Added sections to gallery of examples

Modified travis_script.sh to account for the new structure of the gallery

Added README.txt files in directories of gallery examples

Fixed references to gallery images in user guide pages

Fixed broken links

doc/examples/segmentation/plot_rag.py

@@ -0,0 +1,81 @@
+"""
+=======================
+Region Adjacency Graphs
+=======================
+
+This example demonstrates the use of the `merge_nodes` function of a Region
+Adjacency Graph (RAG). The `RAG` class represents a undirected weighted graph
+which inherits from `networkx.graph` class. When a new node is formed by
+merging two nodes, the edge weight of all the edges incident on the resulting
+node can be updated by a user defined function `weight_func`.
+
+The default behaviour is to use the smaller edge weight in case of a conflict.
+The example below also shows how to use a custom function to select the larger
+weight instead.
+
+"""
+from skimage.future.graph import rag
+import networkx as nx
+from matplotlib import pyplot as plt
+import numpy as np
+
+
+def max_edge(g, src, dst, n):
+    """Callback to handle merging nodes by choosing maximum weight.
+
+    Returns either the weight between (`src`, `n`) or (`dst`, `n`)
+    in `g` or the maximum of the two when both exist.
+
+    Parameters
+    ----------
+    g : RAG
+        The graph under consideration.
+    src, dst : int
+        The vertices in `g` to be merged.
+    n : int
+        A neighbor of `src` or `dst` or both.
+
+    Returns
+    -------
+    weight : float
+        The weight between (`src`, `n`) or (`dst`, `n`) in `g` or the
+        maximum of the two when both exist.
+
+    """
+
+    w1 = g[n].get(src, {'weight': -np.inf})['weight']
+    w2 = g[n].get(dst, {'weight': -np.inf})['weight']
+    return max(w1, w2)
+
+
+def display(g, title):
+    """Displays a graph with the given title."""
+    pos = nx.circular_layout(g)
+    plt.figure()
+    plt.title(title)
+    nx.draw(g, pos)
+    nx.draw_networkx_edge_labels(g, pos, font_size=20)
+
+
+g = rag.RAG()
+g.add_edge(1, 2, weight=10)
+g.add_edge(2, 3, weight=20)
+g.add_edge(3, 4, weight=30)
+g.add_edge(4, 1, weight=40)
+g.add_edge(1, 3, weight=50)
+
+# Assigning dummy labels.
+for n in g.nodes():
+    g.node[n]['labels'] = [n]
+
+gc = g.copy()
+
+display(g, "Original Graph")
+
+g.merge_nodes(1, 3)
+display(g, "Merged with default (min)")
+
+gc.merge_nodes(1, 3, weight_func=max_edge, in_place=False)
+display(gc, "Merged with max without in_place")
+
+plt.show()