Python Numpy recarray sort bidirectional

numpy, python, recarray, sorting

Solution

You can do this with `numpy.lexsort`

In [1]: import numpy as np
In [2]: a = np.array([(4,0), (1,9), (1,0), (4,9)],
                     dtype=[('x',int),('y',float)])

In [3]: a
Out[3]: 
array([(4, 0.0), (1, 9.0), (1, 0.0), (4, 9.0)], 
      dtype=[('x', '<i8'), ('y', '<f8')])

In [4]: a['x']
Out[4]: array([4, 1, 1, 4])

In [5]: a['y']
Out[5]: array([ 0.,  9.,  0.,  9.])

The order priority of the arguments to `lexsort` are opposite that of `np.sort(..., order=...)`. So, to sort first by descending `'x'` and then by ascending `'y'`:

In [6]: a[np.lexsort((a['y'], -a['x']))]
Out[6]: 
array([(4, 0.0), (4, 9.0), (1, 0.0), (1, 9.0)], 
      dtype=[('x', '<i8'), ('y', '<f8')])

Notes:

- This works assuming all your values are numerical (since the negative won't reverse string sorting).

- I've seen somewhere the use of `a['x'][::-1]` as a key instead of `-a['x']` but that's not working for me right now.

Problem

I have a structured numpy array, and I am sorting it by a order. It works pretty fine but in just one direction! Descending: ``` sort(myStructuredArray,order=my_order)[::-1] ``` and Ascending: ``` sort(myStructuredArray,order=my_order) ``` The order my_order is something like `[col1,col2,-col3,col4,-col5,...,colN]` and for some columns I would like to order it ascending like col1,col2 and colN and for others descending col3 and col5 (minus signal) . In this example I would like to sort my array first by col1 ascending, then by col2 ascending, then by col3 descending, then by col4 ascending, then by col5 descending and so on... How can I do that? Thank you

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