That’s probably true. But using the if construction in the high level function
is certainly fine; and avoids having to use the if in the low-level kernel,
which will be called many times.
On 22 May 2015, at 10:31, Toivo Henningsson toivo@gmail.com wrote:
I would think that calling the
R has such a function:
http://www.inside-r.org/r-doc/base/with
But given the mess that is R's scoping rules, this is perhaps not something
we should attempt to emulate. I think Toivo's suggestion is very reasonable.
On Friday, 22 May 2015 05:53:39 UTC+1, Toivo Henningsson wrote:
I think at
Thanks for the detailed response. The MathConst idea is possibly a great
suggestion which I will look into. With respect to the calling the
low-level function, I don't think there is a big difference between your
suggestion and my one-liner, as long as the return type of the function is
the
Hi
I am trying to fit a sinusoidal model (y = *a* + *b*x + *c**sin( *d* * x *
pi - *e ** pi)) to time series data. I can successfully fit an
unconstrained model with the curve_fit function using the LsqFit package.
My problem is that the frequency parameter (*d* above) needs to be in the
range
See also https://groups.google.com/d/msg/julia-users/HLLxDpaONh8/zEBlsGKZxHcJ
and the correction about get! below it.
--Tim
On Friday, May 22, 2015 01:16:10 AM Alex wrote:
Hi,
This came up recently on the mailing
list:
Hi Josha,
I am not sure if there is a function like that in the standard library. But
you can use something like this
function rsplit!(v,r)
a = Array(Vector{eltype(v)},0)
while length(v) = length(r)
push!(a, splice!(v,r))
end
!isempty(v) push!(a, v)
On Thursday, May 21, 2015 at 4:55:16 PM UTC-4, Jey Kottalam wrote:
Hi Jeff,
they relied on a 3rd party to containerize a Pythonprogram for
transmission
That is due to the pecularities of Python's serialization module than
anything intrinsic to creating a Spark binding. (E.g.
On Friday, May 22, 2015 at 5:51:04 PM UTC+10, Stéphane Mottelet wrote:
Hello,
I wonder why unique has only one output. I need the index of first
occurence of each unique row of a matrix, how can I do ?
Unique returns an array of all the unique elements, not indexes.
Thanks for
Hi,
This came up recently on the mailing
list:
https://groups.google.com/forum/#!searchin/julia-users/unique/julia-users/205gVuPuZFU/m4g5I3ehCgQJ
Maybe the discussion there helps.
Best,
Alex.
On Friday, 22 May 2015 09:51:04 UTC+2, Stéphane Mottelet wrote:
Hello,
I wonder why unique has
Hello,
I wonder why unique has only one output. I need the index of first
occurence of each unique row of a matrix, how can I do ?
Thanks for help,
S.
I would think that calling the function as in your initial example would
cause type inference to conclude Union types for alpha and beta, and cause
code generation to always use dynamic dispatch.
Another thing to consider is to make sure that the called function is still
type stable when passed a
I've noticed that a common pattern in my code is to use macroexpand inside
functions/macros to generate expressions which are then further manipulated
into what I need. As an example, here's a short function I wrote to unroll
a finite difference stencil at a wall (which is then spliced into a
BTW, I've measured throughput of Redis on my machine, and it resulted in
only 30K/sec, which is 10 times slower than ZMQ. Possibly, some hybrid
solution of several alternative backends will work.
On Saturday, May 23, 2015 at 2:04:02 AM UTC+3, Andrei Zh wrote:
It still helps a lot, because
It still helps a lot, because you can have many reporting programs, each
talking to different processes on the server, and those processes are able
to get the transactions done very quickly, with multiple write daemons and
journaling daemons doing the actual I/O from the shared buffer
Jey - just checking if you are listing what the project needs - or if you would
be able to participate to build these?
-viral
On 23-May-2015, at 7:54 am, Jey Kottalam j...@cs.berkeley.edu wrote:
The core functionality is there, but there's also more to be
implemented to have a complete
The core functionality is there, but there's also more to be
implemented to have a complete interface to spark-core:
- distributed I/O
- broadcast vars
- accumulator vars
- custom partitioners
- persistence (caching)
- missing transforms and actions
-Jey
On Fri, May 22, 2015 at 12:46 AM, Jeff
I am just curious whether someone currently uses Sumatra
https://pythonhosted.org/Sumatra/ for managing and keeping track of
scentific projects, of course, written in julia.
I just tried it but without good results.
DataFrames apparently do not allow columns to be multidimensional DataArrays.
julia DataFrame(A = 1:5, B = DataArray(reshape(1:15,(5,3
ERROR: ArgumentError: setindex!(::DataFrame, ...) only broadcasts scalars, not
arrays
in setindex! at
You dont have to worry about this, pmap distributes the work onto the workers
(one each), and once a worker is done it gets a new piece of work to do.
Am 21.05.2015 um 09:49 schrieb Fred fred.softwa...@gmail.com:
Hi !
When the number of tasks exceed the number of CPUs, is it safe to send
DataFrames was written with the intent that columns are vector-like
objects. Sometimes other objects can be used, but support of features gets
iffy. Options that might work include:
* Wrap your multidimensional object in a vector type that returns the
appropriate subset when indexed by a row.
Hello colleagues,
maybe it's obvious, how do i track down import conflicts (not in my code)?
I have here
_
_ _ _(_)_ | A fresh approach to technical computing
(_) | (_) (_)| Documentation: http://docs.julialang.org
_ _ _| |_ __ _ | Type help()
In 0.4 you can also use the Val{T} type for dispatching on particular
values (it's used in Base.LinAlg in a couple of places).
Things like this highlight how old the BLAS specification really is:
level-3 BLAS (the most recent) is now 27 years old. They were written with
machines such as the
The best way is probably to introduce a small type hierarchy for your heat
capacity specification, some of which interpolate and some of which don't.
For example,
```
abstract HeatCapacity
immutable ConstantHeatCapacity{T} : HeatCapacity
C::T
end
heatcapacity(c::ConstantHeatCapacity, x) =
Example desired behavior:
Float32 - Float32
Array{Int}- Array{Float64}
Array{Float32} - Array{Float32}
Complex{Int} - Complex{Float32}
Complex{Float32} - Complex{Float32}
Dual{Int} - Dual{Int}
etc.
In short, I want to do convert some vector/algebra over the field of S to
be over the field of T
Hi, Alex,
Thank you very much for the coding. It is really helpful. However, this
code itself can not solve all the problem because since there are two
additional requirements for this task (sorry I forgot to mention on the
first place) .
1) the sampling have to be random
2) the last few
Second code block should have
call(rsf::RunsSomeFunction, x) = rsf.f(x)
instead and, if it's not obvious from the `call` functions, I'm using 0.4 -
would be happy to hear about what the plans are for making higher-order
functions faster so I can pass them around as arguments without worrying
I'm aware of the fact that higher-order functions will currently be slow,
and you can get around this by using a package like FastAnonymous or by
using custom types:
function SomeFunction(value, par)
# do stuff with value based on parameter
end
type RunsSomeFunction
par1
end
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