On 2/21/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
On 2/21/07, Timothy Hochberg <[EMAIL PROTECTED]> wrote:
>
>
>
> On 2/21/07, Charles R Harris < [EMAIL PROTECTED]> wrote:
> >
> >
> >
> > On 2/21/07, Robert Kern < [EMAIL PROTECTED]> wrote:
> > >
> > > Christopher Barker wrote:
> > > > Rob
On 2/21/07, Timothy Hochberg <[EMAIL PROTECTED]> wrote:
On 2/21/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
>
>
>
> On 2/21/07, Robert Kern < [EMAIL PROTECTED]> wrote:
> >
> > Christopher Barker wrote:
> > > Robert Kern wrote:
> > >> Christopher Barker wrote:
> > >>> I wonder if there are
In article <[EMAIL PROTECTED]>,
Zachary Pincus <[EMAIL PROTECTED]> wrote:
> Hello folks,
>
> I've developed some command-line tools for biologists using python/
> numpy and some custom C and Fortran extensions, and I'm trying to
> figure out how to easily distribute them...
>
> For people us
On 2/21/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
On 2/21/07, Robert Kern <[EMAIL PROTECTED]> wrote:
>
> Christopher Barker wrote:
> > Robert Kern wrote:
> >> Christopher Barker wrote:
> >>> I wonder if there are any C math libs that do a better job than
> you'd
> >>> expect from standar
On 2/21/07, Robert Kern <[EMAIL PROTECTED]> wrote:
Christopher Barker wrote:
> Robert Kern wrote:
>> Christopher Barker wrote:
>>> I wonder if there are any C math libs that do a better job than you'd
>>> expect from standard FP? (short of unlimited precision ones)
>> With respect to π and the z
If none of the suggested methods turn out to be efficient enough due to
copying overhead, here's a way to reduce the copying overhead by trading
memory (and a bit of complexity) for copying overhead. The general thrust is
to allocate M extra slices of memory and then shift the data every M time
sl
On 21/02/07, Robert Kern <[EMAIL PROTECTED]> wrote:
> Well, you can always use long double if it is implemented on your platform.
> You
> will have to construct a value for π yourself, though. I'm afraid that we
> don't
> really make that easy.
If the trig functions are implemented at all, you
On 21/02/07, Alexander Michael <[EMAIL PROTECTED]> wrote:
> On 2/21/07, Mike Ressler <[EMAIL PROTECTED]> wrote:
> > Would loading your data via memmap, then slicing it, do your job
> > (using numpy.memmap)? ...
>
> Interesting idea. I think Anne's suggestion that sliced assignment
> will reduce to
Christopher Barker wrote:
> Robert Kern wrote:
>> Christopher Barker wrote:
>>> I wonder if there are any C math libs that do a better job than you'd
>>> expect from standard FP? (short of unlimited precision ones)
>> With respect to π and the zeros of sin() and cos()? Not really.
I'll back off o
On 2/21/07, Christopher Barker <[EMAIL PROTECTED]> wrote:
Anne Archibald wrote:
> Or, to see more clearly, try taking (on a pocket calculator, say)
> sin(3.14) (or even sin(pi)).
This is an interesting point. I took a class from William Kahan once
(pass/fail, thank god!), and one question he po
On 2/21/07, Mike Ressler <[EMAIL PROTECTED]> wrote:
> Would loading your data via memmap, then slicing it, do your job
> (using numpy.memmap)? ...
Interesting idea. I think Anne's suggestion that sliced assignment
will reduce to an efficient memcpy fits my needs a bit better than
memmap because I'
I grew up a TI guy - my recollection is that they stated in the user
manual that though the display could show "only" 10 decimal digits,
memory saved and computations used 16; perhaps nowadays it is even more,
but unless you're doing millions of sequential calculations (how often
do you do that
Robert Kern wrote:
> Christopher Barker wrote:
>> I wonder if there are any C math libs that do a better job than you'd
>> expect from standard FP? (short of unlimited precision ones)
>
> With respect to π and the zeros of sin() and cos()? Not really. If
> numpy.sin(numpy.pi) were to give you 0.0
Robert Kern wrote:
> Christopher Barker wrote:
>
>> I wonder if there are any C math libs that do a better job than you'd
>> expect from standard FP? (short of unlimited precision ones)
>>
>
> With respect to π and the zeros of sin() and cos()? Not really. If
> numpy.sin(numpy.pi) were to
Christopher Barker wrote:
> I wonder if there are any C math libs that do a better job than you'd
> expect from standard FP? (short of unlimited precision ones)
With respect to π and the zeros of sin() and cos()? Not really. If
numpy.sin(numpy.pi) were to give you 0.0, it would be *wrong*. numpy.
Anne Archibald wrote:
>Discontiguous blocks are somewhat inconvenient; one of the key
>assumptions of numpy is that memory is stored in contiguous,
>homogeneous blocks.
>
Not to add anything really useful to this discussion, but I should
correct this wording before it gives incorrect conception
Toon Knapen wrote:
>Hi all,
>
>Is there detailed info on the installation process available.
>
>I'm asking because in addition to installing numpy on linux-x86, I'm
>also trying to install numpy on aix-power and windows-x86. So before
>bombarding the ml with questions, I would like to get my han
Anne Archibald wrote:
> Or, to see more clearly, try taking (on a pocket calculator, say)
> sin(3.14) (or even sin(pi)).
This is an interesting point. I took a class from William Kahan once
(pass/fail, thank god!), and one question he posed to us was:
How many digits of pi is used in an HP calcu
Anne Archibald wrote:
> On 21/02/07, Zachary Pincus <[EMAIL PROTECTED]> wrote:
>
>
>> A corrolary: in general do not two floating-point values for equality
>> -- use something like numpy.allclose. (Exception -- equality is
>> expected if the exact sequence of operations to generate two numbers
>
On 2/21/07, Mike Ressler <[EMAIL PROTECTED]> wrote:
> Would loading your data via memmap, then slicing it, do your job
> (using numpy.memmap)? ...
Interesting idea. I think Anne's suggestion that sliced assignment
will reduce to an efficient memcpy fits my needs a bit better than
memmap because I'
As far as a computer is concerned, those numbers are "around" zero -
"growing-up" w/ Matlab, e.g., one quickly learns to recognize these
numbers for what they are. One way to return zero for numbers like
these is
if numpy.allclose(x, 0): return 0 (or 0*x to assure that 0 is the same
type as x
On 2/21/07, Alexander Michael <[EMAIL PROTECTED]> wrote:
> ... T is to large to fit in memory, so I need to
> load up H, perform my calculations, pop the oldest N x P slice and
> push the newest N x P slice into the data cube. What's the best way to
> do this that will maintain fast computations al
It's true -- blindly using allclose isn't a lot better than blindly
using equality testing. (Though given the choice between blindly
using one and blindly using the other, I'd still probably vote for
allclose... it won't get you quantum mechanics, but it'll do fine for
a lot of other things
Anne Archibald schrieb:
> On 21/02/07, WolfgangZillig <[EMAIL PROTECTED]> wrote:
>> Hi,
>>
>> I'm quite new to numpy/scipy so please excuse if my problem is too obvious.
>>
>> example code:
>>
>> import numpy as n
>> print n.sin(n.pi)
>> print n.cos(n.pi/2.0)
>>
>> results in:
>> 1.22460635382e-016
On 21/02/07, Zachary Pincus <[EMAIL PROTECTED]> wrote:
> A corrolary: in general do not two floating-point values for equality
> -- use something like numpy.allclose. (Exception -- equality is
> expected if the exact sequence of operations to generate two numbers
> were identical.)
I really can't
On 21/02/07, WolfgangZillig <[EMAIL PROTECTED]> wrote:
> Hi,
>
> I'm quite new to numpy/scipy so please excuse if my problem is too obvious.
>
> example code:
>
> import numpy as n
> print n.sin(n.pi)
> print n.cos(n.pi/2.0)
>
> results in:
> 1.22460635382e-016
> 6.12303176911e-017
>
> I've expecte
Your results are indeed around zero.
>>> numpy.allclose(0, 1.22460635382e-016)
True
It's not exactly zero because floating point math is in general not
exact. You'll need to check out a reference about doing floating
point operations numerically for more details, but in general you
should
WolfgangZillig wrote:
> Hi,
>
> I'm quite new to numpy/scipy so please excuse if my problem is too obvious.
>
> example code:
>
> import numpy as n
> print n.sin(n.pi)
> print n.cos(n.pi/2.0)
>
> results in:
> 1.22460635382e-016
> 6.12303176911e-017
>
> I've expected something around 0. Can an
On 2/21/07, WolfgangZillig <[EMAIL PROTECTED]> wrote:
Hi,
I'm quite new to numpy/scipy so please excuse if my problem is too
obvious.
example code:
import numpy as n
print n.sin(n.pi)
print n.cos(n.pi/2.0)
results in:
1.22460635382e-016
6.12303176911e-017
I've expected something around 0. C
On 21/02/07, Alexander Michael <[EMAIL PROTECTED]> wrote:
> I'm new to numpy and looking for advice on setting up and managing
> array data for my particular problem. I'm collecting observations of P
> properties for N objects over a rolling horizon of H sample times. I
> could conceptually store t
Hi,
I'm quite new to numpy/scipy so please excuse if my problem is too obvious.
example code:
import numpy as n
print n.sin(n.pi)
print n.cos(n.pi/2.0)
results in:
1.22460635382e-016
6.12303176911e-017
I've expected something around 0. Can anybody explain what I am doing
wrong here?
There's probably a better forum for this conversation, but...
Barry Wark wrote:
> Perhaps we should consider two use cases: interactive use ala Matlab
> and larger code bases.
A couple key points -- yes, interactive use is different than larger
code bases, but I think it's a "Bad Idea" to promit
Andrew Straw wrote:
> Here's one that seems like
> it might work, but I haven't tried it yet:
> http://software.jessies.org/terminator
Now if only there was a decent terminal emulator for Windows that didn't
use cygwin...
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Respons
I'm new to numpy and looking for advice on setting up and managing
array data for my particular problem. I'm collecting observations of P
properties for N objects over a rolling horizon of H sample times. I
could conceptually store the data in three-dimensional array with
shape (N,P,H) that would a
Hi all,
Is there detailed info on the installation process available.
I'm asking because in addition to installing numpy on linux-x86, I'm
also trying to install numpy on aix-power and windows-x86. So before
bombarding the ml with questions, I would like to get my hands on all
doc available (I
Hi Andre,
I've downloaded bpycdf and it works very nicely with numpy; thanks
very much for all your effort.
One small problem; I'm probably being stupid, but I cannot see how to
set a _Fillvalue as Float32.
regards, George Nurser.
On 12/02/07, Andre Gosselin <[EMAIL PROTECTED]> wrote:
> A small
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