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 // - zip - concat two arrays into one map // min returns the minimum value in the array 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 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 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 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 [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 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 zipped := []T{cap: lists.len} // combine each list item for the ndx position into one array for list_ndx in 0 .. lists.len { zipped << lists[list_ndx][ndx] } arr << zipped } return arr } return [][]T{} } // chunk array to arrays with n elements // example: arrays.chunk([1, 2, 3], 2) => [[1, 2], [3]] 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 A: `arrays.window([1, 2, 3, 4], size: 2)` => `[[1, 2], [2, 3], [3, 4]]` // example B: `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. // Future work: Fix generic operator overloading detection issue. // usage: `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. // usage: `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. // usage: `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 // usage: `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. // usage: `arrays.assort(['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 }