def determinePrecision(pi):
pi = str(pi)
pi_ref = str(gmpy.pi(10000)) # reference pi
min_len = min(len(pi), len(pi_ref))
i = 0
while i < min_len and pi[i] == pi_ref[i]:
i += 1
return i
def determinePrecision(pi):
pi = str(pi)
pi_ref = str(gmpy.pi(10000)) # reference pi
min_len = min(len(pi), len(pi_ref))
i = 0
while i < min_len and pi[i] == pi_ref[i]:
i += 1
return i
#variable precision trigonometry functions import gmpy import numpy from matplotlib import pyplot import pickle import math N=1000 pi=gmpy.pi(N) pi2=pi/2 pi2_minus = -pi2 pix2 = pi*2 pi_minus = -pi mpone=gmpy.mpf(1,N) eps=gmpy.mpf(2)**(-N) def sin_taylor(x): x2 = x*x s=0 i=2 an = x sgn = 1 while True: s = s + sgn*an an = an*x2/(i*(i+1)) i += 2
/____________
n=0
There are three main calculations in this Javascript program:
- Taylor series for the square root of 8,
- Ramanujan's series for 1/Pi,
- Newton-Raphson method for the reciprocal.
"""
fact_cache = [1,1,2,6,24,120,720,5040]
def fact(n):
if n < len(fact_cache): return fact_cache[n]
return n*fact(n-1)
def rama(nsteps,prec=10):
from gmpy import mpf
pre = mpf('8',prec).sqrt()/mpf('9801',prec)
sum = mpf('0',prec)
for i in range(nsteps):
num = fact(4*i)*(1103+26390*i)
den = pow(fact(i),4)*pow(396,4*i)
sum += mpf(num,prec)/mpf(den,prec)
print mpf(1,prec)/(pre*sum)
if __name__ == '__main__':
from gmpy import pi
print pi(1000)
rama(100,1000)
def test_pi():
from gmpy import pi # import the Gnu Multiprecision library pi function
val = pi(1000000) # ~300,000 digits of pi
digpi = digits_to_list(val)
