I am not sure if this is what you are looking for:
xini = 0.0
xend = 10.0
res = [xini]
x = xini
while x xend
x = nextfloat(x)
push!(res,x)
end
This will generate a quite large `res` vector...
Regarding intervals, together with David Sanders we have been working on
Thanks for sharing! Great talk
If you didn't configure your mac properly, esc-enter does the job.
julia set_bigfloat_precision(1)
1
julia big(pi)
Just a tiny little note on:
[1; 2; 3] is precisely the same thing as [1, 2, 3]
julia [1; 2; 3] == [1,2,3]
true
julia [1; 2; 3] === [1,2,3]
false
Luis
I also get the same value (4705360871073570227520) that you quoted when using
Int128; I guess that
the difference is due to some round-off error from using Float64...
On Jun 29, 2014, at 11:29 AM, gentlebeldin gentlebel...@hotmail.com wrote:
You're right, my code seems to be fast, because it
Thanks for the explanations, and sorry for the delay to answer.
I've been getting into your code to understand it in detail, since I'm not
too familiar with the functional approach. I think one important difference
among our codes, is that I represent the many-variables polynomial in its
2014 05:38:19 UTC+2 schrieb Luis Benet:
Thanks for the explanations. I really really like the trick of the dictionary
and the way you define
the functions, so everything works without fixing constants before hand. This
could make
life much simpler for our many-variable implementation
looks a bit different, cf. attachment.
Am Donnerstag, 19. Juni 2014 22:19:01 UTC+2 schrieb Luis Benet:
I have uploaded it as a gist:
http://nbviewer.ipython.org/gist/lbenet/616fa81f3c12c9cfcf97
On Jun 19, 2014, at 3:07 PM, gentlebeldin gentle...@hotmail.com wrote:
I suspected that's
.
Am Freitag, 20. Juni 2014 19:10:25 UTC+2 schrieb Luis Benet:
Hi,
I took a look on your code at night. It is very nice because its simplicity,
almost magical!.
There are few points which are not yet clear to me. I guess that by default
you calculate
at least 4 terms
I have uploaded it as a gist:
http://nbviewer.ipython.org/gist/lbenet/616fa81f3c12c9cfcf97
On Jun 19, 2014, at 3:07 PM, gentlebeldin gentlebel...@hotmail.com wrote:
I suspected that's what you meant: in theory, energy is conserved, and
looking at the real figures would tell us how good the
Hi all,
today we released TaylorSeries.jl v0.0.1
(https://github.com/lbenet/TaylorSeries.jl), which computes polynomial
expansions around a point in one and *more* independent variables using
automatic differentiation techniques. Some details on how to use it are on
the README file. We also
Hi,
can you post some information/recommendation about nearby hotels or other
accommodation possibilities?
Thanks,
Luis
Hi Hans,
Two additional packages are TaylorSeries (not in METADATA right now) and
HyperDualNumbers, which I 'derived' from the C code by the authors (see
below links).
The link where TaylorSeries.jl can be found is
https://github.com/lbenet/TaylorSeries.jl .
It implements handling
Hi,
I have followed the discussion, and would like to announce a package that
we are developing:
https://github.com/lbenet/TaylorSeries.jl
since it does a bunch of things discussed above, though so far for 1
independent variable. It expands
different functions (so far a limited number of basic
Hi Jason,
It looks like the scope of this is very similar to PowerSeries.jl. We
should do some benchmarking and API bikeshedding, and think about combining
efforts.
Are there places your new package is obviously superior? I see
L'Hospital's rule for division: that's a nice idea.
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