The following line of code is a recursive helper function for generating the nth Fibonacci number. From Julia's REPL include("filename.jl"). It's the only line of code in the file and it won't compile. Julia ver. 4.5 and 5.1. Have tried using bracketing parentheses and also have rewritten in standard if-else format, all to no avail. This code will simply not compile for me. Can anyone see what I'm doing wrong?
helper(current, next, n) = n==0 ? current : helper(next, current+next, n-1)
Related
I have a script that defines a function, and later intended to call the function but forgot to add the parentheses, like this:
function myfunc()
println("inside myfunc")
end
myfunc # This line is silently ignored. The function isn't invoked and there's no error message.
After a while I did figure out that I was missing the parentheses, but since Julia didn't give me an error, I'm wondering what that line is actually doing? I'm assuming that it must be doing something with the myfunc statement, but I don't know Julia well enough to understand what is happening.
I tried --depwarn=yes but don't see a julia command line switch to increase the warning level or verbosity. Please let me know if one exists.
For background context, the reason this came up is that I'm trying to translate a Bash script to Julia, and there are numerous locations where an argument-less function is defined and then invoked, and in Bash you don't need parentheses after the function name to invoke it.
The script is being run from command line (julia stub.jl) and I'm using Julia 1.0.3 on macOS.
It doesn't silently ignore the function. Calling myfunc in an interactive session will show you what happens: the call returns the function object to the console, and thus call's the show method for Function, showing how many methods are currently defined for that function in your workspace.
julia> function myfunc()
println("inside myfunc")
end
myfunc (generic function with 1 method)
julia> myfunc
myfunc (generic function with 1 method)
Since you're calling this in a script, show is never called, and thus you don't see any result. But it doesn't error, because the syntax is valid.
Thanks to DNF for the helpful comment on it being in a script.
It does nothing.
As in c, an expression has a value: in c the expression _ a=1+1; _ has the value _ 2 _ In c, this just fell out of the parser: they wanted to be able to evaluate expressions like _ a==b _
In Julia, it's the result of designing a language where the code you write is handled as a data object of the language. In Julia, the expression "a=1+1" has the value "a=1+1".
In c, the fact that
a=1+1;
is an acceptable line of code means that, accidentally,
a;
is also an acceptable line of code. The same is true in Julia: the compiler expects to see a data value there: any data value you put may be acceptable: even for example the data value that represents the calculated value returned by a function:
myfunc()
or the value that represents the function object itself:
myfunc
As in c, the fact that data values are everywhere in your code just indicates that the syntax allows data values everywhere in your code and that the compiler does nothing with data values that are everywhere in your code.
How do you find out where a macro is from in Julia. I'm looking at someone's code and they're using an #debug("string") macro. There are no using statements in the particular file that would tell me where it's loaded from, so I assume it's loaded form somewhere else in the code.
I might guess at the debug module for Julia, but it doesn't seem like it's being used that way, it seems like it's being used more for logging, so I'm a bit unsure of how to track it down through the code.
A macro location can be obtained using the #which macro, this is a feature introduced in 0.5.
julia> #which #printf("%0.2f", 1/3)
#printf(args...) at printf.jl:1178
Similar to #which, you can use #edit to open the source file and #functionloc to get the function location programmatically.
You can go to help mode in the Julia repl by keyboard shortcut shfit+?
help?> #debug
No documentation found.
#debug is a macro.
# 1 method for macro "#debug":
#debug(msg...) at /home/guo/.julia/v0.5/Logging/src/logging_macros.jl:11
I guess the marco #debug is probably from the package Logging.jl.
This is probably a newbie question... but is it possible to show the definition of a (user defined) function? While debugging/optimizing it is convenient to quickly see how a certain function was programmed.
Thanks in advance.
You can use the #edit macro, which is supposed to take you to the definition of a method, similarly to how the #which macro which shows the file and line # where that particular method was defined, for example:
julia> #which push!(CDFBuf(),"foo")
push!{T<:CDF.CDFBuf}(buff::T, x) at /d/base/DA/DA.jl:105
julia> #which search("foobar","foo")
search(s::AbstractString, t::AbstractString) at strings/search.jl:146
Note that methods that are part of Julia will show a path relative to the julia source directory "base".
While this is not an automatic feature available with Julia in general (as pointed out by Stefan), if you add docstrings when you define your initial function, you can always use the help?> prompt to query this docstring. For example
julia> """mytestfunction(a::Int, b)""" function mytestfunction(a::Int, b)
return true
This attaches the docstring "mytestfunction(a::Int, b)" to the function mytestfunction(a::Int, b). Once this is defined, you can then use the Julia help prompt (by typing ? at the REPL), to query this documentation.
help?> mytestfunction
mytestfunction(a::Int, b)
Consider the following code:
File C.jl
module C
export printLength
printLength = function(arr)
println(lentgh(arr))
end
end #module
File Main.jl
using C
main = function()
arr = Array(Int64, 4)
printLength(arr)
end
main()
Let's try to execute it.
$ julia Main.jl
ERROR: lentgh not defined
in include at /usr/bin/../lib64/julia/sys.so
in process_options at /usr/bin/../lib64/julia/sys.so
in _start at /usr/bin/../lib64/julia/sys.so
while loading /home/grzes/julia_sucks/Main.jl, in expression starting on line 8
Obviously, it doesn't compile, because lentgh is misspelled. The problem is the message I received. expression starting on line 8 is simply main(). Julia hopelessly fails to point the invalid code fragment -- it just points to the invocation of main, but the erroneous line is not even in that file! Now imagine a real project where an error hides really deep in the call stack. Julia still wouldn't tell anything more than that the problem started on the entry point of the execution. It is impossible to work like that...
Is there a way to force Julia to give a little more precise messages?
In this case it's almost certainly a consequence of inlining: your printLength function is so short, it's almost certainly inlined into the call site, which is why you get the line number 8.
Eventually, it is expected that inlining won't cause problems for backtraces. At the moment, your best bet---if you're running julia's pre-release 0.4 version---is to start julia as julia --inline=no and run your tests again.
I am using the Kernel Density Estimator toolbox form http://www.ics.uci.edu/~ihler/code/kde.html . But I am getting the following error when I try to execute the demo files -
>> demo_kde_3
KDE Example #3 : Product sampling methods (single, anecdotal run)
Attempt to reference field of non-structure array.
Error in double (line 10)
if (npd.N > 0) d = 1; % return 1 if the density exists
Error in repmat (line 49)
nelems = prod(double(siz));
Error in kde (line 39)
if (size(ks,1) == 1) ks = repmat(ks,[size(points,1),1]); end;
Error in demo_kde_3 (line 8)
p = kde([.1,.45,.55,.8],.05); % create a mixture of 4 gaussians for
testing
Can anyone suggest what might be wrong? I am new to Matlab and having a hard time to figure out the problem.
Thank You,
Try changing your current directory away from the #kde folder; you may have to add the #kde folder to your path when you do this. For example run:
cd('c:\');
addpath('full\path\to\the\folder\#kde');
You may also need to add
addpath('full\path\to\the\folder\#kde\examples');
Then see if it works.
It looks like function repmat (a mathworks function) is picking up the #kde class's version of the double function, causing an error. Usually, only objects of the class #kde can invoke that functions which are in the #kde folder.
I rarely use the #folder form of class definitions, so I'm not completely sure of the semantics; I'm curious if this has any effect on the error.
In general, I would not recommend using the #folder class format for any development that you do. The mathworks overhauled their OO paradigm a few versions ago to a much more familiar (and useful) format. Use help classdef to see more. This #kde code seems to predate this upgrade.
MATLAB gives you the code line where the error occurs. As double and repmat belong to MATLAB, the bug probably is in kde.m line 39. Open that file in MATLAB debugger, set a breakpoint on that line (so the execution stops immediately before the execution of that specific line), and then when the code is stopped there, check the situation. Try the entire code line in console (copy-paste or type it, do not single-step, as causing an uncatched error while single-stepping ends the execution of code in debugger), it should give you an error (but doesn't stop execution). Then try pieces of the code of that code line, what works as it should and what not, eg. does the result of size(points, 1) make any sense.
However, debugging unfamiliar code is not an easy task, especially if you're a beginner in MATLAB. But if you learn and understand the essential datatypes of MATLAB (arrays, cell arrays and structs) and the different ways they can be addressed, and apply that knowledge to the situation on the line 39 of kde.m, hopefully you can fix the bug.
Repmat calls double and expects the built-in double to be called.
However I would guess that this is not part of that code:
if (npd.N > 0) d = 1; % return 1 if the density exists
So if all is correct this means that the buil-tin function double has been overloaded, and that this is the reason why the code crashes.
EDIT:
I see that #Pursuit has already addressed the issue but I will leave my answer in place as it describes the method of detection a bit more.