On Wed, Oct 9, 2013 at 7:48 PM, Bernhard Spinnler
wrote:
> Hi Richard,
>
> Ah, I searched the list but didn't find those posts before…
>
> I can easily imagine that correlation is defined differently in different
> disciplines. Both ways are correct and it's just a convention or definition.
> In m
Looks like Wolfram MathWorld would favor the docstring, but the possibility
of a "use-domain" dependency seems plausible (after all, a similar dilemma
is observed, e.g., w/ the Fourier Transform)--I guess one discipline's
future is another discipline's past. :-)
http://mathworld.wolfram.com/Autoco
Hi Richard,
Ah, I searched the list but didn't find those posts before…
I can easily imagine that correlation is defined differently in different
disciplines. Both ways are correct and it's just a convention or definition. In
my field (Digital Communications, Digital Signal Processing) the vast
https://github.com/xianyi/OpenBLAS/issues/304
On 09.10.2013 17:24, Julian Taylor wrote:
> yes thats probably openblas fault.
> Openblas crashes all the time as soon as your matrices get bigger than a
> couple of megabytes.
> I'll investigate and report it upstream (as I have already far too often
yes thats probably openblas fault.
Openblas crashes all the time as soon as your matrices get bigger than a
couple of megabytes.
I'll investigate and report it upstream (as I have already far too often
for the exact same reason ...)
On Wed, Oct 9, 2013 at 5:05 PM, Charanpal Dhanjal wrote:
> Oops
Oops, the second line should have been
export OPENBLAS_NUM_THREADS=8
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> >/ I get a segmentation fault upon running the following:
> />/
> />/ import numpy
> />/ A = numpy.ones((700, 8))
> />/ Q, R = numpy.linalg.qr(A)
> />/
> />/ on Python 2.7.3, Linux 64-bit using numpy 1.9.0.dev-ec3603f linked
> />/ against OpenBLAS. If A is a smaller matrix then the QR decompo
On Wed, Oct 9, 2013 at 8:04 AM, Charanpal Dhanjal wrote:
> I get a segmentation fault upon running the following:
>
> import numpy
> A = numpy.ones((700, 8))
> Q, R = numpy.linalg.qr(A)
>
> on Python 2.7.3, Linux 64-bit using numpy 1.9.0.dev-ec3603f linked
> against OpenBLAS. If A is a smaller
That does work thanks.
And in a for loop was my goal, so this works for me.
for i in np.unique(testdata[:,0]):
print(i, testdata[testdata[:,0]==i][:,2].mean())
(datetime.date(2013, 10, 7), 2.9336)
(datetime.date(2013, 10, 8), 5.634)
(datetime.date(2013, 10, 9), 4.2
I think you need this
>>> testdata[testdata[:,0]==today][:,2].mean()
4.267
>>> testdata[testdata[:,0]==yesterday][:,2].mean()
5.634
>>> testdata[testdata[:,0]==twodaysago][:,2].mean()
2.9336
On 10/09/2013 06:46 AM, Roelf Schreurs wrote:
Hi
I have the fol
I get a segmentation fault upon running the following:
import numpy
A = numpy.ones((700, 8))
Q, R = numpy.linalg.qr(A)
on Python 2.7.3, Linux 64-bit using numpy 1.9.0.dev-ec3603f linked
against OpenBLAS. If A is a smaller matrix then the QR decomposition
works (for example A has shape (40
Hi
I have the following array and want to calculate the average per day.
Import numpy as np
from datetime import date
today = date(today.year, today.month, 9)
yesterday = date(today.year, today.month, 8)
twodaysago = date(today.year, today.month, 7)
testdata = np.array([[today, "r", 3.2],[toda
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