Small documentation fixes and updates

doc/conf.py

@@ -44,7 +44,7 @@ master_doc = 'index'
 
 # General information about the project.
 project = u'graph-tool'
-copyright = u'2009, Tiago de Paula Peixoto <tiago@forked.de>'
+copyright = u'2010, Tiago de Paula Peixoto <tiago@forked.de>'
 
 # The version info for the project you're documenting, acts as replacement for
 # |version| and |release|, also used in various other places throughout the

doc/price.py

@@ -10,7 +10,7 @@ seed(42)
 from graph_tool.all import *
 
 # let's construct a Price network (the one that existed before Barabasi). It is
-# a directed network, with preferential attachment. The algorithm below is a
+# a directed network, with preferential attachment. The algorithm below is
 # very naive, and a bit slow, but quite simple.
 
 # We start with an empty, directed graph
@@ -64,7 +64,7 @@ gca().set_ylim(1e-1,1e5)
 gca().set_xlim(0.8,1e3)
 subplots_adjust(left=0.2,bottom=0.2)
 xlabel("$k_{in}$")
-ylabel("$P(k_{in})$")
+ylabel("$NP(k_{in})$")
 savefig("deg-hist.png")
 
 # let's do a random walk on the graph and print the age of the vertices we find,
@@ -84,7 +84,7 @@ for i in xrange(0, 100):
         n_list.append(w)
     v = n_list[randint(0, len(n_list))]
 
-# let's save our graph for posterity We want to save the age properties as
+# let's save our graph for posterity. We want to save the age properties as
 # well... To do this, they must become "internal" properties, as such:
 
 g.vertex_properties["age"] = v_age

doc/quickstart.rst

@@ -261,6 +261,9 @@ method, i.e.,
     # this assigns random values to the properties
     vprop_double.get_array()[:] = random(g.num_vertices())
 
+    # or more conveniently (this is equivalent to the above)
+    vprop_double.a = random(g.num_vertices())
+
 Internal property maps
 ++++++++++++++++++++++
 
@@ -302,7 +305,7 @@ file-like object. A graph can also be loaded from disk with the
     #  ... fill the graph ...
     g.save("my_graph.xml.gz")    
     g2 = load_graph("my_graph.xml.gz")
-    # g and g2 should be a copy of each other
+    # g and g2 should be copies of each other
 
 Graph classes can also be pickled with the :mod:`pickle` module.
 
@@ -313,9 +316,9 @@ An Example: Building a Price Network
 A Price network is the first known model of a "scale-free" graph, invented in
 1976 by `de Solla Price
 <http://en.wikipedia.org/wiki/Derek_J._de_Solla_Price>`_. It is defined
-dynamically, and at each time step a new vertex is added to the graph, and
+dynamically, where at each time step a new vertex is added to the graph, and
 connected to an old vertex, with probability proportional to its in-degree. The
-following program implements this construction method using ``graph-tool``.
+following program implements this construction using ``graph-tool``.
 
 .. literalinclude:: price.py
    :linenos:
@@ -342,7 +345,7 @@ The following is what should happen when the program is run.
     vertex: 0 in-degree: 210 out-degree: 0 age: 0
     Nowhere else to go... We found the main hub!
 
-This is the degree distribution, with 100000 nodes. If you want to really see a
+This is the degree distribution, with 100000 nodes. If you want to see a broader
 power law, try to increase the number of vertices to something like :math:`10^6`
 or :math:`10^7`.
 
@@ -367,10 +370,10 @@ use the :func:`~graph_tool.draw.graph_draw` function.
 Graph filtering
 ---------------
 
-One of the very nice features from ``graph-tool`` is the "on-the-fly" filtering
-of edges and/or vertices. Filtering means the temporary masking of
-vertices/edges, which are not really removed, and can be easily
-recovered. Vertices or edges which are to be filtered should be marked with a
+One of the very nice features of ``graph-tool`` is the "on-the-fly" filtering of
+edges and/or vertices. Filtering means the temporary masking of vertices/edges,
+which are in fact not really removed, and can be easily recovered. Vertices or
+edges which are to be filtered should be marked with a
 :class:`~graph_tool.PropertyMap` with value type ``bool``, and then set with
 :meth:`~graph_tool.Graph.set_vertex_filter` or
 :meth:`~graph_tool.Graph.set_edge_filter` methods. By default, vertex or edges

src/graph_tool/__init__.py

@@ -51,7 +51,7 @@ Use the built-in ``help`` function to view a function's docstring::
 
    >>> help(gt.Graph)
 
-Classes
+Summary
 -------
 
 .. autosummary::
@@ -67,6 +67,8 @@ Classes
    value_types
    show_config
 
+Classes
+-------
 """
 
 __author__ = "Tiago de Paula Peixoto <tiago@forked.de>"

src/graph_tool/generation/__init__.py

@@ -293,7 +293,7 @@ def random_rewire(g, strat="uncorrelated", parallel_edges=False,
     Notes
     -----
     This algorithm iterates through all the edges in the network and tries to
-    swap its target our edge with another edge.
+    swap its target or source with the target or source of another edge.
 
     .. note::
         If `parallel_edges` = False, parallel edges are not placed during