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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
Author Profile Icon Jan Erik Solem
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

15.3.1 Timing with a magic function

The easiest way to measure the execution time of a single statement is to use IPython’s magic function %timeit.

The shell IPython adds additional functionality to standard Python. These extra functions are called magic functions.

As the execution time of a single statement can be extremely short, the statement is placed in a loop and executed several times. By taking the minimum measured time, you make sure that other tasks running on the computer do not influence the measured result too much.

Let's consider four alternative ways to extract nonzero elements from an array as follows:

A=zeros((1000,1000))
A[53,67]=10

def find_elements_1(A):
    b = []
    n, m = A.shape
    for i in range(n):
        for j in range(m):
            if abs(A[i, j]) > 1.e-10:
                b.append(A[i, j])
    return b

def find_elements_2(A):
    return [a for a in A.reshape((-1, )) if abs(a) > 1.e-10]

def find_elements_3...
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