book

Python For Engineering and Scientific Computing

by Rheinwerk Publishing, Inc, Veit Steinkamp

June 2025

Intermediate to advanced

515 pages

17h 5m

English

Packt Publishing

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1.1 Development Environments1.1.1 IDLE1.1.2 Thonny1.1.3 Spyder1.1.4 Pip
1.2.1 NumPy1.2.2 Matplotlib1.2.3 SymPy1.2.4 SciPy1.2.5 VPython
2.1 Linear Program Structures2.1.1 Linear Programs without Function Calls
2.2.1 Built-In Functions2.2.2 Functions without Parameters and without Return Values2.2.3 Functions with Parameters and a Return2.2.4 Functions with Multiple Return Values2.2.5 Functions Call Other Functions
2.3.1 Single Selection2.3.2 Multiple Selection
2.4.1 The while Loop2.4.2 The for Loop

2.5.1 Tuples2.5.2 Lists2.5.3 Dictionaries2.5.4 Sets
2.7.1 Objects and Classes2.7.2 Inheritance
3.1 NumPy Functions3.1.1 Creating One-Dimensional Arrays Using arange() and linspace()3.1.2 Creating Two-Dimensional Arrays Using array()3.1.3 Slicing3.1.4 Mathematical NumPy Functions3.1.5 Statistical NumPy Functions
3.2.1 Addition of Vectors3.2.2 Scalar Product3.2.3 Cross Product3.2.4 Triple Product3.2.5 Dyadic Product
3.3.1 Chain Shape with B Parameters3.3.2 Usage Example: Calculating the Energy of a Rotating Rigid Body in Space
3.4.1 Systems of Equations with Real Coefficients3.4.2 Systems of Equations with Complex Coefficients
4.1 2D Function Plots4.1.1 Basic Structure of a Function Plot4.1.2 Gridlines4.1.3 Labels4.1.4 Line Styles4.1.5 Designing Axes4.1.6 Coloring Areas4.1.7 Subplots4.1.8 Parameter Representation4.1.9 Changing Function Parameters Interactively4.1.10 Contour Plots
4.2.1 Helical Line4.2.2 Circular Ring4.2.3 Combining a 3D Plot with a Contour Plot
4.3.1 Vector Addition4.3.2 Vector Field
4.4.1 Rectangles4.4.2 Circles and Lines4.4.3 Arrows4.4.4 Polygons4.4.5 Usage Example: A Metal Rod in a Magnetic Field
4.5.1 A Simple Animation: Shifting a Sine Function4.5.2 Animated Oblique Throw4.5.3 Animated Planetary Orbit
5.1 Basic Mathematical Operations5.1.1 Addition5.1.2 Multiplication of Terms5.1.3 Multiplication of Linear Factors5.1.4 Division5.1.5 Exponentiation5.1.6 Usage Example: Analyzing an Electrical Power Transmission System
5.2.1 Calculation Rule5.2.2 Transmission Function of a Catenary Circuit
5.3.1 Linear Systems of Equations5.3.2 Nonlinear Systems of Equations
5.8.1 Limits of Sequences5.8.2 Limits of Functions5.8.3 Differential Quotient
5.9.1 Usage Example: Curve Sketching
5.10.1 Indefinite Integral5.10.2 Definite Integral5.10.3 Usage Example: Stored Electrical Energy
5.11.1 Linear First-Order Differential Equations5.11.2 General Solution of a Second-Order Differential Equation5.11.3 Special Solution of a Second-Order Differential Equation
5.12.1 Solving Differential Equations5.12.2 Analyzing Networks with Transmission Functions
5.14.1 Second Moment of Area5.14.2 Equation of the Bending Line
6.1 Numerical Computation of Zeros
6.4.1 Methods of Numerical Differentiation6.4.2 Drawing a Tangent Slope6.4.3 Derivative of a Sine Function6.4.4 Usage Example: Free Fall
6.5.1 Methods of Numerical Integration6.5.2 Definite Integral6.5.3 Integrating a Constant6.5.4 Usage Example: Free Fall6.5.5 Improper Integral6.5.6 Calculating Arc Lengths6.5.7 Volume and Surfaces of Rotating Bodies6.5.8 Double Integrals6.5.9 Triple Integrals
6.6.1 Numerical Solution of Differential Equations6.6.2 First-Order Linear Differential Equation6.6.3 Second-Order Linear Differential Equation6.6.4 Nonlinear Second-Order Differential Equation6.6.5 Second-Order Differential Equation System: Coupled Spring-Mass System6.6.6 Nonlinear Second-Order Differential Equation System: Double Pendulum
6.7.1 Basic Use of the Fast Fourier Transform Algorithm6.7.2 Frequency Spectra of Non-Sinusoidal Periodic Signals6.7.3 Reconstructing a Noisy Signal
6.8.1 Generating and Saving Signals6.8.2 Reading and Displaying Signals
6.9.1 Frequency Response of a Butterworth Lowpass6.9.2 Frequency Response of a Crossover6.9.3 Filtering Signals
6.11.1 Exponential Growth6.11.2 Logistic Growth6.11.3 Predator-Prey Relationship for Exponential Growth6.11.4 Predator-Prey Relationship for Logistic Growth
7.1 The Coordinate System
7.2.1 Cylinder7.2.2 Cuboid7.2.3 Points7.2.4 Lines7.2.5 Sphere7.2.6 Penetration7.2.7 Composite Bodies
7.3.1 Vertical Movement7.3.2 Horizontal Movement7.3.3 Movement in Space7.3.4 Composite Motion7.3.5 Rotational Motion7.3.6 Random Motion
7.4.1 Simple Pendulum7.4.2 Spring Pendulum
8.1 Mathematical Operations
8.2.1 Symbolic Method
8.4.1 Complex Frequency Response of a Series Resonant Circuit8.4.2 Locus Curves
8.5.1 Task8.5.2 Equivalent Circuit Diagram of a Three-Phase Power Line
9.1 Generating, Saving, and Reading Measurement Values9.1.1 Generating Measurement Values9.1.2 Converting a Measurement Series into a Table9.1.3 Writing Measurement Values to a File9.1.4 Reading Measurement Values from a File
9.2.1 Frequency Tables9.2.2 Histograms
9.3.1 Arithmetic Mean9.3.2 Mode, Median, Harmonic Mean, and Geometric Mean
9.5.1 Graphical Representation of the Density Function9.5.2 Probability Distribution
9.7.1 Computing the Regression Parameters9.7.2 Representing the Scatter Plot and the Regression Line
10.1 Logical Operations10.1.1 Conjunction10.1.2 Disjunction10.1.3 Negation
10.2.1 Simple Postulates10.2.2 De Morgan’s Laws10.2.3 Distributive Law
10.3.1 Simplifying Logic Functions by Factoring Out10.3.2 Simplification Using the Disjunctive Normal Form10.3.3 Simplification Using the Conjunctive Normal Form
11.1 Interactions with Command Buttons, Textboxes, and Labels11.1.1 Labels11.1.2 Textboxes and Command Buttons
11.2.1 The pack Method11.2.2 The grid Method11.2.3 Summary
11.5.1 Representing Lines11.5.2 Function Plots11.5.3 Querying Mouse Coordinates
A.1 Glossary: Basic Applied Computer Science Terminology

Overview

Python For Engineering and Scientific Computing is your comprehensive guide to leveraging Python for technical problem-solving. Through practical applications and projects, you'll master libraries like NumPy, SciPy, and Matplotlib to handle computational tasks and visualize results effectively. From basic syntax to advanced modeling, this book equips you for real-world engineering and scientific challenges.

What this Book will help me do

Master Python basics and understand its application for engineers.
Perform numerical and symbolic computations using leading Python libraries.
Visualize data effectively with toolkits such as Matplotlib and VPython.
Develop practical applications, from statistical analysis to GUI programming.
Apply Python in technical scenarios, embracing automation and problem-solving.

Author(s)

Veit Steinkamp and colleagues at Rheinwerk Publishing specialize in technical education, providing clear and thorough guidance for readers aiming to become professionals. Veit brings unique expertise in Python programming for engineering and science, stemming from extensive practical experience in these fields.

Who is it for?

This book is crafted for engineers and scientists looking to integrate Python into their workflow. It suits readers with foundational programming knowledge who seek to explore numerical methods, data visualization, and interactive tools using Python. Ideal for anyone aiming to apply computation in technical and scientific projects.