[Numpy-discussion] Unwanted upcast from uint64 to float64
I'm using windows datetimes (100nano-seconds since 0001,1,1) as time in a numpy array and was hit by this behaviour. >>> numpy.__version__ '1.0b4' >>> a=numpy.array([63292539433000L],numpy.uint64) >>> t=a[0] >>> t 63292539433000L >>> type(t) >>> t+1 6.3292539433e+017 >>> type(t+1) >>> t==(t+1) True I was trying to set t larger than any time in an array. Is there any reason for the scalar to upcast in this case? //Torgil - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] upcast
> To answer the original question, you need to use a higher precision > array or explicitly cast it to higher precision. > > In [49]:(a.astype(int)*100)/100 > Out[49]:array([200]) Thank you. This is what I wanted to know. Lars - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Use of numarray from numpy package [# INC NO 24609]
Andrew Straw wrote:
> LANDRIU David SAp wrote:
>> Hello,
>>
>> I come back to my question : how to use numarray
>> with the numpy installation ?
>>
>> {ccali22}~(0)>setenv PYTHONPATH /usr/local/lib/python2.3/site-packages/numpy
>>
> Here's where you went wrong. You want:
>
> setenv PYTHONPATH /usr/local/lib/python2.3/site-packages
>
>> {ccali22}~(0)>python
>> Python 2.3.5 (#2, Oct 17 2005, 17:20:02)
>> [GCC 3.2.3 20030502 (Red Hat Linux 3.2.3-52)] on linux2
>> Type "help", "copyright", "credits" or "license" for more information.
>>
> from numarray import *
>
>> Traceback (most recent call last):
>> File "", line 1, in ?
>> File "/usr/local/lib/python2.3/site-packages/numpy/numarray/__init__.py",
>> line 1, in ?
>> from util import *
>> File "/usr/local/lib/python2.3/site-packages/numpy/numarray/util.py", line
>> 2, in ?
>> from numpy import geterr
>> ImportError: No module named numpy
>>
>
> Note that you're actually importing a numarray within numpy's directory
> structure. That's because of your PYTHONPATH. numpy ships numpy.numarray
> to provide backwards compatibility. To use it, you must do "import
> numpy.numarray as numarray"
>
Just to explain -- there is only a numarray directory inside numpy
to provide some special treatment for people that do the transition from
numarray to numpy - meaning: they can do somthing like
from numpy import numarray
and get a "numpy(!) version" that behaves more like numarray than the
straight numpy ...
Similar for
"from numarray import oldnumaric as Numeric" (for people coming from
Numeric )
Yes - it is actually confusing, but that's the baggage when there are 2
(now 3) numerical python packages is human history.
The future will be much brighter - forget all of the above, and just use
import numpy
(I like "import numpy as N" for less typing - others prefer even
"from numpy import *"
)
Hope that helps,
- Sebastian Haase
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Re: [Numpy-discussion] amd64 support
Keith Goodman wrote: > I plan to build an amd64 box and run debian etch. Are there any big, > 64-bit, show-stopping problems in numpy? Any minor annoyances? > I am not aware of any - we use fine on 32bit and 64bit with debian sarge and etch. -Sebastian Haase - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] upcast
On 8/30/06, Lars Friedrich <[EMAIL PROTECTED]> wrote: Hello,I would like to discuss the following code:#***start***import numpy as Na = N.array((200), dtype = N.uint8)print (a * 100) / 100b = N.array((200, 200), dtype = N.uint8)print (b * 100) / 100 #***stop***The first print statement will print "200" because the uint8-value iscast "upwards", I suppose. The second statement prints "[0 0]". Isuppose this is due to overflows during the calculation. How can I tell numpy to do the upcast also in the second case, returning"[200 200]"? I am interested in the fastest solution regarding executiontime. In my application I would like to store the result in an Numeric.UInt8-array.Thanks for every commentTo answer the original question, you need to use a higher precision array or explicitly cast it to higher precision.In [49]:(a.astype(int)*100)/100 Out[49]:array([200]) Chuck - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] upcast
On 8/30/06, Lars Friedrich <[EMAIL PROTECTED]> wrote: Hello,I would like to discuss the following code:#***start***import numpy as Na = N.array((200), dtype = N.uint8)print (a * 100) / 100This is actually a scalar, i.e., a zero dimensional array. N.uint8(200) would give you the same thing, because (200) is a number, not a tuple like (200,). In any caseIn [44]:a = array([200], dtype=uint8)In [45]:a*100Out[45]:array([32], dtype=uint8)In [46]:uint8(100)*100 Out[46]:1i.e. , the array arithmetic is carried out in mod 256 because Numpy keeps the array type when multiplying by scalars. On the other hand, when multiplying a *scalar* by a number, the lower precision scalars are upconverted in the conventional way. Numpy makes the choices it does for space efficiency. If you want to work in uint8 you don't have to recast every time you multiply by a small integer. I suppose one could demand using uint8(1) instead of 1, but the latter is more convenient. Integers can be tricky once the ordinary precision is exceeded and modular arithmetic takes over, it just happens more easily for uint8 than for uint32.Chuck - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Changing Fatal error into ImportError?
On 8/30/06, Robert Kern <[EMAIL PROTECTED]> wrote: > I don't see where we're calling Py_FatalError. The problem might be in Python > or > mwadap. Indeed, import_array() raises a PyExc_ImportError. Sorry for the noise: it looks like this was already fixed: http://projects.scipy.org/scipy/numpy/changeset/3044 since the code causing problems had been built /before/ 3044, we got the FatalError. But with modules built post-3044, it's all good (I artificially hacked the number to force the error): In [1]: import mwadap Overwriting info= from scipy.misc (was from numpy.lib.utils) --- exceptions.RuntimeError Traceback (most recent call last) RuntimeError: module compiled against version 101 of C-API but this version of numpy is 102 --- exceptions.ImportError Traceback (most recent call last) /home/fperez/research/code/mwadap-merge/mwadap/test/ /home/fperez/usr/lib/python2.3/site-packages/mwadap/__init__.py 9 glob,loc = globals(),locals() 10 for name in __all__: ---> 11 __import__(name,glob,loc,[]) 12 13 # Namespace cleanup /home/fperez/usr/lib/python2.3/site-packages/mwadap/Operator.py 18 19 # Our own packages ---> 20 import mwrep 21 from mwadap import mwqmfl, utils, Function, flinalg 22 ImportError: numpy.core.multiarray failed to import In [2]: Cheers, f - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Changing Fatal error into ImportError?
Fernando Perez wrote: > Hi all, > > this was mentioned in the past, but I think it fell through the cracks: > > Python 2.3.4 (#1, Mar 10 2006, 06:12:09) > [GCC 3.4.5 20051201 (Red Hat 3.4.5-2)] on linux2 > Type "help", "copyright", "credits" or "license" for more information. > >>> import mwadap > Overwriting info= from scipy.misc (was > from numpy.lib.utils) > RuntimeError: module compiled against version 90909 of C-API but this > version of numpy is 102 > Fatal Python error: numpy.core.multiarray failed to import... exiting. > > I really think that this should raise ImportError, but NOT kill the > python interpreter. If this happens in the middle of a long-running > interactive session, you'll lose all of your current state/work, where > a simple ImportError would have been enough to tell you that this > particular module needed recompilation. > > FatalError should be reserved for situations where the internal state > of the Python VM itself can not realistically be expected to be sane > (corruption, complete memory exhaustion for even internal allocations, > etc.) But killing the user's session for a failed import is a bit > much, IMHO. I don't see where we're calling Py_FatalError. The problem might be in Python or mwadap. Indeed, import_array() raises a PyExc_ImportError. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
[Numpy-discussion] Changing Fatal error into ImportError?
Hi all, this was mentioned in the past, but I think it fell through the cracks: Python 2.3.4 (#1, Mar 10 2006, 06:12:09) [GCC 3.4.5 20051201 (Red Hat 3.4.5-2)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import mwadap Overwriting info= from scipy.misc (was from numpy.lib.utils) RuntimeError: module compiled against version 90909 of C-API but this version of numpy is 102 Fatal Python error: numpy.core.multiarray failed to import... exiting. I really think that this should raise ImportError, but NOT kill the python interpreter. If this happens in the middle of a long-running interactive session, you'll lose all of your current state/work, where a simple ImportError would have been enough to tell you that this particular module needed recompilation. FatalError should be reserved for situations where the internal state of the Python VM itself can not realistically be expected to be sane (corruption, complete memory exhaustion for even internal allocations, etc.) But killing the user's session for a failed import is a bit much, IMHO. Cheers, f - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] stumped numpy user seeks help
On 8/30/06, Sven Schreiber <[EMAIL PROTECTED]> wrote: > Mathew Yeates schrieb: > will be a numpy matrix, use if you don't like that. But here > it's really nice to work with matrices, because otherwise .sum() will > give you a 1-d array sometimes, and that will suddenly look like a row > to (instead of a nice column vector) and wouldn't work -- > that's why matrices are so great and everybody should be using them ;-) column_stack would work perfectly in place of hstack there if it only didn't have the silly behavior of transposing arguments that already are 2-d. For reminders, here's the replacement implementation of column_stack I proposed on July 21: def column_stack(tup): def transpose_1d(array): if array.ndim<2: return _nx.transpose(atleast_2d(array)) else: return array arrays = map(transpose_1d,map(atleast_1d,tup)) return _nx.concatenate(arrays,1) This was in a big ticket I submitted about overhauling r_,c_,etc, which was largely ignored. Maybe I should resubmit this by itself... --bb - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
[Numpy-discussion] (no subject)
Hi, currently I´m trying to compile the latest numpy version (1.0b4) under an SGI IRIX 6.5 environment. I´m using the gcc 3.4.6 compiler and python 2.4.3 (self compiled). During the compilation of numpy.core I get a nasty error message: ... copying build/src.irix64-6.5-2.4/numpy/__config__.py -> build/lib.irix64-6.5-2.4/numpy copying build/src.irix64-6.5-2.4/numpy/distutils/__config__.py -> build/lib.irix64-6.5-2.4/numpy/distutils running build_ext customize UnixCCompiler customize UnixCCompiler using build_ext customize MipsFCompiler customize MipsFCompiler customize MipsFCompiler using build_ext building 'numpy.core.umath' extension compiling C sources C compiler: gcc -fno-strict-aliasing -DNDEBUG -D_FILE_OFFSET_BITS=64 -DHAVE_LARGEFILE_SUPPORT -fmessage-length=0 -Wall -O2 compile options: '-Ibuild/src.irix64-6.5-2.4/numpy/core/src -Inumpy/core/include -Ibuild/src.irix64-6.5-2.4/numpy/core -Inumpy/core/src -Inumpy/core/include -I/usr/local/include/python2.4 -c' gcc: build/src.irix64-6.5-2.4/numpy/core/src/umathmodule.c numpy/core/src/umathmodule.c.src: In function `nc_sqrtf': numpy/core/src/umathmodule.c.src:602: warning: implicit declaration of function `hypotf' numpy/core/src/umathmodule.c.src: In function `nc_sqrtl': numpy/core/src/umathmodule.c.src:602: warning: implicit declaration of function `fabsl' ... ... lots of math functions ... ... numpy/core/src/umathmodule.c.src: In function `LONGDOUBLE_frexp': numpy/core/src/umathmodule.c.src:1940: warning: implicit declaration of function `frexpl' numpy/core/src/umathmodule.c.src: In function `LONGDOUBLE_ldexp': numpy/core/src/umathmodule.c.src:1957: warning: implicit declaration of function `ldexpl' In file included from numpy/core/src/umathmodule.c.src:2011: build/src.irix64-6.5-2.4/numpy/core/__umath_generated.c: At top level: build/src.irix64-6.5-2.4/numpy/core/__umath_generated.c:15: error: `acosl' undeclared here (not in a function) build/src.irix64-6.5-2.4/numpy/core/__umath_generated.c:15: error: initializer element is not constant build/src.irix64-6.5-2.4/numpy/core/__umath_generated.c:15: error: (near initialization for `arccos_data[2]') ... ... lots of math functions ... ... build/src.irix64-6.5-2.4/numpy/core/__umath_generated.c:192: error: initializer element is not constant build/src.irix64-6.5-2.4/numpy/core/__umath_generated.c:192: error: (near initialization for `tanh_data[2]') numpy/core/include/numpy/ufuncobject.h:328: warning: 'generate_overflow_error' defined but not used numpy/core/src/umathmodule.c.src: In function `nc_sqrtf': numpy/core/src/umathmodule.c.src:602: warning: implicit declaration of function `hypotf' ... ... lots of math functions ... ... numpy/core/src/umathmodule.c.src: In function `FLOAT_frexp': numpy/core/src/umathmodule.c.src:1940: warning: implicit declaration of function `frexpf' numpy/core/src/umathmodule.c.src: In function `FLOAT_ldexp': numpy/core/src/umathmodule.c.src:1957: warning: implicit declaration of function `ldexpf' numpy/core/src/umathmodule.c.src: In function `LONGDOUBLE_frexp': numpy/core/src/umathmodule.c.src:1940: warning: implicit declaration of function `frexpl' numpy/core/src/umathmodule.c.src: In function `LONGDOUBLE_ldexp': numpy/core/src/umathmodule.c.src:1957: warning: implicit declaration of function `ldexpl' In file included from numpy/core/src/umathmodule.c.src:2011: build/src.irix64-6.5-2.4/numpy/core/__umath_generated.c: At top level: build/src.irix64-6.5-2.4/numpy/core/__umath_generated.c:15: error: `acosl' undeclared here (not in a function) build/src.irix64-6.5-2.4/numpy/core/__umath_generated.c:15: error: initializer element is not constant ... ... lots of math functions ... ... build/src.irix64-6.5-2.4/numpy/core/__umath_generated.c:192: error: initializer element is not constant build/src.irix64-6.5-2.4/numpy/core/__umath_generated.c:192: error: (near initialization for `tanh_data[2]') numpy/core/include/numpy/ufuncobject.h:328: warning: 'generate_overflow_error' defined but not used error: Command "gcc -fno-strict-aliasing -DNDEBUG -D_FILE_OFFSET_BITS=64 -DHAVE_LARGEFILE_SUPPORT -fmessage-length=0 -Wall -O2 -Ibuild/src.irix64-6.5-2.4/numpy/core/src -Inumpy/core/include -Ibuild/src.irix64-6.5-2.4/numpy/core -Inumpy/core/src -Inumpy/core/include -I/usr/local/include/python2.4 -c build/src.irix64-6.5-2.4/numpy/core/src/umathmodule.c -o build/temp.irix64-6.5-2.4/build/src.irix64-6.5-2.4/numpy/core/src/umathmodule.o" failed with exit status 1 Can somebody explain me, what´s going wrong. It seems there is some header files missing. thanks, thilo -- Der GMX SmartSurfer hilft bis zu 70% Ihrer Onlinekosten zu sparen! Ideal für Modem und ISDN: http://www.gmx.net/de/go/smartsurfer - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server
Re: [Numpy-discussion] Interfacing with PIL?
Tim Hochberg wrote:
> Johannes Loehnert wrote:
>>> I'm somewhat new to both libraries...is there any way to create a 2D
>>> array of pixel values from an image object from the Python Image
>>> Library? I'd like to do some arithmetic on the values.
the latest version of PIL (maybe not released yet) supports the array
interface, so you may be able to do something like:
A = numpy.asarray(PIL_image)
see the PIL page:
http://effbot.org/zone/pil-changes-116.htm
where it says:
Changes from release 1.1.5 to 1.1.6
Added "fromarray" function, which takes an object implementing the NumPy
array interface and creates a PIL Image from it. (from Travis Oliphant).
Added NumPy array interface support (__array_interface__) to the Image
class (based on code by Travis Oliphant). This allows you to easily
convert between PIL image memories and NumPy arrays:
import numpy, Image
i = Image.open('lena.jpg')
a = numpy.asarray(i) # a is readonly
i = Image.fromarray(a)
> On a related note, does anyone have a good recipe for converting a PIL
> image to a wxPython image?
Does a PIL image support the buffer protocol? There will be a:
wx.ImageFromBuffer()
soon, and there is now;
wx.Image.SetDataBuffer()
if not, I think this will work:
I = wx.EmptyImage(width, height)
DataString = PIL_image.tostring()
I.SetDataBuffer(DataString)
This will only work if the PIL image is an 24 bit RGB image, of course.
Just make sure to keep DataString around, so that the data buffer
doesn't get deleted. wx.ImageFromBuffer() will do that foryou, but it's
not available until 2.7 comes out.
Ideally, both PIL and wx will support the array interface, and we can
just do:
I = wx.ImageFromArray(PIL_Image)
and not get any data copying as well.
Also, Robin has just added some methods to directly manipulate
wxBitmaps, so you can use a numpy array as the data buffer for a
wx.Bitmap. This can help prevent a lot of data copies. see a test here:
http://cvs.wxwidgets.org/viewcvs.cgi/wxWidgets/wxPython/demo/RawBitmapAccess.py?rev=1.3&content-type=text/vnd.viewcvs-markup
-Chris
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Re: [Numpy-discussion] Interfacing with PIL?
Johannes Loehnert wrote: > Am Mittwoch, 30. August 2006 19:20 schrieb Ghalib Suleiman: > >> I'm somewhat new to both libraries...is there any way to create a 2D >> array of pixel values from an image object from the Python Image >> Library? I'd like to do some arithmetic on the values. >> > > Yes. > > To transport the data: > import numpy image = arr = numpy.fromstring(image.tostring(), dtype=numpy.uint8) > > (alternately use dtype=numpy.uint32 if you want RGBA packed in one number). > > arr will be a 1d array with length (height * width * b(ytes)pp). Use reshape > to get it into a reasonable form. > On a related note, does anyone have a good recipe for converting a PIL image to a wxPython image? The last time I tried this, the best I could come up with was: stream = cStringIO.StringIO() img.save(stream, "png") # img is PIL Image stream.seek(0) image = wx.ImageFromStream(stream) # image is a wxPython Image -tim - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Interfacing with PIL?
Am Mittwoch, 30. August 2006 19:20 schrieb Ghalib Suleiman: > I'm somewhat new to both libraries...is there any way to create a 2D > array of pixel values from an image object from the Python Image > Library? I'd like to do some arithmetic on the values. Yes. To transport the data: >>> import numpy >>> image = >>> arr = numpy.fromstring(image.tostring(), dtype=numpy.uint8) (alternately use dtype=numpy.uint32 if you want RGBA packed in one number). arr will be a 1d array with length (height * width * b(ytes)pp). Use reshape to get it into a reasonable form. HTH, Johannes - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
[Numpy-discussion] Interfacing with PIL?
I'm somewhat new to both libraries...is there any way to create a 2D array of pixel values from an image object from the Python Image Library? I'd like to do some arithmetic on the values. - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Use of numarray from numpy package [# INC NO 24609]
Andrew Straw wrote:
>> {ccali22}~(0)>setenv PYTHONPATH /usr/local/lib/python2.3/site-packages/numpy
>>
> Here's where you went wrong. You want:
>
> setenv PYTHONPATH /usr/local/lib/python2.3/site-packages
Which you shouldn't need at all. site-packages should be on sys.path by
default.
-Chris
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[Numpy-discussion] upcast
Hello, I would like to discuss the following code: #***start*** import numpy as N a = N.array((200), dtype = N.uint8) print (a * 100) / 100 b = N.array((200, 200), dtype = N.uint8) print (b * 100) / 100 #***stop*** The first print statement will print "200" because the uint8-value is cast "upwards", I suppose. The second statement prints "[0 0]". I suppose this is due to overflows during the calculation. How can I tell numpy to do the upcast also in the second case, returning "[200 200]"? I am interested in the fastest solution regarding execution time. In my application I would like to store the result in an Numeric.UInt8-array. Thanks for every comment Lars - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] fftfreq very slow; rfftfreq incorrect?
On Wed, Aug 30, 2006 at 12:04:22PM +0100, Andrew Jaffe wrote:
> the current implementation of fftfreq (which is meant to return the
> appropriate frequencies for an FFT) does the following:
>
> k = range(0,(n-1)/2+1)+range(-(n/2),0)
> return array(k,'d')/(n*d)
>
> I have tried this with very long (2**24) arrays, and it is ridiculously
> slow. Should this instead use arange (or linspace?) and concatenate
> rather than converting the above list? This seems to result in
> acceptable performance, but we could also perhaps even pre-allocate the
> space.
Please try the attached benchmark.
> The numpy.fft.rfftfreq seems just plain incorrect to me. It seems to
> produce lots of duplicated frequencies, contrary to the actual output of
> rfft:
>
> def rfftfreq(n,d=1.0):
> """ rfftfreq(n, d=1.0) -> f
>
> DFT sample frequencies (for usage with rfft,irfft).
>
> The returned float array contains the frequency bins in
> cycles/unit (with zero at the start) given a window length n and a
> sample spacing d:
>
>f = [0,1,1,2,2,...,n/2-1,n/2-1,n/2]/(d*n) if n is even
>f = [0,1,1,2,2,...,n/2-1,n/2-1,n/2,n/2]/(d*n) if n is odd
>
> None of these should be doubled, right?
>
> """
> assert isinstance(n,int)
> return array(range(1,n+1),dtype=int)/2/float(n*d)
Please produce a code snippet to demonstrate the problem. We can then
fix the bug and use your code as a unit test.
Regards
Stéfan
import numpy as N
from numpy.testing import *
import timeit
def fftfreq0(n,d=1.0):
""" fftfreq(n, d=1.0) -> f
DFT sample frequencies
The returned float array contains the frequency bins in
cycles/unit (with zero at the start) given a window length n and a
sample spacing d:
f = [0,1,...,n/2-1,-n/2,...,-1]/(d*n) if n is even
f = [0,1,...,(n-1)/2,-(n-1)/2,...,-1]/(d*n) if n is odd
"""
assert isinstance(n,int) or isinstance(n,integer)
k = range(0,(n-1)/2+1)+range(-(n/2),0)
return N.array(k,'d')/(n*d)
def fftfreq1(n,d=1.0):
""" fftfreq(n, d=1.0) -> f
DFT sample frequencies
The returned float array contains the frequency bins in
cycles/unit (with zero at the start) given a window length n and a
sample spacing d:
f = [0,1,...,n/2-1,-n/2,...,-1]/(d*n) if n is even
f = [0,1,...,(n-1)/2,-(n-1)/2,...,-1]/(d*n) if n is odd
"""
assert isinstance(n,int) or isinstance(n,integer)
k = N.hstack((N.arange(0,(n-1)/2 + 1), N.arange(-(n/2),0))) / (n*d)
return k
def fftfreq2(n,d=1.0):
""" fftfreq(n, d=1.0) -> f
DFT sample frequencies
The returned float array contains the frequency bins in
cycles/unit (with zero at the start) given a window length n and a
sample spacing d:
f = [0,1,...,n/2-1,-n/2,...,-1]/(d*n) if n is even
f = [0,1,...,(n-1)/2,-(n-1)/2,...,-1]/(d*n) if n is odd
"""
assert isinstance(n,int) or isinstance(n,integer)
k = N.empty(n)
midpoint = (n-1)/2+1
k[:midpoint] = N.arange(0,(n-1)/2 + 1)
k[midpoint:] = N.arange(-(n/2),0)
k *= 1./(n*d)
return k
for i in [int(x) for x in 1e5,1e5+1,1e6,1e6+1]:
print "Benchmarking for n=%d" % i
def bench(fname,out="x"):
return timeit.Timer("__main__.%s=__main__.%s(%d)" % (out,fname,i),
"import __main__").timeit(number=10)
print "Old: ", bench("fftfreq0",out="a")
print "New_concat: ", bench("fftfreq1",out="b")
print "New_inplace: ", bench("fftfreq2",out="c")
print
assert_array_almost_equal(a,b)
assert_array_almost_equal(b,c)
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Re: [Numpy-discussion] Use of numarray from numpy package [# INC NO 24609]
LANDRIU David SAp wrote:
> Hello,
>
> I come back to my question : how to use numarray
> with the numpy installation ?
>
> {ccali22}~(0)>setenv PYTHONPATH /usr/local/lib/python2.3/site-packages/numpy
>
Here's where you went wrong. You want:
setenv PYTHONPATH /usr/local/lib/python2.3/site-packages
> {ccali22}~(0)>python
> Python 2.3.5 (#2, Oct 17 2005, 17:20:02)
> [GCC 3.2.3 20030502 (Red Hat Linux 3.2.3-52)] on linux2
> Type "help", "copyright", "credits" or "license" for more information.
>
from numarray import *
> Traceback (most recent call last):
> File "", line 1, in ?
> File "/usr/local/lib/python2.3/site-packages/numpy/numarray/__init__.py",
> line 1, in ?
> from util import *
> File "/usr/local/lib/python2.3/site-packages/numpy/numarray/util.py", line
> 2, in ?
> from numpy import geterr
> ImportError: No module named numpy
>
Note that you're actually importing a numarray within numpy's directory
structure. That's because of your PYTHONPATH. numpy ships numpy.numarray
to provide backwards compatibility. To use it, you must do "import
numpy.numarray as numarray"
Cheers!
Andrew
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[Numpy-discussion] amd64 support
I plan to build an amd64 box and run debian etch. Are there any big, 64-bit, show-stopping problems in numpy? Any minor annoyances? - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] possible bug with numpy.object_
On 8/30/06, Stefan van der Walt <[EMAIL PROTECTED]> wrote: > The current behaviour makes sense, but is maybe not consistent: > > N.array([],dtype=object).size == 1 > N.array([[],[]],dtype=object).size == 2 Yes, including one more term in this check: In [5]: N.array([],dtype=object).size Out[5]: 1 In [6]: N.array([[]],dtype=object).size Out[6]: 1 In [7]: N.array([[],[]],dtype=object).size Out[7]: 2 Intuitively, I'd have expected the answers to be 0,1,2, instead of 1,1,2. Cheers, f - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] stumped numpy user seeks help
On Tue, Aug 29, 2006 at 03:46:45PM -0700, Mathew Yeates wrote: > My head is about to explode. > > I have an M by N array of floats. Associated with the columns are > character labels > ['a','b','b','c','d','e','e','e'] note: already sorted so duplicates > are contiguous > > I want to replace the 2 'b' columns with the sum of the 2 columns. > Similarly, replace the 3 'e' columns with the sum of the 3 'e' columns. > > The resulting array still has M rows but less than N columns. Anyone? > Could be any harder than Sudoku. I attach one possible solution (allowing for the same column name occurring in different places, i.e. ['a','b','b','a']). I'd be glad for any suggestions on how to clean up the code. Regards Stéfan import numpy as N import itertools x = N.ones((4,6)) fields = ['a','a','b','b','b','a'] fields_ = [] field_lengths = [] for k,g in itertools.groupby(fields): fields_.append(k) field_lengths.append(len(list(g))) indices = N.cumsum([0] + list(field_lengths)) oshape = list(x.shape) oshape[1] = len(indices)-1 y = N.empty(oshape,dtype=x.dtype) for i,s in enumerate(itertools.imap(slice,indices[:-1],indices[1:])): y[:,i] = x[:,s].sum(axis=1) print 'Input:' print '--' print fields print x print print 'Output:' print '---' print fields_ print y - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Use of numarray from numpy package [# INC NO 24609]
On Aug 30, 2006, at 8:51 AM, LANDRIU David SAp wrote: > Hello, > > I come back to my question : how to use numarray > with the numpy installation ? > If you are using both at the same time, one thing you don't want to do is from numpy import * from numarray import * You can do that with one or the other but not both. Are you doing that? Perry Greenfield - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] fromiter shape argument -- was Re: For loop tips
Torgil Svensson wrote: >>return uL,asmatrix(fromiter((idx[x] for x in L),dtype=int)) >> > > Is it possible for fromiter to take an optional shape (or count) > argument in addition to the dtype argument? Yes. fromiter(iterable, dtype, count) works. > If both is given it could > preallocate memory and we only have to iterate over L once. > Regardless, L is only iterated over once. In general you can't rewind iterators, so that's a requirement. This is accomplished by doing successive overallocation similar to the way appending to a list is handled. By specifying the count up front you save a bunch of reallocs, but no iteration. -tim > //Torgil > > On 8/29/06, Keith Goodman <[EMAIL PROTECTED]> wrote: > >> On 8/29/06, Torgil Svensson <[EMAIL PROTECTED]> wrote: >> >>> something like this? >>> >>> def list2index(L): >>>uL=sorted(set(L)) >>>idx=dict((y,x) for x,y in enumerate(uL)) >>>return uL,asmatrix(fromiter((idx[x] for x in L),dtype=int)) >>> >> Wow. That's amazing. Thank you. >> >> - >> Using Tomcat but need to do more? Need to support web services, security? >> Get stuff done quickly with pre-integrated technology to make your job easier >> Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo >> http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 >> ___ >> Numpy-discussion mailing list >> Numpy-discussion@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/numpy-discussion >> >> > > - > Using Tomcat but need to do more? Need to support web services, security? > Get stuff done quickly with pre-integrated technology to make your job easier > Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo > http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 > ___ > Numpy-discussion mailing list > Numpy-discussion@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/numpy-discussion > > > - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Use of numarray from numpy package
Hi David, Numeric, numarray and numpy are three different packages that can live independently, but that can also coexist if you like so. If you're new to this packages, you should stick to numpy, as the other ones are getting phased out. It's difficult to see what's going wrong without having seen how you installed it. I see that you tried >>> from numarray import * Perhaps a stupid question, but you did import numpy with >>> from numpy import * didn't you? Cheers, Joris Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Use of numarray from numpy package [# INC NO 24609]
Hello,
I come back to my question : how to use numarray
with the numpy installation ?
After some update in the system there is another
error message :
>> AttributeError: 'module' object has no attribute 'NewAxis'
It seems , from advice of the system manager, that an kind of
alias failed to execute the right action.
Thanks in advance for your answer,
Cheers,
David Landriu
- Begin Forwarded Message -
>Date: Wed, 30 Aug 2006 14:14:27 +0200 (MEST)
>To: LANDRIU David SAp <[EMAIL PROTECTED]>
>Subject: Re: Use of numarray from numpy package [# INC NO 24609]
>From: User Support <[EMAIL PROTECTED]>
>Error-to: Jean-Rene Rouet <[EMAIL PROTECTED]>
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>
>
>Réponse de User-Support à votre question :
>--
>
>Rebonjour
>Essayez maintenat svp
>
>WW
Voici ce que j'obtiens maintenant :
{ccali22}~(0)>setenv PYTHONPATH /usr/local/lib/python2.3/site-packages/numpy
{ccali22}~(0)>
{ccali22}~(0)>
{ccali22}~(0)>python
Python 2.3.5 (#2, Oct 17 2005, 17:20:02)
[GCC 3.2.3 20030502 (Red Hat Linux 3.2.3-52)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from numarray import *
Traceback (most recent call last):
File "", line 1, in ?
AttributeError: 'module' object has no attribute 'NewAxis'
>>>
##
##
Hello,
is it necessary to install numarray separately to use numpy ?
Indeed, after numpy installation, when I try to use it in the code,
I get the same error as below :
.../...
Python 2.4.1 (#1, May 13 2005, 13:45:18)
[GCC 3.2.3 20030502 (Red Hat Linux 3.2.3-42)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from numarray import *
Traceback (most recent call last):
File "", line 1, in ?
File "/usr/local/lib/python2.3/site-packages/numpy/numarray/__init__.py",
line 1, in ?
from util import *
File "/usr/local/lib/python2.3/site-packages/numpy/numarray/util.py", line 2,
in ?
from numpy import geterr
ImportError: No module named numpy
>>>
Thanks for your answer,
Cheers,
David Landriu
David Landriu DAPNIA/SAp CEA SACLAY (France)
Phone : (33|0)169088785
Fax: (33|0)169086577
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Re: [Numpy-discussion] stumped numpy user seeks help
Mathew Yeates schrieb: > My head is about to explode. > > I have an M by N array of floats. Associated with the columns are > character labels > ['a','b','b','c','d','e','e','e'] note: already sorted so duplicates > are contiguous > > I want to replace the 2 'b' columns with the sum of the 2 columns. > Similarly, replace the 3 'e' columns with the sum of the 3 'e' columns. > > The resulting array still has M rows but less than N columns. Anyone? > Could be any harder than Sudoku. > Hi, I don't have time for this ;-) , but I learnt something useful along the way... import numpy as n m = n.ones([2,6]) a = ['b', 'c', 'c', 'd', 'd', 'd'] startindices = set([a.index(x) for x in a]) out = n.empty([m.shape[0], 0]) for i in startindices: temp = n.mat(m[:, i : i + a.count(a[i])]).sum(axis = 1) out = n.hstack([out, temp]) print out Not sure if axis = 1 is needed, but until the defaults have settled a bit it can't hurt. You need python 2.4 for the built-in , and will be a numpy matrix, use if you don't like that. But here it's really nice to work with matrices, because otherwise .sum() will give you a 1-d array sometimes, and that will suddenly look like a row to (instead of a nice column vector) and wouldn't work -- that's why matrices are so great and everybody should be using them ;-) hth, sven - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] possible bug with numpy.object_
On Tue, Aug 29, 2006 at 10:49:58AM -0600, Travis Oliphant wrote: > Matt Knox wrote: > > is the following behaviour expected? or is this a bug with > > numpy.object_ ? I'm using numpy 1.0b1 > > > > >>> print numpy.array([],numpy.float64).size > > 0 > > > > >>> print numpy.array([],numpy.object_).size > > 1 > > > > Should the size of an array initialized from an empty list not always > > be 1 ? or am I just crazy? > > > Not in this case. Explictly creating an object array from any object > (even the empty-list object) gives you a 0-d array containing that > object. When you explicitly create an object array a different section > of code handles it and gives this result. This is a recent change, and > I don't think this use-case was considered as a backward incompatibility > (which I believe it is). Perhaps we should make it so array([],) > always returns an empty array. I'm not sure. Comments? The current behaviour makes sense, but is maybe not consistent: N.array([],dtype=object).size == 1 N.array([[],[]],dtype=object).size == 2 Regards Stéfan - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] fftfreq very slow; rfftfreq incorrect?
[copied to the scipy list since rfftfreq is only in scipy] Andrew Jaffe wrote: > Hi all, > > the current implementation of fftfreq (which is meant to return the > appropriate frequencies for an FFT) does the following: > > k = range(0,(n-1)/2+1)+range(-(n/2),0) > return array(k,'d')/(n*d) > > I have tried this with very long (2**24) arrays, and it is ridiculously > slow. Should this instead use arange (or linspace?) and concatenate > rather than converting the above list? This seems to result in > acceptable performance, but we could also perhaps even pre-allocate the > space. > > The numpy.fft.rfftfreq seems just plain incorrect to me. It seems to > produce lots of duplicated frequencies, contrary to the actual output of > rfft: > > def rfftfreq(n,d=1.0): > """ rfftfreq(n, d=1.0) -> f > > DFT sample frequencies (for usage with rfft,irfft). > > The returned float array contains the frequency bins in > cycles/unit (with zero at the start) given a window length n and a > sample spacing d: > >f = [0,1,1,2,2,...,n/2-1,n/2-1,n/2]/(d*n) if n is even >f = [0,1,1,2,2,...,n/2-1,n/2-1,n/2,n/2]/(d*n) if n is odd > > None of these should be doubled, right? > > """ > assert isinstance(n,int) > return array(range(1,n+1),dtype=int)/2/float(n*d) > > Thanks, > > Andrew > > > - > Using Tomcat but need to do more? Need to support web services, security? > Get stuff done quickly with pre-integrated technology to make your job easier > Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo > http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
[Numpy-discussion] fftfreq very slow; rfftfreq incorrect?
Hi all,
the current implementation of fftfreq (which is meant to return the
appropriate frequencies for an FFT) does the following:
k = range(0,(n-1)/2+1)+range(-(n/2),0)
return array(k,'d')/(n*d)
I have tried this with very long (2**24) arrays, and it is ridiculously
slow. Should this instead use arange (or linspace?) and concatenate
rather than converting the above list? This seems to result in
acceptable performance, but we could also perhaps even pre-allocate the
space.
The numpy.fft.rfftfreq seems just plain incorrect to me. It seems to
produce lots of duplicated frequencies, contrary to the actual output of
rfft:
def rfftfreq(n,d=1.0):
""" rfftfreq(n, d=1.0) -> f
DFT sample frequencies (for usage with rfft,irfft).
The returned float array contains the frequency bins in
cycles/unit (with zero at the start) given a window length n and a
sample spacing d:
f = [0,1,1,2,2,...,n/2-1,n/2-1,n/2]/(d*n) if n is even
f = [0,1,1,2,2,...,n/2-1,n/2-1,n/2,n/2]/(d*n) if n is odd
None of these should be doubled, right?
"""
assert isinstance(n,int)
return array(range(1,n+1),dtype=int)/2/float(n*d)
Thanks,
Andrew
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[Numpy-discussion] Use of numarray from numpy package
Hello, is it necessary to install numarray separately to use numpy ? Indeed, after numpy installation, when I try to use it in the code, I get the same error as below : .../... Python 2.4.1 (#1, May 13 2005, 13:45:18) [GCC 3.2.3 20030502 (Red Hat Linux 3.2.3-42)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> from numarray import * Traceback (most recent call last): File "", line 1, in ? File "/usr/local/lib/python2.3/site-packages/numpy/numarray/__init__.py", line 1, in ? from util import * File "/usr/local/lib/python2.3/site-packages/numpy/numarray/util.py", line 2, in ? from numpy import geterr ImportError: No module named numpy >>> Thanks for your answer, Cheers, David Landriu David Landriu DAPNIA/SAp CEA SACLAY (France) Phone : (33|0)169088785 Fax: (33|0)169086577 - - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] array indexing problem
Charles R Harris schrieb: > You can get what you expect using matrices: > ... > But generally it is best to just use arrays and get used to the conventions. > Well, there are different views on this subject, and I'm happy that the numpy crew is really trying (and good at it) to make array *and* matrix users happy. So please let us coexist peacefully. -sven - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Irregular arrays
Travis, A sparse matrix is a different animal serving a different purpose, i.e., solution of linear systems. Those storage formats are geared for that application: upper diagonal, block diagonal, stripwise, etc. To be more specific: here tight numerical arrays are presumably discussed. Python and other languages could define an "irregular list of irregular lists" or "aggregation of objects" configuration. Probably Lisp would be better for that. But it is not my driving interest. My interest is packed storage minimizing memory consumption and access time, with bonus points for integration with numerical recipes and element-wise operations. Again, actual demonstration would be appreciated. I selected an example with minimal deviation from a regular array to simplify things. The shape is essentially a cube with a planar cut across one corner. The Mathematica code shows it is very easy to define in that language. (I am not sure whether it is tightly packed but it shows O(N) performance graphs.) - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] [ANN] NumPy 1.0b4 now available
Hi, Travis I tried numpy1.0b4 and add this to setup.py includes = ["numpy.core._internal"] then it works! And all scripts can be packed into a single executables with "bundle_files":2, "skip_archive":0, zipfile = None, --skip_archive option is not needed now. - >I suspect you need to force-include the numpy/core/_internal.py file by >specifying it in your setup.py file as explained on the py2exe site. >That module is only imported by the multiarraymodule.c file which I >suspect py2exe can't automatically discern. > >In 1.0 we removed the package-loader issues which are probably giving >the scipy-style subpackage errors. So, very likely you might be O.K. >with the beta releases of 1.0 as long as you tell py2exe about >numpy/core/_internal.py so that it gets included in the distribution. > >Please post any successes. > >Best, > >-Travis > >-- >http://mail.python.org/mailman/listinfo/python-list -- bruce.who.hk 2006-08-30 - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
