[Scipysvn] r5258  in trunk/doc/source/tutorial: . examples
scipysvn@scip...
scipysvn@scip...
Sun Dec 14 08:05:57 CST 2008
Author: jarrod.millman
Date: 20081214 08:05:54 0600 (Sun, 14 Dec 2008)
New Revision: 5258
Modified:
trunk/doc/source/tutorial/examples/11
trunk/doc/source/tutorial/general.rst
trunk/doc/source/tutorial/index.rst
Log:
minor reorganization
Modified: trunk/doc/source/tutorial/examples/11
===================================================================
 trunk/doc/source/tutorial/examples/11 20081214 13:08:09 UTC (rev 5257)
+++ trunk/doc/source/tutorial/examples/11 20081214 14:05:54 UTC (rev 5258)
@@ 1,4 +1,4 @@
>>> info(optimize.fmin)
+>>> sp.info(optimize.fmin)
fmin(func, x0, args=(), xtol=0.0001, ftol=0.0001, maxiter=None, maxfun=None,
full_output=0, disp=1, retall=0, callback=None)
Modified: trunk/doc/source/tutorial/general.rst
===================================================================
 trunk/doc/source/tutorial/general.rst 20081214 13:08:09 UTC (rev 5257)
+++ trunk/doc/source/tutorial/general.rst 20081214 14:05:54 UTC (rev 5258)
@@ 1,58 +1,49 @@
General information
===================
+============
+Introduction
+============
Examples in this tutorial

+.. contents::
Throughout this tutorial it is assumed that the user
has imported all of the names defined in the SciPy toplevel namespace
using the command
+SciPy is a collection of mathematical algorithms and convenience
+functions built on the Numpy extension for Python. It adds
+significant power to the interactive Python session by exposing the
+user to highlevel commands and classes for the manipulation and
+visualization of data. With SciPy, an interactive Python session
+becomes a dataprocessing and systemprototyping environment rivaling
+sytems such as Matlab, IDL, Octave, RLab, and SciLab.
 >>> from scipy import *
+The additional power of using SciPy within Python, however, is that a
+powerful programming language is also available for use in developing
+sophisticated programs and specialized applications. Scientific
+applications written in SciPy benefit from the development of
+additional modules in numerous niche's of the software landscape by
+developers across the world. Everything from parallel programming to
+web and database subroutines and classes have been made available to
+the Python programmer. All of this power is available in addition to
+the mathematical libraries in SciPy.
Scipy subpackages need to be imported separately, for example
+This document provides a tutorial for the firsttime user of SciPy to
+help get started with some of the features available in this powerful
+package. It is assumed that the user has already installed the
+package. Some general Python facility is also assumed such as could be
+acquired by working through the Tutorial in the Python distribution.
+For further introductory help the user is directed to the Numpy
+documentation.
 >>> from scipy import linalg, optimize
+For brevity and convenience, we will often assume that the main
+packages (numpy, scipy, and matplotlib) have been imported as::
+ >>> import numpy as np
+ >>> import scipy as sp
+ >>> import matplotlib as mpl
+ >>> import matplotlib.pyplot as plt
Finding Documentation

+These are the import conventions that our community has adopted
+after discussion on public mailing lists. You will see these
+conventions used throughout NumPy and SciPy source code and
+documentation. While we obviously don't require you to follow
+these conventions in your own code, it is highly recommended.
Scipy and Numpy have HTML and PDF versions of their documentation
available at http://docs.scipy.org/, which currently details nearly
all available functionality. However, this documentation is still
workinprogress, and some parts may be incomplete or sparse.

Python also provides the facility of documentation strings. The
functions and classes available in SciPy use this method for online
documentation. There are two methods for reading these messages and
getting help. Python provides the command :func:`help` in the pydoc
module. Entering this command with no arguments (i.e. ``>>> help`` )
launches an interactive help session that allows searching through the
keywords and modules available to all of Python. Running the command
help with an object as the argument displays the calling signature,
and the documentation string of the object.

The pydoc method of help is sophisticated but uses a pager to display
the text. Sometimes this can interfere with the terminal you are
running the interactive session within. A scipyspecific help system
is also available under the command scipy.info. The signature and
documentation string for the object passed to the help command are
printed to standard output (or to a writeable object passed as the
third argument). The second keyword argument of "scipy.info" defines
the maximum width of the line for printing. If a module is passed as
the argument to help than a list of the functions and classes defined
in that module is printed. For example:

.. literalinclude:: examples/11

Another useful command is :func:`source`. When given a function
written in Python as an argument, it prints out a listing of the
source code for that function. This can be helpful in learning about
an algorithm or understanding exactly what a function is doing with
its arguments. Also don't forget about the Python command ``dir``
which can be used to look at the namespace of a module or package.

SciPy Organization

@@ 83,6 +74,10 @@
:mod:`weave` C/C++ integration
================== =====================================================================
+Scipy subpackages need to be imported separately, for example::
+
+ >>> from scipy import linalg, optimize
+
Because of their ubiquitousness, some of the functions in these
subpackages are also made available in the scipy namespace to ease
their use in interactive sessions and programs. In addition, many
@@ 90,3 +85,46 @@
toplevel of the :mod:`scipy` package. Before looking at the
subpackages individually, we will first look at some of these common
functions.
+
+Finding Documentation
+
+
+Scipy and Numpy have HTML and PDF versions of their documentation
+available at http://docs.scipy.org/, which currently details nearly
+all available functionality. However, this documentation is still
+workinprogress, and some parts may be incomplete or sparse. As
+we are a volunteer organization and depend on the community for
+growth, your participationeverything from providing feedback to
+improving the documentation and codeis welcome and actively
+encouraged.
+
+Python also provides the facility of documentation strings. The
+functions and classes available in SciPy use this method for online
+documentation. There are two methods for reading these messages and
+getting help. Python provides the command :func:`help` in the pydoc
+module. Entering this command with no arguments (i.e. ``>>> help`` )
+launches an interactive help session that allows searching through the
+keywords and modules available to all of Python. Running the command
+help with an object as the argument displays the calling signature,
+and the documentation string of the object.
+
+The pydoc method of help is sophisticated but uses a pager to display
+the text. Sometimes this can interfere with the terminal you are
+running the interactive session within. A scipyspecific help system
+is also available under the command ``sp.info``. The signature and
+documentation string for the object passed to the ``help`` command are
+printed to standard output (or to a writeable object passed as the
+third argument). The second keyword argument of ``sp.info`` defines
+the maximum width of the line for printing. If a module is passed as
+the argument to help than a list of the functions and classes defined
+in that module is printed. For example:
+
+.. literalinclude:: examples/11
+
+Another useful command is :func:`source`. When given a function
+written in Python as an argument, it prints out a listing of the
+source code for that function. This can be helpful in learning about
+an algorithm or understanding exactly what a function is doing with
+its arguments. Also don't forget about the Python command ``dir``
+which can be used to look at the namespace of a module or package.
+
Modified: trunk/doc/source/tutorial/index.rst
===================================================================
 trunk/doc/source/tutorial/index.rst 20081214 13:08:09 UTC (rev 5257)
+++ trunk/doc/source/tutorial/index.rst 20081214 14:05:54 UTC (rev 5258)
@@ 4,33 +4,6 @@
.. sectionauthor:: Travis E. Oliphant
SciPy is a collection of mathematical algorithms and convenience
functions built on the Numpy extension for Python. It adds
significant power to the interactive Python session by exposing the
user to highlevel commands and classes for the manipulation and
visualization of data. With SciPy, an interactive Python session
becomes a dataprocessing and systemprototyping environment rivaling
sytems such as Matlab, IDL, Octave, RLab, and SciLab.

The additional power of using SciPy within Python, however, is that a
powerful programming language is also available for use in developing
sophisticated programs and specialized applications. Scientific
applications written in SciPy benefit from the development of
additional modules in numerous niche's of the software landscape by
developers across the world. Everything from parallel programming to
web and database subroutines and classes have been made available to
the Python programmer. All of this power is available in addition to
the mathematical libraries in SciPy.

This document provides a tutorial for the firsttime user of SciPy to
help get started with some of the features available in this powerful
package. It is assumed that the user has already installed the
package. Some general Python facility is also assumed such as could be
acquired by working through the Tutorial in the Python distribution.
For further introductory help the user is directed to the Numpy
documentation.


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