Question

我正在试图弄清楚如何使用h5py一次将一个多维结构的numpy数组写入hdf5文件的一个字段，但是我收到一个关于广播不同形状的数组的错误。我需要分开创建数据集的步骤，并将数据写入数据集中，如示例所示。

这是我最小的工作示例。

writehdf5.py

#!/bin/env python
import h5py
from numpy.random import randn

print 'Creating Test Data'
mass = randn(10)
altitude = randn(10)
position = randn(10, 3)
velocity = randn(10, 3)

print 'Write 1 dimensional arrays'
hdf5 = h5py.File('test1.hdf', 'w')
dataset = hdf5.create_dataset('test dataset', (10,),
                              dtype=[('mass', '<f8'),
                                     ('altitude', '<f8')])
dataset['mass'] = mass
dataset['altitude'] = altitude
hdf5.close()

print 'Write 2 dimensional arrays'
hdf5 = h5py.File('test2.hdf', 'w')
dataset = hdf5.create_dataset('test dataset', (10,),
                              dtype=[('position', '<f8', 3),
                                     ('velocity', '<f8', 3)])
print dataset['position'].shape
print position.shape
dataset['position'] = position  # <-- Error Occurs Here
dataset['velocity'] = velocity
hdf5.close()

运行时会给我以下输出。

>> python writehdf5.py 
Creating Test Data
Write 1 dimensional arrays
Write 2 dimensional arrays
(10, 3)
(10, 3)
Traceback (most recent call last):
  File "mwe.py", line 27, in <module>
    dataset['position'] = position  # <-- Error Occurs Here
  File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper (/builddir/build/BUILD/h5py-2.5.0/h5py/_objects.c:2450)
  File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper (/builddir/build/BUILD/h5py-2.5.0/h5py/_objects.c:2407)
  File "/usr/lib64/python2.7/site-packages/h5py/_hl/dataset.py", line 514, in __setitem__
    val = numpy.asarray(val, dtype=dtype, order='C')
  File "/usr/lib64/python2.7/site-packages/numpy/core/numeric.py", line 462, in asarray
    return array(a, dtype, copy=False, order=order)
ValueError: could not broadcast input array from shape (10,3) into shape (10,3,3)

>> h5dump test1.hdf 
HDF5 "test1.hdf" {
GROUP "/" {
   DATASET "test dataset" {
      DATATYPE  H5T_COMPOUND {
         H5T_IEEE_F64LE "mass";
         H5T_IEEE_F64LE "altitude";
      }
      DATASPACE  SIMPLE { ( 10 ) / ( 10 ) }
      DATA {
      (0): {
            0.584402,
            1.50107
         },
      (1): {
            -0.284148,
            -0.521783
         },
      (2): {
            -0.461751,
            0.53352
         },
      (3): {
            2.06525,
            -0.0364377
         },
      (4): {
            -0.835377,
            1.35912
         },
      (5): {
            -1.31011,
            1.21051
         },
      (6): {
            0.103971,
            -0.669617
         },
      (7): {
            0.244425,
            -0.654791
         },
      (8): {
            0.468478,
            2.60204
         },
      (9): {
            0.837614,
            1.21362
         }
      }
   }
}
}

>> h5dump test2.hdf 
HDF5 "test2.hdf" {
GROUP "/" {
   DATASET "test dataset" {
      DATATYPE  H5T_COMPOUND {
         H5T_ARRAY { [3] H5T_IEEE_F64LE } "position";
         H5T_ARRAY { [3] H5T_IEEE_F64LE } "velocity";
      }
      DATASPACE  SIMPLE { ( 10 ) / ( 10 ) }
      DATA {
      (0): {
            [ 0, 0, 0 ],
            [ 0, 0, 0 ]
         },
      (1): {
            [ 0, 0, 0 ],
            [ 0, 0, 0 ]
         },
      (2): {
            [ 0, 0, 0 ],
            [ 0, 0, 0 ]
         },
      (3): {
            [ 0, 0, 0 ],
            [ 0, 0, 0 ]
         },
      (4): {
            [ 0, 0, 0 ],
            [ 0, 0, 0 ]
         },
      (5): {
            [ 0, 0, 0 ],
            [ 0, 0, 0 ]
         },
      (6): {
            [ 0, 0, 0 ],
            [ 0, 0, 0 ]
         },
      (7): {
            [ 0, 0, 0 ],
            [ 0, 0, 0 ]
         },
      (8): {
            [ 0, 0, 0 ],
            [ 0, 0, 0 ]
         },
      (9): {
            [ 0, 0, 0 ],
            [ 0, 0, 0 ]
         }
      }
   }
}
}

我可以看到我的数据集正在被正确初始化，但是当我尝试用数据填充字段时，我不明白我得到的错误。数据集和要写入的数据的形状显然是相同的。

非常感谢任何有关我缺失的帮助（很可能是简单的事情）！

Answer 1

您的脚本在我的计算机（PY3），h5py版本2.6.0上正常运行。看起来你有2.5。

必须是v2.5.0中修复的v2.5.0中的错误。

使用h5py一次将多维结构化numpy数组写入hdf5一个字段会引发numpy广播错误

1 个答案: