matplotlib-checkins Mailing List for matplotlib

Revision: 5601
 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5601&view=rev
Author: mdboom
Date: 2008年06月19日 12:55:41 -0700 (2008年6月19日)
Log Message:
-----------
Add initial support for inheritance diagrams.
Modified Paths:
--------------
 trunk/matplotlib/doc/api/artist_api.rst
 trunk/matplotlib/doc/api/collections_api.rst
 trunk/matplotlib/doc/conf.py
 trunk/matplotlib/doc/devel/transformations.rst
Added Paths:
-----------
 trunk/matplotlib/doc/sphinxext/inheritance_diagram.py
Modified: trunk/matplotlib/doc/api/artist_api.rst
===================================================================
--- trunk/matplotlib/doc/api/artist_api.rst	2008年06月19日 19:53:12 UTC (rev 5600)
+++ trunk/matplotlib/doc/api/artist_api.rst	2008年06月19日 19:55:41 UTC (rev 5601)
@@ -2,6 +2,8 @@
 matplotlib artists
 *******************
 
+.. inheritance-diagram:: matplotlib.patches matplotlib.lines matplotlib.text
+
 :mod:`matplotlib.artist`
 =============================
 
Modified: trunk/matplotlib/doc/api/collections_api.rst
===================================================================
--- trunk/matplotlib/doc/api/collections_api.rst	2008年06月19日 19:53:12 UTC (rev 5600)
+++ trunk/matplotlib/doc/api/collections_api.rst	2008年06月19日 19:55:41 UTC (rev 5601)
@@ -2,6 +2,7 @@
 matplotlib collections
 **********************
 
+.. inheritance-diagram:: matplotlib.collections
 
 :mod:`matplotlib.collections`
 =============================
Modified: trunk/matplotlib/doc/conf.py
===================================================================
--- trunk/matplotlib/doc/conf.py	2008年06月19日 19:53:12 UTC (rev 5600)
+++ trunk/matplotlib/doc/conf.py	2008年06月19日 19:55:41 UTC (rev 5601)
@@ -28,7 +28,7 @@
 # Add any Sphinx extension module names here, as strings. They can be extensions
 # coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
 extensions = ['mathpng', 'math_symbol_table', 'sphinx.ext.autodoc',
- 'only_directives', 'plot_directive']
+ 'only_directives', 'plot_directive', 'inheritance_diagram']
 
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
Modified: trunk/matplotlib/doc/devel/transformations.rst
===================================================================
--- trunk/matplotlib/doc/devel/transformations.rst	2008年06月19日 19:53:12 UTC (rev 5600)
+++ trunk/matplotlib/doc/devel/transformations.rst	2008年06月19日 19:55:41 UTC (rev 5601)
@@ -2,6 +2,8 @@
 Working with transformations
 ==============================
 
+.. inheritance-diagram:: matplotlib.transforms matplotlib.path
+
 :mod:`matplotlib.transforms`
 =============================
 
Added: trunk/matplotlib/doc/sphinxext/inheritance_diagram.py
===================================================================
--- trunk/matplotlib/doc/sphinxext/inheritance_diagram.py	 (rev 0)
+++ trunk/matplotlib/doc/sphinxext/inheritance_diagram.py	2008年06月19日 19:55:41 UTC (rev 5601)
@@ -0,0 +1,414 @@
+"""
+Defines a docutils directive for inserting inheritance diagrams.
+
+Provide the directive with one or more classes or modules (separated
+by whitespace). For modules, all of the classes in that module will
+be used.
+
+Example::
+
+ Given the following classes:
+
+ class A: pass
+ class B(A): pass
+ class C(A): pass
+ class D(B, C): pass
+ class E(B): pass
+
+ .. inheritance-diagram: D E
+
+ Produces a graph like the following:
+
+ A
+ / \
+ B C
+ / \ /
+ E D
+
+The graph is inserted as a PNG+image map into HTML and a PDF in
+LaTeX.
+"""
+
+import inspect
+import os
+import subprocess
+try:
+ from hashlib import md5
+except ImportError:
+ from md5 import md5
+
+from docutils.nodes import Body, Element
+from docutils.writers.html4css1 import HTMLTranslator
+from sphinx.latexwriter import LaTeXTranslator
+from docutils.parsers.rst import directives
+from sphinx.roles import xfileref_role
+from sphinx.directives.desc import py_sig_re
+
+class DotException(Exception):
+ pass
+
+class InheritanceGraph(object):
+ """
+ Given a list of classes, determines the set of classes that
+ they inherit from all the way to the root "object", and then
+ is able to generate a graphviz dot graph from them.
+ """
+ def __init__(self, class_names, show_builtins=False):
+ """
+ *class_names* is a list of child classes to show bases from.
+
+ If *show_builtins* is True, then Python builtins will be shown
+ in the graph.
+ """
+ self.class_names = class_names
+ self.classes = self._import_classes(class_names)
+ self.all_classes = self._all_classes(self.classes)
+ if len(self.all_classes) == 0:
+ raise ValueError("No classes found for inheritance diagram")
+ self.show_builtins = show_builtins
+
+ def _import_class_or_module(self, name):
+ """
+ Import a class using its fully-qualified *name*.
+ """
+ try:
+ path, base, signature = py_sig_re.match(name).groups()
+ except:
+ raise ValueError(
+ "Invalid class '%s' specified for inheritance diagram" % name)
+ fullname = (path or '') + base
+ path = path and path.rstrip('.')
+ if not path:
+ raise ValueError(
+ "Invalid class '%s' specified for inheritance diagram" % name)
+ try:
+ module = __import__(path, None, None, [])
+ except ImportError:
+ raise ValueError(
+ "Could not import class '%s' specified for inheritance diagram" % name)
+
+ try:
+ todoc = module
+ for comp in fullname.split('.')[1:]:
+ todoc = getattr(todoc, comp)
+ except AttributeError:
+ raise ValueError(
+ "Could not find class '%s' specified for inheritance diagram" % name)
+
+ # If a class, just return it
+ if inspect.isclass(todoc):
+ return [todoc]
+ elif inspect.ismodule(todoc):
+ classes = []
+ for cls in todoc.__dict__.values():
+ if inspect.isclass(cls) and cls.__module__ == todoc.__name__:
+ classes.append(cls)
+ return classes
+ raise ValueError(
+ "'%s' does not resolve to a class or module" % name)
+
+ def _import_classes(self, class_names):
+ """
+ Import a list of classes.
+ """
+ classes = []
+ for name in class_names:
+ classes.extend(self._import_class_or_module(name))
+ return classes
+
+ def _all_classes(self, classes):
+ """
+ Return a list of all classes that are ancestors of *classes*.
+ """
+ all_classes = {}
+
+ def recurse(cls):
+ all_classes[cls] = None
+ for c in cls.__bases__:
+ if c not in all_classes:
+ recurse(c)
+
+ for cls in classes:
+ recurse(cls)
+
+ return all_classes.keys()
+
+ def class_name(self, cls):
+ """
+ Given a class object, return a fully-qualified name. This
+ works for things I've tested in matplotlib so far, but may
+ not be completely general.
+ """
+ module = cls.__module__
+ if module == '__builtin__':
+ return cls.__name__
+ return '.'.join([module, cls.__name__])
+
+ def get_all_class_names(self):
+ """
+ Get all of the class names involved in the graph.
+ """
+ return [self.class_name(x) for x in self.all_classes]
+
+ # These are the default options for
+ default_graph_options = {
+ "rankdir": "LR",
+ "size": '"11.0, 11.0"'
+ }
+ default_node_options = {
+ "shape": "box",
+ "fontsize": 10,
+ "height": 0.25,
+ "fontname": "sans",
+ "style": '"setlinewidth(0.5)"'
+ }
+ default_edge_options = {
+ "arrowsize": 0.5,
+ "style": '"setlinewidth(0.5)"'
+ }
+
+ def _format_node_options(self, options):
+ return ','.join(["%s=%s" % x for x in options.items()])
+ def _format_graph_options(self, options):
+ return ''.join(["%s=%s;\n" % x for x in options.items()])
+
+ def generate_dot(self, fd, name, urls={},
+ graph_options={}, node_options={},
+ edge_options={}):
+ """
+ Generate a graphviz dot graph from the classes that
+ were passed in to __init__.
+
+ *fd* is a Python file-like object to write to.
+
+ *name* is the name of the graph
+
+ *urls* is a dictionary mapping class names to http urls
+
+ *graph_options*, *node_options*, *edge_options* are
+ dictionaries containing key/value pairs to pass on as graphviz
+ properties.
+ """
+ g_options = self.default_graph_options.copy()
+ g_options.update(graph_options)
+ n_options = self.default_node_options.copy()
+ n_options.update(node_options)
+ e_options = self.default_edge_options.copy()
+ e_options.update(edge_options)
+
+ fd.write('digraph %s {\n' % name)
+ fd.write(self._format_graph_options(g_options))
+
+ for cls in self.all_classes:
+ if not self.show_builtins and cls in __builtins__.values():
+ continue
+
+ name = self.class_name(cls)
+
+ # Write the node
+ this_node_options = n_options.copy()
+ url = urls.get(name)
+ if url is not None:
+ this_node_options['URL'] = '"%s"' % url
+ fd.write(' "%s" [%s];\n' %
+ (name, self._format_node_options(this_node_options)))
+
+ # Write the edges
+ for base in cls.__bases__:
+ if not self.show_builtins and base in __builtins__.values():
+ continue
+
+ base_name = self.class_name(base)
+ fd.write(' "%s" -> "%s" [%s];\n' %
+ (self.class_name(base), name,
+ self._format_node_options(e_options)))
+ fd.write('}\n')
+
+ def run_dot(self, args, name, urls={},
+ graph_options={}, node_options={}, edge_options={}):
+ """
+ Run graphviz 'dot' over this graph, returning whatever 'dot'
+ writes to stdout.
+
+ *args* will be passed along as commandline arguments.
+
+ *name* is the name of the graph
+
+ *urls* is a dictionary mapping class names to http urls
+
+ Raises DotException for any of the many os and
+ installation-related errors that may occur.
+ """
+ try:
+ dot = subprocess.Popen(['dot'] + list(args),
+ stdin=subprocess.PIPE, stdout=subprocess.PIPE,
+ close_fds=True)
+ except OSError:
+ raise DotException("Could not execute 'dot'. Are you sure you have 'graphviz' installed?")
+ except ValueError:
+ raise DotException("'dot' called with invalid arguments")
+ except:
+ raise DotException("Unexpected error calling 'dot'")
+
+ self.generate_dot(dot.stdin, name, urls, graph_options, node_options,
+ edge_options)
+ dot.stdin.close()
+ result = dot.stdout.read()
+ returncode = dot.wait()
+ if returncode != 0:
+ raise DotException("'dot' returned the errorcode %d" % returncode)
+ return result
+
+class inheritance_diagram(Body, Element):
+ """
+ A docutils node to use as a placeholder for the inheritance
+ diagram.
+ """
+ pass
+
+def inheritance_diagram_directive_run(clstexts, state):
+ """
+ Run when the inheritance_diagram directive is first encountered.
+ """
+ node = inheritance_diagram()
+
+ # Create a graph starting with the list of classes
+ graph = InheritanceGraph(clstexts)
+
+ # Create xref nodes for each target of the graph's image map and
+ # add them to the doc tree so that Sphinx can resolve the
+ # references to real URLs later. These nodes will eventually be
+ # removed from the doctree after we're done with them.
+ for name in graph.get_all_class_names():
+ refnodes, x = xfileref_role(
+ 'class', ':class:`%s`' % name, name, 0, state)
+ node.extend(refnodes)
+ # Store the graph object so we can use it to generate the
+ # dot file later
+ node['graph'] = graph
+ # Store the original content for use as a hash
+ node['content'] = " ".join(clstexts)
+ return [node]
+
+def html_output_graph(self, node):
+ """
+ Output the graph for HTML. This will insert a PNG with clickable
+ image map.
+ """
+ graph = node['graph']
+
+ # Determine where to write the PNG to. This follows
+ # the same procedure as mathpng.py
+ name = 'inheritance%s' % md5(node['content']).hexdigest()[-10:]
+ png_path = '_static/%s.png' % name
+
+ path = '_static'
+ source = self.document.attributes['source']
+ count = source.split('/doc/')[-1].count('/')
+ for i in range(count):
+ if os.path.exists(path): break
+ path = '../'+path
+ path = '../'+path #specifically added for matplotlib
+
+ # Create a mapping from fully-qualified class names to URLs.
+ urls = {}
+ for child in node:
+ try:
+ urls[child['reftitle']] = child['refuri']
+ except KeyError:
+ try:
+ urls[child['reftitle']] = '#' + child['refid']
+ except KeyError:
+ pass
+
+ # These arguments to dot will save a PNG file to disk and write
+ # an HTML image map to stdout.
+ image_map = graph.run_dot(['-Tpng', '-o%s' % png_path, '-Tcmapx'],
+ name, urls)
+ return ('<img src="%s/%s.png" usemap="#%s"/>%s' %
+ (path, name, name, image_map))
+
+def latex_output_graph(self, node):
+ """
+ Output the graph for LaTeX. This will insert a PDF.
+ """
+ graph = node['graph']
+
+ # Determine where to write the PNG to. This follows
+ # the same procedure as mathpng.py
+ name = 'inheritance%s' % md5(node['content']).hexdigest()[-10:]
+ pdf_path = '_static/%s.pdf' % name
+
+ path = '_static'
+ source = self.document.attributes['source']
+ count = source.split('/doc/')[-1].count('/')
+ for i in range(count):
+ if os.path.exists(path): break
+ path = '../'+path
+ path = '../'+path #specifically added for matplotlib
+
+ graph.run_dot(['-Tpdf', '-o%s' % pdf_path], name,
+ graph_options={'size': '"6.0,6.0"'})
+ return '\\includegraphics{../../_static/%s.pdf}' % name
+
+def visit_inheritance_diagram(inner_func):
+ """
+ This is just a wrapper around html/latex_output_graph to make it
+ easier to handle errors and insert warnings.
+ """
+ def visitor(self, node):
+ try:
+ content = inner_func(self, node)
+ except DotException, e:
+ # Insert the exception as a warning in the document
+ warning = self.document.reporter.warning(str(e), line=node.line)
+ warning.parent = node
+ node.children = [warning]
+ else:
+ source = self.document.attributes['source']
+ self.body.append(content)
+ node.children = []
+ return visitor
+
+def do_nothing(self, node):
+ pass
+
+# Deal with the old and new way of registering directives
+try:
+ from docutils.parsers.rst import Directive
+except ImportError:
+ from docutils.parsers.rst.directives import _directives
+ def inheritance_diagram_directive(name, arguments, options, content, lineno,
+ content_offset, block_text, state,
+ state_machine):
+ return inheritance_diagram_directive_run(arguments, state)
+ inheritance_diagram_directive.__doc__ = __doc__
+ inheritance_diagram_directive.arguments = (1, 100, 0)
+ inheritance_diagram_directive.options = {}
+ inheritance_diagram_directive.content = 0
+ _directives['inheritance-diagram'] = inheritance_diagram_directive
+else:
+ class inheritance_diagram_directive(Directive):
+ has_content = False
+ required_arguments = 1
+ optional_arguments = 100
+ final_argument_whitespace = False
+ option_spec = {}
+
+ def run(self):
+ return inheritance_diagram_directive_run(self.arguments, self.state)
+ inheritance_diagram_directive.__doc__ = __doc__
+
+ directives.register_directive('inheritance-diagram',
+ inheritance_diagram_directive)
+
+def setup(app):
+ app.add_node(inheritance_diagram)
+
+ HTMLTranslator.visit_inheritance_diagram = \
+ visit_inheritance_diagram(html_output_graph)
+ HTMLTranslator.depart_inheritance_diagram = do_nothing
+
+ LaTeXTranslator.visit_inheritance_diagram = \
+ visit_inheritance_diagram(latex_output_graph)
+ LaTeXTranslator.depart_inheritance_diagram = do_nothing
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Revision: 5600
 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5600&view=rev
Author: mdboom
Date: 2008年06月19日 12:53:12 -0700 (2008年6月19日)
Log Message:
-----------
docstring formatting fixes.
Modified Paths:
--------------
 trunk/matplotlib/lib/matplotlib/artist.py
Modified: trunk/matplotlib/lib/matplotlib/artist.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/artist.py	2008年06月19日 19:24:45 UTC (rev 5599)
+++ trunk/matplotlib/lib/matplotlib/artist.py	2008年06月19日 19:53:12 UTC (rev 5600)
@@ -23,7 +23,8 @@
 
 class Artist(object):
 """
- Abstract base class for someone who renders into a FigureCanvas
+ Abstract base class for someone who renders into a
+ :class:`FigureCanvas`.
 """
 
 aname = 'Artist'
@@ -52,12 +53,15 @@
 
 def remove(self):
 """
- Remove the artist from the figure if possible. The effect will not
- be visible until the figure is redrawn, e.g., with ax.draw_idle().
- Call ax.relim() to update the axes limits if desired.
+ Remove the artist from the figure if possible. The effect
+ will not be visible until the figure is redrawn, e.g., with
+ :meth:`matplotlib.axes.Axes.draw_idle`. Call
+ :meth:`matplotlib.axes.Axes.relim` to update the axes limits
+ if desired.
 
- Note: relim() will not see collections even if the collection
- was added to axes with autolim=True.
+ Note: :meth:`~matplotlib.axes.Axes.relim` will not see
+ collections even if the collection was added to axes with
+ *autolim* = True.
 
 Note: there is no support for removing the artist's legend entry.
 """
@@ -134,16 +138,18 @@
 
 def set_transform(self, t):
 """
- set the Transformation instance used by this artist
-
- ACCEPTS: a matplotlib.transform transformation instance
+ Set the :class:`~matplotlib.transforms.Transform` instance
+ used by this artist.
 """
 self._transform = t
 self._transformSet = True
 self.pchanged()
 
 def get_transform(self):
- 'return the Transformation instance used by this artist'
+ """
+ Return the :class:`~matplotlib.transforms.Transform`
+ instance used by this artist.
+ """
 if self._transform is None:
 self._transform = IdentityTransform()
 return self._transform
@@ -228,26 +234,26 @@
 None - picking is disabled for this artist (default)
 
 boolean - if True then picking will be enabled and the
- artist will fire a pick event if the mouse event is over
- the artist
+ artist will fire a pick event if the mouse event is over
+ the artist
 
 float - if picker is a number it is interpreted as an
- epsilon tolerance in points and the the artist will fire
- off an event if it's data is within epsilon of the mouse
- event. For some artists like lines and patch collections,
- the artist may provide additional data to the pick event
- that is generated, eg the indices of the data within
- epsilon of the pick event
+ epsilon tolerance in points and the the artist will fire
+ off an event if it's data is within epsilon of the mouse
+ event. For some artists like lines and patch collections,
+ the artist may provide additional data to the pick event
+ that is generated, eg the indices of the data within
+ epsilon of the pick event
 
 function - if picker is callable, it is a user supplied
- function which determines whether the artist is hit by the
- mouse event.
+ function which determines whether the artist is hit by the
+ mouse event::
 
 hit, props = picker(artist, mouseevent)
 
- to determine the hit test. if the mouse event is over the
- artist, return hit=True and props is a dictionary of
- properties you want added to the PickEvent attributes
+ to determine the hit test. if the mouse event is over the
+ artist, return hit=True and props is a dictionary of
+ properties you want added to the PickEvent attributes.
 
 ACCEPTS: [None|float|boolean|callable]
 """
@@ -288,17 +294,18 @@
 """
 Set the artist's clip path, which may be:
 
- a) a Patch (or subclass) instance
+ a) a :class:`~matplotlib.patches.Patch` (or subclass) instance
 
- b) a Path instance, in which cas aoptional transform may
- be provided, which will be applied to the path before using it
- for clipping.
+ b) a :class:`~matplotlib.path.Path` instance, in which case
+ an optional :class:`~matplotlib.transforms.Transform`
+ instance may be provided, which will be applied to the
+ path before using it for clipping.
 
- c) None, to remove the clipping path
+ c) *None*, to remove the clipping path
 
 For efficiency, if the path happens to be an axis-aligned
 rectangle, this method will set the clipping box to the
- corresponding rectangle and set the clipping path to None.
+ corresponding rectangle and set the clipping path to *None*.
 
 ACCEPTS: a Path instance and a Transform instance, a Patch
 instance, or None
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Revision: 5599
 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5599&view=rev
Author: jdh2358
Date: 2008年06月19日 12:24:45 -0700 (2008年6月19日)
Log Message:
-----------
added a releae guide to devel docs
Modified Paths:
--------------
 trunk/matplotlib/doc/devel/index.rst
 trunk/matplotlib/doc/faq/environment_variables_faq.rst
 trunk/matplotlib/doc/faq/howto_faq.rst
 trunk/matplotlib/doc/faq/installing_faq.rst
 trunk/matplotlib/doc/faq/troubleshooting_faq.rst
Added Paths:
-----------
 trunk/matplotlib/doc/devel/release_guide.rst
Modified: trunk/matplotlib/doc/devel/index.rst
===================================================================
--- trunk/matplotlib/doc/devel/index.rst	2008年06月19日 19:13:15 UTC (rev 5598)
+++ trunk/matplotlib/doc/devel/index.rst	2008年06月19日 19:24:45 UTC (rev 5599)
@@ -14,6 +14,7 @@
 
 coding_guide.rst
 documenting_mpl.rst
+ release_guide.rst
 transformations.rst
 add_new_projection.rst
 outline.rst
Added: trunk/matplotlib/doc/devel/release_guide.rst
===================================================================
--- trunk/matplotlib/doc/devel/release_guide.rst	 (rev 0)
+++ trunk/matplotlib/doc/devel/release_guide.rst	2008年06月19日 19:24:45 UTC (rev 5599)
@@ -0,0 +1,86 @@
+.. _release-guide:
+
+*************************
+Doing a matplolib release
+*************************
+
+A guide for developers who are doing a matplotlib release
+
+* Edit :file:`__init__.py` and bump the version number
+
+
+.. _release-testing:
+
+Testing
+=======
+
+* Make sure :file:`examples/tests/backend_driver.py` runs without errors
+ and check the output of the PNG, PDF, PS and SVG backends
+
+* Run :file:`unit/memleak_hawaii3.py` and make sure there are no
+ memory leaks
+
+* try some GUI examples, eg :file:`simple_plot.py` with GTKAgg, TkAgg, etc...
+
+* remove font cache and tex cache from :file:`.matplotlib` and test
+ with and without cache on some example script
+
+.. _release-packaging:
+
+Packaging
+=========
+
+* Make sure the :file:`MANIFEST.in` us up to date and remove
+ :file:`MANIFEST` so it will be rebuilt by MANIFEST.in
+
+* run `svn-clean
+ <http://svn.collab.net/repos/svn/trunk/contrib/client-side/svn-clean>`_
+ from in the mpl svn directory before building the sdist
+
+* unpack the sdist and make sure you can build from that directory
+
+* Use :file:`setup.cfg` to set the default backends. For windows and
+ OSX, the default backend should be TkAgg.
+
+* on windows, unix2dos the rc file
+
+.. _release-uploading:
+
+Uploading
+=========
+
+* Post the win32 and OS-X binaries for testing and make a request on
+ matplotlib-devel for testing. Pester us if we don't respond
+
+
+* ftp the source and binaries to the anonymous FTP site::
+
+ local> cd dist
+ local> ncftp upload.sourceforge.net
+ ncftp> cd incoming
+ ncftp> put tar.gz, zip exe
+
+* go https://sourceforge.net/project/admin/?group_id=80706 and do a
+ file release. Click on the "Admin" tab to log in as an admin, and
+ then the "File Releases" tab. Go to the bottom and click "add
+ release" and enter the package name but not the version number in
+ the "Package Name" box. You will then be prompted for the "New
+ release name" at which point you can add the version number, eg
+ somepackage-0.1 and click "Create this release".
+
+ You will then be taken to a fairly self explanatory page where you
+ can enter the Change notes, the release notes, and select which
+ packages from the incoming ftp archive you want to include in this
+ release. For each binary, you will need to select the platform and
+ file type, and when you are done you click on the "notify users who
+ are monitoring this package link"
+
+
+.. _release-announcing:
+
+Announcing
+==========
+
+Announce the release on matplotlib-announce, matplotlib-users and
+matplotlib-devel. Include a summary of highlights from the CHANGELOG
+and/or post the whole CHANGELOG since the last release.
\ No newline at end of file
Modified: trunk/matplotlib/doc/faq/environment_variables_faq.rst
===================================================================
--- trunk/matplotlib/doc/faq/environment_variables_faq.rst	2008年06月19日 19:13:15 UTC (rev 5598)
+++ trunk/matplotlib/doc/faq/environment_variables_faq.rst	2008年06月19日 19:24:45 UTC (rev 5599)
@@ -4,6 +4,8 @@
 Environment Variables
 *********************
 
+.. contents::
+
 .. envvar:: HOME
 
 The user's home directory. On linux, :envvar:`~ <HOME>` is shorthand for :envvar:`HOME`.
Modified: trunk/matplotlib/doc/faq/howto_faq.rst
===================================================================
--- trunk/matplotlib/doc/faq/howto_faq.rst	2008年06月19日 19:13:15 UTC (rev 5598)
+++ trunk/matplotlib/doc/faq/howto_faq.rst	2008年06月19日 19:24:45 UTC (rev 5599)
@@ -4,6 +4,9 @@
 Howto
 *****
 
+.. contents::
+
+
 .. _howto-subplots-adjust:
 
 How do I move the edge of my axes area over to make room for my tick labels?
Modified: trunk/matplotlib/doc/faq/installing_faq.rst
===================================================================
--- trunk/matplotlib/doc/faq/installing_faq.rst	2008年06月19日 19:13:15 UTC (rev 5598)
+++ trunk/matplotlib/doc/faq/installing_faq.rst	2008年06月19日 19:24:45 UTC (rev 5599)
@@ -4,6 +4,7 @@
 Installation
 *************
 
+.. contents::
 
 
 How do I report a compilation problem?
Modified: trunk/matplotlib/doc/faq/troubleshooting_faq.rst
===================================================================
--- trunk/matplotlib/doc/faq/troubleshooting_faq.rst	2008年06月19日 19:13:15 UTC (rev 5598)
+++ trunk/matplotlib/doc/faq/troubleshooting_faq.rst	2008年06月19日 19:24:45 UTC (rev 5599)
@@ -4,6 +4,8 @@
 Troubleshooting
 ***************
 
+.. contents::
+
 .. _matplotlib-version:
 
 What is my matplotlib version?
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

Revision: 5598
 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5598&view=rev
Author: jdh2358
Date: 2008年06月19日 12:13:15 -0700 (2008年6月19日)
Log Message:
-----------
replaced gtk timeout example
Added Paths:
-----------
 trunk/matplotlib/examples/animation/gtk_timeout.py
Removed Paths:
-------------
 trunk/matplotlib/examples/animation/dynamic_demo.py
Deleted: trunk/matplotlib/examples/animation/dynamic_demo.py
===================================================================
--- trunk/matplotlib/examples/animation/dynamic_demo.py	2008年06月19日 17:23:34 UTC (rev 5597)
+++ trunk/matplotlib/examples/animation/dynamic_demo.py	2008年06月19日 19:13:15 UTC (rev 5598)
@@ -1,27 +0,0 @@
-#!/usr/bin/env python
-
-import gobject
-import gtk
-
-from pylab import *
-
-
-fig = figure(1)
-ind = arange(30)
-X = rand(len(ind),10)
-lines = plot(X[:,0], 'o')
-
-manager = get_current_fig_manager()
-def updatefig(*args):
- lines[0].set_data(ind, X[:,updatefig.count])
- manager.canvas.draw()
- updatefig.count += 1
- if updatefig.count<10:
- return True
- else:
- return False
-
-updatefig.count = 0
-
-gobject.timeout_add(300, updatefig)
-show()
Added: trunk/matplotlib/examples/animation/gtk_timeout.py
===================================================================
--- trunk/matplotlib/examples/animation/gtk_timeout.py	 (rev 0)
+++ trunk/matplotlib/examples/animation/gtk_timeout.py	2008年06月19日 19:13:15 UTC (rev 5598)
@@ -0,0 +1,19 @@
+import gobject
+import numpy as np
+import matplotlib
+matplotlib.use('GTKAgg')
+
+import matplotlib.pyplot as plt
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+line, = ax.plot(np.random.rand(10))
+ax.set_ylim(0, 1)
+
+def update():
+ line.set_ydata(np.random.rand(10))
+ fig.canvas.draw_idle()
+ return True # return False to terminate the updates
+
+gobject.timeout_add(100, update) # you can also use idle_add to update when gtk is idle
+plt.show()
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

Revision: 5597
 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5597&view=rev
Author: jdh2358
Date: 2008年06月19日 10:23:34 -0700 (2008年6月19日)
Log Message:
-----------
added support for custom positioning of axis labels
Modified Paths:
--------------
 trunk/matplotlib/doc/faq/howto_faq.rst
 trunk/matplotlib/lib/matplotlib/axis.py
Added Paths:
-----------
 trunk/matplotlib/doc/pyplots/align_ylabels.py
Modified: trunk/matplotlib/doc/faq/howto_faq.rst
===================================================================
--- trunk/matplotlib/doc/faq/howto_faq.rst	2008年06月19日 16:54:54 UTC (rev 5596)
+++ trunk/matplotlib/doc/faq/howto_faq.rst	2008年06月19日 17:23:34 UTC (rev 5597)
@@ -113,6 +113,24 @@
 ``markersize``. For more information on configuring ticks, see
 :ref:`axis-container` and :ref:`tick-container`.
 
+
+.. _howto-align-label:
+
+How do I align my ylabels across multiple subplots?
+===================================================
+
+If you have multiple subplots over one another, and the y data have
+different scales, you can often get ylabels that do not align
+vertically across the multiple subplots, which can be unattractive.
+By default, matplotlib positions the x location of the ylabel so that
+it does not overlap any of the y ticks. You can override this default
+behavior by specifying the coordinates of the label. The example
+below shows the default behavior in the left subplots, and the manual
+setting in the right subplots.
+
+.. plot:: align_ylabels.py
+ :include-source:
+
 .. _howto-webapp:
 
 How do I use matplotlib in a web application server?
Added: trunk/matplotlib/doc/pyplots/align_ylabels.py
===================================================================
--- trunk/matplotlib/doc/pyplots/align_ylabels.py	 (rev 0)
+++ trunk/matplotlib/doc/pyplots/align_ylabels.py	2008年06月19日 17:23:34 UTC (rev 5597)
@@ -0,0 +1,35 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+box = dict(facecolor='yellow', pad=5, alpha=0.2)
+
+fig = plt.figure()
+fig.subplots_adjust(left=0.2, wspace=0.6)
+
+
+ax1 = fig.add_subplot(221)
+ax1.plot(2000*np.random.rand(10))
+ax1.set_title('ylabels not aligned')
+ax1.set_ylabel('misaligned 1', bbox=box)
+ax1.set_ylim(0, 2000)
+ax3 = fig.add_subplot(223)
+ax3.set_ylabel('misaligned 2',bbox=box)
+ax3.plot(np.random.rand(10))
+
+
+labelx = -0.3 # axes coords
+
+ax2 = fig.add_subplot(222)
+ax2.set_title('ylabels aligned')
+ax2.plot(2000*np.random.rand(10))
+ax2.set_ylabel('aligned 1', bbox=box)
+ax2.yaxis.set_label_coords(labelx, 0.5)
+ax2.set_ylim(0, 2000)
+
+ax4 = fig.add_subplot(224)
+ax4.plot(np.random.rand(10))
+ax4.set_ylabel('aligned 2', bbox=box)
+ax4.yaxis.set_label_coords(labelx, 0.5)
+
+
+plt.show()
Modified: trunk/matplotlib/lib/matplotlib/axis.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axis.py	2008年06月19日 16:54:54 UTC (rev 5596)
+++ trunk/matplotlib/lib/matplotlib/axis.py	2008年06月19日 17:23:34 UTC (rev 5597)
@@ -503,9 +503,9 @@
 
 """
 Public attributes
- transData - transform data coords to display coords
- transAxis - transform axis coords to display coords
 
+ * transData - transform data coords to display coords
+ * transAxis - transform axis coords to display coords
 
 """
 LABELPAD = 5
@@ -533,6 +533,7 @@
 #self.major = dummy()
 #self.minor = dummy()
 
+ self._autolabelpos = True
 self.label = self._get_label()
 self.offsetText = self._get_offset_text()
 self.majorTicks = []
@@ -542,6 +543,29 @@
 self.cla()
 self.set_scale('linear')
 
+
+ def set_label_coords(self, x, y, transform=None):
+ """
+ Set the coordinates of the label. By default, the x
+ coordinate of the y label is determined by the tick label
+ bounding boxes, but this can lead to poor alignment of
+ multiple ylabels if there are multiple axes. Ditto for the y
+ coodinate of the x label.
+
+ You can also specify the coordinate system of the label with
+ the transform. If None, the default coordinate system will be
+ the axes coordinate system (0,0) is (left,bottom), (0.5, 0.5)
+ is middle, etc
+
+ """
+
+ self._autolabelpos = False
+ if transform is None:
+ transform = self.axes.transAxes
+
+ self.label.set_transform(transform)
+ self.label.set_position((x, y))
+
 def get_transform(self):
 return self._scale.get_transform()
 
@@ -703,7 +727,9 @@
 # just the tick labels that actually overlap note we need a
 # *copy* of the axis label box because we don't wan't to scale
 # the actual bbox
+
 self._update_label_position(ticklabelBoxes, ticklabelBoxes2)
+
 self.label.draw(renderer)
 
 self._update_offset_text_position(ticklabelBoxes, ticklabelBoxes2)
@@ -1139,8 +1165,9 @@
 verticalalignment='top',
 horizontalalignment='center',
 )
+
 label.set_transform( mtransforms.blended_transform_factory(
- self.axes.transAxes, mtransforms.IdentityTransform() ))
+ self.axes.transAxes, mtransforms.IdentityTransform() ))
 
 self._set_artist_props(label)
 self.label_position='bottom'
@@ -1184,7 +1211,7 @@
 Update the label position based on the sequence of bounding
 boxes of all the ticklabels
 """
-
+ if not self._autolabelpos: return
 x,y = self.label.get_position()
 if self.label_position == 'bottom':
 if not len(bboxes):
@@ -1374,7 +1401,7 @@
 rotation='vertical',
 )
 label.set_transform( mtransforms.blended_transform_factory(
- mtransforms.IdentityTransform(), self.axes.transAxes) )
+ mtransforms.IdentityTransform(), self.axes.transAxes) )
 
 self._set_artist_props(label)
 self.label_position='left'
@@ -1418,7 +1445,7 @@
 Update the label position based on the sequence of bounding
 boxes of all the ticklabels
 """
-
+ if not self._autolabelpos: return
 x,y = self.label.get_position()
 if self.label_position == 'left':
 if not len(bboxes):
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

Revision: 5596
 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5596&view=rev
Author: jdh2358
Date: 2008年06月19日 09:54:54 -0700 (2008年6月19日)
Log Message:
-----------
added auto subplots adj faq
Modified Paths:
--------------
 trunk/matplotlib/Makefile
 trunk/matplotlib/doc/faq/howto_faq.rst
 trunk/matplotlib/doc/glossary/index.rst
 trunk/matplotlib/doc/make.py
 trunk/matplotlib/doc/users/installing.rst
Added Paths:
-----------
 trunk/matplotlib/doc/pyplots/auto_subplots_adjust.py
Modified: trunk/matplotlib/Makefile
===================================================================
--- trunk/matplotlib/Makefile	2008年06月19日 13:59:08 UTC (rev 5595)
+++ trunk/matplotlib/Makefile	2008年06月19日 16:54:54 UTC (rev 5596)
@@ -39,7 +39,7 @@
 	rm -rf build;\
 	python make.py clean;\
 	svn up;\
-	python make.py html latex sf;
+	python make.py html latex sf sfpdf;
 
 
 
Modified: trunk/matplotlib/doc/faq/howto_faq.rst
===================================================================
--- trunk/matplotlib/doc/faq/howto_faq.rst	2008年06月19日 13:59:08 UTC (rev 5595)
+++ trunk/matplotlib/doc/faq/howto_faq.rst	2008年06月19日 16:54:54 UTC (rev 5596)
@@ -54,6 +54,40 @@
 `axes_demo.py <http://matplotlib.sf.net/examples/axes_demo.py>`_ for
 an example of placing axes manually.
 
+.. _howto-auto-adjust:
+
+How do I automatically make room for my tick labels?
+====================================================
+
+In most use cases, it is enought to simpy change the subplots adjust
+parameters as described in :ref:`howto-subplots-adjust`. But in some
+cases, you don't know ahead of time what your tick labels will be, or
+how large they will be (data and labels outside your control may be
+being fed into your graphing application), and you may need to
+automatically adjust your subplot parameters based on the size of the
+tick labels. Any :class:`matplotlib.text.Text` instance can report
+its extent in window coordinates (a negative x coordinate is outside
+the window), but there is a rub.
+
+The :class:`matplotlib.backend_bases.RendererBase` instance, which is
+used to calculate the text size, is not known until the figure is
+drawn (:meth:`matplotlib.figure.Figure.draw`). After the window is
+drawn and the text instance knows its renderer, you can call
+:meth:`matplotlib.text.Text.get_window_extent``. One way to solve
+this chicken and egg problem is to wait until the figure is draw by
+connecting
+(:meth:`matplotlib.backend_bases.FigureCanvasBase.mpl_connect`) to the
+"on_draw" signal (:class:`~matplotlib.backend_bases.DrawEvent`) and
+get the window extent there, and then do something with it, eg move
+the left of the canvas over; see :ref:`event-handling-tutorial`.
+
+Here is a recursive, iterative solution that will gradually move the
+left of the subplot over until the label fits w/o going outside the
+figure border (requires matplotlib 0.98)
+
+.. plot:: auto_subplots_adjust.py
+ :include-source:
+
 .. _howto-ticks:
 
 How do I configure the tick linewidths?
Modified: trunk/matplotlib/doc/glossary/index.rst
===================================================================
--- trunk/matplotlib/doc/glossary/index.rst	2008年06月19日 13:59:08 UTC (rev 5595)
+++ trunk/matplotlib/doc/glossary/index.rst	2008年06月19日 16:54:54 UTC (rev 5596)
@@ -8,73 +8,138 @@
 .. glossary::
 
 AGG
- The Anti-Grain Geometry rendering engine, capable of rendering
- high-quality images.
+ The Anti-Grain Geometry (`Agg <http://antigrain.com>`_) rendering engine, capable of rendering
+ high-quality images
 
 Cairo
- The Cairo graphics engine
+ The `Cairo graphics <http://cairographics.org>`_ engine
 
 EPS
- Encapsulated Postscript
+ Encapsulated Postscript (`EPS <http://en.wikipedia.org/wiki/Encapsulated_PostScript>`_)
 
 FLTK
- FLTK (pronounced "fulltick") is a cross-platform C++ GUI toolkit for
+ `FLTK <http://www.fltk.org/>`_ (pronounced "fulltick") is a cross-platform C++ GUI toolkit for
 UNIX/Linux (X11), Microsoft Windows, and MacOS X
 
+ freetype
+ `freetype <http://www.freetype.org/>`_ is a font rasterization
+ library used by matplotlib which supports TrueType, Type 1, and
+ OpenType fonts.
+
+
 GDK
 The Gimp Drawing Kit for GTK+
 
 GTK
- The GTK graphical user interface library
+ The GIMP Toolkit (`GTK <http://www.gtk.org/>`_) graphical user interface library
 
 JPG
- A compression method and file format for photographic images
+ The Joint Photographic Experts Group (`JPEG
+ <http://en.wikipedia.org/wiki/Jpeg>`_) compression method and
+ file format for photographic images
 
+ numpy
+ `numpy <http://numpy.scipy.org>`_ is the standard numerical
+ array library for python, the successor to Numeric and numarray.
+ numpy provides fast operations for homogeneous data sets and
+ common mathematical operations like correlations, standard
+ deviation, fourier transforms, and convolutions.
+
 PDF
- Adobe's Portable Document Format
+ Adobe's Portable Document Format (`PDF <http://en.wikipedia.org/wiki/Portable_Document_Format>`_)
 
 PNG
- PNG stands for Portable Network Graphics, a raster graphics format that
- employs lossless data compression which is more suitable for line art
- than the lossy jpg format. Unlike the gif format, png is not encumbered
- by requirements for a patent license.
+ Portable Network Graphics (`PNG
+ <http://en.wikipedia.org/wiki/Portable_Network_Graphics>`_), a raster graphics format
+ that employs lossless data compression which is more suitable
+ for line art than the lossy jpg format. Unlike the gif format,
+ png is not encumbered by requirements for a patent license.
 
 PS
- Postscript
+ Postscript (`PS <http://en.wikipedia.org/wiki/PostScript>`_) is a
+ vector graphics ASCII text language widely used in printers and
+ publishing. Postscript was developerd by adobe systems and is
+ starting to show its age: for example is does not have an alpha
+ channel. PDF was designed in part as a next-generation document
+ format to replace postscript
 
+ pyfltk
+ `pyfltk <http://pyfltk.sourceforge.net/>`_ provides python
+ wrappers for the :term:`FLTK` widgets library for use with
+ FLTKAgg
+
+ pygtk
+ `pygtk <http://www.pygtk.org/>`_ provides python wrappers for
+ the :term:`GTK` widgets library for use with the GTK or GTKAgg
+ backend. Widely used on linux, and is often packages as
+ 'python-gtk2'
+
+ pyqt
+ `pyqt <http://wiki.python.org/moin/PyQt>`_ provides python
+ wrappers for the :term:`Qt` widgets library and is requied by
+ the matplotlib QtAgg and Qt4Agg backends. Widely used on linux
+ and windows; many linux distributions package this as
+ 'python-qt3' or 'python-qt4'.
+
+ python
+ `python <http://python.org>`_ is an object oriented interpreted
+ language widely used for scripting, application development, web
+ application servers, scientific computing and more.
+
 Qt
- Qt is a cross-platform application framework for desktop and embedded
- development.
+ `Qt <http://trolltech.com/products/qt/>`__ is a cross-platform
+ application framework for desktop and embedded development.
 
 Qt4
- Qt4 is the most recent version of Qt cross-platform application framework
- for desktop and embedded development.
+ `Qt4 <http://trolltech.com/products/qt/>`__ is the most recent
+ version of Qt cross-platform application framework for desktop
+ and embedded development.
 
 raster graphics
- Raster graphics, or bitmaps, represent an image as an array of pixels
- which is resolution dependent. Raster graphics are generally most
- practical for photo-realistic images, but do not scale easily without
- loss of quality. See `raster graphics <http://en.wikipedia.org/wiki/Raster_graphics>`_
+ `Raster graphics
+ <http://en.wikipedia.org/wiki/Raster_graphics>`_, or bitmaps,
+ represent an image as an array of pixels which is resolution
+ dependent. Raster graphics are generally most practical for
+ photo-realistic images, but do not scale easily without loss of
+ quality.
 
 SVG
- The Scalable Vector Graphics format.
+ The Scalable Vector Graphics format (`SVG
+ <http://en.wikipedia.org/wiki/Svg>`_). An XML based vector
+ graphics format supported by many web browsers.
 
 TIFF
- Tagged Image File Format
+ Tagged Image File Format (`TIFF
+ <http://en.wikipedia.org/wiki/Tagged_Image_File_Format>`_) is a
+ file format for storing images, including photographs and line
+ art.
 
 Tk
- Tk is a graphical user interface for Tcl and many other dynamic
- languages. It can produce rich, native applications that run unchanged
- across Windows, Mac OS X, Linux and more.
+ `Tk <http://www.tcl.tk/>`_ is a graphical user interface for Tcl
+ and many other dynamic languages. It can produce rich, native
+ applications that run unchanged across Windows, Mac OS X, Linux
+ and more.
 
+ vector graphics
+ `vector graphics
+ <http://en.wikipedia.org/wiki/Vector_graphics>`_ use geometrical
+ primitives based upon mathematical equations to represent images
+ in computer graphics. Primitives can include points, lines,
+ curves, and shapes or polygons. Vector graphics are scalable,
+ which means that they can be resized without suffering from
+ issues related to inherent resolution like are seen in raster
+ graphics. Vector graphics are generally most practical for
+ typesetting and graphic design applications.
+
+ wxpython
+ `wxpython <http://www.wxpython.org/>`_ provides python wrappers
+ for the :term:`wxWidgets` library for use with the WX and WXAgg
+ backends. Widely used on linux, OS-X and windows, it is often
+ packaged by linux distributions as 'python-wxgtk'
+
 wxWidgets
- A cross-platform GUI and tools library for GTK, MS Windows, and MacOS.
+ `WX <http://www.wxwidgets.org/>`_ is cross-platform GUI and
+ tools library for GTK, MS Windows, and MacOS. It uses native
+ widgets for each operating system, so applications will have the
+ look-and-feel that users on that operating system expect.
 
- vector graphics
- The use of geometrical primitives based upon mathematical equations to
- represent images in computer graphics. Primitives can include points,
- lines, curves, and shapes or polygons. Vector graphics are scalable,
- which means that they can be resized without suffering from issues
- related to inherent resolution like are seen in raster graphics. Vector
- graphics are generally most practical for typesetting and graphic design
- applications. See `vector graphics <http://en.wikipedia.org/wiki/Vector_graphics>`_
Modified: trunk/matplotlib/doc/make.py
===================================================================
--- trunk/matplotlib/doc/make.py	2008年06月19日 13:59:08 UTC (rev 5595)
+++ trunk/matplotlib/doc/make.py	2008年06月19日 16:54:54 UTC (rev 5596)
@@ -17,8 +17,12 @@
 def sf():
 'push a copy to the sf site'
 os.system('cd build; rsync -avz html jd...@ma...:/home/groups/m/ma/matplotlib/htdocs/doc/ -essh')
- os.system('cd build/latex; scp Matplotlib.pdf jd...@ma...:/home/groups/m/ma/matplotlib/htdocs/doc/')
 
+def sfpdf():
+ 'push a copy to the sf site'
+
+ #os.system('cd build/latex; scp Matplotlib.pdf jd...@ma...:/home/groups/m/ma/matplotlib/htdocs/doc/')
+
 def figs():
 os.system('cd users/figures/ && python make.py')
 
@@ -73,6 +77,7 @@
 'latex':latex,
 'clean':clean,
 'sf':sf,
+ 'sfpdf':sfpdf,
 'all':all,
 }
 
Added: trunk/matplotlib/doc/pyplots/auto_subplots_adjust.py
===================================================================
--- trunk/matplotlib/doc/pyplots/auto_subplots_adjust.py	 (rev 0)
+++ trunk/matplotlib/doc/pyplots/auto_subplots_adjust.py	2008年06月19日 16:54:54 UTC (rev 5596)
@@ -0,0 +1,19 @@
+import matplotlib.pyplot as plt
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+ax.plot(range(10))
+ax.set_yticks((2,5,7))
+labels = ax.set_yticklabels(('really, really, really', 'long', 'labels'))
+
+def on_draw(event):
+ for label in labels:
+ bbox = label.get_window_extent()
+ if bbox.xmin<0:
+ fig.subplots_adjust(left=1.1*fig.subplotpars.left)
+ fig.canvas.draw()
+ break
+
+fig.canvas.mpl_connect('draw_event', on_draw)
+
+plt.show()
Modified: trunk/matplotlib/doc/users/installing.rst
===================================================================
--- trunk/matplotlib/doc/users/installing.rst	2008年06月19日 13:59:08 UTC (rev 5595)
+++ trunk/matplotlib/doc/users/installing.rst	2008年06月19日 16:54:54 UTC (rev 5596)
@@ -14,18 +14,18 @@
 and numpy) since the others are built into the matplotlib windows
 installers available for download at the sourceforge site.
 
-python 2.4 (or later but not python3)
- matplotlib requires python 2.4 or later
+:term:`python` 2.4 (or later but not python3)
+ matplotlib requires python 2.4 or later (`download <http://www.python.org/download/>`__)
 
-numpy 1.1 (or later)
- array support for python
+:term:`numpy` 1.1 (or later)
+ array support for python (`download <http://sourceforge.net/project/showfiles.php?group_id=1369&package_id=175103>`__)
 
 libpng 1.1 (or later)
- library for loading and saving PNG files. libpng requires zlib. If
+ library for loading and saving :term:`PNG` files (`download <http://www.libpng.org/pub/png/libpng.html>`__). libpng requires zlib. If
 you are a windows user, you can ignore this since we build support
- into the matplotlib single click installer.
+ into the matplotlib single click installer
 
-freetype 1.4 (or later)
+:term:`freetype` 1.4 (or later)
 library for reading true type font files. If you are a windows
 user, you can ignore this since we build support into the
 matplotlib single click installer.
@@ -37,25 +37,25 @@
 :ref:`what-is-a-backend` for more details on the optional matplotlib
 backends and the capabilities they provide
 
-tk 8.3 or later
+:term:`tk` 8.3 or later
 The TCL/Tk widgets library used by the TkAgg backend
 
-pyqt 3.1 or later
+:term:`pyqt` 3.1 or later
 The Qt3 widgets library python wrappers for the QtAgg backend
 
-pyqt 4.0 or later
+:term:`pyqt` 4.0 or later
 The Qt4 widgets library python wrappersfor the Qt4Agg backend
 
-pygtk 2.2 or later
+:term:`pygtk` 2.2 or later
 The python wrappers for the GTK widgets library for use with the GTK or GTKAgg backend
 
-wxpython 2.6 or later
+:term:`wxpython` 2.6 or later
 The python wrappers for the wx widgets library for use with the WXAgg backend
 
-wxpython 2.8 or later
+:term:`wxpython` 2.8 or later
 The python wrappers for the wx widgets library for use with the WX backend
 
-pyfltk 1.0 or later
+:term:`pyfltk` 1.0 or later
 The python wrappers of the FLTK widgets library for use with FLTKAgg
 
 **Required libraries that ship with matplotlib**
@@ -65,7 +65,7 @@
 developers and packagers who may want to disable the matplotlib
 version and ship a packaged version.
 
-agg2.4
+:term:`agg` 2.4
 The antigrain C++ rendering engine
 
 pytz 2007g or later
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

Revision: 5595
 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5595&view=rev
Author: jdh2358
Date: 2008年06月19日 06:59:08 -0700 (2008年6月19日)
Log Message:
-----------
added the installing doc
Modified Paths:
--------------
 trunk/matplotlib/doc/faq/installing_faq.rst
Added Paths:
-----------
 trunk/matplotlib/doc/users/installing.rst
Modified: trunk/matplotlib/doc/faq/installing_faq.rst
===================================================================
--- trunk/matplotlib/doc/faq/installing_faq.rst	2008年06月19日 13:23:04 UTC (rev 5594)
+++ trunk/matplotlib/doc/faq/installing_faq.rst	2008年06月19日 13:59:08 UTC (rev 5595)
@@ -55,10 +55,12 @@
 
 easy_install -m PackageName
 
+
 3. Delete any .egg files or directories from your :ref:`installation
 directory <locating-matplotlib-install>`.
 
 
+
 Windows installer
 -----------------
 
Added: trunk/matplotlib/doc/users/installing.rst
===================================================================
--- trunk/matplotlib/doc/users/installing.rst	 (rev 0)
+++ trunk/matplotlib/doc/users/installing.rst	2008年06月19日 13:59:08 UTC (rev 5595)
@@ -0,0 +1,91 @@
+.. _installing:
+
+**********
+Installing
+**********
+
+Dependencies
+============
+
+**Requirements**
+
+These are external packages which you will need to install before
+installing matplotlib. Windows users only need the first two (python
+and numpy) since the others are built into the matplotlib windows
+installers available for download at the sourceforge site.
+
+python 2.4 (or later but not python3)
+ matplotlib requires python 2.4 or later
+
+numpy 1.1 (or later)
+ array support for python
+
+libpng 1.1 (or later)
+ library for loading and saving PNG files. libpng requires zlib. If
+ you are a windows user, you can ignore this since we build support
+ into the matplotlib single click installer.
+
+freetype 1.4 (or later)
+ library for reading true type font files. If you are a windows
+ user, you can ignore this since we build support into the
+ matplotlib single click installer.
+
+**Optional**
+
+These are optional packages which you may want to install to use
+matplotlib with a user interface toolkit. See
+:ref:`what-is-a-backend` for more details on the optional matplotlib
+backends and the capabilities they provide
+
+tk 8.3 or later
+ The TCL/Tk widgets library used by the TkAgg backend
+
+pyqt 3.1 or later
+ The Qt3 widgets library python wrappers for the QtAgg backend
+
+pyqt 4.0 or later
+ The Qt4 widgets library python wrappersfor the Qt4Agg backend
+
+pygtk 2.2 or later
+ The python wrappers for the GTK widgets library for use with the GTK or GTKAgg backend
+
+wxpython 2.6 or later
+ The python wrappers for the wx widgets library for use with the WXAgg backend
+
+wxpython 2.8 or later
+ The python wrappers for the wx widgets library for use with the WX backend
+
+pyfltk 1.0 or later
+ The python wrappers of the FLTK widgets library for use with FLTKAgg
+
+**Required libraries that ship with matplotlib**
+
+If you are downloading matplotlib or installing from source or
+subversion, you can ignore this section. This is useful for matplotlib
+developers and packagers who may want to disable the matplotlib
+version and ship a packaged version.
+
+agg2.4
+ The antigrain C++ rendering engine
+
+pytz 2007g or later
+ timezone handling for python datetime objects
+
+dateutil 1.1 or later
+ extensions to python datetime handling
+
+**Optional libraries that ship with matplotlib**
+
+As above, if you are downloading matplotlib or installing from source
+or subversion, you can ignore this section. This is useful for
+matplotlib developers and packagers who may want to disable the
+matplotlib version and ship a packaged version.
+
+enthought traits 2.6
+ The traits component of the Enthought Tool Suite used in the
+ experimental matplotlib traits rc system. matplotlib has decided
+ to stop installing this library so packagers should not distribute
+ the version included with matplotlib. packagers do not need to
+ list this as a requirement because the traits support is
+ experimental and disabled by default.
+
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

Revision: 5594
 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5594&view=rev
Author: mdboom
Date: 2008年06月19日 06:23:04 -0700 (2008年6月19日)
Log Message:
-----------
Fix rgrids and thetagrids.
Modified Paths:
--------------
 trunk/matplotlib/lib/matplotlib/projections/polar.py
 trunk/matplotlib/lib/matplotlib/pyplot.py
Modified: trunk/matplotlib/lib/matplotlib/projections/polar.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/projections/polar.py	2008年06月19日 13:16:16 UTC (rev 5593)
+++ trunk/matplotlib/lib/matplotlib/projections/polar.py	2008年06月19日 13:23:04 UTC (rev 5594)
@@ -316,6 +316,7 @@
 self._theta_label2_position.clear().translate(0.0, 1.0 / frac)
 for t in self.xaxis.get_ticklabels():
 t.update(kwargs)
+ return self.xaxis.get_ticklines(), self.xaxis.get_ticklabels()
 set_thetagrids.__doc__ = cbook.dedent(set_thetagrids.__doc__) % kwdocd
 
 def set_rgrids(self, radii, labels=None, angle=None, rpad=None, **kwargs):
@@ -358,6 +359,7 @@
 self._r_label2_position.clear().translate(angle, -self._rpad * rmax)
 for t in self.yaxis.get_ticklabels():
 t.update(kwargs)
+ return self.yaxis.get_ticklines(), self.yaxis.get_ticklabels()
 
 set_rgrids.__doc__ = cbook.dedent(set_rgrids.__doc__) % kwdocd
 
Modified: trunk/matplotlib/lib/matplotlib/pyplot.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/pyplot.py	2008年06月19日 13:16:16 UTC (rev 5593)
+++ trunk/matplotlib/lib/matplotlib/pyplot.py	2008年06月19日 13:23:04 UTC (rev 5594)
@@ -951,8 +951,8 @@
 if not isinstance(ax, PolarAxes):
 raise RuntimeError('rgrids only defined for polar axes')
 if len(args)==0:
- lines = ax.rgridlines()
- labels = ax.rgridlabels()
+ lines = ax.yaxis.get_ticklines()
+ labels = ax.yaxis.get_ticklabels()
 else:
 lines, labels = ax.set_rgrids(*args, **kwargs)
 
@@ -1011,8 +1011,8 @@
 if not isinstance(ax, PolarAxes):
 raise RuntimeError('rgrids only defined for polar axes')
 if len(args)==0:
- lines = ax.thetagridlines()
- labels = ax.thetagridlabels()
+ lines = ax.xaxis.get_ticklines()
+ labels = ax.xaxis.get_ticklabels()
 else:
 lines, labels = ax.set_thetagrids(*args, **kwargs)
 
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

Revision: 5593
 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5593&view=rev
Author: mdboom
Date: 2008年06月19日 06:16:16 -0700 (2008年6月19日)
Log Message:
-----------
Lots of docstring formatting fixes.
Modified Paths:
--------------
 trunk/matplotlib/doc/faq/installing_faq.rst
 trunk/matplotlib/lib/matplotlib/__init__.py
 trunk/matplotlib/lib/matplotlib/artist.py
 trunk/matplotlib/lib/matplotlib/axes.py
 trunk/matplotlib/lib/matplotlib/backend_bases.py
 trunk/matplotlib/lib/matplotlib/contour.py
 trunk/matplotlib/lib/matplotlib/figure.py
 trunk/matplotlib/lib/matplotlib/image.py
 trunk/matplotlib/lib/matplotlib/lines.py
 trunk/matplotlib/lib/matplotlib/pyplot.py
 trunk/matplotlib/lib/matplotlib/quiver.py
 trunk/matplotlib/lib/matplotlib/text.py
Modified: trunk/matplotlib/doc/faq/installing_faq.rst
===================================================================
--- trunk/matplotlib/doc/faq/installing_faq.rst	2008年06月19日 12:16:50 UTC (rev 5592)
+++ trunk/matplotlib/doc/faq/installing_faq.rst	2008年06月19日 13:16:16 UTC (rev 5593)
@@ -55,8 +55,8 @@
 
 easy_install -m PackageName
 
-3. Delete any .egg files or directories from your `installation directory
- <locating-matplotlib-install>`.
+3. Delete any .egg files or directories from your :ref:`installation
+ directory <locating-matplotlib-install>`.
 
 
 Windows installer
Modified: trunk/matplotlib/lib/matplotlib/__init__.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/__init__.py	2008年06月19日 12:16:50 UTC (rev 5592)
+++ trunk/matplotlib/lib/matplotlib/__init__.py	2008年06月19日 13:16:16 UTC (rev 5593)
@@ -684,11 +684,11 @@
 
 def rc(group, **kwargs):
 """
- Set the current rc params. Group is the grouping for the rc, eg
- for lines.linewidth the group is 'lines', for axes.facecolor, the
- group is 'axes', and so on. Group may also be a list or tuple
- of group names, eg ('xtick','ytick'). kwargs is a list of
- attribute name/value pairs, eg::
+ Set the current rc params. Group is the grouping for the rc, eg.
+ for ``lines.linewidth`` the group is ``lines``, for
+ ``axes.facecolor``, the group is ``axes``, and so on. Group may
+ also be a list or tuple of group names, eg. (*xtick*, *ytick*).
+ *kwargs* is a dictionary attribute name/value pairs, eg::
 
 rc('lines', linewidth=2, color='r')
 
@@ -728,7 +728,8 @@
 rc('font', **font) # pass in the font dict as kwargs
 
 This enables you to easily switch between several configurations.
- Use rcdefaults to restore the default rc params after changes.
+ Use :func:`~matplotlib.pyplot.rcdefaults` to restore the default
+ rc params after changes.
 """
 
 aliases = {
@@ -756,7 +757,7 @@
 def rcdefaults():
 """
 Restore the default rc params - the ones that were created at
- matplotlib load time
+ matplotlib load time.
 """
 rcParams.update(rcParamsDefault)
 
Modified: trunk/matplotlib/lib/matplotlib/artist.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/artist.py	2008年06月19日 12:16:50 UTC (rev 5592)
+++ trunk/matplotlib/lib/matplotlib/artist.py	2008年06月19日 13:16:16 UTC (rev 5593)
@@ -707,31 +707,32 @@
 
 def setp(h, *args, **kwargs):
 """
- matplotlib supports the use of setp ("set property") and getp to set
- and get object properties, as well as to do introspection on the
- object For example, to set the linestyle of a line to be dashed, you
- can do
+ matplotlib supports the use of :func:`setp` ("set property") and
+ :func:`getp` to set and get object properties, as well as to do
+ introspection on the object. For example, to set the linestyle of a
+ line to be dashed, you can do::
 
 >>> line, = plot([1,2,3])
 >>> setp(line, linestyle='--')
 
 If you want to know the valid types of arguments, you can provide the
- name of the property you want to set without a value
+ name of the property you want to set without a value::
 
 >>> setp(line, 'linestyle')
 linestyle: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' ]
 
 If you want to see all the properties that can be set, and their
- possible values, you can do
+ possible values, you can do::
 
 >>> setp(line)
 ... long output listing omitted
 
- setp operates on a single instance or a list of instances. If you
- are in query mode introspecting the possible values, only the first
- instance in the sequence is used. When actually setting values,
- all the instances will be set. Eg, suppose you have a list of two
- lines, the following will make both lines thicker and red
+ :func:`setp` operates on a single instance or a list of instances.
+ If you are in query mode introspecting the possible values, only
+ the first instance in the sequence is used. When actually setting
+ values, all the instances will be set. Eg., suppose you have a
+ list of two lines, the following will make both lines thicker and
+ red::
 
 >>> x = arange(0,1.0,0.01)
 >>> y1 = sin(2*pi*x)
@@ -739,8 +740,8 @@
 >>> lines = plot(x, y1, x, y2)
 >>> setp(lines, linewidth=2, color='r')
 
- setp works with the matlab(TM) style string/value pairs or with
- python kwargs. For example, the following are equivalent
+ :func:`setp` works with the matlab(TM) style string/value pairs or
+ with python kwargs. For example, the following are equivalent
 
 >>> setp(lines, 'linewidth', 2, 'color', r') # matlab style
 >>> setp(lines, linewidth=2, color='r') # python style
Modified: trunk/matplotlib/lib/matplotlib/axes.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axes.py	2008年06月19日 12:16:50 UTC (rev 5592)
+++ trunk/matplotlib/lib/matplotlib/axes.py	2008年06月19日 13:16:16 UTC (rev 5593)
@@ -1546,17 +1546,18 @@
 
 grid(self, b=None, **kwargs)
 
- Set the axes grids on or off; b is a boolean
+ Set the axes grids on or off; *b* is a boolean
 
- if b is None and len(kwargs)==0, toggle the grid state. if
- kwargs are supplied, it is assumed that you want a grid and b
- is thus set to True
+ If *b* is *None* and len(kwargs)==0, toggle the grid state. If
+ kwargs are supplied, it is assumed that you want a grid and *b*
+ is thus set to *True*
 
 kawrgs are used to set the grid line properties, eg::
 
 ax.grid(color='r', linestyle='-', linewidth=2)
 
- Valid Line2D kwargs are
+ Valid :class:`~matplotlib.lines.Line2D` kwargs are
+
 %(Line2D)s
 """
 if len(kwargs): b = True
@@ -2457,40 +2458,44 @@
 
 text(x, y, s, fontdict=None, **kwargs)
 
- Add text in string s to axis at location x,y (data coords)
+ Add text in string *s* to axis at location *x*, *y*, data
+ coordinates.
 
 Keyword arguments:
 
- fontdict:
- a dictionary to override the default text properties.
- If fontdict is None, the defaults are determined by your rc
+ *fontdict*:
+ A dictionary to override the default text properties.
+ If *fontdict* is *None*, the defaults are determined by your rc
 parameters.
- withdash: [ False | True ]
- creates a TextWithDash instance instead of a Text instance.
 
+ *withdash*: [ False | True ]
+ Creates a :class:`~matplotlib.text.TextWithDash` instance
+ instead of a :class:`~matplotlib.text.Text` instance.
+
 Individual keyword arguments can be used to override any given
 parameter::
 
 text(x, y, s, fontsize=12)
 
 The default transform specifies that text is in data coords,
- alternatively, you can specify text in axis coords (0,0 lower left and
- 1,1 upper right). The example below places text in the center of the
- axes::
+ alternatively, you can specify text in axis coords (0,0 is
+ lower-left and 1,1 is upper-right). The example below places
+ text in the center of the axes::
 
 text(0.5, 0.5,'matplotlib',
 horizontalalignment='center',
 verticalalignment='center',
 transform = ax.transAxes)
 
- You can put a rectangular box around the text instance (eg to
- set a background color) by using the keyword bbox. bbox is a
- dictionary of patches.Rectangle properties (see help
- for Rectangle for a list of these). For example::
+ You can put a rectangular box around the text instance (eg. to
+ set a background color) by using the keyword *bbox*. *bbox* is
+ a dictionary of :class:`matplotlib.patches.Rectangle`
+ properties. For example::
 
 text(x, y, s, bbox=dict(facecolor='red', alpha=0.5))
 
- Valid kwargs are Text properties
+ Valid kwargs are :class:`matplotlib.text.Text` properties:
+
 %(Text)s
 """
 default = {
@@ -2536,6 +2541,7 @@
 textcoords='data', arrowprops=None, **kwargs)
 
 Keyword arguments:
+
 %(Annotation)s
 """
 a = mtext.Annotation(*args, **kwargs)
@@ -2556,30 +2562,33 @@
 
 Axis Horizontal Line
 
- Draw a horizontal line at y from xmin to xmax. With the default
- values of xmin=0 and xmax=1, this line will always span the horizontal
- extent of the axes, regardless of the xlim settings, even if you
- change them, eg with the xlim command. That is, the horizontal extent
- is in axes coords: 0=left, 0.5=middle, 1.0=right but the y location is
- in data coordinates.
+ Draw a horizontal line at *y* from *xmin* to *xmax*. With the
+ default values of *xmin* = 0 and *xmax* = 1, this line will
+ always span the horizontal extent of the axes, regardless of
+ the xlim settings, even if you change them, eg. with the
+ :meth:`set_xlim` command. That is, the horizontal extent is
+ in axes coords: 0=left, 0.5=middle, 1.0=right but the *y*
+ location is in data coordinates.
 
- Return value is the Line2D instance. kwargs are the same as kwargs to
- plot, and can be used to control the line properties. Eg
+ Return value is the :class:`~matplotlib.lines.Line2D`
+ instance. kwargs are the same as kwargs to plot, and can be
+ used to control the line properties. Eg.,
 
- * draw a thick red hline at y=0 that spans the xrange
+ * draw a thick red hline at *y* = 0 that spans the xrange
 
 >>> axhline(linewidth=4, color='r')
 
- * draw a default hline at y=1 that spans the xrange
+ * draw a default hline at *y* = 1 that spans the xrange
 
 >>> axhline(y=1)
 
- * draw a default hline at y=.5 that spans the the middle half of
+ * draw a default hline at *y* = .5 that spans the the middle half of
 the xrange
 
 >>> axhline(y=.5, xmin=0.25, xmax=0.75)
 
- Valid kwargs are Line2D properties
+ Valid kwargs are :class:`~matplotlib.lines.Line2D` properties:
+
 %(Line2D)s
 """
 
@@ -2603,30 +2612,33 @@
 
 Axis Vertical Line
 
- Draw a vertical line at x from ymin to ymax. With the default values
- of ymin=0 and ymax=1, this line will always span the vertical extent
- of the axes, regardless of the xlim settings, even if you change them,
- eg with the xlim command. That is, the vertical extent is in axes
- coords: 0=bottom, 0.5=middle, 1.0=top but the x location is in data
- coordinates.
+ Draw a vertical line at *x* from *ymin* to *ymax*. With the
+ default values of *ymin* = 0 and *ymax* = 1, this line will
+ always span the vertical extent of the axes, regardless of the
+ xlim settings, even if you change them, eg. with the
+ :meth:`set_xlim` command. That is, the vertical extent is in
+ axes coords: 0=bottom, 0.5=middle, 1.0=top but the *x* location
+ is in data coordinates.
 
- Return value is the Line2D instance. kwargs are the same as
- kwargs to plot, and can be used to control the line properties. Eg
+ Return value is the :class:`~matplotlib.lines.Line2D`
+ instance. kwargs are the same as kwargs to plot, and can be
+ used to control the line properties. Eg.,
 
- * draw a thick red vline at x=0 that spans the yrange
+ * draw a thick red vline at *x* = 0 that spans the yrange
 
 >>> axvline(linewidth=4, color='r')
 
- * draw a default vline at x=1 that spans the yrange
+ * draw a default vline at *x* = 1 that spans the yrange
 
 >>> axvline(x=1)
 
- * draw a default vline at x=.5 that spans the the middle half of
+ * draw a default vline at *x* = .5 that spans the the middle half of
 the yrange
 
 >>> axvline(x=.5, ymin=0.25, ymax=0.75)
 
- Valid kwargs are Line2D properties
+ Valid kwargs are :class:`~matplotlib.lines.Line2D` properties:
+
 %(Line2D)s
 """
 
@@ -2648,26 +2660,31 @@
 
 axhspan(ymin, ymax, xmin=0, xmax=1, **kwargs)
 
- Axis Horizontal Span. ycoords are in data units and x
- coords are in axes (relative 0-1) units
+ Axis Horizontal Span.
 
- Draw a horizontal span (regtangle) from ymin to ymax. With the
- default values of xmin=0 and xmax=1, this always span the xrange,
- regardless of the xlim settings, even if you change them, eg with the
- xlim command. That is, the horizontal extent is in axes coords:
- 0=left, 0.5=middle, 1.0=right but the y location is in data
+ *y* coords are in data units and *x* coords are in axes (relative
+ 0-1) units.
+
+ Draw a horizontal span (rectangle) from *ymin* to *ymax*.
+ With the default values of *xmin* = 0 and *xmax* = 1, this
+ always span the xrange, regardless of the xlim settings, even
+ if you change them, eg. with the :meth:`set_xlim` command.
+ That is, the horizontal extent is in axes coords: 0=left,
+ 0.5=middle, 1.0=right but the *y* location is in data
 coordinates.
 
- Return value is the patches.Polygon instance.
+ Return value is a :class:`matplotlib.patches.Polygon`
+ instance.
 
 Examples:
 
- * draw a gray rectangle from y=0.25-0.75 that spans the horizontal
- extent of the axes
+ * draw a gray rectangle from *y* = 0.25-0.75 that spans the
+ horizontal extent of the axes
 
 >>> axhspan(0.25, 0.75, facecolor='0.5', alpha=0.5)
 
- Valid kwargs are Polygon properties
+ Valid kwargs are :class:`~matplotlib.patches.Polygon` properties:
+
 %(Polygon)s
 """
 # convert y axis units
@@ -2686,17 +2703,21 @@
 
 axvspan(xmin, xmax, ymin=0, ymax=1, **kwargs)
 
- Axis Vertical Span. xcoords are in data units and y coords
- are in axes (relative 0-1) units
+ Axis Vertical Span.
 
- Draw a vertical span (regtangle) from xmin to xmax. With the default
- values of ymin=0 and ymax=1, this always span the yrange, regardless
- of the ylim settings, even if you change them, eg with the ylim
- command. That is, the vertical extent is in axes coords: 0=bottom,
- 0.5=middle, 1.0=top but the y location is in data coordinates.
+ *x* coords are in data units and *y* coords are in axes (relative
+ 0-1) units.
 
- return value is the patches.Polygon instance.
+ Draw a vertical span (rectangle) from *xmin* to *xmax*. With
+ the default values of *ymin* = 0 and *ymax* = 1, this always
+ span the yrange, regardless of the ylim settings, even if you
+ change them, eg. with the :meth:`set_ylim` command. That is,
+ the vertical extent is in axes coords: 0=bottom, 0.5=middle,
+ 1.0=top but the *y* location is in data coordinates.
 
+ Return value is the :class:`matplotlib.patches.Polygon`
+ instance.
+
 Examples:
 
 * draw a vertical green translucent rectangle from x=1.25 to 1.55 that
@@ -2704,7 +2725,9 @@
 
 >>> axvspan(1.25, 1.55, facecolor='g', alpha=0.5)
 
- Valid kwargs are Polygon properties:
+ Valid kwargs are :class:`~matplotlib.patches.Polygon`
+ properties:
+
 %(Polygon)s
 """
 # convert x axis units
@@ -2725,27 +2748,28 @@
 
 hlines(y, xmin, xmax, colors='k', linestyle='solid', **kwargs)
 
- plot horizontal lines at each y from xmin to xmax.
+ Plot horizontal lines at each *y* from *xmin* to *xmax*.
 
- Returns the LineCollection that was added
+ Returns the :class:`~matplotlib.collections.LineCollection`
+ that was added.
 
 Required arguments:
 
- y:
+ *y*:
 a 1-D numpy array or iterable.
 
- xmin and xmax:
- can be scalars or len(x) numpy arrays. If they are scalars, then
- the respective values are constant, else the widths of the lines
- are determined by xmin and xmax
+ *xmin* and *xmax*:
+ can be scalars or ``len(x)`` numpy arrays. If they are
+ scalars, then the respective values are constant, else the
+ widths of the lines are determined by *xmin* and *xmax*.
 
 Optional keyword arguments:
 
- colors:
+ *colors*:
 a line collections color argument, either a single color
- or a len(y) list of colors
+ or a ``len(y)`` list of colors
 
- linestyle:
+ *linestyle*:
 [ 'solid' | 'dashed' | 'dashdot' | 'dotted' ]
 
 """
@@ -2800,20 +2824,21 @@
 
 vlines(x, ymin, ymax, color='k')
 
- Plot vertical lines at each x from ymin to ymax. ymin or ymax can be
- scalars or len(x) numpy arrays. If they are scalars, then the
- respective values are constant, else the heights of the lines are
- determined by ymin and ymax
+ Plot vertical lines at each *x* from *ymin* to *ymax*. *ymin*
+ or *ymax* can be scalars or len(*x*) numpy arrays. If they are
+ scalars, then the respective values are constant, else the
+ heights of the lines are determined by *ymin* and *ymax*.
 
+ *colors* is a line collections color args, either a single color
+ or a len(*x*) list of colors
 
- colors is a line collections color args, either a single color
- or a len(x) list of colors
+ *linestyle* is one of [ 'solid' | 'dashed' | 'dashdot' | 'dotted' ]
 
- linestyle is one of [ 'solid' | 'dashed' | 'dashdot' | 'dotted' ]
+ Returns the :class:`matplotlib.collections.LineCollection`
+ that was added.
 
- Returns the collections.LineCollection that was added
+ kwargs are :class:`~matplotlib.collections.LineCollection` properties:
 
- kwargs are collections.LineCollection properties:
 %(LineCollection)s
 """
 
@@ -2870,19 +2895,22 @@
 #### Basic plotting
 def plot(self, *args, **kwargs):
 """
- Plot lines and/or markers to the Axes. ``*args`` is a variable length
- argument, allowing for multiple *x*, *y* pairs with an optional format
- string. For example, each of the following is legal::
+ Plot lines and/or markers to the
+ :class:`~matplotlib.axes.Axes`. *args* is a variable length
+ argument, allowing for multiple *x*, *y* pairs with an
+ optional format string. For example, each of the following is
+ legal::
 
 plot(x, y) # plot x and y using the default line style and color
 plot(x, y, 'bo') # plot x and y using blue circle markers
 plot(y) # plot y using x as index array 0..N-1
 plot(y, 'r+') # ditto, but with red plusses
 
- If ``x`` and/or ``y`` is 2-dimensional, then the corresponding columns
+ If *x* and/or *y* is 2-dimensional, then the corresponding columns
 will be plotted.
 
- An arbitrary number of ``x``, ``y``, ``fmt`` groups can be specified, as in::
+ An arbitrary number of *x*, *y*, *fmt* groups can be
+ specified, as in::
 
 a.plot(x1, y1, 'g^', x2, y2, 'g-')
 
@@ -2929,16 +2957,16 @@
 w # white
 
 In addition, you can specify colors in many weird and
- wonderful ways, including full names (``'green'``), hex strings
- (``'#008000'``), RGB or RGBA tuples (``(0,1,0,1)``) or grayscale
- intensities as a string (``'0.8'``). Of these, the string
- specifications can be used in place of a ``fmt`` group, but the
- tuple forms can be used only as ``kwargs``.
+ wonderful ways, including full names (``'green'``), hex
+ strings (``'#008000'``), RGB or RGBA tuples (``(0,1,0,1)``) or
+ grayscale intensities as a string (``'0.8'``). Of these, the
+ string specifications can be used in place of a ``fmt`` group,
+ but the tuple forms can be used only as ``kwargs``.
 
 Line styles and colors are combined in a single format string, as in
 ``'bo'`` for blue circles.
 
- The ``**kwargs`` can be used to set line properties (any property that has
+ The *kwargs* can be used to set line properties (any property that has
 a ``set_*`` method). You can use this to set a line label (for auto
 legends), linewidth, anitialising, marker face color, etc. Here is an
 example::
@@ -2948,19 +2976,21 @@
 axis([0, 4, 0, 10])
 legend()
 
- If you make multiple lines with one plot command, the ``kwargs`` apply
- to all those lines, e.g.::
+ If you make multiple lines with one plot command, the kwargs
+ apply to all those lines, e.g.::
 
 plot(x1, y1, x2, y2, antialised=False)
 
 Neither line will be antialiased.
 
- The kwargs are Line2D properties:
+ The kwargs are :class:`~matplotlib.lines.Line2D` properties:
+
 %(Line2D)s
 
- kwargs ``scalex`` and ``scaley``, if defined, are passed on to
- :meth:`autoscale_view` to determine whether the *x* and *y* axes
- are autoscaled; the default is ``True``.
+ kwargs *scalex* and *scaley*, if defined, are passed on to
+ :meth:`~matplotlib.axes.Axes.autoscale_view` to determine
+ whether the *x* and *y* axes are autoscaled; the default is
+ *True*.
 """
 scalex = kwargs.pop( 'scalex', True)
 scaley = kwargs.pop( 'scaley', True)
@@ -2985,36 +3015,48 @@
 
 plot_date(x, y, fmt='bo', tz=None, xdate=True, ydate=False, **kwargs)
 
- Similar to the plot() command, except the x or y (or both) data
- is considered to be dates, and the axis is labeled accordingly.
+ Similar to the :func:`~matplotlib.pyplot.plot` command, except
+ the *x* or *y* (or both) data is considered to be dates, and the
+ axis is labeled accordingly.
 
- x and/or y can be a sequence of dates represented as float days since
+ *x* and/or *y* can be a sequence of dates represented as float days since
 0001年01月01日 UTC.
 
- See dates for helper functions date2num, num2date
- and drange for help on creating the required floating point dates
+ See :mod:`~matplotlib.dates` for helper functions
+ :func:`~matplotlib.dates.date2num`,
+ :func:`~matplotlib.dates.num2date` and
+ :func:`~matplotlib.dates.drange` for help on creating the
+ required floating point dates.
 
 Keyword arguments:
 
- fmt: string
+ *fmt*: string
 The plot format string.
- tz: [ None | timezone string ]
- The time zone to use in labeling dates. If None, defaults to rc
+
+ *tz*: [ None | timezone string ]
+ The time zone to use in labeling dates. If *None*, defaults to rc
 value.
- xdate: [ True | False ]
- If True, the x-axis will be labeled with dates.
- ydate: [ False | True ]
- If True, the y-axis will be labeled with dates.
 
+ *xdate*: [ True | False ]
+ If *True*, the *x*-axis will be labeled with dates.
+
+ *ydate*: [ False | True ]
+ If *True*, the *y*-axis will be labeled with dates.
+
 Note if you are using custom date tickers and formatters, it
 may be necessary to set the formatters/locators after the call
- to plot_date since plot_date will set the default tick locator
- to ticker.AutoDateLocator (if the tick locator is not already set to
- a ticker.DateLocator instance) and the default tick formatter to
- AutoDateFormatter (if the tick formatter is not already set to
- a DateFormatter instance).
+ to :meth:`plot_date` since :meth:`plot_date` will set the
+ default tick locator to
+ :class:`matplotlib.ticker.AutoDateLocator` (if the tick
+ locator is not already set to a
+ :class:`matplotlib.ticker.DateLocator` instance) and the
+ default tick formatter to
+ :class:`matplotlib.ticker.AutoDateFormatter` (if the tick
+ formatter is not already set to a
+ :class:`matplotlib.ticker.DateFormatter` instance).
 
- Valid kwargs are Line2D properties:
+ Valid kwargs are :class:`~matplotlib.lines.Line2D` properties:
+
 %(Line2D)s
 
 """
@@ -3040,22 +3082,27 @@
 
 loglog(*args, **kwargs)
 
- Make a plot with log scaling on the x and y axis. The args to loglog
- are the same as the args to plot. See plot for more info.
+ Make a plot with log scaling on the *x* and *y* axis.
 
- loglog supports all the keyword arguments of plot and
- Axes.set_xscale/Axes.set_yscale.
+ :func:`~matplotlib.pyplot.loglog` supports all the keyword
+ arguments of :func:`~matplotlib.pyplot.plot` and
+ :meth:`matplotlib.axes.Axes.set_xscale`/:meth:`matplotlib.axes.Axes.set_yscale`.
 
 Notable keyword arguments:
 
- basex/basey: scalar > 1
- base of the x/y logarithm
- subsx/subsy: [ None | sequence ]
- the location of the minor x/yticks; None defaults to
- autosubs, which depend on the number of decades in the
- plot; see set_xscale/set_yscale for details
+ *basex*/*basey*: scalar > 1
+ base of the *x*/*y* logarithm
 
- The remaining valid kwargs are Line2D properties:
+ *subsx*/*subsy*: [ None | sequence ]
+ the location of the minor *x*/*y* ticks; *None* defaults
+ to autosubs, which depend on the number of decades in the
+ plot; see
+ :meth:`matplotlib.axes.Axes.set_xscale`/:meth:`matplotlib.axes.Axes.set_yscale`
+ for details
+
+ The remaining valid kwargs are
+ :class:`~matplotlib.lines.Line2D` properties:
+
 %(Line2D)s
 """
 if not self._hold: self.cla()
@@ -3084,23 +3131,26 @@
 
 semilogx(*args, **kwargs)
 
- Make a plot with log scaling on the x axis. The args to
- semilogx are the same as the args to plot. See plot for
- more info.
+ Make a plot with log scaling on the *x* axis.
 
- semilogx supports all the keyword arguments of plot and
- Axes.set_xscale.
+ :func:`semilogx` supports all the keyword arguments of
+ :func:`~matplotlib.pyplot.plot` and
+ :meth:`matplotlib.axes.Axes.set_xscale`.
 
 Notable keyword arguments:
 
- basex: scalar > 1
- base of the x logarithm
- subsx: [ None | sequence ]
- the location of the minor xticks; None defaults to
+ *basex*: scalar > 1
+ base of the *x* logarithm
+
+ *subsx*: [ None | sequence ]
+ The location of the minor xticks; *None* defaults to
 autosubs, which depend on the number of decades in the
- plot; see set_xscale for details
+ plot; see :meth:`~matplotlib.axes.Axes.set_xscale` for
+ details.
 
- The remaining valid kwargs are Line2D properties:
+ The remaining valid kwargs are
+ :class:`~matplotlib.lines.Line2D` properties:
+
 %(Line2D)s
 """
 if not self._hold: self.cla()
@@ -3122,23 +3172,26 @@
 
 semilogy(*args, **kwargs)
 
- Make a plot with log scaling on the y axis. The args to
- semilogy are the same as the args to plot. See plot for
- more info.
+ Make a plot with log scaling on the *y* axis.
 
- semilogy supports all the keyword arguments of plot and
- Axes.set_yscale.
+ :func:`semilogy` supports all the keyword arguments of
+ :func:`~matplotlib.pylab.plot` and
+ :meth:`matplotlib.axes.Axes.set_yscale`.
 
 Notable keyword arguments:
 
- basey: scalar > 1
- base of the y logarithm
- subsy: [ None | sequence ]
- the location of the minor yticks; None defaults to
+ *basey*: scalar > 1
+ Base of the *y* logarithm
+
+ *subsy*: [ None | sequence ]
+ The location of the minor yticks; *None* defaults to
 autosubs, which depend on the number of decades in the
- plot; see set_yscale for details
+ plot; see :meth:`~matplotlib.axes.Axes.set_yscale` for
+ details.
 
- The remaining valid kwargs are Line2D properties:
+ The remaining valid kwargs are
+ :class:`~matplotlib.lines.Line2D` properties:
+
 %(Line2D)s
 """
 if not self._hold: self.cla()
@@ -3161,33 +3214,47 @@
 acorr(x, normed=False, detrend=mlab.detrend_none, usevlines=False,
 maxlags=None, **kwargs)
 
- Plot the autocorrelation of x. If normed=True, normalize the
- data but the autocorrelation at 0-th lag. x is detrended by
- the detrend callable (default no normalization.
+ Plot the autocorrelation of *x*. If *normed* = *True*,
+ normalize the data but the autocorrelation at 0-th lag. *x* is
+ detrended by the *detrend* callable (default no normalization).
 
- data are plotted as ``plot(lags, c, **kwargs)``
+ Data are plotted as ``plot(lags, c, **kwargs)``
 
- return value is lags, c, line where lags are a length
- 2*maxlags+1 lag vector, c is the 2*maxlags+1 auto correlation
- vector, and line is a Line2D instance returned by plot. The
- default linestyle is None and the default marker is 'o',
- though these can be overridden with keyword args. The cross
- correlation is performed with numpy correlate with
- mode=2.
+ Return value is a tuple (*lags*, *c*, *line*) where:
 
- If usevlines is True, Axes.vlines rather than Axes.plot is used
- to draw vertical lines from the origin to the acorr.
- Otherwise the plotstyle is determined by the kwargs, which are
- Line2D properties. If usevlines, the return value is lags, c,
- linecol, b where linecol is the collections.LineCollection and b is the x-axis
+ - *lags* are a length 2*maxlags+1 lag vector
 
- if usevlines=True, kwargs are passed onto Axes.vlines
- if usevlines=False, kwargs are passed onto Axes.plot
+ - *c* is the 2*maxlags+1 auto correlation vector
 
- maxlags is a positive integer detailing the number of lags to show.
- The default value of None will return all (2*len(x)-1) lags.
+ - *line* is a :class:`~matplotlib.lines.Line2D` instance
+ returned by :meth:`plot`
 
- See the respective function for documentation on valid kwargs
+ The default *linestyle* is None and the default *marker* is
+ ``'o'``, though these can be overridden with keyword args.
+ The cross correlation is performed with :func:`numpy.correlate` with
+ *mode* = 2.
+
+ If *usevlines* is *True*:
+
+ :meth:`~matplotlib.axes.Axes.vlines` rather than
+ :meth:`~matplotlib.axes.Axes.plot` is used to draw
+ vertical lines from the origin to the acorr. Otherwise,
+ the plot style is determined by the kwargs, which are
+ :class:`~matplotlib.lines.Line2D` properties. The return
+ value is a tuple (*lags*, *c*, *linecol*, *b*) where
+
+ - *linecol* is the
+ :class:`~matplotlib.collections.LineCollection`
+
+ - *b* is the *x*-axis.
+
+ *maxlags* is a positive integer detailing the number of lags
+ to show. The default value of *None* will return all
+ ``(2*len(x)-1)`` lags.
+
+ See the respective :meth:`~matplotlib.axes.Axes.plot` or
+ :meth:`~matplotlib.axes.Axes.vlines` functions for
+ documentation on valid kwargs.
 """
 return self.xcorr(x, x, **kwargs)
 acorr.__doc__ = cbook.dedent(acorr.__doc__) % martist.kwdocd
@@ -3200,35 +3267,42 @@
 xcorr(x, y, normed=False, detrend=mlab.detrend_none,
 usevlines=False, **kwargs):
 
- Plot the cross correlation between x and y. If normed=True,
- normalize the data but the cross correlation at 0-th lag. x
- and y are detrended by the detrend callable (default no
- normalization. x and y must be equal length
+ Plot the cross correlation between *x* and *y*. If *normed* =
+ *True*, normalize the data but the cross correlation at 0-th
+ lag. *x* and y are detrended by the *detrend* callable
+ (default no normalization). *x* and *y* must be equal length.
 
- data are plotted as ``plot(lags, c, **kwargs)``
+ Data are plotted as ``plot(lags, c, **kwargs)``
 
- return value is lags, c, line where lags are a length
- ``2*maxlags+1`` lag vector, c is the ``2*maxlags+1`` auto correlation
- vector, and line is a Line2D instance returned by plot. The
- default linestyle is None and the default marker is 'o',
- though these can be overridden with keyword args. The cross
- correlation is performed with numpy correlate with
- mode=2.
+ Return value is a tuple (*lags*, *c*, *line*) where:
 
- If usevlines is True, Axes.vlines rather than Axes.plot is used
- to draw vertical lines from the origin to the acorr.
- Otherwise the plotstyle is determined by the kwargs, which are
- Line2D properties. If usevlines, the return value is lags, c,
- linecol, b where linecol is the collections.LineCollection and b is the
- x-axis
+ - *lags* are a length ``2*maxlags+1`` lag vector
 
- if ``usevlines=True``, kwargs are passed onto Axes.vlines
- if ``usevlines=False``, kwargs are passed onto Axes.plot
+ - *c* is the ``2*maxlags+1`` auto correlation vector
 
- maxlags is a positive integer detailing the number of lags to show.
- The default value of None will return all ``(2*len(x)-1)`` lags.
+ - *line* is a :class:`~matplotlib.lines.Line2D` instance
+ returned by :func:`~matplotlib.pyplot.plot`.
 
- See the respective function for documentation on valid kwargs
+ The default *linestyle* is *None* and the default *marker* is
+ 'o', though these can be overridden with keyword args. The
+ cross correlation is performed with :func:`numpy.correlate`
+ with *mode* = 2.
+
+ If *usevlines* is *True*:
+
+ :func:`~matplotlib.pyplot.vlines`
+ rather than :func:`~matplotlib.pyplot.plot` is used to draw
+ vertical lines from the origin to the xcorr. Otherwise the
+ plotstyle is determined by the kwargs, which are
+ :class:`~matplotlib.lines.Line2D` properties.
+
+ The return value is a tuple (*lags*, *c*, *linecol*, *b*)
+ where *linecol* is the
+ :class:`matplotlib.collections.LineCollection` instance and
+ *b* is the *x*-axis.
+
+ *maxlags* is a positive integer detailing the number of lags to show.
+ The default value of *None* will return all ``(2*len(x)-1)`` lags.
 """
 
 Nx = len(x)
@@ -3269,20 +3343,27 @@
 
 legend(*args, **kwargs)
 
- Place a legend on the current axes at location loc. Labels are a
- sequence of strings and loc can be a string or an integer specifying
- the legend location
+ Place a legend on the current axes at location *loc*. Labels are a
+ sequence of strings and *loc* can be a string or an integer specifying
+ the legend location.
 
 To make a legend with existing lines::
 
 legend()
 
- legend by itself will try and build a legend using the label
+ :meth:`legend` by itself will try and build a legend using the label
 property of the lines/patches/collections. You can set the label of
- a line by doing plot(x, y, label='my data') or line.set_label('my
- data'). If label is set to '_nolegend_', the item will not be shown
- in legend.
+ a line by doing::
 
+ plot(x, y, label='my data')
+
+ or::
+
+ line.set_label('my data').
+
+ If label is set to '_nolegend_', the item will not be shown in
+ legend.
+
 To automatically generate the legend from labels::
 
 legend( ('label1', 'label2', 'label3') )
@@ -3325,32 +3406,41 @@
 
 Keyword arguments:
 
- isaxes: [ True | False ]
+ *isaxes*: [ True | False ]
 Indicates that this is an axes legend
- numpoints: integer
+
+ *numpoints*: integer
 The number of points in the legend line, default is 4
- prop: [ None | FontProperties ]
- A FontProperties instance, or None to use rc settings.
- see :class:`~matplotlib.font_manager.FontProperties`
- pad: [ None | scalar ]
+
+ *prop*: [ None | FontProperties ]
+ A :class:`matplotlib.font_manager.FontProperties`
+ instance, or *None* to use rc settings.
+
+ *pad*: [ None | scalar ]
 The fractional whitespace inside the legend border, between 0 and 1.
- If None, use rc settings
- markerscale: [ None | scalar ]
- The relative size of legend markers vs. original. If None, use rc
- settings
- shadow: [ None | False | True ]
- If True, draw a shadow behind legend. If None, use rc settings.
- labelsep: [ None | scalar ]
- The vertical space between the legend entries. If None, use rc
- settings
- handlelen: [ None | scalar ]
- The length of the legend lines. If None, use rc settings.
- handletextsep: [ None | scalar ]
- The space between the legend line and legend text. If None, use rc
+ If *None*, use rc settings.
+
+ *markerscale*: [ None | scalar ]
+ The relative size of legend markers vs. original. If *None*, use rc
 settings.
- axespad: [ None | scalar ]
- The border between the axes and legend edge. If None, use rc
+
+ *shadow*: [ None | False | True ]
+ If *True*, draw a shadow behind legend. If *None*, use rc settings.
+
+ *labelsep*: [ None | scalar ]
+ The vertical space between the legend entries. If *None*, use rc
 settings.
+
+ *handlelen*: [ None | scalar ]
+ The length of the legend lines. If *None*, use rc settings.
+
+ *handletextsep*: [ None | scalar ]
+ The space between the legend line and legend text. If *None*, use rc
+ settings.
+
+ *axespad*: [ None | scalar ]
+ The border between the axes and legend edge. If *None*, use rc
+ settings.
 """
 
 def get_handles():
@@ -3409,21 +3499,21 @@
 
 step(x, y, *args, **kwargs)
 
- x and y must be 1-D sequences, and it is assumed, but not checked,
- that x is uniformly increasing.
+ Make a step plot. Additional keyword args to :func:`step` are the same
+ as those for :func:`~matplotlib.pyplot.plot`.
 
+ *x* and *y* must be 1-D sequences, and it is assumed, but not checked,
+ that *x* is uniformly increasing.
+
 Keyword arguments:
 
- where: [ 'pre' | 'post' | 'mid' ]
- if 'pre', the interval from x[i] to x[i+1] has level y[i]
+ *where*: [ 'pre' | 'post' | 'mid' ]
+ If 'pre', the interval from x[i] to x[i+1] has level y[i]
 
- if 'post', that interval has level y[i+1]
+ If 'post', that interval has level y[i+1]
 
- if 'mid', the jumps in y occur half-way between the x-values.
-
- Make a step plot. Additional keyword args to step are the same
- as those for plot. See plot for more info.
-
+ If 'mid', the jumps in *y* occur half-way between the
+ *x*-values.
 '''
 
 where = kwargs.pop('where', 'pre')
@@ -3450,12 +3540,14 @@
 
 Make a bar plot with rectangles bounded by:
 
- left, left+width, bottom, bottom+height
+ *left*, *left* + *width*, *bottom*, *bottom* + *height*
 (left, right, bottom and top edges)
 
- left, height, width, and bottom can be either scalars or sequences
+ *left*, *height*, *width*, and *bottom* can be either scalars
+ or sequences
 
- Return value is a list of Rectangle patch instances
+ Return value is a list of
+ :class:`matplotlib.patches.Rectangle` instances.
 
 Required arguments:
 
@@ -3488,18 +3580,20 @@
 axis as-is; True sets it to log scale
 ============= ===================================================
 
- For vertical bars, align='edge' aligns bars by their left edges in
- left, while 'center' interprets these values as the x coordinates of
- the bar centers. For horizontal bars, 'edge' aligns bars by their
- bottom edges in bottom, while 'center' interprets these values as the
- y coordinates of the bar centers.
+ For vertical bars, *align* = 'edge' aligns bars by their left
+ edges in left, while *align* = 'center' interprets these
+ values as the *x* coordinates of the bar centers. For
+ horizontal bars, *align* = 'edge' aligns bars by their bottom
+ edges in bottom, while *align* = 'center' interprets these
+ values as the *y* coordinates of the bar centers.
 
- The optional arguments color, edgecolor, linewidth, xerr, and yerr can
- be either scalars or sequences of length equal to the number of bars.
- This enables you to use bar as the basis for stacked bar charts, or
- candlestick plots.
+ The optional arguments *color*, *edgecolor*, *linewidth*,
+ *xerr*, and *yerr* can be either scalars or sequences of
+ length equal to the number of bars. This enables you to use
+ bar as the basis for stacked bar charts, or candlestick plots.
 
 Other optional kwargs:
+
 %(Rectangle)s
 """
 if not self._hold: self.cla()
@@ -3698,12 +3792,14 @@
 
 Make a horizontal bar plot with rectangles bounded by:
 
- left, left+width, bottom, bottom+height
+ *left*, *left* + *width*, *bottom*, *bottom* + *height*
 (left, right, bottom and top edges)
 
- bottom, width, height, and left can be either scalars or sequences
+ *bottom*, *width*, *height*, and *left* can be either scalars
+ or sequences
 
- Return value is a list of Rectangle patch instances
+ Return value is a list of
+ :class:`matplotlib.patches.Rectangle` instances.
 
 Required arguments:
 
@@ -3735,16 +3831,18 @@
 axis as-is; True sets it to log scale
 ============= ===================================================
 
- Setting align='edge' aligns bars by their bottom edges in bottom,
- while 'center' interprets these values as the y coordinates of the bar
- centers.
+ Setting *align* = 'edge' aligns bars by their bottom edges in
+ bottom, while *align* = 'center' interprets these values as
+ the *y* coordinates of the bar centers.
 
- The optional arguments color, edgecolor, linewidth, xerr, and yerr can
- be either scalars or sequences of length equal to the number of bars.
- This enables you to use barh as the basis for stacked bar charts, or
- candlestick plots.
+ The optional arguments *color*, *edgecolor*, *linewidth*,
+ *xerr*, and *yerr* can be either scalars or sequences of
+ length equal to the number of bars. This enables you to use
+ barh as the basis for stacked bar charts, or candlestick
+ plots.
 
 other optional kwargs:
+
 %(Rectangle)s
 """
 
@@ -3760,8 +3858,8 @@
 
 broken_barh(self, xranges, yrange, **kwargs)
 
- A collection of horizontal bars spanning yrange with a sequence of
- xranges
+ A collection of horizontal bars spanning *yrange* with a sequence of
+ *xranges*.
 
 Required arguments:
 
@@ -3772,7 +3870,10 @@
 yrange sequence of (ymin, ywidth)
 ======== ==========================
 
- kwargs are collections.BrokenBarHCollection properties:
+ kwargs are
+ :class:`matplotlib.collections.BrokenBarHCollection`
+ properties:
+
 %(BrokenBarHCollection)s
 
 these can either be a single argument, ie::
@@ -3781,8 +3882,7 @@
 
 or a sequence of arguments for the various bars, ie::
 
- facecolors = 'black', 'red', 'green'
-
+ facecolors = ('black', 'red', 'green')
 """
 col = mcoll.BrokenBarHCollection(xranges, yrange, **kwargs)
 self.add_collection(col, autolim=True)
@@ -3798,15 +3898,17 @@
 
 stem(x, y, linefmt='b-', markerfmt='bo', basefmt='r-')
 
- A stem plot plots vertical lines (using linefmt) at each x location
- from the baseline to y, and places a marker there using markerfmt. A
- horizontal line at 0 is is plotted using basefmt
+ A stem plot plots vertical lines (using *linefmt*) at each *x*
+ location from the baseline to *y*, and places a marker there
+ using *markerfmt*. A horizontal line at 0 is is plotted using
+ *basefmt*.
 
- Return value is (markerline, stemlines, baseline) .
+ Return value is a tuple (*markerline*, *stemlines*,
+ *baseline*).
 
- See
- http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html
- for details and examples/stem_plot.py for a demo.
+ See `this document
+ <http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html>`_
+ for details and :file:`examples/pylab_examples/stem_plot.py` for a demo.
 """
 remember_hold=self._hold
 if not self._hold: self.cla()
@@ -3829,56 +3931,68 @@
 def pie(self, x, explode=None, labels=None, colors=None,
 autopct=None, pctdistance=0.6, shadow=False,
 labeldistance=1.1):
- """
+ r"""
 call signature::
 
 pie(x, explode=None, labels=None,
 colors=('b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'),
 autopct=None, pctdistance=0.6, labeldistance=1.1, shadow=False)
 
- Make a pie chart of array x. The fractional area of each wedge is
- given by x/sum(x). If sum(x)<=1, then the values of x give the
- fractional area directly and the array will not be normalized.
+ Make a pie chart of array *x*. The fractional area of each
+ wedge is given by x/sum(x). If sum(x) <= 1, then the values
+ of x give the fractional area directly and the array will not
+ be normalized.
 
 Keyword arguments:
 
- explode: [ None | len(x) sequence ]
- If not None, is a len(x) array which specifies the
+ *explode*: [ None | len(x) sequence ]
+ If not *None*, is a len(*x*) array which specifies the
 fraction of the radius with which to offset each wedge.
- colors: [ None | color sequence ]
+
+ *colors*: [ None | color sequence ]
 A sequence of matplotlib color args through which the pie chart
 will cycle.
- labels: [ None | len(x) sequence of strings ]
+
+ *labels*: [ None | len(x) sequence of strings ]
 A sequence of strings providing the labels for each wedge
- autopct: [ None | format string | format function ]
- If not None, is a string or function used to label the
+
+ *autopct*: [ None | format string | format function ]
+ If not *None*, is a string or function used to label the
 wedges with their numeric value. The label will be placed inside
- the wedge. If it is a format string, the label will be fmt%pct.
- If it is a function, it will be called
- pctdistance: scalar
- The ratio between the center of each pie slice and the start of the
- text generated by autopct. Ignored if autopct is None; default is
- 0.6.
- labeldistance: scalar
+ the wedge. If it is a format string, the label will be ``fmt%pct``.
+ If it is a function, it will be called.
+
+ *pctdistance*: scalar
+ The ratio between the center of each pie slice and the
+ start of the text generated by *autopct*. Ignored if
+ *autopct* is *None*; default is 0.6.
+
+ *labeldistance*: scalar
 The radial distance at which the pie labels are drawn
- shadow: [ False | True ]
+
+ *shadow*: [ False | True ]
 Draw a shadow beneath the pie.
 
 The pie chart will probably look best if the figure and axes are
- square. Eg::
+ square. Eg.::
 
 figure(figsize=(8,8))
 ax = axes([0.1, 0.1, 0.8, 0.8])
 
 Return value:
- If autopct is None, return a list of (patches, texts), where patches
- is a sequence of mpatches.Wedge instances and texts is a
- list of the label Text instnaces
+ If *autopct* is None, return the tuple (*patches*, *texts*):
 
- If autopct is not None, return (patches, texts, autotexts), where
- patches and texts are as above, and autotexts is a list of text
- instances for the numeric labels
+ - *patches* is a sequence of
+ :class:`matplotlib.patches.Wedge` instances
 
+ - *texts* is a list of the label
+ :class:`matplotlib.text.Text` instances.
+
+ If *autopct* is not *None*, return the tuple (*patches*,
+ *texts*, *autotexts*), where *patches* and *texts* are as
+ above, and *autotexts* is a list of
+ :class:`~matplotlib.text.Text` instances for the numeric
+ labels.
 """
 self.set_frame_on(False)
 
@@ -3975,40 +4089,47 @@
 barsabove=False, lolims=False, uplims=False,
 xlolims=False, xuplims=False)
 
- Plot x versus y with error deltas in yerr and xerr.
- Vertical errorbars are plotted if yerr is not None.
- Horizontal errorbars are plotted if xerr is not None.
+ Plot *x* versus *y* with error deltas in *yerr* and *xerr*.
+ Vertical errorbars are plotted if *yerr* is not *None*.
+ Horizontal errorbars are plotted if *xerr* is not *None*.
 
- x, y, xerr, and yerr can all be scalars, which plots a single error bar
- at x, y.
+ *x*, *y*, *xerr*, and *yerr* can all be scalars, which plots a
+ single error bar at *x*, *y*.
 
 Optional keyword arguments:
 
- xerr/yerr: [ scalar | N, Nx1, Nx2 array-like ]
+ *xerr*/*yerr*: [ scalar | N, Nx1, Nx2 array-like ]
 If a scalar number, len(N) array-like object, or an Nx1 array-like
 object, errorbars are drawn +/- value.
 
 If a rank-1, Nx2 Numpy array, errorbars are drawn at -column1 and
 +column2
- fmt: '-'
- The plot format symbol for y. If fmt is None, just plot the
+
+ *fmt*: '-'
+ The plot format symbol for *y*. If *fmt* is *None*, just plot the
 errorbars with no line symbols. This can be useful for creating a
 bar plot with errorbars.
- ecolor: [ None | mpl color ]
+
+ *ecolor*: [ None | mpl color ]
 a matplotlib color arg which gives the color the errorbar lines; if
- None, use the marker color.
- elinewidth: scalar
- the linewidth of the errorbar lines. If None, use the linewidth.
- capsize: scalar
+ *None*, use the marker color.
+
+ *elinewidth*: scalar
+ the linewidth of the errorbar lines. If *None*, use the linewidth.
+
+ *capsize*: scalar
 the size of the error bar caps in points
- barsabove: [ True | False ]
- if True, will plot the errorbars above the plot symbols. Default is
- below.
- lolims/uplims/xlolims/xuplims: [ False | True ]
- These arguments can be used to indicate that a value gives only
- upper/lower limits. In that case a caret symbol is used to indicate
- this. lims-arguments may be of the same type as xerr and yerr.
 
+ *barsabove*: [ True | False ]
+ if *True*, will plot the errorbars above the plot
+ symbols. Default is below.
+
+ *lolims*/*uplims*/*xlolims*/*xuplims*: [ False | True ]
+ These arguments can be used to indicate that a value gives
+ only upper/lower limits. In that case a caret symbol is
+ used to indicate this. lims-arguments may be of the same
+ type as *xerr* and *yerr*.
+
 All other keyword arguments are passed on to the plot command for the
 markers, so you can add additional key=value pairs to control the
 errorbar markers. For example, this code makes big red squares with
@@ -4018,16 +4139,20 @@
 errorbar(x, y, yerr, marker='s',
 mfc='red', mec='green', ms=20, mew=4)
 
- where mfc, mec, ms and mew are aliases for the longer property names,
- markerfacecolor, markeredgecolor, markersize and markeredgewith.
+ where *mfc*, *mec*, *ms* and *mew* are aliases for the longer
+ property names, *markerfacecolor*, *markeredgecolor*, *markersize*
+ and *markeredgewith*.
 
 valid kwargs for the marker properties are
+
 %(Line2D)s
 
 Return value is a length 3 tuple. The first element is the
- Line2D instance for the y symbol lines. The second element is
- a list of error bar cap lines, the third element is a list of
- line collections for the horizontal and vertical error ranges
+ :class:`~matplotlib.lines.Line2D` instance for the *y* symbol
+ lines. The second element is a list of error bar cap lines,
+ the third element is a list of
+ :class:`~matplotlib.collections.LineCollection` instances for
+ the horizontal and vertical error ranges.
 """
 
 self._process_unit_info(xdata=x, ydata=y, kwargs=kwargs)
@@ -4196,38 +4321,38 @@
 boxplot(x, notch=0, sym='+', vert=1, whis=1.5,
 positions=None, widths=None)
 
- Make a box and whisker plot for each column of x or
- each vector in sequence x.
- The box extends from the lower to upper quartile values
- of the data, with a line at the median. The whiskers
- extend from the box to show the range of the data. Flier
- points are those past the end of the whiskers.
+ Make a box and whisker plot for each column of *x* or each
+ vector in sequence *x*. The box extends from the lower to
+ upper quartile values of the data, with a line at the median.
+ The whiskers extend from the box to show the range of the
+ data. Flier points are those past the end of the whiskers.
 
- ``notch = 0`` (default) produces a rectangular box plot.
- ``notch = 1`` will produce a notched box plot
+ - *notch* = 0 (default) produces a rectangular box plot.
+ - *notch* = 1 will produce a notched box plot
 
- sym (default 'b+') is the default symbol for flier points.
+ *sym* (default 'b+') is the default symbol for flier points.
 Enter an empty string ('') if you don't want to show fliers.
 
- ``vert = 1`` (default) makes the boxes vertical.
- ``vert = 0`` makes horizontal boxes. This seems goofy, but
- that's how Matlab did it.
+ - *vert* = 1 (default) makes the boxes vertical.
+ - *vert* = 0 makes horizontal boxes. This seems goofy, but
+ that's how Matlab did it.
 
- whis (default 1.5) defines the length of the whiskers as
+ *whis* (default 1.5) defines the length of the whiskers as
 a function of the inner quartile range. They extend to the
 most extreme data point within ( ``whis*(75%-25%)`` ) data range.
 
- positions (default 1,2,...,n) sets the horizontal positions of
+ *positions* (default 1,2,...,n) sets the horizontal positions of
 the boxes. The ticks and limits are automatically set to match
 the positions.
 
- widths is either a scalar or a vector and sets the width of
+ *widths* is either a scalar or a vector and sets the width of
 each box. The default is 0.5, or ``0.15*(distance between extreme
 positions)`` if that is smaller.
 
- x is an array or a sequence of vectors.
+ *x* is an array or a sequence of vectors.
 
- Returns a list of the lines added.
+ Returns a list of the :class:`matplotlib.lines.Line2D`
+ instances added.
 
 """
 if not self._hold: self.cla()
@@ -4382,24 +4507,26 @@
 vmin=None, vmax=None, alpha=1.0, linewidths=None,
 verts=None, **kwargs)
 
- Make a scatter plot of x versus y, where x, y are 1-D sequences
- of the same length, N.
+ Make a scatter plot of *x* versus *y*, where *x*, *y* are 1-D
+ sequences of the same length, *N*.
 
 Keyword arguments:
 
- s:
+ *s*:
 size in points^2. It is a scalar or an array of the same
- length as x and y.
- c:
- a color. c can be a single color format string, or a
- sequence of color specifications of length N, or a sequence
- of N numbers to be mapped to colors using the cmap and norm
- specified via kwargs (see below). Note that c should not be
- a single numeric RGB or RGBA sequence because that is
- indistinguishable from an array of values to be colormapped.
- c can be a 2-D array in which the rows are RGB or RGBA,
- however.
- marker:
+ length as *x* and *y*.
+
+ *c*:
+ a color. *c* can be a single color format string, or a
+ sequence of color specifications of length *N*, or a
+ sequence of *N* numbers to be mapped to colors using the
+ *cmap* and *norm* specified via kwargs (see below). Note
+ that *c* should not be a single numeric RGB or RGBA
+ sequence because that is indistinguishable from an array
+ of values to be colormapped. *c* can be a 2-D array in
+ which the rows are RGB or RGBA, however.
+
+ *marker*:
 can be on...
 
[truncated message content]

Revision: 5592
 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5592&view=rev
Author: jdh2358
Date: 2008年06月19日 05:16:50 -0700 (2008年6月19日)
Log Message:
-----------
reverted typo I accidentally introduced into mathtext.rst
Modified Paths:
--------------
 trunk/matplotlib/doc/users/mathtext.rst
Modified: trunk/matplotlib/doc/users/mathtext.rst
===================================================================
--- trunk/matplotlib/doc/users/mathtext.rst	2008年06月19日 12:15:20 UTC (rev 5591)
+++ trunk/matplotlib/doc/users/mathtext.rst	2008年06月19日 12:16:50 UTC (rev 5592)
@@ -4,7 +4,7 @@
 ================================
 
 You can use TeX markup in any matplotlib text string. Note that you
-do not need to have TeX installed, since matplotlib ships its own` TeX
+do not need to have TeX installed, since matplotlib ships its own TeX
 expression parser, layout engine and fonts. The layout engine is a
 fairly direct adaptation of the layout algorithms in Donald Knuth's
 TeX, so the quality is quite good (matplotlib also provides a
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

Revision: 5591
 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5591&view=rev
Author: jdh2358
Date: 2008年06月19日 05:15:20 -0700 (2008年6月19日)
Log Message:
-----------
added installing section to users guide
Modified Paths:
--------------
 trunk/matplotlib/doc/users/index.rst
 trunk/matplotlib/doc/users/mathtext.rst
 trunk/matplotlib/lib/matplotlib/lines.py
Modified: trunk/matplotlib/doc/users/index.rst
===================================================================
--- trunk/matplotlib/doc/users/index.rst	2008年06月18日 22:06:03 UTC (rev 5590)
+++ trunk/matplotlib/doc/users/index.rst	2008年06月19日 12:15:20 UTC (rev 5591)
@@ -13,6 +13,7 @@
 :maxdepth: 2
 
 intro.rst
+ installing.rst
 pyplot_tutorial.rst
 navigation_toolbar.rst
 customizing.rst
Modified: trunk/matplotlib/doc/users/mathtext.rst
===================================================================
--- trunk/matplotlib/doc/users/mathtext.rst	2008年06月18日 22:06:03 UTC (rev 5590)
+++ trunk/matplotlib/doc/users/mathtext.rst	2008年06月19日 12:15:20 UTC (rev 5591)
@@ -4,7 +4,7 @@
 ================================
 
 You can use TeX markup in any matplotlib text string. Note that you
-do not need to have TeX installed, since matplotlib ships its own TeX
+do not need to have TeX installed, since matplotlib ships its own` TeX
 expression parser, layout engine and fonts. The layout engine is a
 fairly direct adaptation of the layout algorithms in Donald Knuth's
 TeX, so the quality is quite good (matplotlib also provides a
Modified: trunk/matplotlib/lib/matplotlib/lines.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/lines.py	2008年06月18日 22:06:03 UTC (rev 5590)
+++ trunk/matplotlib/lib/matplotlib/lines.py	2008年06月19日 12:15:20 UTC (rev 5591)
@@ -837,7 +837,7 @@
 def _draw_thin_diamond(self, renderer, gc, path, path_trans):
 offset = renderer.points_to_pixels(self._markersize)
 transform = Affine2D().translate(-0.5, -0.5) \
- .rotate_deg(45).scale(offset * 0.6, offset)
+ .rot<ate_deg(45).scale(offset * 0.6, offset)
 rgbFace = self._get_rgb_face()
 renderer.draw_markers(gc, Path.unit_rectangle(), transform,
 path, path_trans, rgbFace)
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