From ededdfaf56d6f7d07ae171310dc701601adec45f Mon Sep 17 00:00:00 2001
From: Almar Klein <almar.klein@gmail.com>
Date: Wed, 25 May 2016 10:53:06 +0200
Subject: [PATCH] improve docs and acks related to new MC alg

---
 CONTRIBUTORS.txt                             |  3 +++
 skimage/measure/_marching_cubes_lewiner.py   | 14 ++++++++------
 skimage/measure/mc_meta/visual_test.py       |  4 ++--
 skimage/measure/tests/test_marching_cubes.py |  1 +
 4 files changed, 14 insertions(+), 8 deletions(-)

diff --git a/CONTRIBUTORS.txt b/CONTRIBUTORS.txt
index e4c852e6..921a2b1b 100644
--- a/CONTRIBUTORS.txt
+++ b/CONTRIBUTORS.txt
@@ -230,6 +230,9 @@
 - Alex Izvorski
   Color spaces for YUV and related spaces
 
+- Thomas Lewiner
+  Design and original implementation of the Lewiner marching cubes algorithm
+
 - Jeff Hemmelgarn
   Minimum threshold
 
diff --git a/skimage/measure/_marching_cubes_lewiner.py b/skimage/measure/_marching_cubes_lewiner.py
index 7f8339e5..ab5976af 100644
--- a/skimage/measure/_marching_cubes_lewiner.py
+++ b/skimage/measure/_marching_cubes_lewiner.py
@@ -52,7 +52,9 @@ def marching_cubes_lewiner(volume, level=None, spacing=(1., 1., 1.),
         If given and True, the classic marching cubes by Lorensen (1987)
         is used. This option is included for reference purposes. Note
         that this algorithm has ambiguities and is not guaranteed to
-        produce a topologically correct result.
+        produce a topologically correct result. The results with using
+        this option are *not* generally the same as the ``marching_cubes()``
+        function.
     
     Returns
     -------
@@ -74,11 +76,11 @@ def marching_cubes_lewiner(volume, level=None, spacing=(1., 1., 1.),
     Notes about the algorithm
     -------------------------
     
-    The algorithm [1] is an improved version of Chernyaev's Marching Cubes 33
-    algorithm, originally written in C++. It is an efficient algorithm
-    that relies on heavy use of lookup tables to handle the many different 
-    cases. This keeps the algorithm relatively easy. The current algorithm
-    is a port of Lewiner's algorithm and written in Cython.
+    The algorithm [1] is an improved version of Chernyaev's Marching
+    Cubes 33 algorithm. It is an efficient algorithm that relies on
+    heavy use of lookup tables to handle the many different cases,
+    keeping the algorithm relatively easy. This implementation is
+    written in Cython, ported from Lewiner's C++ implementation.
     
     References
     ----------
diff --git a/skimage/measure/mc_meta/visual_test.py b/skimage/measure/mc_meta/visual_test.py
index e8b7e717..f04ade92 100644
--- a/skimage/measure/mc_meta/visual_test.py
+++ b/skimage/measure/mc_meta/visual_test.py
@@ -27,7 +27,7 @@ elif SELECT == 2:
     isovalue = 0.2
 
 elif SELECT == 3:
-    # Generate two donuts
+    # Generate two donuts using a formula by Thomas Lewiner
     n = 48
     a, b = 2.5/n, -1.25
     isovalue = 0.0
@@ -53,7 +53,7 @@ elif SELECT == 4:
 
 # Get surface meshes
 t0 = time.time()
-vertices1, faces1, *_ = marching_cubes_lewiner(vol, isovalue, gradient_direction=gradient_dir, use_classic=False)
+vertices1, faces1, *_ = marching_cubes_lewiner(vol, isovalue, gradient_direction=gradient_dir, use_classic=True)
 print('finding surface lewiner took %1.0f ms' % (1000*(time.time()-t0)) )
 
 t0 = time.time()
diff --git a/skimage/measure/tests/test_marching_cubes.py b/skimage/measure/tests/test_marching_cubes.py
index 25262682..e46a4207 100644
--- a/skimage/measure/tests/test_marching_cubes.py
+++ b/skimage/measure/tests/test_marching_cubes.py
@@ -138,6 +138,7 @@ def test_both_algs_same_result_donut():
     for iz in range(vol.shape[0]):
         for iy in range(vol.shape[1]):
             for ix in range(vol.shape[2]):
+                # Double-torii formula by Thomas Lewiner
                 z, y, x = float(iz)*a+b, float(iy)*a+b, float(ix)*a+b
                 vol[iz,iy,ix] = ( ( 
                     (8*x)**2 + (8*y-2)**2 + (8*z)**2 + 16 - 1.85*1.85 ) * ( (8*x)**2 +