Hi,
I was just looking at the einsum function.
To me, it's a really elegant and clear way of doing array operations, which
is the core of what numpy is about.
It removes the need to remember a range of functions, some of which I find
tricky (e.g. tile).
Unfortunately the present implementation
Folks,
np.linalg.lstsq of a random-uniform A 50 x 32 with 3 columns all 0
returns x[:3] 0 as expected,
but 4 columns all 0 = huge x:
lstsq (50, 32) with 4 columns all 0:
[ -3.7e+09 -3.6e+13 -1.9e+13 -2.9e+12 7.3e-01 ...
This may be a roundoff problem, or even a Mac Altivec lapack bug,
On Wed, Oct 24, 2012 at 1:33 PM, denis denis-bz...@t-online.de wrote:
Folks,
np.linalg.lstsq of a random-uniform A 50 x 32 with 3 columns all 0
returns x[:3] 0 as expected,
but 4 columns all 0 = huge x:
lstsq (50, 32) with 4 columns all 0:
[ -3.7e+09 -3.6e+13 -1.9e+13 -2.9e+12
As numpy.fromfile seems to require full file object functionalities
like seek, I can not use it with the sys.stdin pipe.
So how could I stream a binary pipe directly into numpy?
I can imagine storing the data in a string and use StringIO but the
files are 3.6 GB large, just the binary, and that
On Wed, Oct 24, 2012 at 3:00 PM, Michael Aye kmichael@gmail.com wrote:
As numpy.fromfile seems to require full file object functionalities
like seek, I can not use it with the sys.stdin pipe.
So how could I stream a binary pipe directly into numpy?
I can imagine storing the data in a
On Wed, Oct 24, 2012 at 4:47 AM, Robert Kern robert.k...@gmail.com wrote:
How about this?
def nancumsum(x):
nans = np.isnan(x)
x = np.array(x)
x[nans] = 0
reset_idx = np.zeros(len(x), dtype=int)
reset_idx[nans] = np.arange(len(x))[nans]
reset_idx =
Hi, All,
I am trying to install numpy from http://www.scipy.org/Download .
by
git clone git://github.com/numpy/numpy.git numpy
But, when I ran
python setup.py install
I got:
SystemError: Cannot compile 'Python.h'. Perhaps you need to install
python-dev|python-devel
Where to get python-dev ?
