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Effective Computation in Physics 1st Edition by Anthony Scopatz, Kathryn D Huff ISBN 1491901535 9781491901533

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Author(s): Anthony Scopatz, Kathryn D. Huff
ISBN(s): 9781491901533, 1491901535
Edition: 1
File Details: PDF, 8.49 MB
Year: 2015
Language: english
SKU: EB-5151048 Category: Tags: ,

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Product details: 

ISBN 10: 1491901535

ISBN 13: 9781491901533

Author: Anthony Scopatz, Kathryn D. Huff

More physicists today are taking on the role of software developer as part of their research, but software development isnâ??t always easy or obvious, even for physicists. This practical book teaches essential software development skills to help you automate and accomplish nearly any aspect of research in a physics-based field. Written by two PhDs in nuclear engineering, this book includes practical examples drawn from a working knowledge of physics concepts. Youâ??ll learn how to use the Python programming language to perform everything from collecting and analyzing data to building software and publishing your results. In four parts, this book includes: Getting Started: Jump into Python, the command line, data containers, functions, flow control and logic, and classes and objects Getting It Done: Learn about regular expressions, analysis and visualization, NumPy, storing data in files and HDF5, important data structures in physics, computing in parallel, and deploying software Getting It Right: Build pipelines and software, learn to use local and remote version control, and debug and test your code Getting It Out There: Document your code, process and publish your findings, and collaborate efficiently; dive into software licenses, ownership, and copyright procedures

Table of contents: 

Case Study on How to Use This Book: Radioactive Decay Constants
Accessing Data and Libraries
Creating a Simple Program
Automating Data Collection
Analyzing and Plotting the Data
Keeping Track of Changes
Testing the Code
Documenting the Code
Publishing
What to Do While Reading This Book
Conventions Used in This Book
Using Code Examples
Installation and Setup
Step 1: Download and Install Miniconda (or Anaconda)
Step 2: Install the Packages
Safari® Books Online
How to Contact Us
Acknowledgments
I. Getting Started
1. Introduction to the Command Line
Navigating the Shell
The Shell Is a Programming Language
Paths and pwd
Home Directory (~)
Listing the Contents (ls)
Changing Directories (cd)
File Inspection (head and tail)
Manipulating Files and Directories
Creating Files (nano, emacs, vi, cat, >, and touch)
Copying and Renaming Files (cp and mv)
Making Directories (mkdir)
Deleting Files and Directories (rm)
Flags and Wildcards
Getting Help
Reading the Manual (man)
Finding the Right Hammer (apropos)
Combining Utilities with Redirection and Pipes (>, >>, and |)
Permissions and Sharing
Seeing Permissions (ls -l)
Setting Ownership (chown)
Setting Permissions (chmod)
Creating Links (ln)
Connecting to Other Computers (ssh and scp)
The Environment
Saving Environment Variables (.bashrc)
Running Programs (PATH)
Nicknaming Commands (alias)
Scripting with Bash
Command Line Wrap-up
2. Programming Blastoff with Python
Running Python
Comments
Variables
Special Variables
Boolean Values
None Is Not Zero!
NotImplemented Is Not None!
Operators
Strings
String Indexing
String Concatenation
String Literals
String Methods
Modules
Importing Modules
Importing Variables from a Module
Aliasing Imports
Aliasing Variables on Import
Packages
The Standard Library and the Python Ecosystem
Python Wrap-up
3. Essential Containers
Lists
Tuples
Sets
Dictionaries
Containers Wrap-up
4. Flow Control and Logic
Conditionals
if-else Statements
if-elif-else Statements
if-else Expression
Exceptions
Raising Exceptions
Loops
while Loops
for Loops
Comprehensions
Flow Control and Logic Wrap-up
5. Operating with Functions
Functions in Python
Keyword Arguments
Variable Number of Arguments
Multiple Return Values
Scope
Recursion
Lambdas
Generators
Decorators
Function Wrap-up
6. Classes and Objects
Object Orientation
Objects
Classes
Class Variables
Instance Variables
Constructors
Methods
Static Methods
Duck Typing
Polymorphism
Decorators and Metaclasses
Object Orientation Wrap-up
II. Getting It Done
7. Analysis and Visualization
Preparing Data
Experimental Data
Simulation Data
Metadata
Loading Data
NumPy
PyTables
Pandas
Blaze
Cleaning and Munging Data
Missing Data
Analysis
Model-Driven Analysis
Data-Driven Analysis
Visualization
Visualization Tools
Gnuplot
matplotlib
Bokeh
Inkscape
Analysis and Visualization Wrap-up
8. Regular Expressions
Messy Magnetism
Metacharacters on the Command Line
Listing Files with Simple Patterns
Globally Finding Filenames with Patterns (find)
grep, sed, and awk
Finding Patterns in Files (grep)
Finding and Replacing Patterns in Files (sed)
Finding and Replacing a Complex Pattern
sed Extras
Manipulating Columns of Data (awk)
Python Regular Expressions
Regular Expressions Wrap-up
9. NumPy: Thinking in Arrays
Arrays
dtypes
Slicing and Views
Arithmetic and Broadcasting
Fancy Indexing
Masking
Structured Arrays
Universal Functions
Other Valuable Functions
NumPy Wrap-up
10. Storing Data: Files and HDF5
Files in Python
An Aside About Computer Architecture
Big Ideas in HDF5
File Manipulations
Hierarchy Layout
Chunking
In-Core and Out-of-Core Operations
In-Core
Out-of-Core
Querying
Compression
HDF5 Utilities
Storing Data Wrap-up
11. Important Data Structures in Physics
Hash Tables
Resizing
Collisions
Data Frames
Series
The Data Frame Structure
B-Trees
K-D Trees
Data Structures Wrap-up
12. Performing in Parallel
Scale and Scalability
Problem Classification
Example: N-Body Problem
No Parallelism
Threads
Multiprocessing
MPI
Parallelism Wrap-up
13. Deploying Software
Deploying the Software Itself
pip
Conda
Virtual Machines
Docker
Deploying to the Cloud
Deploying to Supercomputers
Deployment Wrap-up
III. Getting It Right
14. Building Pipelines and Software
make
Running make
Makefiles
Targets
Special Targets
Building and Installing Software
Configuration of the Makefile
Compilation
Installation
Building Software and Pipelines Wrap-up
15. Local Version Control
What Is Version Control?
The Lab Notebook of Computational Physics
Version Control Tool Types
Getting Started with Git
Installing Git
Getting Help (git –help)
Control the Behavior of Git (git config)
Local Version Control with Git
Creating a Local Repository (git init)
Staging Files (git add)
Checking the Status of Your Local Copy (git status)
Saving a Snapshot (git commit)
git log: Viewing the History
Viewing the Differences (git diff)
Unstaging or Reverting a File (git reset)
Discard Revisions (git revert)
Listing, Creating, and Deleting Branches (git branch)
Switching Between Branches (git checkout)
Merging Branches (git merge)
Dealing with Conflicts
Version Conrol Wrap-Up
16. Remote Version Control
Repository Hosting (github.com)
Creating a Repository on GitHub
Declaring a Remote (git remote)
Sending Commits to Remote Repositories (git push)
Downloading a Repository (git clone)
Fetching the Contents of a Remote (git fetch)
Merging the Contents of a Remote (git merge)
Pull = Fetch and Merge (git pull)
Conflicts
Resolving Conflicts
Remote Version Control Wrap-up
17. Debugging
Encountering a Bug
Print Statements
Interactive Debugging
Debugging in Python (pdb)
Setting the Trace
Stepping Forward
Querying Variables
Setting the State
Running Functions and Methods
Continuing the Execution
Breakpoints
Profiling
Viewing the Profile with pstats
Viewing the Profile Graphically
Line Profiling with Kernprof
Linting
Debugging Wrap-up
18. Testing
Why Do We Test?
When Should We Test?
Where Should We Write Tests?
What and How to Test?
Running Tests
Edge Cases
Corner Cases
Unit Tests
Integration Tests
Regression Tests
Test Generators
Test Coverage
Test-Driven Development
Testing Wrap-up
IV. Getting It Out There
19. Documentation
Why Prioritize Documentation?
Documentation Is Very Valuable
Documentation Is Easier Than You Think
Types of Documentation

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