Vector operation koans

koans/VectorOperationKoans.jl

@@ -1,2 +1,90 @@
 module VectorOperationKoans
+using LinearAlgebra
+
+    #=
+    Vectors are a commmon data structure containers present in most common programming
+    languages. Particularly in Julia, they are represented as a 1D Array. Also, basic linear algebra
+    operations are useful for common needed calculations such as norms and distances.
+    Here is some useful documentation for arrays (and vectors) in Julia and the LinearAlgebra module:
+        - https://docs.julialang.org/en/v1/base/arrays/
+        - https://docs.julialang.org/en/v1/stdlib/LinearAlgebra/
+    =#
+
+function vector_length(vec)
+    #=
+     Return the length of the vector "vec".
+     Ex: vec = [ 9, 5, 6]; return 3.
+    =#
+end
+
+function range_1_to_n(n)
+    #=
+     Return a vector with ordered elements from 1 to n.
+     Ex: n = 5; return [1, 2, 3, 4, 5].
+    =#
+end
+
+function vector_of_zeros(n)
+    #=
+     Return a vector with n zero elements.
+     Ex: n = 4; return [0, 0, 0, 0].
+    =#
+end
+
+function vector_of_ones(n)
+    #=
+     Return a vector with n ones.
+     Ex: n = 3; return [1, 1, 1].
+    =#
+end
+
+function elementwise_sum(x, y)
+    #=
+     Return the element-wise sum of the vectors x and y.
+     Ex: x = [2, 4, 6]; y = [8, 0, -1]; return [10, 4, 5].
+    =#
+end
+
+function elementwise_substraction(x, y)
+    #=
+     Return the element-wise substraction of the vectors x and y.
+     Ex: x = [2, 4, 6]; y = [8, 0, -1]; return [-6, 4, 7].
+    =#
+end
+
+function scalar_vector_addition(vec, k)
+    #=
+     Return the outcome of adding the scalar k to the vector vec.
+     Ex: k = 2; vec = [3, 4, 5]; return [5, 6, 7].
+    =#
+end
+
+function scalar_vector_multiplication(vec, k)
+    #=
+     Return the outcome of multiplying the scalar k to the vector vec.
+     Ex: k = 2; vec = [3, 4, 5]; return [6, 8, 10].
+    =#
+end
+
+function scalar_product(x, y)
+    #=
+     Return the scalar or dot product of x and y.
+     Ex: x = [2, 4, 6]; y = [3, 7, 8]; return 82 (2*3 + 4*7 + 8*6).
+    =#
+end
+
+function norm_l2(x)
+    #=
+     Return the norm L2 of the vector x.
+     Ex: x = [4, -3, 7]; return ≈ 8.6 (sqrt(4*4 + -3*-3 + 7*7))
+    =#
+end
+
+function euclidean_distance(x, y)
+    #=
+     Return the euclidean distance between x and y.
+     Ex: x = [1, 2, 4]; y = [ 5, 6, 7]; return ≈ 6.4 (sqrt( (1-5)^2 + (2-6)^2 + (4-7)^2 ))
+    =#
+end
+
 end

solutions/VectorOperationKoans.jl

@@ -0,0 +1,101 @@
+module VectorOperationKoans
+using LinearAlgebra
+
+    #=
+    Vectors are a commmon data structure containers present in most common programming
+    languages. Particularly in Julia, they are represented as a 1D Array. Also, basic linear algebra
+    operations are useful for common needed calculations such as norms and distances.
+    Here is some useful documentation for arrays (and vectors) in Julia and the LinearAlgebra module:
+        - https://docs.julialang.org/en/v1/base/arrays/
+        - https://docs.julialang.org/en/v1/stdlib/LinearAlgebra/
+    =#
+
+function vector_length(vec)
+    #=
+     Return the length of the vector "vec".
+     Ex: vec = [ 9, 5, 6]; return 3.
+    =#
+    return length(vec)
+end
+
+function range_1_to_n(n)
+    #=
+     Return a vector with ordered elements from 1 to n.
+     Ex: n = 5; return [1, 2, 3, 4, 5].
+    =#
+    return collect(1:n)
+end
+
+function vector_of_zeros(n)
+    #=
+     Return a vector with n zero elements.
+     Ex: n = 4; return [0, 0, 0, 0].
+    =#
+    return zeros(n)
+end
+
+function vector_of_ones(n)
+    #=
+     Return a vector with n ones.
+     Ex: n = 3; return [1, 1, 1].
+    =#
+    return ones(n)
+end
+
+function elementwise_sum(x, y)
+    #=
+     Return the element-wise sum of the vectors x and y.
+     Ex: x = [2, 4, 6]; y = [8, 0, -1]; return [10, 4, 5].
+    =#
+    return x+y
+end
+
+function elementwise_substraction(x, y)
+    #=
+     Return the element-wise substraction of the vectors x and y.
+     Ex: x = [2, 4, 6]; y = [8, 0, -1]; return [-6, 4, 7].
+    =#
+    return x-y
+end
+
+function scalar_vector_addition(vec, k)
+    #=
+     Return the outcome of adding the scalar k to the vector vec.
+     Ex: k = 2; vec = [3, 4, 5]; return [5, 6, 7].
+    =#
+    return vec.+k
+end
+
+function scalar_vector_multiplication(vec, k)
+    #=
+     Return the outcome of multiplying the scalar k to the vector vec.
+     Ex: k = 2; vec = [3, 4, 5]; return [6, 8, 10].
+    =#
+    return k*vec
+end
+
+function scalar_product(x, y)
+    #=
+     Return the scalar or dot product of x and y.
+     Ex: x = [2, 4, 6]; y = [3, 7, 8]; return 82 (2*3 + 4*7 + 8*6).
+    =#
+    return dot(x, y)
+end
+
+function norm_l2(x)
+    #=
+     Return the norm L2 of the vector x.
+     Ex: x = [4, -3, 7]; return ≈ 8.6 (sqrt(4*4 + -3*-3 + 7*7))
+    =#
+    norm(x)
+end
+
+function euclidean_distance(x, y)
+    #=
+     Return the euclidean distance between x and y.
+     Ex: x = [1, 2, 4]; y = [ 5, 6, 7]; return ≈ 6.4 (sqrt( (1-5)^2 + (2-6)^2 + (4-7)^2 ))
+    =#
+    norm(x-y)
+end
+
+end

tests/solutions/tests_solutions.jl

@@ -56,9 +56,34 @@ end
 # @testset "Arrays" begin
 # end
 
-# using VectorOperationKoans
-# @testset "Vector Operators" begin
-# end
+
+using VectorOperationKoans
+@testset "Vector Operation" begin
+    @test VectorOperationKoans.vector_length([1,2,3]) == 3
+    @test VectorOperationKoans.vector_length([1]) == 1
+    @test VectorOperationKoans.range_1_to_n(3) == [1, 2, 3]
+    @test VectorOperationKoans.range_1_to_n(10) == [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
+    @test VectorOperationKoans.vector_of_zeros(3) == [0, 0, 0]
+    @test VectorOperationKoans.vector_of_zeros(9) == [0, 0, 0, 0, 0, 0, 0, 0, 0]
+    @test VectorOperationKoans.vector_of_ones(3) == [1, 1, 1]
+    @test VectorOperationKoans.vector_of_ones(9) == [1, 1, 1, 1, 1, 1, 1, 1, 1]
+    @test VectorOperationKoans.elementwise_sum([2, 3], [3, 5]) == [5, 8]
+    @test VectorOperationKoans.elementwise_sum([-2, 3], [3, -5]) == [1, -2]
+    @test VectorOperationKoans.elementwise_sum([0, 3], [3, -5]) == [3, -2]
+    @test VectorOperationKoans.elementwise_substraction([0, 3],[3, -5]) == [-3, 8]
+    @test VectorOperationKoans.elementwise_substraction([1, 10],[40, -95]) == [-39, 105]
+    @test VectorOperationKoans.scalar_vector_addition([1, 2, 3], 4) == [5, 6, 7]
+    @test VectorOperationKoans.scalar_vector_addition([-10, 30], -40) == [-50, -10]
+    @test VectorOperationKoans.scalar_vector_addition([-10, 30], -40) == [-50, -10]
+    @test VectorOperationKoans.scalar_vector_multiplication([1, 5, 10], 4) == [4, 20, 40]
+    @test VectorOperationKoans.scalar_vector_multiplication([0, -3, 5, 6], 3) == [0, -9, 15, 18]
+    @test VectorOperationKoans.scalar_product([1, 2], [3, 4]) == 11
+    @test VectorOperationKoans.scalar_product([-4, 6], [6, 8]) == 24
+    @test VectorOperationKoans.norm_l2([1, 1]) == sqrt(2)
+    @test VectorOperationKoans.norm_l2([4, -10]) == sqrt(116)
+    @test VectorOperationKoans.euclidean_distance([1, 3], [3, 5]) == sqrt(8)
+    @test VectorOperationKoans.euclidean_distance([3, 5, 8], [3, -5, 0]) == sqrt(164)
+end
 
 # using MultiDimensionalArrayKoans
 # @testset "Multi-dimensional Arrays" begin

tests/tests.jl

@@ -132,3 +132,32 @@ using PythonInterop
     @test PythonInterop.jlfib(5, pyfib) == 5
     @test PythonInterop.jlfib(7, pyfib) == 13
 end
+
+using VectorOperationKoans
+@testset "Vector Operation" begin
+    @test VectorOperationKoans.vector_length([1,2,3]) == 3
+    @test VectorOperationKoans.vector_length([1]) == 1
+    @test VectorOperationKoans.range_1_to_n(3) == [1, 2, 3]
+    @test VectorOperationKoans.range_1_to_n(10) == [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
+    @test VectorOperationKoans.vector_of_zeros(3) == [0, 0, 0]
+    @test VectorOperationKoans.vector_of_zeros(9) == [0, 0, 0, 0, 0, 0, 0, 0, 0]
+    @test VectorOperationKoans.vector_of_ones(3) == [1, 1, 1]
+    @test VectorOperationKoans.vector_of_ones(9) == [1, 1, 1, 1, 1, 1, 1, 1, 1]
+    @test VectorOperationKoans.elementwise_sum([2, 3], [3, 5]) == [5, 8]
+    @test VectorOperationKoans.elementwise_sum([-2, 3], [3, -5]) == [1, -2]
+    @test VectorOperationKoans.elementwise_sum([0, 3], [3, -5]) == [3, -2]
+    @test VectorOperationKoans.elementwise_substraction([0, 3],[3, -5]) == [-3, 8]
+    @test VectorOperationKoans.elementwise_substraction([1, 10],[40, -95]) == [-39, 105]
+    @test VectorOperationKoans.scalar_vector_addition([1, 2, 3], 4) == [5, 6, 7]
+    @test VectorOperationKoans.scalar_vector_addition([-10, 30], -40) == [-50, -10]
+    @test VectorOperationKoans.scalar_vector_addition([-10, 30], -40) == [-50, -10]
+    @test VectorOperationKoans.scalar_vector_multiplication([1, 5, 10], 4) == [4, 20, 40]
+    @test VectorOperationKoans.scalar_vector_multiplication([0, -3, 5, 6], 3) == [0, -9, 15, 18]
+    @test VectorOperationKoans.scalar_product([1, 2], [3, 4]) == 11
+    @test VectorOperationKoans.scalar_product([-4, 6], [6, 8]) == 24
+    @test VectorOperationKoans.norm_l2([1, 1]) == sqrt(2)
+    @test VectorOperationKoans.norm_l2([4, -10]) == sqrt(116)
+    @test VectorOperationKoans.euclidean_distance([1, 3], [3, 5]) == sqrt(8)
+    @test VectorOperationKoans.euclidean_distance([3, 5, 8], [3, -5, 0]) == sqrt(164)
+end
+