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                                                                    *mini.fuzzy*
                                                                     *MiniFuzzy*
Minimal and fast fuzzy matching.

# Setup~

This module doesn't need setup, but it can be done to improve usability.
Setup with `require('mini.fuzzy').setup({})` (replace `{}` with your
`config` table). It will create global Lua table `MiniFuzzy` which you can
use for scripting or manually (with `:lua MiniFuzzy.*`).

See |MiniFuzzy.config| for `config` structure and default values.

You can override runtime config settings locally to buffer inside
`vim.b.minifuzzy_config` which should have same structure as
`MiniFuzzy.config`.
See |mini.nvim-buffer-local-config| for more details.

# Notes~

1. Currently there is no explicit design to work with multibyte symbols,
   but simple examples should work.
2. Smart case is used: case insensitive if input word (which is usually a
    user input) is all lower ase. Case sensitive otherwise.

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                                                           *MiniFuzzy-algorithm*
# Algorithm design~

General design uses only width of found match and index of first letter
match. No special characters or positions (like in fzy and fzf) are used.

Given input `word` and target `candidate`:
- The goal is to find matching between `word`'s letters and letters in
  `candidate`, which minimizes certain score. It is assumed that order of
  letters in `word` and those matched in `candidate` should be the same.
- Matching is represented by matched positions: an array `positions` of
  integers with length equal to number of letters in `word`. The following
  should be always true in case of a match: `candidate`'s letter at index
  `positions[i]` is letters[i]` for all valid `i`.
- Matched positions are evaluated based only on two features: their width
  (number of indexes between first and last positions) and first match
  (index of first letter match). There is a global setting `cutoff` for
  which all feature values greater than it can be considered "equally bad".
- Score of matched positions is computed with following explicit formula:
  `cutoff * min(width, cutoff) + min(first, cutoff)`. It is designed to be
  equivalent to first comparing widths (lower is better) and then comparing
  first match (lower is better). For example, if `word = 'time'`:
    - '_time' (width 4) will have a better match than 't_ime' (width 5).
    - 'time_a' (width 4, first 1) will have a better match than 'a_time'
      (width 4, first 3).
- Final matched positions are those which minimize score among all possible
  matched positions of `word` and `candidate`.

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                                                             *MiniFuzzy.setup()*
                          `MiniFuzzy.setup`({config})
Module setup

Parameters~
{config} `(table)` Module config table. See |MiniFuzzy.config|.

Usage~
`require('mini.fuzzy').setup({})` (replace `{}` with your `config` table)

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                                                              *MiniFuzzy.config*
                               `MiniFuzzy.config`
Module config

Default values:
>
  MiniFuzzy.config = {
    -- Maximum allowed value of match features (width and first match). All
    -- feature values greater than cutoff can be considered "equally bad".
    cutoff = 100,
  }
<

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                                                             *MiniFuzzy.match()*
                     `MiniFuzzy.match`({word}, {candidate})
Compute match data of input `word` and `candidate` strings

It tries to find best match for input string `word` (usually user input)
and string `candidate`. Returns table with elements:
- `positions` - array with letter indexes inside `candidate` which
  matched to corresponding letters in `word`. Or `nil` if no match.
- `score` - positive number representing how good the match is (lower is
  better). Or `-1` if no match.

Parameters~
{word} `(string)` Input word (usually user input).
{candidate} `(string)` Target word (usually with which matching is done).

Return~
`(table)` Table with matching information (see function's description).

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                                                        *MiniFuzzy.filtersort()*
               `MiniFuzzy.filtersort`({word}, {candidate_array})
Filter string array

This leaves only those elements of input array which matched with `word`
and sorts from best to worst matches (based on score and index in original
array, both lower is better).

Parameters~
{word} `(string)` String which will be searched.
{candidate_array} `(table)` Lua array of strings inside which word will be
  searched.

Return~
`(...)` Arrays of matched candidates and their indexes in original input.

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                                                 *MiniFuzzy.process_lsp_items()*
                 `MiniFuzzy.process_lsp_items`({items}, {base})
Fuzzy matching for `lsp_completion.process_items` of |MiniCompletion.config|

Parameters~
{items} `(table)` Lua array with LSP 'textDocument/completion' response items.
{base} `(string)` Word to complete.

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                                              *MiniFuzzy.get_telescope_sorter()*
                    `MiniFuzzy.get_telescope_sorter`({opts})
Custom getter for `telescope.nvim` sorter

Designed to be used as value for |telescope.defaults.file_sorter| and
|telescope.defaults.generic_sorter| inside `setup()` call.

Parameters~
{opts} `(table)` Options (currently not used).

Usage~
>
  require('telescope').setup({
    defaults = {
      generic_sorter = require('mini.fuzzy').get_telescope_sorter
    }
  })


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