Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Welcome To Ask or Share your Answers For Others

Categories

0 votes
248 views
in Technique[技术] by (71.8m points)

python - How to store an array in hdf5 file which is too big to load in memory?

Is there any way to store an array in an hdf5 file, which is too big to load in memory?

if I do something like this

f = h5py.File('test.hdf5','w')
f['mydata'] = np.zeros(2**32)

I get a memory error.

See Question&Answers more detail:os

与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
Welcome To Ask or Share your Answers For Others

1 Reply

0 votes
by (71.8m points)

According to the documentation, you can use create_dataset to create a chunked array stored in the hdf5. Example:

>>> import h5py
>>> f = h5py.File('test.h5', 'w')
>>> arr = f.create_dataset('mydata', (2**32,), chunks=True)
>>> arr
<HDF5 dataset "mydata": shape (4294967296,), type "<f4">

Slicing the HDF5 dataset returns Numpy-arrays.

>>> arr[:10]
array([ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.], dtype=float32)
>>> type(arr[:10])
numpy.array

You can set values as for a Numpy-array.

>>> arr[3:5] = 3
>>> arr[:6]
array([ 0.,  0.,  0.,  3.,  3.,  0.], dtype=float32)

I don't know if this is the most efficient way, but you can iterate over the whole array in chunks. And for instance setting it to random values:

>>> import numpy as np
>>> for i in range(0, arr.size, arr.chunks[0]):
        arr[i: i+arr.chunks[0]] = np.random.randn(arr.chunks[0])
>>> arr[:5]
array([ 0.62833798,  0.03631227,  2.00691652, -0.16631022,  0.07727782], dtype=float32)

与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
OGeek|极客中国-欢迎来到极客的世界,一个免费开放的程序员编程交流平台!开放,进步,分享!让技术改变生活,让极客改变未来! Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Click Here to Ask a Question

1.4m articles

1.4m replys

5 comments

57.0k users

...