>
> are you doing something like np.polyfit(model, obs, 1) ?
>
> If you are using polyfit with deg=1, i.e. fitting a straight line,
> then this could be also calculated using the weights in histogram2d.
>
> histogram2d (histogramdd) uses np.digitize and np.bincount, so I'm
> surprised if the hi
On 06/21/2010 06:30 AM, Michael Green wrote:
> On Sun, Jun 20, 2010 at 1:19 AM, Charles R Harris
> wrote:
>>
>> Have you checked the actual configuration that was used to compile lapack,
>> *not* the command line flags. I never had with success with the automatic
>> builds using the compressed fi
On Jun 20, 2010, at 7:28 PM, Bevan Jenkins wrote:
>
> I downloaded the git branch, I had to use the Download
> pierregm/scikits.timeseries-sandbox at master via a zip file as I have not
> managed to get Git to work at Uni yet.
> After deleting the old scikit I built and installed the new versio
Pierre GM gmail.com> writes:
>
> On Jun 10, 2010, at 7:16 PM, Bevan Jenkins wrote:
> > Hello,
> >
> > I have posted previously about dates prior to 1900 but this seems to be a
> > seperate issue. The error message is definitley different.
> > I can not seem to convert a timseseries from one f
Hi Ralf,
Thanks for the information. I'll have a look at it, and see if it
solves the issue.
Cheers,
Chris
On 18 June 2010 01:53, Ralf Gommers wrote:
>
>
> On Tue, Jun 15, 2010 at 11:06 AM, Chris LeBlanc wrote:
>>
>> Hi,
>>
>> Firstly thanks to everyone that has helped bring NumPy to the poin
On Sun, Jun 20, 2010 at 1:19 AM, Charles R Harris
wrote:
>
> Have you checked the actual configuration that was used to compile lapack,
> *not* the command line flags. I never had with success with the automatic
> builds using the compressed files. Also check the actual installed libraries
>
>
Y
On Jun 20, 2010, at 2:28 PM, Pauli Virtanen wrote:
> su, 2010-06-20 kello 13:56 -0400, Tony S Yu kirjoitti:
>> I came across some strange behavior when multiplying numpy floats and
>> python lists: the list is returned unchanged:
>>
>>> In [18]: np.float64(1.2) * [1, 2]
>>>
>>> Out[18]: [1, 2]
Hi, I was just digging through the fromnumeric.py code when I noticed that
the function _wrapit used asarray() rather than asanyarray(). I don't know
if this function really gets used anymore (as it gets called in special
situations), but would seem to be an issue as it would cause arrays such as
Hi,
We have currently a number of open tickets that are stalled
primarily because a developer is not able to reproduce
the bug, and more input would be needed from the original
reporter (or someone else with the same problem).
Stealing ideas from Launchpad, I added a new `needs_info` ticket
statu
su, 2010-06-20 kello 13:56 -0400, Tony S Yu kirjoitti:
> I came across some strange behavior when multiplying numpy floats and
> python lists: the list is returned unchanged:
>
> > In [18]: np.float64(1.2) * [1, 2]
> >
> > Out[18]: [1, 2]
Probably a bug, it seems to round the result first to an
Tony S Yu wrote:
> I came across some strange behavior when multiplying numpy floats and python
> lists: the list is returned unchanged:
>
>
>> In [18]: np.float64(1.2) * [1, 2]
>>
>> Out[18]: [1, 2]
>>
>
>
Apparently the np.float64 object is cast to an int, and python's * is used:
In
I came across some strange behavior when multiplying numpy floats and python
lists: the list is returned unchanged:
> In [18]: np.float64(1.2) * [1, 2]
>
> Out[18]: [1, 2]
On the other hand, multiplying an array scalar and a python list gives the
expected answer
> In [19]: np.array(1.2) * [1,
On Sun, Jun 20, 2010 at 4:24 AM, Tom Durrant wrote:
> Hi All,
> I have a problem involving lat/lon data. Basically, I am evaluating
> numerical weather model data against satellite data, and trying to produce
> gridded plots of various statistics. There are various steps involved with
> this, bu
Hi All,
I have a problem involving lat/lon data. Basically, I am evaluating
numerical weather model data against satellite data, and trying to produce
gridded plots of various statistics. There are various steps involved with
this, but basically, I get to the point where I have four arrays of th
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