Algorithm of finding numbers - python

Write a recursive algorithm which enumerates dominant primes. Your algorithm should print dominant primes as it finds them (rather than at the end).By default we limit the dominant primes we are looking for to a maximum value of 10^12, the expected run time should be around or less than a minute.
The following is my python code which doesn't work as expected:
import math
def test_prime(n):
k = 2
maxk = int(math.sqrt(n))
while k <= maxk:
if n % k == 0:
return False
if k == 2:
k += 1
else:
k += 2
return (n is not 1)
def dominant_prime_finder(maxprime=10**12,n=1):
l = 1 #length of the current number
while n // 10 > 0:
l += 1
n //= 10
if test_prime(n) == True:
is_dominant_prime = True
index_smaller = n
while l > 1 and index_smaller > 9:
index_smaller //= 10
if test_prime(index_smaller) == False:
is_dominant_prime = False
break
for i in range(1,10):
if test_prime(i*10**l + n) == True:
is_dominant_prime = False
break
if is_dominant_prime == True:
print(n)
while n <= maxprime:
dominant_prime_finder()

You can solve the problem without enumerating all the numbers under 10^12 which is inefficient by doing a recursion on the length of the number.
It works the following way:
The prime number of length 1 are: 2,3,5,7.
For all these numbers check the third condition, for any digit dn+1∈{1,…,9} , dn+1dn…d0 is not prime. For 2 it's okay. For 3 it fails (13 for instance). Store all the prime you find in a list L. Do this for all the prime of length 1.
In L you now have all the prime number of length 2 with a prime as first digit, thus you have all the candidates for dominant prime of length 2
Doing this recursively gets you all the dominant prime, in python:
def test_prime(n):
k = 2
maxk = int(math.sqrt(n))
while k <= maxk:
if n % k == 0:
return False
if k == 2:
k += 1
else:
k += 2
return (n is not 1)
def check_add_digit(number,length):
res = []
for i in range(1,10):
if test_prime( i*10**(length) + number ):
res.append(i*10**(length) + number)
return res
def one_step(list_prime,length):
## Under 10^12
if length > 12:
return None
for prime in list_prime:
res = check_add_digit(prime,length)
if len(res) == 0:
#We have a dominant prime stop
print(prime)
else:
#We do not have a dominant prime but a list of candidates for length +1
one_step(res,length+1)
one_step([2,3,5,7], length=1)
This works in under a minute on my machine.

Well, there are several issues with this code:
You modify the original n at the beginning (n //= 10). This basically causes n to always be one digit. Use another variable instead:
m = n
while m // 10 > 0:
l += 1
m //= 10
Your recursive call doesn't update n, so you enter an infinite loop:
while n <= maxprime:
dominant_prime_finder()
Replace with:
if n <= maxprime:
dominant_prime_finder(maxprime, n + 1)
Even after fixing these issues, you'll cause a stack overflow simply because the dominant prime numbers are very far apart (2, 5, 3733, 59399...). So instead of using a recursive approach, use, for example, a generator:
def dominant_prime_finder(n=1):
while True:
l = 1 #length of the current number
m = n
while m // 10 > 0:
l += 1
m //= 10
if test_prime(n):
is_dominant_prime = True
index_smaller = n
while l > 1 and index_smaller > 9:
index_smaller //= 10
if not test_prime(index_smaller):
is_dominant_prime = False
break
for i in range(1,10):
if test_prime(i*10**l + n):
is_dominant_prime = False
break
if is_dominant_prime:
yield n
n = n + 1
g = dominant_prime_finder()
for i in range(1, 10): # find first 10 dominant primes
print(g.next())

This problem is cool. Here's how we can elaborate the recurrence:
def dominant_prime_finder(maxprime=10**12):
def f(n):
if n > maxprime:
return
is_dominant = True
power = 10**(math.floor(math.log(n, 10)) + 1)
for d in xrange(1, 10):
candidate = d * power + n
if test_prime(candidate):
f(candidate)
is_dominant = False
if is_dominant:
print int(n)
for i in [2,3,5,7]:
f(i)

Related

Looking to bring runtime under 20 seconds

The following program, balanced_centrifuge(), takes positive integers (n, k), where k <= n, and determines whether k and n-k can be expressed as a sum of the prime factors of n (note, repetition of factors is allowed). I've been able to walk through the logic of this code and it makes sense, but the runtime is over 20 seconds which is too slow for my tester. It works for all the suggested test cases however, (6,3), (7,0), (15,8), (222, 107), and (1234, 43). Where is the slowdown occurring?
import itertools
def balanced_centrifuge(n,k):
if n == 1:
return False
if k == 0 or n - k == 0:
return True
primes = get_primes(n)
final_answer = is_sum(primes, k) and is_sum(primes,n-k)
return final_answer
def get_primes(n):
i = 2
factors = []
while i * i <= n:
if n % i != 0:
i += 1
else:
n //= i
factors.append(i)
if n > 1:
factors.append(n)
return factors
def is_sum(primes, goal):
if primes == []:
return False
for i in range(goal//primes[0]+1, 0, -1):
ans = itertools.combinations_with_replacement(primes, i)
for comb in ans:
#print(comb)
# single tuple with i elements to try
if sum(comb) == goal:
return True
return False

Function doesn't return anything after giving a big number as an argument

I'm learning Python by doing Project Euler questions and am stuck on Problem #3.
I think I've found a solution that works, but when inserting the large number 600851475143 it just doesn't return anything. I believe that it just loads and loads cause even with 6008514 it takes 10 secs to return the answer.
# What is the largest prime factor of the number x?
import math
def isPrime(x):
try:
sqr = math.sqrt(x)
if x == 0 or x == 1:
return 0
for n in range (2 , int(sqr)+1):
if x % n == 0:
return 0
return 1
except:
return 'Give positive numbers.'
def largestPrimeFactor(x):
if isPrime(x) == 1:
return 'This number is prime.'
else:
largest = -1
mid = x/2
for n in range(2,int(mid)+1):
if isPrime(n):
if x % n == 0:
largest = n
if largest == -1:
return 'Enter numbers above 1.'
else:
return largest
print(largestPrimeFactor(600851475143))
This code should work:
import math
def isPrime(x):
try:
sqr = math.sqrt(x)
if x == 0 or x == 1:
return 0
n = 2
highest = x
while n < highest:
if x%n ==0:
return 0
highest = x/ n
n +=1
return 1
except:
return 'Give positive numbers.'
def largestPrimeFactor(x):
if isPrime(x) == 1:
return 'This number is prime.'
n = 2
highest = x
largest = 1
while n < highest:
if x%n == 0:
if isPrime(n):
largest = n
highest = x/n
n +=1
return largest
print(largestPrimeFactor(600851475143))
I made an optimization:
you check if every number is a factor of x while if for example 2 is not a factor of x for sure the maximum factor of x can be x/2. Hence if n is not a factor of x the maximum possible factor of x can just be x/n.
The code for large numbers just takes really long time, as pointed out by comments. I report other bugs.
Bug 1. Inappropriate use of try/except clause. It is recommended that try contains a single command and except catches the error. PEP8 also recommends specifying the type of error. Moreover, for your function, the error is never raised.
Bug 2. Redundancy. If x is not prime, you call isPrime for each value (let's call it i) from 2 to x/2. isPrime cycles for each number from 2 to sqrt(i). Therefore, isPrime(i) takes O(sqrt(i)) time, and we call it for i from 2 to x/2. Roughly, its running time is about O(x^(3/2)). Even if don't know a more optimal approach, this approach asks for memoization.
i have another way:
def Largest_Prime_Factor(n):
prime_factor = 1
i = 2
while i <= n / i:
if n % i == 0:
prime_factor = i
n /= i
else:
i += 1
if prime_factor < n:
prime_factor = n
return prime_factor
it faster than previous
try it:
import math
def maxPrimeFactors (n):
maxPrime = -1
while n % 2 == 0:
maxPrime = 2
n >>= 1
for i in range(3, int(math.sqrt(n)) + 1, 2):
while n % i == 0:
maxPrime = i
n = n / i
if n > 2:
maxPrime = n
return int(maxPrime)
n = 600851475143
print(maxPrimeFactors(n))

Primenumber position search ends in too big scale what to do?

def isprime(number):
counter = 0
for n in range(1,number+1):
if number % n == 0:
counter += 1
if counter == 2:
return True
This is a function to check whether the number is prime at all.
my_list = []
n1 = 1
while len(my_list) <= 10000:
n1 += 1
if isprime(n1) is True:
my_list.append(n1)
print(my_list[-1])
So this is my code for now, it works totally fine but is not optimized at all and I wanted to learn from bottom up how to make such a function faster, so that my computer is able to do the calculations.
I tried to find the 10001 prime number.
(started with zero so that is the reason for the <= 10000)
For numbers the size you need to solve Project Euler #7, it is sufficient to determine primality by trial division. Here is a simple primality checker using a 2,3,5-wheel, which is about twice as fast as the naive primality checker posted by Yakov Dan:
def isPrime(n): # 2,3,5-wheel
ws = [1,2,2,4,2,4,2,4,6,2,6]
w, f = 0, 2
while f * f <= n:
if n % f == 0:
return False
f = f + ws[w]
w = w + 1
if w == 11: w = 3
return True
For larger numbers, it is better to use a Miller-Rabin primality checker:
def isPrime(n, k=5): # miller-rabin
from random import randint
if n < 2: return False
for p in [2,3,5,7,11,13,17,19,23,29]:
if n % p == 0: return n == p
s, d = 0, n-1
while d % 2 == 0:
s, d = s+1, d/2
for i in range(k):
x = pow(randint(2, n-1), d, n)
if x == 1 or x == n-1: continue
for r in range(1, s):
x = (x * x) % n
if x == 1: return False
if x == n-1: break
else: return False
return True
Either of those methods will be much slower than the Sieve of Eratosthenes, invented over two thousand years ago by a Greek mathematician:
def primes(n): # sieve of eratosthenes
i, p, ps, m = 0, 3, [2], n // 2
sieve = [True] * m
while p <= n:
if sieve[i]:
ps.append(p)
for j in range((p*p-3)/2, m, p):
sieve[j] = False
i, p = i+1, p+2
return ps
To solve Project Euler #7, call the sieve with n = 120000 and discard the excess primes. It will be more convenient for you to use a sieve in the form of a generator:
def primegen(start=0): # stackoverflow.com/a/20660551
if start <= 2: yield 2 # prime (!) the pump
if start <= 3: yield 3 # prime (!) the pump
ps = primegen() # sieving primes
p = next(ps) and next(ps) # first sieving prime
q = p * p; D = {} # initialization
def add(m, s): # insert multiple/stride
while m in D: m += s # find unused multiple
D[m] = s # save multiple/stride
while q <= start: # initialize multiples
x = (start // p) * p # first multiple of p
if x < start: x += p # must be >= start
if x % 2 == 0: x += p # ... and must be odd
add(x, p+p) # insert in sieve
p = next(ps) # next sieving prime
q = p * p # ... and its square
c = max(start-2, 3) # first prime candidate
if c % 2 == 0: c += 1 # candidate must be odd
while True: # infinite list
c += 2 # next odd candidate
if c in D: # c is composite
s = D.pop(c) # fetch stride
add(c+s, s) # add next multiple
elif c < q: yield c # c is prime; yield it
else: # (c == q) # add p to sieve
add(c+p+p, p+p) # insert in sieve
p = next(ps) # next sieving prime
q = p * p # ... and its square
I discuss all these things at my blog.
Fast primality tests are a huge subject.
What is often fast enough is to check if a number is divisible by two or by three, and then to check all possible divisors from 4 to the square root of the number.
So, try this:
def is_prime(n):
if n == 1:
return False
if n == 2:
return True
if n == 3:
return True
if n % 2 == 0
return False
if n % 3 == 0
return False
for d in range(5, int(n**0.5)+1,2):
if n % d == 0
return False
return True

All prime numbers within a range

I am trying to write a program that will print all the primes within a given range. I have written it, the output is almost okay, it prints primes, but for some reason it prints 4, which is not a prime...
Any assistant will be most appreciated !
def primes():
start = int(input("Enter the starting number: "))
end = int(input("Enter the ending number: "))
num = 0
i = 0
ctr = 0
for num in range(start,end+1,1):
ctr = 0
for i in range(2,num//2,1):
if num % i == 0 :
ctr = ctr + 1
break
if (ctr==0 and num != 1):
print(num)
for i in range(2,num//2,1):
Lets check this snippet of code when num = 4,it becomes
for i in range(2,2,1):
Now we see the problem.
Solution..?
for i in range(2,(num//2)+1,1):
The following methods are all possible prime checkers you might use to check within your range:
def isPrime(Number): # slow
return 2 in [Number, 2 ** Number % Number]
def isprime(n): # out of memory errors with big numbers
"""check if integer n is a prime"""
# make sure n is a positive integer
n = abs(int(n))
# 0 and 1 are not primes
if n < 2:
return False
# 2 is the only even prime number
if n == 2:
return True
# all other even numbers are not primes
if not n & 1:
return False
# range starts with 3 and only needs to go up the squareroot of n
# for all odd numbers
for x in range(3, int(n ** 0.5) + 1, 2):
if n % x == 0:
return False
return True
def is_prime(n): # Best until now
if n == 2 or n == 3:
return True
if n < 2 or n % 2 == 0:
return False
if n < 9:
return True
if n % 3 == 0:
return False
r = int(n ** 0.5)
f = 5
while f <= r:
# print '\t', f
if n % f == 0:
return False
if n % (f + 2) == 0:
return False
f += 6
return True
for i in range(2,num//2,1):
Above line is wrong. You are iterating from 2 to num / 2 - 1.
You should iterate from 2 to sqrt(num). (range(2, int(math.sqrt(n)) + 1))
Alternatively you can do a special check for 2 and modify your range to range(3, int(math.sqrt(n) + 1, 2)

Prime factorization - list

I am trying to implement a function primeFac() that takes as input a positive integer n and returns a list containing all the numbers in the prime factorization of n.
I have gotten this far but I think it would be better to use recursion here, not sure how to create a recursive code here, what would be the base case? to start with.
My code:
def primes(n):
primfac = []
d = 2
while (n > 1):
if n%d==0:
primfac.append(d)
# how do I continue from here... ?
A simple trial division:
def primes(n):
primfac = []
d = 2
while d*d <= n:
while (n % d) == 0:
primfac.append(d) # supposing you want multiple factors repeated
n //= d
d += 1
if n > 1:
primfac.append(n)
return primfac
with O(sqrt(n)) complexity (worst case). You can easily improve it by special-casing 2 and looping only over odd d (or special-casing more small primes and looping over fewer possible divisors).
The primefac module does factorizations with all the fancy techniques mathematicians have developed over the centuries:
#!python
import primefac
import sys
n = int( sys.argv[1] )
factors = list( primefac.primefac(n) )
print '\n'.join(map(str, factors))
This is a comprehension based solution, it might be the closest you can get to a recursive solution in Python while being possible to use for large numbers.
You can get proper divisors with one line:
divisors = [ d for d in xrange(2,int(math.sqrt(n))) if n % d == 0 ]
then we can test for a number in divisors to be prime:
def isprime(d): return all( d % od != 0 for od in divisors if od != d )
which tests that no other divisors divides d.
Then we can filter prime divisors:
prime_divisors = [ d for d in divisors if isprime(d) ]
Of course, it can be combined in a single function:
def primes(n):
divisors = [ d for d in range(2,n//2+1) if n % d == 0 ]
return [ d for d in divisors if \
all( d % od != 0 for od in divisors if od != d ) ]
Here, the \ is there to break the line without messing with Python indentation.
I've tweaked #user448810's answer to use iterators from itertools (and python3.4, but it should be back-portable). The solution is about 15% faster.
import itertools
def factors(n):
f = 2
increments = itertools.chain([1,2,2], itertools.cycle([4,2,4,2,4,6,2,6]))
for incr in increments:
if f*f > n:
break
while n % f == 0:
yield f
n //= f
f += incr
if n > 1:
yield n
Note that this returns an iterable, not a list. Wrap it in list() if that's what you want.
Most of the above solutions appear somewhat incomplete. A prime factorization would repeat each prime factor of the number (e.g. 9 = [3 3]).
Also, the above solutions could be written as lazy functions for implementation convenience.
The use sieve Of Eratosthenes to find primes to test is optimal, but; the above implementation used more memory than necessary.
I'm not certain if/how "wheel factorization" would be superior to applying only prime factors, for division tests of n.
While these solution are indeed helpful, I'd suggest the following two functions -
Function-1 :
def primes(n):
if n < 2: return
yield 2
plist = [2]
for i in range(3,n):
test = True
for j in plist:
if j>n**0.5:
break
if i%j==0:
test = False
break
if test:
plist.append(i)
yield i
Function-2 :
def pfactors(n):
for p in primes(n):
while n%p==0:
yield p
n=n//p
if n==1: return
list(pfactors(99999))
[3, 3, 41, 271]
3*3*41*271
99999
list(pfactors(13290059))
[3119, 4261]
3119*4261
13290059
Here is my version of factorization by trial division, which incorporates the optimization of dividing only by two and the odd integers proposed by Daniel Fischer:
def factors(n):
f, fs = 3, []
while n % 2 == 0:
fs.append(2)
n /= 2
while f * f <= n:
while n % f == 0:
fs.append(f)
n /= f
f += 2
if n > 1: fs.append(n)
return fs
An improvement on trial division by two and the odd numbers is wheel factorization, which uses a cyclic set of gaps between potential primes to greatly reduce the number of trial divisions. Here we use a 2,3,5-wheel:
def factors(n):
gaps = [1,2,2,4,2,4,2,4,6,2,6]
length, cycle = 11, 3
f, fs, nxt = 2, [], 0
while f * f <= n:
while n % f == 0:
fs.append(f)
n /= f
f += gaps[nxt]
nxt += 1
if nxt == length:
nxt = cycle
if n > 1: fs.append(n)
return fs
Thus, print factors(13290059) will output [3119, 4261]. Factoring wheels have the same O(sqrt(n)) time complexity as normal trial division, but will be two or three times faster in practice.
I've done a lot of work with prime numbers at my blog. Please feel free to visit and study.
def get_prime_factors(number):
"""
Return prime factor list for a given number
number - an integer number
Example: get_prime_factors(8) --> [2, 2, 2].
"""
if number == 1:
return []
# We have to begin with 2 instead of 1 or 0
# to avoid the calls infinite or the division by 0
for i in xrange(2, number):
# Get remainder and quotient
rd, qt = divmod(number, i)
if not qt: # if equal to zero
return [i] + get_prime_factors(rd)
return [number]
Most of the answer are making things too complex. We can do this
def prime_factors(n):
num = []
#add 2 to list or prime factors and remove all even numbers(like sieve of ertosthenes)
while(n%2 == 0):
num.append(2)
n /= 2
#divide by odd numbers and remove all of their multiples increment by 2 if no perfectlly devides add it
for i in xrange(3, int(sqrt(n))+1, 2):
while (n%i == 0):
num.append(i)
n /= i
#if no is > 2 i.e no is a prime number that is only divisible by itself add it
if n>2:
num.append(n)
print (num)
Algorithm from GeeksforGeeks
prime factors of a number:
def primefactors(x):
factorlist=[]
loop=2
while loop<=x:
if x%loop==0:
x//=loop
factorlist.append(loop)
else:
loop+=1
return factorlist
x = int(input())
alist=primefactors(x)
print(alist)
You'll get the list.
If you want to get the pairs of prime factors of a number try this:
http://pythonplanet.blogspot.in/2015/09/list-of-all-unique-pairs-of-prime.html
def factorize(n):
for f in range(2,n//2+1):
while n%f == 0:
n //= f
yield f
It's slow but dead simple. If you want to create a command-line utility, you could do:
import sys
[print(i) for i in factorize(int(sys.argv[1]))]
Here is an efficient way to accomplish what you need:
def prime_factors(n):
l = []
if n < 2: return l
if n&1==0:
l.append(2)
while n&1==0: n>>=1
i = 3
m = int(math.sqrt(n))+1
while i < m:
if n%i==0:
l.append(i)
while n%i==0: n//=i
i+= 2
m = int(math.sqrt(n))+1
if n>2: l.append(n)
return l
prime_factors(198765430488765430290) = [2, 3, 5, 7, 11, 13, 19, 23, 3607, 3803, 52579]
You can use sieve Of Eratosthenes to generate all the primes up to (n/2) + 1 and then use a list comprehension to get all the prime factors:
def rwh_primes2(n):
# http://stackoverflow.com/questions/2068372/fastest-way-to-list-all-primes-below-n-in-python/3035188#3035188
""" Input n>=6, Returns a list of primes, 2 <= p < n """
correction = (n%6>1)
n = {0:n,1:n-1,2:n+4,3:n+3,4:n+2,5:n+1}[n%6]
sieve = [True] * (n/3)
sieve[0] = False
for i in xrange(int(n**0.5)/3+1):
if sieve[i]:
k=3*i+1|1
sieve[ ((k*k)/3) ::2*k]=[False]*((n/6-(k*k)/6-1)/k+1)
sieve[(k*k+4*k-2*k*(i&1))/3::2*k]=[False]*((n/6-(k*k+4*k-2*k*(i&1))/6-1)/k+1)
return [2,3] + [3*i+1|1 for i in xrange(1,n/3-correction) if sieve[i]]
def primeFacs(n):
primes = rwh_primes2((n/2)+1)
return [x for x in primes if n%x == 0]
print primeFacs(99999)
#[3, 41, 271]
from sets import Set
# this function generates all the possible factors of a required number x
def factors_mult(X):
L = []
[L.append(i) for i in range(2,X) if X % i == 0]
return L
# this function generates list containing prime numbers upto the required number x
def prime_range(X):
l = [2]
for i in range(3,X+1):
for j in range(2,i):
if i % j == 0:
break
else:
l.append(i)
return l
# This function computes the intersection of the two lists by invoking Set from the sets module
def prime_factors(X):
y = Set(prime_range(X))
z = Set(factors_mult(X))
k = list(y & z)
k = sorted(k)
print "The prime factors of " + str(X) + " is ", k
# for eg
prime_factors(356)
Simple way to get the desired solution
def Factor(n):
d = 2
factors = []
while n >= d*d:
if n % d == 0:
n//=d
# print(d,end = " ")
factors.append(d)
else:
d = d+1
if n>1:
# print(int(n))
factors.append(n)
return factors
This is the code I made. It works fine for numbers with small primes, but it takes a while for numbers with primes in the millions.
def pfactor(num):
div = 2
pflist = []
while div <= num:
if num % div == 0:
pflist.append(div)
num /= div
else:
div += 1
# The stuff afterwards is just to convert the list of primes into an expression
pfex = ''
for item in list(set(pflist)):
pfex += str(item) + '^' + str(pflist.count(item)) + ' * '
pfex = pfex[0:-3]
return pfex
I would like to share my code for finding the prime factors of number given input by the user:
a = int(input("Enter a number: "))
def prime(a):
b = list()
i = 1
while i<=a:
if a%i ==0 and i!=1 and i!=a:
b.append(i)
i+=1
return b
c = list()
for x in prime(a):
if len(prime(x)) == 0:
c.append(x)
print(c)
def prime_factors(num, dd=2):
while dd <= num and num>1:
if num % dd == 0:
num //= dd
yield dd
dd +=1
Lot of answers above fail on small primes, e.g. 3, 5 and 7. The above is succinct and fast enough for ordinary use.
print list(prime_factors(3))
[3]

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