https://github.com/bjpcjp/numeric-python

Covers a variety of computational topics including integration, differential equations, statistical analysis and signal processing.
https://github.com/bjpcjp/numeric-python

differential-equations matplotlib numpy pandas python scipy seaborn

Last synced: about 2 months ago
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Covers a variety of computational topics including integration, differential equations, statistical analysis and signal processing.

• Host: GitHub
• URL: https://github.com/bjpcjp/numeric-python
• Owner: bjpcjp
• Created: 2017-05-03T21:43:18.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2023-11-14T13:51:57.000Z (about 1 year ago)
• Last Synced: 2023-11-14T16:55:37.462Z (about 1 year ago)
• Topics: differential-equations, matplotlib, numpy, pandas, python, scipy, seaborn
• Language: Jupyter Notebook
• Homepage:
• Size: 40.1 MB
• Stars: 7
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Numeric Computing with Python, 2nd edition

### [Original ebook on Apress](https://www.apress.com/us/book/9781484242452)

![book-cover](pics/bookcover-2nd-ed.png)

### 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