From 1769cdddcffb7c9d9e26600392eeac5252a4bd37 Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@gmail.com>
Date: Wed, 6 May 2015 00:47:31 +0530
Subject: [PATCH 01/18] added boundary rag construction

---
 doc/examples/plot_rag_boundary.py      | 28 ++++++++++
 skimage/future/graph/__init__.py       |  3 +-
 skimage/future/graph/rag.py            | 73 ++++++++++++++++++++++++++
 skimage/future/graph/tests/test_rag.py | 17 ++++++
 4 files changed, 120 insertions(+), 1 deletion(-)
 create mode 100644 doc/examples/plot_rag_boundary.py

diff --git a/doc/examples/plot_rag_boundary.py b/doc/examples/plot_rag_boundary.py
new file mode 100644
index 00000000..eeff1589
--- /dev/null
+++ b/doc/examples/plot_rag_boundary.py
@@ -0,0 +1,28 @@
+"""
+==========================
+Region Boundary based RAGs
+==========================
+
+This example demonstrates construction of region boundary based RAGs with the
+`rag_boundary` function.
+"""
+from skimage.future import graph
+from skimage import data, segmentation, color, filters, io
+from matplotlib import pyplot as plt, colors
+
+img = data.coffee()
+gimg = color.rgb2gray(img)
+
+labels = segmentation.slic(img, compactness=30, n_segments=400)
+edges = filters.sobel(gimg)
+edges_rgb = color.gray2rgb(edges)
+
+mimg = segmentation.mark_boundaries(img, labels, (0,0,0))
+
+g = graph.rag_boundary(labels, edges)
+
+cmap = colors.ListedColormap(['#0000ff', '#ff0000'])
+out = graph.draw_rag(labels, g, edges_rgb, node_color="#ffff00", colormap=cmap)
+
+io.imshow(out)
+io.show()
diff --git a/skimage/future/graph/__init__.py b/skimage/future/graph/__init__.py
index 6b7e0aaa..e73c8d19 100644
--- a/skimage/future/graph/__init__.py
+++ b/skimage/future/graph/__init__.py
@@ -1,5 +1,5 @@
 from .graph_cut import cut_threshold, cut_normalized
-from .rag import rag_mean_color, RAG, draw_rag
+from .rag import rag_mean_color, RAG, draw_rag, rag_boundary
 from .graph_merge import merge_hierarchical
 ncut = cut_normalized
 
@@ -9,4 +9,5 @@ __all__ = ['rag_mean_color',
            'ncut',
            'draw_rag',
            'merge_hierarchical',
+           'rag_boundary'
            'RAG']
diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index 6a45447b..6c8fa502 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -311,6 +311,79 @@ def rag_mean_color(image, labels, connectivity=2, mode='distance',
     return graph
 
 
+def rag_boundary(labels, edge_map, connectivity=2):
+    """ Comouter RAG based on region boundaries
+
+    Given an image's initial segmentation and its edge map this method
+    constructs the corresponding Region Adjacency Graph (RAG). Each node in the
+    RAG represents a set of pixels within the image with the same label in
+    `labels`. The weight between two adjacent regions is the average value
+    in `edge_map` along their boundary.
+
+    labels : ndarray
+        The labelled image.
+    edge_map : ndarray
+        This should have the same shape as that of `labels`. For all pixels
+        along the boundary between 2 adjacent regions, the average value of the
+        corresponding pixels in `edge_map` is the edge weight between them.
+    connectivity : int, optional
+        Pixels with a squared distance less than `connectivity` from each other
+        are considered adjacent. It can range from 1 to `labels.ndim`. Its
+        behavior is the same as `connectivity` parameter in
+        `scipy.ndimage.filters.generate_binary_structure`.
+
+    Examples
+    --------
+    >>> from skimage import data, segmentation, filters, color
+    >>> from skimage.future import graph
+    >>> img = data.chelsea()
+    >>> labels = segmentation.slic(img)
+    >>> edge_map = filters.sobel(color.rgb2gray(img))
+    >>> rag = graph.rag_mean_color(labels, edge_map)
+
+    """
+
+    graph = RAG()
+
+    #Computing the relative indices of the neighbors
+    nbr_indices = list(np.ndindex(*[2]*labels.ndim))
+    del nbr_indices[0]
+    nbr_indices_arr = ([idx for idx in nbr_indices if np.linalg.norm(idx)
+                   <= connectivity])
+
+
+    iter_shape = tuple(np.array(labels.shape) - 1)
+
+    for index in np.ndindex(iter_shape):
+
+        index_arr = np.array(index)
+        current = labels[index]
+        graph.add_node(current, {'labels':[current]})
+
+        for nbr_index in nbr_indices_arr:
+
+            adjacent_idx = tuple(index_arr + nbr_index)
+            adjacent = labels[adjacent_idx]
+
+            if current==adjacent:
+                continue
+
+            if graph.has_edge(current, adjacent):
+                graph[current][adjacent]['pixel count'] += 2
+                intensity = edge_map[index] + edge_map[adjacent_idx]
+                graph[current][adjacent]['total intensity'] += intensity
+            else:
+                graph.add_edge(current, adjacent)
+                graph[current][adjacent]['pixel count'] = 2
+                intensity = edge_map[index] + edge_map[adjacent_idx]
+                graph[current][adjacent]['total intensity'] = intensity
+
+    for (x, y, data) in graph.edges_iter(data=True):
+        data['weight'] = data['total intensity']/data['pixel count']
+
+    return graph
+
+
 def draw_rag(labels, rag, img, border_color=None, node_color='#ffff00',
              edge_color='#00ff00', colormap=None, thresh=np.inf,
              desaturate=False, in_place=True):
diff --git a/skimage/future/graph/tests/test_rag.py b/skimage/future/graph/tests/test_rag.py
index e5882e20..8f1df909 100644
--- a/skimage/future/graph/tests/test_rag.py
+++ b/skimage/future/graph/tests/test_rag.py
@@ -196,3 +196,20 @@ def test_generic_rag_3d():
     assert h.has_edge(0, 1) and h.has_edge(0, 3) and not h.has_edge(0, 7)
     k = graph.RAG(labels, connectivity=3)
     assert k.has_edge(0, 1) and k.has_edge(1, 2) and k.has_edge(2, 5)
+
+
+def test_rag_boundary():
+    labels = np.zeros((16, 16), dtype='uint8')
+    edge_map = np.zeros_like(labels, dtype=float)
+
+    edge_map[8,:] = 0.5
+    edge_map[:,8] = 1.0
+
+    labels[:8, :8] = 1
+    labels[:8, 8:] = 2
+    labels[8:, :8] = 3
+    labels[8:, 8:] = 4
+
+    g = graph.rag_boundary(labels, edge_map, connectivity=1)
+    assert len(g.nodes()) == 4
+    assert len(g.edges()) == 4
\ No newline at end of file

From 3cf6c8b1ce204d69f8654e960db42d298b3ed8ee Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@gmail.com>
Date: Wed, 6 May 2015 00:50:58 +0530
Subject: [PATCH 02/18] removed unnecessary statement

---
 doc/examples/plot_rag_boundary.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/doc/examples/plot_rag_boundary.py b/doc/examples/plot_rag_boundary.py
index eeff1589..5324a2bd 100644
--- a/doc/examples/plot_rag_boundary.py
+++ b/doc/examples/plot_rag_boundary.py
@@ -17,8 +17,6 @@ labels = segmentation.slic(img, compactness=30, n_segments=400)
 edges = filters.sobel(gimg)
 edges_rgb = color.gray2rgb(edges)
 
-mimg = segmentation.mark_boundaries(img, labels, (0,0,0))
-
 g = graph.rag_boundary(labels, edges)
 
 cmap = colors.ListedColormap(['#0000ff', '#ff0000'])

From caba3041d170311c801ed84d63fa975aa265ac84 Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@gmail.com>
Date: Wed, 6 May 2015 00:55:04 +0530
Subject: [PATCH 03/18] indentation correction

---
 doc/examples/plot_rag_boundary.py      | 2 +-
 skimage/future/graph/rag.py            | 7 +++----
 skimage/future/graph/tests/test_rag.py | 4 ++--
 3 files changed, 6 insertions(+), 7 deletions(-)

diff --git a/doc/examples/plot_rag_boundary.py b/doc/examples/plot_rag_boundary.py
index 5324a2bd..fb2e51a5 100644
--- a/doc/examples/plot_rag_boundary.py
+++ b/doc/examples/plot_rag_boundary.py
@@ -8,7 +8,7 @@ This example demonstrates construction of region boundary based RAGs with the
 """
 from skimage.future import graph
 from skimage import data, segmentation, color, filters, io
-from matplotlib import pyplot as plt, colors
+from matplotlib import pyplot as colors
 
 img = data.coffee()
 gimg = color.rgb2gray(img)
diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index 6c8fa502..ab6d2fc7 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -349,8 +349,7 @@ def rag_boundary(labels, edge_map, connectivity=2):
     nbr_indices = list(np.ndindex(*[2]*labels.ndim))
     del nbr_indices[0]
     nbr_indices_arr = ([idx for idx in nbr_indices if np.linalg.norm(idx)
-                   <= connectivity])
-
+                        <= connectivity])
 
     iter_shape = tuple(np.array(labels.shape) - 1)
 
@@ -358,14 +357,14 @@ def rag_boundary(labels, edge_map, connectivity=2):
 
         index_arr = np.array(index)
         current = labels[index]
-        graph.add_node(current, {'labels':[current]})
+        graph.add_node(current, {'labels': [current]})
 
         for nbr_index in nbr_indices_arr:
 
             adjacent_idx = tuple(index_arr + nbr_index)
             adjacent = labels[adjacent_idx]
 
-            if current==adjacent:
+            if current == adjacent:
                 continue
 
             if graph.has_edge(current, adjacent):
diff --git a/skimage/future/graph/tests/test_rag.py b/skimage/future/graph/tests/test_rag.py
index 8f1df909..4af3d854 100644
--- a/skimage/future/graph/tests/test_rag.py
+++ b/skimage/future/graph/tests/test_rag.py
@@ -202,8 +202,8 @@ def test_rag_boundary():
     labels = np.zeros((16, 16), dtype='uint8')
     edge_map = np.zeros_like(labels, dtype=float)
 
-    edge_map[8,:] = 0.5
-    edge_map[:,8] = 1.0
+    edge_map[8, :] = 0.5
+    edge_map[:, 8] = 1.0
 
     labels[:8, :8] = 1
     labels[:8, 8:] = 2

From 4041fc635410bd719adad93f2497c6ba227c2de5 Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@gmail.com>
Date: Wed, 6 May 2015 01:02:01 +0530
Subject: [PATCH 04/18] corrected colors import

---
 doc/examples/plot_rag_boundary.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/examples/plot_rag_boundary.py b/doc/examples/plot_rag_boundary.py
index fb2e51a5..b35ec221 100644
--- a/doc/examples/plot_rag_boundary.py
+++ b/doc/examples/plot_rag_boundary.py
@@ -8,7 +8,7 @@ This example demonstrates construction of region boundary based RAGs with the
 """
 from skimage.future import graph
 from skimage import data, segmentation, color, filters, io
-from matplotlib import pyplot as colors
+from matplotlib import colors
 
 img = data.coffee()
 gimg = color.rgb2gray(img)

From 4c05e6567068a7f082239558b4ca9aebe4dd2b42 Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@nyu.edu>
Date: Thu, 17 Dec 2015 00:48:56 -0500
Subject: [PATCH 05/18] changed logic to use erosion/dilation

---
 skimage/future/graph/rag.py | 50 ++++++++++++++++---------------------
 1 file changed, 21 insertions(+), 29 deletions(-)

diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index ab6d2fc7..51019798 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -2,8 +2,9 @@ import networkx as nx
 import numpy as np
 from numpy.lib.stride_tricks import as_strided
 from scipy import ndimage as ndi
+from scipy import sparse
 import math
-from ... import draw, measure, segmentation, util, color
+from ... import draw, measure, segmentation, util, color, morphology
 try:
     from matplotlib import colors
     from matplotlib import cm
@@ -344,41 +345,32 @@ def rag_boundary(labels, edge_map, connectivity=2):
     """
 
     graph = RAG()
+    eroded = morphology.erosion(labels)
+    dilated = morphology.dilation(labels)
+    boundaries = eroded != dilated
 
-    #Computing the relative indices of the neighbors
-    nbr_indices = list(np.ndindex(*[2]*labels.ndim))
-    del nbr_indices[0]
-    nbr_indices_arr = ([idx for idx in nbr_indices if np.linalg.norm(idx)
-                        <= connectivity])
+    small_labels = eroded[boundaries]
+    large_labels = dilated[boundaries]
+    data = edge_map[boundaries]
 
-    iter_shape = tuple(np.array(labels.shape) - 1)
+    # coo logic sums values of duplicate indices
+    edge_data = sparse.coo_matrix((data, (small_labels, large_labels))).tocsr()
 
-    for index in np.ndindex(iter_shape):
+    # create a repeating array of [1., 1., ...] using stride tricks to save memory
+    counts = np.ones((1,), dtype=float)
+    counts = as_strided(counts, shape=small_labels.shape, strides=(0,))
+    # use COO matrix to count the ones at each location
+    edge_count = sparse.coo_matrix((counts, (small_labels, large_labels))).tocsr()
 
-        index_arr = np.array(index)
-        current = labels[index]
-        graph.add_node(current, {'labels': [current]})
+    edge_data.data /= edge_count.data
 
-        for nbr_index in nbr_indices_arr:
+    rows, cols = edge_data.nonzero()
+    graph_data = zip(rows, cols, edge_data.data)
 
-            adjacent_idx = tuple(index_arr + nbr_index)
-            adjacent = labels[adjacent_idx]
+    graph.add_weighted_edges_from(graph_data)
 
-            if current == adjacent:
-                continue
-
-            if graph.has_edge(current, adjacent):
-                graph[current][adjacent]['pixel count'] += 2
-                intensity = edge_map[index] + edge_map[adjacent_idx]
-                graph[current][adjacent]['total intensity'] += intensity
-            else:
-                graph.add_edge(current, adjacent)
-                graph[current][adjacent]['pixel count'] = 2
-                intensity = edge_map[index] + edge_map[adjacent_idx]
-                graph[current][adjacent]['total intensity'] = intensity
-
-    for (x, y, data) in graph.edges_iter(data=True):
-        data['weight'] = data['total intensity']/data['pixel count']
+    for n in graph.nodes():
+        graph.node[n].update({'labels': [n]})
 
     return graph
 

From a95c0bdddcc385052e31a56e88c5769616b0f773 Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@nyu.edu>
Date: Thu, 17 Dec 2015 01:05:07 -0500
Subject: [PATCH 06/18] passing selem argument

---
 skimage/future/graph/rag.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index 51019798..8cd09106 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -345,8 +345,10 @@ def rag_boundary(labels, edge_map, connectivity=2):
     """
 
     graph = RAG()
-    eroded = morphology.erosion(labels)
-    dilated = morphology.dilation(labels)
+    fp = ndi.generate_binary_structure(labels.ndim, connectivity)
+    print(fp)
+    eroded = morphology.erosion(labels, selem=fp)
+    dilated = morphology.dilation(labels, selem=fp)
     boundaries = eroded != dilated
 
     small_labels = eroded[boundaries]

From e8f2805d644b61085010b4e2918473fd640f44b4 Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@nyu.edu>
Date: Wed, 6 Jan 2016 15:04:09 -0500
Subject: [PATCH 07/18] changed to eosion/dilation logic

---
 doc/examples/plot_rag_boundary.py |  5 ++--
 skimage/future/graph/rag.py       | 50 +++++++++++++++----------------
 2 files changed, 27 insertions(+), 28 deletions(-)

diff --git a/doc/examples/plot_rag_boundary.py b/doc/examples/plot_rag_boundary.py
index b35ec221..c975f884 100644
--- a/doc/examples/plot_rag_boundary.py
+++ b/doc/examples/plot_rag_boundary.py
@@ -9,6 +9,7 @@ This example demonstrates construction of region boundary based RAGs with the
 from skimage.future import graph
 from skimage import data, segmentation, color, filters, io
 from matplotlib import colors
+import numpy as np
 
 img = data.coffee()
 gimg = color.rgb2gray(img)
@@ -19,8 +20,8 @@ edges_rgb = color.gray2rgb(edges)
 
 g = graph.rag_boundary(labels, edges)
 
-cmap = colors.ListedColormap(['#0000ff', '#ff0000'])
-out = graph.draw_rag(labels, g, edges_rgb, node_color="#ffff00", colormap=cmap)
+out = graph.draw_rag(labels, g, edges_rgb, node_color="#ffff00",
+                     colormap='plasma')
 
 io.imshow(out)
 io.show()
diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index 8cd09106..fc6e1d6f 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -344,37 +344,35 @@ def rag_boundary(labels, edge_map, connectivity=2):
 
     """
 
-    graph = RAG()
-    fp = ndi.generate_binary_structure(labels.ndim, connectivity)
-    print(fp)
-    eroded = morphology.erosion(labels, selem=fp)
-    dilated = morphology.dilation(labels, selem=fp)
-    boundaries = eroded != dilated
+    conn = ndi.generate_binary_structure(labels.ndim, connectivity)
+    eroded = ndi.grey_erosion(labels, footprint=conn)
+    dilated = ndi.grey_dilation(labels, footprint=conn)
+    boundaries0 = (eroded != labels)
+    boundaries1 = (dilated != labels)
+    labels_small = np.concatenate((eroded[boundaries0], labels[boundaries1]))
+    labels_large = np.concatenate((labels[boundaries0], dilated[boundaries1]))
+    n = np.max(labels_large) + 1
 
-    small_labels = eroded[boundaries]
-    large_labels = dilated[boundaries]
-    data = edge_map[boundaries]
+    # use a dummy broadcast array as data for RAG
+    ones = np.broadcast_to(np.ones((1,), dtype=np.int_),
+                           labels_small.shape)
+    count_matrix = sparse.coo_matrix((ones, (labels_small, labels_large)),
+                                     dtype=np.int_, shape=(n, n)).tocsr()
+    data = np.concatenate((edge_map[boundaries0], edge_map[boundaries1]))
 
-    # coo logic sums values of duplicate indices
-    edge_data = sparse.coo_matrix((data, (small_labels, large_labels))).tocsr()
+    data_coo = sparse.coo_matrix((data, (labels_small, labels_large)))
+    graph_matrix = data_coo.tocsr()
+    graph_matrix.data /= count_matrix.data
 
-    # create a repeating array of [1., 1., ...] using stride tricks to save memory
-    counts = np.ones((1,), dtype=float)
-    counts = as_strided(counts, shape=small_labels.shape, strides=(0,))
-    # use COO matrix to count the ones at each location
-    edge_count = sparse.coo_matrix((counts, (small_labels, large_labels))).tocsr()
+    rag = nx.Graph()
+    rows, cols = graph_matrix.nonzero()
+    graph_data = zip(rows, cols, graph_matrix.data)
+    rag.add_weighted_edges_from(graph_data)
 
-    edge_data.data /= edge_count.data
+    for n in rag.nodes():
+        rag.node[n].update({'labels': [n]})
 
-    rows, cols = edge_data.nonzero()
-    graph_data = zip(rows, cols, edge_data.data)
-
-    graph.add_weighted_edges_from(graph_data)
-
-    for n in graph.nodes():
-        graph.node[n].update({'labels': [n]})
-
-    return graph
+    return rag
 
 
 def draw_rag(labels, rag, img, border_color=None, node_color='#ffff00',

From 422dfc6c22178071e46b001920891e5ff254e63a Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@nyu.edu>
Date: Wed, 6 Jan 2016 15:17:48 -0500
Subject: [PATCH 08/18] cleanup

---
 doc/examples/plot_rag_boundary.py      | 2 --
 skimage/future/graph/__init__.py       | 2 +-
 skimage/future/graph/rag.py            | 6 +++---
 skimage/future/graph/tests/test_rag.py | 2 +-
 4 files changed, 5 insertions(+), 7 deletions(-)

diff --git a/doc/examples/plot_rag_boundary.py b/doc/examples/plot_rag_boundary.py
index c975f884..5063d96a 100644
--- a/doc/examples/plot_rag_boundary.py
+++ b/doc/examples/plot_rag_boundary.py
@@ -8,8 +8,6 @@ This example demonstrates construction of region boundary based RAGs with the
 """
 from skimage.future import graph
 from skimage import data, segmentation, color, filters, io
-from matplotlib import colors
-import numpy as np
 
 img = data.coffee()
 gimg = color.rgb2gray(img)
diff --git a/skimage/future/graph/__init__.py b/skimage/future/graph/__init__.py
index e73c8d19..d685a793 100644
--- a/skimage/future/graph/__init__.py
+++ b/skimage/future/graph/__init__.py
@@ -9,5 +9,5 @@ __all__ = ['rag_mean_color',
            'ncut',
            'draw_rag',
            'merge_hierarchical',
-           'rag_boundary'
+           'rag_boundary',
            'RAG']
diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index fc6e1d6f..566c7261 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -4,7 +4,7 @@ from numpy.lib.stride_tricks import as_strided
 from scipy import ndimage as ndi
 from scipy import sparse
 import math
-from ... import draw, measure, segmentation, util, color, morphology
+from ... import draw, measure, segmentation, util, color
 try:
     from matplotlib import colors
     from matplotlib import cm
@@ -364,10 +364,10 @@ def rag_boundary(labels, edge_map, connectivity=2):
     graph_matrix = data_coo.tocsr()
     graph_matrix.data /= count_matrix.data
 
-    rag = nx.Graph()
+    rag = RAG()
     rows, cols = graph_matrix.nonzero()
     graph_data = zip(rows, cols, graph_matrix.data)
-    rag.add_weighted_edges_from(graph_data)
+    rag.add_weighted_edges_from(graph_data, attr='weight')
 
     for n in rag.nodes():
         rag.node[n].update({'labels': [n]})
diff --git a/skimage/future/graph/tests/test_rag.py b/skimage/future/graph/tests/test_rag.py
index 4af3d854..dafa0ddc 100644
--- a/skimage/future/graph/tests/test_rag.py
+++ b/skimage/future/graph/tests/test_rag.py
@@ -212,4 +212,4 @@ def test_rag_boundary():
 
     g = graph.rag_boundary(labels, edge_map, connectivity=1)
     assert len(g.nodes()) == 4
-    assert len(g.edges()) == 4
\ No newline at end of file
+    assert len(g.edges()) == 4

From a5f6db59cbb2b01ac173ec4a13237c53ee0f5d84 Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@nyu.edu>
Date: Wed, 6 Jan 2016 15:42:10 -0500
Subject: [PATCH 09/18] doc example

---
 skimage/future/graph/rag.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index 566c7261..4faea16c 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -340,7 +340,7 @@ def rag_boundary(labels, edge_map, connectivity=2):
     >>> img = data.chelsea()
     >>> labels = segmentation.slic(img)
     >>> edge_map = filters.sobel(color.rgb2gray(img))
-    >>> rag = graph.rag_mean_color(labels, edge_map)
+    >>> rag = graph.rag_boundary(labels, edge_map)
 
     """
 

From ea18fcb99be6a88d8e883672ed050687498a6140 Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@nyu.edu>
Date: Wed, 6 Jan 2016 16:23:43 -0500
Subject: [PATCH 10/18] use as strided

---
 skimage/future/graph/rag.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index 4faea16c..dd45f2fc 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -354,8 +354,8 @@ def rag_boundary(labels, edge_map, connectivity=2):
     n = np.max(labels_large) + 1
 
     # use a dummy broadcast array as data for RAG
-    ones = np.broadcast_to(np.ones((1,), dtype=np.int_),
-                           labels_small.shape)
+    ones = as_strided(np.ones((1,), dtype=np.float), shape=labels_small.shape,
+                      strides=(0,))
     count_matrix = sparse.coo_matrix((ones, (labels_small, labels_large)),
                                      dtype=np.int_, shape=(n, n)).tocsr()
     data = np.concatenate((edge_map[boundaries0], edge_map[boundaries1]))

From a4a406349bfdd5cb3a1fc8660893dc9be353eaf5 Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@nyu.edu>
Date: Wed, 6 Jan 2016 19:58:40 -0500
Subject: [PATCH 11/18] moved example file

---
 doc/examples/{ => segmentation}/plot_rag_boundary.py | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 rename doc/examples/{ => segmentation}/plot_rag_boundary.py (100%)

diff --git a/doc/examples/plot_rag_boundary.py b/doc/examples/segmentation/plot_rag_boundary.py
similarity index 100%
rename from doc/examples/plot_rag_boundary.py
rename to doc/examples/segmentation/plot_rag_boundary.py

From 772d1ccc15ffbf86798d85e8a332b51569d37b46 Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@nyu.edu>
Date: Wed, 6 Jan 2016 20:23:55 -0500
Subject: [PATCH 12/18] changed colormap to jet

---
 doc/examples/segmentation/plot_rag_boundary.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/examples/segmentation/plot_rag_boundary.py b/doc/examples/segmentation/plot_rag_boundary.py
index 5063d96a..4b29b6bd 100644
--- a/doc/examples/segmentation/plot_rag_boundary.py
+++ b/doc/examples/segmentation/plot_rag_boundary.py
@@ -19,7 +19,7 @@ edges_rgb = color.gray2rgb(edges)
 g = graph.rag_boundary(labels, edges)
 
 out = graph.draw_rag(labels, g, edges_rgb, node_color="#ffff00",
-                     colormap='plasma')
+                     colormap='jet')
 
 io.imshow(out)
 io.show()

From def8ca7f753905bced082b8c0369747e1a934a8a Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@nyu.edu>
Date: Wed, 6 Jan 2016 21:29:42 -0500
Subject: [PATCH 13/18] change mcap to viridis

---
 doc/examples/segmentation/plot_rag_boundary.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/doc/examples/segmentation/plot_rag_boundary.py b/doc/examples/segmentation/plot_rag_boundary.py
index 4b29b6bd..4d909360 100644
--- a/doc/examples/segmentation/plot_rag_boundary.py
+++ b/doc/examples/segmentation/plot_rag_boundary.py
@@ -8,6 +8,8 @@ This example demonstrates construction of region boundary based RAGs with the
 """
 from skimage.future import graph
 from skimage import data, segmentation, color, filters, io
+from skimage.util.colormap import viridis
+
 
 img = data.coffee()
 gimg = color.rgb2gray(img)
@@ -18,8 +20,8 @@ edges_rgb = color.gray2rgb(edges)
 
 g = graph.rag_boundary(labels, edges)
 
-out = graph.draw_rag(labels, g, edges_rgb, node_color="#ffff00",
-                     colormap='jet')
+out = graph.draw_rag(labels, g, edges_rgb, node_color="#999999",
+                     colormap=viridis)
 
 io.imshow(out)
 io.show()

From f9dfa1d81d139dc833af5870c7c8b1e1604ffc25 Mon Sep 17 00:00:00 2001
From: Juan Nunez-Iglesias <juan.n@unimelb.edu.au>
Date: Fri, 8 Jan 2016 17:25:10 +1100
Subject: [PATCH 14/18] Make mean boundary RAG testing more robust

---
 skimage/future/graph/tests/test_rag.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/skimage/future/graph/tests/test_rag.py b/skimage/future/graph/tests/test_rag.py
index dafa0ddc..27d31a99 100644
--- a/skimage/future/graph/tests/test_rag.py
+++ b/skimage/future/graph/tests/test_rag.py
@@ -211,5 +211,7 @@ def test_rag_boundary():
     labels[8:, 8:] = 4
 
     g = graph.rag_boundary(labels, edge_map, connectivity=1)
-    assert len(g.nodes()) == 4
-    assert len(g.edges()) == 4
+    assert set(g.nodes()) == set([1, 2, 3, 4])
+    assert set(g.edges()) == set([(1, 2), (1, 3), (2, 4), (3, 4)])
+    assert g[1][3]['weight'] == 0.25
+    assert g[2][4]['weight'] == 0.34375

From 30145ab7f4d59b50aa40adffd753968e327c34eb Mon Sep 17 00:00:00 2001
From: Juan Nunez-Iglesias <juan.n@unimelb.edu.au>
Date: Fri, 8 Jan 2016 22:10:20 +1100
Subject: [PATCH 15/18] Use function to update graph edges from CSR

---
 skimage/future/graph/rag.py | 44 ++++++++++++++++++++++++++++++++++---
 1 file changed, 41 insertions(+), 3 deletions(-)

diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index dd45f2fc..ab31171e 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -12,6 +12,45 @@ except ImportError:
     pass
 
 
+def _edge_generator_from_csr(csr_matrix):
+    """Yield weighted edge triples for use by NetworkX from a CSR matrix.
+
+    This function is a straight rewrite of
+    `networkx.convert_matrix._csr_gen_triples`. Since that is a private
+    function, it is safer to include our own here.
+
+    Parameters
+    ----------
+    csr_matrix : scipy.sparse.csr_matrix
+        The input matrix. An edge (i, j, w) will be yielded if there is a
+        data value for coordinates (i, j) in the matrix, even if that value
+        is 0.
+
+    Yields
+    ------
+    i, j, w : (int, int, float) tuples
+        Each value `w` in the matrix along with its coordinates (i, j).
+
+    Examples
+    --------
+
+    >>> dense = np.eye(2, dtype=np.float)
+    >>> csr = sparse.csr_matrix(dense)
+    >>> edges = _edge_generator_from_csr(csr)
+    >>> type(edges)
+    generator
+    >>> list(edges)
+    [(0, 0, 1.0), (1, 1, 1.0)]
+    """
+    nrows = csr_matrix.shape[0]
+    values = csr_matrix.data
+    indptr = csr_matrix.indptr
+    col_indices = csr_matrix.indices
+    for i in range(nrows):
+        for j in range(indptr[i], indptr[i + 1]):
+            yield i, col_indices[j], data[j]
+
+
 def min_weight(graph, src, dst, n):
     """Callback to handle merging nodes by choosing minimum weight.
 
@@ -365,9 +404,8 @@ def rag_boundary(labels, edge_map, connectivity=2):
     graph_matrix.data /= count_matrix.data
 
     rag = RAG()
-    rows, cols = graph_matrix.nonzero()
-    graph_data = zip(rows, cols, graph_matrix.data)
-    rag.add_weighted_edges_from(graph_data, attr='weight')
+    rag.add_weighted_edges_from(_edge_generator_from_csr(graph_matrix),
+                                weight='weight')
 
     for n in rag.nodes():
         rag.node[n].update({'labels': [n]})

From 802214d5acedc32507e9c1a041afdcb96c6963b0 Mon Sep 17 00:00:00 2001
From: Juan Nunez-Iglesias <juan.n@unimelb.edu.au>
Date: Fri, 8 Jan 2016 22:11:31 +1100
Subject: [PATCH 16/18] Hold pixel count in mean boundary RAG edges

This value is needed to combine edges when merging nodes.
---
 skimage/future/graph/rag.py            | 2 ++
 skimage/future/graph/tests/test_rag.py | 1 +
 2 files changed, 3 insertions(+)

diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index ab31171e..646a7cc6 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -406,6 +406,8 @@ def rag_boundary(labels, edge_map, connectivity=2):
     rag = RAG()
     rag.add_weighted_edges_from(_edge_generator_from_csr(graph_matrix),
                                 weight='weight')
+    rag.add_weighted_edges_from(_edge_generator_from_csr(count_matrix),
+                                weight='count')
 
     for n in rag.nodes():
         rag.node[n].update({'labels': [n]})
diff --git a/skimage/future/graph/tests/test_rag.py b/skimage/future/graph/tests/test_rag.py
index 27d31a99..4b2e4cff 100644
--- a/skimage/future/graph/tests/test_rag.py
+++ b/skimage/future/graph/tests/test_rag.py
@@ -215,3 +215,4 @@ def test_rag_boundary():
     assert set(g.edges()) == set([(1, 2), (1, 3), (2, 4), (3, 4)])
     assert g[1][3]['weight'] == 0.25
     assert g[2][4]['weight'] == 0.34375
+    assert g[1][3]['count'] == 16

From 753c8caf4ee0f6d18dfd6b6722568979f1550735 Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@nyu.edu>
Date: Fri, 8 Jan 2016 14:11:56 -0500
Subject: [PATCH 17/18] correct variable name mistake

---
 skimage/future/graph/rag.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index 646a7cc6..739c3010 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -48,7 +48,7 @@ def _edge_generator_from_csr(csr_matrix):
     col_indices = csr_matrix.indices
     for i in range(nrows):
         for j in range(indptr[i], indptr[i + 1]):
-            yield i, col_indices[j], data[j]
+            yield i, col_indices[j], values[j]
 
 
 def min_weight(graph, src, dst, n):

From 22bf68d9b42322f59ba76441bdade2e206cd8f4a Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@nyu.edu>
Date: Fri, 8 Jan 2016 21:49:01 -0500
Subject: [PATCH 18/18] removed failing doctest line

---
 skimage/future/graph/rag.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/skimage/future/graph/rag.py b/skimage/future/graph/rag.py
index 739c3010..dae5bbd1 100644
--- a/skimage/future/graph/rag.py
+++ b/skimage/future/graph/rag.py
@@ -37,8 +37,6 @@ def _edge_generator_from_csr(csr_matrix):
     >>> dense = np.eye(2, dtype=np.float)
     >>> csr = sparse.csr_matrix(dense)
     >>> edges = _edge_generator_from_csr(csr)
-    >>> type(edges)
-    generator
     >>> list(edges)
     [(0, 0, 1.0), (1, 1, 1.0)]
     """