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Scientific Computing with Python 3

You're reading from   Scientific Computing with Python 3 An example-rich, comprehensive guide for all of your Python computational needs

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Product type Paperback
Published in Dec 2016
Publisher Packt
ISBN-13 9781786463517
Length 332 pages
Edition 1st Edition
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Authors (4):
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Jan Erik Solem Jan Erik Solem
Author Profile Icon Jan Erik Solem
Jan Erik Solem
Claus Fuhrer Claus Fuhrer
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Claus Fuhrer
Olivier Verdier Olivier Verdier
Author Profile Icon Olivier Verdier
Olivier Verdier
Claus Führer Claus Führer
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Claus Führer
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Table of Contents (17) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Variables and Basic Types 3. Container Types 4. Linear Algebra – Arrays 5. Advanced Array Concepts 6. Plotting 7. Functions 8. Classes 9. Iterating 10. Error Handling 11. Namespaces, Scopes, and Modules 12. Input and Output 13. Testing 14. Comprehensive Examples 15. Symbolic Computations - SymPy References

Functions acting on arrays


There are different types of functions acting on arrays. Some act elementwise, and they return an array of the same shape. Those are called universal functions. Other array functions return an array of a different shape.

Universal functions

Universal functions are functions that act elementwise on arrays. They thus have an output array that has the same shape as the input array. These functions allow us to compute the result of a scalar function on a whole array at once.

Built-in universal functions

A typical example is the cos function (the one provided by NumPy):

cos(pi) # -1
cos(array([[0, pi/2, pi]])) # array([[1, 0, -1]])

Note that universal functions work on arrays in a componentwise manner. This is also true for operators, such as multiplication or exponent:

2 * array([2, 4]) # array([4, 8])
array([1, 2]) * array([1, 8]) # array([1, 16])
array([1, 2])**2 # array([1, 4])
2**array([1, 2]) # array([1, 4])
array([1, 2])**array([1, 2]) # array...
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