Is there a command that will prevent Julia from printing out all of the values in an array when I create it? This can be annoying when creating large arrays in the REPL. For example when I run this:
julia> bigArray = Array[ [1:1000000], [1:1000000] ]
I would rather it not print all of the values to the console. Any help is appreciated!
Add a semicolon
julia> bigArray = Array[ [1:1000000], [1:1000000] ];
Related
The result variable is a json-type string, which is very long. What is the option in Julia REPL that allows only a limited output when the variable is this long? DataFrame is originally only partially output. I hope that the general variables will also be output like that.
You can overwrite the display method for AbstractStrings:
import Main.display
display(x::AbstractString) =
show(length(x)<=50 ? x : SubString(x,1,50)*"…")
Let us test it:
julia> str = join(rand('a':'z', 200))
"wcbifwzglgqyenrcdgdxagohlwdoxrrumoaltklkjauptwzrmi…"
I have an array a=rand(100), I want to get every value except the values at the indices notidx=[2;50]. Is there a clean way to get a at the other values? I am looking for a good way to do both a copy and a view.
Currently I make the array [1;3:49;51:100] by symdiff(1:100,notidx), but a[symdiff(1:length(a),notidx)] and view(a,a[symdiff(1:length(a),notidx)]) are not very clean (or understandable to others) ways of doing this.
I don't have anything super clean, but you can do
a[setdiff(1:end, notidx)]
which is slightly cleaner than what you had, or
ind = trues(length(a))
ind[notidx] = false
a[ind]
which is pretty verbose but very clear.
Update:
If you are using julia-v0.5+, you can also use the new generator expression, for example:
view(a, [i for i in indices(a)... if i ∉ notidx])
and
[a[i] for i in indices(a)... if i ∉ notidx]
Old post:
To get a copy, you can firstly make a copy of a, then manipulate it with deleteat! to delete those values at specific indices. After you've done this, it's convenient to get a view of a via indexin:
a = rand(100)
# => 100-element Array{Float64,1}:
0.62636
0.488919
0.499884
....
b = copy(a)
deleteat!(b, [2,50])
# => 98-element Array{Float64,1}:
0.62636
0.499884
....
Is there a way to enforce a dictionary being constant?
I have a function which reads out a file for parameters (and ignores comments) and stores it in a dict:
function getparameters(filename::AbstractString)
f = open(filename,"r")
dict = Dict{AbstractString, AbstractString}()
for ln in eachline(f)
m = match(r"^\s*(?P<key>\w+)\s+(?P<value>[\w+-.]+)", ln)
if m != nothing
dict[m[:key]] = m[:value]
end
end
close(f)
return dict
end
This works just fine. Since i have a lot of parameters, which i will end up using on different places, my idea was to let this dict be global. And as we all know, global variables are not that great, so i wanted to ensure that the dict and its members are immutable.
Is this a good approach? How do i do it? Do i have to do it?
Bonus answerable stuff :)
Is my code even ok? (it is the first thing i did with julia, and coming from c/c++ and python i have the tendencies to do things differently.) Do i need to check whether the file is actually open? Is my reading of the file "julia"-like? I could also readall and then use eachmatch. I don't see the "right way to do it" (like in python).
Why not use an ImmutableDict? It's defined in base but not exported. You use one as follows:
julia> id = Base.ImmutableDict("key1"=>1)
Base.ImmutableDict{String,Int64} with 1 entry:
"key1" => 1
julia> id["key1"]
1
julia> id["key1"] = 2
ERROR: MethodError: no method matching setindex!(::Base.ImmutableDict{String,Int64}, ::Int64, ::String)
in eval(::Module, ::Any) at .\boot.jl:234
in macro expansion at .\REPL.jl:92 [inlined]
in (::Base.REPL.##1#2{Base.REPL.REPLBackend})() at .\event.jl:46
julia> id2 = Base.ImmutableDict(id,"key2"=>2)
Base.ImmutableDict{String,Int64} with 2 entries:
"key2" => 2
"key1" => 1
julia> id.value
1
You may want to define a constructor which takes in an array of pairs (or keys and values) and uses that algorithm to define the whole dict (that's the only way to do so, see the note at the bottom).
Just an added note, the actual internal representation is that each dictionary only contains one key-value pair, and a dictionary. The get method just walks through the dictionaries checking if it has the right value. The reason for this is because arrays are mutable: if you did a naive construction of an immutable type with a mutable field, the field is still mutable and thus while id["key1"]=2 wouldn't work, id.keys[1]=2 would. They go around this by not using a mutable type for holding the values (thus holding only single values) and then also holding an immutable dict. If you wanted to make this work directly on arrays, you could use something like ImmutableArrays.jl but I don't think that you'd get a performance advantage because you'd still have to loop through the array when checking for a key...
First off, I am new to Julia (I have been using/learning it since only two weeks). So do not put any confidence in what I am going to say unless it is validated by others.
The dictionary data structure Dict is defined here
julia/base/dict.jl
There is also a data structure called ImmutableDict in that file. However as const variables aren't actually const why would immutable dictionaries be immutable?
The comment states:
ImmutableDict is a Dictionary implemented as an immutable linked list,
which is optimal for small dictionaries that are constructed over many individual insertions
Note that it is not possible to remove a value, although it can be partially overridden and hidden
by inserting a new value with the same key
So let us call what you want to define as a dictionary UnmodifiableDict to avoid confusion. Such object would probably have
a similar data structure as Dict.
a constructor that takes a Dict as input to fill its data structure.
specialization (a new dispatch?) of the the method setindex! that is called by the operator [] =
in order to forbid modification of the data structure. This should be the case of all other functions that end with ! and hence modify the data.
As far as I understood, It is only possible to have subtypes of abstract types. Therefore you can't make UnmodifiableDict as a subtype of Dict and only redefine functions such as setindex!
Unfortunately this is a needed restriction for having run-time types and not compile-time types. You can't have such a good performance without a few restrictions.
Bottom line:
The only solution I see is to copy paste the code of the type Dict and its functions, replace Dict by UnmodifiableDict everywhere and modify the functions that end with ! to raise an exception if called.
you may also want to have a look at those threads.
https://groups.google.com/forum/#!topic/julia-users/n-lqjybIO_w
https://github.com/JuliaLang/julia/issues/1974
REVISION
Thanks to Chris Rackauckas for pointing out the error in my earlier response. I'll leave it below as an illustration of what doesn't work. But, Chris is right, the const declaration doesn't actually seem to improve performance when you feed the dictionary into the function. Thus, see Chris' answer for the best resolution to this issue:
D1 = [i => sind(i) for i = 0.0:5:3600];
const D2 = [i => sind(i) for i = 0.0:5:3600];
function test(D)
for jdx = 1:1000
# D[2] = 2
for idx = 0.0:5:3600
a = D[idx]
end
end
end
## Times given after an initial run to allow for compiling
#time test(D1); # 0.017789 seconds (4 allocations: 160 bytes)
#time test(D2); # 0.015075 seconds (4 allocations: 160 bytes)
Old Response
If you want your dictionary to be a constant, you can use:
const MyDict = getparameters( .. )
Update Keep in mind though that in base Julia, unlike some other languages, it's not that you cannot redefine constants, instead, it's just that you get a warning when doing so.
julia> const a = 2
2
julia> a = 3
WARNING: redefining constant a
3
julia> a
3
It is odd that you don't get the constant redefinition warning when adding a new key-val pair to the dictionary. But, you still see the performance boost from declaring it as a constant:
D1 = [i => sind(i) for i = 0.0:5:3600];
const D2 = [i => sind(i) for i = 0.0:5:3600];
function test1()
for jdx = 1:1000
for idx = 0.0:5:3600
a = D1[idx]
end
end
end
function test2()
for jdx = 1:1000
for idx = 0.0:5:3600
a = D2[idx]
end
end
end
## Times given after an initial run to allow for compiling
#time test1(); # 0.049204 seconds (1.44 M allocations: 22.003 MB, 5.64% gc time)
#time test2(); # 0.013657 seconds (4 allocations: 160 bytes)
To add to the existing answers, if you like immutability and would like to get performant (but still persistent) operations which change and extend the dictionary, check out FunctionalCollections.jl's PersistentHashMap type.
If you want to maximize performance and take maximal advantage of immutability, and you don't plan on doing any operations on the dictionary whatsoever, consider implementing a perfect hash function-based dictionary. In fact, if your dictionary is a compile-time constant, these can even be computed ahead of time (using metaprogramming) and precompiled.
lets say I have written a function for adding two numbers.
function [result] = add_twonum(a1,a2)
result = a1+a2;
endfunction
in the main file, when I call
result = add_twonum(1,2)
I expect result = 3 .
However it says
!--error 4
Undefined variable: add_twonum
Please help me. I have used Matlab a lot but never scilab. I tried every possible way I know of. like changing current directory etc etc.
In the main file, you need to execute the function first, with
exec('add_twonum.sci');
assuming add_twonum.sci is the file which contains your function. Then you can call the function:
result = add_twonum(a1,a2);
Problem
I read in an array of strings from a file.
julia> file = open("word-pairs.txt");
julia> lines = readlines(file);
But Julia doesn't know that they're strings.
julia> typeof(lines)
Array{Any,1}
Question
Can I tell Julia this somehow?
Is it possible to insert type information onto a computed result?
It would be helpful to know the context where this is an issue, because there might be a better way to express what you need - or there could be a subtle bug somewhere.
Can I tell Julia this somehow?
No, because the readlines function explicitly creates an Any array (a = {}): https://github.com/JuliaLang/julia/blob/master/base/io.jl#L230
Is it possible to insert type information onto a computed result?
You can convert the array:
r = convert(Array{ASCIIString,1}, w)
Or, create your own readstrings function based on the link above, but using ASCIIString[] for the collection array instead of {}.
Isaiah is right about the limits of readlines. More generally, often you can say
n = length(A)::Int
when generic type inference fails but you can guarantee the type in your particular case.
As of 0.3.4:
julia> typeof(lines)
Array{Union(ASCIIString,UTF8String),1}
I just wanted to warn against:
convert(Array{ASCIIString,1}, lines)
that can fail (for non-ASCII) while I guess, in this case nothing needs to be done, this should work:
convert(Array{UTF8String,1}, lines)