# Activity Selector Implementations

## Table of Contents

```
# from pypi
from expects import contain_exactly, equal, expect
```

## Example Data

```
PADDING = 0
start = [PADDING, 1, 3, 0, 5, 3, 5, 6, 8, 8, 2, 12]
finish = [PADDING, 4, 5, 6, 7, 9, 9, 10, 11, 12, 14, 16]
expected_activities = [1, 4, 8, 11]
expect(len(start)).to(equal(len(finish)))
```

## A Recursive Selector

```
def recursive_activity_selector(start, finish, k: int=0) -> list:
"""Selects the optimal activities
Note:
This assumes that the start and finish lists are pre-padded with
zeros (1 each).
Args:
start: list of start times for each activity
finish: list of end times for each activity
k: the current activity (index)
Returns:
optimal list of activities
"""
n = len(start)
m = k + 1
while m < n and start[m] < finish[k]:
m += 1
if m < n:
return [m] + recursive_activity_selector(start, finish, m)
return []
```

```
activities = recursive_activity_selector(start, finish)
expect(activities).to(contain_exactly(*expected_activities))
print(activities)
```

[1, 4, 8, 11]

## An Iterative Selector

```
def iterative_activity_selector(start: list, finish: list) -> list:
"""An iterative activity selector
Note:
This assumes that the start and finish lists are pre-padded with
dummy values.
Args:
start: list of starting times
finish: list of end times
"""
n = len(start)
activities = [1]
k = 1
for m in range(2, n):
if start[m] >= finish[k]:
activities += [m]
k = m
return activities
```

```
activities = iterative_activity_selector(start, finish)
expect(activities).to(contain_exactly(*expected_activities))
print(activities)
```