%use numpy(0.1.4)

val a = array(arrayOf(1L, 2L, 3L))
val b = array<Double>(listOf(listOf(1.5f, 2f, 3f), listOf(4f, 5f, 6f)))
val c = array<Double>(
    listOf(
        listOf(listOf(1.5f, 2f, 3f), listOf(4f, 5f, 6f)),
        listOf(listOf(3f, 2f, 1f), listOf(4f, 5f, 6f))
    )
)

zeros<Int>(3, 4) // Create an array of zeros
ones<Short>(2, 3, 4) // Create an array of ones
val d = arange<Long>(10, 25, 5) // Create an array of evenly spaced values (step value)

linspace<Float>(0, 2, 9) // Create an array of evenly spaced values (number of samples)

val e = full(intArrayOf(2, 2), 7L) // Create a constant array
val f = eye<Double>(2) // Create a 2x2 identity matrix
Random.random(2, 2) // Create an array with random values
empty<Float>(3, 2) // Create an empty array

// a.toFile("my_array")
// fromfile<Long>("my_array")

a.shape // Array domensions
b.ndim // Number of array dimensions
e.size // Number of array elements
b.dtype // Dara type of array elements
b.dtype.name // Name of data type
b.asType<Double, Int>() // Convert an array to a different type

val g = a - b
println("Subtraction:")
println(a - b) // Subraction

println("Addition:")
println(b + a) // Addition

println("Division:")
println(a / b) // Division

println("Multiplication:")
println(a * b) // Multiplication

exp(b) // Exponentiation
sqrt(b) // Square root
sin(a) // Sin
cos(b) // Cos
log(a) // natural logarithm
e.dot(f) // Dot product

println("Element-wise comparison")
println(c eq b)

println("Element-wise comparison")
println(a lt 2)

println("Array comparison")
println(a == b)

a.sum() // Array sum
a.min() // Array minimum value
b.max(0) // Maximum value of an array row
b.cumSum(1) // Cumulative sum of the lements
a.mean() // Mean
median(b) // Median
corrcoef<Long, Long>(a) // Correlation coefficient
std(d) // Standard deviation

var h = a.view<Long, Long>()
copy(a)
h = copy(a)

a.sort()
c.sort(axis = 0)

println(a[2]) // Select the element at the 2nd index
println(b[1, 2]) // Select the element at row 1 column 2

println(a[0..2]) // Select items at index 0 and 1
println(b[0..2, 1]) // Select items at rows 0 and 1 in column 1

println(b[None..1]) // Select all items at row 0

println(c[1, None..None, None..None]) // Same as [1, ...] or [1, :, :] in Python
println(a[None..None..-1]) // Reversed array a

a[a lt 2] // Select elements from a less than 2

println(b[arrayOf(1, 0, 1, 0), arrayOf(0, 1, 2, 0)]) // Select elements (1,0), (0,1), (1,2) and (0, 0)

println(b[arrayOf(1, 0, 1, 0)][None..None, arrayOf(0, 1, 2, 0)]) // Select a subset of the matrix's rows and columns

// Flat array iteration
for (element in a.flatIter()) {
    print("$element ")
}
println()

// Iteration along the axes of the array
for (ax in b) {
    println(ax)
}

val i = transpose(b) // Permute array dimensions
i.t

b.ravel() // Flatten the array
g.reshape(3, -2) // Reshape, but don't chenge data

h.resize(2, 6) // Change to new array with shape (2,6)
append(h.view(), g) // Append items to an array
insert(a, 1, array(arrayOf(5L))) // Insert items in an array
delete(a, 1) // Delete items from an array

println(concatenate(a, d, axis = 0)) // Concatenate arrays

println(vstack(a.view(), b)) // Stack arrays vertically

println(hstack(e.view(), f)) // Stack arrays horizontally

println(columnStack(a, d)) // Create stacked column-wise arrays

hsplit(a, 3) // Split the array horizontally at the 3rd index