Introduction to Python Programming.pptx

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Q.1 Are each of the following True or False
a. In Python, classes do not enforce information hiding.
b. In Python, classes cannot be used as a parameter of a function.
c. Increasing the number of buckets in a hash table typically increases the amount
of time needed to locate a value in the table.
d. “Normal distribution” and “Gaussian distribution” are different names for the
same thing.
e. “Standard deviation” and “coefficient of variation” are different names for the
same thing.
Solution:
a. True
b. False
c. False
d. True
e. False

Q.2 Consider the following code:
import random
tots = [0.00]*3
maxVals = [0.0]*3
mean = 100.0
stdDevs = [0.0, 20.0, 40.0]
for i in range(1000):
for j in range(len(tots)):
next = random.gauss(mean, stdDevs[j])
tots[j] += next
if next > maxVals[j]:
maxVals[j] = next
What are the expected values of each element of tots at the end of the code?
Solution:
100,000 100,000 1000,000

Q.3 Is each of the following True or False
1. One would expect maxVals[0] to be less than maxVals[1].
2. One would expect maxVals[1] to be less than maxVals[2].
3. If the code were run twice, the value of tots[0] would be the same each time.
Solution:
1. True
2. True
3. True
Q.4 What does the following code print?
class Shape(object):
def________eq__________(s1, s2):
return s1.area() == s2.area()
def________lt ___________(s1, s2):
return s1.circum() < s2.circum()

class Rectangle(Shape):
def__init__(self, h, w):
self.height = float(h)
self.width = float(w)
def circum(self):
return 2*(self.height + self.width)
def str (self):
return 'Rectangle with area ' + str(self.height*self.width)
class Square(Rectangle):
def____init____(self, s):
Rectangle.__init__(self, s, s)
def____str____(self):
return 'Square with side ' + str(self.height)
class Circle(Shape):
def__init__(self, radius):
self.radius = float(radius)
def circum(self):
return 3.14159*(2*self.radius)

def__lt__(self, other):
return self.radius < other.radius
def__str__(self):
return 'Circle with diameter ' + str(2.0*self.radius)
def reorder(L):
for e in L:
if e < L[0]:
L[0] = e
L = [Square(6), Rectangle(2, 3), Circle(1)]
try:
reorder(L)
for e in L:
print e
except:
for e in L:
print e
Solution:

Square with side 5.0
Rectangle with area 6.0
Circle with radius 2.0
Square with side 6.0
Rectangle with area 6.0
Circle with radius 1.0
Q.5 Write a function that uses a Monte Carlo simulation to find the probability of a
run of at least 4 consecutive heads out of ten flips of a fair coin, and then returns
that probability. Assume that 10,000 trials are sufficient to provide an accurate
answer. You may invoke the function:
def simThrows(numFlips):
"""Simulates a sequence of numFlips coin flips, and returns True if the sequence
contains a run of at least four consecutive heads and False otherwise.""“
Solution:
def runSim(numTrials, numThrows):
numSuccess = 0.0

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for t in range(numTrials):
if simThrows(numThrows):
numSuccess += 1.0
return numSuccess/numTrials
def sim():
return runSim(100000, 4)
Q.6 If pylab.polyfit is used to fit an nth degree and an (n+1)th degree polynomial
to the same data, is one guaranteed to provide a least squares fit that is at least as
good as the other? If so, which and why? If not, why not?
Solution:
Yes. The (n+1)th degree fit will be at least as tight, because it always possible to set
unnecessary coefficients to 0.

Introduction to Python Programming.pptx

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