# Quiz 6b#

## Question 1#

What is the position of the center of the top-left card (Ace of Clubs, A♣) in the tiled image discussed in the “Tiled images” video? Remember that each card in this tiled image has size 73 x 98 pixels.

(Note that the tiled image used in the current version of your Blackjack mini-project is slightly smaller.)

`(36.5, 49)`

`(5 * 73 + 36.5, 1 * 98 + 49)`

`(0, 0)`

`(73, 98)`

\

`(36.5, 49)`

\

## Question 2#

What is the position of the center of the bottom-right card (King of Diamonds, K♦) in the tiled image discussed in the “Tiled images” video? Again, remember that each card in this tiled image has size 73 x 98 pixels.

Enter two numbers, separated only by spaces.

Enter answer here:\

912.5, 343.0

```
CARD_SIZE = [73, 98]
CARD_POS = [CARD_SIZE[0]/2, CARD_SIZE[1]/2]
def card_pos(i, j):
return CARD_POS[0] + i * CARD_SIZE[0], \
CARD_POS[1] + j * CARD_SIZE[1]
print(card_pos(12, 3))
```

## Question 3#

When using Dropbox to store images for use with CodeSkulptor, what
should the `www`

portion of the DropBox URL be
replaced by?

Refer to the video on tiled images.

`dl`

`gif`

`html`

`jpg`

`www`

\

`dl`

\

## Question 4#

Within the `__init__`

method, the new object
should be returned with what code?

No `return`

statement is needed in
`__init__`

.

`return self`

`return`

`return whatever_the_object_is_named`

(Use the
appropriate variable name.) \

No `return`

statement is needed in
`__init__`

. \

## Question 5#

One way of understanding code is to think about other code that accomplishes the same thing — i.e., given the same starting values, it returns and/or mutates the same values.

This following defines one way to concatenate multiple lists. For
example,
`list_extend_many([[1,2], [3], [4, 5, 6], [7]])`

returns `[1, 2, 3, 4, 5, 6, 7]`

and doesn’t
mutate anything.

```
def list_extend_many(lists):
"""Returns a list that is the concatenation of all the lists in the given list-of-lists."""
result = []
for l in lists:
result.extend(l)
return result
```

Which of the following definitions are equivalent? I.e., which always produce the same output for the same input, and never mutate the input or any global variable?

```
def list_extend_many(lists):
result = []
i = len(lists)
while i >= 0:
i -= 1
result.extend(lists[i])
return result
```

\

```
def list_extend_many(lists):
result = []
i = 0
while i < len(lists):
result.extend(lists[i])
i += 1
return result
```

\

```
def list_extend_many(lists):
result = []
for i in range(len(lists)):
result.extend(lists[i])
return result
```

\

```
def list_extend_many(lists):
result = []
i = 0
while i < len(lists):
i += 1
result.extend(lists[i])
return result
```

The following code appends the lists in `lists`

in reverse order.

```
def list_extend_many(lists):
result = []
i = len(lists)
while i >= 0:
i -= 1
result.extend(lists[i])
return result
```

Same order:

```
def list_extend_many(lists):
result = []
i = 0
while i < len(lists):
result.extend(lists[i])
i += 1
return result
```

Same order:

```
def list_extend_many(lists):
result = []
for i in range(len(lists)):
result.extend(lists[i])
return result
```

Results in an error:

```
def list_extend_many(lists):
result = []
i = 0
while i < len(lists):
i += 1
result.extend(lists[i])
return result
```

## Question 6#

Which of the following programs would never end if it weren’t for
CodeSkulptor’s timeout? Assume no `break`

or
`return`

statement is used in the elided loop
bodies.

You might want to add a `print`

statement to each
loop to better understand the behavior.

```
n = 1
while n > 0:
#… # Assume this doesn't modify n.
n += 1
```

\

```
n = 1000
while n > 0:
#… # Assume this doesn't modify n.
n -= 1
```

\

```
while True:
#…
```

\

```
my_list = #…
for x in my_list:
#… # Assume this doesn't mutate my_list.
```

```
n = 1
while n > 0:
#… # Assume this doesn't modify n.
n += 1
```

```
while True:
#…
```

## Question 7#

Convert the following English description into code.

Initialize

`n`

to be 1000. Initialize`numbers`

to be a list of numbers from 2 to`n`

but not including`n`

.With

`results`

starting as the empty list, repeat the following as long as`numbers`

contains any numbers.

Add the first number in

`numbers`

to the end of`results`

.

Remove every number in

`numbers`

that is evenly divisible by (has no remainder when divided by) the number that you had just added to`results`

.

How long is `results`

?

To test your code, when `n`

is instead 100, the
length of `results`

is 25.

Enter answer here:\

168

```
def f(n):
numbers = list(range(2, n))
results = []
while numbers:
div = numbers[0]
results.append(div)
numbers = [x for x in numbers if x % div != 0]
return len(results)
print(f(100))
print(f(1000))
```

## Question 8#

We can use loops to simulate natural processes over time. Write a program that calculates the populations of two kinds of “wumpuses” over time. At the beginning of year 1, there are 1000 slow wumpuses and 1 fast wumpus. This one fast wumpus is a new mutation. Not surprisingly, being fast gives it an advantage, as it can better escape from predators. Each year, each wumpus has one offspring. (We’ll ignore the more realistic niceties of sexual reproduction, like distinguishing males and females.). There are no further mutations, so slow wumpuses beget slow wumpuses, and fast wumpuses beget fast wumpuses. Also, each year 40% of all slow wumpuses die each year, while only 30% of the fast wumpuses do.

So, at the beginning of year one there are 1000 slow wumpuses. Another 1000 slow wumpuses are born. But, 40% of these 2000 slow wumpuses die, leaving a total of 1200 at the end of year one. Meanwhile, in the same year, we begin with 1 fast wumpus, 1 more is born, and 30% of these die, leaving 1.4. (We’ll also allow fractional populations, for simplicity.)

Beginning of Year + Slow Wumpuses + Fast Wumpuses

1 1000 1 2 1200 1.4 3 1440 1.96 … … …

Enter the first year in which the fast wumpuses outnumber the slow wumpuses. Remember that the table above shows the populations at the start of the year.

Enter answer here:\

46

```
SLOWS_FACTOR = 1.2
FASTS_FACTOR = 1.4
year = 1
slows = 1000
fasts = 1
def iterate_one_year():
global slows, fasts, year
slows *= SLOWS_FACTOR
fasts *= FASTS_FACTOR
year += 1
while slows >= fasts:
iterate_one_year()
print(year)
```