2011/9/20 Stéfan van der Walt :
> Hi all,
>
> Matthew Brett showed me an interesting code snippet this evening:
>
> # Construct input data
>
> In [15]: x
> Out[15]:
> array([[ 0, 1, 2],
> [ 3, 4, 5],
> [ 6, 7, 8],
> [ 9, 10, 11]])
>
> # Fancy indexing with 1D boolean array
>
Ralf, thanks for your answer.
However, in short:
I want `pip install numpy; pip install scipy` to work on OS X Lion without
extra effort :-)
On 19.09.2011, at 19:05, Ralf Gommers wrote:
> Do you think it's possible to teach numpy to use different CC, CXX?
>
>> This is possible, but numpy pro
Hi,
Stefan, which version of Python and NumPy are you using?
I am upgrading Python and NumPy, and would like to get it working on the
official releases of Python 2.7.2 + NumPy 1.6.1
In Python 2.6 + NumPy 1.5.1 on win32, it works.
In Python 2.7.2 + NumPy 1.6.1 on win32, np.frompyfunc(add,2,1).acc
On Tue, Sep 20, 2011 at 5:13 AM, Samuel John wrote:
> Ralf, thanks for your answer.
>
> However, in short:
>
> I want `pip install numpy; pip install scipy` to work on OS X Lion without
> extra effort :-)
>
>
> On 19.09.2011, at 19:05, Ralf Gommers wrote:
>> Do you think it's possible to teach n
He is using the development version of Numpy, which is probably the main
difference (I tried it too with Numpy 1.6.1 on an x86_64 Linux architecture
and got the same bug).
If you want to use an official Numpy release you'll probably need to
downgrade to 1.5.x and wait until the next Numpy release.
Understood. Thanks Olivier, Stefan.
On Tue, Sep 20, 2011 at 9:18 AM, Olivier Delalleau wrote:
> He is using the development version of Numpy, which is probably the main
> difference (I tried it too with Numpy 1.6.1 on an x86_64 Linux architecture
> and got the same bug).
> If you want to use an
Hi All,
I am extracting a list of lists from an application. In this case, my list
has 12 lists.
I then coverted each list into a numpy array. This returns 12 different
arrays. Very well. The 12 different arrays are like as follows:
[2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2
Thanks, just getting back to this. I just checked again, and after
setting my LD_LIBRARY_PATH properly, ldd shows _dotblas.so pointing
and the sunmath and sunperf libraries. However the test_03.py still
runs at about 8-9 seconds ... far too slow.
~/local/lib/python3.1/site-packages/numpy/core $ ld
Let's say your "list of lists" is called my_list, and assuming you are using
python 2.7+:
import collections
import numpy
for tmp_list in my_list:
array = numpy.array(tmp_list)
counts = collections.Counter(array)
print counts
Note that you don't even need to use numpy for that (you ca
Thanks.
There are other computations I have to do with numpy, hence the use.
Second, I am on python 2.6.
Any help?
Sent from my BlackBerry wireless device from MTN
-Original Message-
From: Olivier Delalleau
Sender: numpy-discussion-boun...@scipy.org
Date: Tue, 20 Sep 2011 09:56:45
To
What about:
>>> listoflists = [[1,1,1], [1,2,3], [2,2,2]]
>>> for eachlist in listoflists:
... print eachlist.count(1), eachlist.count(2), eachlist.count(3)
...
3 0 0
1 1 1
0 3 0
>>>
Chico
> Hi All,
>
> I am extracting a list of lists from an application. In this case, my list
> has 12 lis
Hi Chico, my list needs to be converted to a numpy array first before I do the
count. Some other calculations rely on the count and its going to be built all
on numpy.
I have tried the collections.Counter() option but in python 2.6, the module
collections has no Counter function.
Anymore sug
If you know the values that you want to count, you could just do:
(data_array == value).sum()
to find the number of times that "value" occurs in "data_array".
You could use np.unique(data_array) to find the unique values and then count
the number of occurrences of each value.
On Tue, Sep 20, 201
On Tue, Sep 20, 2011 at 10:06 AM, wrote:
> Hi Chico, my list needs to be converted to a numpy array first before I do
> the count. Some other calculations rely on the count and its going to be
> built all on numpy.
>
> I have tried the collections.Counter() option but in python 2.6, the module
Thanks Josef.
This seems like a way to go except that it is giving extra values I don't need.
For instance, it is also returning a count for 0s and as it were, I don't have
zeros at all in my list.
Second, I want a situation where, I can have a dictionary that has the figure
and number of ti
Hi all,
I've been working quite a lot with sparse vectors and sparse matrices
(basically
as feature vectors in the context of machine learning), and have noticed
that they
do crop up in a lot of places (e.g. the CVXOPT library, in scikits, ...) and
that people
tend to either reinvent the wheel (i.
data = [[1,2,1,1,4,2,1], [1,2,1,1,4,2,1,2,2,2,1,1,1],[1],[2]]
def count_dict(arr):
return dict([(x,(arr==x).sum()) for x in np.unique(arr)])
[count_dict(x) for x in data]
yields:
[{1: 4, 2: 2, 4: 1}, {1: 7, 2: 5, 4: 1}, {1: 1}, {2: 1}]
not efficient, but it works
On Tue, Sep 20, 2011 at 7:27
On Tue, Sep 20, 2011 at 10:42 AM, Yannick Versley wrote:
> Hi all,
> I've been working quite a lot with sparse vectors and sparse matrices
> (basically
> as feature vectors in the context of machine learning), and have noticed
> that they
> do crop up in a lot of places (e.g. the CVXOPT library, i
Hi!
On 20.09.2011, at 14:41, David Cournapeau wrote:
> On Tue, Sep 20, 2011 at 5:13 AM, Samuel John wrote:
>> Ralf, thanks for your answer.
>>
>> However, in short:
>>
>> I want `pip install numpy; pip install scipy` to work on OS X Lion without
>> extra effort :-)
[...]
> I will try to look
The blas implementation you are using may be slow. Here's my ldd on
_dotblas.so, that shows it is using libblas (this is on Ubuntu 11.04):
linux-vdso.so.1 => (0x7fffad5ff000)
libblas.so.3gf => /usr/lib/libblas.so.3gf (0x7fc608ea4000)
libc.so.6 => /lib/x86_64-linux-
Here's another python 2.6 version:
import itertools
import numpy
for tmp_list in my_list:
array = numpy.array(tmp_list)
counts = dict((x, len(list(c))) for x, c in
itertools.groupby(sorted(array)))
print counts
2011/9/20
> Thanks.
> There are other computations I have to do with nu
>
> This question seems like it's more relevant to the scipy mailing list,
> since scipy has scipy.sparse.
>
My point was that the current situation (i.e., people reinventing the wheel)
was a by-product of the fact that there's nothing as standardized as
numpy's ndarray or Python's buffer interface
Thanks all for the very helpful answers. These answers all appear to have
helped me in different ways especially in learning something new.
I guess I didn't ask the right question after all.
What I really want is a way to loop through individual arrays of the 12
arrays that I have.
Here are my s
I keep getting this error: #warning "Using deprecated NumPy
API, disable it by #defining NPY_NO_DEPRECATED_API" and a bunch of
undefined variables when comping cython code with numpy
I am new to cython and numpy and I am having trouble getting a *.pyx extension
to compile with this in the header:
On Tue, Sep 20, 2011 at 12:43 AM, Robert Kern wrote:
> If the array is short in a dimension, it gets implicitly continued
> with Falses. You can see this in one dimension:
[...]
> I honestly don't know if this is documented or tested anywhere or even
> if this existed in older versions.
The beh
2011/9/20 DIPO ELEGBEDE
> 3. Get each array one after the other and work with it. (This is where the
> problem is).
>
> How can I fetch out array1, then array2 then array3 up to array12?
>
> Is it possible to slice?
>
>
Not really sure what your problem is, but since you should have now a list
of
Olivier, the code you sent did so much magic and I'm definitely using that.
What baffles me is that looping through the 12 arrays seem impossible.
I have tried what you just sent but it won't just work.
You could confirm this.
Sent from my BlackBerry wireless device from MTN
-Original Mess
Can you please provide your current code, even if incomplete / not working?
It's hard to tell what's wrong without looking at the code.
-=- Olivier
2011/9/20
> Olivier, the code you sent did so much magic and I'm definitely using that.
> What baffles me is that looping through the 12 arrays see
I think that should sort it.
def p(option_lists):
for option_list in option_lists:
array = numpy.array(option_list)
for i in array: print i
the option_lists here is the list of lists
looping through it and then converting it into a numpy array is quiet easy.
If I try to loop
I'm trying to understand what you want to do, but I'm afraid it's still not
clear, so I'm sorry if that reply doesn't help either.
It looks to me as if you first want to convert your list of lists into a
list of arrays, then iterate through this list of arrays.
If that's it, then you can just do:
On Tue, Sep 20, 2011 at 9:56 AM, David Cottrell
wrote:
> Thanks, just getting back to this. I just checked again, and after
> setting my LD_LIBRARY_PATH properly, ldd shows _dotblas.so pointing
> and the sunmath and sunperf libraries. However the test_03.py still
> runs at about 8-9 seconds ... fa
The test_03.py was basically a linalg.svd test (which I think is a
linalg only routine?"). I guess for linalg checking, I should run ldd
on lapack_lite.so? (included below).
It's sounding like I need to get ATLAS up and running, but I'm still
puzzled as to why the svd routine seems to be so much s
On Tue, Sep 20, 2011 at 3:18 PM, David Cottrell
wrote:
> The test_03.py was basically a linalg.svd test (which I think is a
> linalg only routine?"). I guess for linalg checking, I should run ldd
> on lapack_lite.so? (included below).
>
> It's sounding like I need to get ATLAS up and running, but
On Tue, Sep 20, 2011 at 1:18 PM, David Cournapeau wrote:
> On Tue, Sep 20, 2011 at 9:56 AM, David Cottrell
> wrote:
>> Thanks, just getting back to this. I just checked again, and after
>> setting my LD_LIBRARY_PATH properly, ldd shows _dotblas.so pointing
>> and the sunmath and sunperf libraries
Yannick
Sounds great. Would cross-post on the Scipy list as that is where the
scipy.sparse developers hang out.
Dinesh
From: Yannick Versley
Sent: Tuesday, September 20, 2011 8:33 AM
To: Discussion of Numerical Python
Subject: Re: [Numpy-discussion] sparse vectors / matrices / tensors
Th
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