You can try easy_install or pip.
-=- Olivier
2012/1/21 Peng Yu
> Hi,
>
>
> Perl has something like ppm so that I can just use one command to
> download and install perl modules. But I don't find such thing in
> python. As shown on http://docs.python.org/install/index.html, it
> seems that I hav
Hi,
Perl has something like ppm so that I can just use one command to
download and install perl modules. But I don't find such thing in
python. As shown on http://docs.python.org/install/index.html, it
seems that I have to download the packages first unzip it then install
it. I'm wondering if the
Hi,
I read the Mandelbrot code using NumPy at this page:
http://mentat.za.net/numpy/intro/intro.html
but when I run it, it gives me integer overflows. As such, I have
fixed the code, so that it doesn't overflow here:
https://gist.github.com/1655320
and I have also written an equivalent Fortran
On Sat, Jan 21, 2012 at 6:26 PM, John Salvatier
wrote:
> I ran into this a while ago and was confused why cov did not behave the way
> pierre suggested.
same here,
When I rewrote scipy.stats.spearmanr, I matched the numpy behavior for
two arrays, while R only returns the cross-correlation part.
I ran into this a while ago and was confused why cov did not behave the way
pierre suggested.
On Jan 21, 2012 12:48 PM, "Elliot Saba" wrote:
> Thank you Sturla, that's exactly what I want.
>
> I'm sorry that I was not able to reply for so long, but Pierre's code is
> similar to what I have alread
Thank you Sturla, that's exactly what I want.
I'm sorry that I was not able to reply for so long, but Pierre's code is
similar to what I have already implemented, and I am in support of changing
the functionality of cov(). I am unaware of any arguments for a covariance
function that works in this
Hi All,
I'd like some feedback on how mask NA should interact with views. The
immediate problem is how to deal with the real and imaginary parts of
complex numbers. If the original has a masked value, it should show up as
masked in the real and imaginary parts. But what should happen on
assignment
unique has an option to get indexes out which you can use in
combination with sort to get the actual counts out.
tab0 = zeros( 256*256*256 , dtype=int)
col=ravel(((im0[...,0].astype('u4')*256+im0[...,1])*256)+im0[...,2])
col,idx=unique(sort(col),True)
idx=hstack([idx,[2500*2500]])
tab0[col]=idx[1:
