Re: [Numpy-discussion] minimal numpy ?

Hi Robert, Robert wrote: > for use in binary distribution where I need only basics and fast > startup/low memory footprint, I try to isolate the minimal ndarray > type and what I need.. > > with "import numpy" or "import numpy.core.multiarray" almost the > whole numpy package tree is imported,

Re: [Numpy-discussion] How to include numpy headers in C across versions 1.1, 1.2, and 1.3

Charles R Harris wrote: > > > On Mon, May 11, 2009 at 4:49 PM, Peter Wang > wrote: > > Hey guys, > > I've got a small C extension that uses isnan() and (in numpy 1.1) had > been importing it from ufuncobject.h. I see that it has now moved > into npy_mat

Re: [Numpy-discussion] How to include numpy headers in C across versions 1.1, 1.2, and 1.3

On Mon, May 11, 2009 at 4:49 PM, Peter Wang wrote: > Hey guys, > > I've got a small C extension that uses isnan() and (in numpy 1.1) had > been importing it from ufuncobject.h. I see that it has now moved > into npy_math.h in 1.3. > > What is the best way to ensure that I can reliably include th

Re: [Numpy-discussion] How to merge or SQL join record arrays in Python?

On May 11, 2009, at 6:36 PM, Skipper Seabold wrote: > On Mon, May 11, 2009 at 6:18 PM, Wei Su wrote: >> >> Hi, Pierre: >> >> Thanks for the reply. I can now actually turn a big list into a >> record >> array. My question is actually how to join related record arrays in >> Python.. >> This is

[Numpy-discussion] How to include numpy headers in C across versions 1.1, 1.2, and 1.3

Hey guys, I've got a small C extension that uses isnan() and (in numpy 1.1) had been importing it from ufuncobject.h. I see that it has now moved into npy_math.h in 1.3. What is the best way to ensure that I can reliably include this function across versions 1.1, 1.2, and 1.3? (Checking

Re: [Numpy-discussion] How to merge or SQL join record arrays in Python?

On Mon, May 11, 2009 at 6:18 PM, Wei Su wrote: > > Hi, Pierre: > > Thanks for the reply. I can now actually turn a big list into a record > array. My question is actually how to join related record arrays in Python.. > This is done in SAS by MERGE and PROC SQL and by merge() in R. But I have no >

Re: [Numpy-discussion] How to merge or SQL join record arrays in Python?

On May 11, 2009, at 6:18 PM, Wei Su wrote: > > Thanks for the reply. I can now actually turn a big list into a > record array. My question is actually how to join related record > arrays in Python.. This is done in SAS by MERGE and PROC SQL and by > merge() in R. But I have no idea how to do

[Numpy-discussion] minimal numpy ?

for use in binary distribution where I need only basics and fast startup/low memory footprint, I try to isolate the minimal ndarray type and what I need.. with "import numpy" or "import numpy.core.multiarray" almost the whole numpy package tree is imported, _dotblas etc. cxFreeze produces some

Re: [Numpy-discussion] How to merge or SQL join record arrays in Python?

  Hi, Pierre:   Thanks for the reply. I can now actually turn a big list into a record array. My question is actually how to join related record arrays in Python. This is done in SAS by MERGE and PROC SQL and by merge() in R. But I have no idea how to do it in Python.   Thanks.   Wei Su --- On

Re: [Numpy-discussion] How to merge or SQL join record arrays in Python?

On May 11, 2009, at 5:44 PM, Wei Su wrote: > > Coming from SAS and R, this is probably the first thing I want to do > now that I can convert my data into record arrays. But I could not > find any clues after googling for a while. Any hint or suggestions > will be great! That depends what yo

Re: [Numpy-discussion] List of arrays

Wei Su wrote: > The codes do not work. Guess you forgot something there. l wasn't defined: In [16]: a = np.arange(10) In [17]: b = np.arange(5) In [20]: l = [a,b] In [21]: l Out[21]: [array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4])] In [22]: np.concatenate(l) Out[22]: array([0,

[Numpy-discussion] How to merge or SQL join record arrays in Python?

    Hi, All,   Coming from SAS and R, this is probably the first thing I want to do now that I can convert my data into record arrays. But I could not find any clues after googling for a while. Any hint or suggestions will be great!   Thanks a lot.   Wei Su ___

Re: [Numpy-discussion] List of arrays

Hi, Francesc:   The codes do not work. Guess you forgot something there.   Thanks.   Wei Su --- On Mon, 5/11/09, Francesc Alted wrote: From: Francesc Alted Subject: Re: [Numpy-discussion] List of arrays To: "Discussion of Numerical Python" Date: Monday, May 11, 2009, 10:40 AM A Monday 11 M

Re: [Numpy-discussion] strange behavior convolving via fft

Thanks Stefan. 2009/5/11 Stéfan van der Walt > 2009/5/11 Chris Colbert : > > Does the scipy implementation do this differently? I thought that since > FFTW > > support has been dropped, that scipy and numpy use the same routines... > > Just to be clear, I was referring to scipy.signal.fftconvolv

Re: [Numpy-discussion] strange behavior convolving via fft

2009/5/11 Chris Colbert : > Does the scipy implementation do this differently? I thought that since FFTW > support has been dropped, that scipy and numpy use the same routines... Just to be clear, I was referring to scipy.signal.fftconvolve, not scipy's FFT (which is the same as NumPy's). Regards

Re: [Numpy-discussion] strange behavior convolving via fft

Hi Chris, If you have MxN and PxQ signals, you must pad them to shape M+P-1 x N+Q-1, in order to prevent circular convolution (i.e. values on the one end sliding back in at the other). Regards Stéfan 2009/5/11 Chris Colbert : > Stefan, > > Did I pad my example incorrectly? Both images were upped

Re: [Numpy-discussion] strange behavior convolving via fft

Stefan, Did I pad my example incorrectly? Both images were upped to the larger nearest power of 2 (256)... Does the scipy implementation do this differently? I thought that since FFTW support has been dropped, that scipy and numpy use the same routines... Thanks! Chris 2009/5/11 Stéfan van der

Re: [Numpy-discussion] strange behavior convolving via fft

Hi Chris 2009/5/11 Chris Colbert : > When convolving an image with a large kernel, its know that its faster to > perform the operation as multiplication in the frequency domain. The below > code example shows that the results of my 2d filtering are shifted from the > expected value a distance 1/2

Re: [Numpy-discussion] strange behavior convolving via fft

Ok, that makes sense. Thanks Chuck. On Mon, May 11, 2009 at 2:41 PM, Charles R Harris wrote: > > > On Mon, May 11, 2009 at 9:40 AM, Chris Colbert wrote: > >> at least I think this is strange behavior. >> >> When convolving an image with a large kernel, its know that its faster to >> perform t

Re: [Numpy-discussion] strange behavior convolving via fft

On Mon, May 11, 2009 at 9:40 AM, Chris Colbert wrote: > at least I think this is strange behavior. > > When convolving an image with a large kernel, its know that its faster to > perform the operation as multiplication in the frequency domain. The below > code example shows that the results of my

Re: [Numpy-discussion] OS-X binary name...

David Cournapeau wrote: > On Wed, May 6, 2009 at 3:03 PM, Christopher Barker >> The binary for OS-X on sourceforge is called: >> >> numpy-1.3.0-py2.5-macosx10.5.dmg >> >> However, as far as I can tell, it works just fine on OS-X 10.4, and >> maybe even 10.3.9. > > I have to confess I don't underst

[Numpy-discussion] strange behavior convolving via fft

at least I think this is strange behavior. When convolving an image with a large kernel, its know that its faster to perform the operation as multiplication in the frequency domain. The below code example shows that the results of my 2d filtering are shifted from the expected value a distance 1/2

Re: [Numpy-discussion] String manipulation

On 5/11/2009 8:36 AM Nils Wagner apparently wrote: > I would like to split strings made of digits after eight > characters each. [l[i*8:(i+1)*8] for i in range(len(l)/8)] Alan Isaac ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://

Re: [Numpy-discussion] FAIL: Test bug in reduceat with structured arrays

Mon, 11 May 2009 16:22:37 +0200, Nils Wagner kirjoitti: > On Mon, 11 May 2009 14:05:13 + (UTC) > Pauli Virtanen wrote: >> Mon, 11 May 2009 14:06:07 +0200, Nils Wagner kirjoitti: >>> Can someone reproduce the following failure ? I am using >> numpy.__version__ >>> '1.4.0.dev6983' >>> >>

Re: [Numpy-discussion] String manipulation

On 5/11/2009 8:03 AM Nils Wagner apparently wrote: line_a > '12345678abcdefgh12345678' > Is it possible to split line_a such that the output > is > > ['12345678', 'abcdefgh', '12345678'] More of a comp.lang.python question, I think: out = list() for k, g in groupby('123abc456',lambda x: x.

Re: [Numpy-discussion] FAIL: Test bug in reduceat with structured arrays

On Mon, 11 May 2009 14:05:13 + (UTC) Pauli Virtanen wrote: > Mon, 11 May 2009 14:06:07 +0200, Nils Wagner kirjoitti: >> Can someone reproduce the following failure ? I am using > numpy.__version__ >> '1.4.0.dev6983' >> >> =

Re: [Numpy-discussion] String manipulation

hi, > here is my workaround. > > from numpy import arange > line_a = '11.122.233.3' # without > separator > line_b = '11.1 22.2 33.3' # including space > as a delimiter > > div, mod = divmod(len(line_a),8) > liste = [] > for j in arange(0,div): > liste.append(li

Re: [Numpy-discussion] FAIL: Test bug in reduceat with structured arrays

Mon, 11 May 2009 14:06:07 +0200, Nils Wagner kirjoitti: > Can someone reproduce the following failure ? I am using numpy.__version__ > '1.4.0.dev6983' > > == > FAIL: Test bug in reduceat with structured arrays copied for spee

Re: [Numpy-discussion] String manipulation

On Mon, 11 May 2009 15:03:02 +0200 Sebastien Binet wrote: > On Monday 11 May 2009 14:36:17 Nils Wagner wrote: >> On Mon, 11 May 2009 14:25:46 +0200 >> >> Francesc Alted wrote: >> > A Monday 11 May 2009, Nils Wagner escrigué: >> >> Hi all, >> >> >> >> Please consider two strings >> >> >> >> >>

Re: [Numpy-discussion] String manipulation

On Monday 11 May 2009 14:36:17 Nils Wagner wrote: > On Mon, 11 May 2009 14:25:46 +0200 > > Francesc Alted wrote: > > A Monday 11 May 2009, Nils Wagner escrigué: > >> Hi all, > >> > >> Please consider two strings > >> > >> >>> line_a > >> > >> '12345678abcdefgh12345678' > >> > >> >>> line_b > >>

Re: [Numpy-discussion] String manipulation

On Mon, 11 May 2009 14:25:46 +0200 Francesc Alted wrote: > A Monday 11 May 2009, Nils Wagner escrigué: >> Hi all, >> >> Please consider two strings >> >> >>> line_a >> >> '12345678abcdefgh12345678' >> >> >>> line_b >> >> '12345678 abcdefgh 12345678' >> >> >>> line_b.split() >> >> ['12345678', 'a

Re: [Numpy-discussion] String manipulation

A Monday 11 May 2009, Francesc Alted escrigué: > Although regular expressions seems a bit thought to learn, they will ^^^ --> tough :-\ -- Francesc Alted "One would expect people to feel threatened by the 'giant brains or machines that think'. In

Re: [Numpy-discussion] String manipulation

A Monday 11 May 2009, Nils Wagner escrigué: > Hi all, > > Please consider two strings > > >>> line_a > > '12345678abcdefgh12345678' > > >>> line_b > > '12345678 abcdefgh 12345678' > > >>> line_b.split() > > ['12345678', 'abcdefgh', '12345678'] > > Is it possible to split line_a such that the output

[Numpy-discussion] FAIL: Test bug in reduceat with structured arrays

Hi all, Can someone reproduce the following failure ? I am using >>> numpy.__version__ '1.4.0.dev6983' == FAIL: Test bug in reduceat with structured arrays copied for speed. --

[Numpy-discussion] String manipulation

Hi all, Please consider two strings >>> line_a '12345678abcdefgh12345678' >>> line_b '12345678 abcdefgh 12345678' >>> line_b.split() ['12345678', 'abcdefgh', '12345678'] Is it possible to split line_a such that the output is ['12345678', 'abcdefgh', '12345678'] Nils

Re: [Numpy-discussion] List of arrays

On Mon, 11 May 2009 06:54:45 -0400 Alan G Isaac wrote: > On 5/11/2009 6:28 AM Nils Wagner apparently wrote: >> How can I convert a list of arrays into one array ? > > Do you mean one long array, so that ``concatenate`` > is appropriate, or a 2d array, in which case you > can just use ``array``.

Re: [Numpy-discussion] List of arrays

On 5/11/2009 6:28 AM Nils Wagner apparently wrote: > How can I convert a list of arrays into one array ? Do you mean one long array, so that ``concatenate`` is appropriate, or a 2d array, in which case you can just use ``array``. But your example looks like you should preallocate the larger array

Re: [Numpy-discussion] List of arrays

A Monday 11 May 2009, Nils Wagner escrigué: > Hi all, > > How can I convert a list of arrays into one array ? > > Nils > > >>> data > > [array([ 40. , 285.6, 45. , 285.3, 50. , 285.1, > 55. , 284.8]), array([ 60. , 284.5, 65. , 282.8, > 70. , 281.1, 75. , 280. ]), array([ 80.

[Numpy-discussion] List of arrays

Hi all, How can I convert a list of arrays into one array ? Nils >>> data [array([ 40. , 285.6, 45. , 285.3, 50. , 285.1, 55. , 284.8]), array([ 60. , 284.5, 65. , 282.8, 70. , 281.1, 75. , 280. ]), array([ 80. , 278.8, 85. , 278.1, 90. , 277.4, 95. , 276.9]