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From Python to Numpy

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Introduction

What is NumPy?Creation in NumPy Reshaping in NumPy Indexing in NumPy Broadcasting in NumPy NumPy Vectorization Readability vs. Speed

Anatomy of an Array

Views and Copies

Coding Example: How to find if one vector is view of the other?

Solution Review

Code Vectorization

Introduction Uniform Vectorization Coding Example: Game of life (Python approach)Coding Example: Game of life (NumPy approach)Coding Example: Reaction-Diffusion Temporal Vectorization Coding Example: The Mandelbrot Set (Python approach)Coding Example: The Mandelbrot Set (NumPy approach)Coding Example: Minkowski-Bouligand Dimension Spatial Vectorization Coding Example: Implement the behavior of Boids (Python approach)Coding Example: Implement the behavior of Boids (NumPy approach)Conclusion

Problem Vectorization

Introduction Coding Example: Find shortest path in a maze Coding Example: Find shortest path in a maze (Breadth-First approach)Coding Example: Find shortest path in a maze (Bellman-Ford approach)Coding Example: Fluid Dynamics Coding Example: Blue Noise Sampling Coding Example: Blue Noise Sampling using DART method Coding Example: Blue Noise Sampling using Bridson method Conclusion

Custom Vectorization

Typed list Coding Example: Modifying the list Memory-aware Array: Glumpy Memory-aware Array: Array Subclass in GPUData class Conclusion

Beyond NumPy

Back to Python NumPy & co Scipy & co Conclusion

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Introduction

Introduction

In this lesson, we'll learn how to maximize the speed using NumPy!

This chapter explains the basic anatomy of NumPy arrays, especially regarding the memory layout, view, copy and the data type. They are critical notions to understand if you want your computation to benefit from NumPy philosophy.

Let’s consider a simple example where we want to clear all the values from ...