Changes from the fourth to the fifth edition.
Substantial changes were introduced in the fourth edition, and the
fifth edition is primarily a consolidation of those changes. Many
typos have been corrected and many explanations and exercises have
been improved. The emphasis on unit tests and test functions,
especially in exercises, is stronger than in the previous edition.
Symbolic computation with the aid of SymPy is used to a larger extent
and integrated with numerical computing throughout the book. All
classes are now new-style (instead of old-style/classic as in previous
editions). Examples on Matplotlib do not use the pylab module
anymore, but pyplot and MATLAB-like syntax is still favored to ease
the transition between Python and MATLAB. The concept of closures is
more explicit than in earlier editions (see the new Section 7.1.7)
since this is a handy and popular construction much used in the
scientific Python community. We also discuss the difference between
Python 2 and 3 and demonstrate how to use the future module to write
code that runs under both versions.
The most substantial new material in the fifth edition appears toward
the end of Chapter 5 and regards high-performance computing, linear
algebra, and visualization of scalar and vector fields.
The numbering of sections and in particular exercises differs from
previous editions.
On Unix/Linux or Mac, download the tarfile book-examples-5th.tar.gz for the 5th edition and pack it out by
tar xvzf book-examples-5th.tar.gz
On Windows, download book-examples-5th.zip for the 4th edition and pack it out by
unzip book-examples-5th.zip
or double click on the file icon.
The result is a folder (directory)
tree src with subfolders containing
the program examples for different chapters in the book
(formulas, looplist, etc., as explained in the introduction to
each chapter).
An important change from the 4th edition is that the directory files
in the 4th edition is named dictstring in the 5th edition.
You can also directly access the latest version of the example files at GitHub, see the src directory (to download a file, click the Raw button on the right first to get the pure text file in the browser and then right-click to download). To copy the whole repository to your computer, run
git clone https://github.com/hplgit/scipro-primer.git
Here is a PDF file or an HTML file with an errata list for the 5th edition of the book. If you find any typo or error, please report it to the author.
There are several ways to access Python, either on your computer or in the cloud. Appendix H.1 in the book gives an overview of recommended technologies and how to use them to get the software you need for working with the book. Our primary recommendation is to install Anaconda - it suffices for the book. However, if you intend to do more advanced scientific computing in the future, we strongly recommend to use a virtual Ubuntu machine for all that work.
SciTools. The package SciTools is freqently referred to and used in the book. You may want to install SciTools directly from its Git version control repository. This makes it easy to upgrade the package at any time. SciTools is hosted at GitHub (note that the old repository at Googlecode only contains old versions - stay away from those!). Make sure you have the Git version control system on your computer (if not, googling for installation of Git brings you to simple procedures, depending on the platform you are on). Get the SciTools source code and install it by
git clone https://github.com/hplgit/scitools.git
cd scitools
sudo python setup.py install
Whenever you want to upgrade the package, just go to the scitools
folder and run the commands
git pull origin master
sudo python setup.py install
A simpler installation procedure applies pip:
pip install -e git+https://github.com/hplgit/scitools.git#egg=scitools --upgrade
Note that you have to rerun this command to install new versions of SciTools in the future.
If you have an Ubuntu installation, Python is already there. The minimum extra packages are installed by this command:
sudo apt-get install python-matplotlib python-scipy python-gnuplot gnuplot gnuplot-x11 python-scitools
The Gnuplot packages are optional (you can exclusively used Matplotlib instead).
A comprehensive installation with lots of useful packages can be
performed by a Bash script. Download this file (install_rich.sh) and run it by bash install_rich.sh.
There is a slide collection from lectures based on the latest edition of the book.
On Unix/Linux or Mac, download the tarfile book-examples-4th.tar.gz for the 4th edition and pack it out by
tar xvzf book-examples-4th.tar.gz
On Windows, download book-examples-4th.zip for the 4th edition and pack it out by
unzip book-examples-4th.zip
or double click on the file icon.
The result is a folder (directory)
tree src with subfolders containing
the program examples for different chapters in the book
(formulas, looplist, etc., as explained in the introduction to
each chapter).
You can also directly access the latest version of the example files at GitHub, see the src-4th directory (to download a file, click the Raw button on the right first to get the pure text file in the browser and then right-click to download). To copy the whole repository to your computer, run
git clone https://github.com/hplgit/scipro-primer.git
Here is a PDF file or an HTML file with an errata list for the 4th edition of the book. If you find any typo or error, please report it to the author.
There is a slide collection from lectures based on the latest edition of the book.
On Unix/Linux or Mac, download the tarfile book-examples-3rd.tar.gz for the 3rd edition and pack it out by
tar xvzf book-examples-3rd.tar.gz
On Windows, download book-examples-3rd.zip for the 3rd edition and pack it out by
unzip book-examples-3rd.zip
or double click on the file icon.
The result is a folder (directory)
tree src with subfolders containing
the program examples for different chapters in the book
(formulas, looplist, etc., as explained in the introduction to
each chapter).
You can also directly access the latest version of the example files at GitHub, see the src-3rd directory (to download a file, click the Raw button on the right first to get the pure text file in the browser and then right-click to download). To copy the whole repository to your computer, run
git clone https://github.com/hplgit/scipro-primer.git
The old software description is now outdated, so we refer to the new one that appears in the 4th edition.
You may want to install SciTools directly from its Mercurial version control
repository. This makes it easy to upgrade the package at any time.
SciTools is hosted at Googlecode.
Make sure you have the Mercurial (hg) version control system
on your computer (if not, do sudo pip install mercurial on Linux or Mac,
and pip install mercurial in a Windows Command Prompt or Power Shell window).
Get the SciTools source code and install it by
hg clone https://langtangen@code.google.com/p/scitools/
cd scitools
sudo python setup.py install
Whenever you want to upgrade the package, just go to the scitools
folder and run the commands
hg pull
hg update
sudo python setup.py install
If you have an Ubuntu installation, Python is already there. The minimum extra packages are installed by this command:
sudo apt-get install python-matplotlib python-scipy python-gnuplot gnuplot gnuplot-x11 python-scitools
A comprehensive installation with lots of useful packages can be
performed by a Bash script. Download this file (install_rich.sh) and run it by bash install_rich.sh.
There is a PDF file with an errata list for the 3rd edition of the book.
There is a slide collection from lectures based on the latest edition edition of the book.
The resource page for the first two editions is located elsewhere.