是否可以在不加载整个文件的情况下从hdf5文件中读取一组给定的行?我有相当大的hdf5文件和大量的数据集,这是我为减少时间和内存使用而考虑的一个例子:
#! /usr/bin/env python
import numpy as np
import h5py
infile = 'field1.87.hdf5'
f = h5py.File(infile,'r')
group = f['Data']
mdisk = group['mdisk'].value
val = 2.*pow(10.,10.)
ind = np.where(mdisk>val)[0]
m = group['mcold'][ind]
print m
ind
不会给出连续的行,而是分散的行。
上面的代码失败了,但它遵循切片hdf5数据集的标准方法。我得到的错误信息是:
Traceback (most recent call last):
File "./read_rows.py", line 17, in <module>
m = group['mcold'][ind]
File "/cosma/local/Python/2.7.3/lib/python2.7/site-packages/h5py-2.3.1-py2.7-linux-x86_64.egg/h5py/_hl/dataset.py", line 425, in __getitem__
selection = sel.select(self.shape, args, dsid=self.id)
File "/cosma/local/Python/2.7.3/lib/python2.7/site-packages/h5py-2.3.1-py2.7-linux-x86_64.egg/h5py/_hl/selections.py", line 71, in select
sel[arg]
File "/cosma/local/Python/2.7.3/lib/python2.7/site-packages/h5py-2.3.1-py2.7-linux-x86_64.egg/h5py/_hl/selections.py", line 209, in __getitem__
raise TypeError("PointSelection __getitem__ only works with bool arrays")
TypeError: PointSelection __getitem__ only works with bool arrays
答案 0 :(得分:3)
我有一个示例h5py文件:
data = f['data']
# <HDF5 dataset "data": shape (3, 6), type "<i4">
# is arange(18).reshape(3,6)
ind=np.where(data[:]%2)[0]
# array([0, 0, 0, 1, 1, 1, 2, 2, 2], dtype=int32)
data[ind] # getitem only works with boolean arrays error
data[ind.tolist()] # can't read data (Dataset: Read failed) error
最后一个错误是由列表中的重复值引起的。
但使用具有唯一值的列表进行索引工作正常
In [150]: data[[0,2]]
Out[150]:
array([[ 0, 1, 2, 3, 4, 5],
[12, 13, 14, 15, 16, 17]])
In [151]: data[:,[0,3,5]]
Out[151]:
array([[ 0, 3, 5],
[ 6, 9, 11],
[12, 15, 17]])
具有适当尺寸切片的数组也是如此:
In [157]: data[ind[[0,3,6]],:]
Out[157]:
array([[ 0, 1, 2, 3, 4, 5],
[ 6, 7, 8, 9, 10, 11],
[12, 13, 14, 15, 16, 17]])
In [165]: f['data'][:2,np.array([0,3,5])]
Out[165]:
array([[ 0, 3, 5],
[ 6, 9, 11]])
In [166]: f['data'][[0,1],np.array([0,3,5])]
# errror about only one indexing array allowed
因此,如果索引是正确的 - 唯一值,并匹配数组维度,它应该可以工作。
我的简单示例并未测试加载了多少数组。文档听起来好像从文件中选择了元素而没有将整个数组加载到内存中。