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Python code written by myself
The function "fac"
uses recursive method in defining function to calculate the factorial of an integer. The function "Fac"
uses a for loop in doing the same thing. We want to compare the time these two methods and another function "math.factorial"
need to spend for doing the same thing. Here is the code.
import math
def fac(n):
n = round(n)
if n == 0:
return 1
else:
return n*fac(n-1)
def Fac(n):
n = round(n)
if n == 0:
return 1
else:
sum = 1
for i in range(1,n+1):
sum *= i
return sum
def runtime(s):
import time
time1 = time.clock()
fac(s)
time2 = time.clock()
Fac(s)
time3 = time.clock()
math.factorial(s)
time4 = time.clock()
x1 = time2 - time1
x2 = time3 - time2
x3 = time4 - time3
print('The time function "fac" spent was: ', x1, 'seconds.')
print('The time function "Fac" spent was: ', x2, 'seconds.')
print('The time function "math.factorial" spent was: ', x3, 'seconds.')
Now we can run the function "runtime"
with arbitrary positive integer we want to test.
>>> runtime(5)
The time function "fac" spent was: 1.1999999999900979e-05 seconds.
The time function "Fac" spent was: 8.000000000230045e-06 seconds.
The time function "math.factorial" spent was: 3.000000000419334e-06 seconds.
>>> runtime(10)
The time function "fac" spent was: 1.4000000000180535e-05 seconds.
The time function "Fac" spent was: 9.000000000369823e-06 seconds.
The time function "math.factorial" spent was: 2.9999999995311555e-06 seconds.
>>> runtime(20)
The time function "fac" spent was: 2.3000000000550358e-05 seconds.
The time function "Fac" spent was: 9.999999999621423e-06 seconds.
The time function "math.factorial" spent was: 3.000000000419334e-06 seconds.
>>> runtime(50)
The time function "fac" spent was: 4.2000000000541604e-05 seconds.
The time function "Fac" spent was: 1.4999999999432134e-05 seconds.
The time function "math.factorial" spent was: 5.999999999950489e-06 seconds.
We can see that the recursive method is even much slower than even the notorious looping for its slowness. The function "math.factorial"
provided by Python itself is quickest. So recursive method should be avoided if we have better ways of coding.
The crude Python code is the following. We use Newton-Raphson method to fulfill it.
def Sqrt(x):
tol = 1e-8
x0 = x
diff = abs(x0**2 - x)
while diff > tol:
x0 = (x0**2 + x)/(2*x0)
diff = abs(x0**2 - x)
return(x0)
The following function takes a string as input and calculate the frequency of each letter, the print the freq table.
def most_frequent(S):
S.lower()
dic = dict() # create an empty dictionary
for i in S:
dic[i] = 1 + dic.get(i, 0) # fill up the dictionary with letters and their freq
t = []
for i in dic:
t.append((dic[i], i)) # create a tuple from the dictionary
res = sorted(t, reverse = True) # sort the tuple
for x, y in res:
print(y, x)
Some texts in English are selected and run the function most_frequent
.
data = open("word.txt")
x = data.read()
print(most_frequent(x))
The result is as follows, the first several lines are the same with wikipedia record.
7959
e 4958
t 3581
a 2892
o 2884
i 2810
n 2609
s 2500
r 2271
h 1944
l 1698
d 1270
c 1262
u 1105
m 927
p 829
y 764
f 711
g 674
w 635
b 602
v 457
, 404
. 356
k 273
236
’ 154
T 97
A 94
I 92
S 90
x 87
- 74
E 62
j 54
W 53
B 46
– 44
‘ 41
q 40
: 40
C 38
0 37
L 34
1 32
? 31
R 30
P 30
O 29
M 29
H 29
D 29
N 26
; 26
' 24
F 23
2 21
) 21
( 21
G 19
9 19
Y 17
U 17
K 15
z 14
7 11
J 10
V 9
6 9
8 6
5 6
4 6
… 4
] 4
[ 4
& 4
! 4
” 3
“ 3
Z 3
é 2
3 2
— 1
Q 1
% 1
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