som 8.0.5 → 8.0.6

raw patch · 5 files changed

+29/−14 lines, 5 filesdep +assertdep +deepseqdep ~basePVP: major bump suggested

API removals or changes: PVP suggests a major version bump

Dependencies added: assert, deepseq

Dependency ranges changed: base

API changes (from Hackage documentation)

Files

• som.cabal +7/−4
• src/Data/Datamining/Clustering/DSOMInternal.hs +4/−2
• src/Data/Datamining/Clustering/SOMInternal.hs +3/−2
• src/Data/Datamining/Clustering/SSOMInternal.hs +3/−5
• test/Data/Datamining/Clustering/SSOMQC.hs +12/−1

@@ -1,5 +1,5 @@ Name:              som-Version:           8.0.5+Version:           8.0.6 Stability:         experimental Synopsis:          Self-Organising Maps. Description:       A Kohonen Self-organising Map (SOM) maps input patterns @@ -33,13 +33,15 @@ source-repository this   type:     git   location: https://github.com/mhwombat/som.git-  tag:      8.0.5+  tag:      8.0.6   library   hs-source-dirs:  src-  build-depends:   base ==4.*,+  build-depends:   assert ==0.0.*,+                   base >=4.8 && <5,                    containers ==0.5.*,+                   deepseq ==1.4.*,                    grid ==7.* && >=7.7,                    MonadRandom ==0.4.*   ghc-options:     -Wall@@ -54,7 +56,8 @@  test-suite som-tests   type:            exitcode-stdio-1.0-  build-depends:   base ==4.*,+  build-depends:   assert ==0.0.*,+                   base >=4.8 && <5,                    test-framework-quickcheck2 == 0.3.*,                    QuickCheck ==2.8.*,                    test-framework ==0.8.*,

@@ -12,13 +12,15 @@ -- ------------------------------------------------------------------------ {-# LANGUAGE TypeFamilies, FlexibleContexts, FlexibleInstances,-    MultiParamTypeClasses #-}+    MultiParamTypeClasses, DeriveAnyClass, DeriveGeneric #-}  module Data.Datamining.Clustering.DSOMInternal where +import Control.DeepSeq (NFData) import qualified Data.Foldable as F (Foldable, foldr) import Data.List (foldl', minimumBy) import Data.Ord (comparing)+import GHC.Generics (Generic) import qualified Math.Geometry.Grid as G (Grid(..), FiniteGrid(..)) import qualified Math.Geometry.GridMap as GM (GridMap(..)) import Data.Datamining.Clustering.Classifier(Classifier(..))@@ -59,7 +61,7 @@     --   If @amount@=1, the result should be identical to the @target@.     --   If @amount@=0, the result should be the unmodified @pattern@.     makeSimilar :: p -> x -> p -> p-  }+  } deriving (Generic, NFData)  instance (F.Foldable gm) => F.Foldable (DSOM gm x k) where   foldr f x g = F.foldr f x (gridMap g)

@@ -12,10 +12,11 @@ -- ------------------------------------------------------------------------ {-# LANGUAGE TypeFamilies, FlexibleContexts, FlexibleInstances,-    MultiParamTypeClasses, DeriveGeneric #-}+    MultiParamTypeClasses, DeriveAnyClass, DeriveGeneric #-}  module Data.Datamining.Clustering.SOMInternal where +import Control.DeepSeq (NFData) import qualified Data.Foldable as F (Foldable, foldr) import Data.List (foldl', minimumBy) import Data.Ord (comparing)@@ -111,7 +112,7 @@     --   directly modify it, then the counter will represent the number     --   of patterns that this SOM has classified.     counter :: t-  } deriving (Generic)+  } deriving (Generic, NFData)  instance (F.Foldable gm) => F.Foldable (SOM t d gm x k) where   foldr f x g = F.foldr f x (gridMap g)

@@ -12,10 +12,11 @@ -- ------------------------------------------------------------------------ {-# LANGUAGE TypeFamilies, FlexibleContexts, FlexibleInstances,-    MultiParamTypeClasses, DeriveGeneric #-}+    MultiParamTypeClasses, DeriveAnyClass, DeriveGeneric #-}  module Data.Datamining.Clustering.SSOMInternal where +import Control.DeepSeq (NFData) import Data.List (foldl', minimumBy) import Data.Ord (comparing) import Data.Datamining.Clustering.Classifier(Classifier(..))@@ -33,9 +34,6 @@ --   * 0 < r0 < 1 -- --   * 0 < d------   where << means "is much smaller than" (not the Haskell @<<@---   operator!) exponential :: Floating a => a -> a -> a -> a exponential r0 d t = r0 * exp (-d*t) @@ -77,7 +75,7 @@     --   directly modify it, then the counter will represent the number     --   of patterns that this SSOM has classified.     counter :: t-  } deriving (Generic)+  } deriving (Generic, NFData)  -- | Extracts the current models from the SSOM. --   A synonym for @'sMap'@.

@@ -23,7 +23,7 @@   absDifference) import Data.Datamining.Clustering.Classifier(classify,   classifyAndTrain, reportAndTrain, differences, diffAndTrain, models,-  train, trainBatch)+  train, trainBatch, numModels) import Data.Datamining.Clustering.SSOMInternal import qualified Data.Map.Strict as M @@ -138,6 +138,15 @@           s1 = trainNode s (classify s p) p           s2 = train s p +prop_train_node_only_modifies_one_model :: Int -> SSOMTestData -> Property+prop_train_node_only_modifies_one_model n (SSOMTestData s _ ps)+  = property $ as == as' && bs == bs'+    where p = head ps+          k = n `mod` (numModels s)+          s' = trainNode s k p+          (as, _:bs) = splitAt k (models s)+          (as', _:bs') = splitAt k (models s')+ -- | The training set consists of the same vectors in the same order, --   several times over. So the resulting classifications should consist --   of the same integers in the same order, over and over.@@ -266,6 +275,8 @@       prop_classifyAndTrainEquiv,     testProperty "prop_diffAndTrainEquiv" prop_diffAndTrainEquiv,     testProperty "prop_trainNodeEquiv" prop_trainNodeEquiv,+    testProperty "prop_train_node_only_modifies_one_model"+      prop_train_node_only_modifies_one_model,     testProperty "prop_batch_training_works" prop_batch_training_works,     testProperty "prop_classification_is_consistent"       prop_classification_is_consistent,