A lab report on modeling and simulation with python code
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The document outlines multiple experiments aimed at implementing various mathematical algorithms in Python, including linear congruential generators, Bernoulli distribution, binomial distribution, geometric distribution, GCD, and LCM. Each experiment is accompanied by its objective and sample source code. References to external resources for further reading are also provided.
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![Experiment Name: Write a program to implement Bernouli distribution in python.
Objective: The Bernoulli distribution essentially models a single trial of flipping a weighted
coin. It is the probability distribution of a random variable taking on only two values,
1 ("success") and 0 ("failure") with complementary probabilities p and 1-p respectively. This
program is to implement Bernouli distribution in python.
Source Code:
u = []
def test(p):
printf()
if u[0]<=p:
return 1
else:
return 0
def printf():
m=16;
a=5.0;
c=3.0;
z=7.0;
for num in range (1,21):
r=(a*z+c)%m;
#print r;
z=r;
u.append(z/m)](https://image.slidesharecdn.com/lab-report-180514211943/85/A-lab-report-on-modeling-and-simulation-with-python-code-2-320.jpg)
![Experiment Name: Write a program to implement Binomal distribution in python.
Objective: A binomial distribution is the sum of independent and identically distributed
Bernoulli random variables. This program is to implement Binomal in python.
Source Code:
u = []
count = []
m = 16
a = 5
c = 3
z = 7
for num in range (m):
r = (a*z+c)%m
z = r
u.append(float(z)/m)
print u
def test(w):
count = 0
for i in w:
print u[0] ," ",i
if u[0]<=i:
count+=1;
return count
p = []](https://image.slidesharecdn.com/lab-report-180514211943/85/A-lab-report-on-modeling-and-simulation-with-python-code-4-320.jpg)
![Experiment Name: Write a program to implement geometry distribution in python.
Objective: The geometric distribution is a special case of the negative binomial distribution. It
deals with the number of trials required for a single success. Thus, the geometric distribution is a
negative binomial distribution where the number of successes (r) is equal to 1. This program is to
implement geometry algorithm in python.
Source Code:
u = []
count = []
m = 16
a = 5
c = 3
z = 7
for num in range (m):
r = (a*z+c)%m
z = r
u.append(float(z)/m)
print u
def test(w):
count = 0
for i in w:
print u[0] ," ",i
if u[0]<=i:
count+=1](https://image.slidesharecdn.com/lab-report-180514211943/85/A-lab-report-on-modeling-and-simulation-with-python-code-6-320.jpg)
![else:
break
return count
p = []
f = input("")
fori in range(f):
j = input("")
p.append( float(j))
l = len(p)
c = test(p)
print c," ",l
print float(c)/float(l)
Reference: stattrek.com/statistics/dictionary.aspx?definition=geometric_distribution](https://image.slidesharecdn.com/lab-report-180514211943/85/A-lab-report-on-modeling-and-simulation-with-python-code-7-320.jpg)
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1. Print even numbers from a list, calculate ASCII distance between characters, get binary form of a number, and convert between bases.
2. Count vowels in a string, check if a number's binary has even 1's, sort by vowel count.
3. Return top occurring characters, implement map and generator functions.
4. Convert iterable to list, user-defined map, generate even numbers, filter evens from list.
5. Implement round robin scheduling algorithm.
6. Sort and transfer words between files, remove duplicates and sort a list.
7. Check for anagrams, implement left binary search.
8. Define
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- 1. Experiment Name: Write a program to implement Linear Congruential Generators in python. Objective: A linear congruential generator (LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear equation. This program is to implement LCG. Source Code: m=16; a=5.0; c=3.0; z=7.0; for num in range (1,21): r=(a*z+c)%m; z=r; #print z/m; print r ; Reference: https://en.wikipedia.org/wiki/Linear_congruential_generator
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