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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
Author Profile Icon Claus Fuhrer
Claus Fuhrer
Olivier Verdier Olivier Verdier
Author Profile Icon Olivier Verdier
Olivier Verdier
Claus Führer Claus Führer
Author Profile Icon Claus Führer
Claus Führer
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Toc

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

Class attributes

Attributes specified in the class declaration are called class attributes. Consider the following example:

class Newton:
    tol = 1e-8 # this is a class attribute
    def __init__(self,f):
        self.f = f # this is not a class attribute
    ....

Class attributes are useful for simulating default values and can be used if values have to be reset:

N1 = Newton(f)
N2 = Newton(g)

Both instances have an attribute, tol, with the value initialized in the class definition:

N1.tol # 1e-8
N2.tol # 1e-8

Altering the class attribute automatically affects all the corresponding attributes of all instances:

Newton.tol = 1e-10
N1.tol # 1e-10
N2.tol # 1e-10

Altering tol for one instance does not affect the other instance:

N2.tol = 1.e-4
N1.tol  # still 1.e-10

But now N2.tol is detached from the class attribute. Changing Newton.tol no longer has any effect on N2.tol:

Newton.tol = 1e-5 # now all instances of the Newton classes have 1e-5
N1.tol # 1.e-5
N2.tol # 1e-4 but not...
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