diff --git a/LICENSE b/LICENSE
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+++ b/LICENSE
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+                    GNU GENERAL PUBLIC LICENSE
+                       Version 3, 29 June 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
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+
+  17. Interpretation of Sections 15 and 16.
+
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+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program.  It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+    {one line to give the program's name and a brief idea of what it does.}
+    Copyright (C) {year}  {name of author}
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
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+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
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+
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+    along with this program.  If not, see <http://www.gnu.org/licenses/>.
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+Also add information on how to contact you by electronic and paper mail.
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+    {project}  Copyright (C) {year}  {fullname}
+    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+    This is free software, and you are welcome to redistribute it
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+
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+if any, to sign a "copyright disclaimer" for the program, if necessary.
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+<http://www.gnu.org/licenses/>.
+
+  The GNU General Public License does not permit incorporating your program
+into proprietary programs.  If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
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diff --git a/Setup.hs b/Setup.hs
new file mode 100644
--- /dev/null
+++ b/Setup.hs
@@ -0,0 +1,2 @@
+import Distribution.Simple
+main = defaultMain
diff --git a/modularity.cabal b/modularity.cabal
new file mode 100644
--- /dev/null
+++ b/modularity.cabal
@@ -0,0 +1,33 @@
+name:                modularity
+version:             0.2.0.2
+synopsis:            Find the modularity of a network.
+description:         Report Q, the Newman-Girvan modularity of an adjacency matrix.
+homepage:            http://github.com/GregorySchwartz/modularity#readme
+license:             GPL-3
+license-file:        LICENSE
+author:              Gregory W. Schwartz
+maintainer:          gsch@pennmedicine.upenn.edu
+copyright:           2018 Gregory W. Schwartz
+category:            Bioinformatics
+build-type:          Simple
+-- extra-source-files:
+cabal-version:       >=1.10
+
+library
+  hs-source-dirs:      src
+  exposed-modules:     Math.Modularity.Dense
+                     , Math.Modularity.Sparse
+                     , Math.Modularity.Types
+                     , Math.Modularity.Eigen.Sparse
+  build-depends:       base >= 4.7 && < 5
+                     , eigen
+                     , hmatrix
+                     , sparse-linear-algebra
+                     , spectral-clustering
+                     , vector
+  ghc-options:         -O2
+  default-language:    Haskell2010
+
+source-repository head
+  type:     git
+  location: https://github.com/GregorySchwartz/modularity
diff --git a/src/Math/Modularity/Dense.hs b/src/Math/Modularity/Dense.hs
new file mode 100644
--- /dev/null
+++ b/src/Math/Modularity/Dense.hs
@@ -0,0 +1,43 @@
+{- Math.Modularity
+Gregory W. Schwartz
+
+Collects the functions pertaining to finding the Newman-Girvan modularity of an
+adjacency matrix.
+-}
+
+module Math.Modularity.Dense
+    ( getModularity
+    , Q (..)
+    ) where
+
+-- Remote
+import Data.Bool (bool)
+import qualified Data.Vector as V
+import qualified Data.Vector.Storable as VS
+import qualified Numeric.LinearAlgebra as H
+
+-- Local
+import Math.Modularity.Types
+
+type LabelVector     = H.Vector Double
+type AdjacencyMatrix = H.Matrix Double
+
+-- | Find modularity from a vector of community labels (0 or 1) corresponding to
+-- rows in the adjacency matrix. Needs 0s on the diagonal for the adjacency
+-- matrix.
+getModularity :: LabelVector -> AdjacencyMatrix -> Q
+getModularity moduleVec mat = Q $ (1 / (2 * m)) * sumQ mat
+  where
+    sumQ = V.sum
+         . V.imap (\ v
+                  -> H.sumElements
+                   . VS.imap (\w x -> inner v w x * delta v w)
+                  )
+         . V.fromList
+         . H.toRows
+    inner v w x = x - ((k v * k w) / (2 * m))
+    delta v w = ((s v * s w) + 1) / 2
+    m = (/ 2) . H.sumElements $ mat -- Symmetric matrix so divide by 2.
+    d = H.vector . fmap H.sumElements . H.toRows $ mat
+    s = bool (-1) 1 . (== 0) . H.atIndex moduleVec
+    k = H.atIndex d
diff --git a/src/Math/Modularity/Eigen/Sparse.hs b/src/Math/Modularity/Eigen/Sparse.hs
new file mode 100644
--- /dev/null
+++ b/src/Math/Modularity/Eigen/Sparse.hs
@@ -0,0 +1,80 @@
+{- Math.Sparse.Modularity.Eigen.FeatureMatrix
+Gregory W. Schwartz
+
+Collects the functions pertaining to finding the Newman-Girvan modularity of a
+sparse adjacency matrix.
+-}
+
+{-# LANGUAGE BangPatterns #-}
+{-# LANGUAGE TupleSections #-}
+
+module Math.Modularity.Eigen.Sparse
+    ( getModularity
+    , getBModularity
+    , Q (..)
+    , testModularity
+    ) where
+
+-- Remote
+import Data.Bool (bool)
+import Math.Clustering.Spectral.Eigen.FeatureMatrix (B (..), getB)
+import qualified Data.Eigen.SparseMatrix as S
+import qualified Data.Vector.Storable as VS
+
+-- Local
+import Math.Modularity.Types
+
+type LabelVector     = S.SparseMatrixXd
+type AdjacencyMatrix = S.SparseMatrixXd
+
+-- | Find modularity from a vector of community labels (0 or 1) corresponding to
+-- rows in the adjacency matrix. Needs 0s on the diagonal for the adjacency
+-- matrix.
+getModularity :: LabelVector -> AdjacencyMatrix -> Q
+getModularity moduleVec mat = Q $ (1 / (2 * m)) * sumQ mat
+  where
+    sumQ :: S.SparseMatrixXd -> Double
+    sumQ = S.getSum
+         . S._imap (\ i j v -> inner i j v * delta i j)
+    inner v w x = x - ((k v * k w) / (2 * m))
+    delta v w = ((s v * s w) + 1) / 2
+    m = (/ 2) . S.getSum $ mat -- Symmetric matrix so divide by 2.
+    d = S.getColSums mat
+    s = bool (-1) 1 . (== 0) . (S.!) moduleVec . (,0)
+    k = (S.!) d . (0,)
+
+-- | Find modularity from a vector of community labels (0 or 1) corresponding to
+-- rows in the normalized matrix B. See Shu et al., "Efficient Spectral
+-- Neighborhood Blocking for Entity Resolution", 2011.
+-- L = sum_i^n sum_j^n A(i,j) - n = 1^TA1 - n = (B^T1)^T(B^T1) - n.
+getBModularity :: LabelVector -> B -> Q
+getBModularity moduleVec (B b) = Q . sum . fmap inner $ [first, second]
+  where
+    inner v = (a v v / l) - ((a v (S.ones n) / l) ** 2)
+    first  = moduleVec
+    second = S.fromDenseList
+           . (fmap . fmap) (bool 1 0 . (== 1))
+           . S.toDenseList
+           $ moduleVec
+    l    = a (S.ones n) (S.ones n)
+    a :: S.SparseMatrixXd -> S.SparseMatrixXd -> Double
+    a oneL oneR = ( flip (S.!) (0, 0)
+                  $ (S.transpose (partA oneL)) * (partA oneR)
+                  )
+                - (S.getSum oneL)
+    partA one = (S.transpose b) * one
+    n    = S.rows b
+
+-- | Set the diagonal of a sparse matrix to 0.
+setDiag0 :: S.SparseMatrixXd -> S.SparseMatrixXd
+setDiag0 = S._imap (\x y z -> if x == y then 0 else z)
+
+-- | Test whether getModularity BB^T is the same as getBModularity B.
+testModularity :: (Bool, Q, Q)
+testModularity = (modA == modB, modA, modB)
+  where
+    items = S.fromDenseList (fmap (:[]) [1,1,0,0] :: [[Double]])
+    b     = getB True $ S.fromDenseList ([[1,1],[0,0],[0,0],[1,1]] :: [[Double]])
+    a     = setDiag0 $ (unB b) * S.transpose (unB b)
+    modA  = getModularity items a
+    modB  = getBModularity items b
diff --git a/src/Math/Modularity/Sparse.hs b/src/Math/Modularity/Sparse.hs
new file mode 100644
--- /dev/null
+++ b/src/Math/Modularity/Sparse.hs
@@ -0,0 +1,98 @@
+{- Math.Sparse.Modularity
+Gregory W. Schwartz
+
+Collects the functions pertaining to finding the Newman-Girvan modularity of a
+sparse adjacency matrix.
+-}
+
+{-# LANGUAGE BangPatterns #-}
+
+module Math.Modularity.Sparse
+    ( getModularity
+    , getBModularity
+    , Q (..)
+    , testModularity
+    ) where
+
+-- Remote
+import Data.Bool (bool)
+import Math.Clustering.Spectral.Sparse (B (..), getB)
+import qualified Data.Sparse.Common as S
+import qualified Numeric.LinearAlgebra.Sparse as S
+import qualified Data.Vector as V
+
+-- Local
+import Math.Modularity.Types
+
+type LabelVector     = S.SpVector Double
+type AdjacencyMatrix = S.SpMatrix Double
+
+-- | Find modularity from a vector of community labels (0 or 1) corresponding to
+-- rows in the adjacency matrix. Needs 0s on the diagonal for the adjacency
+-- matrix.
+getModularity :: LabelVector -> AdjacencyMatrix -> Q
+getModularity moduleVec mat = Q $ (1 / (2 * m)) * sumQ mat
+  where
+    sumQ :: S.SpMatrix Double -> Double
+    sumQ = sum
+         . fmap (\ (!v, !xs)
+                  -> sum
+                   . fmap (\(!w, !x) -> inner v w x * delta v w)
+                   . zip [0,1..]
+                   . S.toDenseListSV
+                   $ xs
+                )
+         . zip [0,1..]
+         . S.toRowsL
+    inner v w x = x - ((k v * k w) / (2 * m))
+    delta v w = ((s v * s w) + 1) / 2
+    m = (/ 2) . sum $ mat -- Symmetric matrix so divide by 2.
+    d = S.sparsifySV . S.vr . fmap sum . S.toRowsL $ mat
+    s = bool (-1) 1 . (== 0) . flip S.lookupDenseSV moduleVec
+    k = flip S.lookupDenseSV d
+
+-- | Find modularity from a vector of community labels (0 or 1) corresponding to
+-- rows in the normalized matrix B. See Shu et al., "Efficient Spectral
+-- Neighborhood Blocking for Entity Resolution", 2011.
+-- L = sum_i^n sum_j^n A(i,j) - n = 1^TA1 - n = (B^T1)^T(B^T1) - n.
+getBModularity :: LabelVector -> B -> Q
+getBModularity moduleVec (B b) = Q . sum . fmap inner $ [first, second]
+  where
+    inner v = (a v v / l) - ((a v (ones n) / l) ** 2)
+    first  = S.fromColsL [moduleVec]
+    second = S.fromColsL
+           . (:[])
+           . S.sparsifySV
+           . S.vr
+           . fmap (bool 1 0 . (== 1))
+           . S.toDenseListSV
+           $ moduleVec
+    l    = a (ones n) (ones n)
+    a :: S.SpMatrix Double -> S.SpMatrix Double -> Double
+    a oneL oneR = ( flip S.lookupWD_SM (0, 0)
+                  $ (S.transposeSM (partA oneL)) S.#~# (partA oneR)
+                  )
+                - (sum oneL)
+    partA one = (S.transposeSM b) S.#~# one
+    n    = S.nrows b
+
+-- | Get a column vector of ones.
+ones :: Int -> S.SpMatrix Double
+ones n = S.fromColsL [S.onesSV n]
+
+-- | Set the diagonal of a sparse matrix to 0.
+setDiag0 :: S.SpMatrix Double -> S.SpMatrix Double
+setDiag0 mat = S.fromListSM (S.dimSM mat)
+             . fmap (\(!x, !y, !z) -> if x == y then (x, y, 0) else (x, y, z))
+             . S.toListSM
+             $ mat
+
+-- | Test whether getModularity BB^T is the same as getBModularity B.
+testModularity :: (Bool, Q, Q)
+testModularity = (modA == modB, modA, modB)
+  where
+    items = S.fromListDenseSV 4 ([1,1,0,0] :: [Double])
+    b     = getB True $ S.fromListDenseSM 4 ([1,1,0,0,0,0,1,1] :: [Double])
+    a     = setDiag0 $ (unB b) S.#~# S.transposeSM (unB b)
+    modA  = getModularity items a
+    modB  = getBModularity items b
diff --git a/src/Math/Modularity/Types.hs b/src/Math/Modularity/Types.hs
new file mode 100644
--- /dev/null
+++ b/src/Math/Modularity/Types.hs
@@ -0,0 +1,17 @@
+{- Math.Modularity.Types
+Gregory W. Schwartz
+
+Collects the types used in modularity.
+-}
+
+{-# LANGUAGE GeneralizedNewtypeDeriving #-}
+{-# LANGUAGE DeriveGeneric #-}
+
+module Math.Modularity.Types where
+
+-- Remote
+import GHC.Generics (Generic)
+
+-- Local
+
+newtype Q = Q { unQ :: Double } deriving (Eq, Ord, Read, Show, Num, Generic)