/Numeric-Python

Covers a variety of computational topics including integration, differential equations, statistical analysis and signal processing.

Primary LanguageJupyter Notebook

Numeric Computing with Python, 2nd edition

book-cover

TODO:

  • Fix FeniCS installation bugs (Chapter 11)
ChapterTopics
Intro Python, iPython, Jupyter
Intro to NumPy Arrays: Create, Index, Slice, Reshape, Resize, Vectorized ops, Matrix & Vector ops
Intro to SymPy Symbols, Expressions, Manipulations, Calculus, Equations, Linear Algebra
Plotting & Visualization
Intro to Matplotlib
Plots, Steps, Bargraphs, Histograms, ErrorBars, ScatterPlots, Fill_Between, QuiverPlots, ColorMaps, 3D Plots
Equation Solvers with SciPy Linear Equations (square, rectangular), Eigenvalues, NonLinear Equations
Optimization with SciPy Univariate, Multivariate (unconstrained), Nonlinear Least Squares, Constrained
Interpolation with SciPy Polynomials, Splines, Multivariate
Integration with SciPy & Scikit-monaco Numerical Methods, Multiple integration, Symbolic & arbitrary precision, Integral transforms
Ordinary Differential Equations (ODEs) Direction fields, Laplace transforms, Numerical methods
Sparse Matrices & Graphs Matrix ops, Linear equation systems incl. Eigenvalues, Graphs/Networks
Partial Differential Equations (PDEs) Finite-difference methods, Finite element methods & libraries, PDE solvers with FEniCS
Data Analysis with Pandas & Seaborn Series, DataFrames, TimeSeries
Statistics with SciPy & NumPy Probability, Random numbers, Distributions, Hypothesis testing, Nonparametric methods
Statistical Modeling with Stasmodels & Patsy Model definitions, Linear regression, Logistic regression, Poisson models, Time series
Intro to Machine Learning with scikit-learn Concepts, Regression, Classification, Clustering
Bayesian Statistics with pyMC Concepts, Sampling posterior distributions, Linear regression
Signal Processing with SciPy, fftpack, signal, wavfile & io Spectral analysis (Fourier transforms, windows, spectrograms), Signal filters (Convolution, FIR/IIR filters)
Data I/O CSV, HDF5 (h5py files, groups, datasets, attributes, PyTables, HDFStore), JSON, Serialization
Code optimization Numba, Cython