Documentation update, following new graph_draw() function

doc/Makefile

 PDFIMAGES = $(shell ls *.pdf)
 PNGIMAGES = ${PDFIMAGES:.pdf=.png}
-HUGEIMAGES = $(shell find . -maxdepth 1 -name "*.pdf"  -size +1000k)
+HUGEIMAGES = $(shell find . -maxdepth 1 -name "*.pdf"  -size +10000k)
 ORIGIMAGES = ${HUGEIMAGES:.pdf=.pdf-orig}
 
-PNGCONV = gm convert -density 600 -resample 50 -trim -antialias -quality 9 -filter Cubic
+#PNGCONV = gm convert -density 1200 -resample 50 -trim -antialias -quality 9 -filter Cubic
+PNGCONV = pdftoppm -png -singlefile -r 96 -freetype yes -aa yes -aaVector yes
+PDFCONV = gm convert
 
 all: $(ORIGIMAGES) $(PNGIMAGES)
 	sphinx-build -E -b html . build
 
 %.pdf-orig: %.pdf
-	cp $< $@ 
-	gm mogrify -resize 600 -trim -antialias -filter Cubic $<
+	$(PNGCONV) $< > $@-tmp.png
+	$(PDFCONV) $@-tmp.png $@
+	rm $@-tmp.png
 
 %.png: %.pdf
-	test -d $<-orig && $(PNGCONV) $<-orig $@  || true
-	test -d $<-orig || $(PNGCONV) $< $@ || true
+	test -d $<-orig && $(PNGCONV) $<-orig > $@ || true
+	test -d $<-orig || $(PNGCONV) $< > $@ || true
 
 latex:
 	sphinx-build -E -b latex . build

doc/conf.py

@@ -26,7 +26,8 @@ sys.path.append(os.path.abspath('.'))
 # coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
 extensions = ['sphinx.ext.autodoc', 'sphinx.ext.doctest',
               'sphinx.ext.intersphinx', 'mathjax', 'sphinx.ext.autosummary',
-              'sphinxext.numpydoc', 'sphinx.ext.extlinks']
+              'sphinxext.numpydoc', 'sphinx.ext.extlinks',
+              'matplotlib.sphinxext.plot_directive']
 
 mathjax_path = "MathJax/MathJax.js"
 
@@ -92,47 +93,7 @@ pygments_style = 'sphinx'
 
 # doctest
 
-doctest_global_setup = \
-r"""
-from matplotlib import rc
-from matplotlib import rcParams
-
-font_size=12
-rcParams["figure.figsize"] = (4,3)
-rcParams["font.family"] = "serif"
-rcParams["font.serif"] = ["Palatino"]
-rcParams["font.size"] = font_size
-rcParams["axes.labelsize"] = font_size
-rcParams["xtick.labelsize"] = font_size
-rcParams["ytick.labelsize"] = font_size
-rcParams["legend.numpoints"] = 1
-rcParams["legend.fontsize"] = "small"
-rcParams["lines.markersize"] = 4
-rcParams["figure.subplot.right"] = 0.95
-rcParams["figure.subplot.top"] = 0.95
-rcParams["figure.subplot.right"] = 0.95
-rcParams["figure.subplot.top"] = 0.95
-rcParams["figure.subplot.left"] = 0.2
-rcParams["figure.subplot.bottom"] = 0.2
-
-rcParams["text.usetex"] = True
-
-rcParams["ps.usedistiller"] = "xpdf"
-rcParams["pdf.compression"] = 9
-rcParams["ps.useafm"] = True
-rcParams["path.simplify"] = True
-rcParams["text.latex.preamble"] = ["\usepackage{times}",
-                                   #"\usepackage{euler}",
-                                   "\usepackage{amssymb}",
-                                   "\usepackage{amsmath}"]
-
-from numpy import *
-import scipy
-import scipy.stats
-from math import *
-import numpy as np
-import graph_tool.all as gt
-"""
+doctest_global_setup = open("pyenv.py").read()
 
 # Options for HTML outputs
 # -----------------------
@@ -232,10 +193,9 @@ latex_elements = {
 # Example configuration for intersphinx: refer to the Python standard library.
 intersphinx_mapping = {'python': ('http://docs.python.org', None),
                        'numpy': ('http://docs.scipy.org/doc/numpy', None),
-                       'scipy': ('http://docs.scipy.org/doc/scipy/reference',
-                                 None),
-                       'matplotlib': ('http://matplotlib.sourceforge.net',
-                                      None)}
+                       'scipy': ('http://docs.scipy.org/doc/scipy/reference', None),
+                       'matplotlib': ('http://matplotlib.sourceforge.net', None),
+                       'cairo': ('http://www.cairographics.org/documentation/pycairo/3/', None)}
 
 extlinks = {'ticket': ('http://projects.skewed.de/graph-tool/ticket/%s',
                        'ticket '),
@@ -247,3 +207,8 @@ extlinks = {'ticket': ('http://projects.skewed.de/graph-tool/ticket/%s',
 numpydoc_show_class_members = False
 autodoc_member_order = 'bysource'
 autodoc_docstring_signature = False
+
+# plot directive
+import pyenv
+plot_rcparams = pyenv.rcParams
+#plot_pre_code = open("pyenv.py").read()

doc/draw.rst

 .. automodule:: graph_tool.draw
-   :members:
-   :undoc-members:
+
+    Layout algorithms
+    =================
+
+    .. autofunction:: sfdp_layout
+    .. autofunction:: fruchterman_reingold_layout
+    .. autofunction:: arf_layout
+    .. autofunction:: random_layout
+
+
+    Graph drawing
+    =============
+
+
+    .. autofunction:: graph_draw
+    .. autofunction:: graphviz_draw
+
+
+    Low-level graph drawing
+    ^^^^^^^^^^^^^^^^^^^^^^^
+
+    .. autofunction:: cairo_draw
+    .. autofunction:: interactive_window
+    .. autoclass::  GraphWidget
+       :members:
+       :undoc-members:
+    .. autoclass::  GraphWindow
+       :members:
+       :undoc-members:

doc/gt_theme/static/gt_style.css

 @import url("flasky.css");
 
+table.docutils {
+    margin-left:1em; 
+    margin-right:1em;
+}
+
 table.docutils td {
     padding-left: 0.5em;
 }
 
-table.docutils.field-list
-{
+table.docutils.field-list {
+    margin-left: 0; 
+    margin-right: 0;
     border-collapse: separate; 
     border-spacing: 0em 1em;
 }
@@ -16,6 +22,12 @@ table.docutils td.field-body  {
     padding-left: 1em;
 }
 
+table.docutils.citation
+{
+    margin-left: 0; 
+    margin-right: 0;
+}
+
 /* stupid workaround to hide ugly c++ signature stuff from sphinx*/
 dl.method dl.last {
     visibility: collapse;

doc/price.py

@@ -52,21 +52,6 @@ for i in xrange(1, N):
     vlist.append(v)
 
 # now we have a graph!
-# let's calculate its in-degree distribution and plot it to a file
-
-in_hist = vertex_hist(g, "in")
-
-figure(figsize=(4, 3))
-errorbar(in_hist[1][:-1], in_hist[0], fmt="o", yerr=sqrt(in_hist[0]),
-         label="in")
-gca().set_yscale("log")
-gca().set_xscale("log")
-gca().set_ylim(1e-1, 1e5)
-gca().set_xlim(0.8, 1e3)
-subplots_adjust(left=0.2, bottom=0.2)
-xlabel("$k_{in}$")
-ylabel("$NP(k_{in})$")
-savefig("deg-hist.pdf")
 
 # let's do a random walk on the graph and print the age of the vertices we find,
 # just for fun.

doc/pyenv.py

+from matplotlib import rc
+from matplotlib import rcParams
+
+font_size=14
+rcParams["figure.figsize"] = (6,4.5)
+rcParams["font.family"] = "Serif"
+rcParams["font.serif"] = ["Palatino"]
+rcParams["font.size"] = font_size
+rcParams["axes.labelsize"] = font_size
+rcParams["xtick.labelsize"] = font_size - 2
+rcParams["ytick.labelsize"] = font_size - 2
+rcParams["legend.numpoints"] = 1
+rcParams["legend.fontsize"] = "small"
+rcParams["lines.markersize"] = 4
+rcParams["figure.subplot.right"] = 0.95
+rcParams["figure.subplot.top"] = 0.95
+rcParams["figure.subplot.right"] = 0.95
+rcParams["figure.subplot.top"] = 0.95
+rcParams["figure.subplot.left"] = 0.2
+rcParams["figure.subplot.bottom"] = 0.2
+
+rcParams["text.usetex"] = True
+
+rcParams["ps.usedistiller"] = "xpdf"
+rcParams["pdf.compression"] = 9
+rcParams["ps.useafm"] = True
+rcParams["path.simplify"] = True
+rcParams["text.latex.preamble"] = [#"\usepackage{times}",
+                                   #"\usepackage{euler}",
+                                   "\usepackage{amssymb}",
+                                   "\usepackage{amsmath}"]
+
+from numpy import *
+import scipy
+import scipy.stats
+from math import *
+import numpy as np
+import graph_tool.all as gt

doc/quickstart.rst

@@ -83,7 +83,8 @@ visualize the graph we created so far with the
 
 .. doctest::
 
-   >>> graph_draw(g, vprops={"label": g.vertex_index}, output="two-nodes.pdf")
+   >>> graph_draw(g, vertex_text=g.vertex_index, vertex_font_size=18,
+   ...            output_size=(200, 200), output="two-nodes.pdf")
    <...>
 
 .. figure:: two-nodes.*
@@ -140,11 +141,11 @@ Edges and vertices can also be removed at any time with the
 .. note::
 
    Removing a vertex is an :math:`O(N)` operation. The vertices are
-   internally stored in a STL vector, so removing an element somewhere
-   in the middle of the list requires the shifting of the rest of the
-   list. Thus, fast :math:`O(1)` removals are only possible if one can
-   guarantee that only vertices in the end of the list are removed (the
-   ones last added to the graph).
+   internally stored in a `STL vector <http://en.wikipedia.org/wiki/Vector_%28STL%29>`_,
+   so removing an element somewhere in the middle of the list requires
+   the shifting of the rest of the list. Thus, fast :math:`O(1)`
+   removals are only possible if one can guarantee that only vertices in
+   the end of the list are removed (the ones last added to the graph).
 
    Removing an edge is an :math:`O(k_{s} + k_{t})` operation, where
    :math:`k_{s}` is the out-degree of the source vertex, and
@@ -455,10 +456,35 @@ 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`.
 
-.. figure:: deg-hist.*
+.. plot::
+   :context:
    :align: center
 
-   In-degree distribution of a price network with 100000 nodes.
+   #from pyenv import *
+   from pylab import *
+   import graph_tool.all as gt
+
+   g = gt.load_graph("price.xml.gz")
+
+   in_hist = gt.vertex_hist(g, "in")
+
+   figure()
+   y = in_hist[0]
+   err = sqrt(in_hist[0])
+   err[err >= y] = y[err >= y] - 1e-2
+   errorbar(in_hist[1][:-1], in_hist[0], fmt="o", yerr=err,
+            label="in")
+   gca().set_yscale("log")
+   gca().set_xscale("log")
+   gca().set_ylim(1e-1, 1e5)
+   gca().set_xlim(0.8, 1e3)
+   subplots_adjust(left=0.2, bottom=0.2)
+   xlabel("$k_{in}$")
+   ylabel("$NP(k_{in})$")
+   Title ("In-degree distribution of a price network with $10^5$ nodes.")
+   tight_layout()
+   show()
+
 
 We can draw the graph to see some other features of its topology. For that we
 use the :func:`~graph_tool.draw.graph_draw` function.
@@ -467,7 +493,9 @@ use the :func:`~graph_tool.draw.graph_draw` function.
 
    g = load_graph("price.xml.gz")
    age = g.vertex_properties["age"]
-   graph_draw(g, size=(15,15), vcolor=age, output="price.pdf")
+   graph_draw(g, output_size=(1000, 1000), vertex_color=age,
+              vertex_fill_color=age, vertex_size=2.5, edge_pen_width=1.5,
+              output="price.png")
 
 .. figure:: price.*
    :align: center
@@ -512,7 +540,8 @@ edge filtering.
 
    g, pos = triangulation(random((500, 2)) * 4, type="delaunay")
    tree = min_spanning_tree(g)
-   graph_draw(g, pos=pos, pin=True, size=(8, 8), ecolor=tree, output="min_tree.pdf")
+   graph_draw(g, pos=pos, edge_color=tree, output_size=(400, 400),
+              output="min_tree.pdf")
 
 The ``tree`` property map has a bool type, with value "1" if the edge belongs to
 the tree, and "0" otherwise. Below is an image of the original graph, with the
@@ -526,7 +555,7 @@ We can now filter out the edges which don't belong to the minimum spanning tree.
 .. testcode::
 
     g.set_edge_filter(tree)
-    graph_draw(g, pos=pos, pin=True, size=(8, 8), output="min_tree_filtered.pdf")
+    graph_draw(g, pos=pos, output_size=(400, 400), output="min_tree_filtered.pdf")
 
 This is how the graph looks when filtered:
 
@@ -541,9 +570,9 @@ and draws them as colors and line thickness in the graph.
 .. testcode::
 
     bv, be = betweenness(g)
-    be.a *= 10
-    graph_draw(g, pos=pos, pin=True, size=(8,8), vsize=0.07, vcolor=bv,
-               eprops={"penwidth":be}, output="filtered-bt.pdf")
+    be.a /= be.a.max() / 5
+    graph_draw(g, pos=pos, vertex_fill_color=bv, edge_pen_width=be,
+               output_size=(400, 400), output="filtered-bt.pdf")
 
 .. figure:: filtered-bt.*
    :align: center
@@ -555,9 +584,9 @@ The original graph can be recovered by setting the edge filter to ``None``.
 
     g.set_edge_filter(None)
     bv, be = betweenness(g)
-    be.a *= 10
-    graph_draw(g, pos=pos, pin=True, size=(8,8), vsize=0.07, vcolor=bv,
-               eprops={"penwidth":be}, output="nonfiltered-bt.pdf")
+    be.a /= be.a.max() / 5
+    graph_draw(g, pos=pos, vertex_fill_color=bv, edge_pen_width=be,
+               output_size=(400, 400), output="nonfiltered-bt.pdf")
 
 .. figure:: nonfiltered-bt.*
    :align: center
@@ -611,9 +640,10 @@ Like above, the result should be the isolated minimum spanning tree:
 .. doctest::
 
     >>> bv, be = betweenness(tv)
-    >>> be.a *= 10
-    >>> graph_draw(tv, pos=pos, pin=True, size=(8,8), vsize=0.07, vcolor=bv,
-    ...            eprops={"penwidth":be}, output="mst-view.pdf")
+    >>> be.a /= be.a.max() / 5
+    >>> graph_draw(tv, pos=pos, vertex_fill_color=bv,
+    ...            edge_pen_width=be, output_size=(400, 400),
+    ...            output="mst-view.pdf")
     <...>
 
 
@@ -643,22 +673,23 @@ edges, we can do:
 .. doctest::
 
     >>> bv, be = betweenness(g)
-    >>> u = GraphView(g, efilt=lambda e: be[e] > 0.01)
+    >>> u = GraphView(g, efilt=lambda e: be[e] > be.a.max() / 2)
 
 This creates a graph view ``u`` which contains only the edges of ``g``
-which have a normalized betweenness centrality larger than 0.01. Note
-that, differently from the case above, this is an :math:`O(E)`
-operation, where :math:`E` is the number of edges, since the supplied
-function must be called :math:`E` times to construct a filter property
-map. Thus, supplying a constructed filter map is always faster, but
-supplying a function can be more convenient.
+which have a normalized betweenness centrality larger than half of the
+maximum value. Note that, differently from the case above, this is an
+:math:`O(E)` operation, where :math:`E` is the number of edges, since
+the supplied function must be called :math:`E` times to construct a
+filter property map. Thus, supplying a constructed filter map is always
+faster, but supplying a function can be more convenient.
 
 The graph view constructed above can be visualized as
 
 .. doctest::
 
-    >>> graph_draw(u, pos=pos, pin=True, size=(8,8), vsize=0.07, vcolor=bv,
-    ...            output="central-edges-view.pdf")
+    >>> be.a /= be.a.max() / 5
+    >>> graph_draw(u, pos=pos, vertex_fill_color=bv, output_size=(400, 400),
+    ... output="central-edges-view.pdf")
     <...>
 
 .. figure:: central-edges-view.*
@@ -671,10 +702,10 @@ Composing graph views
 """""""""""""""""""""
 
 Since graph views are regular graphs, one can just as easily create
-graph views of graph views. This provides a convenient way of composing
-filters. For instance, in order to isolate the minimum spanning tree of
-all vertices of the example above which have a degree larger than four,
-one can do:
+graph views `of graph views`. This provides a convenient way of
+composing filters. For instance, in order to isolate the minimum
+spanning tree of all vertices of the example above which have a degree
+larger than four, one can do:
 
 
     >>> u = GraphView(g, vfilt=lambda v: v.out_degree() > 4)
@@ -685,8 +716,7 @@ The resulting graph view can be visualized as
 
 .. doctest::
 
-    >>> graph_draw(u, pos=pos, pin=True, size=(8,8), vsize=0.07,
-    ...            output="composed-filter.pdf")
+    >>> graph_draw(u, pos=pos, output_size=(400, 400), output="composed-filter.pdf")
     <...>
 
 .. figure:: composed-filter.*

src/graph_tool/community/__init__.py

@@ -87,9 +87,9 @@ def community_structure(g, n_iter, n_spins, gamma=1.0, corr="erdos",
 
     See Also
     --------
-    community_structure: obtain the community structure
-    modularity: calculate the network modularity
-    condensation_graph: network of communities
+    community_structure: Obtain the community structure
+    modularity: Calculate the network modularity
+    condensation_graph: Network of communities, or blocks
 
     Notes
     -----
@@ -145,19 +145,17 @@ def community_structure(g, n_iter, n_spins, gamma=1.0, corr="erdos",
     >>> from numpy.random import seed
     >>> seed(42)
     >>> g = gt.load_graph("community.xml")
-    >>> pos = (g.vertex_properties["pos_x"], g.vertex_properties["pos_y"])
+    >>> pos = g.vertex_properties["pos"]
     >>> spins = gt.community_structure(g, 10000, 20, t_range=(5, 0.1),
     ...                                history_file="community-history1")
-    >>> gt.graph_draw(g, pos=pos, pin=True, vsize=0.3, vcolor=spins,
-    ...               output="comm1.pdf", size=(10,10))
+    >>> gt.graph_draw(g, pos=pos, vertex_fill_color=spins, output_size=(420, 420), output="comm1.pdf")
     <...>
     >>> spins = gt.community_structure(g, 10000, 40, t_range=(5, 0.1),
-    ...                                gamma=2.5,
-    ...                                history_file="community-history2")
-    >>> gt.graph_draw(g, pos=pos, pin=True, vsize=0.3, vcolor=spins,
-    ...               output="comm2.pdf", size=(10,10))
+    ...                                gamma=2.5, history_file="community-history2")
+    >>> gt.graph_draw(g, pos=pos, vertex_fill_color=spins, output_size=(420, 420), output="comm2.pdf")
+    <...>
+    >>> figure(figsize=(6, 4))
     <...>
-    >>> clf()
     >>> xlabel("iterations")
     <...>
     >>> ylabel("number of communities")
@@ -239,7 +237,7 @@ def modularity(g, prop, weight=None):
     --------
     community_structure: obtain the community structure
     modularity: calculate the network modularity
-    condensation_graph: network of communities
+    condensation_graph: Network of communities, or blocks
 
     Notes
     -----
@@ -307,9 +305,9 @@ def condensation_graph(g, prop, weight=None):
 
     See Also
     --------
-    community_structure: obtain the community structure
-    modularity: calculate the network modularity
-    condensation_graph:  network of communities
+    community_structure: Obtain the community structure
+    modularity: Calculate the network modularity
+    condensation_graph: Network of communities, or blocks
 
     Notes
     -----
@@ -324,13 +322,12 @@ def condensation_graph(g, prop, weight=None):
     >>> from numpy.random import poisson, seed
     >>> seed(42)
     >>> g = gt.random_graph(1000, lambda: poisson(3), directed=False)
+    >>> g = gt.GraphView(g, vfilt=gt.label_largest_component(g))
     >>> spins = gt.community_structure(g, 10000, 100)
     >>> ng = gt.condensation_graph(g, spins)
     >>> size = ng[0].new_vertex_property("double")
-    >>> size.a = log(ng[2].a+1)
-    >>> gt.graph_draw(ng[0], vsize=size, vcolor=ng[1], splines=True,
-    ...               eprops={"len":20, "penwidth":10}, vprops={"penwidth":10},
-    ...               output="comm-network.pdf", size=(10,10))
+    >>> size.a = 50 * ng[2].a / ng[2].a.max()
+    >>> gt.graph_draw(ng[0], vertex_fill_color=ng[1], vertex_size=size, output="comm-network.pdf")
     <...>
 
     .. figure:: comm-network.*

src/graph_tool/correlations/__init__.py

@@ -269,9 +269,9 @@ def corr_hist(g, deg_source, deg_target, bins=[[0, 1], [0, 1]], weight=None,
     ...                     directed=False, mix_time=100)
     >>> h = gt.corr_hist(g, "out", "out")
     >>> clf()
-    >>> xlabel("source out-degree")
+    >>> xlabel("Source out-degree")
     <...>
-    >>> ylabel("target out-degree")
+    >>> ylabel("Target out-degree")
     <...>
     >>> imshow(h[0], interpolation="nearest")
     <...>
@@ -355,9 +355,9 @@ def combined_corr_hist(g, deg1, deg2, bins=[[0, 1], [0, 1]], float_count=True):
     >>> g = gt.random_graph(10000, lambda: sample_k(40))
     >>> h = gt.combined_corr_hist(g, "in", "out")
     >>> clf()
-    >>> xlabel("in-degree")
+    >>> xlabel("In-degree")
     <...>
-    >>> ylabel("out-degree")
+    >>> ylabel("Out-degree")
     <...>
     >>> imshow(h[0], interpolation="nearest")
     <...>
@@ -447,12 +447,12 @@ def avg_neighbour_corr(g, deg_source, deg_target, bins=[0, 1], weight=None):
     ...                     directed=False, mix_time=100)
     >>> h = gt.avg_neighbour_corr(g, "out", "out")
     >>> clf()
-    >>> xlabel("source out-degree")
+    >>> xlabel("Source out-degree")
     <...>
-    >>> ylabel("target out-degree")
+    >>> ylabel("Target out-degree")
     <...>
     >>> errorbar(h[2][:-1], h[0], yerr=h[1], fmt="o")
-    (...)
+    <...>
     >>> savefig("avg_corr.pdf")
 
     .. figure:: avg_corr.*
@@ -524,12 +524,12 @@ def avg_combined_corr(g, deg1, deg2, bins=[0, 1]):
     >>> g = gt.random_graph(10000, lambda: sample_k(40))
     >>> h = gt.avg_combined_corr(g, "in", "out")
     >>> clf()
-    >>> xlabel("in-degree")
+    >>> xlabel("In-degree")
     <...>
-    >>> ylabel("out-degree")
+    >>> ylabel("Out-degree")
     <...>
     >>> errorbar(h[2][:-1], h[0], yerr=h[1], fmt="o")
-    (...)
+    <...>
     >>> savefig("combined_avg_corr.pdf")
 
     .. figure:: combined_avg_corr.*

src/graph_tool/draw/__init__.py

@@ -19,23 +19,45 @@
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
 """
-``graph_tool.draw`` - Graph drawing
------------------------------------
+``graph_tool.draw`` - Graph drawing and layout
+----------------------------------------------
 
 Summary
 +++++++
 
+Layout algorithms
+=================
+
 .. autosummary::
    :nosignatures:
 
-   graph_draw
    sfdp_layout
    fruchterman_reingold_layout
    arf_layout
    random_layout
-   cairo_draw
+
+
+Graph drawing
+=============
+
+.. autosummary::
+   :nosignatures:
+
+   graph_draw
    graphviz_draw
 
+
+Low-level graph drawing
+^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autosummary::
+   :nosignatures:
+
+   cairo_draw
+   interactive_window
+   GraphWidget
+   GraphWindow
+
 Contents
 ++++++++
 """
@@ -177,7 +199,7 @@ def fruchterman_reingold_layout(g, weight=None, a=None, r=1., scale=None,
     >>> seed(42)
     >>> g = gt.price_network(300)
     >>> pos = gt.fruchterman_reingold_layout(g, n_iter=1000)
-    >>> gt.graph_draw(g, pos=pos, pin=True, output="graph-draw-fr.pdf")
+    >>> gt.graph_draw(g, pos=pos, output="graph-draw-fr.pdf")
     <...>
 
     .. figure:: graph-draw-fr.*
@@ -258,7 +280,7 @@ def arf_layout(g, weight=None, d=0.5, a=10, dt=0.001, epsilon=1e-6,
     >>> seed(42)
     >>> g = gt.price_network(300)
     >>> pos = gt.arf_layout(g, max_iter=0)
-    >>> gt.graph_draw(g, pos=pos, pin=True, output="graph-draw-arf.pdf")
+    >>> gt.graph_draw(g, pos=pos, output="graph-draw-arf.pdf")
     <...>
 
     .. figure:: graph-draw-arf.*

src/graph_tool/draw/graphviz_draw.py

@@ -242,7 +242,7 @@ def graphviz_draw(g, pos=None, size=(15, 15), pin=False, layout=None,
 
     Notes
     -----
-    This function is a wrapper for the [graphviz] routines. Extensive additional
+    This function is a wrapper for the [graphviz]_ routines. Extensive additional
     documentation for the graph, vertex and edge properties is available at:
     http://www.graphviz.org/doc/info/attrs.html.
 

src/graph_tool/flow/__init__.py

@@ -58,7 +58,8 @@ The following network will be used as an example throughout the documentation.