On 12/11/11 8:40 AM, Ralf Gommers wrote:
> On Wed, Dec 7, 2011 at 7:50 PM, Chris.Barker * If we have a good, fast ascii (or unicode?) to array reader, hopefully
> it could be leveraged for use in the more complex cases. So that rather
> than genfromtxt() being written from sc
On 12/9/11 11:25 AM, Ng, Enrico wrote:
> I am trying to pass a multi-dimensional ndarray to C as a multi-dimensional C
> array for the purposes of passing it to mathematica. I am using
> PyArray_AsCArray but getting an error.
I understand that SWIG, Boost, et. al are perhaps too heavyweight for
Hi folks,
This is a continuation of a conversation already started, but i gave it
a new, more appropriate, thread and subject.
On 12/6/11 2:13 PM, Wes McKinney wrote:
> we should start talking
> about building a *high performance* flat file loading solution with
> good column type inference and
Hi folks,
I'm working on a "ragged array" class -- an array that can store and
work with what can be considered tabular data, with the rows of
different lengths:
"""
ragged_array
A "ragged" array class -- build on numpy
The idea is to be able to store data that is essentially 2-d, but each
On 11/14/11 2:02 PM, Andrea Zonca wrote:
On Mon, Nov 14, 2011 at 09:24, Chris.Barker wrote:
On 11/11/11 8:28 PM, Craig Yoshioka wrote:
I once wrote a generic n-dimensional binning routine in C that I
could find if anyone is interested in integrating it into numpy... it
didn't do
On 11/10/11 3:57 AM, Olivier Delalleau wrote:
> In such a situation you should probably use a dictionary from the start,
all good suggestions, but while we're at it:
On 11/10/11 2:17 AM, Chao YUE wrote:
> Does anyone know how I can quickly use the name of a ndarray as a string?
This reflects a k
On 11/11/11 8:28 PM, Craig Yoshioka wrote:
> I once wrote a generic n-dimensional binning routine in C that I
> could find if anyone is interested in integrating it into numpy... it
> didn't do size increases though... and I think I implemented it so
> that binning by a non-divisible factor trimmed
On 11/13/11 9:55 AM, Olivier Delalleau wrote:
> idea, since it will throw out a lot of information if you decrease the
> number of bins:
I agree -- I'd think about looking at a smooth interpolation -- maybe
kernel density estimation?
On 11/14/11 8:12 AM, Sturla Molden wrote:
> Fit a poisson dist
On 11/7/11 10:16 AM, Carlos Neves wrote:
> I am a robotics student and I have used numpy to develop a controller
> for a humanoid robot. Now I am trying to implement the same controller
> to a different robot, NAO - http://www.aldebaran-robotics.com/
> This robot has a Linux based OS with Python 2.
On 11/2/11 7:16 PM, Nathaniel Smith wrote:
> By R compatibility, I specifically had in mind in-memory
> compatibility.
The R crowd has had a big voice in this discussion, and I understand
that there are some nice lessons to be learned from it with regard to
the NA issues.
However, I think makin
On 10/31/11 6:38 PM, Stéfan van der Walt wrote:
> On Mon, Oct 31, 2011 at 6:25 PM, Matthew Brett
> wrote:
>> Oh, dear, I'm suffering now:
>> In [12]: res> 2**31-1
>> Out[12]: array([False], dtype=bool)
> I'm seeing:
...
> Your result seems very strange, because the numpy scalars should
> perf
On 10/28/11 11:37 AM, Matthew Brett wrote:
> The main motivation for the alterNEP was our strong feeling that
> separating ABSENT and IGNORE was easier to comprehend and cleaner.
I don't know about easier to comprehend, or cleaner, but it is more
feature-full.
I see two issues here:
1) being ab
On 10/27/11 7:51 PM, Travis Oliphant wrote:
> As I mentioned. I find the ability to separate an ABSENT idea from an
> IGNORED idea convincing. In other words, I think distinguishing between
> masks and bit-patterns is not just an implementation detail, but
> provides a useful concept for multiple u
On 10/14/11 5:04 AM, Neal Becker wrote:
> suppose I have:
>
> In [10]: u
> Out[10]:
> array([[0, 1, 2, 3, 4],
> [5, 6, 7, 8, 9]])
>
> And I have a vector v:
> v = np.array ((0,1,0,1,0))
>
> I want to form an output vector which selects items from u where v is the
> index
> of the row of
On 10/13/11 6:03 AM, Linus Jundén wrote:
> I am about to make a NumPy presentation for my colleges in about a
> week. I want to tell them something about the history of the library
> and what kind of code it relies on.
> Is NumPy based on some external code like e.g. BLAS, LAPACK etc or is
> it co
On 9/27/11 2:14 AM, oc-spam66 wrote:
>> if you want to write to a string, why not use .tostring()?
>
> Because A.tostring() returns the binary data, while I would like the text
> representation.
> More precisely, I would like to use A.tofile(sep="\t").
I see -- I've always thought mingling bina
> On 25.09.2011 18:23, OC wrote:
>> as said in the subject, the following code produces an error. Is it normal ?
>>
>> **
>> A = r_[1]
>> file_buffer = StringIO()
>> A.tofile(file_buffer)
>>
>> IOError: first argument must be a string or open
On 9/12/11 4:38 PM, Christopher Jordan-Squire wrote:
> I did some timings to see what the advantage would be, in the simplest
> case possible, of taking multiple lines from the file to process at a
> time.
Nice work, only a minor comment:
> f6 and f7 use stripped down versions of Chris
> Barker's
On 9/8/11 1:43 PM, Christopher Jordan-Squire wrote:
> I just ran a quick test on my machine of this idea. With
>
> dt = np.dtype([('x',np.float32),('y', np.int32),('z', np.float64)])
> temp = np.empty((), dtype=dt)
> temp2 = np.zeros(1,dtype=dt)
>
> In [96]: def f():
> ...: l=[0]*3
>
On 9/2/11 2:45 PM, Christopher Jordan-Squire wrote:
> It doesn't have to parse the entire file to determine the dtypes. It
> builds up a regular expression for what it expects to see, in terms of
> dtypes. Then it just loops over the lines, only parsing if the regular
> expression doesn't match. It
On 9/2/11 9:16 AM, Christopher Jordan-Squire wrote:
>>> I agree it would make a very nice addition, and could complement my
>>> pre-allocation option for loadtxt - however there I've also been made
>>> aware that this approach breaks streamed input etc., so the buffer.resize(…)
>>> methods in accum
On 9/2/11 8:22 AM, Derek Homeier wrote:
> I agree it would make a very nice addition, and could complement my
> pre-allocation option for loadtxt - however there I've also been made
> aware that this approach breaks streamed input etc., so the buffer.resize(…)
> methods in accumulator would be the
On 8/31/11 3:58 AM, Dieter Weber wrote:
> just wanted to show an example of how python3 + numpy compares with just
> python3 and many other languages and language implementations:
> http://shootout.alioth.debian.org/u64q/performance.php?test=mandelbrot#about
hmmm - it would be interesting to see w
On 8/27/11 11:08 AM, Christopher Jordan-Squire wrote:
> I've submitted a pull request for a new method for loading data from
> text files into a record array/masked record array.
> Click on the link for more info, but the general idea is to create a
> regular expression for what entries should loo
On 8/26/11 5:04 AM, Derek Homeier wrote:
> Hmm, the pure Python version might be, but, I've used cPickle for a long time
> and never noted any stability problems.
well, here is the NEP:
https://github.com/numpy/numpy/blob/master/doc/neps/npy-format.txt
It addresses the why's and hows of the for
On 8/24/11 9:22 AM, Anthony Scopatz wrote:
> You can use Python pickling, if you do *not* have a requirement for:
I can't recall why, but it seem pickling of numpy arrays has been
fragile and not very performant.
I like the npy / npz format, built in to numpy, if you don't need:
> - acc
Simon Palmer wrote:
> "Does JSON have a representation for n-d arrays? In my little work with
> it, it looked pretty lame for arrays of number, so I'd be surprised."
>
> yes it does, thet are just treated as nested lists and the square
> bracket notation is used.
then it looks like one of str(ar
Linda Seltzer wrote:
> I would appreciate it if someone could answer my question without
> referring to subjects such as APIs and interfaces, since I am only
> concerned with a mathematical application at this time.
caution: this is a bit rude -- that was an excellent and informative
answer to yo
Bill Baxter wrote:
>import numpy as npy
Bill,
for what it's worth, I *think* this group has reached a consensus to use:
import numpy as np
We all have different tastes for how they might want to spell it, but
the more consistent we are, the easier it will be for newbies.
-Chris
--
Chri
Keith Goodman wrote:
>> Interestingly, MATLAB (v7.5.0) takes a different approach:
>> ans =
>> 1271
-A
>> ans =
>> 127 -1
can anyone explain that? -- just curious.
Charles R Harris wrote:
> We could simply define the range of int8 as [-127,127], but that is
> somewhat problematical
Could we add a "from __future__ import something" along with a
deprecation warning?
This could be used for Tim's "new matrix" class, or any other API change.
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/OR&R(206) 526-6959 voice
7600
Hi all,
I have a n X m X 3 array, and I a n X M array. I want to assign the
values in the n X m to all three of the slices in the bigger array:
A1 = np.zeros((5,4,3))
A2 = np.ones((5,4))
A1[:,:,0] = A2
A1[:,:,1] = A2
A1[:,:,2] = A2
However,it seems I should be able to broadcast that, so I don't
Travis E. Oliphant wrote:
> Stéfan van der Walt wrote:
>> 2008/4/30 Christopher Barker <[EMAIL PROTECTED]>:
>>> Since it is optional, shouldn't it be keyword argument?
>>>
>> Thanks, fixed in r5115.
>>
>>
> This was too hasty. I had considered this before.
>
> The problem with this is t
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