{ "metadata": { "name": "" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Introduction to scientific computing with Python" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "J.R. Johansson (robert@riken.jp) http://dml.riken.jp/~rob/\n", "\n", "The latest version of this [IPython notebook](http://ipython.org/notebook.html) lecture is available at [http://github.com/jrjohansson/scientific-python-lectures](http://github.com/jrjohansson/scientific-python-lectures).\n", "\n", "The other notebooks in this lecture series are indexed at [http://jrjohansson.github.com](http://jrjohansson.github.com)." ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "The role of computing in science" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Science has traditionally been divided into experimental and theoretical disciplines, but during the last several decades computing has emerged as a very important part of science. Scientific computing is often closely related to theory, but it also has many characteristics in common with experimental work. It is therefore often viewed as a new third branch of science. In most fields of science, computational work is an important complement to both experiments and theory, and nowadays a vast majority of both experimental and theoretical papers involve some numerical calculations, simulations or computer modeling.\n", "\n", "
Software | Version |
---|---|
Python | 2.7.5 (default, May 19 2013, 13:26:46) [GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] |
IPython | 0.13.2 |
OS | posix [darwin] |
numpy | 1.7.1 |
scipy | 0.12.0 |
matplotlib | 1.2.1 |
sympy | 0.7.2 |
Thu Aug 08 11:18:41 2013 JST |