jcoffey-dev
7dae9b29fd
Upstream commit: 474dd0229cb20cf513036619781ed97bd8073c3f Enterprise-only files removed or emptied: 63 Enterprise-only snippets removed: 117 in 50 files Dangling module declarations removed: 5 Cargo edits turning enterprise off: 14 Verification: clean Enterprise feature gates left for rebuilt features: 19 in 18 files Produced by tools/fork/strip.py. The full report is in docs/fork/strip-reports/ on main.
160 lines
4.2 KiB
Rust
160 lines
4.2 KiB
Rust
/*
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* SPDX-FileCopyrightText: 2020 Stalwart Labs LLC <[email protected]>
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*
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* SPDX-License-Identifier: AGPL-3.0-only OR LicenseRef-SEL
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*/
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use std::collections::{HashMap, HashSet};
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use sieve::{Context, runtime::Variable};
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pub fn fn_count<'x>(_: &'x Context<'x>, v: Vec<Variable>) -> Variable {
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match &v[0] {
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Variable::Array(a) => a.len(),
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v => {
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if !v.is_empty() {
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1
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} else {
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0
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}
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}
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}
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.into()
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}
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pub fn fn_sort<'x>(_: &'x Context<'x>, v: Vec<Variable>) -> Variable {
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let is_asc = v[1].to_bool();
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let mut arr = (*v[0].to_array()).clone();
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if is_asc {
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arr.sort_unstable();
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} else {
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arr.sort_unstable_by(|a, b| b.cmp(a));
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}
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arr.into()
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}
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pub fn fn_dedup<'x>(_: &'x Context<'x>, v: Vec<Variable>) -> Variable {
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let arr = v[0].to_array();
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let mut result = Vec::with_capacity(arr.len());
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for item in arr.iter() {
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if !result.contains(item) {
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result.push(item.clone());
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}
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}
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result.into()
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}
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pub fn fn_cosine_similarity<'x>(_: &'x Context<'x>, v: Vec<Variable>) -> Variable {
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let mut word_freq: HashMap<Variable, [u32; 2]> = HashMap::new();
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for (idx, var) in v.into_iter().enumerate() {
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match var {
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Variable::Array(l) => {
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for item in l.iter() {
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word_freq.entry(item.clone()).or_insert([0, 0])[idx] += 1;
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}
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}
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_ => {
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for char in var.to_string().chars() {
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word_freq.entry(char.to_string().into()).or_insert([0, 0])[idx] += 1;
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}
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}
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}
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}
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let mut dot_product = 0;
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let mut magnitude_a = 0;
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let mut magnitude_b = 0;
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for count in word_freq.values() {
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dot_product += count[0] * count[1];
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magnitude_a += count[0] * count[0];
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magnitude_b += count[1] * count[1];
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}
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if magnitude_a != 0 && magnitude_b != 0 {
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dot_product as f64 / (magnitude_a as f64).sqrt() / (magnitude_b as f64).sqrt()
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} else {
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0.0
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}
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.into()
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}
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pub fn cosine_similarity(a: &[&str], b: &[&str]) -> f64 {
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let mut word_freq: HashMap<&str, [u32; 2]> = HashMap::new();
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for (idx, items) in [a, b].into_iter().enumerate() {
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for item in items {
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word_freq.entry(item).or_insert([0, 0])[idx] += 1;
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}
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}
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let mut dot_product = 0;
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let mut magnitude_a = 0;
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let mut magnitude_b = 0;
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for count in word_freq.values() {
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dot_product += count[0] * count[1];
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magnitude_a += count[0] * count[0];
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magnitude_b += count[1] * count[1];
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}
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if magnitude_a != 0 && magnitude_b != 0 {
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dot_product as f64 / (magnitude_a as f64).sqrt() / (magnitude_b as f64).sqrt()
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} else {
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0.0
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}
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}
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pub fn fn_jaccard_similarity<'x>(_: &'x Context<'x>, v: Vec<Variable>) -> Variable {
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let mut word_freq = [HashSet::new(), HashSet::new()];
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for (idx, var) in v.into_iter().enumerate() {
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match var {
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Variable::Array(l) => {
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for item in l.iter() {
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word_freq[idx].insert(item.clone());
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}
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}
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_ => {
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for char in var.to_string().chars() {
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word_freq[idx].insert(char.to_string().into());
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}
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}
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}
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}
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let intersection_size = word_freq[0].intersection(&word_freq[1]).count();
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let union_size = word_freq[0].union(&word_freq[1]).count();
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if union_size != 0 {
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intersection_size as f64 / union_size as f64
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} else {
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0.0
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}
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.into()
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}
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pub fn fn_is_intersect<'x>(_: &'x Context<'x>, v: Vec<Variable>) -> Variable {
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match (&v[0], &v[1]) {
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(Variable::Array(a), Variable::Array(b)) => a.iter().any(|x| b.contains(x)),
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(Variable::Array(a), item) | (item, Variable::Array(a)) => a.contains(item),
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_ => false,
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}
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.into()
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}
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pub fn fn_winnow<'x>(_: &'x Context<'x>, mut v: Vec<Variable>) -> Variable {
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match v.remove(0) {
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Variable::Array(a) => a
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.iter()
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.filter(|i| !i.is_empty())
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.cloned()
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.collect::<Vec<_>>()
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.into(),
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v => v,
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}
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}
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