, 8.120089097236803e+27, -1.645612730013634e-14], [3.1387749004352372e-06, 8.120089097236803e+27, -1.645612730013634e-14], [3.1387749004352372e-06, 8.120089097236803e+27, -1.645612730013634e-14], [3.1387749004352372e-06, 8.120089097236803e+27, -1.645612730013634e-14]]

with h5py.File('data.hdf5', 'w') as hf:
    # Add data to new file
    dset = hf.create_dataset("X", data=tempArray1, compression="gzip", chunks=True, maxshape=(None,3), dtype='f4') # Size is as the size of tempArray1
    print(hf["X"].shape[0])

    # Append data existing file
    hf["X"].resize((hf["X"].shape[0] + 10, 3)) # Size is as the size of X+ 10
    print(hf["X"].shape[0])
    fromRow = hf["X"].shape[0]
    hf["X"][fromRow:] = tempArray2

这是它的样子:

Key: X
Data:
 [[ 0.9293238  -0.3278967   0.18110771]
 [ 0.9293238  -0.3278967   0.18110771]
 [ 0.9293238  -0.3278967   0.18110771]
 [ 0.9293238  -0.3278967   0.18110771]
 [ 0.9293238  -0.3278967   0.18110771]
 [ 0.9293238  -0.3278967   0.18110771]
 [ 0.9293238  -0.3278967   0.18110771]
 [ 0.9293238  -0.3278967   0.18110771]
 [ 0.9293238  -0.3278967   0.18110771]
 [ 0.9293238  -0.3278967   0.18110771]
 [ 0.          0.          0.        ]
 [ 0.          0.          0.        ]
 [ 0.          0.          0.        ]
 [ 0.          0.          0.        ]
 [ 0.          0.          0.        ]
 [ 0.          0.          0.        ]
 [ 0.          0.          0.        ]
 [ 0.          0.          0.        ]
 [ 0.          0.          0.        ]
 [ 0.          0.          0.        ]]
Length of data: 20

奇怪的是,当我将值 fromRow 替换为数字 10 时,如 fromRow = 10,代表现有 table 的结尾,它起作用了。

输出:

Key: X
Data:
 [[ 9.2932379e-01 -3.2789671e-01  1.8110771e-01]
 [ 9.2932379e-01 -3.2789671e-01  1.8110771e-01]
 [ 9.2932379e-01 -3.2789671e-01  1.8110771e-01]
 [ 9.2932379e-01 -3.2789671e-01  1.8110771e-01]
 [ 9.2932379e-01 -3.2789671e-01  1.8110771e-01]
 [ 9.2932379e-01 -3.2789671e-01  1.8110771e-01]
 [ 9.2932379e-01 -3.2789671e-01  1.8110771e-01]
 [ 9.2932379e-01 -3.2789671e-01  1.8110771e-01]
 [ 9.2932379e-01 -3.2789671e-01  1.8110771e-01]
 [ 9.2932379e-01 -3.2789671e-01  1.8110771e-01]
 [ 3.1387749e-06  8.1200891e+27 -1.6456127e-14]
 [ 3.1387749e-06  8.1200891e+27 -1.6456127e-14]
 [ 3.1387749e-06  8.1200891e+27 -1.6456127e-14]
 [ 3.1387749e-06  8.1200891e+27 -1.6456127e-14]
 [ 3.1387749e-06  8.1200891e+27 -1.6456127e-14]
 [ 3.1387749e-06  8.1200891e+27 -1.6456127e-14]
 [ 3.1387749e-06  8.1200891e+27 -1.6456127e-14]
 [ 3.1387749e-06  8.1200891e+27 -1.6456127e-14]
 [ 3.1387749e-06  8.1200891e+27 -1.6456127e-14]
 [ 3.1387749e-06  8.1200891e+27 -1.6456127e-14]]
Length of data: 20

知道我做错了什么吗?

在调整 X 数据集的大小后,您将获得 fromRow。在调整大小之前,您需要该值。请参阅下面的代码。

with h5py.File('data.hdf5', 'w') as hf:
    # Add data to new file
    dset = hf.create_dataset("X", data=tempArray1, compression="gzip", chunks=True, maxshape=(None,3), dtype='f4') # Size is as the size of tempArray1
    print(hf["X"].shape[0])
# new location to get fromRow:
    fromRow = hf["X"].shape[0]

    # Append data existing file
    hf["X"].resize((hf["X"].shape[0] + 10, 3)) # Size is as the size of X+ 10
    print(hf["X"].shape[0])        
    hf["X"][fromRow:] = tempArray2