Python/project_euler/problem_072/sol1.py
Kamil 8d94f7745f
Euler072 - application of vector operations to reduce calculation time and refactoring numpy (#9229)
* Replacing the generator with numpy vector operations from lu_decomposition.

* Revert "Replacing the generator with numpy vector operations from lu_decomposition."

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* Application of vector operations  to reduce calculation time and refactoring numpy.

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Python

"""
Problem 72 Counting fractions: https://projecteuler.net/problem=72
Description:
Consider the fraction, n/d, where n and d are positive integers. If n<d and HCF(n,d)=1,
it is called a reduced proper fraction.
If we list the set of reduced proper fractions for d ≤ 8 in ascending order of size, we
get: 1/8, 1/7, 1/6, 1/5, 1/4, 2/7, 1/3, 3/8, 2/5, 3/7, 1/2, 4/7, 3/5, 5/8, 2/3, 5/7,
3/4, 4/5, 5/6, 6/7, 7/8
It can be seen that there are 21 elements in this set.
How many elements would be contained in the set of reduced proper fractions for
d ≤ 1,000,000?
Solution:
Number of numbers between 1 and n that are coprime to n is given by the Euler's Totient
function, phi(n). So, the answer is simply the sum of phi(n) for 2 <= n <= 1,000,000
Sum of phi(d), for all d|n = n. This result can be used to find phi(n) using a sieve.
Time: 1 sec
"""
import numpy as np
def solution(limit: int = 1_000_000) -> int:
"""
Returns an integer, the solution to the problem
>>> solution(10)
31
>>> solution(100)
3043
>>> solution(1_000)
304191
"""
# generating an array from -1 to limit
phi = np.arange(-1, limit)
for i in range(2, limit + 1):
if phi[i] == i - 1:
ind = np.arange(2 * i, limit + 1, i) # indexes for selection
phi[ind] -= phi[ind] // i
return np.sum(phi[2 : limit + 1])
if __name__ == "__main__":
print(solution())