如何批量选择和numpy的计算阵列？ [英] How to batch select and calculate arrays in Numpy?

问题描述

如何（1）批量选择下HDF5文件中的所有阵列，则（2）对这些阵列应用的计算，最后3批在另一个HDF5文件中创建新的数组？

How to (1) batch select all arrays under a hdf5 file, then (2) apply calculations on those arrays and finally (3) batch create new arrays in another hdf5 file?

例如：

import numpy
import tables

file = openFile('file1',"r")

array1 = file.root.array1
array1_cal = (array1 <= 1)
newfile.createArray('/','array1_cal',array1_cal)

array2 = file.root.array2
array2_cal = (array2 <= 1)
newfile.createArray('/','array2_cal',array2_cal)

我已经下了单HDF5文件和几个HDF5文件100+阵列，我怎么能批量处理他们？非常感谢。

I have 100+ arrays under a single hdf5 file and several hdf5 files, how can I batch process them? Thanks a lot.

推荐答案

通过 PyTables 您可以使用 walkNodes 函数递归迭代的节点。下面是一个例子：

With PyTables you can use the walkNodes function to recursively iterate through nodes. Here is an example:

# Recursively print all the nodes hanging from '/detector'.
print "Nodes hanging from group '/detector':"
for node in h5file.walkNodes('/detector', classname='EArray'):
    data = node[:]
    // do some calculation 
    // store new array in second file 

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