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Gaby Webb c17 whales #6

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7b17be5
Update README description
kyra-patton Sep 22, 2022
fee1c64
Update examples to use dictionaries
kyra-patton Sep 22, 2022
9ae2f8d
Merge pull request #1 from ada-c17/kp/c17-update
kyra-patton Sep 22, 2022
db38388
update test cases
char-adadev Sep 22, 2022
46777ec
Merge pull request #2 from ada-c17/cm/update-tests
char-adadev Sep 22, 2022
01c4b86
passes 7/10 tests
gabw13 Nov 7, 2022
b2ae037
passes all tests
gabw13 Nov 21, 2022
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76 changes: 38 additions & 38 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -11,57 +11,57 @@ In this exercise you should be able to:

## Description

Given a set of N puppies (numbered 0, 1, 2, ..., N - 1), we would like to split them into two groups of any size to use two play areas.
Given a set of N puppies, we would like to split them into two groups of any size to use two play areas.

Some dogs have a history of fighting with specific other dogs and shouldn't be put into the same play area.

Formally, if dislikes[i] = [a, b], it means dog i is not allowed to put in the same group as dog a or dog b.
Formally, if `dislikes[i] = [a, b]`, it means dog `i` is not allowed to put in the same group as dog `a` or dog `b`.

Return true if and only if it is possible to split the dogs into two groups where no fighting will occur.
Dislike is mutual. If dog `a` that dislikes dog `b`, dog `b` also dislikes dog `a`.

### Example 1
Return `True` if and only if it is possible to split the dogs into two groups where no fighting will occur. Otherwise, return `False`.

### Example 1
*Input*:
``` python
dislikes = {
"Fido": [],
"Nala": ["Cooper", "Spot"],
"Cooper": ["Nala", "Bruno"],
"Spot": ["Nala"],
"Bruno": ["Cooper"]
}
```
Input: dislikes = [ [],
[2, 3],
[1, 4],
[1],
[2]
]
Output: true
```

Explanation: group1 [0, 1, 4], group2 [2, 3]
*Output*: `True`
Explanation: group1: `["Fido", "Nala", "Bruno"]`, group2: `["Cooper", "Spot"]`

### Example 2

```
Input: dislikes = [ [],
[2, 3],
[1, 3],
[1, 2]
]
Output: false
*Input*:
```python
dislikes = {
"Fido": [],
"Nala": ["Cooper", "Spot"],
"Coooper": ["Nala", "Spot"],
"Spot": ["Nala", "Cooper"]
}
```

Explanation: All the nodes 1-3 are interconnected and so there is no way to split them up.
*Output*: `False`
Explanation: The nodes `Nala`, `Cooper`, and `Spot` are interconnected and so there is no way to split them up.

### Example 3

```
Input: dislikes = [ [],
[2, 5],
[1, 3],
[2, 4],
[3, 5],
[1, 4]
]
Output: false
*Input*:
```Python
dislikes = {
"Fido": [],
"Nala": ["Cooper", "Cali"],
"Cooper": ["Nala", "Spot"],
"Spot": ["Cooper", "Bruno"],
"Bruno": ["Spot", "Cali"],
"Cali": ["Nala", "Bruno"]
}
```

### Note

The graph is undirected, so if dog 1 dislikes dog 2, then dog 2 also dislikes dog 1.
*Output*: `False`
Explanation: There is no way to split `Nala`, `Cooper`, `Spot`, `Bruno`, and `Cali` up into two groups such that they are all separated from the dogs they dislike.

## Source

Expand Down
33 changes: 30 additions & 3 deletions graphs/possible_bipartition.py
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Expand Up @@ -5,8 +5,35 @@ def possible_bipartition(dislikes):
""" Will return True or False if the given graph
can be bipartitioned without neighboring nodes put
into the same partition.
Time Complexity: ?
Space Complexity: ?
Time Complexity: O(N + E) where N is the number of nodes & E is the number of edges
Space Complexity: O(N) where N is the number of nodes
"""
pass

if len(dislikes) == 0:
return True

groups = {}
for key in dislikes.keys():
groups[key] = 0

first_pup = list(dislikes.keys())[0]
groups[first_pup] = 1
queue = [first_pup]
visited = set()

for pup in dislikes:
while queue:
current = queue.pop(0)
visited.add(current)

if dislikes[current]:
for dog in dislikes[current]:
if groups[dog] == 0:
groups[dog] = groups[current] + 1
queue.append(dog)
elif groups[dog] == groups[current]:
return False
if pup not in visited:
queue.append(pup)
return True

158 changes: 112 additions & 46 deletions tests/test_possible_bipartition.py
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Expand Up @@ -3,12 +3,13 @@

def test_example_1():
# Arrange
dislikes = [ [],
[2, 3],
[1, 4],
[1],
[2]
]
dislikes = {
"Fido": [],
"Rufus": ["James", "Alfie"],
"James": ["Rufus", "T-Bone"],
"Alfie": ["Rufus"],
"T-Bone": ["James"]
}

# Act
answer = possible_bipartition(dislikes)
Expand All @@ -17,12 +18,12 @@ def test_example_1():
assert answer

def test_example_2():
# Arrange
dislikes = [ [],
[2, 3],
[1, 3],
[1, 2]
]
dislikes = {
"Fido": [],
"Rufus": ["James", "Alfie"],
"James": ["Rufus", "Alfie"],
"Alfie": ["Rufus", "James"]
}

# Act
answer = possible_bipartition(dislikes)
Expand All @@ -32,13 +33,14 @@ def test_example_2():

def test_example_r():
# Arrange
dislikes = [ [],
[2, 5],
[1, 3],
[2, 4],
[3, 5],
[1, 4]
]
dislikes = {
"Fido": [],
"Rufus": ["James", "Scruffy"],
"James": ["Rufus", "Alfie"],
"Alfie": ["Rufus", "T-Bone"],
"T-Bone": ["Alfie", "Scruffy"],
"Scruffy": ["Rufus", "T-Bone"]
}

# Act
answer = possible_bipartition(dislikes)
Expand All @@ -48,14 +50,15 @@ def test_example_r():

def test_will_return_true_for_a_graph_which_can_be_bipartitioned():
# Arrange
dislikes = [ [3, 6],
[2, 5],
[1, 3],
[0, 2],
[5],
[1, 4],
[0]
]
dislikes = {
"Fido": ["Alfie", "Bruno"],
"Rufus": ["James", "Scruffy"],
"James": ["Rufus", "Alfie"],
"Alfie": ["Fido", "James"],
"T-Bone": ["Scruffy"],
"Scruffy": ["Rufus", "T-Bone"],
"Bruno": ["Fido"]
}

# Act
answer = possible_bipartition(dislikes)
Expand All @@ -65,14 +68,15 @@ def test_will_return_true_for_a_graph_which_can_be_bipartitioned():

def test_will_return_false_for_graph_which_cannot_be_bipartitioned():
# Arrange
dislikes = [ [3, 6],
[2, 5],
[1, 3],
[0, 2, 4],
[3, 5],
[1, 4],
[0]
]
dislikes = {
"Fido": ["Alfie", "Bruno"],
"Rufus": ["James", "Scruffy"],
"James": ["Rufus", "Alfie"],
"Alfie": ["Fido", "James", "T-Bone"],
"T-Bone": ["Alfie", "Scruffy"],
"Scruffy": ["Rufus", "T-Bone"],
"Bruno": ["Fido"]
}

# Act
answer = possible_bipartition(dislikes)
Expand All @@ -82,23 +86,85 @@ def test_will_return_false_for_graph_which_cannot_be_bipartitioned():


def test_will_return_true_for_empty_graph():
assert possible_bipartition([])
assert possible_bipartition({})

def test_will_return_false_for_another_graph_which_cannot_be_bipartitioned():
# Arrange
dislikes = [ [3, 6],
[2, 5],
[1, 3],
[0, 2, 4],
[3, 5],
[1, 4],
[0],
[8],
[7]
]
dislikes = {
"Fido": ["Alfie", "Bruno"],
"Rufus": ["James", "Scruffy"],
"James": ["Rufus", "Alfie"],
"Alfie": ["Fido", "James", "T-Bone"],
"T-Bone": ["Alfie", "Scruffy"],
"Scruffy": ["Rufus", "T-Bone"],
"Bruno": ["Fido"],
"Spot": ["Nala"],
"Nala": ["Spot"]
}

# Act
answer = possible_bipartition(dislikes)

# Assert
assert not answer

def test_multiple_dogs_at_beginning_dont_dislike_any_others():
# Arrange
dislikes = {
"Fido": [],
"Rufus": [],
"James": [],
"Alfie": ["T-Bone"],
"T-Bone": ["Alfie", "Scruffy"],
"Scruffy": ["T-Bone"],
"Bruno": ["Nala"],
"Spot": ["Nala"],
"Nala": ["Bruno", "Spot"]
}

# Act
answer = possible_bipartition(dislikes)

# Assert
assert answer


def test_multiple_dogs_in_middle_dont_dislike_any_others():
# Arrange
dislikes = {
"Fido": ["Alfie"],
"Rufus": ["James", "Scruffy"],
"James": ["Rufus", "Alfie"],
"Alfie": ["Fido", "James"],
"T-Bone": [],
"Scruffy": ["Rufus"],
"Bruno": [],
"Spot": ["Nala"],
"Nala": ["Spot"]
}

# Act
answer = possible_bipartition(dislikes)

# Assert
assert answer

def test_will_return_false_for_disconnected_graph_which_cannot_be_bipartitioned():
# Arrange
dislikes = {
"Ralph": ["Tony"],
"Tony": ["Ralph"],
"Fido": ["Alfie", "Bruno"],
"Rufus": ["James", "Scruffy"],
"James": ["Rufus", "Alfie"],
"Alfie": ["Fido", "James", "T-Bone"],
"T-Bone": ["Alfie", "Scruffy"],
"Scruffy": ["Rufus", "T-Bone"],
"Bruno": ["Fido"]
}

# Act
answer = possible_bipartition(dislikes)

# Assert
assert not answer