Well, testing under windows 64 bit, Python 3.5.2, positive powers of
integers give integers and negative powers of integers give floats. So,
do you want to raise an exception when taking a negative power of an
element of an array of integers? Because not doing so would be
inconsistent with rais
Hi all,
Just to have the options clear. Is the operator '**' going to be handled
in any different manner than pow?
Thanks.
Armando
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Also in favor of 2. Always return a float for '**'
On 04.06.2016 21:47, josef.p...@gmail.com wrote:
On Sat, Jun 4, 2016 at 3:43 PM, Charles R Harris
wrote:
On Sat, Jun 4, 2016 at 11:22 AM, Charles R Harris
wrote:
Hi All,
I've made a new post so that we can make an explicit decision.
AFAIC
Hi,
The English versions:
http://www.esrf.eu/Jobs/english/recruitment-portal
Best regards,
Armando
On 13.06.2015 10:53, Jerome Kieffer wrote:
> Dear Pythonistas,
>
> The European Synchrotron, ESRF, located in the French Alps, just got
> approved a large upgrade in which data-analysis is a key
On 15.10.2014 21:48, Chris Barker wrote:
> Sorry about SWIG -- maybe a chance to move on ;-)
>
> I'd go with Cython -- this is pretty straightforward, and it handles
> the buffer protocol for you under the hood.
>
+1
All the standard containers are automatically wrapped and C++ exceptions
can
On 21.02.2014 10:55, David Goldsmith wrote:
> On Thu, Feb 20, 2014 at 10:37 PM, wrote:
>
>> Date: Fri, 21 Feb 2014 07:43:17 +0100
>> From: "V. Armando Sol?"
>> *Ref. 8173* *- Deadline for returning application forms: *
>> *01/04/2014*
>
> I assume thats the European date format, i.e., the due da
Sorry, the link was in French ...
The English version:
http://esrf.profilsearch.com/recrute/fo_form_cand.php?_lang=en&id=300
Best regards,
Armando
On 20.02.2014 18:21, V. Armando Sole wrote:
> Dear colleagues,
>
> The ESRF is looking for a Software Developer:
>
> http://es
Dear colleagues,
The ESRF is looking for a Software Developer:
http://esrf.profilsearch.com/recrute/fo_annonce_voir.php?id=300
Our ideal candidate would be experienced on OpenGL, OpenCL and Python.
Best regards,
Armando
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NumPy-Discussion mailing l
On 22.02.2013 19:54, Sergio Callegari wrote:
>>
>> from scipy.linalg.blas import fblas
>> dgemm = fblas.dgemm._cpointer
>> sgemm = fblas.sgemm._cpointer
>>
>
> OK, but this gives me a PyCObject. How do I make it a function
> pointer of the
> correct type in cython?
>
In cython I do not know it.
On 18.02.2013 22:47, Pauli Virtanen wrote:
> 18.02.2013 23:29, V. Armando Sole kirjoitti:
> [clip]
>> I find Dag's approach more appealing.
>>
>> SciPy can be problematic (windows 64-bit) and if one could offer
>> access
>> to the linear algebr
On 18.02.2013 21:23, Pauli Virtanen wrote:
> 18.02.2013 20:41, Dag Sverre Seljebotn kirjoitti:
> [clip]
>> I think there should be a new project, pylapack or similar, for
>> this,
>> outside of NumPy and SciPy. NumPy and SciPy could try to import it,
>> and
>> if found, fetch a function pointer
Hi Sturla,
Quoting Sturla Molden :
> Den 10.03.2012 22:56, skrev Sturla Molden:
>>
>> I am not sure why NumPy uses f2c'd routines instead of a dependency
>> on BLAS and LAPACK like SciPy.
>
> Actually, np.dot does depend on the CBLAS interface to BLAS (_dotblas.c).
>
> But the lapack methods in
_Python_Guide/8.18/contents.html
> is more up-to-date and we are on github too:
> https://github.com/DiamondLightSource
>
> Peter
>
>
> On 9 December 2011 13:05, Vicente Sole wrote:
>> Quoting Robert Kern :
>>
>>> On Fri, Dec 9, 2011 at 11:00, Yang Zhang wrote:
&
Quoting Robert Kern :
> On Fri, Dec 9, 2011 at 11:00, Yang Zhang wrote:
>
>> Thanks for the clarification. Alas. So is there no simple workaround
>> to making numpy work in environments such as Jepp?
>
> I don't think so, no.
>
It is far from being an optimal solution (in fact I dislike it) bu
Hi,
I have never seen myself a NetCDF file but if your NetCDF file is
using HDF5 as format (possible since NetCDF 4 if I am not mistaken),
you should be able to use h5py or PyTables to access and or modify it.
Best regards,
Armando
Quoting Chao YUE :
> Dear all,
>
> I want to change some v
Quoting josef.p...@gmail.com:
> but the two options don't produce the same result in general, the
> cumsum version doesn't restart from zero, I think
>
> try
> x0 = np.random.randint(5,size=30).cumsum()
> with delta=3
>
> I don't see a way around recursive looping
>
The x0 data are already sorted
.
Armando
Quoting Vicente Sole :
>>> ? Well a loop or list comparison seems like a good choice to me. It is
>>> much more obvious at the expense of two LOCs. Did you profile the two
>>> possibilities and are they actually performance-critical?
>>>
>>> che
>> ? Well a loop or list comparison seems like a good choice to me. It is
>> much more obvious at the expense of two LOCs. Did you profile the two
>> possibilities and are they actually performance-critical?
>>
>> cheers
>>
The second is between 8 and ten times faster on my machine.
import numpy
Correct. I thought just multiplying by -1 and inverting the logical
condition would give me the same output.
This makes exactly what I want:
>>> x= numpy.arange(10.)
>>> delta=3
>>> y=[x[0]]
>>> for value in x:
> ... if (value-y[-1]) < delta:
> ...y.append(value)
> ...
>>> y
[0., 4.
With A and X being arrays:
B=numpy.zeros(A.shape, A.dtype)
B[A>0] = X
Armando
Quoting gerardob :
>
> Let A be a square matrix of 0's and 1's, and let X be a one dimesional
> vector.
> The length of X is equal to the number of 1's that A has.
> I would like to produce a new matrix B by traversi
Quoting Bruce Southey :
> On 01/18/2010 12:47 PM, Vicente Sole wrote:
>> Quoting Bruce Southey :
>>
>>>
>>> If you obtain the code from any package then you are bound by the terms
>>> of that code. So while a user might not be 'inconvenienced'
At 01:44 23/01/2009 -0600, Robert Kern wrote:
>It is an inevitable consequence of several features interacting
>together. Basically, Python expands "a[b] += 1" into this:
>
> c = a[b]
> d = c.__iadd__(1)
> a[b] = d
>
>Basically, the array c doesn't know that it was created by indexing a,
>so
Hello,
In an effort to suppress for loops, I have arrived to the following situation.
Through vectorial logical operations I generate a set of indices for which
the contents of an array have to be incremented. My problem can be reduced
to the following:
#This works
import numpy
a=numpy.zeros(1
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