On Thu, Jun 23, 2011 at 8:41 PM, Nathaniel Smith wrote:
> Internally, there are
> a bunch of different NA values -- for floats it's a particular NaN,
> for integers it's INT_MIN, for booleans it's 2 (IIRC), etc.
So, Bender runs on R?
(Sorry, couldn't resist. Futurama season premiere is tonigh
On Thu, Jun 23, 2011 at 5:56 PM, Benjamin Root wrote:
> Lastly, I am not entirely familiar with R, so I am also very curious about
> what this magical "NA" value is, and how it compares to how NaNs work.
> Although, Pierre brought up the very good point that NaNs woulldn't work
> anyway with integ
On Thu, Jun 23, 2011 at 5:21 PM, Mark Wiebe wrote:
> On Thu, Jun 23, 2011 at 7:00 PM, Nathaniel Smith wrote:
>> It's should also be possible to accomplish a general solution at the
>> dtype level. We could have a 'dtype factory' used like:
>> np.zeros(10, dtype=np.maybe(float))
>> where np.maybe
On Jun 24, 2011, at 2:56 AM, Benjamin Root wrote:
>
> As a heavy masked_array user, I regret not being able to participate more in
> this discussion as I am madly cranking out matplotlib code. I would like to
> say that I have always seen masked arrays as being the "next step up" from
> using
On Jun 24, 2011, at 2:42 AM, Mark Wiebe wrote:
> On Thu, Jun 23, 2011 at 7:28 PM, Pierre GM wrote:
> Sorry y'all, I'm just commenting bits by bits:
>
> "One key problem is a lack of orthogonality with other features, for instance
> creating a masked array with physical quantities can't be done
On Thu, Jun 23, 2011 at 7:28 PM, Pierre GM wrote:
> Sorry y'all, I'm just commenting bits by bits:
>
> "One key problem is a lack of orthogonality with other features, for
> instance creating a masked array with physical quantities can't be done
> because both are separate subclasses of ndarray.
On Thu, Jun 23, 2011 at 7:28 PM, Pierre GM wrote:
> Sorry y'all, I'm just commenting bits by bits:
>
> "One key problem is a lack of orthogonality with other features, for
> instance creating a masked array with physical quantities can't be done
> because both are separate subclasses of ndarray.
On Thu, Jun 23, 2011 at 7:31 PM, Charles R Harris wrote:
> On Thu, Jun 23, 2011 at 6:21 PM, Mark Wiebe wrote:
>
>> On Thu, Jun 23, 2011 at 7:00 PM, Nathaniel Smith wrote:
>>
>>> On Thu, Jun 23, 2011 at 2:44 PM, Robert Kern
>>> wrote:
>>> > On Thu, Jun 23, 2011 at 15:53, Mark Wiebe wrote:
>>>
On Thu, Jun 23, 2011 at 6:21 PM, Mark Wiebe wrote:
> On Thu, Jun 23, 2011 at 7:00 PM, Nathaniel Smith wrote:
>
>> On Thu, Jun 23, 2011 at 2:44 PM, Robert Kern
>> wrote:
>> > On Thu, Jun 23, 2011 at 15:53, Mark Wiebe wrote:
>> >> Enthought has asked me to look into the "missing data" problem an
On Jun 24, 2011, at 2:21 AM, Charles R Harris wrote:
>
>
> On Thu, Jun 23, 2011 at 6:00 PM, Nathaniel Smith wrote:
> On Thu, Jun 23, 2011 at 2:44 PM, Robert Kern wrote:
> > On Thu, Jun 23, 2011 at 15:53, Mark Wiebe wrote:
> >> Enthought has asked me to look into the "missing data" problem an
Sorry y'all, I'm just commenting bits by bits:
"One key problem is a lack of orthogonality with other features, for instance
creating a masked array with physical quantities can't be done because both are
separate subclasses of ndarray. The only reasonable way to deal with this is to
move the m
On Thu, Jun 23, 2011 at 7:00 PM, Nathaniel Smith wrote:
> On Thu, Jun 23, 2011 at 2:44 PM, Robert Kern
> wrote:
> > On Thu, Jun 23, 2011 at 15:53, Mark Wiebe wrote:
> >> Enthought has asked me to look into the "missing data" problem and how
> NumPy
> >> could treat it better. I've considered th
On Thu, Jun 23, 2011 at 6:00 PM, Nathaniel Smith wrote:
> On Thu, Jun 23, 2011 at 2:44 PM, Robert Kern
> wrote:
> > On Thu, Jun 23, 2011 at 15:53, Mark Wiebe wrote:
> >> Enthought has asked me to look into the "missing data" problem and how
> NumPy
> >> could treat it better. I've considered th
On Thu, Jun 23, 2011 at 5:51 PM, wrote:
> On Thu, Jun 23, 2011 at 5:37 PM, Mark Wiebe wrote:
> > On Thu, Jun 23, 2011 at 4:19 PM, Nathaniel Smith wrote:
> >>
> >> I'd like to see a statement of what the "missing data problem" is, and
> >> how this solves it? Because I don't think this is entire
On Thu, Jun 23, 2011 at 5:00 PM, Nathaniel Smith wrote:
> Speaking as a user who's avoided numpy.ma, it wasn't actually because
> of the behavior I pointed out (I never got far enough to notice it),
> but because I got the distinct impression that it was a "second-class
> citizen" in numpy-land. I
On Thu, Jun 23, 2011 at 2:44 PM, Robert Kern wrote:
> On Thu, Jun 23, 2011 at 15:53, Mark Wiebe wrote:
>> Enthought has asked me to look into the "missing data" problem and how NumPy
>> could treat it better. I've considered the different ideas of adding dtype
>> variants with a special signal va
On Thu, Jun 23, 2011 at 6:51 PM, wrote:
> On Thu, Jun 23, 2011 at 5:37 PM, Mark Wiebe wrote:
> > On Thu, Jun 23, 2011 at 4:19 PM, Nathaniel Smith wrote:
> >>
> >> I'd like to see a statement of what the "missing data problem" is, and
> >> how this solves it? Because I don't think this is entire
On Thu, Jun 23, 2011 at 6:39 PM, Christopher Barker
wrote:
> Nathaniel Smith wrote:
> > IME
> > it's important for the default behavior to be to fail loudly when
> > things are wonky, not to silently patch them up, possibly
> > incorrectly!)
>
> +1 for default behavior to fail, raise errors, or re
On Thu, Jun 23, 2011 at 5:37 PM, Mark Wiebe wrote:
> On Thu, Jun 23, 2011 at 4:19 PM, Nathaniel Smith wrote:
>>
>> I'd like to see a statement of what the "missing data problem" is, and
>> how this solves it? Because I don't think this is entirely intuitive,
>> or that everyone necessarily has th
Nathaniel Smith wrote:
> IME
> it's important for the default behavior to be to fail loudly when
> things are wonky, not to silently patch them up, possibly
> incorrectly!)
+1 for default behavior to fail, raise errors, or return "unknown
values" is these situations.
Though that behavior should
On Jun 24, 2011, at 12:43 AM, Mark Wiebe wrote:
> On Thu, Jun 23, 2011 at 5:24 PM, Pierre GM wrote:
>
...
> Mmh, after timeseries, now masked arrays... Mark, I start to see a pattern
> here ;)
>
> I think it speaks to what's on Enthought's mind, in any case. :)
Eh...
>
> Anyhow, yes, there
On Thu, Jun 23, 2011 at 6:33 PM, Charles R Harris wrote:
>
>
> On Thu, Jun 23, 2011 at 5:14 PM, Mark Wiebe wrote:
>
>> On Thu, Jun 23, 2011 at 6:02 PM, Charles R Harris <
>> charlesr.har...@gmail.com> wrote:
>>
>>> On Thu, Jun 23, 2011 at 4:43 PM, Mark Wiebe wrote:
>>>
On Thu, Jun 23, 2011
On Thu, Jun 23, 2011 at 5:14 PM, Mark Wiebe wrote:
> On Thu, Jun 23, 2011 at 6:02 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>> On Thu, Jun 23, 2011 at 4:43 PM, Mark Wiebe wrote:
>>
>>> On Thu, Jun 23, 2011 at 5:24 PM, Pierre GM wrote:
>>>
On Jun 23, 2011, at 11:55 P
On Thu, Jun 23, 2011 at 6:02 PM, Charles R Harris wrote:
> On Thu, Jun 23, 2011 at 4:43 PM, Mark Wiebe wrote:
>
>> On Thu, Jun 23, 2011 at 5:24 PM, Pierre GM wrote:
>>
>>>
>>> On Jun 23, 2011, at 11:55 PM, Mark Wiebe wrote:
>>>
>>> > On Thu, Jun 23, 2011 at 4:46 PM, Charles R Harris <
>>> charl
On Thu, Jun 23, 2011 at 4:43 PM, Mark Wiebe wrote:
> On Thu, Jun 23, 2011 at 5:24 PM, Pierre GM wrote:
>
>>
>> On Jun 23, 2011, at 11:55 PM, Mark Wiebe wrote:
>>
>> > On Thu, Jun 23, 2011 at 4:46 PM, Charles R Harris <
>> charlesr.har...@gmail.com> wrote:
>> > On Thu, Jun 23, 2011 at 2:53 PM, Ma
On Thu, Jun 23, 2011 at 5:24 PM, Pierre GM wrote:
>
> On Jun 23, 2011, at 11:55 PM, Mark Wiebe wrote:
>
> > On Thu, Jun 23, 2011 at 4:46 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
> > On Thu, Jun 23, 2011 at 2:53 PM, Mark Wiebe wrote:
> > Enthought has asked me to look into the "
On Thu, Jun 23, 2011 at 5:05 PM, Keith Goodman wrote:
> On Thu, Jun 23, 2011 at 1:53 PM, Mark Wiebe wrote:
> > Enthought has asked me to look into the "missing data" problem and how
> NumPy
> > could treat it better. I've considered the different ideas of adding
> dtype
> > variants with a speci
On Jun 23, 2011, at 11:55 PM, Mark Wiebe wrote:
> On Thu, Jun 23, 2011 at 4:46 PM, Charles R Harris
> wrote:
> On Thu, Jun 23, 2011 at 2:53 PM, Mark Wiebe wrote:
> Enthought has asked me to look into the "missing data" problem and how NumPy
> could treat it better. I've considered the differe
On Thu, Jun 23, 2011 at 4:08 PM, Robert Kern wrote:
> On Thu, Jun 23, 2011 at 17:05, Charles R Harris
> wrote:
> >
> > On Thu, Jun 23, 2011 at 4:04 PM, Robert Kern
> wrote:
> >>
> >> On Thu, Jun 23, 2011 at 17:02, Charles R Harris
> >> wrote:
> >> >
> >> > On Thu, Jun 23, 2011 at 3:48 PM, Gael
On Thu, Jun 23, 2011 at 4:54 PM, Eric Firing wrote:
> On 06/23/2011 11:19 AM, Nathaniel Smith wrote:
> > I'd like to see a statement of what the "missing data problem" is, and
> > how this solves it? Because I don't think this is entirely intuitive,
> > or that everyone necessarily has the same i
On Thu, Jun 23, 2011 at 17:05, Charles R Harris
wrote:
>
> On Thu, Jun 23, 2011 at 4:04 PM, Robert Kern wrote:
>>
>> On Thu, Jun 23, 2011 at 17:02, Charles R Harris
>> wrote:
>> >
>> > On Thu, Jun 23, 2011 at 3:48 PM, Gael Varoquaux
>> > wrote:
>>
>> >> Ufuncs need work, but I have
>> >> the im
On Thu, Jun 23, 2011 at 4:48 PM, Gael Varoquaux <
gael.varoqu...@normalesup.org> wrote:
> On Thu, Jun 23, 2011 at 03:53:31PM -0500, Mark Wiebe wrote:
> >concluded that adding masks to the core ndarray appears is the best
> way to
> >deal with the problem in general.
>
> It seems to me that
On Thu, Jun 23, 2011 at 4:04 PM, Robert Kern wrote:
> On Thu, Jun 23, 2011 at 17:02, Charles R Harris
> wrote:
> >
> > On Thu, Jun 23, 2011 at 3:48 PM, Gael Varoquaux
> > wrote:
>
> >> Ufuncs need work, but I have
> >> the impression that your proposal is simply to solve the special case of
> >
On Thu, Jun 23, 2011 at 1:53 PM, Mark Wiebe wrote:
> Enthought has asked me to look into the "missing data" problem and how NumPy
> could treat it better. I've considered the different ideas of adding dtype
> variants with a special signal value and masked arrays, and concluded that
> adding masks
On Thu, Jun 23, 2011 at 17:02, Charles R Harris
wrote:
>
> On Thu, Jun 23, 2011 at 3:48 PM, Gael Varoquaux
> wrote:
>> Ufuncs need work, but I have
>> the impression that your proposal is simply to solve the special case of
>> masked data in the ufunc by breaking the simple numpy array model.
>
On Thu, Jun 23, 2011 at 3:48 PM, Gael Varoquaux <
gael.varoqu...@normalesup.org> wrote:
> On Thu, Jun 23, 2011 at 03:53:31PM -0500, Mark Wiebe wrote:
> >concluded that adding masks to the core ndarray appears is the best
> way to
> >deal with the problem in general.
>
> It seems to me that
On Thu, Jun 23, 2011 at 4:46 PM, Charles R Harris wrote:
> On Thu, Jun 23, 2011 at 2:53 PM, Mark Wiebe wrote:
>
>> Enthought has asked me to look into the "missing data" problem and how
>> NumPy could treat it better. I've considered the different ideas of adding
>> dtype variants with a special
On 06/23/2011 11:19 AM, Nathaniel Smith wrote:
> I'd like to see a statement of what the "missing data problem" is, and
> how this solves it? Because I don't think this is entirely intuitive,
> or that everyone necessarily has the same idea.
>
>> Reduction operations like 'sum', 'prod', 'min', and
On Thu, Jun 23, 2011 at 4:44 PM, Robert Kern wrote:
> On Thu, Jun 23, 2011 at 15:53, Mark Wiebe wrote:
> > Enthought has asked me to look into the "missing data" problem and how
> NumPy
> > could treat it better. I've considered the different ideas of adding
> dtype
> > variants with a special s
On Thu, Jun 23, 2011 at 3:44 PM, Robert Kern wrote:
> On Thu, Jun 23, 2011 at 15:53, Mark Wiebe wrote:
> > Enthought has asked me to look into the "missing data" problem and how
> NumPy
> > could treat it better. I've considered the different ideas of adding
> dtype
> > variants with a special s
On Thu, Jun 23, 2011 at 03:53:31PM -0500, Mark Wiebe wrote:
>concluded that adding masks to the core ndarray appears is the best way to
>deal with the problem in general.
It seems to me that this is going to make the numpy array a way more
complex object. Althought it is currently quite si
On Thu, Jun 23, 2011 at 2:53 PM, Mark Wiebe wrote:
> Enthought has asked me to look into the "missing data" problem and how
> NumPy could treat it better. I've considered the different ideas of adding
> dtype variants with a special signal value and masked arrays, and concluded
> that adding mask
On Thu, Jun 23, 2011 at 15:53, Mark Wiebe wrote:
> Enthought has asked me to look into the "missing data" problem and how NumPy
> could treat it better. I've considered the different ideas of adding dtype
> variants with a special signal value and masked arrays, and concluded that
> adding masks t
On Thu, Jun 23, 2011 at 4:19 PM, Nathaniel Smith wrote:
> I'd like to see a statement of what the "missing data problem" is, and
> how this solves it? Because I don't think this is entirely intuitive,
> or that everyone necessarily has the same idea.
>
I agree it represents different problems in
I'd like to see a statement of what the "missing data problem" is, and
how this solves it? Because I don't think this is entirely intuitive,
or that everyone necessarily has the same idea.
> Reduction operations like 'sum', 'prod', 'min', and 'max' will operate as if
> the values weren't there
F
Enthought has asked me to look into the "missing data" problem and how NumPy
could treat it better. I've considered the different ideas of adding dtype
variants with a special signal value and masked arrays, and concluded that
adding masks to the core ndarray appears is the best way to deal with th
Hi,
I have found a very strange bug that I cannot understand. I would like to do
something like this:
Given 4 pairs of numpy arrays (x1, y1, x2, y2, x3, y3, x4, y4), I would like to
compute each corresponding inner product ip = np.dot(yi.T, xj), for i = 1,...4
and j = 1,...,4. (Something lik
This is now merged.
-Mark
On Wed, Jun 22, 2011 at 9:24 AM, Mark Wiebe wrote:
> Pull request is here:
>
> https://github.com/numpy/numpy/pull/95
>
> -Mark
>
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On Thu, Jun 23, 2011 at 8:20 AM, Neal Becker wrote:
> Olivier Delalleau wrote:
>
>> What about :
>> dict((k, [e for e in arr if (e['x0'], e['x1']) == k]) for k in cases)
>> ?
>
> Not bad! Thanks!
>
> BTW, is there an easier way to get the unique keys, then this:
>
> cases = tuple (set (tuple((e['
Olivier Delalleau wrote:
> What about :
> dict((k, [e for e in arr if (e['x0'], e['x1']) == k]) for k in cases)
> ?
Not bad! Thanks!
BTW, is there an easier way to get the unique keys, then this:
cases = tuple (set (tuple((e['a'],e['b'])) for e in u))
>
> (note: it is inefficient written thi
What about :
dict((k, [e for e in arr if (e['x0'], e['x1']) == k]) for k in cases)
?
(note: it is inefficient written this way though)
-=- Olivier
2011/6/23 Neal Becker
> I have a set of experiments that I want to plot. There will be many plots.
> Each will show different test conditions.
>
>
I have a set of experiments that I want to plot. There will be many plots.
Each will show different test conditions.
Suppose I put each of the test conditions and results into a recarray. The
recarray could be:
arr = np.empty ((#experiments,), dtype=[('x0',int), ('x1',int), ('y0',int)]
wher
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