Tue, 29 Sep 2009 14:55:44 -0400, Neal Becker wrote:
This seems to work now, but I'm wondering if Charles is correct, that
inheritance isn't such a great idea here.
The advantage of inheritance is I don't have to implement forwarding all
the functions, a pretty big advantage. (I wonder if
On Wed, Sep 30, 2009 at 2:57 AM, Pauli Virtanen pav...@iki.fi wrote:
Tue, 29 Sep 2009 14:55:44 -0400, Neal Becker wrote:
This seems to work now, but I'm wondering if Charles is correct, that
inheritance isn't such a great idea here.
The advantage of inheritance is I don't have to implement
Lets say I have function that applies a homogeneous transformation
matrix to an Nx3 array of points using np.dot.
since the matrix is 4x4 I have to add a 4 column of ones to the array
so the function looks something like this:
def foo():
--snip--
pts = np.column_stack((Xquad, Yquad,
In the source in my working copy. Is that going to cause problems? I
wasn't sure if it was possible to document methods that didn't yet exist
in the code in the wiki.
Mike
David Goldsmith wrote:
On Tue, Sep 29, 2009 at 10:55 AM, Michael Droettboom md...@stsci.edu
mailto:md...@stsci.edu
I have implemented lots more fixed_pt operations, code attached (sorry for
long lines, hope that's not a problem)import numpy as np
import copy
def rnd (x, frac_bits, _max):
A rounding policy
x1 = x (frac_bits-1)
if (x1 == _max):
return x1 1
else:
return
On Sep 29, 2009, at 3:32 PM, David Warde-Farley wrote:
Is there an easy way to get multiple subdtypes out? e.g. if I have a
dtype
dtype([('foo', 'i4'), ('bar', 'i8'), ('baz', 'S100')])
and an array with that dtype, is there a way to only get the 'foo' and
'bar'?
arr[('foo','bar')]
On Sep 29, 2009, at 4:14 PM, Charles R Harris wrote:
On Tue, Sep 29, 2009 at 2:52 PM, Neal Becker ndbeck...@gmail.com
wrote:
I need the max value of an np scalar type. I had used this code:
def get_max(is_signed, base_type, total_bits):
print 'get_max:', is_signed, base_type,
Hi,
Maybe someone could explain to me what is going on here!?
N.who()
NameShape BytesType
SLmap 2048 x 2048 16777216 int32
SLmap_fast 2048 x 2048 16777216
On Sep 30, 2009, at 6:43 AM, Chris Colbert wrote:
Lets say I have function that applies a homogeneous transformation
matrix to an Nx3 array of points using np.dot.
since the matrix is 4x4 I have to add a 4 column of ones to the array
so the function looks something like this:
def foo():
Ralf Gommers wrote:
On Wed, Sep 30, 2009 at 9:03 AM, Michael Droettboom md...@stsci.edu
mailto:md...@stsci.edu wrote:
In the source in my working copy. Is that going to cause problems? I
wasn't sure if it was possible to document methods that didn't yet
exist
in the
On Wed, Sep 30, 2009 at 9:51 AM, Travis Oliphant oliph...@enthought.com wrote:
On Sep 29, 2009, at 3:32 PM, David Warde-Farley wrote:
Is there an easy way to get multiple subdtypes out? e.g. if I have a
dtype
dtype([('foo', 'i4'), ('bar', 'i8'), ('baz', 'S100')])
and an array with that
I looked and looked in the docs, but couldn't find an answer to this:
When writing a ufunc, is it possible somehow to raise a Python exception
(by acquiring the GIL first to raise it, set a flag and a callback which
will be called with the GIL, or otherwise?). Or should one always use
NaN even
On Wed, Sep 30, 2009 at 10:24 AM, Skipper Seabold jsseab...@gmail.comwrote:
On Wed, Sep 30, 2009 at 9:51 AM, Travis Oliphant oliph...@enthought.com
wrote:
On Sep 29, 2009, at 3:32 PM, David Warde-Farley wrote:
Is there an easy way to get multiple subdtypes out? e.g. if I have a
dtype
On Tue, Sep 29, 2009 at 4:36 PM, Bruce Southey bsout...@gmail.com wrote:
snip
Hi,
The first case just has to handle a missing delimiter - actually I expect
that most of my cases would relate this. So here is simple Python code to
generate arbitrary large list with the occasional missing
On Wed, Sep 30, 2009 at 09:34, Dag Sverre Seljebotn
da...@student.matnat.uio.no wrote:
I looked and looked in the docs, but couldn't find an answer to this:
When writing a ufunc, is it possible somehow to raise a Python exception
(by acquiring the GIL first to raise it, set a flag and a
Russell E. Owen wrote:
All the official numpy 1.3.0 Mac binaries are labelled macosx10.5.
Does anyone know if these are backwards compatible with MacOS X 10.4
numpy-1.3.0-py2.5-macosx10.5.dmg works fine on macosx 10.4.11 ppc
(with Python 2.5.1)
-- denis
On Tue, Sep 29, 2009 at 4:36 PM, Bruce Southey bsout...@gmail.com wrote:
Hi,
The first case just has to handle a missing delimiter - actually I expect
that most of my cases would relate this. So here is simple Python code to
generate arbitrary large list with the occasional missing delimiter.
On Wed, Sep 30, 2009 at 11:01 AM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
On Wed, Sep 30, 2009 at 10:24 AM, Skipper Seabold jsseab...@gmail.com
wrote:
On Wed, Sep 30, 2009 at 9:51 AM, Travis Oliphant oliph...@enthought.com
wrote:
On Sep 29, 2009, at 3:32 PM, David Warde-Farley
jah jah.mailinglist at gmail.com writes:
Hi,Suppose I have a set of x,y,c data ... matplotlib.pyplot.contour() ).
JAH, is griddata() working and fast enough for you ?
How many points are you contouring ?
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On Wed, Sep 30, 2009 at 11:47 AM, Skipper Seabold jsseab...@gmail.comwrote:
On Wed, Sep 30, 2009 at 11:01 AM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
That's really helpful to know. Is it too early to document this on
the wiki http://docs.scipy.org/doc/numpy/user/basics.rec.html?
On Wed, Sep 30, 2009 at 12:00 PM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
No, all the docs should be in the wiki. The page corresponding to the link
you gave is http://docs.scipy.org/numpy/docs/numpy.doc.structured_arrays/
And if you use diff to svn on that page you can see that it
On 09/30/2009 10:22 AM, Skipper Seabold wrote:
On Tue, Sep 29, 2009 at 4:36 PM, Bruce Southeybsout...@gmail.com wrote:
snip
Hi,
The first case just has to handle a missing delimiter - actually I expect
that most of my cases would relate this. So here is simple Python code to
generate
On Wed, Sep 30, 2009 at 12:56 PM, Bruce Southey bsout...@gmail.com wrote:
On 09/30/2009 10:22 AM, Skipper Seabold wrote:
On Tue, Sep 29, 2009 at 4:36 PM, Bruce Southeybsout...@gmail.com wrote:
snip
Hi,
The first case just has to handle a missing delimiter - actually I expect
that most of
Hello,
How to conditionally index an array as shown below :
a = arange(10)
a[5a8]
to get
array([6,7])
I can't do this with where either.
What is the cure for this?
Thanks.
--
Gökhan
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NumPy-Discussion@scipy.org
There may be a more elegant way, but:
In [2]: a = np.arange(10)
In [3]: a[(a5) (a8)]
Out[3]: array([6, 7])
On Wed, Sep 30, 2009 at 1:27 PM, Gökhan Sever gokhanse...@gmail.com wrote:
Hello,
How to conditionally index an array as shown below :
a = arange(10)
a[5a8]
to get
array([6,7])
Gökhan Sever wrote:
How to conditionally index an array as shown below :
a = arange(10)
a[5a8]
to get
array([6,7])
In [56]: a[(5a) (a8)]
Out[56]: array([6, 7])
not as efficient as it might be, but it works.
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response
Thanks this works.
My second question how to access a second array using this condition?
I am trying slice another array using a compound condition on the reference
array.
say:
a = 1,2,3,4,5,
b = 20,30,40,50,60
I want to get elements of a only when a = 3,4. I know I need indices but how
?
On Wed, Sep 30, 2009 at 14:40, Gökhan Sever gokhanse...@gmail.com wrote:
Thanks this works.
My second question how to access a second array using this condition?
I am trying slice another array using a compound condition on the reference
array.
say:
a = 1,2,3,4,5,
b = 20,30,40,50,60
I
On Wed, Sep 30, 2009 at 2:45 PM, Robert Kern robert.k...@gmail.com wrote:
On Wed, Sep 30, 2009 at 14:40, Gökhan Sever gokhanse...@gmail.com wrote:
Thanks this works.
My second question how to access a second array using this condition?
I am trying slice another array using a compound
So, Ralf (or anyone), how, if at all, should we modify the status of the
existing chararray objects/methods in the wiki? Assuming you have no
problem sharing them with me, Michael, I could add those docstrings you
created for the existing methods, and we can promote them to Ready for
Review; they
In the spirit of the 'advice' site, and given that we're thinking of
moving scipy.org to more static content (once I have some free time on
my hands again, which should be soon!), I set up a 'subreddit' on
reddit.com for Python-in-Science related links. I even came up with a
somewhat
On Wed, Sep 30, 2009 at 4:37 PM, David Goldsmith d.l.goldsm...@gmail.comwrote:
So, Ralf (or anyone), how, if at all, should we modify the status of the
existing chararray objects/methods in the wiki?
Nothing has to be done until *after* Mike has committed his changes to svn.
Please see my
On Wed, Sep 30, 2009 at 2:09 PM, Ralf Gommers
ralf.gomm...@googlemail.comwrote:
On Wed, Sep 30, 2009 at 4:37 PM, David Goldsmith
d.l.goldsm...@gmail.comwrote:
So, Ralf (or anyone), how, if at all, should we modify the status of the
existing chararray objects/methods in the wiki?
Nothing
On 30-Sep-09, at 9:51 AM, Travis Oliphant wrote:
Try (with a later version of NumPy --- possibly trunk):
arr[['foo', 'bar']]
(i.e. with a list instead of a tuple)
Aha! Thanks Travis.
I guess tuples for multi-dimensional indexing _and_ multi-field
indexing would be semantically awkward,
On Wed, Sep 30, 2009 at 8:57 AM, denis bzowy denis-bz...@t-online.dewrote:
jah jah.mailinglist at gmail.com writes:
Hi,Suppose I have a set of x,y,c data ... matplotlib.pyplot.contour() ).
JAH, is griddata() working and fast enough for you ?
How many points are you contouring ?
Hi All,
It seems that repr applied do an object array does not provide the info
needed to recreate it:
In [22]: y = array([Decimal(1)]*2)
In [23]: repr(y)
Out[23]: 'array([1, 1], dtype=object)'
And of course, there is going to be a problem with arrays of more than one
dimension anyway. But I
On Wed, Sep 30, 2009 at 21:45, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi All,
It seems that repr applied do an object array does not provide the info
needed to recreate it:
In [22]: y = array([Decimal(1)]*2)
In [23]: repr(y)
Out[23]: 'array([1, 1], dtype=object)'
And of
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