module arrays // Common arrays functions: // - min / max - return the value of the minumum / maximum // - idx_min / idx_max - return the index of the first minumum / maximum // - merge - combine two sorted arrays and maintain sorted order // - chunk - chunk array to arrays with n elements // - window - get snapshots of the window of the given size sliding along array with the given step, where each snapshot is an array // - group - merge two arrays by interleaving e.g. arrays.group([1,3,5], [2,4,6]) => [[1,2],[3,4],[5,6]] // - flatten - reduce dimensionality of array by one. e.g. arrays.flatten([[1,2],[3,4],[5,6]]) => [1,2,3,4,5,6] // min returns the minimum value in the array // Example: arrays.min([1,2,3,0,9]) // => 0 pub fn min(a []T) ?T { if a.len == 0 { return error('.min called on an empty array') } mut val := a[0] for e in a { if e < val { val = e } } return val } // max returns the maximum the maximum value in the array // Example: arrays.max([1,2,3,0,9]) // => 9 pub fn max(a []T) ?T { if a.len == 0 { return error('.max called on an empty array') } mut val := a[0] for e in a { if e > val { val = e } } return val } // idx_min returns the index of the minimum value in the array // Example: arrays.idx_min([1,2,3,0,9]) // => 3 pub fn idx_min(a []T) ?int { if a.len == 0 { return error('.idx_min called on an empty array') } mut idx := 0 mut val := a[0] for i, e in a { if e < val { val = e idx = i } } return idx } // idx_max returns the index of the maximum value in the array // Example: arrays.idx_max([1,2,3,0,9]) // => 4 pub fn idx_max(a []T) ?int { if a.len == 0 { return error('.idx_max called on an empty array') } mut idx := 0 mut val := a[0] for i, e in a { if e > val { val = e idx = i } } return idx } // merge two sorted arrays (ascending) and maintain sorted order // Example: arrays.merge([1,3,5,7], [2,4,6,8]) // => [1,2,3,4,5,6,7,8] [direct_array_access] pub fn merge(a []T, b []T) []T { mut m := []T{len: a.len + b.len} mut ia := 0 mut ib := 0 mut j := 0 // TODO efficient approach to merge_desc where: a[ia] >= b[ib] for ia < a.len && ib < b.len { if a[ia] <= b[ib] { m[j] = a[ia] ia++ } else { m[j] = b[ib] ib++ } j++ } // a leftovers for ia < a.len { m[j] = a[ia] ia++ j++ } // b leftovers for ib < b.len { m[j] = b[ib] ib++ j++ } return m } // group n arrays into a single array of arrays with n elements // // This function is analogous to the "zip" function of other languages. // To fully interleave two arrays, follow this function with a call to `flatten`. // // NOTE: An error will be generated if the type annotation is omitted. // Example: arrays.group([1,2,3],[4,5,6]) // => [[1, 4], [2, 5], [3, 6]] pub fn group(lists ...[]T) [][]T { mut length := if lists.len > 0 { lists[0].len } else { 0 } // calculate length of output by finding shortest input array for ndx in 1 .. lists.len { if lists[ndx].len < length { length = lists[ndx].len } } if length > 0 { mut arr := [][]T{cap: length} // append all combined arrays into the resultant array for ndx in 0 .. length { mut grouped := []T{cap: lists.len} // combine each list item for the ndx position into one array for list_ndx in 0 .. lists.len { grouped << lists[list_ndx][ndx] } arr << grouped } return arr } return [][]T{} } // chunk array into a single array of arrays where each element is the next `size` elements of the original // Example: arrays.chunk([1, 2, 3, 4, 5, 6, 7, 8, 9], 2)) // => [[1, 2], [3, 4], [5, 6], [7, 8], [9]] pub fn chunk(list []T, size int) [][]T { // allocate chunk array mut chunks := [][]T{cap: list.len / size + if list.len % size == 0 { 0 } else { 1 }} for i := 0; true; { // check chunk size is greater than remaining element size if list.len < i + size { // check if there's no more element to chunk if list.len <= i { break } chunks << list[i..] break } chunks << list[i..i + size] i += size } return chunks } pub struct WindowAttribute { size int step int = 1 } // get snapshots of the window of the given size sliding along array with the given step, where each snapshot is an array. // - `size` - snapshot size // - `step` - gap size between each snapshot, default is 1. // // Example: arrays.window([1, 2, 3, 4], size: 2) => [[1, 2], [2, 3], [3, 4]] // Example: arrays.window([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], size: 3, step: 2) // => [[1, 2, 3], [3, 4, 5], [5, 6, 7], [7, 8, 9]] pub fn window(list []T, attr WindowAttribute) [][]T { // allocate snapshot array mut windows := [][]T{cap: list.len - attr.size + 1} for i := 0; true; { // check remaining elements size is less than snapshot size if list.len < i + attr.size { break } windows << list[i..i + attr.size] i += attr.step } return windows } // sum up array, return nothing when array has no elements // // NOTICE: currently V has bug that cannot make sum function takes custom struct with + operator overloaded // which means you can only pass array of numbers for now. // TODO: Fix generic operator overloading detection issue. // Example: arrays.sum([1, 2, 3, 4, 5])? // => 15 pub fn sum(list []T) ?T { if list.len == 0 { return error('Cannot sum up array of nothing.') } else { mut head := list[0] for i, e in list { if i == 0 { continue } else { head += e } } return head } } // accumulates values with the first element and applying providing operation to current accumulator value and each elements. // If the array is empty, then returns error. // Example: arrays.reduce([1, 2, 3, 4, 5], fn (t1 int, t2 int) int { return t1 * t2 })? // => 120 pub fn reduce(list []T, reduce_op fn (t1 T, t2 T) T) ?T { if list.len == 0 { return error('Cannot reduce array of nothing.') } else { mut value := list[0] for i, e in list { if i == 0 { continue } else { value = reduce_op(value, e) } } return value } } // accumulates values with providing initial value and applying providing operation to current accumulator value and each elements. // Example: arrays.fold(['H', 'e', 'l', 'l', 'o'], 0, fn (r int, t string) int { return r + t[0] }) // => 149 pub fn fold(list []T, init R, fold_op fn (r R, t T) R) R { mut value := init for e in list { value = fold_op(value, e) } return value } // flattens n + 1 dimensional array into n dimensional array // Example: arrays.flatten([[1, 2, 3], [4, 5]]) // => [1, 2, 3, 4, 5] pub fn flatten(list [][]T) []T { // calculate required capacity mut required_size := 0 for e1 in list { for _ in e1 { required_size += 1 } } // allocate flattened array mut result := []T{cap: required_size} for e1 in list { for e2 in e1 { result << e2 } } return result } // grouping list of elements with given key selector. // Example: arrays.group_by(['H', 'el', 'lo'], fn (v string) int { return v.len }) // => {1: ['H'], 2: ['el', 'lo']} pub fn group_by(list []V, grouping_op fn (v V) K) map[K][]V { mut result := map[K][]V{} for v in list { key := grouping_op(v) // check if key exists, if not, then create a new array with matched value, otherwise append. if key in result { result[key] << v } else { result[key] = [v] } } return result } // concatenate an array with an arbitrary number of additional values // // NOTE: if you have two arrays, you should simply use the `<<` operator directly // Example: arrays.concat([1, 2, 3], 4, 5, 6) == [1, 2, 3, 4, 5, 6] // => true // Example: arrays.concat([1, 2, 3], ...[4, 5, 6]) == [1, 2, 3, 4, 5, 6] // => true // Example: arr << [4, 5, 6] // does what you need if arr is mutable [deprecated] pub fn concat(a []T, b ...T) []T { mut m := []T{cap: a.len + b.len} m << a m << b return m } // returns the smallest element >= val, requires `arr` to be sorted // Example: arrays.lower_bound([2, 4, 6, 8], 3)? // => 4 pub fn lower_bound(arr []T, val T) ?T { if arr.len == 0 { return error('.lower_bound called on an empty array') } mut left, mut right := 0, arr.len - 1 for ; left <= right; { idx := (left + right) / 2 elem := arr[idx] if elem < val { left = idx + 1 } else { right = idx - 1 } } if left >= arr.len { return error('') } else { return arr[left] } } // returns the largest element <= val, requires `arr` to be sorted // Example: arrays.upper_bound([2, 4, 6, 8], 3)? // => 2 pub fn upper_bound(arr []T, val T) ?T { if arr.len == 0 { return error('.upper_bound called on an empty array') } mut left, mut right := 0, arr.len - 1 for ; left <= right; { idx := (left + right) / 2 elem := arr[idx] if elem > val { right = idx - 1 } else { left = idx + 1 } } if right < 0 { return error('') } else { return arr[right] } } // binary search, requires `arr` to be sorted, returns index of found item or error. // Binary searches on sorted lists can be faster than other array searches because at maximum // the algorithm only has to traverse log N elements // Example: arrays.binary_search([1, 2, 3, 4], 4) ? // => 3 pub fn binary_search(arr []T, target T) ?int { mut left := 0 mut right := arr.len - 1 for ; left <= right; { idx := (left + right) / 2 elem := arr[idx] if elem == target { return idx } if elem < target { left = idx + 1 } else { right = idx - 1 } } return error('') } // rotate_left rotates the array in-place such that the first `mid` elements of the array move to the end // while the last `arr.len - mid` elements move to the front. After calling `rotate_left`, the element // previously at index `mid` will become the first element in the array. // Example: // ```v // mut x := [1,2,3,4,5,6] // arrays.rotate_left(mut x,2) // println(x) // [3, 4, 5, 6, 1, 2] // ``` pub fn rotate_left(mut arr []T, mid int) { assert mid <= arr.len && mid >= 0 k := arr.len - mid p := &T(arr.data) unsafe { ptr_rotate(mid, &T(usize(voidptr(p)) + usize(sizeof(T)) * usize(mid)), k) } } // rotate_right rotates the array in-place such that the first `arr.len - k` elements of the array move to the end // while the last `k` elements move to the front. After calling `rotate_right`, the element previously at index `arr.len - k` // will become the first element in the array. // Example: // ```v // mut x := [1,2,3,4,5,6] // arrays.rotate_right(mut x, 2) // println(x) // [5, 6, 1, 2, 3, 4] // ``` pub fn rotate_right(mut arr []T, k int) { assert k <= arr.len && k >= 0 mid := arr.len - k p := &T(arr.data) unsafe { ptr_rotate(mid, &T(usize(voidptr(p)) + usize(sizeof(T)) * usize(mid)), k) } } [unsafe] fn ptr_rotate(left_ int, mid &T, right_ int) { mut left := usize(left_) mut right := usize(right_) for { delta := if left < right { left } else { right } if delta <= raw_array_cap() { break } unsafe { swap_nonoverlapping(&T(usize(voidptr(mid)) - left * usize(sizeof(T))), &T(usize(voidptr(mid)) + usize(right - delta) * usize(sizeof(T))), int(delta)) } if left <= right { right -= delta } else { left -= delta } } unsafe { sz := usize(sizeof(T)) rawarray := C.malloc(raw_array_malloc_size()) dim := &T(usize(voidptr(mid)) - left * sz + right * sz) if left <= right { C.memcpy(rawarray, voidptr(usize(voidptr(mid)) - left * sz), left * sz) C.memmove(voidptr(usize(voidptr(mid)) - left * sz), voidptr(mid), right * sz) C.memcpy(voidptr(dim), rawarray, left * sz) } else { C.memcpy(rawarray, voidptr(mid), right * sz) C.memmove(voidptr(dim), voidptr(usize(voidptr(mid)) - left * sz), left * sz) C.memcpy(voidptr(usize(voidptr(mid)) - left * sz), rawarray, right * sz) } C.free(rawarray) } } struct Block { mut: x u64 y u64 z u64 w u64 } struct UnalignedBlock { mut: x u64 y u64 z u64 w u64 } const ( extra_size = 32 * sizeof(usize) ) fn raw_array_cap() usize { if sizeof(T) > arrays.extra_size { return 1 } else { return arrays.extra_size / sizeof(T) } } fn raw_array_malloc_size() usize { if sizeof(T) > arrays.extra_size { return usize(sizeof(T)) * 2 } else { return 32 * usize(sizeof(usize)) } } [unsafe] fn memswap(x voidptr, y voidptr, len usize) { block_size := sizeof(Block) mut i := usize(0) for i + block_size <= len { mut t_ := Block{} t := voidptr(&t_) xi := usize(x) + i yi := usize(y) + i unsafe { C.memcpy(t, voidptr(xi), block_size) C.memcpy(voidptr(xi), voidptr(yi), block_size) C.memcpy(t, voidptr(yi), block_size) } i += block_size } if i < len { mut t_ := UnalignedBlock{} t := voidptr(&t_) rem := len - i xi := usize(x) + i yi := usize(y) + i unsafe { C.memcpy(t, voidptr(xi), rem) C.memcpy(voidptr(xi), voidptr(yi), rem) C.memcpy(voidptr(yi), t, rem) } } } [unsafe] fn swap_nonoverlapping(x_ &T, y_ &T, count int) { x := voidptr(x_) y := voidptr(y_) len := usize(sizeof(T)) * usize(count) unsafe { memswap(x, y, len) } }