On Fri, Sep 17, 2010 at 1:19 PM, wrote:
> On Fri, Sep 10, 2010 at 3:01 PM, wrote:
>> On Fri, Sep 10, 2010 at 1:58 PM, Christopher Barrington-Leigh
>> wrote:
>>> Interesting. Thanks Erin, Josef and Keith.
>>
>> thanks to the stata page at least I figured out that WLS is aweights
>> with asumpti
>> Though, really, it's annoying that numpy.loadtxt needs both the
>> readline function *and* the iterator protocol. If it just used
>> iterators, you could do:
>>
>> def truncator(fh, delimiter='END'):
>> for line in fh:
>>if line.strip() == delimiter:
>> break
>>yield line
>>
>> num
Hello,
Consider these two sets of container arrays --one defined as usual np array
the others as ma arrays:
all_measured = np.ma.zeros((16, 18))
all_predicted = np.ma.zeros((16, 18))
all_measured2 = np.zeros((16, 18))
all_predicted2 = np.zeros((16, 18))
I do a computation within
Argsort twice and you get the rank.
a1.argsort(axis=0).argsort(axis=0)
That's because argsort is it's own inverse when applied to the ranks.
On Tue, Sep 7, 2010 at 1:01 PM, Alexander Michael wrote:
> Calculating ranks by inverting the results of an argsort is
> straightforward and fast for 1D a
D'oh, Zachary already gave that answer.
On Sun, Sep 19, 2010 at 10:17 PM, John Schulman wrote:
> Argsort twice and you get the rank.
>
> a1.argsort(axis=0).argsort(axis=0)
>
> That's because argsort is it's own inverse when applied to the ranks.
>
> On Tue, Sep 7, 2010 at 1:01 PM, Alexander Micha
