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SciPy Recipes

You're reading from   SciPy Recipes A cookbook with over 110 proven recipes for performing mathematical and scientific computations

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Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781788291460
Length 386 pages
Edition 1st Edition
Languages
Tools
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Authors (3):
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V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Ruben Oliva Ramos Ruben Oliva Ramos
Author Profile Icon Ruben Oliva Ramos
Ruben Oliva Ramos
Luiz Felipe Martins Luiz Felipe Martins
Author Profile Icon Luiz Felipe Martins
Luiz Felipe Martins
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Toc

Table of Contents (11) Chapters Close

Preface 1. Getting to Know the Tools FREE CHAPTER 2. Getting Started with NumPy 3. Using Matplotlib to Create Graphs 4. Data Wrangling with pandas 5. Matrices and Linear Algebra 6. Solving Equations and Optimization 7. Constants and Special Functions 8. Calculus, Interpolation, and Differential Equations 9. Statistics and Probability 10. Advanced Computations with SciPy

Matrix operations and functions on two-dimensional arrays

Basic matrix operations form the backbone of quite a few statistical analyses—for example, neural networks. In this section, we will be covering some of the most used operations and functions on 2D arrays:

  • Addition
  • Multiplication by scalar
  • Matrix arithmetic
  • Matrix-matrix multiplication
  • Matrix inversion
  • Matrix transposition

In the following sections, we will look into the methods of implementing each of them in Python using SciPy/NumPy.

How to do it…

Let's look the the different methods.

Matrix addition

In order to understand how matrix addition is done, we will first initialize two arrays:

# Initializing an array
x = np.array([[1, 1], [2, 2]])
y ...
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