I just discovered the:
Scipy Superpack for OS X
http://trichech.us/?page_id=4
Maybe this will help folks looking for an OS_X Scipy build.
-Chris
--
Christopher Barker, Ph.D.
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Christopher Barker wrote:
> [EMAIL PROTECTED] wrote:
>> I have been working on
>> f2py rewrite to support wrapping Fortran 90 types among other F90
>> constructs and as a result we have almost a complete Fortran parser in
>> Python. It is relatively easy to use this parser to automatically convert
[EMAIL PROTECTED] wrote:
> I have been working on
> f2py rewrite to support wrapping Fortran 90 types among other F90
> constructs and as a result we have almost a complete Fortran parser in
> Python. It is relatively easy to use this parser to automatically convert
> Fortran 77 codes that we have
On Wed, 27 Dec 2006, Christopher Barker wrote:
> Travis Oliphant wrote:
> > It is the
> > combination of SciPy+NumPy+Matplotlib+IPython (+ perhaps a good IDE)
> > that can succeed at being a MATLAB/IDL replacement for a lot of people.
>
>
> > What is also needed is a good "package" of it al
Travis Oliphant wrote:
> It is the
> combination of SciPy+NumPy+Matplotlib+IPython (+ perhaps a good IDE)
> that can succeed at being a MATLAB/IDL replacement for a lot of people.
> What is also needed is a good "package" of it all --- like the Enthon
> distribution. This requires quite a
Robert Kern schrieb:
> Rather, to put it accurately, numpy should not get large chunks of scipy
> functionality that require FORTRAN dependencies for reasons that should be
> obvious from that description. scipy.stats.distributions is just such a chunk.
I was probably not very clear, I was refe
Travis Oliphant wrote:
> I'm always confused about how to distribute something like SciPy for the
> MAC. What exactly should be distributed? Is it possible to use
> distutils to get it done?
To get a package format that is actually useful (bdist_dumb just doesn't cut it
on any platform, real
Sven Schreiber wrote:
> Robert Kern schrieb:
>
>> Pierre GM wrote:
>>
> So, to put it "pointedly" (if that's the right word...?):
> Numpy should not get small functions from scipy -> because the size of
> scipy doesn't matter -> because scipy's modules will be installable as
> add-ons separ
Christopher Barker wrote:
> It can be a pain to build this kind of thing on OS-X, as Apple has not
> supported a Fortran compiler yet, but it can (and has) been done. IN
> fact, the Mac is a great target for pre-built binaries as there is only
> a small variety of hardware to support, and Apple
> Alan G Isaac wrote:
>> Strip it down like you suggest and aside from Windows
>> users (and Macs are increasingly popular among my
>> students) you'll have only the few that are not
>> intimidated by building SciPy (which still has no
>> intaller for Python 2.5).
On Fri, 22 Dec 2006, Robert
Alan G Isaac wrote:
> PS A question: is it a good thing if more students start
> using NumPy *now*? It looks to me like building community
> size is an important current goal for NumPy. Strip it down
> like you suggest and aside from Windows users (and Macs are
> increasingly popular among m
Sven Schreiber wrote:
> So, to put it "pointedly" (if that's the right word...?):
> Numpy should not get small functions from scipy -> because the size of
> scipy doesn't matter -> because scipy's modules will be installable as
> add-ons separately (and because there will be ready-to-use installers
Sven Schreiber wrote:
> So, to put it "pointedly" (if that's the right word...?):
> Numpy should not get small functions from scipy -> because the size of
> scipy doesn't matter -> because scipy's modules will be installable as
> add-ons separately (and because there will be ready-to-use installers
On Fri, Dec 22, 2006 at 10:47:33AM +0100, Sven Schreiber wrote:
> Please don't feel offended, I just want to make the point (as usual)
> that this way numpy is going to be a good library for other software
> projects, but not super-attractive for direct users (aka "matlab
> converts", although I pe
Robert Kern schrieb:
> Pierre GM wrote:
>> Talking about that, what happened to these projects of modular installation
>> of scipy ? Robert promised us last month to explain what went wrong with his
>> approach, but never had the time...
>
> I created a module (scipy_subpackages.py, IIRC) next
Pierre GM wrote:
> On Thursday 21 December 2006 16:10, Travis Oliphant wrote:
>
>> I much prefer to make SciPy an easy install for as many people as
>> possible and/or work on breaking up SciPy into modular components that
>> can be installed separately if needed.
>
> Talking about that, what
On Thursday 21 December 2006 16:10, Travis Oliphant wrote:
> I much prefer to make SciPy an easy install for as many people as
> possible and/or work on breaking up SciPy into modular components that
> can be installed separately if needed.
Talking about that, what happened to these projects o
A key thing to remember here is that each user has their particular set
of "small things" that are all they need from scipy -- put us all
together, and you have SciPy -- that's what it is for.
> As a user, I suggest that this becomes a reasonable goal
> when up to date SciPy installers are main
Mark Janikas wrote:
> Thanks for all the input so far. The only thing that seems odd about
> the omission of probability or quantile functions in NumPy is that all
> the random number generators are present in RandomArray.
A big part of the issue is that getting many of those pdfs into NumPy
wou
On 21/12/06, Alan G Isaac <[EMAIL PROTECTED]> wrote:
> A Dijous 21 Desembre 2006 05:59, A. M. Archibald escrigué:
> > It seems to me that numpy should include only tools for
> > basic calculations on arrays of numbers. The ufuncs,
> > simple wrappers (dot, for example). Anything that requires
> > n
A Dijous 21 Desembre 2006 05:59, A. M. Archibald escrigué:
> It seems to me that numpy should include only tools for
> basic calculations on arrays of numbers. The ufuncs,
> simple wrappers (dot, for example). Anything that requires
> nontrivial amounts of math (matrix inversion, statistical
>
A Dijous 21 Desembre 2006 05:59, A. M. Archibald escrigué:
> On 20/12/06, Alan G Isaac <[EMAIL PROTECTED]> wrote:
> > On Wed, 20 Dec 2006, Robert Kern apparently wrote:
> > > We have a full complement of PDFs, CDFs, etc. in scipy.
> >
> > This is my "most missed" functionality in NumPy.
> > (For no
: Thursday, December 21, 2006 7:10 AM
To: Discussion of Numerical Python
Subject: Re: [Numpy-discussion] Newbie Question, Probability
A. M. Archibald schrieb:
> On 20/12/06, Alan G Isaac <[EMAIL PROTECTED]> wrote:
>> This is my "most missed" functionality in NumPy.
>
On 12/20/06, A. M. Archibald <[EMAIL PROTECTED]> wrote:
> Moreover it damages the performance of
> numpy. For example, dot would be faster (for arrays that happen to be
> matrix-shaped, and possibly in general) if it could use ATLAS' routine
> from BLAS.
I thought numpy uses ATLAS. Matrix multipl
A. M. Archibald schrieb:
> On 20/12/06, Alan G Isaac <[EMAIL PROTECTED]> wrote:
>> This is my "most missed" functionality in NumPy.
>> (For now I feel cannot ask students to install SciPy.)
>> Although it is a slippery slope, and I definitely do not
>> want NumPy to slide down it, I would certainl
On 20/12/06, Alan G Isaac <[EMAIL PROTECTED]> wrote:
> On Wed, 20 Dec 2006, Robert Kern apparently wrote:
> > We have a full complement of PDFs, CDFs, etc. in scipy.
>
> This is my "most missed" functionality in NumPy.
> (For now I feel cannot ask students to install SciPy.)
> Although it is a slip
On Dec 20, 2006, at 8:41 PM, Alan G Isaac wrote:
> On Wed, 20 Dec 2006, Robert Kern apparently wrote:
>> We have a full complement of PDFs, CDFs, etc. in scipy.
>
> This is my "most missed" functionality in NumPy.
> (For now I feel cannot ask students to install SciPy.)
If they're already install
On Wed, 20 Dec 2006, Robert Kern apparently wrote:
> We have a full complement of PDFs, CDFs, etc. in scipy.
This is my "most missed" functionality in NumPy.
(For now I feel cannot ask students to install SciPy.)
Although it is a slippery slope, and I definitely do not
want NumPy to slide down
Mark Janikas wrote:
> Hello all,
>
> Is there a way to get probability values for the various families of
> distributions in numpy? I.e. ala R:
We have a full complement of PDFs, CDFs, etc. in scipy.
In [1]: from scipy import stats
In [2]: stats.norm.pdf(1.96, loc=0.0, scale=1.0)
Out[2]: arr
Hello all,
Is there a way to get probability values for the various families of
distributions in numpy? I.e. ala R:
> pnorm(1.96, mean = 0 , sd = 1)
[1] 0.9750021
# for the normal
> pt(1.65, df=100)
[1] 0.9489597
# for student t
Any suggestions would be greatly appreciat
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