X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=src%2FLinear%2FMatrix.hs;h=69a74b50eeacf7ea944c790d3858dd0cba12c266;hb=d8dc884aa9b16c7bbd88c4c107ddd684a339a191;hp=c48f722265b19e3bd195ce5dc16e3ab44162d137;hpb=504257320e56784b914ff69e8efb22d6191e3372;p=numerical-analysis.git

diff --git a/src/Linear/Matrix.hs b/src/Linear/Matrix.hs
index c48f722..69a74b5 100644
--- a/src/Linear/Matrix.hs
+++ b/src/Linear/Matrix.hs
@@ -2,6 +2,7 @@
 {-# LANGUAGE FlexibleContexts #-}
 {-# LANGUAGE FlexibleInstances #-}
 {-# LANGUAGE MultiParamTypeClasses #-}
+{-# LANGUAGE NoMonomorphismRestriction #-}
 {-# LANGUAGE ScopedTypeVariables #-}
 {-# LANGUAGE TypeFamilies #-}
 {-# LANGUAGE RebindableSyntax #-}
@@ -43,7 +44,6 @@ import qualified Data.Vector.Fixed as V (
   toList,
   zipWith
   )
-import Data.Vector.Fixed.Boxed (Vec)
 import Data.Vector.Fixed.Cont (Arity, arity)
 import Linear.Vector
 import Normed
@@ -213,6 +213,18 @@ construct lambda = Mat $ generate make_row
     make_row i = generate (lambda i)
 
 
+-- | Create an identity matrix with the right dimensions.
+--
+--   Examples:
+--
+--   >>> identity_matrix :: Mat3 Int
+--   ((1,0,0),(0,1,0),(0,0,1))
+--   >>> identity_matrix :: Mat3 Double
+--   ((1.0,0.0,0.0),(0.0,1.0,0.0),(0.0,0.0,1.0))
+--
+identity_matrix :: (Arity m, Ring.C a) => Mat m m a
+identity_matrix =
+  construct (\i j -> if i == j then (fromInteger 1) else (fromInteger 0))
 
 -- | Given a positive-definite matrix @m@, computes the
 --   upper-triangular matrix @r@ with (transpose r)*r == m and all
@@ -416,8 +428,8 @@ instance (Algebraic.C a,
           ToRational.C a,
           Arity m)
          => Normed (Mat (S m) N1 a) where
-  -- | Generic p-norms. The usual norm in R^n is (norm_p 2). We treat
-  --   all matrices as big vectors.
+  -- | Generic p-norms for vectors in R^n that are represented as nx1
+  --   matrices.
   --
   --   Examples:
   --
@@ -445,7 +457,26 @@ instance (Algebraic.C a,
     fromRational' $ toRational $ V.maximum $ V.map V.maximum rows
 
 
-
+-- | Compute the Frobenius norm of a matrix. This essentially treats
+--   the matrix as one long vector containing all of its entries (in
+--   any order, it doesn't matter).
+--
+--   Examples:
+--
+--   >>> let m = fromList [[1, 2, 3],[4,5,6],[7,8,9]] :: Mat3 Double
+--   >>> frobenius_norm m == sqrt 285
+--   True
+--
+--   >>> let m = fromList [[1, -1, 1],[-1,1,-1],[1,-1,1]] :: Mat3 Double
+--   >>> frobenius_norm m == 3
+--   True
+--
+frobenius_norm :: (Algebraic.C a, Ring.C a) => Mat m n a -> a
+frobenius_norm (Mat rows) =
+  sqrt $ element_sum $ V.map row_sum rows
+  where
+    -- | Square and add up the entries of a row.
+    row_sum = element_sum . V.map (^2)
 
 
 -- Vector helpers. We want it to be easy to create low-dimension