multiarrays.jl

# repeat can be useful to expand a grid
# as in R's expand.grid() function:

# <hide>
function printsum(a)
    println(summary(a), ": ", repr(a))
end
# </hide>

m1 = hcat(repeat([1,2],inner=[1],outer=[3*2]),
		  repeat([1,2,3],inner=[2],outer=[2]),
		  repeat([1,2,3,4],inner=[3],outer=[1]))
printsum(m1)
#> 12×3 Array{Int64,2}: [1 1 1; 2 1 1; 1 2 1; 2 2 2; 1 3 2; 2 3 2; 1 1 3; 2 1 3;
#> 	1 2 3; 2 2 4; 1 3 4; 2 3 4]

# for simple repetitions of arrays,
# use repeat
m2 = repeat(m1,1,2) 	# replicate a9 once into dim1 and twice into dim2
println("size: ", size(m2))
#> size: (12, 6)

m3 = repeat(m1,2,1) 	# replicate a9 twice into dim1 and once into dim2
println("size: ", size(m3))
#> size: (24, 3)

# Julia comprehensions are another way to easily create
# multidimensional arrays

m4 = [i+j+k for i=1:2, j=1:3, k=1:2]	# creates a 2x3x2 array of Int64
m5 = ["Hi Im # $(i+2*(j-1 + 3*(k-1)))" for i=1:2, j=1:3, k=1:2]
# expressions are very flexible
# you can specify the type of the array by just
# placing it in front of the expression

import LegacyStrings
m5 = LegacyStrings.ASCIIString["Hi Im element # $(i+2*(j-1 + 3*(k-1)))" for i=1:2, j=1:3, k=1:2]
printsum(m5)
#> 2×3×2 Array{LegacyStrings.ASCIIString,3}: LegacyStrings.ASCIIString[
#> 	"Hi Im element # 1" "Hi Im element # 3" "Hi Im element # 5";
#> 	"Hi Im element # 2" "Hi Im element # 4" "Hi Im element # 6"]
#>
#> LegacyStrings.ASCIIString["Hi Im element # 7" "Hi Im element # 9"
#> 	"Hi Im element # 11"; "Hi Im element # 8" "Hi Im element # 10" "Hi Im element # 12"]

# Array reductions
# many functions in Julia have an array method
# to be applied to specific dimensions of an array:

sum(m4, dims=3)		# takes the sum over the third dimension
sum(m4, dims=(1,3))	# sum over first and third dim

maximum(m4, dims=2)	# find the max elt along dim 2
findmax(m4, dims=3)	# find the max elt and its index along dim 3
					# (available only in very recent Julia versions)

# Broadcasting
# when you combine arrays of different sizes in an operation,
# an attempt is made to "spread" or "broadcast" the smaller array
# so that the sizes match up. broadcast operators are preceded by a dot:

m4 .+ 3		# add 3 to all elements
m4 .+ [1,2]		# adds vector [1,2] to all elements along first dim

# slices and views
m4=m4[:,:,1]	# holds dim 3 fixed
m4[:,2,:]	# that's a 2x1x2 array. not very intuititive to look at

# get rid of dimensions with size 1:
dropdims(m4[:,2,:], dims=2)	# that's better

# assign new values to a certain view
m4[:,:,1] = rand(1:6,2,3)
printsum(m4)
#> 2×3 Array{Int64,2}: [3 5 3; 1 3 5]

# (for more examples of try, catch see Error Handling above)
try
	# this will cause an error, you have to assign the correct type
	m4[:,:,1] = rand(2,3)
catch err
	println(err)
end
#> InexactError(:Int64, Int64, 0.7603891754678744)

try
	# this will cause an error, you have to assign the right shape
	m4[:,:,1] = rand(1:6,3,2)
catch err
	println(err)
end
#> DimensionMismatch("tried to assign 3×2 array to 2×3×1 destination")