On Mon, Jun 4, 2012 at 11:10 AM, Patrick Redmond <[email protected]> wrote:
> Here's how I sorted primarily by field 'a' descending and secondarily by
> field 'b' ascending:
could you multiply the numeric field by -1, sort, then put it back --
somethign like:
data *- -1
data_sorted = np.sort(data, order=['a','b'])
data_sorted *= -1
(reverse if necessary -- I lost track...)
-Chris
> (Note that 'a' is the second column, 'b' is the first)
>
>>>> data
> array([('b', 0.03),
> ('c', 0.03),
> ('f', 0.03),
> ('e', 0.01),
> ('d', 0.04),
> ('a', 0.04)],
> dtype=[('b', '|S32'), ('a', '<f8')])
>>>> data.sort(order='b') # sort by b
>>>> data = data[::-1] # reverse
>>>> data[numpy.argsort(data['a'])][::-1] # sort by a and reverse
> array([('a', 0.04),
> ('d', 0.04),
> ('b', 0.03),
> ('c', 0.03),
> ('f', 0.03),
> ('e', 0.01)],
> dtype=[('b', '|S32'), ('a', '<f8')])
>
> My question is whether there's an easier way to do this.
could you multipily the nubmeric field by -1, sort, then multiply it again?
Originally I
> thought it would be possible to just do:
>
>>>> data.sort(order=('-a', 'b'))
>
> ...indicating that the order of 'a' is descending, but this isn't part of
> NumPy's sort behavior.
>
> Your help is appreciated!
>
> Thank you,
> Patrick
>
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