This accessible and self-contained guide provides a comprehensive introduction to the popular programming language, Python, with a focus on applications in chemistry and chemical physics. End of chapter problems are included throughout, with worked solutions available, and additional resources are provided on a companion website.
This accessible and self-contained guide provides a comprehensive introduction to the popular programming language, Python, with a focus on applications in chemistry and chemical physics. End of chapter problems are included throughout, with worked solutions available, and additional resources are provided on a companion website.
Christian Hill is a physicist and physical chemist with over twenty-five years' experience in scientific programming, data analysis and database design in atomic and molecular physics. Currently the Head of the Atomic and Molecular Data Unit at International Atomic Energy Agency, Vienna, he has previously held positions at the University of Cambridge, the University of Oxford, and University College London.
Inhaltsangabe
1. Introduction 2. Basic Python usage 3. Strings 4. Lists and loops 5. Comparisons and flow control 6. Functions 7. Data structures 8. File input/output 9. Basic numpy 10. Graph plotting with Matplotlib 11. The steady-state approximation 12. Liquid-vapour equilibrium 13. Jupyter notebook 14. LaTeX 15. Chemistry databases and file formats 16. More NumPy and Matplotlib 17. Thermodynamic cycles 18. Vectors, matrices and linear algebra 19. Linear least squares fitting I 20. Linear least squares fitting II 21. Numerical integration 22. Optimization with scipy.optimize 23. Vibrational spectroscopy 24. The morse oscillator 25. Solving ordinary differential equations 26. The oregonator 27. Root-finding with scipy.optimize 28. Rotational spectroscopy 29. Peak finding 30. Fitting the vibrational spectrum of CO 31. pandas 32. Simulating a powder diffraction spectrum 33. The Hückel approximation 34. Nonlinear fitting and constrained optimization 35. SymPy 36. Molecular orbital theory for H2+ 37. Approximations of the helium atom electronic energy 38. Computational chemistry with Psi4 and Python 39. Atomic structure 40. Solutions.
1. Introduction 2. Basic Python usage 3. Strings 4. Lists and loops 5. Comparisons and flow control 6. Functions 7. Data structures 8. File input/output 9. Basic numpy 10. Graph plotting with Matplotlib 11. The steady-state approximation 12. Liquid-vapour equilibrium 13. Jupyter notebook 14. LaTeX 15. Chemistry databases and file formats 16. More NumPy and Matplotlib 17. Thermodynamic cycles 18. Vectors, matrices and linear algebra 19. Linear least squares fitting I 20. Linear least squares fitting II 21. Numerical integration 22. Optimization with scipy.optimize 23. Vibrational spectroscopy 24. The morse oscillator 25. Solving ordinary differential equations 26. The oregonator 27. Root-finding with scipy.optimize 28. Rotational spectroscopy 29. Peak finding 30. Fitting the vibrational spectrum of CO 31. pandas 32. Simulating a powder diffraction spectrum 33. The Hückel approximation 34. Nonlinear fitting and constrained optimization 35. SymPy 36. Molecular orbital theory for H2+ 37. Approximations of the helium atom electronic energy 38. Computational chemistry with Psi4 and Python 39. Atomic structure 40. Solutions.
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