将几个hdf5文件合并到一个pytable中 [英] merging several hdf5 files into one pytable

问题描述

我有几个hdf5文件，每个文件都具有相同的结构.我想通过某种方式合并hdf5文件来从其中创建一个pytable.

I have several hdf5 files, each of them with the same structure. I'd like to create one pytable out of them by somehow merging the hdf5 files.

我的意思是，如果file1中的数组的大小为x，file2中的数组的大小为y，则pytable中的结果数组的大小将为x + y，首先包含来自file1的所有条目，然后包含所有来自file2的条目.

What I mean is that if an array in file1 has size x and array in file2 has size y, the resulting array in the pytable will be of size x+y, containing first all the entries from file1 and then all the entries from file2.

推荐答案

此操作的方式在某种程度上取决于您拥有的数据类型.数组和CArray具有静态大小，因此您需要预先分配数据空间.因此，您将执行以下操作:

How you want to do this depends slightly on the data type that you have. Arrays and CArrays have a static size so you need to preallocate the data space. Thus you would do something like the following:

import tables as tb
file1 = tb.open_file('/path/to/file1', 'r')
file2 = tb.open_file('/path/to/file2', 'r')
file3 = tb.open_file('/path/to/file3', 'r')
x = file1.root.x
y = file2.root.y

z = file3.create_array('/', 'z', atom=x.atom, shape=(x.nrows + y.nrows,))
z[:x.nrows] = x[:]
z[x.nrows:] = y[:]

但是，EArray和表是可扩展的.因此，您不需要预先分配大小，而可以使用copy_node()和append()代替.

However, EArrays and Tables are extendable. Thus you don't need to preallocate the size and can copy_node() and append() instead.

import tables as tb
file1 = tb.open_file('/path/to/file1', 'r')
file2 = tb.open_file('/path/to/file2', 'r')
file3 = tb.open_file('/path/to/file3', 'r')
x = file1.root.x
y = file2.root.y

z = file1.copy_node('/', name='x', newparent=file3.root, newname='z')
z.append(y)

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