A Friday 25 June 2010 21:33:43 John Salvatier escrigué:
Hello,
Does anyone know whether it is possible to use numexpr with scipy ufuncs
(such as those in scipy.special) or user made ufuncs? This functionality
would be extremely useful. I don't see them in the list of supported
functions
Hi,
la, 2010-06-26 kello 14:24 +0200, Francesc Alted kirjoitti:
[clip]
Yeah, you need to explicitly code the support for new functions in numexpr.
But another possibility, more doable, would be to code the scipy.special
functions by using numexpr as a computing back-end.
Would it be
OK, perhaps I will just continue preevaluating the expressions involving
special functions. Thank you for the help Fancesc
+1 to Pauli's suggestion.
On Sat, Jun 26, 2010 at 6:19 AM, Pauli Virtanen p...@iki.fi wrote:
Hi,
la, 2010-06-26 kello 14:24 +0200, Francesc Alted kirjoitti:
[clip]
2010/6/26 Pauli Virtanen p...@iki.fi
Hi,
la, 2010-06-26 kello 14:24 +0200, Francesc Alted kirjoitti:
[clip]
Yeah, you need to explicitly code the support for new functions in
numexpr.
But another possibility, more doable, would be to code the scipy.special
functions by using numexpr as
The context here is astronomy and optics. The real point is in the last
paragraph.
I'm looking at a paper that deals with 5 NL (nonlinear) equations and 8
unknown parameters.
A. a=a0+arctan((y-y0)/(x-x0)
B. z=V*r+S*e**(D*r)
r=sqrt((x-x0)**2+(y-y0)**2)
and
C.
Sat, 26 Jun 2010 17:51:52 +0100, Francesc Alted wrote:
[clip]
Well, I'd say that this support can be faked in numexpr easily. For
example, if one want to compute a certain ufunc called, say, sincos(x)
defined as sin(cos(x)) (okay, that's very simple, but it will suffice
for demonstration
The basic problem with nonlinear least squares fitting, as with other
nonlinear minimization problems, is that the standard algorithms find
only a local minimum. It's easy to miss the global minimum and instead
settle on a local minimum that is in fact a horrible fit.
To deal with this, there are
numpy.random.logseries(p, size=None)
but the parameters section,
Parameters:
loc : float
scale : float 0.
size : {tuple, int}
Output shape. If the given shape is, e.g., (m, n, k), then m * n * k
samples are drawn.
Notice that p loc and what about scale.
I'll file a ticket unless I am
On Sat, Jun 26, 2010 at 2:41 PM, Vincent Davis vinc...@vincentdavis.net wrote:
numpy.random.logseries(p, size=None)
but the parameters section,
Parameters:
loc : float
scale : float 0.
size : {tuple, int}
Output shape. If the given shape is, e.g., (m, n, k), then m * n * k
samples are
On Sat, Jun 26, 2010 at 4:47 PM, Vincent Davis vinc...@vincentdavis.net wrote:
On Sat, Jun 26, 2010 at 2:41 PM, Vincent Davis vinc...@vincentdavis.net
wrote:
numpy.random.logseries(p, size=None)
but the parameters section,
Parameters:
loc : float
scale : float 0.
size : {tuple, int}
On Sat, Jun 26, 2010 at 1:41 PM, Vincent Davis vinc...@vincentdavis.netwrote:
numpy.random.logseries(p, size=None)
but the parameters section,
Parameters:
loc : float
scale : float 0.
size : {tuple, int}
Output shape. If the given shape is, e.g., (m, n, k), then m * n * k
samples are
On Sat, Jun 26, 2010 at 4:58 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
On Sat, Jun 26, 2010 at 1:41 PM, Vincent Davis vinc...@vincentdavis.net
wrote:
numpy.random.logseries(p, size=None)
but the parameters section,
Parameters:
loc : float
scale : float 0.
size : {tuple, int}
On Sat, Jun 26, 2010 at 3:04 PM, josef.p...@gmail.com wrote:
On Sat, Jun 26, 2010 at 4:58 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
On Sat, Jun 26, 2010 at 1:41 PM, Vincent Davis vinc...@vincentdavis.net
wrote:
numpy.random.logseries(p, size=None)
but the parameters section,
On Sat, Jun 26, 2010 at 5:12 PM, Vincent Davis vinc...@vincentdavis.net wrote:
On Sat, Jun 26, 2010 at 3:04 PM, josef.p...@gmail.com wrote:
On Sat, Jun 26, 2010 at 4:58 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
On Sat, Jun 26, 2010 at 1:41 PM, Vincent Davis vinc...@vincentdavis.net
This is a little strange and I am not sure what is going on. Look at
the number of spaced before the first number in the array.
x = np.array([629.54440098249688162, 26186.5470310494529258 ])
x
array([ 629.54440098249688162, 26186.5470310494529258 ])
3 spaces before 629.544...
x =
On Sat, Jun 26, 2010 at 3:18 PM, josef.p...@gmail.com wrote:
On Sat, Jun 26, 2010 at 5:12 PM, Vincent Davis vinc...@vincentdavis.net
wrote:
On Sat, Jun 26, 2010 at 3:04 PM, josef.p...@gmail.com wrote:
On Sat, Jun 26, 2010 at 4:58 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
On Sat,
numpy.random.pareto, missing returns in the docs
http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.pareto.html#numpy.random.pareto
Vincent
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numpy.random.poisson docs missing Returns
http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.poisson.html#numpy.random.poisson
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On Sat, Jun 26, 2010 at 5:40 PM, Vincent Davis vinc...@vincentdavis.net wrote:
numpy.random.poisson docs missing Returns
http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.poisson.html#numpy.random.poisson
You could just copy a generic Returns section to all of these. They
all
Something is systematically wrong if there are this many problems in the
numpy.stats docstrings: numpy is supposed to be (was) almost completely
ready for review; please focus on scipy unless/until the reason why there
are now so many problems in numpy.stats can be determined (I suspect the
On Sat, Jun 26, 2010 at 5:56 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
Something is systematically wrong if there are this many problems in the
numpy.stats docstrings: numpy is supposed to be (was) almost completely
ready for review; please focus on scipy unless/until the reason why
On Sat, Jun 26, 2010 at 3:56 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
Something is systematically wrong if there are this many problems in the
numpy.stats docstrings: numpy is supposed to be (was) almost completely
ready for review; please focus on scipy unless/until the reason why
On Sat, Jun 26, 2010 at 3:03 PM, josef.p...@gmail.com wrote:
On Sat, Jun 26, 2010 at 5:56 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
Something is systematically wrong if there are this many problems in the
numpy.stats docstrings: numpy is supposed to be (was) almost completely
On Sat, Jun 26, 2010 at 6:11 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
On Sat, Jun 26, 2010 at 3:03 PM, josef.p...@gmail.com wrote:
On Sat, Jun 26, 2010 at 5:56 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
Something is systematically wrong if there are this many problems in
I added a set of simple testes for numpy.random. These test only test
that you get results and that they are stable. (see attachment)
That said I get several errors (see below) as a result I assume of how
the resent enthought 6.2 beta does the calculation (The tests results
are from numpy running
On Sat, Jun 26, 2010 at 4:22 PM, josef.p...@gmail.com wrote:
On Sat, Jun 26, 2010 at 6:11 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
On Sat, Jun 26, 2010 at 3:03 PM, josef.p...@gmail.com wrote:
On Sat, Jun 26, 2010 at 5:56 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
On Sat, Jun 26, 2010 at 3:28 PM, Vincent Davis vinc...@vincentdavis.netwrote:
On Sat, Jun 26, 2010 at 4:22 PM, josef.p...@gmail.com wrote:
On Sat, Jun 26, 2010 at 6:11 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
On Sat, Jun 26, 2010 at 3:03 PM, josef.p...@gmail.com wrote:
On
I'd really like arr.copy(order='F') to work -- is it supposed to as
its docstring says, or is it supposed to raise a TypeError as it does
now?
This is on numpy 1.4
import numpy as np
a = np.arange(10).reshape(5,2)
a
array([[0, 1],
[2, 3],
[4, 5],
[6, 7],
[8, 9]])
Kurt Smith wrote:
I'd really like arr.copy(order='F') to work -- is it supposed to as
its docstring says, or is it supposed to raise a TypeError as it does
now?
It works for me if I don't use the keyword. That is,
b = a.copy('F')
But I get the same error if I use order='F', so there
On Sat, Jun 26, 2010 at 3:22 PM, josef.p...@gmail.com wrote:
On Sat, Jun 26, 2010 at 6:11 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
On Sat, Jun 26, 2010 at 3:03 PM, josef.p...@gmail.com wrote:
On Sat, Jun 26, 2010 at 5:56 PM, David Goldsmith
d.l.goldsm...@gmail.com wrote:
Hi! The docstring for numpy.lib.function_base.sinc indicates that the
parameter has to be an ndarray, and that it will return the limiting value 1
for sinc(0). Checking to see if it should actually say array_like, I found
the following (Python 2.6):
np.sinc(np.array((0,0.5)))
array([ 1.
On Sat, Jun 26, 2010 at 23:33, David Goldsmith d.l.goldsm...@gmail.com wrote:
Hi! The docstring for numpy.lib.function_base.sinc indicates that the
parameter has to be an ndarray, and that it will return the limiting value 1
for sinc(0). Checking to see if it should actually say array_like, I
On Sat, Jun 26, 2010 at 9:39 PM, Robert Kern robert.k...@gmail.com wrote:
On Sat, Jun 26, 2010 at 23:33, David Goldsmith d.l.goldsm...@gmail.com
wrote:
Hi! The docstring for numpy.lib.function_base.sinc indicates that the
parameter has to be an ndarray, and that it will return the limiting
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