added several modules
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# Python module for approximating the fixpoint of special linear functions
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# _ _ _ _
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# __ ___ __(_) |_| |_ ___ _ __ | |__ _ _
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# \ \ /\ / / '__| | __| __/ _ \ '_ \ | '_ \| | | |
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# \ V V /| | | | |_| || __/ | | | | |_) | |_| |
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# \_/\_/ |_| |_|\__|\__\___|_| |_| |_.__/ \__, |
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# |___/
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# ____ __ __ _
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# / ___|_ _____ _ __ \ \ / /__ __ _ ___| |
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# \___ \ \ / / _ \ '_ \ \ \ / / _ \ / _` |/ _ \ |
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# ___) \ V / __/ | | | \ V / (_) | (_| | __/ |
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# |____/ \_/ \___|_| |_| \_/ \___/ \__, |\___|_|
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# |___/
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# Licensed under the GPLv2 License, Version 2.0 (the "License");
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# Copyright (c) Sven Vogel
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# iteratively approximate the fixpoint of specific linear functions
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def fixpoint_approximation(start, function, iterations):
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x = start
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for _ in range(iterations):
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x = function(x)
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return x
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# in order to work the linear function has to be in the form:
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# ]-1.0, 1.0[ * x + k
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def linear_function(x):
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return 0.25 * x - 3
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def test():
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print("fixpoint approximation: ", fixpoint_approximation(start=1.0, function=linear_function, iterations=400))
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# Python module for linearly approximating the derivative of any function
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# _ _ _ _
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# __ ___ __(_) |_| |_ ___ _ __ | |__ _ _
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# \ \ /\ / / '__| | __| __/ _ \ '_ \ | '_ \| | | |
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# \ V V /| | | | |_| || __/ | | | | |_) | |_| |
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# \_/\_/ |_| |_|\__|\__\___|_| |_| |_.__/ \__, |
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# |___/
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# ____ __ __ _
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# / ___|_ _____ _ __ \ \ / /__ __ _ ___| |
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# \___ \ \ / / _ \ '_ \ \ \ / / _ \ / _` |/ _ \ |
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# ___) \ V / __/ | | | \ V / (_) | (_| | __/ |
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# |____/ \_/ \___|_| |_| \_/ \___/ \__, |\___|_|
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# |___/
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# Licensed under the GPLv2 License, Version 2.0 (the "License");
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# Copyright (c) Sven Vogel
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# linearly approximate a functions derivative in an interval
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def linear_approximate(interval, function):
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return (function(interval[1]) - function(interval[0])) / (interval[1] - interval[0])
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# function to linearly approximate
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def f(x):
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return 3 + x * x - 5 * x
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def test():
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print("linear approximation: ", linear_approximate([2.0, 3.0], f))
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# Python file for testing various approximation algorithms
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# _ _ _ _
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# __ ___ __(_) |_| |_ ___ _ __ | |__ _ _
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# \ \ /\ / / '__| | __| __/ _ \ '_ \ | '_ \| | | |
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# \ V V /| | | | |_| || __/ | | | | |_) | |_| |
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# \_/\_/ |_| |_|\__|\__\___|_| |_| |_.__/ \__, |
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# |___/
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# ____ __ __ _
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# / ___|_ _____ _ __ \ \ / /__ __ _ ___| |
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# \___ \ \ / / _ \ '_ \ \ \ / / _ \ / _` |/ _ \ |
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# ___) \ V / __/ | | | \ V / (_) | (_| | __/ |
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# |____/ \_/ \___|_| |_| \_/ \___/ \__, |\___|_|
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# |___/
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# Licensed under the GPLv2 License, Version 2.0 (the "License");
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# Copyright (c) Sven Vogel
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import fixpoint_approximation
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import linear_approximation
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import newton_polynom
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# linear_approximation.test()
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# fixpoint_approximation.test()
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newton_polynom.test()
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# Python module for calculating the newton polynom from given points
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# _ _ _ _
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# __ ___ __(_) |_| |_ ___ _ __ | |__ _ _
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# \ \ /\ / / '__| | __| __/ _ \ '_ \ | '_ \| | | |
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# \ V V /| | | | |_| || __/ | | | | |_) | |_| |
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# \_/\_/ |_| |_|\__|\__\___|_| |_| |_.__/ \__, |
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# |___/
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# ____ __ __ _
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# / ___|_ _____ _ __ \ \ / /__ __ _ ___| |
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# \___ \ \ / / _ \ '_ \ \ \ / / _ \ / _` |/ _ \ |
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# ___) \ V / __/ | | | \ V / (_) | (_| | __/ |
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# |____/ \_/ \___|_| |_| \_/ \___/ \__, |\___|_|
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# |___/
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# Licensed under the GPLv2 License, Version 2.0 (the "License");
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# Copyright (c) Sven Vogel
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def combine(p0, p1):
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return (p1[1] - p1[0]) / (p0[1] - p0[0])
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def combine_n(*points):
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k = len(points) - 1
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if k == 1:
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return combine(points[0], points[1])
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else:
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return (combine_n(points[1:k]) - combine_n(points[0:(k - 1)])) / (points[k][0] - points[0][0])
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def newton_polynom(*points):
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for x in range(len(points)):
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print(combine_n(points[0:x]))
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for y in range(x):
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print(format(" * (x - %s)", points[y][0]))
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def test():
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newton_polynom([1, 2], [3, 4], [9, -5])
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