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Scientific Computing with Python

You're reading from   Scientific Computing with Python High-performance scientific computing with NumPy, SciPy, and pandas

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781838822323
Length 392 pages
Edition 2nd Edition
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Authors (4):
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Olivier Verdier Olivier Verdier
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Olivier Verdier
Jan Erik Solem Jan Erik Solem
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Jan Erik Solem
Claus Führer Claus Führer
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Claus Führer
Claus Fuhrer Claus Fuhrer
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Claus Fuhrer
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Table of Contents (23) Chapters Close

Preface 1. Getting Started 2. Variables and Basic Types FREE CHAPTER 3. Container Types 4. Linear Algebra - Arrays 5. Advanced Array Concepts 6. Plotting 7. Functions 8. Classes 9. Iterating 10. Series and Dataframes - Working with Pandas 11. Communication by a Graphical User Interface 12. Error and Exception Handling 13. Namespaces, Scopes, and Modules 14. Input and Output 15. Testing 16. Symbolic Computations - SymPy 17. Interacting with the Operating System 18. Python for Parallel Computing 19. Comprehensive Examples 20. About Packt 21. Other Books You May Enjoy 22. References

5.3.1 Indexing with Boolean arrays

It is often useful to access and modify only parts of an array, depending on its value. For instance, you might want to access all the positive elements of an array. This turns out to be possible using Boolean arrays, which act like masks to select only some elements of an array. The result of such indexing is always a vector. For instance, consider the following example:

B = array([[True, False],
           [False, True]])
M = array([[2, 3],
           [1, 4]])
M[B] # array([2,4]), a vector

In fact, the command M[B] is equivalent to M[B].flatten(). You can then replace the resulting vector with another vector. For instance, you can replace all the elements with zero:

M[B] = 0
M # [[0, 3], [1, 0]]

Or you can replace all the selected values with others:

M[B] = 10, 20
M # [[10, 3], [1, 20]]

By combining the creation of Boolean arrays (M > 2), smart indexing (indexing with a Boolean array), and broadcasting, you can...

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