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Fibonacci Numbers

# fibonacci.py
"""
Calculates the Fibonacci sequence using iteration, recursion, memoization,
and a simplified form of Binet's formula

NOTE 1: the iterative, recursive, memoization functions are more accurate than
the Binet's formula function because the Binet formula function  uses floats

NOTE 2: the Binet's formula function is much more limited in the size of inputs
that it can handle due to the size limitations of Python floats

RESULTS: (n = 20)
fib_iterative runtime: 0.0055 ms
fib_recursive runtime: 6.5627 ms
fib_memoization runtime: 0.0107 ms
fib_binet runtime: 0.0174 ms
"""

from functools import lru_cache
from math import sqrt
from time import time


def time_func(func, *args, **kwargs):
    """
    Times the execution of a function with parameters
    """
    start = time()
    output = func(*args, **kwargs)
    end = time()
    if int(end - start) > 0:
        print(f"{func.__name__} runtime: {(end - start):0.4f} s")
    else:
        print(f"{func.__name__} runtime: {(end - start) * 1000:0.4f} ms")
    return output


def fib_iterative(n: int) -> list[int]:
    """
    Calculates the first n (0-indexed) Fibonacci numbers using iteration
    >>> fib_iterative(0)
    [0]
    >>> fib_iterative(1)
    [0, 1]
    >>> fib_iterative(5)
    [0, 1, 1, 2, 3, 5]
    >>> fib_iterative(10)
    [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55]
    >>> fib_iterative(-1)
    Traceback (most recent call last):
        ...
    Exception: n is negative
    """
    if n < 0:
        raise Exception("n is negative")
    if n == 0:
        return [0]
    fib = [0, 1]
    for _ in range(n - 1):
        fib.append(fib[-1] + fib[-2])
    return fib


def fib_recursive(n: int) -> list[int]:
    """
    Calculates the first n (0-indexed) Fibonacci numbers using recursion
    >>> fib_iterative(0)
    [0]
    >>> fib_iterative(1)
    [0, 1]
    >>> fib_iterative(5)
    [0, 1, 1, 2, 3, 5]
    >>> fib_iterative(10)
    [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55]
    >>> fib_iterative(-1)
    Traceback (most recent call last):
        ...
    Exception: n is negative
    """

    def fib_recursive_term(i: int) -> int:
        """
        Calculates the i-th (0-indexed) Fibonacci number using recursion
        """
        if i < 0:
            raise Exception("n is negative")
        if i < 2:
            return i
        return fib_recursive_term(i - 1) + fib_recursive_term(i - 2)

    if n < 0:
        raise Exception("n is negative")
    return [fib_recursive_term(i) for i in range(n + 1)]


def fib_recursive_cached(n: int) -> list[int]:
    """
    Calculates the first n (0-indexed) Fibonacci numbers using recursion
    >>> fib_iterative(0)
    [0]
    >>> fib_iterative(1)
    [0, 1]
    >>> fib_iterative(5)
    [0, 1, 1, 2, 3, 5]
    >>> fib_iterative(10)
    [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55]
    >>> fib_iterative(-1)
    Traceback (most recent call last):
        ...
    Exception: n is negative
    """

    @lru_cache(maxsize=None)
    def fib_recursive_term(i: int) -> int:
        """
        Calculates the i-th (0-indexed) Fibonacci number using recursion
        """
        if i < 0:
            raise Exception("n is negative")
        if i < 2:
            return i
        return fib_recursive_term(i - 1) + fib_recursive_term(i - 2)

    if n < 0:
        raise Exception("n is negative")
    return [fib_recursive_term(i) for i in range(n + 1)]


def fib_memoization(n: int) -> list[int]:
    """
    Calculates the first n (0-indexed) Fibonacci numbers using memoization
    >>> fib_memoization(0)
    [0]
    >>> fib_memoization(1)
    [0, 1]
    >>> fib_memoization(5)
    [0, 1, 1, 2, 3, 5]
    >>> fib_memoization(10)
    [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55]
    >>> fib_iterative(-1)
    Traceback (most recent call last):
        ...
    Exception: n is negative
    """
    if n < 0:
        raise Exception("n is negative")
    # Cache must be outside recursuive function
    # other it will reset every time it calls itself.
    cache: dict[int, int] = {0: 0, 1: 1, 2: 1}  # Prefilled cache

    def rec_fn_memoized(num: int) -> int:
        if num in cache:
            return cache[num]

        value = rec_fn_memoized(num - 1) + rec_fn_memoized(num - 2)
        cache[num] = value
        return value

    return [rec_fn_memoized(i) for i in range(n + 1)]


def fib_binet(n: int) -> list[int]:
    """
    Calculates the first n (0-indexed) Fibonacci numbers using a simplified form
    of Binet's formula:
    https://en.m.wikipedia.org/wiki/Fibonacci_number#Computation_by_rounding

    NOTE 1: this function diverges from fib_iterative at around n = 71, likely
    due to compounding floating-point arithmetic errors

    NOTE 2: this function doesn't accept n >= 1475 because it overflows
    thereafter due to the size limitations of Python floats
    >>> fib_binet(0)
    [0]
    >>> fib_binet(1)
    [0, 1]
    >>> fib_binet(5)
    [0, 1, 1, 2, 3, 5]
    >>> fib_binet(10)
    [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55]
    >>> fib_binet(-1)
    Traceback (most recent call last):
        ...
    Exception: n is negative
    >>> fib_binet(1475)
    Traceback (most recent call last):
        ...
    Exception: n is too large
    """
    if n < 0:
        raise Exception("n is negative")
    if n >= 1475:
        raise Exception("n is too large")
    sqrt_5 = sqrt(5)
    phi = (1 + sqrt_5) / 2
    return [round(phi**i / sqrt_5) for i in range(n + 1)]


if __name__ == "__main__":
    num = 30
    time_func(fib_iterative, num)
    time_func(fib_recursive, num)  # Around 3s runtime
    time_func(fib_recursive_cached, num)  # Around 0ms runtime
    time_func(fib_memoization, num)
    time_func(fib_binet, num)
About this Algorithm

In mathematics, the Fibonacci numbers commonly denoted F(n), form a sequence, called the Fibonacci sequence, such that each number is the sum of the two preceding ones, starting from 0 and 1. The Sequence looks like this:

[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, ...]

Applications

Finding N-th member of this sequence would be useful in many Applications:

  • Recently Fibonacci sequence and the golden ratio are of great interest to researchers in many fields of

science including high energy physics, quantum mechanics, Cryptography and Coding.

Steps

  1. Prepare Base Matrice
  2. Calculate the power of this Matrice
  3. Take Corresponding value from Matrix

Example

Find 8-th member of Fibonacci

Step 0

| F(n+1)  F(n)  |
| F(n)    F(n-1)|

Step 1

Calculate matrix^1
| 1 1 |
| 1 0 |

Step 2

Calculate matrix^2
| 2 1 |
| 1 1 |

Step 3

Calculate matrix^4
| 5 3 |
| 3 2 |

Step 4

Calculate matrix^8
| 34 21 |
| 21 13 |

Step 5

F(8)=21

Implementation

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