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Preface Introduction to scientific computing with Python 1 Introduction to Python 1.1 Basic Python 1.1.1 Python, numbers and variables 1.1.2 Basic mathematical operations 1.1.3 Mathematical functions and constants 1.1.4 Powers of 10 and scientific notation 1.2 Assignment operators 1.3 Strings, tuples, dictionaries and lists 1.3.1 Strings 1.3.2 Tuples 1.3.3 Dictionaries 1.3.4 Lists 1.3.5 Lists of lists 1.4 Flow control 1.4.1 for loops 1.4.2 Useful applications 1.4.3 Boolean type of variables 1.4.4 while loops 1.4.5 Decisions and the if statement 1.4.6 Error control and exceptions 1.4.7 The command break 1.5 Functions 1.6 Classes 1.7 Accessing data files 1.8 Further reading Chapter highlights Exercises 2 Matrices and Python 2.1 Review of matrices 2.1.1 Matrix properties 2.1.2 Special matrices 2.2 The NumPy module 2.2.1 Matrices and arrays 2.2.2 Slicing 2.2.3 Special matrices, methods and properties 2.2.4 Matrix assignment 2.2.5 Matrix addition and scalar multiplication 2.2.6 Vectorized algorithms 2.2.7 Performance of algorithms 2.2.8 Matrix multiplication 2.2.9 Inverse of a matrix 2.2.10 Determinant of a matrix 2.2.11 Linear systems 2.2.12 Eigenvalues and eigenvectors 2.3 The SciPy module 2.3.1 Systems with banded matrices 2.3.2 Systems with positive definite, banded matrices 2.3.3 Systems with other special matrices 2.4 Drawing graphs with MatPlotLib 2.4.1 Plotting one-dimensional arrays 2.5 Further reading Chapter highlights Exercises 3 Scientific computing<

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