I am trying to write a mutating function where the value passed as first argument mutates depending on the second one.
As an example, remove_when_zero_in_b below should return the values in vector a for those indexes where vector b is not 0.
"""filters 'a' when there is a zero in 'b'"""
function remove_when_zero_in_b!(a::AbstractVector, b::Vector{<:Real})
a = a[b .!= 0]
a
end
E.g.
x = [1.0, 2.0, 3.0, 4.0, 5.0]
y = [0, 1, 0, 2 , 0 ]
remove_when_zero_in_b!(x, y) # should mutate x
Then x should be:
println(x)
2-element Vector{Float64}:
2.0
4.0
However, the function above does not mutate x and remains as the initial vector with 5 elements.
What am I missing here? How would a function mutating x so I obtain the desired result look like?
a = a[b .!= 0] create a new copy of a, you can write,
function remove_when_zero_in_b!(a::AbstractVector, b::Vector{<:Real})
deleteat!(a, b .== 0)
a
end
Related
Is there an equivalent to Python's pop? I have an array x and a boolean array flag of the same length. I would like to extract x[flag] and be able to store it in a variable x_flagged while at the same time remove them in place from x.
x = rand(1:5, 100)
flag = x .> 2
x_flagged = some_function!(x, flag) # Now x would be equal to x[x .<= 2]
Try this one using deleteat!
julia> function pop_r!(list, y) t = list[y]; deleteat!( list, y ); t end
julia> x = rand(1:5, 100)
100-element Vector{Int64}
julia> flag = x .> 2
100-element BitVector
julia> pop_r!( x, flag )
60-element Vector{Int64}
julia> x
40-element Vector{Int64}
You can use splice! with a bit of help from findall:
julia> x_flagged = splice!(x, findall(flag))
59-element Vector{Int64}:
...
julia> size(x)
(41,)
splice!(a::Vector, indices, [replacement]) -> items
Remove items at specified indices, and return a collection containing the removed items.
I am using Julia1.6
Here, X is a D-order multidimeonal array.
How can I slice from i to j on the d-th axis of X ?
Here is an exapmle in case of D=6 and d=4.
X = rand(3,5,6,6,5,6)
Y = X[:,:,:,i:j,:,:]
i and j are given values which are smaller than 6 in the above example.
You can use the built-in function selectdim
help?> selectdim
search: selectdim
selectdim(A, d::Integer, i)
Return a view of all the data of A where the index for dimension d equals i.
Equivalent to view(A,:,:,...,i,:,:,...) where i is in position d.
Examples
≡≡≡≡≡≡≡≡≡≡
julia> A = [1 2 3 4; 5 6 7 8]
2×4 Matrix{Int64}:
1 2 3 4
5 6 7 8
julia> selectdim(A, 2, 3)
2-element view(::Matrix{Int64}, :, 3) with eltype Int64:
3
7
Which would be used something like:
julia> a = rand(10,10,10,10);
julia> selectedaxis = 5
5
julia> indices = 1:2
1:2
julia> selectdim(a,selectedaxis,indices)
Notice that in the documentation example, i is an integer, but you can use ranges of the form i:j as well.
If you need to just slice on a single axis, use the built in selectdim(A, dim, index), e.g., selectdim(X, 4, i:j).
If you need to slice more than one axis at a time, you can build the array that indexes the array by first creating an array of all Colons and then filling in the specified dimensions with the specified indices.
function selectdims(A, dims, indices)
indexer = repeat(Any[:], ndims(A))
for (dim, index) in zip(dims, indices)
indexer[dim] = index
end
return A[indexer...]
end
idx = ntuple( l -> l==d ? (i:j) : (:), D)
Y = X[idx...]
I have a two-element vector whose elements can only be 0 or 1. For the sake of this example, suppose x = [0, 1]. Suppose also there are four objects y00, y01, y10, y11. My goal is to update the corresponding y (y01 in this example) according to the current value of x.
I am aware I can do this using a series of if statements:
if x == [0, 0]
y00 += 1
elseif x == [0, 1]
y01 += 1
elseif x == [1, 0]
y10 += 1
elseif x == [1, 1]
y11 += 1
end
However, I understand this can be done more succinctly using Julia's metaprogramming, although I'm unfamiliar with its usage and can't figure out how.
I want to be able to express something like y{x[1]}{x[2]} += 1 (which is obviously wrong); basically, be able to refer and modify the correct y according to the current value of x.
So far, I've been able to call the actual value of the correct y (but I can't summon the y object itself) with something like
eval(Symbol(string("y", x[1], x[2])))
I'm sorry if I did not use the appropriate lingo, but I hope I made myself clear.
There's a much more elegant way using StaticArrays. You can define a common type for your y values, which will behave like a matrix (which I assume the ys represent?), and defines a lot of things for you:
julia> mutable struct Thing2 <: FieldMatrix{2, 2, Float64}
y00::Float64
y01::Float64
y10::Float64
y11::Float64
end
julia> M = rand(Thing2)
2×2 Thing2 with indices SOneTo(2)×SOneTo(2):
0.695919 0.624941
0.404213 0.0317816
julia> M.y00 += 1
1.6959194941562996
julia> M[1, 2] += 1
1.6249412302897646
julia> M * [2, 3]
2-element SArray{Tuple{2},Float64,1,2} with indices SOneTo(2):
10.266662679181893
0.9037708026795666
(Side note: Julia indices begin at 1, so it might be more idiomatic to use one-based indices for y as well. Alternatively, can create array types with custom indexing, but that's more work, again.)
How about using x as linear indices into an array Y?
x = reshape(1:4, 2, 2)
Y = zeros(4);
Y[ x[1,2] ] += 1
Any time you find yourself naming variables with sequential numbers it's a HUGE RED FLAG that you should just use an array instead. No need to make it so complicated with a custom static array or linear indexing — you can just make y a plain old 2x2 array. The straight-forward transformation is:
y = zeros(2,2)
if x == [0, 0]
y[1,1] += 1
elseif x == [0, 1]
y[1,2] += 1
elseif x == [1, 0]
y[2,1] += 1
elseif x == [1, 1]
y[2,2] += 1
end
Now you can start seeing a pattern here and simplify this by using x as an index directly into y:
y[(x .+ 1)...] += 1
I'm doing two things there: I'm adding one to all the elements of x and then I'm splatting those elements into the indexing expression so they're treated as a two-dimensional lookup. From here, you could make this more Julian by just using one-based indices from the get-go and potentially making x a Tuple or CartesianIndex for improved performance.
With the aid of broadcasting, the following code will work whether x, y, and z are scalars, vectors of size n, or any combination thereof.
b = zeros(n)
b .= x.*y.*z .+ x
However, I'd like a for-loop. The following for-loop only works when x is a vector of size n, y is a scalar, and z is a scalar.
for i = 1:n
b[i] = x[i]*y*z + x[i]
end
To write the equivalent of b .= x.*y.*z .+ x as a for-loop for any case, I can only think of writing a for-loop for every combination of x, y, and z within if-statements. This can get messy with more variables in more complicated math expressions.
Is there a more elegant way to do what I'd like than using many if-statements?
You could define a wrapper type that indexing into it will give array indexing if wrapped variable is array and repeats the same value for all indices for scalars. I have an example below but it probably is not as efficient as using broadcast. And it is not checking if array lengths are consistent. However, a custom wrapper type would alleviate the situation.
julia> function f(x,y,z)
lx,ly,lz = length(x),length(y),length(z)
maxlen = max(lx,ly,lz)
cx = cycle(x)
cy = cycle(y)
cz = cycle(z)
b = zeros(maxlen)
#inbounds for (xi,yi,zi,i) in zip(cx,cy,cz,1:maxlen)
b[i] = xi*yi*zi+xi
end
return b
end
f (generic function with 1 method)
julia> f(1:3,21,2)
3-element Array{Float64,1}:
43.0
86.0
129.0
I am trying to construct all possible combinations of four vectors (parameters in a model) that would give me a big nx4 matrix and I could then run simulation on each set (row) of parameters. In R I would achieve this by using expand.grid in Mathematica style, I could use something like outer product with vcat and reduce the output using hcat.
Is there some function analog of expand.grid from R or outer map function?
Toy example:
A = [1 2]
B = [3 4]
some magic
output = [1 3, 1 4, 2 3, 2 4]
Using the Iterators package, it might look like this:
using Iterators
for p in product([1,2], [3,4])
println(p)
end
where you would replace println with your algorithm. You can also use collect if it's important to get the set of all combinations.
Not the exact notation you show, but a comprehension might be useful.
julia> a=[1, 2];
julia> b=[3, 4];
julia> [[i, j] for j in b, i in a]
2x2 Array{Any,2}:
[1,3] [2,3]
[1,4] [2,4]
julia> [[i, j] for j in b, i in a][:]
4-element Array{Any,1}:
[1,3]
[1,4]
[2,3]
[2,4]