Introduction to Python for Scientific Computing

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1 Introduction to Python for Scientific Computing http://tinyurl.

1 1 Introduction to Python for Scientific Computing By: Bart Oldeman, Calcul Québec McGill HPC

2 Partners and Sponsors 2

3 3 Outline of the workshop What is Python? Why is it useful? How do we run Python codes, including on the Guillimin cluster? How to program with Python? How to use scientific packages in Python (NumPy, SciPy, Matplotlib)? Practical exercises on Guillimin Note: These slides are based on the lectures notes here:

Original author and Benevolent Dictator For Life (BFDL) : Guido van Rossum (originally at CWI, Amsterdam, now

4 4 What is Python? Python is a high-level, general-purpose programming language. Readable code. (Usually) Interpreted, not compiled. Dynamically typed. Original author and Benevolent Dictator For Life (BFDL) : Guido van Rossum (originally at CWI, Amsterdam, now at Dropbox). Named after Monty Python, Van Rossum s favourite TV show. History: Started 1989, Python 1.0 (1994), Python 2.0 (2000), Python 3.0 (2008). Using Python in this workshop.

5 Why is it useful? Provides a general-purpose, open-source, high-level glue between computations. Alternative to programs such as MATLAB, R, Julia, IDL, etc., for many numerical computations. Python is less specialized, which has pros: easier to interface with non-scientific code can do almost everything and cons slightly more cumbersome syntax for arrays Used in many disciplines, e.g. bioinformatics, mathematics, statistics, biology, economics, physics, electrical engineering, geosciences, signal processing. Groups on Guillimin use it, for instance, to study Gene flow in animal populations Climate change Searching for pulsars Computational Fluid Dynamics 5

6 Scientific Python stack Python The base language. It has batteries included but no fast array type by default. Numpy Provides efficient powerful numerical array type with associated routines. Almost all scientific software written in Python uses Numpy. Scipy Higher level than Numpy, provides many data processing routines, for instance optimization, regression, interpolation. Matplotlib Most popular 2D (and basic 3D) plotting library. Ipython Advance Python shell that integrates well with scientific Python packages. Mayavi 3D visualization. Mpi4py Use MPI from Python. Cython C-extensions for Python. Sympy Symbolic mathematics. 6

7 7 Exercise 1: Log in to Guillimin, setting up the environment Windows users: please use 1) Log in to Guillimin: ssh -X 2) Check for loaded software modules: guillimin> module list 3) See all available modules: guillimin> module av 4) Load necessary modules: guillimin> module add python/ ) Check loaded modules again 6) Verify that you have access to the correct Python package: guillimin> which python3 output: /software/centos-6/tools/python-3.3.2/bin/python3

8 8 Interactive job submission 1) Copy all workshop files to your home directory: guillimin> cp -a /software/workshop/python/*./ 2) Inspect the file interactive.pbs : guillimin> cat interactive.pbs #!/bin/bash #PBS -l nodes=1:ppn=1,walltime=06:00:00 #PBS -N python-interactive #PBS -V #PBS -X #PBS -I

9 9 Interactive job submission 3) guillimin> qsub interactive.pbs qsub: waiting for job gm-1r16-n04.guillimin.clumeq.ca to start qsub: job gm-1r16-n04.guillimin.clumeq.ca ready Begin PBS Prologue Wed Mar 11 12:51:09 EDT Job ID: gm-1r16-n04.guillimin.clumeq.ca Username: class01 Group: class Nodes: sw-2r08-n24 End PBS Prologue Wed Mar 11 12:51:09 EDT ~]$

10 10 Run Hello World 4) ~]$ cat hello.py print("hello, world!") ~]$ python3 hello.py Hello, world! ~]$ python3 Python (default, Oct , 15:11:42) [GCC (Red Hat )] on linux Type "help", "copyright", "credits" or "license" for more information. >>> print("hello, world!") Hello, world! >>> quit() Note: for Python 2 (unless you use Python 2.6+ with from future import print function) use print "Hello, world!" instead.

11 11 Run Hello World (IPython) 5) ~]$ ipython Python (default, Oct , 15:11:42) Type "copyright", "credits" or "license" for more information. IPython An enhanced Interactive Python.? -> Introduction and overview of IPython s features. %quickref -> Quick reference. help -> Python s own help system. object? -> Details about object, use object?? for extra details. In [1]: print("hello, world!") Hello, world! In [2]: %run hello.py Hello, world! In [3]: quit [classxx@sw-2r08-n24 ~]$ module add zeromq [classxx@sw-2r08-n24 ~]$ ipython qtconsole # Brings up a GUI

12 12 Python script for I/O: examples/io.py import import math os data_dir = os. path. join (os. path. dirname ( file ), "..", " data ") infile = " numbers " outfile = " f_numbers " f = open (os. path. join ( data_dir, infile ), r ) g = open (os. path. join ( data_dir, outfile ), w ) def func (y): if y >= 0.0: return y **5.0* math. exp (-y) else : return 0.0 for line in f: line = line. split () x, y = float ( line [0]), float ( line [1]) g. write ("\%g \%12.5 e\\n" \% (x, func (y))) f. close () g. close ()

13 13 Setting up the IPython Notebook The IPython Notebook is a web-based interactive computational environment where execution, text, mathematics, plots and rich media combine into a single document. We use it for the remainder of the workshop. Setting up IPython notebook/jupyter: 1. Open in a web browser. 2. In the web page, trust this web site and login using your class account. Please Continue any unresponsive scripts. Alternatively, you could install a scientific Python distribution such as Continuum s Anaconda or Enthought s Canopy and use IPython Notebook locally. In that case you can obtain the workshop files as follows: yourlaptop> git clone -b mcgill \ yourlaptop> cd cq-formation-intro-python

14 14 Further reading: Python, NumPy, SciPy, Matplotlib and Ipython can all be found at the.org website, for instance: Official non-scientific Python tutorial: Two more scientific tutorials: Software Carpentry: Followup questions? Contact

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