diff --git a/Data/Random/Manifold.hs b/Data/Random/Manifold.hs
--- a/Data/Random/Manifold.hs
+++ b/Data/Random/Manifold.hs
@@ -21,6 +21,7 @@
 import Data.Manifold.TreeCover
 
 import Data.Semigroup
+import Data.Maybe (catMaybes)
 
 import Data.Random
 
@@ -40,7 +41,7 @@
 shadeT' :: (PseudoAffine x, SimpleSpace (Needle x), Scalar (Needle x) ~ ℝ)
                       => Interior x -> Variance (Needle x) -> RVarT m x
 shadeT' ctr expa = ((ctr.+~^) . sumV) <$> mapM (\v -> (v^*) <$> stdNormalT) eigSpan
-   where eigSpan = normSpanningSystem expa
+   where eigSpan = varianceSpanningSystem expa
 
 -- | A shade can be considered a specification for a generalised normal distribution.
 -- 
@@ -59,7 +60,12 @@
         ( WithField ℝ Manifold x, SimpleSpace (Needle x)
         , WithField ℝ Manifold y, SimpleSpace (Needle y) )
        => Int -> Shade x -> (x -> Shade y) -> RVarT m (x`Shaded`y)
-uncertainFunctionSamplesT n shx f = do
+uncertainFunctionSamplesT n shx f = case ( dualSpaceWitness :: DualNeedleWitness x
+                                         , dualSpaceWitness :: DualNeedleWitness y
+                                         , boundarylessWitness :: BoundarylessWitness x
+                                         , pseudoAffineWitness :: PseudoAffineWitness y ) of
+    ( DualSpaceWitness, DualSpaceWitness, BoundarylessWitness
+     ,PseudoAffineWitness (SemimanifoldWitness BoundarylessWitness) ) -> do
       domainSpls <- replicateM n $ rvarT shx
       pts <- forM domainSpls $ \x -> do
          y <- rvarT $ f x
@@ -84,16 +90,17 @@
                        mkControlSample ((x,y):css)
                          $ confidence + occlusion shl (x,y)
              css <- mkControlSample [] 0
-             let [Shade (xCtrl,yCtrl) expaCtrl :: Shade (x,y)] = pointsShades css
+             let [Shade (xCtrl,yCtrl) expaCtrl :: Shade (x,y)]
+                       = pointsShades . catMaybes $ toInterior<$>css
                  yCtrl :: Interior y
                  expayCtrl = dualNorm . snd $ summandSpaceNorms expaCtrl
                  jCtrl = dependence expaCtrl
                  jFin = jOrig^*η ^+^ jCtrl^*η'
-                 Option (Just δx) = xlc.-~.xCtrl
+                 Just δx = xlc.-~.xCtrl
                  η, η' :: ℝ
                  η = nPerTwig / (nPerTwig + fromIntegral (length css))
                  η' = 1 - η
-                 Option (Just δy) = yCtrl.-~.ylc
+                 Just δy = yCtrl.-~.ylc
              return ( xlc .+~^ δx^*η'
                     , ( Shade' (ylc .+~^ δy^*η')
                                (scaleNorm (sqrt η) expay <> scaleNorm (sqrt η') expayCtrl)
diff --git a/manifold-random.cabal b/manifold-random.cabal
--- a/manifold-random.cabal
+++ b/manifold-random.cabal
@@ -2,7 +2,7 @@
 -- documentation, see http://haskell.org/cabal/users-guide/
 
 name:                manifold-random
-version:             0.3.0.0
+version:             0.4.0.0
 synopsis:            Sampling random points on general manifolds.
 -- description:         
 homepage:            https://github.com/leftaroundabout/manifolds
@@ -26,7 +26,7 @@
   -- other-extensions:    
   build-depends:       base >=4.7 && <5
                        , random-fu >=0.2 && <0.3
-                       , manifolds >=0.3 && < 0.3.1
+                       , manifolds == 0.4.0.0
                        , constrained-categories
                        , semigroups
                        , vector-space