Re: [Numpy-discussion] Math Library

2010-04-18 Thread Sebastian Walter
On Tue, Apr 13, 2010 at 12:29 AM, Charles R Harris
 wrote:
>
>
> On Mon, Apr 12, 2010 at 4:19 PM, Travis Oliphant 
> wrote:
>>
>> On Apr 11, 2010, at 4:17 PM, Sebastian Walter wrote:
>>
>> >
>> > Ermm, the reply above is quite poor, sorry about that.
>> > What I meant to say is the following:
>> >
>> > If there is going to be a discussion about creating a pure C numpy
>> > library I'd like to join ;)
>>
>> Great.   I would really like to get the discussion going.   In an
>> ideal world we can finish any kind of significant re-factoring in time
>> for SciPy this year.    It actually feels like the kind of thing that
>> can motivate NumPy 2.0 a bit better.
>>
>> It sounds to me like nobody will be opposed as long as there is
>> continuity to the project and current code still works without
>> disruption (i.e. the current C-API for Python extensions is available).
>>
>> I am interested in re-factoring in such a way to create minimal impact
>> on current NumPy C-API users, but improve maintainability going
>> forward and the ability for other projects to use NumPy.
>>
>
> My own thoughts were to have a lowlevel 'loop' library that worked with
> strided memory, and an intermediate level above that for buffer objects.
> Numpy ufuncs would be a level above that and implement policy type things
> like casting, kinds, etc.
>
> Then there is the lowlevel c-library for the functions. I don't think we
> should aim at duplicating commonly available functions like sin and exp, but
> rather that subset that are sometimes unavailable. In particular, I would
> like to get away from having to use double versions of functions instead of
> type specific versions.

This sounds reasonable. However, I'm not sure that I understand exactly what
the consequences would be. Maybe it would be a good idea that one
writes down prototypical examples that should be supported by the new
code?

Sebastian


>
> Chuck
>
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Re: [Numpy-discussion] Math Library

2010-04-15 Thread Keith Goodman
On Wed, Apr 14, 2010 at 9:32 PM, James Bergstra
 wrote:
> On Tue, Apr 6, 2010 at 10:08 AM, David Cournapeau wrote:
>> could be put out of multiarray proper. Also, exposing an API for
>> things like fancy indexing would be very useful, but I don't know if
>> it even makes sense - I think a pure python implementation of fancy
>> indexing as a reference would be very useful for array-like classes (I
>> am thinking about scipy.sparse, for example).
>>
>> Unfortunately, I won't be able to help much in the near future (except
>> maybe for the fancy indexing as this could be useful for my job),
>>
>> David
>
> Hi, I am also interested in a pure python implementation of fancy
> indexing... at least the array-type fancy indexing, if not the boolean
> kind.  If someone knows of an implementation please let me know.  I'll
> email the list again if I make any serious progress on it.

Until then, I'm interested in a function that takes an index as input
and returns True if fancy indexing is requested, False otherwise. That
might be useful for your function as well. I'd use it so that my
__getitem__ method can at least say that fancy indexing is not
supported.
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Re: [Numpy-discussion] Math Library

2010-04-14 Thread James Bergstra
On Tue, Apr 6, 2010 at 10:08 AM, David Cournapeau wrote:
> could be put out of multiarray proper. Also, exposing an API for
> things like fancy indexing would be very useful, but I don't know if
> it even makes sense - I think a pure python implementation of fancy
> indexing as a reference would be very useful for array-like classes (I
> am thinking about scipy.sparse, for example).
>
> Unfortunately, I won't be able to help much in the near future (except
> maybe for the fancy indexing as this could be useful for my job),
>
> David

Hi, I am also interested in a pure python implementation of fancy
indexing... at least the array-type fancy indexing, if not the boolean
kind.  If someone knows of an implementation please let me know.  I'll
email the list again if I make any serious progress on it.

James
-- 
http://www-etud.iro.umontreal.ca/~bergstrj
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Re: [Numpy-discussion] Math Library

2010-04-12 Thread Charles R Harris
On Mon, Apr 12, 2010 at 4:19 PM, Travis Oliphant wrote:

>
> On Apr 11, 2010, at 4:17 PM, Sebastian Walter wrote:
>
> >
> > Ermm, the reply above is quite poor, sorry about that.
> > What I meant to say is the following:
> >
> > If there is going to be a discussion about creating a pure C numpy
> > library I'd like to join ;)
>
> Great.   I would really like to get the discussion going.   In an
> ideal world we can finish any kind of significant re-factoring in time
> for SciPy this year.It actually feels like the kind of thing that
> can motivate NumPy 2.0 a bit better.
>
> It sounds to me like nobody will be opposed as long as there is
> continuity to the project and current code still works without
> disruption (i.e. the current C-API for Python extensions is available).
>
> I am interested in re-factoring in such a way to create minimal impact
> on current NumPy C-API users, but improve maintainability going
> forward and the ability for other projects to use NumPy.
>
>
My own thoughts were to have a lowlevel 'loop' library that worked with
strided memory, and an intermediate level above that for buffer objects.
Numpy ufuncs would be a level above that and implement policy type things
like casting, kinds, etc.

Then there is the lowlevel c-library for the functions. I don't think we
should aim at duplicating commonly available functions like sin and exp, but
rather that subset that are sometimes unavailable. In particular, I would
like to get away from having to use double versions of functions instead of
type specific versions.

Chuck
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Re: [Numpy-discussion] Math Library

2010-04-12 Thread Travis Oliphant

On Apr 11, 2010, at 4:17 PM, Sebastian Walter wrote:

>
> Ermm, the reply above is quite poor, sorry about that.
> What I meant to say is the following:
>
> If there is going to be a discussion about creating a pure C numpy
> library I'd like to join ;)

Great.   I would really like to get the discussion going.   In an  
ideal world we can finish any kind of significant re-factoring in time  
for SciPy this year.It actually feels like the kind of thing that  
can motivate NumPy 2.0 a bit better.

It sounds to me like nobody will be opposed as long as there is  
continuity to the project and current code still works without  
disruption (i.e. the current C-API for Python extensions is available).

I am interested in re-factoring in such a way to create minimal impact  
on current NumPy C-API users, but improve maintainability going  
forward and the ability for other projects to use NumPy.

-Travis

--
Travis Oliphant
Enthought Inc.
1-512-536-1057
http://www.enthought.com
oliph...@enthought.com





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Re: [Numpy-discussion] Math Library

2010-04-11 Thread Sebastian Walter
On Sun, Apr 11, 2010 at 12:59 PM, Sebastian Walter
 wrote:
> On Tue, Apr 6, 2010 at 9:16 PM, Travis Oliphant  
> wrote:
>>
>> On Apr 6, 2010, at 9:08 AM, David Cournapeau wrote:
>>
>> Hi Travis,
>>
>> On Tue, Apr 6, 2010 at 7:43 AM, Travis Oliphant 
>> wrote:
>>
>>
>> I should have some time over the next couple of weeks, and I am very
>>
>> interested in refactoring the NumPy code to separate out the Python
>>
>> interface layer from the "library" layer as much as possible.   I had
>>
>> some discussions with people at PyCon about making it easier for
>>
>> Jython, IronPython, and perhaps even other high-level languages to
>>
>> utilize NumPy.
>>
>> Is there a willingness to consider as part of this reorganization
>>
>> creating a clear boundary between the NumPy library code and the
>>
>> Python-specific interface to it?   What other re-organization thoughts
>>
>> are you having David?
>>
>> This is mainly it, reorganizing the code for clearer boundaries
>> between boilerplate (python C API) and actual compuational code.
>> Besides helping other python implementations, I think this would
>> benefit NumPy itself in the long run (code maintainability), as well
>> as scipy (and other C extensions). I think the npymath effort is a
>> good example: albeit simple in nature (the API and boundaries are
>> obvious), it has already helped a lot to solve numerous platform
>> specific issues in numpy and scipy, and I think the overall code
>> quality is better.
>>
>> My own goals were:
>> - exposing core computational parts through an exported C API, so
>> that other C extensions may use it (for example, exposing basic
>> blas/lapack operations)
>> - dynamic loading of the code (for example depending on the CPU
>> capabilities - I have a git branch somewhere where I started exposing
>> a simple C API to query cpu capabilities like cache size or SSE
>> dynamically to that intent)
>> - more amenable codebase: I think multiarray in particular is too
>> big. I don't know the code well enough to know what can be split and
>> how, but I would have hoped that the scalartypes, the type descriptor
>> could be put out of multiarray proper. Also, exposing an API for
>> things like fancy indexing would be very useful, but I don't know if
>> it even makes sense - I think a pure python implementation of fancy
>> indexing as a reference would be very useful for array-like classes (I
>> am thinking about scipy.sparse, for example).
>>
>> Unfortunately, I won't be able to help much in the near future (except
>> maybe for the fancy indexing as this could be useful for my job),
>>
>>
>> I understand.   It just happens that there is some significant time for me
>> to look at this over the next few weeks and I would really like to make
>> progress on re-factoring.   I think it's O.K. if you don't have time right
>> now to help as long as you have time to offer criticism and suggestions.
>> We could even do that over Skype with whomever else wanted to join us (we
>> could do a GotoMeeting discussion as well) if you think it would be faster
>> to just talk in a group setting instead of email.     Of course, a summary
>> of any off-line discussion should be sent to the list.
>
> I'm not sure how much I could contribute to the discussion since I
> have only quite hazy
> knowledge of the numpy core. However, I'm interested in the outcome of
> the refactoring
> since I'm facing a "similar" problem in
> http://github.com/b45ch1/taylorpoly where I've implemented core
> algorithms in C
> for formal power series over the reals. Basically the formal
> powerseries are a new dtype and the goal is to be able to
> do computations like
> x = numpy.zeros((2,3),dtype='name of the formal powerseries')
> y = numpy.sin(x)

Ermm, the reply above is quite poor, sorry about that.
What I meant to say is the following:

If there is going to be a discussion about creating a pure C numpy
library I'd like to join ;)

>
> Sebastian
>
>
>> Thanks for the input,
>> -Travis
>>
>>
>>
>>
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>>
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Re: [Numpy-discussion] Math Library

2010-04-11 Thread Sebastian Walter
On Tue, Apr 6, 2010 at 9:16 PM, Travis Oliphant  wrote:
>
> On Apr 6, 2010, at 9:08 AM, David Cournapeau wrote:
>
> Hi Travis,
>
> On Tue, Apr 6, 2010 at 7:43 AM, Travis Oliphant 
> wrote:
>
>
> I should have some time over the next couple of weeks, and I am very
>
> interested in refactoring the NumPy code to separate out the Python
>
> interface layer from the "library" layer as much as possible.   I had
>
> some discussions with people at PyCon about making it easier for
>
> Jython, IronPython, and perhaps even other high-level languages to
>
> utilize NumPy.
>
> Is there a willingness to consider as part of this reorganization
>
> creating a clear boundary between the NumPy library code and the
>
> Python-specific interface to it?   What other re-organization thoughts
>
> are you having David?
>
> This is mainly it, reorganizing the code for clearer boundaries
> between boilerplate (python C API) and actual compuational code.
> Besides helping other python implementations, I think this would
> benefit NumPy itself in the long run (code maintainability), as well
> as scipy (and other C extensions). I think the npymath effort is a
> good example: albeit simple in nature (the API and boundaries are
> obvious), it has already helped a lot to solve numerous platform
> specific issues in numpy and scipy, and I think the overall code
> quality is better.
>
> My own goals were:
> - exposing core computational parts through an exported C API, so
> that other C extensions may use it (for example, exposing basic
> blas/lapack operations)
> - dynamic loading of the code (for example depending on the CPU
> capabilities - I have a git branch somewhere where I started exposing
> a simple C API to query cpu capabilities like cache size or SSE
> dynamically to that intent)
> - more amenable codebase: I think multiarray in particular is too
> big. I don't know the code well enough to know what can be split and
> how, but I would have hoped that the scalartypes, the type descriptor
> could be put out of multiarray proper. Also, exposing an API for
> things like fancy indexing would be very useful, but I don't know if
> it even makes sense - I think a pure python implementation of fancy
> indexing as a reference would be very useful for array-like classes (I
> am thinking about scipy.sparse, for example).
>
> Unfortunately, I won't be able to help much in the near future (except
> maybe for the fancy indexing as this could be useful for my job),
>
>
> I understand.   It just happens that there is some significant time for me
> to look at this over the next few weeks and I would really like to make
> progress on re-factoring.   I think it's O.K. if you don't have time right
> now to help as long as you have time to offer criticism and suggestions.
> We could even do that over Skype with whomever else wanted to join us (we
> could do a GotoMeeting discussion as well) if you think it would be faster
> to just talk in a group setting instead of email.     Of course, a summary
> of any off-line discussion should be sent to the list.

I'm not sure how much I could contribute to the discussion since I
have only quite hazy
knowledge of the numpy core. However, I'm interested in the outcome of
the refactoring
since I'm facing a "similar" problem in
http://github.com/b45ch1/taylorpoly where I've implemented core
algorithms in C
for formal power series over the reals. Basically the formal
powerseries are a new dtype and the goal is to be able to
do computations like
x = numpy.zeros((2,3),dtype='name of the formal powerseries')
y = numpy.sin(x)

Sebastian


> Thanks for the input,
> -Travis
>
>
>
>
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Re: [Numpy-discussion] Math Library

2010-04-06 Thread Travis Oliphant


On Apr 6, 2010, at 9:08 AM, David Cournapeau wrote:


Hi Travis,

On Tue, Apr 6, 2010 at 7:43 AM, Travis Oliphant > wrote:



I should have some time over the next couple of weeks, and I am very
interested in refactoring the NumPy code to separate out the Python
interface layer from the "library" layer as much as possible.   I had
some discussions with people at PyCon about making it easier for
Jython, IronPython, and perhaps even other high-level languages to
utilize NumPy.

Is there a willingness to consider as part of this reorganization
creating a clear boundary between the NumPy library code and the
Python-specific interface to it?   What other re-organization  
thoughts

are you having David?


This is mainly it, reorganizing the code for clearer boundaries
between boilerplate (python C API) and actual compuational code.
Besides helping other python implementations, I think this would
benefit NumPy itself in the long run (code maintainability), as well
as scipy (and other C extensions). I think the npymath effort is a
good example: albeit simple in nature (the API and boundaries are
obvious), it has already helped a lot to solve numerous platform
specific issues in numpy and scipy, and I think the overall code
quality is better.

My own goals were:
- exposing core computational parts through an exported C API, so
that other C extensions may use it (for example, exposing basic
blas/lapack operations)
- dynamic loading of the code (for example depending on the CPU
capabilities - I have a git branch somewhere where I started exposing
a simple C API to query cpu capabilities like cache size or SSE
dynamically to that intent)
- more amenable codebase: I think multiarray in particular is too
big. I don't know the code well enough to know what can be split and
how, but I would have hoped that the scalartypes, the type descriptor
could be put out of multiarray proper. Also, exposing an API for
things like fancy indexing would be very useful, but I don't know if
it even makes sense - I think a pure python implementation of fancy
indexing as a reference would be very useful for array-like classes (I
am thinking about scipy.sparse, for example).

Unfortunately, I won't be able to help much in the near future (except
maybe for the fancy indexing as this could be useful for my job),



I understand.   It just happens that there is some significant time  
for me to look at this over the next few weeks and I would really like  
to make progress on re-factoring.   I think it's O.K. if you don't  
have time right now to help as long as you have time to offer  
criticism and suggestions.


We could even do that over Skype with whomever else wanted to join us  
(we could do a GotoMeeting discussion as well) if you think it would  
be faster to just talk in a group setting instead of email. Of  
course, a summary of any off-line discussion should be sent to the list.


Thanks for the input,

-Travis




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Re: [Numpy-discussion] Math Library

2010-04-06 Thread David Cournapeau
Hi Travis,

On Tue, Apr 6, 2010 at 7:43 AM, Travis Oliphant  wrote:
>
>
> I should have some time over the next couple of weeks, and I am very
> interested in refactoring the NumPy code to separate out the Python
> interface layer from the "library" layer as much as possible.   I had
> some discussions with people at PyCon about making it easier for
> Jython, IronPython, and perhaps even other high-level languages to
> utilize NumPy.
>
> Is there a willingness to consider as part of this reorganization
> creating a clear boundary between the NumPy library code and the
> Python-specific interface to it?   What other re-organization thoughts
> are you having David?

This is mainly it, reorganizing the code for clearer boundaries
between boilerplate (python C API) and actual compuational code.
Besides helping other python implementations, I think this would
benefit NumPy itself in the long run (code maintainability), as well
as scipy (and other C extensions). I think the npymath effort is a
good example: albeit simple in nature (the API and boundaries are
obvious), it has already helped a lot to solve numerous platform
specific issues in numpy and scipy, and I think the overall code
quality is better.

My own goals were:
 - exposing core computational parts through an exported C API, so
that other C extensions may use it (for example, exposing basic
blas/lapack operations)
 - dynamic loading of the code (for example depending on the CPU
capabilities - I have a git branch somewhere where I started exposing
a simple C API to query cpu capabilities like cache size or SSE
dynamically to that intent)
 - more amenable codebase: I think multiarray in particular is too
big. I don't know the code well enough to know what can be split and
how, but I would have hoped that the scalartypes, the type descriptor
could be put out of multiarray proper. Also, exposing an API for
things like fancy indexing would be very useful, but I don't know if
it even makes sense - I think a pure python implementation of fancy
indexing as a reference would be very useful for array-like classes (I
am thinking about scipy.sparse, for example).

Unfortunately, I won't be able to help much in the near future (except
maybe for the fancy indexing as this could be useful for my job),

David
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Re: [Numpy-discussion] Math Library

2010-04-05 Thread Gael Varoquaux
On Mon, Apr 05, 2010 at 05:43:41PM -0500, Travis Oliphant wrote:
> I should have some time over the next couple of weeks, and I am very  
> interested in refactoring the NumPy code to separate out the Python  
> interface layer from the "library" layer as much as possible.   I had  
> some discussions with people at PyCon about making it easier for  
> Jython, IronPython, and perhaps even other high-level languages to  
> utilize NumPy.

> Is there a willingness to consider as part of this reorganization  
> creating a clear boundary between the NumPy library code and the  
> Python-specific interface to it?   What other re-organization thoughts  
> are you having David?

I have been following discussion too well, so please pardon me if my
answer is off topic or irrelevant...

At work, we want to code in a mixture of Python and C, optimizing only
the bottlenecks of the computation in C. When we want to use numerical
facilities in C, we would like to benefit from the fact that numpy
already went through the hard work of getting basic vectorized math
compiled and running on the user's computer.

Indeed, one of the issues that we have been facing lately is that
deploying a Python application with some C can increase a lot the
difficulty of building and installing due to the required C libraries.

The reason I bring this up, is that your refactor could make it easier
for C or Cython coders to use the numpy internal to do their own dirty
work. If the corresponding functions are exposed in the numpy headers, it
would be fairly easy to include them in a numpy.distutils-driven build,
via a call to 'numpy.get_include()'.

My 2 cents,

Gaël
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Re: [Numpy-discussion] Math Library

2010-04-05 Thread Travis Oliphant

On Apr 5, 2010, at 12:10 PM, David Cournapeau wrote:

> On Tue, Apr 6, 2010 at 12:56 AM, Charles R Harris
>  wrote:
>>
>>>
>>
>> Yeah, but there isn't much low level stuff there and I don't want  
>> to toss a
>> lot of real numerical code into it.
>
> I don't understand: there is already math code there, and you cannot
> be much more low level than what's there (there is already quite a bit
> of bit twiddling for long double). I split the code into complex and
> real, IEEE 754 macros/funcs in another file. I don' think we need to
> split into one file / function, at least not with the current size of
> the library.
>
> I think it is much more worthwhile to think about reorganizing the
> rest of numpy.core C code, the npymath library is very low hanging
> fruit in comparison, if only by size.

I should have some time over the next couple of weeks, and I am very  
interested in refactoring the NumPy code to separate out the Python  
interface layer from the "library" layer as much as possible.   I had  
some discussions with people at PyCon about making it easier for  
Jython, IronPython, and perhaps even other high-level languages to  
utilize NumPy.

Is there a willingness to consider as part of this reorganization  
creating a clear boundary between the NumPy library code and the  
Python-specific interface to it?   What other re-organization thoughts  
are you having David?

-Travis

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Re: [Numpy-discussion] Math Library

2010-04-05 Thread Charles R Harris
On Mon, Apr 5, 2010 at 11:10 AM, David Cournapeau wrote:

> On Tue, Apr 6, 2010 at 12:56 AM, Charles R Harris
>  wrote:
> >
> >>
> >
> > Yeah, but there isn't much low level stuff there and I don't want to toss
> a
> > lot of real numerical code into it.
>
> I don't understand: there is already math code there, and you cannot
> be much more low level than what's there (there is already quite a bit
> of bit twiddling for long double). I split the code into complex and
> real, IEEE 754 macros/funcs in another file. I don' think we need to
> split into one file / function, at least not with the current size of
> the library.
>
>
Yeah, but the added code in four versions with documentation for log1p alone
will add substantially to the current size. What I am saying is that the
current code is small because it uses current functions or falls back to
double versions. It doesn't really implement the low level stuff.

Chuck
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Re: [Numpy-discussion] Math Library

2010-04-05 Thread Charles R Harris
On Mon, Apr 5, 2010 at 10:56 AM, David Goldsmith wrote:

> On Mon, Apr 5, 2010 at 9:50 AM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>> On Mon, Apr 5, 2010 at 10:43 AM, Robert Kern wrote:
>>
>>> On Mon, Apr 5, 2010 at 11:11, Charles R Harris
>>>  wrote:
>>> >
>>> >
>>> > On Mon, Apr 5, 2010 at 10:00 AM, Robert Kern 
>>> wrote:
>>> >>
>>> >> On Mon, Apr 5, 2010 at 10:56, Charles R Harris
>>> >>  wrote:
>>> >> >
>>> >> >
>>> >> > On Mon, Apr 5, 2010 at 9:43 AM, Robert Kern 
>>> >> > wrote:
>>> >> >>
>>> >> >> On Mon, Apr 5, 2010 at 10:40, Charles R Harris
>>> >> >>  wrote:
>>> >> >> > Hi All,
>>> >> >> >
>>> >> >> > David Cournapeau has mentioned that he would like to have a numpy
>>> >> >> > math
>>> >> >> > library that would supply missing functions and I'm wondering how
>>> we
>>> >> >> > should
>>> >> >> > organise the source code. Should we put a mathlib directory in
>>> >> >> > numpy/core/src?
>>> >> >>
>>> >> >> David already did this: numpy/core/src/npymath/
>>> >> >>
>>> >> >
>>> >> > Yeah, but there isn't much low level stuff there and I don't want to
>>> >> > toss a
>>> >> > lot of real numerical code into it.
>>> >>
>>> >> Who cares? I don't.
>>> >
>>> > I care. I want the code to be organized.
>>>
>>> Then do it when there is code and we can see what needs to be organized.
>>>
>>>
>> I am writing code and I want to decide up front where to put it. I know
>> where you stand, so you need say no more. I'm waiting to see if other folks
>> have an opinion.
>>
>> Chuck
>>
>
> Will you be using it right away?  If so, organize it locally how think
> it'll work best, work w/ it a little while and see if you "guessed" right or
> if you find yourself wanting to reorganize; then provide it to us w/ the
> benefit of your experience. :-)
>
>
No, but since at some point it will involve the numpy build I would like
some feedback from David C. on how he thinks it should be organized. The
first routines I want to add are for log1p. Note that BSD has both single
and double versions but the single version copies the approximation
coefficients from the double. BSD doesn't have extended or quad precision
versions.

Chuck
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Re: [Numpy-discussion] Math Library

2010-04-05 Thread David Cournapeau
On Tue, Apr 6, 2010 at 12:56 AM, Charles R Harris
 wrote:
>
>>
>
> Yeah, but there isn't much low level stuff there and I don't want to toss a
> lot of real numerical code into it.

I don't understand: there is already math code there, and you cannot
be much more low level than what's there (there is already quite a bit
of bit twiddling for long double). I split the code into complex and
real, IEEE 754 macros/funcs in another file. I don' think we need to
split into one file / function, at least not with the current size of
the library.

I think it is much more worthwhile to think about reorganizing the
rest of numpy.core C code, the npymath library is very low hanging
fruit in comparison, if only by size.

David
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Re: [Numpy-discussion] Math Library

2010-04-05 Thread David Goldsmith
On Mon, Apr 5, 2010 at 9:50 AM, Charles R Harris
wrote:

> On Mon, Apr 5, 2010 at 10:43 AM, Robert Kern wrote:
>
>> On Mon, Apr 5, 2010 at 11:11, Charles R Harris
>>  wrote:
>> >
>> >
>> > On Mon, Apr 5, 2010 at 10:00 AM, Robert Kern 
>> wrote:
>> >>
>> >> On Mon, Apr 5, 2010 at 10:56, Charles R Harris
>> >>  wrote:
>> >> >
>> >> >
>> >> > On Mon, Apr 5, 2010 at 9:43 AM, Robert Kern 
>> >> > wrote:
>> >> >>
>> >> >> On Mon, Apr 5, 2010 at 10:40, Charles R Harris
>> >> >>  wrote:
>> >> >> > Hi All,
>> >> >> >
>> >> >> > David Cournapeau has mentioned that he would like to have a numpy
>> >> >> > math
>> >> >> > library that would supply missing functions and I'm wondering how
>> we
>> >> >> > should
>> >> >> > organise the source code. Should we put a mathlib directory in
>> >> >> > numpy/core/src?
>> >> >>
>> >> >> David already did this: numpy/core/src/npymath/
>> >> >>
>> >> >
>> >> > Yeah, but there isn't much low level stuff there and I don't want to
>> >> > toss a
>> >> > lot of real numerical code into it.
>> >>
>> >> Who cares? I don't.
>> >
>> > I care. I want the code to be organized.
>>
>> Then do it when there is code and we can see what needs to be organized.
>>
>>
> I am writing code and I want to decide up front where to put it. I know
> where you stand, so you need say no more. I'm waiting to see if other folks
> have an opinion.
>
> Chuck
>

Will you be using it right away?  If so, organize it locally how think it'll
work best, work w/ it a little while and see if you "guessed" right or if
you find yourself wanting to reorganize; then provide it to us w/ the
benefit of your experience. :-)

DG
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Re: [Numpy-discussion] Math Library

2010-04-05 Thread Charles R Harris
On Mon, Apr 5, 2010 at 10:43 AM, Robert Kern  wrote:

> On Mon, Apr 5, 2010 at 11:11, Charles R Harris
>  wrote:
> >
> >
> > On Mon, Apr 5, 2010 at 10:00 AM, Robert Kern 
> wrote:
> >>
> >> On Mon, Apr 5, 2010 at 10:56, Charles R Harris
> >>  wrote:
> >> >
> >> >
> >> > On Mon, Apr 5, 2010 at 9:43 AM, Robert Kern 
> >> > wrote:
> >> >>
> >> >> On Mon, Apr 5, 2010 at 10:40, Charles R Harris
> >> >>  wrote:
> >> >> > Hi All,
> >> >> >
> >> >> > David Cournapeau has mentioned that he would like to have a numpy
> >> >> > math
> >> >> > library that would supply missing functions and I'm wondering how
> we
> >> >> > should
> >> >> > organise the source code. Should we put a mathlib directory in
> >> >> > numpy/core/src?
> >> >>
> >> >> David already did this: numpy/core/src/npymath/
> >> >>
> >> >
> >> > Yeah, but there isn't much low level stuff there and I don't want to
> >> > toss a
> >> > lot of real numerical code into it.
> >>
> >> Who cares? I don't.
> >
> > I care. I want the code to be organized.
>
> Then do it when there is code and we can see what needs to be organized.
>
>
I am writing code and I want to decide up front where to put it. I know
where you stand, so you need say no more. I'm waiting to see if other folks
have an opinion.

Chuck
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Re: [Numpy-discussion] Math Library

2010-04-05 Thread Robert Kern
On Mon, Apr 5, 2010 at 11:11, Charles R Harris
 wrote:
>
>
> On Mon, Apr 5, 2010 at 10:00 AM, Robert Kern  wrote:
>>
>> On Mon, Apr 5, 2010 at 10:56, Charles R Harris
>>  wrote:
>> >
>> >
>> > On Mon, Apr 5, 2010 at 9:43 AM, Robert Kern 
>> > wrote:
>> >>
>> >> On Mon, Apr 5, 2010 at 10:40, Charles R Harris
>> >>  wrote:
>> >> > Hi All,
>> >> >
>> >> > David Cournapeau has mentioned that he would like to have a numpy
>> >> > math
>> >> > library that would supply missing functions and I'm wondering how we
>> >> > should
>> >> > organise the source code. Should we put a mathlib directory in
>> >> > numpy/core/src?
>> >>
>> >> David already did this: numpy/core/src/npymath/
>> >>
>> >
>> > Yeah, but there isn't much low level stuff there and I don't want to
>> > toss a
>> > lot of real numerical code into it.
>>
>> Who cares? I don't.
>
> I care. I want the code to be organized.

Then do it when there is code and we can see what needs to be organized.

>> > Maybe a subdirectory?
>>
>> I'm guessing YAGNI. Code first. Reorganize later, if necessary.
>
> Would that be Are or Aren't? I'm going for the first.

"Ain't", actually. Show us the code first. Until you do, I can't
imagine that there will be enough to add another layer of hierarchy to
the four we already have.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
  -- Umberto Eco
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Re: [Numpy-discussion] Math Library

2010-04-05 Thread Charles R Harris
On Mon, Apr 5, 2010 at 10:00 AM, Robert Kern  wrote:

> On Mon, Apr 5, 2010 at 10:56, Charles R Harris
>  wrote:
> >
> >
> > On Mon, Apr 5, 2010 at 9:43 AM, Robert Kern 
> wrote:
> >>
> >> On Mon, Apr 5, 2010 at 10:40, Charles R Harris
> >>  wrote:
> >> > Hi All,
> >> >
> >> > David Cournapeau has mentioned that he would like to have a numpy math
> >> > library that would supply missing functions and I'm wondering how we
> >> > should
> >> > organise the source code. Should we put a mathlib directory in
> >> > numpy/core/src?
> >>
> >> David already did this: numpy/core/src/npymath/
> >>
> >
> > Yeah, but there isn't much low level stuff there and I don't want to toss
> a
> > lot of real numerical code into it.
>
> Who cares? I don't.
>
>
I care. I want the code to be organized.


> > Maybe a subdirectory?
>
> I'm guessing YAGNI. Code first. Reorganize later, if necessary.
>
>
Would that be Are or Aren't? I'm going for the first.

Chuck
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Re: [Numpy-discussion] Math Library

2010-04-05 Thread Robert Kern
On Mon, Apr 5, 2010 at 10:56, Charles R Harris
 wrote:
>
>
> On Mon, Apr 5, 2010 at 9:43 AM, Robert Kern  wrote:
>>
>> On Mon, Apr 5, 2010 at 10:40, Charles R Harris
>>  wrote:
>> > Hi All,
>> >
>> > David Cournapeau has mentioned that he would like to have a numpy math
>> > library that would supply missing functions and I'm wondering how we
>> > should
>> > organise the source code. Should we put a mathlib directory in
>> > numpy/core/src?
>>
>> David already did this: numpy/core/src/npymath/
>>
>
> Yeah, but there isn't much low level stuff there and I don't want to toss a
> lot of real numerical code into it.

Who cares? I don't.

> Maybe a subdirectory?

I'm guessing YAGNI. Code first. Reorganize later, if necessary.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
  -- Umberto Eco
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Re: [Numpy-discussion] Math Library

2010-04-05 Thread Charles R Harris
On Mon, Apr 5, 2010 at 9:43 AM, Robert Kern  wrote:

> On Mon, Apr 5, 2010 at 10:40, Charles R Harris
>  wrote:
> > Hi All,
> >
> > David Cournapeau has mentioned that he would like to have a numpy math
> > library that would supply missing functions and I'm wondering how we
> should
> > organise the source code. Should we put a mathlib directory in
> > numpy/core/src?
>
> David already did this: numpy/core/src/npymath/
>
>
Yeah, but there isn't much low level stuff there and I don't want to toss a
lot of real numerical code into it. Maybe a subdirectory?

Chuck
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Re: [Numpy-discussion] Math Library

2010-04-05 Thread David Goldsmith
On Mon, Apr 5, 2010 at 8:40 AM, Charles R Harris
wrote:

> Hi All,
>
> David Cournapeau has mentioned that he would like to have a numpy math
> library that would supply missing functions and I'm wondering how we should
> organise the source code. Should we put a mathlib directory in
> numpy/core/src? Inside that directory would be functions for
> single/double/extended/quad precision. Should they be in separate
> directories? What about complex versions? I'm thinking that a good start
> would be to borrow the msun functions for doubles. We should also make a
> list of what functions would go into the library and what interface the
> complex functions present.
>
> Thoughts?
>

For starters: you talking things like Airy, Bessel, Gamma, stuff like that?

DG

>
> Chuck
>
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-- 
Mathematician: noun, someone who disavows certainty when their uncertainty
set is non-empty, even if that set has measure zero.
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Re: [Numpy-discussion] Math Library

2010-04-05 Thread Robert Kern
On Mon, Apr 5, 2010 at 10:40, Charles R Harris
 wrote:
> Hi All,
>
> David Cournapeau has mentioned that he would like to have a numpy math
> library that would supply missing functions and I'm wondering how we should
> organise the source code. Should we put a mathlib directory in
> numpy/core/src?

David already did this: numpy/core/src/npymath/

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
  -- Umberto Eco
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