Streamed some refactoring. More work to do
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270
scratch/bk_tree.lua
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270
scratch/bk_tree.lua
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---------------------------
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-- bk-tree datastructure
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--
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-- http://en.wikipedia.org/wiki/BK-tree
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-- @module bk-tree
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-- @author Robin Hübner
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-- robinhubner@gmail.com
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-- @release version 1.0.2
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-- @license MIT
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local bk_tree = {}
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local function lazy_copy(t1)
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local cp = {}
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for k, v in pairs(t1) do
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cp[k] = v
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end
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return cp
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end
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local function min(a, b, c)
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local min_val = a
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if b < min_val then min_val = b end
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if c < min_val then min_val = c end
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return min_val
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end
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----------------------------------
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--- Levenshtein distance function.
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-- @tparam string s1
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-- @tparam string s2
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-- @treturn number the levenshtein distance
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-- @within Metrics
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function bk_tree.levenshtein_dist(s1, s2)
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if s1 == s2 then return 0 end
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if s1:len() == 0 then return s2:len() end
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if s2:len() == 0 then return s1:len() end
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if s1:len() < s2:len() then s1, s2 = s2, s1 end
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t = {}
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for i=1, #s1+1 do
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t[i] = {i-1}
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end
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for i=1, #s2+1 do
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t[1][i] = i-1
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end
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local cost
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for i=2, #s1+1 do
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for j=2, #s2+1 do
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cost = (s1:sub(i-1,i-1) == s2:sub(j-1,j-1) and 0) or 1
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t[i][j] = min(
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t[i-1][j] + 1,
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t[i][j-1] + 1,
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t[i-1][j-1] + cost)
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end
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end
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return t[#s1+1][#s2+1]
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end
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function bk_tree.hook(param)
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local name, callee = debug.getlocal(2, 1)
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local f = debug.getinfo(2, "f").func
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local p = debug.getinfo(3, "f").func
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--[[ previous function in the callstack, if called from the same place,
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don't add to the insert/remove counters. ]]--
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if f == bk_tree.insert and p ~= bk_tree.insert then
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callee.stats.nodes = callee.stats.nodes + 1
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elseif f == bk_tree.remove and p ~= bk_tree.remove then
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callee.stats.nodes = callee.stats.nodes - 1
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elseif f == bk_tree.query and p == bk_tree.query then
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callee.stats.queries = callee.stats.queries + 1
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end
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end
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--- Hooks debugging into tree execution.
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-- Keeps track of number of nodes created, queries made,
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-- note that this must be run directly after tree is created
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-- in order to get correct information.
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-- @within Debug
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--- @usage
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-- local bktree = require "bk-tree"
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-- local tree = bktree:new("word")
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-- tree:debug()
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-- tree:insert("perceive")
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-- tree:insert("beautiful")
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-- tree:insert("definitely")
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-- local result = tree:query("definately", 3)
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-- tree:print_stats()
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--
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-- -- output
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-- Nodes: 4
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-- Queries: 3
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-- Nodes Queried: 75%
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function bk_tree:debug()
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local nc = 0
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if self.root then nc = 1 end
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self.stats = { nodes = nc, queries = 0 }
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debug.sethook(self.hook, "c")
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end
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--- Print execution stats.
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-- Prints nodes queried and total nodes, as well as a fraction of
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-- nodes visited to satisfy the query, resets the counter of nodes queried when called.
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-- @within Debug
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-- @see debug
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function bk_tree:print_stats()
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print("\nNodes: " .. self.stats.nodes)
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print("Queries: " .. self.stats.queries)
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print("Nodes Queried: " .. self.stats.queries/self.stats.nodes*100 .. "%\n")
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self.stats.queries = 0
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end
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--- Fetch execution stats.
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-- Returns a copy of the execution stats that @{print_stats} would print, requires debug to have been enabled
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-- to not just return defaults. Useful if you want to profile things.
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-- @within Debug
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-- @return {key = value,...}
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function bk_tree:get_stats()
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return lazy_copy(self.stats)
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end
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---------------------------
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--- Creates a new bk-tree.
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-- @constructor
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-- @string[opt] root_word the root of the new tree
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-- @tparam[opt=levenshtein_dist] function dist_func the distance function used
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-- @see levenshtein_dist
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-- @return the new bk-tree instance
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--- @usage
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-- local bktree = require "bk-tree"
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-- local tree = bktree:new("word")
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function bk_tree:new(root_word, dist_func)
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local n_obj = {}
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if root_word then n_obj.root = { str = root_word, children = {} } end
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n_obj.dist_func = dist_func or self.levenshtein_dist
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setmetatable(n_obj, self)
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self.__index = self
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return n_obj
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end
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--------------------------------
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--- Inserts word into the tree.
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-- @string word
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-- @treturn bool true if inserted, false if word already exists in tree
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--- @usage
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-- local bktree = require "bk-tree"
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-- local tree = bktree:new("root")
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-- local success = tree:insert("other_word")
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function bk_tree:insert(word, node)
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node = node or self.root
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if not node then
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self.root = { str = word, children = {} }
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return true
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end
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local dist = self.dist_func(word, node.str)
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if dist == 0 then return false end
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local some_node = node.children[dist]
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if not some_node then
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node.children[dist] = { str = word, children = {} }
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return true
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end
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return self:insert(word, some_node)
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end
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--------------------------------
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--- Query the tree for matches.
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-- @string word
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-- @tparam number n max edit distance to use when querying
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-- @treturn {{str=string,distance=number},....} table of tables with matching words, empty table if no matches
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--- @usage
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-- local bktree = require "bk-tree"
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-- local tree = bktree:new("word")
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-- tree:insert("hello")
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-- tree:insert("goodbye")
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-- tree:insert("woop")
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-- local result = tree:query("woop", 1)
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function bk_tree:query(word, n, node, matches)
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node = node or self.root
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matches = matches or {}
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if not node then return matches end
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local dist = self.dist_func(word, node.str)
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if dist <= n then matches[#matches+1] = {str = node.str, distance = dist} end
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for k, child in pairs(node.children) do
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if child ~= nil then
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if k >= dist-n and k <= dist+n then
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self:query(word, n, child, matches)
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end
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end
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end
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return matches
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end
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---------------------------------------------------------
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--- Queries the the tree for a match, sorts the results.
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-- Calls @{query} and returns the results sorted.
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-- @string word
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-- @tparam number n max edit distance to use when querying
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-- @treturn {{str=string,distance=number},....} table of tables with matching words sorted by distance, empty table if no matches
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--- @usage
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-- local bktree = require "bk-tree"
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-- local tree = bktree:new("word")
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-- tree:insert("woop")
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-- tree:insert("worp")
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-- tree:insert("warp")
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-- local result = tree:query_sorted("woop", 3)
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function bk_tree:query_sorted(word, n)
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local result = self:query(word, n)
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table.sort(result, function(a,b) return a.distance < b.distance end)
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return result
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end
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local tree = bk_tree:new("word")
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tree:insert("hello")
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tree:insert("welp")
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tree:insert("function")
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tree:insert("this long line what")
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tree:insert("what this long line what")
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print(vim.inspect(tree))
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print(vim.inspect(tree:query_sorted("what", 3)))
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return bk_tree
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