I'd like to perform FFT over an array of BigFloats in Julia, but so far I couldn't make it possible. I found FFTW.jl and followed the instructions in their docs (importall FFTW, etc.). Sadly this did not help and I'm still getting ERROR: type BigFloat not supported when running a command like fft([BigFloat(1.0)]).
Did anybody experience (and hopefully overcome) similar issues?
FFTW.jl is a wrapper to the C library FFTW which cannot handle BigFloats. You need to find a pure-Julia code, like this one in FastTransforms.jl.
Related
How would I make a 2D raycast? Also, how would I check if 2 line segments intersect (relativity the same thing in my eyes, probably different though). I am not using unity or anything, I am just using plain python (I can translate from most languages to python so I don't really care what language you use) and don't want to use a library so I can learn. But every article I look at has no actual explanation, it just shows code. I've looked at the Geeks4Geeks one and that also really only shows code and does not explain what it does. So if someone could explain it that would be helpful.
I am new to Julia. Have a quick question.
In Fortran, we can do
implicit none
Therefore whenever we use a variable, we need to define it first. Otherwise it will give error.
In Julia, I want to do the same time thing. I want to define the type of each variable first, like Float64, Int64, etc. So that I wish that Julia no longer need to automatically do type conversion, which may slow down the code.
Because I know if Julia code looks like Fortran it usually runs fast.
So, in short, is there a way in Julia such that, I can force it to only use variables whose types has been defined, and otherwise give me an error message? I just want to be strict.
I just wanted to define all the variables first, then use them. Just like Fortran does.
Thanks!
[Edit]
As suggested by the experts who answers the questions, thank you very much! I know that perhaps in Julia there is no need to manually define each variables one by one. Because for one thing, if I do that, the code will become just like Fortran, and it can be very very long especially if I have many variables.
But if I do not define the type of the each variables, is Julia smart enough to know the type? Will it do some conversions which may slow down the code?
Also, even if there is no need to define variables one by one, is there in some situations we may have to manually define the type manually?
No, this is not possible* as such. You can, however, add type annotations at any point in your code, which will raise an error if the variable is not of the expected type:
julia> i = 1
1
julia> i::Int64
1
julia> i = 1.0
1.0
julia> i::Int64
ERROR: TypeError: in typeassert, expected Int64, got a value of type Float64
Stacktrace:
[1] top-level scope
# REPL[4]:1
julia> i=0x01::UInt8
0x01
*Julia is a dynamically-typed language, though there are packages such as https://github.com/aviatesk/JET.jl for static type-checking (i.e., no type annotations required) and https://github.com/JuliaDebug/Cthulhu.jl for exploring Julia's type inference system.
Strict type declaration is not how you achieve performance in Julia.
You achieve the performance by type stability.
Moreover declaring the types is usually not recommended because it decreases interoperability.
Consider the following function:
f(x::Int) = rand() < 4+x ? 1 : "0"
The types of everything seem to be known. However, this is a terrible (from performance point of view) function because the type of output can not be calcuated by looking types of input. And this is exactly how you write the performant code with regard to types.
So how to check your code? There is a special macro #code_warntype to detect such cases so you can correct your code:
Another type related issue are the containers that should not be specified by abstract elements. So you never want to have neither Vector{Any} nor Vector{Real} - rather than that you want Vector{Int} or Vector{Float64}.
See also https://docs.julialang.org/en/v1/manual/performance-tips/ for further discussion.
As I was looking through a bunch of the Flux.jl tutorials here: https://fluxml.ai/tutorials.html many of them use the syntax |> gpu throughout the tutorials. I understand this has something to do with the GPU but what is this special syntax doing?
The syntax you are seeing used here is not specific to Flux.jl but rather a general Julia syntax which simple wraps the statement on the left of the |> in whatever function is on the right. So in this case, it is equivalent do just doing gpu(some_statement) where the some_statement represent the code on the left of the |>.
Read more about this paradigm (Function piping and composition) in the Julia docs: https://docs.julialang.org/en/v1/manual/functions/#Function-composition-and-piping
Could somebody please explain to me what this message might mean?
I have the Julia client running in Atom, and my code works properly and it gets me the results, but for some line executions(ctrl+enter) the instant eval gives me "julia-client: can't render lazy".
It appears that the behind the scenes the code is executed, but the inline evaluations prefers not to output anything.
The lines corresponding to these messages usually should return a 2 dimensional arrays or dataframes, and in Julia usually the type and the dimensions are printed in the eval, but for some specific lines it can't render.
I could not find similar reports anywhere else.
julia version 0.5.0-rc3
This is a problem with package versions being out of sync. It's you're on the Julia release (v0.5), this will be fixed with a Pkg.update(). In the future, this kind of question is better suited for the Juno discussion board
I'm working with large numbers that I can't have rounded off. Using Lua's standard math library, there seem to be no convenient way to preserve precision past some internal limit. I also see there are several libraries that can be loaded to work with big numbers:
http://oss.digirati.com.br/luabignum/
http://www.tc.umn.edu/~ringx004/mapm-main.html
http://lua-users.org/lists/lua-l/2002-02/msg00312.html (might be identical to #2)
http://www.gammon.com.au/scripts/doc.php?general=lua_bc (but I can't find any source)
Further, there are many libraries in C that could be called from Lua, if the bindings where established.
Have you had any experience with one or more of these libraries?
Using lbc instead of lmapm would be easier because lbc is self-contained.
local bc = require"bc"
s=bc.pow(2,1000):tostring()
z=0
for i=1,#s do
z=z+s:byte(i)-("0"):byte(1)
end
print(z)
I used Norman Ramsey's suggestion to solve Project Euler problem #16. I don't think it's a spoiler to say that the crux of the problem is calculating a 303 digit integer accurately.
Here are the steps I needed to install and use the library:
Lua needs to be built with dynamic loading enabled. I use Cygwin, but I changed PLAT in src/Makefile to be linux. The default, none, doesn't enable dynamic loading.
The MAMP needs to be built and installed somewhere that your C compiler can find it. I put libmapm.a in /usr/local/lib/. Next m_apm.h and m_apm_lc.h went to /usr/local/include/.
The makefile for lmamp needs to be altered to the correct location of the Lua and MAMP libraries. For me, that means uncommenting the second declaration of LUA, LUAINC, LUALIB, and LUABIN and editing the declaration of MAMP.
Finally, mapm.so needs to be placed somewhere that Lua will find it. I put it at /usr/local/lib/lua/5.1/.
Thank you all for the suggestions!
The lmapm library by Luiz Figueiredo, one of the authors of the Lua language.
I can't really answer, but I will add LGMP, a GMP binding. Not used.
Not my field of expertise, but I would expect the GNU multiple precision arithmetic library to be quite a standard here, no?
Though not arbitrary precision, Lua decNumber, a Lua 5.1 wrapper for IBM decNumber, implements the proposed General Decimal Arithmetic standard IEEE 754r. It has the Lua 5.1 arithmetic operators and more, full control over rounding modes, and working precision up to 69 decimal digits.
There are several libraries for the problem, each one with your advantages
and disadvantages, the best choice depends on your requeriments. I would say
lbc is a good first pick if it
fulfills your requirements or any other by Luiz Figueiredo. For the most efficient one I guess would be any using GMP bindings as GMP is a standard C library for dealing with large integers and is very well optimized.
Nevertheless in case you are looking for a pure Lua one, lua-bint
library could be an option for dealing with big integers,
I wouldn't say it's the best because there are more efficient
and complete ones such the ones mentioned above, but usually they requires compiling C code
or can be troublesome to setup. However when comparing pure Lua big integer libraries
and depending in your use case it could perhaps be an efficient choice. The library is documented,
code fully covered by tests and have many examples. But take this recommendation with grant of
salt because I am the library author.
To install you can use luarocks if you already have it in your computer or simply download the
bint.lua
file in your project, as it has no other dependencies other than requiring Lua 5.3+.
Here is a small example using it to solve the problem #16 from Project Euler
(mentioned in previous answers):
local bint = require 'bint'(1024)
local n = bint(1) << 1000
local digits = tostring(n)
local sum = 0
for i=1,#digits do
sum = sum + tonumber(digits:sub(i,i))
end
print(sum) -- should output 1366