I have tried to create a program to calculate the base-10 logarithm based on the Taylor series-based algorithm described in "The Mathematical-Function Computation Handbook" (I found an online copy via my University's library).
A similar algorithm is given on another question on StackOverflow for which I cannot find the link right now.
10.3.2 Computing logarithms in a decimal base
For a decimal base, the base-10 logarithm is the natural choice, and the decomposition of the argument into an exponent and a fraction gives us a decimal representation: x = (−1)^s × f × 10^n, either f = 0 exactly, or f is in [1/10, 1).
If f ≤√1/10, set f = 10 × f and n = n − 1, so that f is now in the interval (√1/10,√10]. Then introduce a change of variable, a Taylor-series expansion, and a polynomial representation of that expansion:
z = (f − 1)/( f + 1),
f = (1 + z)/(1 − z),
D = 2 log10(e)
= 2/ log(10)
log10( f) = D × (z + z3/3 + z5/5 + z7/7 + z9/9 + z11/11 + · · · )
≈ D × z + z3Q(z2), polynomial fit incorporates D in Q(z2).
For f in (√1/10,√10], we have z in roughly [−0.5195,+0.5195]. The wider range of z requires longer polynomials compared to the binary case, and also makes the correction term z3Q(z2) relatively larger. Its magnitude does not exceed |0.35z|, so it provides barely one extra decimal digit of precision, instead of two. Accurate computation of z is easier than in the binary case: just set z = fl(fl(f−12)−12)/fl(f+1).
For this I wrote this program in Python:
def log10(x):
n = 0.0 #Start exponent of base 10
while (x >= 1.0):
x = x/10.0
n+=1
# if x <= sqrt(1/10)
if(x<=0.316227766016838):
x = x*10.0
n = n-1
#Produce a change of variable
z = (x-1.0)/(x+1.0)
D = 4.60517018598809 #2*log10(e)
sum = z
for k in range(3,111,2):
sum+=(z**k)/k
return D*n*sum
I compared the results to the math.log10
function, and the results are not as expected. My biggest issue when debugging is understanding the algorithm and why it works.