On Thu, Nov 22, 2012 at 6:20 AM, Francesc Alted wrote:
> As Nathaniel said, there is not a difference in terms of *what* is
> computed. However, the methods that you suggested actually differ on
> *how* they are computed, and that has dramatic effects on the time
> used. For example:
>
> In []:
On Fri, Nov 23, 2012 at 4:38 AM, Bob Dowling wrote:
> I have a simple function defined in the following snippet:
>
> --- start ---
> import numpy
>
> def chebyshev(x, m):
> '''Calculates Chebyshev functions of the first kind using the
> trigonometric identities.'''
>
> theta = numpy.w
On Fri, Nov 23, 2012 at 7:53 AM, Sebastian Berg
wrote:
> On Fri, 2012-11-23 at 10:49 +, Nathaniel Smith wrote:
> > On 23 Nov 2012 03:34, "Charles R Harris"
> > wrote:
> > >
> > > Examples,
> > >
> > > In [13]: ones(()).flags.writeable
> > > Out[13]: True
> > >
> > > In [14]: (-ones(())).flags
hi all,
I'm glad to inform you that stochastic programming and optimization addon
for FuncDesigner v. 0.421 has been released.
Now you can use gradient-based solvers for numerical optimization, such
as ALGENCAN, IPOPT, ralg, gsubg etc. Usually they work faster than
derivative-free (such as scip
On Fri, 2012-11-23 at 10:49 +, Nathaniel Smith wrote:
> On 23 Nov 2012 03:34, "Charles R Harris"
> wrote:
> >
> > Examples,
> >
> > In [13]: ones(()).flags.writeable
> > Out[13]: True
> >
> > In [14]: (-ones(())).flags.writeable
> > Out[14]: False
> >
> > In [15]: (-1*ones(())).flags.writeable
> You may want to use this:
> http://docs.scipy.org/doc/numpy/reference/generated/numpy.piecewise.html
Thank you. That's just what I needed.
Works a treat:
--- start ---
import numpy
def chebyshev(x, m):
'''Calculates Chebyshev functions of the first kind using the
trigonometric identi
Bob Dowling cam.ac.uk> writes:
[clip]
> I'm guessing that numpy.where() is evaluating the complete arccos and
> arccosh arrays and therefore getting invalid arguments.
>
> Now, I can turn off the warnings with numpy.seterr(invalid='ignore') but
> that's not what I would regard as good practice.
I have a simple function defined in the following snippet:
--- start ---
import numpy
def chebyshev(x, m):
'''Calculates Chebyshev functions of the first kind using the
trigonometric identities.'''
theta = numpy.where(
numpy.abs(x)<=1.0,
numpy.arccos(x),
n
On 23 Nov 2012 03:34, "Charles R Harris" wrote:
>
> Examples,
>
> In [13]: ones(()).flags.writeable
> Out[13]: True
>
> In [14]: (-ones(())).flags.writeable
> Out[14]: False
>
> In [15]: (-1*ones(())).flags.writeable
> Out[15]: False
>
> In [16]: (1 + ones(())).flags.writeable
> Out[16]: False
>
>
