Practical Julia: A Hands-On Introduction for Scientific Minds

Cover Page
Title Page
Copyright Page
Dedication Page
About the Author
About the Technical Reviewer
BRIEF CONTENTS
CONTENTS IN DETAIL
ACKNOWLEDGMENTS
INTRODUCTION
   Why Is Julia Popular with Scientists?
   What Will This Book Do for You?
   How to Use This Book
   Book Overview
PART I: LEARNING JULIA
1 GETTING STARTED
   Installation Guide
      Hardware Requirements
      Prerequisites
      Julia Versions
      Installation
      Privacy Note
   The Julia Coding Environment
      The Julia REPL
      Text Editors
      Jupyter Notebooks
      Pluto: A Better Notebook
      Integrated Development Environments
   Recommendations
2 LANGUAGE BASICS
   The Syntax: Data Types, Expressions, and Blocks
      Types of Numbers
      Operations and Expressions
      Logic
      Looping: while Blocks
      if Blocks
   Arrays
   Ranges
      Arrays: Beyond the First Dimension
      Tuples
      Membership
   Strings and Characters
      Characters
      Strings
   More Looping: for Blocks
   Functions
      Composing Functions
      Creating Anonymous Functions
      Broadcasting
   Scope
      Scoping Rules for Functions
      Scoping Rules for Loops
      Modification of Scoping Rules in Interactive Contexts
   Mutability
      Functions That Mutate Their Arguments
      Strings Are Immutable
   Comments in Code
   Congratulations
3 MODULES AND PACKAGES
   Modules
      Understanding Namespaces
      Using Installed Modules
      Selective Importing and Renaming
      Creating Modules
      Documenting Functions with Docstrings
   The Package System
      How to Add and Remove Packages
      The Load Path
      The Nature of a Package
      The Benefits of Packages
      How to Create Packages
      Julia and Git
      The Relationship Between Package Versions and Git Commits
      Version Updating and Pinning
      How to Find Public Packages
   Conclusion
4 THE PLOTTING SYSTEM
   Plots
   The Backend System
   Modes of Interaction with Plots
   2D Plots
      Plotting from Vectors
      Plotting Functions
      Plotting Vectors of Vectors or Functions
      Displaying and Mutating
      Creating Parametric Plots
      Making Polar Plots
      Making Scatterplots
   Optional and Keyword Arguments
   Basic Plot Settings
      Font Attributes
      The Frame Styles
   Working with Plot Settings
      Aspect Ratio and Title Font Size
      Labels and Legend Positioning
      LaTeX Titles and Label Positioning by Data
      Regression Lines
   Saving Plots
   Detail Insets
   3D Plots
      Surface Plots
      Heatmaps
      Contour Plots
      3D Parametric Plots
      Vector Plots
      3D Scatterplots
   Useful Backends
      UnicodePlots
      PyPlot
      PlotlyJS
      PGFPlots and PGFPlotsX
      HDF5
      Gaston
   Layouts
      Making Simple Rectangular Layouts
      Using grid()
      Creating Complex Layouts Using @layout
   Conclusion
5 COLLECTIONS
   Controlling Loop Execution
      The break Statement
      The continue Statement
   Comprehensions and Generators
   More Ways to Join Strings
   Nonstandard String Literals
      Raw Strings
      Semantic Version Strings
      Byte Array Literals
   String Searching and Replacing
   String Interpolation
   Additional Collection Types
      Dictionaries
      Sets
      Structs
      Named Tuples
   Initializing Arrays with Functions
      The repeat() Function
      The fill() Function
      Mutability with the fill() and repeat() Functions
      The zeros() and ones() Functions
      The reshape() Function
   Array Manipulations Useful in Numerical Algorithms
      General Concatenation
      Logical Indexing
      Adjoints and Transposes
      Matrix Multiplication
   Enumeration and Zipping
      The enumerate() Function
      The pairs() Function
      The zip() Function
   Conclusion
6 FUNCTIONS, METAPROGRAMMING, AND ERRORS
   Functions and Their Arguments
      Concise Syntax for Keyword Arguments
      The Splat and Slurp Operators
      Destructuring
      Operators Are Functions Too
      The Mapping, Filtering, and Reduction Operators
   do Blocks
   Symbols and Metaprogramming
      Expression Objects
      Expression Object Interpolation
   Macros
      How to Create Macros
      Useful Macros
   Error Handling
      Types of Errors
      The Call Stack
      try...catch Blocks
      Using throw()
      The finally Clause
   Conclusion
7 DIAGRAMS AND ANIMATIONS
   Diagramming with Luxor
   The Graphs Package
      The Adjacency Matrix
      Factor Trees
   Animations with Javis
      Closures
      Epicycle Animation
   Animations with Reel
   Interactive Visualizations in Pluto
   Conclusion
8 THE TYPE SYSTEM
   Types in Practice
      “Big” and Irrational Types
      Type Promotion
      Collections
      The Type Hierarchy
      Type Assertions and Declarations
   Functions and Methods: Multiple Dispatch
      Creating Multiple Methods
      Extending Built-in Functions with New Methods
      Understanding Union Types and the <: Operator
   User-Defined Types
      Creating Abstract Types
      Creating Composite Types
      Using Composite Types
      Defining structs with Base.@kwdef
   Performance Tips
      Vanquish Type Instability
      Avoid Changing the Types of Variables
   Type Aliases
   Parametric Types
   Plot Recipes
      The Plotting Pipeline
      The Series Recipe
      The Plot Recipe
      Type Recipes
      User Recipes
      The @userplot Macro
   Conclusion
PART II: APPLICATIONS
9 PHYSICS
   Bringing Physical Units into the Computer with Unitful
      Using Unitful Types
      Stripping and Converting Units
      Typesetting Units
      Plotting with Units
      Making Plots for Publication
   Error Propagation with Measurements
   Fluid Dynamics with Oceananigans
      The Physical System
      The Grid
      The Boundary Conditions
      The Diffusivities
      The Equation of State
      The Model and Initial Conditions
      The Simulation
      The Results
   Solving Differential Equations with DifferentialEquations
      Defining the Physics Problem and Its Differential Equation
      Setting Up the Problem
      Solving the Equation System
      Examining the Solutions
      Defining Time-Dependent Parameters
      Parametric Instability
      Combining DifferentialEquations with Measurements
   Conclusion
10 STATISTICS
   Probability
   Random Numbers in Julia
   The Monty Hall Problem
   Counting
      Factorials
      Binomial Coefficients
   Modeling a Pandemic
   Common Statistics Functions
   Distributions
      The Normal Distribution
      Probability Density Functions
   Dealing with Data
      Missing Values
      CSV Files
      Dataframes
   Multivariate Data
   Other Packages
      JuliaDB for Out of Core Datasets
      RCall for Interacting with R
      P-hacking
   Conclusion
11 BIOLOGY
   The Julia Biology Ecosystem
   Simulating Evolution with Agent-Based Modeling
   Overview of the Simulation Problem
   The Predator and Prey Agents
      Constants Defining Model Behavior
      Utility Functions
      Model Initialization
   Functions to Extract Information from the Model
      Stepping Through the Simulation
      Running the Simulation
      Visualizing System Behavior
   Analyzing the Results
   Conclusion
12 MATHEMATICS
   Symbolic Mathematics
      Numerical-Symbolic Modeling with Symbolics
      Math Manipulation with SymPy and Pluto
   Linear Algebra
      Views
      Linear Algebra Examples
      The LinearAlgebra Package
      Specialized Matrix Types
      Equation Solving and factorize()
   Conclusion
13 SCIENTIFIC MACHINE LEARNING
   Automatic Differentiation in a Physics Problem
      Differentiating with ForwardDiff
      Calculating Forces from Potentials
   Probabilistic Programming
      Testing for Fairness of a Coin
      Inferring Model Parameters from Series Observations
   Conclusion
14 SIGNAL AND IMAGE PROCESSING
   Signals in Time
      Exploring a Sound Sample
      Analyzing Frequencies
      Filtering
   Image Processing
      Loading and Converting Images
      Counting Cells Using an Area Fraction
      Counting Cells by Recognizing Features
      Applying Advanced Array Concepts
   Conclusion
15 PARALLEL PROCESSING
   Concurrency Paradigms
   Multithreading
      Easy Multithreading with Folds
      Manual Multithreading with @threads
      Spawning and Synchronizing Tasks
   Multiprocessing
      Easy Multiprocessing with pmap
      Networking with Machine Files
      Going Manual with @spawnat
      Multiprocessing Threads with @distributed
   Summary of Concurrency in Julia
   Conclusion
INDEX