On Thu, Oct 31, 2013 at 2:08 AM, Robert Kern wrote:
> On Thu, Oct 31, 2013 at 12:52 AM, Geoffrey Irving wrote:
>>
>> Is there a standard way in numpy of getting a char with C-native
>> integer signedness? I.e.,
>>
>> boost::is_signed::value ? numpy.byt
Is there a standard way in numpy of getting a char with C-native
integer signedness? I.e.,
boost::is_signed::value ? numpy.byte : numpy.ubyte
but without nonsensical mixing of languages?
Thanks,
Geoffrey
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On Tue, Jul 16, 2013 at 4:51 PM, Anthony Scopatz wrote:
> Hi Geoffrey,
>
> Not to toot my own horn here too much, but you really should have a look at
> xdress (http://xdress.org/ and https://github.com/xdress/xdress). XDress
> will generate a wrapper of the Force class for you and then also crea
Is there a standard way of creating an object array restricted to a
particular python type? I want a safe way of sending arrays of
objects back and forth between Python and C++, and it'd be great if I
could use numpy arrays on the Python side instead of creating a new
type.
For example, I might h
I have the following two structured dtypes:
rotation (quaternion) = dtype([('s','f8'),('v','3f8')])
frame = dtype([('t','3f8'),('r',rotation)])
For various reasons, I usually store rotation arrays in a class
Rotations deriving from ndarray, and frames in a class Frames deriving
from ndarr
t;>>> np.double(None)
> nan
>
> On Mon, Jan 28, 2013 at 3:48 PM, Geoffrey Irving wrote:
>>
>> I discovered this from C via the PyArray_FromAny function, but here it
>> is in Python:
>>
>> &g
I discovered this from C via the PyArray_FromAny function, but here it
is in Python:
>>> asarray(None,dtype=float)
array(nan)
Is this expected or documented behavior? It seems quite unintuitive
and surprising that this wouldn't throw an exception.
Is there a way to disable this behavior
On Thu, Aug 2, 2012 at 3:13 PM, Robert Kern wrote:
> On Thu, Aug 2, 2012 at 11:41 PM, Geoffrey Irving wrote:
>> On Thu, Aug 2, 2012 at 1:26 PM, Robert Kern wrote:
>>> On Thu, Aug 2, 2012 at 8:46 PM, Geoffrey Irving wrote:
>>>> Hello,
>>>>
>>>
On Thu, Aug 2, 2012 at 1:26 PM, Robert Kern wrote:
> On Thu, Aug 2, 2012 at 8:46 PM, Geoffrey Irving wrote:
>> Hello,
>>
>> The attached .npy file was written from custom C++ code. It loads
>> fine in Numpy 1.6.2 with Python 2.6 installed through MacPorts, but
>
Hello,
The attached .npy file was written from custom C++ code. It loads
fine in Numpy 1.6.2 with Python 2.6 installed through MacPorts, but
fails on a different machine with Numpy 2.0.0 installed via Superpack:
box:array% which python
/usr/bin/python
box:array% which python
box:array% python
Py
On Wed, Dec 21, 2011 at 3:56 AM, Charles R Harris
wrote:
> Hi Geoffrey,
>
> On Tue, Dec 20, 2011 at 7:24 PM, Geoffrey Irving wrote:
>>
>> Hello,
>>
>> As a followup to the prior thread on bugs in user defined types in
>> numpy, I converted my rational
Hello,
As a followup to the prior thread on bugs in user defined types in
numpy, I converted my rational number class from C++ to C and switched
to 32 bits to remove the need for unportable 128 bit numbers. It
should be usable as a fairly thorough test case for user defined types
now. It does ra
On Mon, Dec 5, 2011 at 6:59 AM, Charles R Harris
wrote:
> Hi Geoffrey,
>
> On Mon, Dec 5, 2011 at 12:37 AM, Geoffrey Irving wrote:
>>
>> On Sun, Dec 4, 2011 at 6:45 PM, Charles R Harris
>> wrote:
>> >
>> >
>> > On Sun, Dec 4, 2011 at 6:59
On Sun, Dec 4, 2011 at 6:45 PM, Charles R Harris
wrote:
>
>
> On Sun, Dec 4, 2011 at 6:59 PM, Geoffrey Irving wrote:
>>
>> On Sun, Dec 4, 2011 at 5:18 PM, Charles R Harris
>> wrote:
>> >
>> >
>> > On Sun, Dec 4, 2011 at 5:41 PM, Geoff
On Sun, Dec 4, 2011 at 5:18 PM, Charles R Harris
wrote:
>
>
> On Sun, Dec 4, 2011 at 5:41 PM, Geoffrey Irving wrote:
>>
>> This may be the problem. Simple diffs are pleasant. I'm guessing
>> this code doesn't get a lot of testing. Glad it's there,
On Sun, Dec 4, 2011 at 10:02 AM, Charles R Harris
wrote:
>
>
> On Sat, Dec 3, 2011 at 5:28 PM, Geoffrey Irving wrote:
>>
>> When attempting to cast to a user defined type, PyArray_GetCast looks
>> up the cast function in the dictionary but doesn't check if t
case 0:
return 0;
}
}
On Sun, Dec 4, 2011 at 9:29 AM, Charles R Harris
wrote:
>
>
> On Sat, Dec 3, 2011 at 8:14 PM, Geoffrey Irving wrote:
>>
>> Hello,
>>
>> I'm trying to add a fixed precision rational number dtype to numpy,
>>
Hello,
I'm trying to add a fixed precision rational number dtype to numpy,
and am running into an issue trying to register ufunc loops. The code
in question looks like
int npy_rational = PyArray_RegisterDataType(&rational_descr);
PyObject* equal = ... // extract equal object from the imp
When attempting to cast to a user defined type, PyArray_GetCast looks
up the cast function in the dictionary but doesn't check if the entry
exists. This causes segfaults. Here's a patch.
Geoffrey
diff --git a/numpy/core/src/multiarray/convert_datatype.c
b/numpy/core/src/multiarray/convert_datat
Hello,
I have an extension module which holds on to a reference to a numpy
array in a static variable. When the process shuts down, the C++
destructor triggers array_dealloc via Py_DECREF, and I get
Program received signal EXC_BAD_ACCESS, Could not access memory.
Reason: KERN_INVALID_ADDRESS at
On Fri, Oct 1, 2010 at 11:39 AM, Robert Kern wrote:
> On Thu, Sep 30, 2010 at 16:26, Geoffrey Irving wrote:
>> On Fri, Oct 1, 2010 at 10:18 AM, Robert Kern wrote:
>>> On Thu, Sep 30, 2010 at 16:00, Geoffrey Irving wrote:
>>>> On Fri, Oct 1, 2010 at 9:38 AM, Ro
On Fri, Oct 1, 2010 at 10:18 AM, Robert Kern wrote:
> On Thu, Sep 30, 2010 at 16:00, Geoffrey Irving wrote:
>> On Fri, Oct 1, 2010 at 9:38 AM, Robert Kern wrote:
>>> On Thu, Sep 30, 2010 at 15:30, Geoffrey Irving wrote:
>>>> Hello,
>>>>
>&g
On Fri, Oct 1, 2010 at 9:38 AM, Robert Kern wrote:
> On Thu, Sep 30, 2010 at 15:30, Geoffrey Irving wrote:
>> Hello,
>>
>> I'm not sure where the correct place to ask questions about Mayavi, so
>> feel free to redirect me elsewhere.
>
> https://mail.enthou
Hello,
I'm not sure where the correct place to ask questions about Mayavi, so
feel free to redirect me elsewhere.
I have a triangle mesh with a bunch of data on each face. The only
color-relevant argument to triangular_mesh I know about is scalars,
which is one value per vertex. Is there a way
Hello,
If I create an mmap'ed array, and then generate another array
referencing only its base, destruction of the original mmap'ed array
closes the mmap. The second array is then prone to segfaults.
I think the best fix is to put the responsibility for flushing the
mmap onto the actual mmap obj
On Sat, Mar 28, 2009 at 12:47 AM, Robert Kern wrote:
> 2009/3/27 Charles R Harris :
>>
>> On Fri, Mar 27, 2009 at 4:43 PM, Robert Kern wrote:
>>>
>>> On Fri, Mar 27, 2009 at 17:38, Bryan Cole wrote:
>>> > I have a number of arrays of shape (N,4,4). I need to perform a
>>> > vectorised matrix-mul
On Fri, Jan 30, 2009 at 5:18 AM, Neal Becker wrote:
> A nit, but it would be nice if 'ones' could fill with a value other than 1.
>
> Maybe an optional val= keyword?
You can use the "tile" function for this. "tile(3,3)" creates an
array of 3 3's.
Geoffrey
___
On Thu, Dec 18, 2008 at 1:00 PM, Robert Kern wrote:
> On Thu, Dec 18, 2008 at 10:01, Geoffrey Irving wrote:
>> On Wed, Dec 17, 2008 at 4:28 PM, Robert Kern wrote:
>
>>> It just seems to me to be another complication that does not provide
>>> any guarantees. You s
On Wed, Dec 17, 2008 at 4:28 PM, Robert Kern wrote:
> On Wed, Dec 17, 2008 at 17:45, Geoffrey Irving wrote:
>> On Wed, Dec 17, 2008 at 3:34 PM, Robert Kern wrote:
>>> On Wed, Dec 17, 2008 at 16:51, Geoffrey Irving wrote:
>>>> On Wed, Dec 17, 2008 at 2:24 PM, Ro
On Wed, Dec 17, 2008 at 3:34 PM, Robert Kern wrote:
> On Wed, Dec 17, 2008 at 16:51, Geoffrey Irving wrote:
>> On Wed, Dec 17, 2008 at 2:24 PM, Robert Kern wrote:
>>> On Wed, Dec 17, 2008 at 15:52, Geoffrey Irving wrote:
>>>> Currently numpy arrays are eith
On Wed, Dec 17, 2008 at 2:24 PM, Robert Kern wrote:
> On Wed, Dec 17, 2008 at 15:52, Geoffrey Irving wrote:
>> Currently numpy arrays are either writable or unwritable, but
>> unwritable arrays can still be changed through other copies. This
>> means that when a numpy ar
Currently numpy arrays are either writable or unwritable, but
unwritable arrays can still be changed through other copies. This
means that when a numpy array is passed into an interface that
requires immutability for safety reasons, a copy always has to be
made.
One way around this would be to ad
On Wed, Oct 15, 2008 at 12:56 PM, Robert Kern <[EMAIL PROTECTED]> wrote:
> On Wed, Oct 15, 2008 at 02:20, Geoffrey Irving <[EMAIL PROTECTED]> wrote:
>> Hello,
>>
>> Currently in numpy comparing dtypes for equality with == does an
>> internal PyArray_EquivT
Hello,
Currently in numpy comparing dtypes for equality with == does an
internal PyArray_EquivTypes check, which means that the dtypes NPY_INT
and NPY_LONG compare as equal in python. However, the hash function
for dtypes reduces id(), which is therefore inconsistent with ==.
Unfortunately I can'
On Sat, Sep 27, 2008 at 10:01 PM, Nathan Bell <[EMAIL PROTECTED]> wrote:
> On Sun, Sep 28, 2008 at 12:34 AM, Geoffrey Irving <[EMAIL PROTECTED]> wrote:
>>
>> Is there an efficient way to implement a nonuniform gather operation
>> in numpy? Specifically, I wa
Hello,
Is there an efficient way to implement a nonuniform gather operation
in numpy? Specifically, I want to do something like
n,m = 100,1000
X = random.uniform(size=n)
K = random.randint(n, size=m)
Y = random.uniform(size=m)
for k,y in zip(K,Y):
X[k] += y
but I want it to be fast. The n
On Thu, Feb 28, 2008 at 06:55:11PM -0600, Robert Kern wrote:
> On Thu, Feb 28, 2008 at 6:43 PM, Geoffrey Irving <[EMAIL PROTECTED]> wrote:
> > > The magic is in In[27]. We reshape the array of vectors to be
> > > compatible with the shape of the array of matrices. When
On Thu, Feb 28, 2008 at 05:57:29PM -0600, Robert Kern wrote:
> On Thu, Feb 28, 2008 at 4:34 PM, Geoffrey Irving <[EMAIL PROTECTED]> wrote:
> > Hello,
> >
> > I have a large number of points (shape (n,3)), and a matching
> > number of 3x3 matrices (shape (n,3,3)
Hello,
I have a large number of points (shape (n,3)), and a matching
number of 3x3 matrices (shape (n,3,3)), and I want to compute
the product of each matrix times the corresponding point.
I can't see a way to do this operation with dot or tensordot,
since these routines either sum across an inde
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