Remove references to chaco.shell from the documentation

docs/source/index.rst

@@ -43,7 +43,6 @@ give a good overview of the capabilities of Chaco:
 
 * :ref:`Sample Plot Gallery <examples>`
 * :ref:`Tutorial: Interactive plotting with Chaco <tutorial>`
-* :ref:`Tutorial: Using Chaco from IPython <tutorial_ipython>`
 * Examples:
 
   - :ref:`Modeling Van del Waal's Equations <tutorial_van_der_waal>`

docs/source/user_manual/chaco_tutorial.rst

@@ -18,8 +18,8 @@ be used primarily by scientific programmers, and this tutorial requires only
 basic familiarity with Python.
 
 Knowledge of NumPy can be helpful for certain parts of the tutorial. Knowledge
-of GUI programming concepts such as widgets, windows, and events are helpful
-for the last portion of the tutorial, but it is not required.
+of GUI programming concepts such as widgets, windows, and events is helpful,
+but it is not required.
 
 This tutorial demonstrates using Chaco with Traits(UI), so knowledge of the
 `Traits User Manual <http://docs.enthought.com/traits/>`_ framework is also
@@ -100,57 +100,15 @@ drop-down menus (not show here), the user can change plot attributes like the
 colormap and the number of contour levels used in the center plot, as well as
 the actual function being plotted.
 
-
-Script-oriented plotting
-========================
-
-We distinguish between "static" plots and "interactive visualizations"
-because these different applications of a library affect the structure
-of how the library is written, as well as the code you write to use the
-library.
-
-Here is a simple example of the "script-oriented" approach for creating
-a static plot.  This is probably familiar to anyone who has used Gnuplot,
-MATLAB, or Matplotlib::
-
-    from numpy import linspace, pi, sin
-    from chaco.shell import *
-
-    x = linspace(-2*pi, 2*pi, 100)
-    y = sin(x)
-
-    plot(x, y, "r-")
-    title("First plot")
-    ytitle("sin(x)")
-    show()
-
-This creates this plot:
-
-.. image:: images/script_oriented.png
-    :height: 300pt
-
-The basic structure of this example is that we generate some data, then we call
-functions to plot the data and configure the plot. There is a global concept of
-"the active plot", and the functions do high-level manipulations on it. The
-generated plot is then usually saved to disk for inclusion in a journal article
-or presentation slides.
-
-Now, as it so happens, this particular example uses the `chaco.shell`
-script plotting package, so when you run this script, the plot that Chaco opens
-does have some basic interactivity. You can pan and zoom, and even move forwards
-and backwards through your zoom history. But ultimately it's a pretty static
-view into the data.
-
-
 .. _line_plot_example:
 
 Application-oriented plotting
 =============================
 
-The second approach to plotting can be thought of as "application-oriented", for
-lack of a better term. There is definitely a bit more code, and the plot
-initially doesn't look much different, but it sets us up to do more interesting
-things, as you will see later on::
+The main chaco approach to plotting can be thought of as
+"application-oriented", for lack of a better term. The code may appear a bit
+verbose given the simple plot it generates, but it sets us up to do more
+interesting things, as you will see later on::
 
     from numpy import linspace, sin
     from traits.api import HasTraits, Instance
@@ -183,7 +141,7 @@ things, as you will see later on::
         LinePlot().configure_traits()
 
 
-This produces a plot similar to the previous script-oriented code snippet:
+This produces the following plot:
 
 .. image:: images/first_plot.png
     :height: 300pt
@@ -1301,4 +1259,4 @@ trait editor and reusing an existing tool from the built-in set of tools.
 
 
 *This tutorial is based on the "Interactive plotting with Chaco" tutorial
-that was presented by Peter Wang at Scipy 2008*
+that was presented by Peter Wang at Scipy*

docs/source/user_manual/introduction.rst

@@ -35,14 +35,12 @@ of several of graphical back ends <embedding>`. Working at this level allows the
 maximum flexibility, but requires understanding
 :ref:`Chaco's basic elements <basic_elements>`.
 
-Chaco defines two abstraction layers that allow a more high-level (albeit
-less flexible) plotting experience. First, Chaco contains a
+Chaco defines an abstraction layer that allows a more high-level (albeit
+less flexible) plotting experience. Namely, Chaco contains a
 :class:`~chaco.plot.Plot` class that defines several methods that create a
 complete plot given one or more data sets. In other words,
 :class:`~chaco.plot.Plot` knows how to package data for the most common kinds
-of plots. Second, Chaco has a :mod:`shell` module that defines high-level
-plotting functions. This module allows using Chaco as an interactive plotting
-tool that will be familiar to users of matplotlib.
+of plots.
 
 .. _basic_elements: