add, print --match: prioritise infix matches
If the search description occurs in full within the other description, that match gets a +0.5 score boost.
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@ -97,7 +97,7 @@ import "extra" Control.Monad.Extra (whenM)
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import Control.Monad.Reader as R
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import Control.Monad.ST (ST, runST)
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import Data.Array.ST (STArray, getElems, newListArray, writeArray)
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import Data.Char (toUpper)
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import Data.Char (toUpper, isDigit)
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import Data.Default (Default(..))
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import Data.Function ((&))
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import qualified Data.HashTable.Class as H (toList)
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@ -328,33 +328,37 @@ journalAccountNameTree = accountNameTreeFrom . journalAccountNames
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-- the given transaction description and query. Transactions are
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-- listed with their description's similarity score (see
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-- compareDescriptions), sorted by highest score and then by date.
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-- Only transactions with a similarity score greater than the minimum
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-- Only transactions with a similarity score greater than a minimum
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-- threshold (currently 0) are returned.
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journalTransactionsSimilarTo :: Journal -> Query -> Text -> Int -> [(Double,Transaction)]
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journalTransactionsSimilarTo j q desc n =
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journalTransactionsSimilarTo Journal{jtxns} q desc n =
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take n $
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sortBy (\(s1,t1) (s2,t2) -> compare (s2,tdate t2) (s1,tdate t1)) $
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filter ((> threshold).fst)
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[(compareDescriptions desc $ tdescription t, t) | t <- ts]
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[(compareDescriptions desc $ tdescription t, t) | t <- jtxns, q `matchesTransaction` t]
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where
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ts = filter (q `matchesTransaction`) $ jtxns j
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threshold = 0
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-- | Return a similarity measure, from 0 to 1, for two transaction
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-- descriptions. This is like compareStrings, but first strips out
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-- any numbers, to improve accuracy eg when there are bank transaction
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-- ids from imported data.
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-- | Return a similarity score from 0 to 1.5 for two transaction descriptions.
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-- This is based on compareStrings, with the following modifications:
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--
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-- - numbers are stripped out before measuring similarity
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--
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-- - if the (unstripped) first description appears in its entirety within the second,
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-- the score is boosted by 0.5.
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--
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compareDescriptions :: Text -> Text -> Double
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compareDescriptions s t = compareStrings s' t'
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where s' = simplify $ T.unpack s
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t' = simplify $ T.unpack t
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simplify = filter (not . (`elem` ("0123456789" :: String)))
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compareDescriptions a b =
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(if a `T.isInfixOf` b then (0.5+) else id) $
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compareStrings (simplify a) (simplify b)
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where
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simplify = T.unpack . T.filter (not.isDigit)
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-- | Return a similarity measure, from 0 to 1, for two strings. This
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-- | Return a similarity score from 0 to 1 for two strings. This
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-- was based on Simon White's string similarity algorithm
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-- (http://www.catalysoft.com/articles/StrikeAMatch.html), later found
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-- to be https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient,
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-- modified to handle short strings better.
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-- and modified to handle short strings better.
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-- Todo: check out http://nlp.fi.muni.cz/raslan/2008/raslan08.pdf#page=14 .
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compareStrings :: String -> String -> Double
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compareStrings "" "" = 1
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@ -362,14 +366,16 @@ compareStrings [_] "" = 0
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compareStrings "" [_] = 0
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compareStrings [a] [b] = if toUpper a == toUpper b then 1 else 0
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compareStrings s1 s2 = 2 * commonpairs / totalpairs
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where
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pairs1 = S.fromList $ wordLetterPairs $ uppercase s1
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pairs2 = S.fromList $ wordLetterPairs $ uppercase s2
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commonpairs = fromIntegral $ S.size $ S.intersection pairs1 pairs2
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totalpairs = fromIntegral $ S.size pairs1 + S.size pairs2
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where
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pairs1 = S.fromList $ wordLetterPairs $ uppercase s1
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pairs2 = S.fromList $ wordLetterPairs $ uppercase s2
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commonpairs = fromIntegral $ S.size $ S.intersection pairs1 pairs2
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totalpairs = fromIntegral $ S.size pairs1 + S.size pairs2
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wordLetterPairs :: String -> [String]
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wordLetterPairs = concatMap letterPairs . words
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letterPairs :: String -> [String]
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letterPairs (a:b:rest) = [a,b] : letterPairs (b:rest)
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letterPairs _ = []
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