Mathematica Beyond Mathematics: The Wolfram Language in the Real World

ISBN-13: 9781032004839 / Angielski / Twarda / 2022 / 454 str.

Spain) Sanchez Leo Jose Guillermo (Universidad de Salamanca

Opis

Although many books have been written about Mathematica, very few of them cover the new functionality added to the most recent versions of the program. This thoroughly revised second edition introduces the new features using real-world examples based on the experience of the author as a consultant and Wolfram certified instructor.

Spis treści

1. Getting Started. 1.1. Mathematica, an Integrated Technical Computing System. 1.2. First Steps. 1.3. Editing Notebooks. 1.4. Basic Ideas. 1.5. From Graphics to Machine Learnings. 1.6. Additional Resources and Supplementary Materials. 2. Programming: The Beauty and Power of the Wolfram Language. 2.1. Mathematica’s Programming Language: The Wolfram Language. 2.2. Lists Operations. 2.3. Association and Dataset. 2.4. Matrix Operations. 2.5. Set, Set Delayed and Dynamic Variables. 2.6. Functional vs. Procedural Programming. 2.7. Apply, Map, and Other Related Functions. 2.8. Iterative Functions. 2.9. Pure Functions. 2.10. Global and Local Variables. 2.11. Conditional Expressions and Conditions. 2.12. Accuracy and Precision. 2.13. Choosing the Method of Computation. 2.14. Optimizing the Computation Time. 2.15. Cloud Deployment. 2.16. Package Development. 2.17. Additional Resources. 3. Interactive Applications, Image Processing, and More. 3.1. The Manipulate Function. 3.2. Creating Demonstrations. 3.3. Image Processing. 3.4. Image Manipulation. 3.5. Graphs and Networks. 3.6. Application: Finding the Period of a Pendulum. 3.7. Additional Resources. 4. Accessing Scientific and Technical Information. 4.1. The Wolfram Data Framework: Introducing Entities. 4.2. Computable Data Functions. 4.3. The Wolfram Data Repository. 4.4. Weather Data in Real Time. 4.5. Chemical and Physical Properties of Elements and Compounds. 4.6. Life Sciences and Medicine. 4.7. Earth Sciences and Geographic Data. 4.8. Additional Resources. 5. Data Analysis and Manipulation. 5.1. Importing/Exporting. 5.2. Statistical Analysis. 5.3. Probability Distributions. 5.4. Exploratory Data Analysis. 5.5. Bootstrapping and Confidence Estimates. 5.6. Curve Fitting. 5.7. Time Series Analysis. 5.8. Spatial Statistics. 6.9. Additional Resources. 6. Machine Learning and Neural Networks. 6.1. What is Machine Learning. 6.2. Classification. 6.3. Prediction. 6.4. Working with Neural Networks. 6.5. Additional Resources. 7. Calculating π and Other Mathematical Tales. 7.1. The Origins of π. 7.2. Archimedes’ Approximation. 7.3. π with More Than One Billion Decimals. 7.4. Buffon’s Method. 7.5. Application: Are the Decimal Digits of π Random? 7.6. The Strange Connection. 7.7. The Riemann Hypothesis. 7.8. Looking for the Magic Prime Formula. 7.9. Additional Resources. 8. Looking at the Sky. 8.1. A Short Astronomical Walk. 8.2. Solar Analemma. 8.3. Stargazing. 8.4. Application: Determining the Color of the Stars. 8.5. The Measurement of Distances Across the Universe. 8.6. Application: Binary Systems and the Search for Exoplanets. 8.7. Light Curves. 8.8. Additional Resources. 9. Nuclei and Radiations. 9.1. Nuclear and Particle Physics. 9.2. What are Isotopes? 9.3. Decay Constants, Decay Periods and Half-Lives. 9.4. Decay Chains. 9.5. Application: Modeling the Evolution of a Chain of Isotopes Over Time. 9.6. Application: Dating the History of Humankind. 9.7. Application: Calculating Binding Energies. 9.8. Radiation Attenuation. 9.9. Additional Resources. 10. Modeling: Applications in Biokinetics, Epidemiology and More. 10.1. Compartmental Modeling. 10.2. Epidemiological Models. 10.3. Physiological Modeling. 10.4. Fitting a Model. 10.5. Optimal Experimental Designs (OED). 10.6. BIOKMOD: The New Iodine OIR Model (ICRP 137). 10.7. Additional Modeling Examples. 10.8. Modeling Using PDEs. 10.9. Additional Resources. 11. Economic, Financial and Optimization Applications. 11.1. Accessing Economic Information. 11.2. Financial Information. 11.3. Financial Functions. 11.4. Optimization. 11.5. The Shortest Path Problem. 11.6. Optimum Flows. 11.7. Blockchains. 11.8. Additional Resources. 12. Faster, Further. 12.1. Parallel Computing. 12.2. Parallel Programming. 12.3. The Mandelbrot Set. 12.4. Comparing Organisms Genetically. 12.5. Compute Unified Device Architecture (CUDA). 12.6. Software Development with Wolfram Workbench. 12.7. Connecting with Other Programs and Devices. 12.8. Additional Resources.