spectral-clustering 0.3.0.1 → 0.3.0.2

raw patch · 2 files changed

+23/−10 lines, 2 filesPVP: major bump suggested

API removals or changes: PVP suggests a major version bump

API changes (from Hackage documentation)

Files

• spectral-clustering.cabal +1/−1
• src/Math/Clustering/Spectral/Dense.hs +22/−9

@@ -1,6 +1,6 @@ cabal-version: >=1.10 name: spectral-clustering-version: 0.3.0.1+version: 0.3.0.2 license: GPL-3 license-file: LICENSE copyright: 2019 Gregory W. Schwartz

@@ -53,13 +53,15 @@ newtype B1 = B1 { unB1 :: H.Matrix Double } deriving (Show) -- | B2 term frequency-inverse document frequency matrix of B1. newtype B2 = B2 { unB2 :: H.Matrix Double } deriving (Show)--- | Diagonal matrix from \(diag(B(B^{T}1))\).-newtype D  = D { unD :: H.Matrix Double } deriving (Show)+-- | Diagonal matrix from \(diag(B(B^{T}1))\). Here in a vector format.+newtype D  = D { unD :: H.Vector Double } deriving (Show) -- | Matrix from \(D^{-1/2}B}\). newtype C  = C { unC :: H.Matrix Double } deriving (Show) -- | Normed rows of B2. For a complete explanation, see Shu et al., "Efficient -- Spectral Neighborhood Blocking for Entity Resolution", 2011. newtype B  = B { unB :: H.Matrix Double } deriving (Show)+-- | A diagonal matrix in a vector format.+newtype Diag  = Diag { unDiag :: H.Vector Double } deriving (Show)  -- | Assign close to 0 as 0. epsilonZero :: Double -> Double@@ -109,7 +111,6 @@ -- | Get the signed diagonal transformed B matrix. bToD :: B -> D bToD (B b) = D-           . H.diag            . H.flatten            $ (H.cmap abs b)         H.<> ((H.cmap abs $ H.tr b) H.<> ((n H.>< 1) [1,1..]))@@ -118,7 +119,7 @@  -- | Get the matrix C as input for SVD. bdToC :: B -> D -> C-bdToC (B b) (D d) = C $ (H.diag . H.cmap (\x -> x ** (- 1 / 2)) . H.takeDiag $ d) H.<> b+bdToC (B b) (D d) = C $ diagMatMult (Diag $ H.cmap (\x -> x ** (- 1 / 2)) d) b  -- | Obtain the second left singular vector (or N earlier) and E on of a sparse -- matrix.@@ -268,14 +269,14 @@                 . H.eigSH                 $ lNorm   where-    lNorm = H.trustSym $ i - mconcat [invD, mat, invD]-    invD  = H.diag+    lNorm = H.trustSym $ i - (matDiagMult (diagMatMult invD mat) invD)+    invD  = Diag           . H.cmap (\x -> if x == 0 then x else x ** (- 1 / 2))           . getDegreeVector           $ mat     i     = H.ident . H.rows $ mat --- | Sort an matrix by values in a vector.+-- | Sort a matrix by values in a vector. sortMatrixByVec :: H.Vector Double -> H.Matrix Double -> H.Matrix Double sortMatrixByVec xs mat = mat H.¿ sortedIdx   where@@ -283,9 +284,21 @@       reverse . fmap fst . sortBy (compare `on` snd) . zip [0..] . H.toList $ xs  -- | Obtain the signed degree matrix.-getDegreeMatrix :: AdjacencyMatrix -> H.Matrix Double-getDegreeMatrix = H.diag . getDegreeVector+getDegreeMatrix :: AdjacencyMatrix -> Diag+getDegreeMatrix = Diag . getDegreeVector  -- | Obtain the signed degree vector. getDegreeVector :: AdjacencyMatrix -> H.Vector Double getDegreeVector = H.vector . fmap (H.sumElements . H.cmap abs) . H.toRows++-- | Diagonal matrix multiply from vector type.+diagMatMult :: Diag -> H.Matrix Double -> H.Matrix Double+diagMatMult (Diag d) = cimap mult+  where+    mult i _ v = v * (d H.! i)++-- | Diagonal matrix multiply from vector type.+matDiagMult :: H.Matrix Double -> Diag -> H.Matrix Double+matDiagMult m (Diag d) = cimap mult m+  where+    mult _ j v = v * (d H.! j)