numpy-discussion — Discussion list for all users of Numerical Python

Re: [Numpy-discussion] numpy.random.rand function doesn't take tuple

[Robert K. <rob...@gm...>]

David Grant wrote:
> Thanks everyone. My only question now is why there is random_sample and 
> random. My guess is that one is there for compatibility with older 
> releases and so I'm not bothered by it.

Yes.

-- 
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

Re: [Numpy-discussion] numpy.random.rand function doesn't take tuple

[David G. <dav...@gm...>]

On 8/21/06, Robert Kern <rob...@gm...> wrote:
>
> David Grant wrote:
> > I was a bit surprised today to find that numpy.random.rand doesn't
> > take in a tuple as input for the dimensions of the desired array. I am
> > very used to using a tuple for zeros, ones. Also, wouldn't this mean
> > that it would not be possible to add other non-keyword arguments to
> > rand later?
>
> Don't use rand(), then. Use random(). rand()'s sole purpose in life is to
> *not*
> take a tuple. If you like, you can read the archives on the several (long)
> discussions on this and why things are the way they are now. We finally
> achieved
> something resembling consensus, so please let's not resurrect this
> argument.



Thanks everyone. My only question now is why there is random_sample and
random. My guess is that one is there for compatibility with older releases
and so I'm not bothered by it.


-- 
David Grant
http://www.davidgrant.ca

[Numpy-discussion] error message when using insufficient dtype dict

[N. V. <mit...@we...>]

Hello everyone,

I had quite some trouble figuring out the _correct_ way to create 
heterogeneous arrays.

What I wanted to do was something like the following:

 >>>  numpy.array( [(0,0,0)], dtype={'names':['a','b','c'], 
'formats':['f4','f4','f4']})

This works fine. Now, let's do something wrong, e.g. leave out the 
'formats' specifier:

 >>> numpy.array( [(0,0,0)], dtype={'names':['a','b','c']})
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
  File "/usr/lib/python2.4/site-packages/numpy/core/_internal.py", line 
53, in _usefields
    names, formats, offsets, titles = _makenames_list(adict)
  File "/usr/lib/python2.4/site-packages/numpy/core/_internal.py", line 
21, in _makenames_list
    raise ValueError, "entry not a 2- or 3- tuple"
ValueError: entry not a 2- or 3- tuple

This error message was totally unclear to me. After reading a little on 
the scipy wiki I finally realized that (maybe) numpy internally converts 
the dict with the names and the formats to a list of 2-tuples of the 
form (name, format). Since no formats were given, these 2-tuples were 
invalid.

I would suggest a check for the required dict keys and some meaningful 
error message like: "The dtype dictionary must at least contain the 
'names' and the 'formats' items."

Keep up the great work,

Niklas.

Re: [Numpy-discussion] numpy.random.rand function doesn't take tuple

[Robert K. <rob...@gm...>]

David Grant wrote:
> I was a bit surprised today to find that numpy.random.rand doesn't
> take in a tuple as input for the dimensions of the desired array. I am
> very used to using a tuple for zeros, ones. Also, wouldn't this mean
> that it would not be possible to add other non-keyword arguments to
> rand later?

Don't use rand(), then. Use random(). rand()'s sole purpose in life is to *not* 
take a tuple. If you like, you can read the archives on the several (long) 
discussions on this and why things are the way they are now. We finally achieved 
something resembling consensus, so please let's not resurrect this argument.

-- 
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

Re: [Numpy-discussion] numpy.random.rand function doesn't take tuple

[Alan G I. <ai...@am...>]

On Mon, 21 Aug 2006, David Grant apparently wrote:=20
> I was a bit surprised today to find that numpy.random.rand=20
> doesn't take in a tuple as input for the dimensions of the=20
> desired array. I am very used to using a tuple for zeros,=20
> ones. Also, wouldn't this mean that it would not be=20
> possible to add other non-keyword arguments to rand later?=20

You will find a long discussion of this in the archives.

Cheers,
Alan Isaac

PS Thank you for improving the average predictive accuracy=20
of economists.  (You'll understand when you read the thread.)

Re: [Numpy-discussion] numpy.random.rand function doesn't take tuple

[Travis O. <oli...@ee...>]

David Grant wrote:

>I was a bit surprised today to find that numpy.random.rand doesn't
>take in a tuple as input for the dimensions of the desired array. I am
>very used to using a tuple for zeros, ones. Also, wouldn't this mean
>that it would not be possible to add other non-keyword arguments to
>rand later?
>
>  
>

numpy.random.rand??


    Return an array of the given dimensions which is initialized to
    random numbers from a uniform distribution in the range [0,1).

    rand(d0, d1, ..., dn) -> random values

    Note:  This is a convenience function. If you want an
                interface that takes a tuple as the first argument
                use numpy.random.random_sample(shape_tuple).

[Numpy-discussion] numpy.random.rand function doesn't take tuple

[David G. <dav...@gm...>]

I was a bit surprised today to find that numpy.random.rand doesn't
take in a tuple as input for the dimensions of the desired array. I am
very used to using a tuple for zeros, ones. Also, wouldn't this mean
that it would not be possible to add other non-keyword arguments to
rand later?

-- 
David Grant
http://www.davidgrant.ca

Re: [Numpy-discussion] linspace upper bound not met?

[Bill B. <wb...@gm...>]

Out of curiosity I checked on what matlab does.
It does explicity set the last value to 'stop' to avoid the roundoff issue.
In numpy terms, it does something like
   y = r_[start+r_[0:num-1]*(stop-start)/(num-1.0),  stop]

But for numpy it's probably more efficient to just do the 'y[-1] = stop'
like you say.


--bb

On 8/22/06, Alan G Isaac <ai...@am...> wrote:
>
> The definition of linspace is:
> def linspace(start, stop, num=50, endpoint=True, retstep=False):
>     """Return evenly spaced numbers.
>
>     Return 'num' evenly spaced samples from 'start' to 'stop'.  If
>     'endpoint' is True, the last sample is 'stop'. If 'retstep' is
>     True then return the step value used.
>     """
>     num = int(num)
>     if num <= 0:
>         return array([], float)
>     if endpoint:
>         if num == 1:
>             return array([float(start)])
>         step = (stop-start)/float((num-1))
>     else:
>         step = (stop-start)/float(num)
>     y = _nx.arange(0, num) * step + start
>     if retstep:
>         return y, step
>     else:
>         return y
>
> The simplest way to achieve this goal is to add right after
> the assignment to y two new lines:
>    if endpoint:
>        y[-1] = float(stop)
>
> Cheers,
> Alan Isaac
>
> PS I'll take this opportunity to state again my opinion that
> in the denerate case num=1 that if endpoint=True then
> linspace should return stop rather than start.  (Otherwise
> endpoint is ignored. But I do not expect anyone to agree.)
>
>
>
> -------------------------------------------------------------------------
> Using Tomcat but need to do more? Need to support web services, security?
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> Numpy-discussion mailing list
> Num...@li...
> https://lists.sourceforge.net/lists/listinfo/numpy-discussion
>

Re: [Numpy-discussion] linspace upper bound not met?

[Alan G I. <ai...@am...>]

The definition of linspace is:
def linspace(start, stop, num=3D50, endpoint=3DTrue, retstep=3DFalse):
    """Return evenly spaced numbers.

    Return 'num' evenly spaced samples from 'start' to 'stop'.  If
    'endpoint' is True, the last sample is 'stop'. If 'retstep' is
    True then return the step value used.
    """
    num =3D int(num)
    if num <=3D 0:
        return array([], float)
    if endpoint:
        if num =3D=3D 1:
            return array([float(start)])
        step =3D (stop-start)/float((num-1))
    else:
        step =3D (stop-start)/float(num)
    y =3D _nx.arange(0, num) * step + start
    if retstep:
        return y, step
    else:
        return y

The simplest way to achieve this goal is to add right after=20
the assignment to y two new lines:
   if endpoint:
       y[-1] =3D float(stop)

Cheers,
Alan Isaac

PS I'll take this opportunity to state again my opinion that
in the denerate case num=3D1 that if endpoint=3DTrue then=20
linspace should return stop rather than start.  (Otherwise=20
endpoint is ignored. But I do not expect anyone to agree.)

[Numpy-discussion] linspace upper bound not met?

[Bill B. <wb...@gm...>]

I was porting some code over from matlab in which I relied on the upper
bound of linspace to be met exactly.

It turns out that it isn't always exactly met in numpy.

In [390]: filter(lambda x: x[1]!=0.0, [ (i,1.0-numpy.linspace(0,1,i)[-1])
for i in range(2,200) ])
Out[390]:
[(50, 1.1102230246251565e-016),
 (99, 1.1102230246251565e-016),
 (104, 1.1102230246251565e-016),
 (108, 1.1102230246251565e-016),
 (162, 1.1102230246251565e-016),
 (188, 1.1102230246251565e-016),
 (197, 1.1102230246251565e-016),
 (198, 1.1102230246251565e-016)]


I know it's not a good idea to count on floating point equality in general,
but still it doesn't seem too much to expect that the first and last values
returned by linspace are exactly the values asked for if they both have
exact floating point representations.

--bb

Re: [Numpy-discussion] news eafyby

[Faith T. <bi...@am...>]

Hi,
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=20

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[Numpy-discussion] =?GB2312?B?cmU6yOe6zrPJzqrTxdDjtcSztbzk1ve53A==?=

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              <div align="center"><font color="#FFFFFF">[课 程 背 景]</font></div></td>                
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              <p ALIGN="JUSTIFY"><font LANG="ZH-CN">
              &nbsp;&nbsp;&nbsp;</font><font lang="ZH-CN" size="2">  </font><font lang="ZH-CN" size="2"><span style="mso-bidi-font-size: 9.0pt; mso-bidi-font-family: Times New Roman; mso-font-kerning: 1.0pt; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA">对于很多的班组长来讲，从优秀的技术工人走向基层管理岗位，很多时候不得不面对：<br>
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              &nbsp;&nbsp;&nbsp; 参加对象: 班组长、技术员</span></font></td>       
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      <div align="center" style="width: 671; height: 1"> </div>
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            <td width="17%" height="20" bgcolor="#0080C0" class="td"> <div align="center"><font color="#FFFFFF">[课               
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            <td height="64" colspan="2" class="td"> <p><font size="2"><font color="#0000FF">第一篇 班组长的角色认知及其素养</font><br> 
              一、班组长的角色认知<br>
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              现场改善是成本降低的基础&nbsp;<br>
              IE现场改善方法<br>
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              案例：丰田汽车JIT精益生产实际案例</font> 
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            <td height="64" colspan="2" class="td"> <p><span style="font-size:9.0pt;
font-family:宋体;mso-ascii-font-family:&quot;Times New Roman&quot;;mso-hansi-font-family:
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Re: [Numpy-discussion] numpy installation

[Stephen W. <drs...@gm...>]

On 8/18/06, Joris De Ridder <jo...@st...> wrote:
>
>
>
> Sorry about my ignorance about these things. But is lapack_lite linked
> to numpy even if you specify the full lapack library?


As I understand it, lapack_lite is built and used by numpy as a shared
library with a subset of the LAPACK routines.

After some googling I learned that g2c is a lib which takes care that you
> can link fortran and C libraries (again my ignorance...).


Which platform are you on?  If you do

python setup.py build >& spool
grep lapack spool

what output do you get?

Re: [Numpy-discussion] bugfix-patch for numpy-1.0b2 setup

[Albert S. <fu...@gm...>]

Hello all

> <snip>
> Furthermore: the TRAC tickets do not seem to allow attachment of
> patches. Did I miss something there?

After submitting the initial report, you can attach files to the ticket.

Regards,

Albert

Re: [Numpy-discussion] bugfix-patch for numpy-1.0b2 setup

[Norbert N. <Nor...@gm...>]

Travis Oliphant wrote:
> Norbert Nemec wrote:
>   
>> Hi there,
>>
>> in numpy-1.0b2 the logic in setup.py is slightly off. The attached patch
>> fixes the issue.
>>
>> Greetings,
>> Norbert
>>
>> PS: I would have preferred to submit this patch via the sourceforge
>> bug-tracker, but that seems rather confusing: there are tabs "Numarray
>> Patches" and "Numarray Bugs" but no "NumPy bugs" and the tab "Patches"
>> seems to be used for Numeric. Why isn't NumPy handled via the
>> Sourceforge page?
>>   
>>     
> NumPy development happens on the SVN servers at scipy.org and 
> bug-tracking is handled through the Trac system at
>
> http://projects.scipy.org/scipy/numpy
>
> We only use sourceforge for distribution.
>   
OK, sorry. I found this myself in the meantime. I even remember that I
stumbled over this some time ago already. Problem is: I'm submitting
bug-reports, fixes and small patches to so many different projects, that
I start mixing up the details of the individual procedures.

Furthermore: the TRAC tickets do not seem to allow attachment of
patches. Did I miss something there?

> I need more description on why the logic is not right.
>   
The original code reads:

-----------------------

[...snip...]
            if nosmp: moredefs = [('NPY_ALLOW_THREADS', '0')]
            else: moredefs = []
[...snip...]
            if moredefs:
                target_f = open(target,'a')
                for d in moredefs:
                    if isinstance(d,str):
                        target_f.write('#define %s\n' % (d))
                    else:
                        target_f.write('#define %s %s\n' % (d[0],d[1]))
                if not nosmp:  # default is to use WITH_THREAD
                    target_f.write('#ifdef WITH_THREAD\n#define
NPY_ALLOW_THREADS 1\n#else\n#define NPY_ALLOW_THREADS 0\n#endif\n')
                target_f.close()
[...snip...]
----------------

That is: if not nosmp, then moredefs may be empty, in which case
NPY_ALLOW_THREADS is not defined at all. My patch ensures that
NPY_ALLOW_THREADS is defined in any case, either by putting it in
moredefs, or by adding the special conditional define.

The conditional "if moredefs" is not needed at all: the file needs to be
opened in any case, to define NPY_ALLOW_THREADS one way or other.

Greetings,
Norbert

Re: [Numpy-discussion] Patch against Image.py in the PIL

[Simon B. <si...@ar...>]

On Wed, 12 Jul 2006 16:42:55 -0600
Travis Oliphant <oli...@ie...> wrote:

> 
> Attached is a patch that makes PIL Image objects both export and consume 
> the array interface.

Cool !

I found that upon converting to/from a numpy array the image is upside-down.

Simon.



-- 
Simon Burton, B.Sc.
Licensed PO Box 8066
ANU Canberra 2601
Australia
Ph. 61 02 6249 6940
http://arrowtheory.com 

Re: [Numpy-discussion] 1.02b problems

[Tommy G. <tg...@ma...>]

I am trying to install numpy on my Apple Powerbook G4 running OS X  
Tiger (10.4.7).
I am running ActivePython 2.4.3. Installing the numPy package seems  
to work fine but
when I try to import it I get the following:

/Users/tgrav --> python
ActivePython 2.4.3 Build 11 (ActiveState Software Inc.) based on
Python 2.4.3 (#1, Apr  3 2006, 18:07:18)
[GCC 3.3 20030304 (Apple Computer, Inc. build 1666)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
 >>> import numpy
Traceback (most recent call last):
   File "<stdin>", line 1, in ?
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/numpy/__init__.py", line 35, in ?
     import core
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/numpy/core/__init__.py", line 10, in ?
     from numeric import *
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/numpy/core/numeric.py", line 33, in ?
     CLIP = multiarray.CLIP
AttributeError: 'module' object has no attribute 'CLIP'
 >>>

How can I remedy this problem?

Cheers
Tommy
tg...@ma...
http://homepage.mac.com/tgrav/

"Any intelligent fool can make things bigger,
more complex, and more violent. It takes a
touch of genious -- and a lot of courage --
to move in the opposite direction"
                          -- Albert Einstein

[Numpy-discussion] install on Python 2.5

[Daniel F. <djo...@ya...>]

Any advice on installing numpy in Python 2.5 on WindowsXP?

 

 

 

Re: [Numpy-discussion] speed degression

[Charles R H. <cha...@gm...>]

Yes,

On 8/19/06, Joris De Ridder <jo...@st...> wrote:
> Hi,
>
> Some of my code is heavily using large complex arrays, and I noticed a
speed
> degression in NumPy 1.0b2 with respect to Numarray. The following code
snippet
> is an example that on my computer runs 10% faster in Numarray than in
NumPy.
>
> >>> A = zeros(1000000, complex)
> >>> for k in range(1000):
> ...        A *= zeros(1000000, complex)
>
> (I replaced 'complex' with 'Complex' in Numarray).  Can anyone confirm
this?

I see this too.

In [242]: t1 = timeit.Timer('a *= nx.zeros(1000000,"D")','import numarray as
nx; a = nx.zeros(1000000,"D")')

In [243]: t2 = timeit.Timer('a *= nx.zeros(1000000,"D")','import numpy as
nx; a = nx.zeros(1000000,"D")')

In [244]: t1.repeat(3,100)
Out[244]: [5.184194803237915, 5.1135070323944092, 5.1053409576416016]

In [245]: t2.repeat(3,100)
Out[245]: [5.5170519351959229, 5.4989008903503418, 5.479154109954834]

Chuck

[Numpy-discussion] speed degression

[Joris De R. <jo...@st...>]

Hi,

Some of my code is heavily using large complex arrays, and I noticed a speed
degression in NumPy 1.0b2 with respect to Numarray. The following code snippet
is an example that on my computer runs 10% faster in Numarray than in NumPy.

>>> A = zeros(1000000, complex)
>>> for k in range(1000):
...        A *= zeros(1000000, complex)

(I replaced 'complex' with 'Complex' in Numarray).  Can anyone confirm this? 

Ciao,
Joris

[Numpy-discussion] Whitespace

[Charles R H. <cha...@gm...>]

Hi All,

I've noticed a lot of trailing whitespace while browsing through the
numpy subversion repository. So here is a perl script I pinched from
the linux-kernel mailing list that does a good job of removing it.

Chuck

Re: [Numpy-discussion] numpy installation

[Joris De R. <jo...@st...>]

Hi,

   [PL]: s_wsfe is not LAPACK's routine it's a routine from the g2c library.
   [PL]: You have to link it in in addition to lapack_lite.

Thanks for the pointer.

Sorry about my ignorance about these things. But is lapack_lite linked
to numpy even if you specify the full lapack library? 

After some googling I learned that g2c is a lib which takes care that you
can link fortran and C libraries (again my ignorance...). It's still not obvious
for me, though,  where/how I can make the install program do this linking.
I have a /usr/lib/libg2c.a, so I am surprised it doesn't find it right away...

Anybody experienced something similar, or other pointers?

Ciao,
Joris

Re: [Numpy-discussion] =?iso-8859-1?q?attributes_of_scalar_types_-_e?= =?iso-8859-1?q?=2Eg=2E=09numpy=2Eint32=2Eitemsize?=

[Sebastian H. <ha...@ms...>]

On Friday 18 August 2006 16:51, Travis Oliphant wrote:
> Sebastian Haase wrote:
> > On Friday 18 August 2006 15:25, Travis Oliphant wrote:
> >> Sebastian Haase wrote:
> >>> On Friday 18 August 2006 11:38, Travis Oliphant wrote:
> >>>> Sebastian Haase wrote:
> >>>>> Hi,
> >>>>> array dtype descriptors have an attribute itemsize  that gives the
> >>>>> total number of bytes required for an item of that dtype.
> >>>>>
> >>>>> Scalar types, like  numy.int32, also have that attribute,
> >>>>> but it returns "something else" - don't know what:
> >>>>>
> >>>>>
> >>>>> Furthermore there are *lot's*  of more attributes to a scalar dtype,
> >>>>> e.g.
> >>>>
> >>>> The scalar types are actual Python types (classes) whereas the dtype
> >>>> objects are instances.
> >>>>
> >>>> The attributes you are seeing of the typeobject are very useful when
> >>>> you have an instance of that type.
> >>>>
> >>>> With numpy.int32.itemsize you are doing the equivalent of
> >>>> numpy.dtype.itemsize
> >>>
> >>> but why then do I not get the result 4 ?
> >>
> >> Because it's not a "class" attribute, it's an instance attribute.
> >>
> >> What does numpy.dtype.itemsize give you?
> >
> > I'm really sorry for being so dumb - but HOW can I get then the number of
> > bytes needed by a given scalar type ?
>
> Ah, the real question.  Sorry for not catching it earlier.  I've been in
> "make sure this isn't a bug mode" for a long time.
>
> If you have a scalar type you could create one and then check the itemsize:
>
> int32(0).itemsize
>
> Or you could look at the name and parse out how big it is.
>
> There is also a stored dictionary-like object that returns the number of
> bytes for any data-type recognized:
>
> numpy.nbytes[int32]

Thanks, that seems to be a handy "dictionary-like object"

Just for the record - in the meantime I found this:
>>> N.dtype(N.int32).itemsize
4

Cheers,
Sebastian

Re: [Numpy-discussion] bugfix-patch for numpy-1.0b2 setup

[Stefan v. d. W. <st...@su...>]

On Fri, Aug 18, 2006 at 04:45:03PM +0200, Stefan van der Walt wrote:
> Hi Norbert
>=20
> On Fri, Aug 18, 2006 at 03:36:47PM +0200, Norbert Nemec wrote:
> > in numpy-1.0b2 the logic in setup.py is slightly off. The attached pa=
tch
> > fixes the issue.
>=20
> Please file a ticket so that we don't lose track of this.

Urgh, please excuse me.  It seems that I have lost the ability to read
more than one paragraph.

St=E9fan