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add .gitattributes and .gitignore, fix CRLF

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1 parent 1389499 commit 8bc1b79ae9345e0ab019a14ccf400c9e8bebbd2a @ddale ddale committed Feb 21, 2011
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+* text=auto
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@@ -0,0 +1,42 @@
+# Editor temporary/working/backup files #
+#########################################
+.#*
+[#]*#
+*~
+*$
+*.bak
+
+# Compiled source #
+###################
+*.a
+*.com
+*.class
+*.dll
+*.exe
+*.o
+*.py[ocd]
+*.so
+
+# Python files #
+################
+# setup.py working directory
+build
+# sphinx build directory
+doc/_build
+# setup.py dist directory
+dist
+# Egg metadata
+*.egg-info
+
+# OS generated files #
+######################
+.gdb_history
+.DS_Store?
+ehthumbs.db
+Icon?
+Thumbs.db
+
+# Things specific to this project #
+###################################
+lib/matplotlib/mpl-data/matplotlib.conf
+lib/matplotlib/mpl-data/matplotlibrc
@@ -1,134 +1,134 @@
-.. _adding-new-scales:
-
-***********************************************
-Adding new scales and projections to matplotlib
-***********************************************
-
-.. ::author Michael Droettboom
-
-Matplotlib supports the addition of custom procedures that transform
-the data before it is displayed.
-
-There is an important distinction between two kinds of
-transformations. Separable transformations, working on a single
-dimension, are called "scales", and non-separable transformations,
-that handle data in two or more dimensions at a time, are called
-"projections".
-
-From the user's perspective, the scale of a plot can be set with
-:meth:`~matplotlib.axes.Axes.set_xscale` and
-:meth:`~matplotlib.axes.Axes.set_xscale`. Projections can be chosen
-using the ``projection`` keyword argument to the
-:func:`~matplotlib.pylab.plot` or :func:`~matplotlib.pylab.subplot`
-functions, e.g.::
-
- plot(x, y, projection="custom")
-
-This document is intended for developers and advanced users who need
-to create new scales and projections for matplotlib. The necessary
-code for scales and projections can be included anywhere: directly
-within a plot script, in third-party code, or in the matplotlib source
-tree itself.
-
-.. _creating-new-scale:
-
-Creating a new scale
-====================
-
-Adding a new scale consists of defining a subclass of
-:class:`matplotlib.scale.ScaleBase`, that includes the following
-elements:
-
- - A transformation from data coordinates into display coordinates.
-
- - An inverse of that transformation. This is used, for example, to
- convert mouse positions from screen space back into data space.
-
- - A function to limit the range of the axis to acceptable values
- (``limit_range_for_scale()``). A log scale, for instance, would
- prevent the range from including values less than or equal to
- zero.
-
- - Locators (major and minor) that determine where to place ticks in
- the plot, and optionally, how to adjust the limits of the plot to
- some "good" values. Unlike ``limit_range_for_scale()``, which is
- always enforced, the range setting here is only used when
- automatically setting the range of the plot.
-
- - Formatters (major and minor) that specify how the tick labels
- should be drawn.
-
-Once the class is defined, it must be registered with matplotlib so
-that the user can select it.
-
-A full-fledged and heavily annotated example is in
-:file:`examples/api/custom_scale_example.py`. There are also some classes
-in :mod:`matplotlib.scale` that may be used as starting points.
-
-
-.. _creating-new-projection:
-
-Creating a new projection
-=========================
-
-Adding a new projection consists of defining a subclass of
-:class:`matplotlib.axes.Axes`, that includes the following elements:
-
- - A transformation from data coordinates into display coordinates.
-
- - An inverse of that transformation. This is used, for example, to
- convert mouse positions from screen space back into data space.
-
- - Transformations for the gridlines, ticks and ticklabels. Custom
- projections will often need to place these elements in special
- locations, and matplotlib has a facility to help with doing so.
-
- - Setting up default values (overriding
- :meth:`~matplotlib.axes.Axes.cla`), since the defaults for a
- rectilinear axes may not be appropriate.
-
- - Defining the shape of the axes, for example, an elliptical axes,
- that will be used to draw the background of the plot and for
- clipping any data elements.
-
- - Defining custom locators and formatters for the projection. For
- example, in a geographic projection, it may be more convenient to
- display the grid in degrees, even if the data is in radians.
-
- - Set up interactive panning and zooming. This is left as an
- "advanced" feature left to the reader, but there is an example of
- this for polar plots in :mod:`matplotlib.projections.polar`.
-
- - Any additional methods for additional convenience or features.
-
-Once the class is defined, it must be registered with matplotlib
-so that the user can select it.
-
-A full-fledged and heavily annotated example is in
-:file:`examples/api/custom_projection_example.py`. The polar plot
-functionality in :mod:`matplotlib.projections.polar` may also be of
-interest.
-
-API documentation
-=================
-
-matplotlib.scale
-----------------
-
-.. automodule:: matplotlib.scale
- :members:
- :show-inheritance:
-
-matplotlib.projections
-----------------------
-
-.. automodule:: matplotlib.projections
- :members:
- :show-inheritance:
-
-matplotlib.projections.polar
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-.. automodule:: matplotlib.projections.polar
- :members:
- :show-inheritance:
+.. _adding-new-scales:
+
+***********************************************
+Adding new scales and projections to matplotlib
+***********************************************
+
+.. ::author Michael Droettboom
+
+Matplotlib supports the addition of custom procedures that transform
+the data before it is displayed.
+
+There is an important distinction between two kinds of
+transformations. Separable transformations, working on a single
+dimension, are called "scales", and non-separable transformations,
+that handle data in two or more dimensions at a time, are called
+"projections".
+
+From the user's perspective, the scale of a plot can be set with
+:meth:`~matplotlib.axes.Axes.set_xscale` and
+:meth:`~matplotlib.axes.Axes.set_xscale`. Projections can be chosen
+using the ``projection`` keyword argument to the
+:func:`~matplotlib.pylab.plot` or :func:`~matplotlib.pylab.subplot`
+functions, e.g.::
+
+ plot(x, y, projection="custom")
+
+This document is intended for developers and advanced users who need
+to create new scales and projections for matplotlib. The necessary
+code for scales and projections can be included anywhere: directly
+within a plot script, in third-party code, or in the matplotlib source
+tree itself.
+
+.. _creating-new-scale:
+
+Creating a new scale
+====================
+
+Adding a new scale consists of defining a subclass of
+:class:`matplotlib.scale.ScaleBase`, that includes the following
+elements:
+
+ - A transformation from data coordinates into display coordinates.
+
+ - An inverse of that transformation. This is used, for example, to
+ convert mouse positions from screen space back into data space.
+
+ - A function to limit the range of the axis to acceptable values
+ (``limit_range_for_scale()``). A log scale, for instance, would
+ prevent the range from including values less than or equal to
+ zero.
+
+ - Locators (major and minor) that determine where to place ticks in
+ the plot, and optionally, how to adjust the limits of the plot to
+ some "good" values. Unlike ``limit_range_for_scale()``, which is
+ always enforced, the range setting here is only used when
+ automatically setting the range of the plot.
+
+ - Formatters (major and minor) that specify how the tick labels
+ should be drawn.
+
+Once the class is defined, it must be registered with matplotlib so
+that the user can select it.
+
+A full-fledged and heavily annotated example is in
+:file:`examples/api/custom_scale_example.py`. There are also some classes
+in :mod:`matplotlib.scale` that may be used as starting points.
+
+
+.. _creating-new-projection:
+
+Creating a new projection
+=========================
+
+Adding a new projection consists of defining a subclass of
+:class:`matplotlib.axes.Axes`, that includes the following elements:
+
+ - A transformation from data coordinates into display coordinates.
+
+ - An inverse of that transformation. This is used, for example, to
+ convert mouse positions from screen space back into data space.
+
+ - Transformations for the gridlines, ticks and ticklabels. Custom
+ projections will often need to place these elements in special
+ locations, and matplotlib has a facility to help with doing so.
+
+ - Setting up default values (overriding
+ :meth:`~matplotlib.axes.Axes.cla`), since the defaults for a
+ rectilinear axes may not be appropriate.
+
+ - Defining the shape of the axes, for example, an elliptical axes,
+ that will be used to draw the background of the plot and for
+ clipping any data elements.
+
+ - Defining custom locators and formatters for the projection. For
+ example, in a geographic projection, it may be more convenient to
+ display the grid in degrees, even if the data is in radians.
+
+ - Set up interactive panning and zooming. This is left as an
+ "advanced" feature left to the reader, but there is an example of
+ this for polar plots in :mod:`matplotlib.projections.polar`.
+
+ - Any additional methods for additional convenience or features.
+
+Once the class is defined, it must be registered with matplotlib
+so that the user can select it.
+
+A full-fledged and heavily annotated example is in
+:file:`examples/api/custom_projection_example.py`. The polar plot
+functionality in :mod:`matplotlib.projections.polar` may also be of
+interest.
+
+API documentation
+=================
+
+matplotlib.scale
+----------------
+
+.. automodule:: matplotlib.scale
+ :members:
+ :show-inheritance:
+
+matplotlib.projections
+----------------------
+
+.. automodule:: matplotlib.projections
+ :members:
+ :show-inheritance:
+
+matplotlib.projections.polar
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. automodule:: matplotlib.projections.polar
+ :members:
+ :show-inheritance:
@@ -1,31 +1,31 @@
-"""
-You can explicitly set which font family is picked up for a given font
-style (eg 'serif', 'sans-serif', or 'monospace').
-
-In the example below, we only allow one font family (Tahoma) for the
-san-serif font style. You the default family with the font.family rc
-param, eg::
-
- rcParams['font.family'] = 'sans-serif'
-
-and for the font.family you set a list of font styles to try to find
-in order::
-
- rcParams['font.sans-serif'] = ['Tahoma', 'Bitstream Vera Sans', 'Lucida Grande', 'Verdana']
-
-"""
-
-# -*- noplot -*-
-
-from matplotlib import rcParams
-rcParams['font.family'] = 'sans-serif'
-rcParams['font.sans-serif'] = ['Tahoma']
-import matplotlib.pyplot as plt
-
-fig = plt.figure()
-ax = fig.add_subplot(111)
-ax.plot([1,2,3], label='test')
-
-ax.legend()
-plt.show()
-
+"""
+You can explicitly set which font family is picked up for a given font
+style (eg 'serif', 'sans-serif', or 'monospace').
+
+In the example below, we only allow one font family (Tahoma) for the
+san-serif font style. You the default family with the font.family rc
+param, eg::
+
+ rcParams['font.family'] = 'sans-serif'
+
+and for the font.family you set a list of font styles to try to find
+in order::
+
+ rcParams['font.sans-serif'] = ['Tahoma', 'Bitstream Vera Sans', 'Lucida Grande', 'Verdana']
+
+"""
+
+# -*- noplot -*-
+
+from matplotlib import rcParams
+rcParams['font.family'] = 'sans-serif'
+rcParams['font.sans-serif'] = ['Tahoma']
+import matplotlib.pyplot as plt
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+ax.plot([1,2,3], label='test')
+
+ax.legend()
+plt.show()
+
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