I'm learning python 3 and am doing some of the Codeeval stuff and I need to generate a list of prime numbers.
So I wrote a function that would check if a number is prime, and I wasn't getting the answer I was looking for so I found a similar function on this site that does work. However, technically (unless I'm not seeing something) they should produce the same output.
The "trouble" area is in the isPrime function in the range
Both int(n ** .5 +1) and math.ceil(math.sqrt(n)) produce the same value.
So my question is: Why do I end up with a different output between those two ways of getting the square root of a number?
def isPrime(n):
if n == 2:
return True
elif n < 2 or n % 2 == 0:
return False
# for i in range(3,int(n ** .5 + 1),2):
for i in range(3,math.ceil(math.sqrt(n)),2):
if n % i == 0: return False
return True
def generatePrimes(n):
primes = [2]
noOfPrimes = 1
idx = 3
while noOfPrimes < n:
if isPrime(idx):
primes.append(idx)
noOfPrimes+=1
idx += 2
return primes
print((generatePrimes(50)))
Your claim:
Both int(n ** .5 + 1) and math.ceil(math.sqrt(n)) produce the same value.
I disagree:
Let's look at the case when n == 9
int(n ** 0.5 + 1) == 4
math.ceil(math.sqrt(n)) == 3
The code, as written, produces 9, 49, 121, ... any square of a prime number. This is because the upper bound of range() is exclusive and you must add 1 to make it inclusive.
for i in range(3, math.ceil(math.sqrt(n)) + 1, 2):
# ^^^^
You seemed to remember this when using int(n ** .5 + 1), however. Or is that +1 in there for a different reason?
Related
I'm looking for help writing a function that takes a positive integer n as input and prints its prime factorization to the screen. The output should gather the factors together into a single string so that the results of a call like prime_factorization(60) would be to print the string “60 = 2 x 2 x 3 x 5” to the screen. The following is what I have so far.
UPDATE: I made progress and figured out how to find the prime factorization. However, I still need help printing it the correct way as mentioned above.
""""
Input is a positive integer n
Output is its prime factorization, computed as follows:
"""
import math
def prime_factorization(n):
while (n % 2) == 0:
print(2)
# Turn n into odd number
n = n / 2
for i in range (3, int(math.sqrt(n)) + 1, 2):
while (n % i) == 0:
print(i)
n = n / I
if (n > 2):
print(n)
prime_factorization(60)
Note that I am trying to print it so if the input is 60, the output reads " 60 = 2 x 2 x 3 x 5 "
You should always separate computation from presentation. You can build the function as a generator that divides the number by increasing divisors (2 and then odds). When you find one that fits, output it and continue with the result of the division. This will only produce prime factors.
Then use that function to obtain the data to print rather than trying to mix in the printing and formatting.
def primeFactors(N):
p,i = 2,1 # prime divisor and increment
while p*p<=N: # no need to go beyond √N
while N%p == 0: # if is integer divisor
yield p # output prime divisor
N //= p # remove it from the number
p,i = p+i,2 # advance to next potential divisor 2, 3, 5, ...
if N>1: yield N # remaining value is a prime if not 1
output:
N=60
print(N,end=" = ")
print(*primeFactors(N),sep=" x ")
60 = 2 x 2 x 3 x 5
Use a list to store all factors, then print them together in the required format as a string.
import math
def prime_factorization(n):
factors = [] # to store factors
while (n % 2) == 0:
factors.append(2)
# Turn n into odd number
n = n / 2
for i in range (3, int(math.sqrt(n)) + 1, 2):
while (n % i) == 0:
factors.append(i)
n = n / I
if (n > 2):
factors.append(n)
print(" x ".join(str(i) for i in factors)) # to get the required string
prime_factorization(60)
Here is a way of doing it with f-strings. In addition, you need to do integer division (with //) to avoid getting floats in your answer.
""""
Input is a positive integer n
Output is its prime factorization, computed as follows:
"""
import math
def prime_factorization(n):
n_copy = n
prime_list = []
while (n % 2) == 0:
prime_list.append(2)
# Turn n into odd number
n = n // 2
for i in range(3, int(math.sqrt(n)) + 1, 2):
while (n % i) == 0:
prime_list.append(i)
n = n // i
if (n > 2):
prime_list.append(n)
print(f'{n_copy} =', end = ' ')
for factor in prime_list[:-1]:
print (f'{factor} x', end=' ' )
print(prime_list[-1])
prime_factorization(60)
#output: 60 = 2 x 2 x 3 x 5
I have written a code of Wilson prime numbers and my code is working for most of the numbers but it's giving OverflowError: int too large to convert to float for very large numbers. Is there any way to write Wilson prime number code for very large numbers.
The main problem is for checking Wilson prime Wilson primes it should satisfy the following condition. Where P represents a prime number.
Then ((P-1)! + 1) / (P * P) should give a whole number.
And as you can see factorials are involved in this procedure, so for very large numbers it's pretty difficult.
My Code :
def am_i_wilson(n):
import math
n1 = math.sqrt(n)
n1 = math.ceil(n1)
c = 0
def fact(n):
num = 1
for i in range(2,n+1):
num = num*i
return num
if n <= 1:
return False
for i in range(2, n1 + 1):
if n%i == 0:
c+ = 1
if c != 0:
return False
x = (fact(n-1)+1)/((n**2)*1.0)
return x.is_integer()
In my code, I am returning True if the number is Wilson Prime else False. Here n is the number to check if it's Wilson prime or not.
I think this is the most efficient way
import math
def am_i_wilson(num):
if num < 2 or not all(n % i for i in range(2, num)):
return False
return (math.factorial(num - 1) + 1) % (num ** 2) == 0
or you can try this too
import math
def am_i_wilson(n):
if n <= 2:
return False
fact=math.factorial(n-1)
#this conditional checks that the number is prime or not
#this condition is called wilson theorem in number theory
if (fact+1)%n==0:
x = (fact+1)%(n**2)
if x==0:
return True
else:
return False
else:
return False
if anyone has any better method then please answer it.
Your program primarily relies on testing for primes and computing factorials. You separate out the factorial logic but embed an inefficient prime test -- it keeps testing remainders after it knows the number isn't prime! I would separate both out so that they can be tested and optimized independently of the Wilson prime test itself:
def factorial(n):
number = 1
for i in range(2, n + 1):
number *= i
return number
def am_i_prime(n):
if n < 2:
return False
if n % 2 == 0:
return n == 2
for divisor in range(3, int(n ** 0.5) + 1, 2):
if n % divisor == 0:
return False
return True
def am_i_wilson(n):
return am_i_prime(n) and (factorial(n - 1) + 1) % n ** 2 == 0
A more efficient approach, given a fixed target to test up to, would be to implement a prime sieve and for each prime encountered, while you're computing the sieve, test if it's a Wilson prime.
I've been experimenting with prime sieves recently. I did a quick modification (i.e. hack) to one of them written by Robert William Hanks and came up with this. Output first:
$ ./wilson_primes.py 10000
[5, 13, 563]
...so I suspect the Wikipedia article about Wilson primes is correct ;-)
import sys
def fact(n):
num = 1
for i in range(2, n+1):
num *= i
return num
def is_wilson(n):
return (fact(n-1)+1) % n**2 == 0
def rwh_primes1(n):
""" Returns a list of primes < n """
sieve = [True] * (n/2)
for i in range(3,int(n**0.5)+1,2):
if sieve[i/2]:
sieve[i*i/2::i] = [False] * ((n-i*i-1)/(2*i)+1)
# return [2] + [2*i+1 for i in xrange(1,n/2) if sieve[i]]
for i in range(1,n/2):
if sieve[i]:
p = 2*i + 1 # convert index to normal prime
if is_wilson(p): #
yield p #
if len(sys.argv) > 1:
N = int(float(sys.argv[1]))
else:
N = 10000 # default: 1e4 10,000
print [p for p in rwh_primes1(N)]
First I tried just the fact() function and was pleasantly surprised to see it can produce huge results. But it is very slow compared to the original prime sieve. Perhaps it could be made to run faster by remembering the last factorial computed and re-use that to skip part of next factorial computation.
EDIT
I changed fact() to remember its last result, as follows:
last_fact = 1
last_n = 1
def fact2(n):
global last_fact, last_n
num = last_fact
for i in range(last_n+1, n+1):
num *= i
last_n = n
last_fact = num
return num
def is_wilson(n):
return (fact2(n-1)+1) % n**2 == 0
That did speed it up quite a bit. cProfile shows that is_wilson() is now the bottleneck. I can't think of an easy way to make it faster.
I'm trying to solve this problem in hackerrank. At some point I have to check if a number divides n(given input) or not.
This code works perfectly well except one test case(not an issue):
if __name__ == '__main__':
tc = int(input().strip())
for i_tc in range(tc):
n = int(input().strip())
while n % 2 == 0 and n is not 0:
n >>= 1
last = 0
for i in range(3, int(n ** 0.5), 2):
while n % i == 0 and n > 0:
last = n
n = n // i # Concentrate here
print(n if n > 2 else last)
Now you can see that I'm dividing the number only when i is a factor of n.For example if the numbers be i = 2 and n = 4 then n / 2 and n // 2 doesn't make any difference right.
But when I use the below code all test cases are getting failed:
if __name__ == '__main__':
tc = int(input().strip())
for i_tc in range(tc):
n = int(input().strip())
while n % 2 == 0 and n is not 0:
n >>= 1
last = 0
for i in range(3, int(n ** 0.5), 2):
while n % i == 0 and n > 0:
last = n
n = n / i # Notice this is not //
print(n if n > 2 else last)
This is not the first time.Even for this problem I faced the same thing.For this problem I have to only divide by 2 so I used right shift operator to get rid of this.But here I can't do any thing since right shift can't help me.
Why is this happening ? If the numbers are small I can't see any difference but as the number becomes larger it is somehow behaving differently.
It is not even intuitive to use // when / fails. What is the reason for this ?
The main reason of the difference between n // i and n / i given that n and i are of type int and n % i == 0 is that
the type of n // i is still int whereas the type of n / i is float and
integers in Python have unlimited precision whereas the precision of floats is limited.
Therefore, if the value of n // i is outside the range that is accurately representable by the python float type, then it will be not equal to the computed value of n / i.
Illustration:
>>> (10**16-2)/2 == (10**16-2)//2
True
>>> (10**17-2)/2 == (10**17-2)//2
False
>>> int((10**17-2)//2)
49999999999999999
>>> int((10**17-2)/2)
50000000000000000
>>>
I've written this function to calculate sin(x) using Taylor series to any specified degree of accuracy, 'N terms', my problem is the results aren't being returned as expected and I can't figure out why, any help would be appreciated.
What is am expecting is:
1 6.28318530718
2 -35.0585169332
3 46.5467323429
4 -30.1591274102
5 11.8995665347
6 -3.19507604213
7 0.624876542716
8 -0.0932457590621
9 0.0109834031461
What I am getting is:
1 None
2 6.28318530718
3 -35.0585169332
4 46.5467323429
5 -30.1591274102
6 11.8995665347
7 -3.19507604213
8 0.624876542716
9 -0.0932457590621
Thanks in advance.
def factorial(x):
if x <= 1:
return 1
else:
return x * factorial(x-1)
def sinNterms(x, N):
x = float(x)
while N >1:
result = x
for i in range(2, N):
power = ((2 * i)-1)
sign = 1
if i % 2 == 0:
sign = -1
else:
sign = 1
result = result + (((x ** power)*sign) / factorial(power))
return result
pi = 3.141592653589793
for i in range(1,10):
print i, sinNterms(2*pi, i)
I see that you are putting the return under the for which will break it out of the while loop. You should explain if this is what you mean to do. However, given the for i in range(1,10): means that you will ignore the first entry and return None when the input argument i is 1. Is this really what you wanted? Also, since you always exit after the calculation, you should not do a while N > 1 but use if N > 1 to avoid infinite recursion.
The reason why your results are off is because you are using range incorrectly. range(2, N) gives you a list of numbers from 2 to N-1. Thus range(2, 2) gives you an empty list.
You should calculate the range(2, N+1)
def sinNterms(x, N):
x = float(x)
while N >1:
result = x
for i in range(2, N):
Your comment explains that you have the lines of code in the wrong order. You should have
def sinNterms(x, N):
x = float(x)
result = x
# replace the while with an if since you do not need a loop
# Otherwise you would get an infinite recursion
if N > 1:
for i in range(2, N+1):
power = ((2 * i)-1)
sign = 1
if i % 2 == 0:
sign = -1
# The else is not needed as this is the default
# else:
# sign = 1
# use += operator for the calculation
result += (((x ** power)*sign) / factorial(power))
# Now return the value with the indentation under the if N > 1
return result
Note that in order to handle things set factorial to return a float not an int.
An alternative method that saves some calculations is
def sinNterms(x, N):
x = float(x)
lim = 1e-12
result = 0
sign = 1
# This range gives the odd numbers, saves calculation.
for i in range(1, 2*(N+1), 2):
# use += operator for the calculation
temp = ((x ** i)*sign) / factorial(i)
if fabs(temp) < lim:
break
result += temp
sign *= -1
return result
I am trying to find an efficient way to compute Euler's totient function.
What is wrong with this code? It doesn't seem to be working.
def isPrime(a):
return not ( a < 2 or any(a % i == 0 for i in range(2, int(a ** 0.5) + 1)))
def phi(n):
y = 1
for i in range(2,n+1):
if isPrime(i) is True and n % i == 0 is True:
y = y * (1 - 1/i)
else:
continue
return int(y)
Here's a much faster, working way, based on this description on Wikipedia:
Thus if n is a positive integer, then φ(n) is the number of integers k in the range 1 ≤ k ≤ n for which gcd(n, k) = 1.
I'm not saying this is the fastest or cleanest, but it works.
from math import gcd
def phi(n):
amount = 0
for k in range(1, n + 1):
if gcd(n, k) == 1:
amount += 1
return amount
You have three different problems...
y needs to be equal to n as initial value, not 1
As some have mentioned in the comments, don't use integer division
n % i == 0 is True isn't doing what you think because of Python chaining the comparisons! Even if n % i equals 0 then 0 == 0 is True BUT 0 is True is False! Use parens or just get rid of comparing to True since that isn't necessary anyway.
Fixing those problems,
def phi(n):
y = n
for i in range(2,n+1):
if isPrime(i) and n % i == 0:
y *= 1 - 1.0/i
return int(y)
Calculating gcd for every pair in range is not efficient and does not scales. You don't need to iterate throught all the range, if n is not a prime you can check for prime factors up to its square root, refer to https://stackoverflow.com/a/5811176/3393095.
We must then update phi for every prime by phi = phi*(1 - 1/prime).
def totatives(n):
phi = int(n > 1 and n)
for p in range(2, int(n ** .5) + 1):
if not n % p:
phi -= phi // p
while not n % p:
n //= p
#if n is > 1 it means it is prime
if n > 1: phi -= phi // n
return phi
I'm working on a cryptographic library in python and this is what i'm using. gcd() is Euclid's method for calculating greatest common divisor, and phi() is the totient function.
def gcd(a, b):
while b:
a, b=b, a%b
return a
def phi(a):
b=a-1
c=0
while b:
if not gcd(a,b)-1:
c+=1
b-=1
return c
Most implementations mentioned by other users rely on calling a gcd() or isPrime() function. In the case you are going to use the phi() function many times, it pays of to calculated these values before hand. A way of doing this is by using a so called sieve algorithm.
https://stackoverflow.com/a/18997575/7217653 This answer on stackoverflow provides us with a fast way of finding all primes below a given number.
Oke, now we can replace isPrime() with a search in our array.
Now the actual phi function:
Wikipedia gives us a clear example: https://en.wikipedia.org/wiki/Euler%27s_totient_function#Example
phi(36) = phi(2^2 * 3^2) = 36 * (1- 1/2) * (1- 1/3) = 30 * 1/2 * 2/3 = 12
In words, this says that the distinct prime factors of 36 are 2 and 3; half of the thirty-six integers from 1 to 36 are divisible by 2, leaving eighteen; a third of those are divisible by 3, leaving twelve numbers that are coprime to 36. And indeed there are twelve positive integers that are coprime with 36 and lower than 36: 1, 5, 7, 11, 13, 17, 19, 23, 25, 29, 31, and 35.
TL;DR
With other words: We have to find all the prime factors of our number and then multiply these prime factors together using foreach prime_factor: n *= 1 - 1/prime_factor.
import math
MAX = 10**5
# CREDIT TO https://stackoverflow.com/a/18997575/7217653
def sieve_for_primes_to(n):
size = n//2
sieve = [1]*size
limit = int(n**0.5)
for i in range(1,limit):
if sieve[i]:
val = 2*i+1
tmp = ((size-1) - i)//val
sieve[i+val::val] = [0]*tmp
return [2] + [i*2+1 for i, v in enumerate(sieve) if v and i>0]
PRIMES = sieve_for_primes_to(MAX)
print("Primes generated")
def phi(n):
original_n = n
prime_factors = []
prime_index = 0
while n > 1: # As long as there are more factors to be found
p = PRIMES[prime_index]
if (n % p == 0): # is this prime a factor?
prime_factors.append(p)
while math.ceil(n / p) == math.floor(n / p): # as long as we can devide our current number by this factor and it gives back a integer remove it
n = n // p
prime_index += 1
for v in prime_factors: # Now we have the prime factors, we do the same calculation as wikipedia
original_n *= 1 - (1/v)
return int(original_n)
print(phi(36)) # = phi(2**2 * 3**2) = 36 * (1- 1/2) * (1- 1/3) = 36 * 1/2 * 2/3 = 12
It looks like you're trying to use Euler's product formula, but you're not calculating the number of primes which divide a. You're calculating the number of elements relatively prime to a.
In addition, since 1 and i are both integers, so is the division, in this case you always get 0.
With regards to efficiency, I haven't noticed anyone mention that gcd(k,n)=gcd(n-k,n). Using this fact can save roughly half the work needed for the methods involving the use of the gcd. Just start the count with 2 (because 1/n and (n-1)/k will always be irreducible) and add 2 each time the gcd is one.
Here is a shorter implementation of orlp's answer.
from math import gcd
def phi(n): return sum([gcd(n, k)==1 for k in range(1, n+1)])
As others have already mentioned it leaves room for performance optimization.
Actually to calculate phi(any number say n)
We use the Formula
where p are the prime factors of n.
So, you have few mistakes in your code:
1.y should be equal to n
2. For 1/i actually 1 and i both are integers so their evaluation will also be an integer,thus it will lead to wrong results.
Here is the code with required corrections.
def phi(n):
y = n
for i in range(2,n+1):
if isPrime(i) and n % i == 0 :
y -= y/i
else:
continue
return int(y)