2009/7/8 Robert Kern robert.k...@gmail.com:
2009/7/4 Stéfan van der Walt ste...@sun.ac.za:
Thanks, Scott. This should now be fixed in SVN.
You should probably change that to asanyarray() before the masked
array crowd gets upset. :-)
I hadn't thought about that, but I'm don't think it
Tue, 07 Jul 2009 21:30:06 -0500, alan kirjoitti:
Mathematica vs Matlab vs Python
http://www.larssono.com/musings/matmatpy/index.html
The Python code there is not very idiomatic Numpy code. It's written for
Numeric, and fancy indexing etc. are not used.
Seems like the author also left it as
On Wed, Jul 8, 2009 at 5:37 AM, Charles R
Harrischarlesr.har...@gmail.com wrote:
David,
Should any standard c functions used in loops.c.src be the npy_* version?
I've been using fabs, but I'm wondering if that should be npy_fabs.
Yes. Although fabs is available on any platform in theory, we
Hello,
I have several issues which require me to iterate through a fairly large
array (30+ records).
The first case is calculating and hourly average from non-regularly sampled
data. The second is screening one array, based on data in the second array.
The functions are defined below, but
On Fri, Jun 12, 2009 at 7:46 PM, David
Cournapeauda...@ar.media.kyoto-u.ac.jp wrote:
Hi,
I have finally spent some time so that we can install pure C
libraries using numpy.distutils. With this, one could imagine having a C
library for fft, special functions in numpy or scipy, so that the
Le lundi 06 juillet 2009 à 17:57 +0200, Fabrice Silva a écrit :
Le lundi 06 juillet 2009 à 17:13 +0200, Nils Wagner a écrit :
IIRC, the coefficients of your polynomial are complex.
So, you cannot guarantee that the roots are complex
conjugate pairs.
Correct! If the construction is done
John [H2O] washakie at gmail.com writes:
What I am trying to do (obviously?) is find all the values of X that fall
within a time range.
Specifically, one point I do not understand is why the following two methods
fail:
-- 196 ind = np.where( (t1 Y[:,0] t2) ) #same result
Hello guys,
I made a patch for numpy which allows performing
operations in-place to save memory allocations.
For example 'sqrt(a**2 + b**2)' can be performed
allocating only two arrays instead of four.
You find the details in ticket 1153 of numpy-core.
I thought maybe you could be interested.
I am
Thanks, you two. That helps alot. The PyCObject_FromVoidPtr() trick is
good to know--I still have to have my class because it holds other data, but
this definitely points me in the right direction.
On Tue, Jul 7, 2009 at 9:55 PM, Lisandro Dalcin dalc...@gmail.com wrote:
2009/7/7 Stéfan van
On Jul 8, 2009, at 3:18 AM, Scott Sinclair wrote:
2009/7/8 Robert Kern robert.k...@gmail.com:
2009/7/4 Stéfan van der Walt ste...@sun.ac.za:
Thanks, Scott. This should now be fixed in SVN.
You should probably change that to asanyarray() before the masked
array crowd gets upset. :-)
I
On Jul 8, 2009, at 7:03 AM, John [H2O] wrote:
Hello,
I have several issues which require me to iterate through a fairly
large
array (30+ records).
The first case is calculating and hourly average from non-regularly
sampled
data.
Would you like to give the scikits.timeseries
Hi,
Yup. It's not even very idiomatic Python. readlines() is probably a
bad idea unless your file is trivial length, and even ignoring
numpy.loadtxt(), all of this could be considerably simplified with the
built-in csv module.
or a 1-liner with scipy.io.loadmat ...
Best,
Matthew
On Wed, Jul 08, 2009 at 12:48:17PM -0700, Matthew Brett wrote:
Yup. It's not even very idiomatic Python. readlines() is probably a
bad idea unless your file is trivial length, and even ignoring
numpy.loadtxt(), all of this could be considerably simplified with the
built-in csv module.
or
Hi Luca
2009/7/8 Citi, Luca lc...@essex.ac.uk:
Hello guys,
I made a patch for numpy which allows performing
operations in-place to save memory allocations.
For example 'sqrt(a**2 + b**2)' can be performed
allocating only two arrays instead of four.
You find the details in ticket 1153 of
2009/7/8 Robert Kern robert.k...@gmail.com:
2009/7/4 Stéfan van der Walt ste...@sun.ac.za:
Thanks, Scott. This should now be fixed in SVN.
You should probably change that to asanyarray() before the masked
array crowd gets upset. :-)
Thanks, fixed!
Stéfan
2009/7/8 Gael Varoquaux gael.varoqu...@normalesup.org:
On Wed, Jul 08, 2009 at 12:48:17PM -0700, Matthew Brett wrote:
Yup. It's not even very idiomatic Python. readlines() is probably a
bad idea unless your file is trivial length, and even ignoring
numpy.loadtxt(), all of this could be
On Sun, Jul 05, 2009 at 12:22:37AM +0200, Stéfan van der Walt wrote:
2009/7/5 Pauli Virtanen pav...@iki.fi:
2009-07-04 22:52 +0200, Fons Adriaensen f...@kokkinizita.net wrote:
[clip]
I subscribed to numpy-discussion almost two days ago.
I do receive messages from the list, but the ones I
On Wed, Jul 8, 2009 at 11:34 AM, Citi, Luca lc...@essex.ac.uk wrote:
Hello guys,
I made a patch for numpy which allows performing
operations in-place to save memory allocations.
For example 'sqrt(a**2 + b**2)' can be performed
I think this particular function is already available as a
Hi Stefan,
I am afraid I did not explain myself clear enough.
Of course
c = a + b + d
leaves a, b, and d unchanged.
The only array that is overwritten is (a+b) which is a temporary
array that would be destroyed anyway.
Normally the operation above is performed like this:
1) allocation of a
On Wed, Jul 8, 2009 at 10:00 PM, Fons Adriaensenf...@kokkinizita.net wrote:
On Sun, Jul 05, 2009 at 12:22:37AM +0200, Stéfan van der Walt wrote:
2009/7/5 Pauli Virtanen pav...@iki.fi:
2009-07-04 22:52 +0200, Fons Adriaensen f...@kokkinizita.net wrote:
[clip]
I subscribed to
On Wed, Jul 8, 2009 at 3:57 PM, Citi, Luca lc...@essex.ac.uk wrote:
Hi Stefan,
I am afraid I did not explain myself clear enough.
Of course
c = a + b + d
leaves a, b, and d unchanged.
The only array that is overwritten is (a+b) which is a temporary
array that would be destroyed anyway.
@Charles R Harris
For example 'sqrt(a**2 + b**2)' can be performed...
I think this particular function is already available as a ufunc.
I am not sure it is implemented as ufunc.
But in any case it was just an example.
Another example is
sin(2*pi*w+phi)
that is currently implemented
On Wed, Jul 8, 2009 at 17:10, Citi, Lucalc...@essex.ac.uk wrote:
@Charles R Harris
For example 'sqrt(a**2 + b**2)' can be performed...
I think this particular function is already available as a ufunc.
I am not sure it is implemented as ufunc.
hypot(a, b)
--
Robert Kern
I have come to
On Wed, Jul 8, 2009 at 4:10 PM, Citi, Luca lc...@essex.ac.uk wrote:
@Charles R Harris
For example 'sqrt(a**2 + b**2)' can be performed...
I think this particular function is already available as a ufunc.
I am not sure it is implemented as ufunc.
But in any case it was just an example.
Hi,
Ticket #1143 points out that Numpy's reduction operations are not
always cache friendly. I worked a bit on tuning them.
Just to tickle some interest, a pathological case before optimization:
In [1]: import numpy as np
In [2]: x = np.zeros((8, 256))
In [3]: %timeit
On thing to keep in mind is that the inputs might be different views of the
same array so the elements might accessed in an unexpected order.
Only inputs owning their own data and with refcount 1 (i.e. no other array can
be a view of it)
are re-used as outputs.
On Wed, Jul 8, 2009 at 4:16 PM, Pauli Virtanen pav...@iki.fipav%2...@iki.fi
wrote:
Hi,
Ticket #1143 points out that Numpy's reduction operations are not
always cache friendly. I worked a bit on tuning them.
Just to tickle some interest, a pathological case before optimization:
In
On Wed, Jul 8, 2009 at 4:17 PM, Citi, Luca lc...@essex.ac.uk wrote:
On thing to keep in mind is that the inputs might be different views of
the
same array so the elements might accessed in an unexpected order.
Only inputs owning their own data and with refcount 1 (i.e. no other array
can
Hi Pauli
2009/7/9 Pauli Virtanen pav...@iki.fi:
Unfortunately, improving the performance using the above scheme
comes at the cost of some slightly murky heuristics. I didn't
manage to come up with an optimal decision rule, so they are
partly empirical. There is one parameter tuning the
On 2009-07-08, Charles R Harris charlesr.har...@gmail.com wrote:
[clip]
How do the benchmarks compare with just making contiguous copies? Which is
blocking of sort, I suppose.
I think that's slower than just walking over the discontiguous
array:
1) The new code: (on the Athlon
On Wed, Jul 08, 2009 at 11:01:55PM +0100, Peter wrote:
On Wed, Jul 8, 2009 at 10:00 PM, Fons Adriaensenf...@kokkinizita.net wrote:
On Sun, Jul 05, 2009 at 12:22:37AM +0200, Stéfan van der Walt wrote:
2009/7/5 Pauli Virtanen pav...@iki.fi:
2009-07-04 22:52 +0200, Fons Adriaensen
On Wed, Jul 8, 2009 at 17:53, Fons Adriaensenf...@kokkinizita.net wrote:
On Wed, Jul 08, 2009 at 11:01:55PM +0100, Peter wrote:
Anyway - fingers crossed the list is working for you
now...
I'm not convinced... Will try posting again.
And here you are.
--
Robert Kern
I have come to believe
On 2009-07-08, Stéfan van der Walt ste...@sun.ac.za wrote:
I know very little about cache optimality, so excuse the triviality of
this question: Is it possible to design this loop optimally (taking
into account certain build-time measurable parameters), or is it the
kind of thing that can only
On Wed, Jul 8, 2009 at 18:02, Pauli Virtanenpav...@iki.fi wrote:
On 2009-07-08, Stéfan van der Walt ste...@sun.ac.za wrote:
I know very little about cache optimality, so excuse the triviality of
this question: Is it possible to design this loop optimally (taking
into account certain build-time
On Thu, Jul 9, 2009 at 8:02 AM, Pauli Virtanenpav...@iki.fi wrote:
I don't think we want to go the ATNumPy route, or even have
tunable parameters chosen at build or compile time.
Detecting things like cache size at compile time should not be too
difficult, at least for common platforms. Even
Hello all,
(resending for the Nth time, as the previous attempts
didn't make it to the list)
I'm new to this list (and numpy is mostly new to me :-).
Using python 2.6 and numpy 1.3.
My plan is to write some C extensions that will perform
rather specialised processing on multichannel digital
On Wed, Jul 8, 2009 at 5:02 PM, Pauli Virtanen pav...@iki.fipav%2...@iki.fi
wrote:
On 2009-07-08, Stéfan van der Walt ste...@sun.ac.za wrote:
I know very little about cache optimality, so excuse the triviality of
this question: Is it possible to design this loop optimally (taking
into
On 2009-07-08, Charles R Harris charlesr.har...@gmail.com wrote:
In that case I don't see a problem offhand. That said, I haven't looked at
the code yet.
I'm a bit worried about the problem that cropped up in the ticket
with the complex ufuncs. As Luca noted in the ticket,
obj3 =
On Wed, Jul 8, 2009 at 18:28, Pauli Virtanenpav...@iki.fi wrote:
On 2009-07-08, Charles R Harris charlesr.har...@gmail.com wrote:
In that case I don't see a problem offhand. That said, I haven't looked at
the code yet.
I'm a bit worried about the problem that cropped up in the ticket
with
Pierre GM-2 wrote:
Would you like to give the scikits.timeseries package a try ? It's
available at pytseries.sourceforge.net.
Calculatng the hourly average should be straightforward.
I would, in fact I have been investigating it, but I didn't have numpy1.3 up
and running until just
nhmc wrote:
Also, if you don't need the indices, you can just use the conditional
expression as a boolean mask:
condition = (t1 Y[:,0]) (Y[:,0] t2)
Y[:,0][condition]
Neil
'condition' is not an index array? Wouldn't it just be the indices as well?
Would it be possible to do
Also, could someone please explain why:
Tsub = T[ (T[:,0]t1) (T[:,0]t2) ]
Works, but:
Tsub = T[ (t1T[:,0]) (T[:,0]t2) ]
Does not???
Thanks.
--
View this message in context:
http://www.nabble.com/Help-with-np.where-and-datetime-functions-tp24389447p24401687.html
Sent from the
On Wed, Jul 8, 2009 at 19:11, John [H2O]washa...@gmail.com wrote:
Also, could someone please explain why:
Tsub = T[ (T[:,0]t1) (T[:,0]t2) ]
Works, but:
Tsub = T[ (t1T[:,0]) (T[:,0]t2) ]
Does not???
I'm not positive, but I think it boils down to this: Python tries to
look up the method
Hello
The problem is not PyArray_Conjugate itself.
The problem is that whenever you call a function from the C side
and one of the inputs has ref_count 1, it can be overwritten.
This is not a problem from the python side because if the
ufunc sees a ref_count=1 it means that no python object is
On Fri, Jul 3, 2009 at 10:21 PM, Alan Jacksona...@ajackson.org wrote:
I don't see any problem here. If you can replicate your results, we
would need more information about the versions.
Josef
'''
np.version.version
'1.3.0'
scipy.version.version
'0.8.0.dev5789'
'''
In [4]:
Hey All
I am reading thru a file and trying to store the values into another
array, but instead of storing the values 1 by 1, I would like to store
them in bulk sets for optimization purposes.
Here is what I have, which does it 1x1:
z={} #dictionary
r=csv.reader(file)
for i,row in
2009/7/8 Pierre GM pgmdevl...@gmail.com:
On Jul 8, 2009, at 3:18 AM, Scott Sinclair wrote:
2009/7/8 Robert Kern robert.k...@gmail.com:
2009/7/4 Stéfan van der Walt ste...@sun.ac.za:
Thanks, Scott. This should now be fixed in SVN.
You should probably change that to asanyarray() before the
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