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Numpy Beginner's Guide (Update)

Numpy Beginner's Guide (Update)

By : Ivan Idris
2 (1)
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Numpy Beginner's Guide (Update)

Numpy Beginner's Guide (Update)

2 (1)
By: Ivan Idris

Overview of this book

This book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and pointers to learning resources.
Table of Contents (16 chapters)
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14
C. NumPy Functions' References
15
Index

Time for action – computing the modulo

Let's call the previously mentioned functions:

  1. The remainder() function returns the remainder of the two arrays, element-wise. 0 is returned if the second number is 0:
    a = np.arange(-4, 4)
    print("Remainder", np.remainder(a, 2))

    The result of the remainder() function is shown as follows:

    Remainder [0 1 0 1 0 1 0 1]
    
  2. The mod() function does exactly the same as the remainder() function:
    print("Mod", np.mod(a, 2))

    The result of the mod() function is shown as follows:

    Mod [0 1 0 1 0 1 0 1]
    
  3. The % operator is just shorthand for the remainder() function:
    print("% operator", a % 2)

    The result of the % operator is shown as follows:

    % operator [0 1 0 1 0 1 0 1]
    
  4. The fmod() function handles negative numbers differently than mod(), fmod(), and % do. The sign of the remainder is the sign of the dividend, and the sign of the divisor has no influence on the results:
    print("Fmod", np.fmod(a, 2))

    The fmod() result is printed as...

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