Quick installation instructions for STAMP
Contents
Binary release
A precompiled binary is available for Microsoft Windows. The binary has been tested under Windows XP SP3 and Windows 7, but will likely also run under Windows Vista. Please note that the first time your run STAMP it may take a minute or more to load. After this, it will start up far more quickly.
Note: if you have a pristine copy of Microsoft Windows installed, you may need to install the Microsoft Visual C++ 2008 Redistributable Package (32-bit,64-bit). This package contains a number of commonly required runtime components and as such you likely already have them. STAMP will fail with a message indicating the "configuration is incorrect" if you require this package.
Source code on Microsoft Windows
STAMP is implemented in Python and running it from source is easy. Any operating system that supports Python should be able to run STAMP from source. Running from source is the best way to fully exploit and contribute to STAMP. STAMP is dependent on the following libraries:
- Python 2.5 or 2.6 (we recommend Python 2.6.4)
- PyQt4
- NumPy and SciPy (Note: NumPy 1.4.0rc1 is not stable, we recommend using NumPy 1.3.0)
- mpmath
- matplotlib
After you have installed Python and the above libraries, extract the STAMP source code files to a directory (e.g., C:\STAMP). You can now run STAMP by moving to the source directory and entering 'python STAMP.py' on your command line. If you get an error message indicating Python cannot be found you likely need to add it to your system path (check out this website for instructions). If you have trouble installing STAMP, please feel free to contact us.
Source code on Apple's OS X
Running STAMP from source on Apple's OS X is straight-forward. It requires minimal effort on your part, although it does require a lot of compiling to be done by your computer. There are many ways to get STAMP running from source, but we have found the following the simplest (if you have a better way, please let us know):
- Install DarwinPorts
- Update DarwinPorts by typing the following into a console:
sudo port -d selfupdate
From your console, install the necessary dependencies for STAMP using port:
sudo port install python26 sudo port install python_select sudo python_select python26 sudo port install py26-macholib sudo port install py26-sip sudo port install py26-pyqt4 sudo port install py26-numpy sudo port install py26-scipy sudo port install py26-mpmath sudo port install py26-matplotlib
Our first attempt to install py26-pyqt4 failed, but was successful on our second attempt. Here are some rough estimates on the time required to install each of these package: python26 = 1 hour, python_select = 30 seconds, py26-macholib = 1 min, py26-sip = 10 min, py26-pyqt4 = 3 hours, py26-numpy = 3 hours, py26-scipy = 15 min, py26-mpmath = 30 seconds, py26-matplotlib = 5 min.
To test that all dependencies where installed correctly, start a python session and import each package:
import PyQt4 import numpy import scipy import mpmath import matplotlib
After you have installed Python and the above libraries, extract the STAMP source code files to a directory (e.g., ~\STAMP). You can now run STAMP by moving to the source directory and entering 'python STAMP.py' on your command line. If you have trouble installing STAMP, please feel free to contact us.
Command-line interface install
If you wish to use STAMP strictly from the command-line (e.g., as typical of a cluster environment) only the following 3rd-party dependencies are required:
- Python 2.5 or 2.6 (we recommend Python 2.6.4)
- NumPy and SciPy (Note: NumPy 1.4.0rc1 is not stable, we recommend using NumPy 1.3.0)
- mpmath
For details on running STAMP from the command-line please see the User's Guide.
Our build environment
STAMP was developed on Microsoft Windows XP and ported to Apple's Mac OS X. py2exe was used to create the Windows binary. It is generally best to download the latest version of each dependency. Our build environment currently uses the following versions of each dependency:
- Python 2.6.4
- PyQt4 4.6.2
- NumPy 1.3.0
- SciPy 0.7.1
- mpmath 0.13
- matplotlib 0.99.1.1
- py2exe 0.6.9