Hi Warren,
On Sat, Nov 12, 2011 at 9:31 AM, Warren Weckesser
wrote:
>
>
> On Sat, Nov 12, 2011 at 6:43 AM, wrote:
>>
>> On Sat, Nov 12, 2011 at 3:36 AM, Geoffrey Zhu wrote:
>> > Hi,
>> >
>> > I am playing with multiple ways to speed up the fo
Hi,
I am playing with multiple ways to speed up the following expression
(it is in the inner loop):
C[1:(M - 1)]=(a * C[2:] + b * C[1:(M-1)] + c * C[:(M-2)])
where C is an array of about 200-300 elements, M=len(C), a, b, c are scalars.
I played with numexpr, but it was way slower than directly
<[EMAIL PROTECTED]>
> > Date:
> > Tue, 20 Nov 2007 17:13:31 -0500
> > To:
> > "Discussion of Numerical Python"
> >
> > To:
> > "Discussion of Numerical Python"
> >
> >
> > On 20/11/2007, Geoffrey Zhu <[EMAIL
Hi Everyone,
This is off topic for this mailing list but I don't know where else to ask.
I have N tabulated data points { (x_i, y_i, z_i) } that describes a 3D
surface. The surface is pretty "smooth." However, the number of data
points is too large to be stored and manipulated efficiently. To mak
On Nov 13, 2007 2:37 AM, David Cournapeau <[EMAIL PROTECTED]> wrote:
> Geoffrey Zhu wrote:
> >
> > Yes, with the MSI I can always reproduce the problem with
> > numpy.test(). It always hangs.With the egg it does not hang. Pointer
> > problems are usually random, b
On Nov 12, 2007 10:26 PM, David Cournapeau <[EMAIL PROTECTED]> wrote:
> Geoffrey Zhu wrote:
> > On Nov 12, 2007 12:37 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> >> On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
> >>>
On Nov 12, 2007 12:37 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
>
> On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
> > The following code calling numpy v1.0.4 fails to terminate on my machine,
> > which was not the case with v1.0.3.1
> >
> > from numpy import arange, floa
On Nov 9, 2007 11:42 AM, Nils Wagner <[EMAIL PROTECTED]> wrote:
> On Fri, 9 Nov 2007 11:31:54 -0600
> "Geoffrey Zhu" <[EMAIL PROTECTED]> wrote:
>
> > Very interesting! If I use the MSI file, numpy.test()
> >hangs. If,
> >
On Nov 9, 2007 11:45 AM, Travis E. Oliphant <[EMAIL PROTECTED]> wrote:
> Geoffrey Zhu wrote:
> > Very interesting! If I use the MSI file, numpy.test() hangs. If,
> > however, I use the EGG file, it is actually fine.
> >
>
> Can you find the md5sum of these fi
Very interesting! If I use the MSI file, numpy.test() hangs. If,
however, I use the EGG file, it is actually fine.
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On Nov 9, 2007 10:14 AM, Geoffrey Zhu <[EMAIL PROTECTED]> wrote:
>
> On Nov 8, 2007 10:06 PM, David Cournapeau <[EMAIL PROTECTED]> wrote:
> >
> > Geoffrey Zhu wrote:
> > > On Nov 8, 2007 12:12 PM, Robert Kern <[EMAIL PROTECTED]> wrote:
> > >
On Nov 8, 2007 10:06 PM, David Cournapeau <[EMAIL PROTECTED]> wrote:
>
> Geoffrey Zhu wrote:
> > On Nov 8, 2007 12:12 PM, Robert Kern <[EMAIL PROTECTED]> wrote:
> >
> >> Geoffrey Zhu wrote:
> >>
> >>> Good morning.
> >>
On Nov 8, 2007 12:12 PM, Robert Kern <[EMAIL PROTECTED]> wrote:
>
> Geoffrey Zhu wrote:
> > Good morning.
> >
> > I just installed the Windows binary of numpy 1.04. When I ran
> > numpy.test() in IDLE (the Python shell that comes with Python), the
> > pro
Good morning.
I just installed the Windows binary of numpy 1.04. When I ran
numpy.test() in IDLE (the Python shell that comes with Python), the
program hang (or at least is running for half an hour). I am using
Windows XP, duel core intel CPU.
Does anyone know what is going on?
Thanks,
Geoffrey
Hi All,
If I execute the following code, I find that function f() sometimes is
called with an empty array. I am not sure why this is necessary. Is
this a bug?
def f(x):
return x**2
return numpy.piecewise(u, abs(u)<1, [f, 0])
Thanks,
Geoffrey
___
Num
On 10/18/07, Robert Kern <[EMAIL PROTECTED]> wrote:
> Geoffrey Zhu wrote:
> > Hi All,
> >
> > Given three vectors of the same lengths, X, Y, and Z, I am looking for
> > an efficient way to calculate the following:
> >
> > sum(x[i]*y[i]*z[i], for i=
I think I figured out: sum(X*Y*Z).
Never mind.
On 10/18/07, Geoffrey Zhu <[EMAIL PROTECTED]> wrote:
> Hi All,
>
> Given three vectors of the same lengths, X, Y, and Z, I am looking for
> an efficient way to calculate the following:
>
> sum(x[i]*y[i]*z[i], for i=1..n
Hi All,
Given three vectors of the same lengths, X, Y, and Z, I am looking for
an efficient way to calculate the following:
sum(x[i]*y[i]*z[i], for i=1..n )
I am not sure if there is a vectorized way to do this.
Thanks,
Geoffrey
___
Numpy-discussion
On 8/21/07, Timothy Hochberg <[EMAIL PROTECTED]> wrote:
>
>
>
> On 8/21/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
> >
> >
> >
> > On 8/20/07, Geoffrey Zhu < [EMAIL PROTECTED]> wrote:
> > > Hi Everyone,
> > >
> > &g
Hi Everyone,
I am wondering if there is an "extended" outer product. Take the
example in "Guide to Numpy." Instead of doing an multiplication, I
want to call a custom function for each pair.
>>> print outer([1,2,3],[10,100,1000])
[[ 10 100 1000]
[ 20 200 2000]
[ 30 300 3000]]
So I want:
[
[f
On 8/17/07, Robert Kern <[EMAIL PROTECTED]> wrote:
> Geoffrey Zhu wrote:
> > Hi All,
> >
> > I want to construct a numpy array based on Python objects. In the
> > below code, opts is a list of tuples.
> >
> > For example,
> >
> > opts=[ (&#
Hi All,
I want to construct a numpy array based on Python objects. In the
below code, opts is a list of tuples.
For example,
opts=[ ('C', 100, 3, 'A'), ('K', 200, 5.4, 'B')]
If I use a generator like the following:
K=numpy.array(o[2]/1000.0 for o in opts)
It does not work.
I have to use:
nu
Hi Timothy,
On 7/31/07, Timothy Hochberg <[EMAIL PROTECTED]> wrote:
> [SNIP]
>
> > The 'brute-force' way is basically what you suggested -- looping
> > through all the records and building a two-way hash-table of the data.
> >
> > The problem of the brute-force' approach is that it is not taking
Hi Timothy,
On 7/30/07, Timothy Hochberg <[EMAIL PROTECTED]> wrote:
>
>
> On 7/30/07, Geoffrey Zhu <[EMAIL PROTECTED]> wrote:
> > Hi Everyone,
> >
> > I am wondering what is the best (and fast) way to build a pivot table
> > aside from the 'brut
Hi Everyone,
I am wondering what is the best (and fast) way to build a pivot table
aside from the 'brute force way?'
I want to transform an numpy array into a pivot table. For example, if
I have a numpy array like below:
Region Date # of Units
-------
On 7/29/07, Lou Pecora <[EMAIL PROTECTED]> wrote:
> I wrote a basic article on C extensions using NumPy
> arrays on the SciPy.org site. See:
> Cookbook/C_Extensions/NumPy at
>
> http://www.scipy.org/Cookbook/C_Extensions/NumPy_arrays?highlight=%28%28%28-%2A%29%28%5Cr%29%3F%5Cn%29%28.%2A%29Cate
Hi Sebastian,
> Oooh - I see - there is the date: July 24 ...
> [ another email just came in is from 7/18 ...]
> That's quite interesting.
> I have never seen such a delay before
> Was some computer sitting on them being turnted off for 10 days ? ;-)
>
> -Sebastian.
Not knowing that the
On 7/26/07, Robert Kern <[EMAIL PROTECTED]> wrote:
> Geoffrey Zhu wrote:
> >>>>> How do I handle this situation? Is there any way to access any data
> >>>>> type that can be converted into a double?
> >>>> I usually use PyArray_FROM_O
> >>> How do I handle this situation? Is there any way to access any data
> >>> type that can be converted into a double?
> >> I usually use PyArray_FROM_OTF(). That handles the usual cases. It's
> >> pretty much
> >> like starting off a pure Python function with asarray(x, dtype=whatever).
> >>
>
On 7/26/07, Robert Kern <[EMAIL PROTECTED]> wrote:
> Geoffrey Zhu wrote:
> > Hi Everyone,
> >
> > I finally build a C extension. The one problem I found is that it is
> > too picky about the input. For example, it accepts
> > array([1.0,2.0,3.0]) with n
Hi Everyone,
I finally build a C extension. The one problem I found is that it is
too picky about the input. For example, it accepts
array([1.0,2.0,3.0]) with no problem, but when I pass in
array([1,2,3]), since the dtype of the array is now int, my extension
does not like it.
How do I handle thi
Hi,
I am writing a function that would take a list of datetime objects and
a list of single letter characters (such as ["A","B","C"]). The number
of items tend to be big and both the list and the numpy array have all
the functionalities I need.
Do you think I should use numpy arrays or the regula
Hi Robert,
On 7/24/07, Robert Kern <[EMAIL PROTECTED]> wrote:
> Geoffrey Zhu wrote:
> > Thanks for your help. Do you know what exactly is the issue of having
> > to use VS2003 to build extensions? If the interactions are done at DLL
> > level, shouldn't call compi
Hi Robert,
On 7/24/07, Robert Kern <[EMAIL PROTECTED]> wrote:
> Geoffrey Zhu wrote:
> > Hi,
> >
> > I am about to write a C extension module. C functions in the module will
> > take and return numpy arrays. I found a tutorial online, but I am not
> > sur
Hi,
I am about to write a C extension module. C functions in the module will
take and return numpy arrays. I found a tutorial online, but I am not sure
about the following:
1. Can I compile my extension with Visual Studio 2005? My impression is that
I will have to link with numpy libraries, and,
>Hi,
>Well maybe it is a bug on my box (thunderbird) but the topic of the
thread is "-lmkl_lapack64 on i368 ??".
>Nothing to do with "Logical Selector" ;) Should I post another mail
about this topic?
>Xavier
>ps : I'm just sorry for the noise if it is a bug on my side.
>--
Hi Xavier,
I di
Hi Everyone,
I am finding that numpy cannot operate on boolean arrays. For example,
the following does not work:
x=3Darray([(1,2),(2,1),(3,1),(4,1)])
x[x[:,0]>x[:,1] and x[1:]>1,:]
It gives me an syntax error:
---
Traceback (most recent call last):
File "", line 1, in
x[
semantics. I'm sure they
are also documented somewhere but I usually find trying many examples
helpful.
--Tom
On 6/28/07, Geoffrey Zhu <[EMAIL PROTECTED]> wrote:
> Hi All,
>
> I am curious how numpy is implemented. Syntax such as x[10::-2] is
> completely foreign to Pyt
Hi All,
I am curious how numpy is implemented. Syntax such as x[10::-2] is
completely foreign to Python. How does numpy get Python to support it?
Thanks,
Geoffrey
PS. Ignore the disclaimer. The mail server automatically insert that.
___=0A=
=0
over i,
by replacing [i] by [:-2], [i+1] by [1:-1] and [i+2] by [2:]. But I
might be wrong. Can you submit the piece of code with at least the most
internal loop?
Nadav.
-Original Message-
From: [EMAIL PROTECTED] on behalf of Geoffrey Zhu
Sent: Thu 15-Feb-07 18:32
To: Discussio
IL PROTECTED] on behalf of Geoffrey Zhu
> Sent: Thu 15-Feb-07 18:32
> To: Discussion of Numerical Python
> Cc:
> Subject: Re: [Numpy-discussion] Numpy and iterative procedures
>
> Thanks Chuck.
>
> I am trying to use Successive Over-relaxation to solve linear
I am really new to numpy but I just found that v[2:4] means selecting
v[2] and v[3]. V[4] is not included! This is quite different from the
conventions of matlab and R.
___=0A=
=0A=
The information in this email or in any file attached=0A=
h
Numpy-discussion] Numpy and iterative procedures
On 2/15/07, Geoffrey Zhu <[EMAIL PROTECTED]> wrote:
Hi,
I am new to numpy. I'd like to know if it is possible to code
efficient
iterative procedures with numpy.
Specifically, I have the following problem.
Hi,
I am new to numpy. I'd like to know if it is possible to code efficient
iterative procedures with numpy.
Specifically, I have the following problem.
M is an N*N matrix. Q is a N*1 vector. V is an N*1 vector I am trying to
find iteratively from the initial value V_0. The procedure is simply
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