Added Fibonacci_Heap for DSA #9285
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| @@ -0,0 +1,101 @@ | |||
| class FibonacciNode: | |||
| def __init__(self, key): | |||
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Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: key
| self.parent = None | ||
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| class FibonacciHeap: | ||
| def __init__(self): |
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Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:
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class FibonacciNode:
def init(self, key) -> None:
self.key = key
self.children = []
self.marked = False
self.degree = 0
self.parent = None
class FibonacciHeap:
def init(self) -> None:
self.trees = []
self.least = None
self.count = 0
| self.least = None | ||
| self.count = 0 | ||
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| def insert(self, key): |
There was a problem hiding this comment.
Please provide return type hint for the function: insert. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function insert
Please provide type hint for the parameter: key
| if self.least is None or key < self.least.key: | ||
| self.least = new_node | ||
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| def extract_min(self): |
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Please provide return type hint for the function: extract_min. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function extract_min
| self.consolidate() | ||
| return min_node.key | ||
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| def consolidate(self): |
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Please provide return type hint for the function: consolidate. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function consolidate
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| self.trees = [node for node in degree_counts if node is not None] | ||
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| def link(self, node1, node2): |
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Please provide return type hint for the function: link. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function link
Please provide type hint for the parameter: node1
Please provide type hint for the parameter: node2
| node1.degree += 1 | ||
| node2.marked = False | ||
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| def decrease_key(self, node, new_key): |
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Please provide return type hint for the function: decrease_key. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function decrease_key
Please provide type hint for the parameter: node
Please provide type hint for the parameter: new_key
| self.cut(node, parent) | ||
| self.cascading_cut(parent) | ||
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| def cut(self, node, parent): |
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Please provide return type hint for the function: cut. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function cut
Please provide type hint for the parameter: node
Please provide type hint for the parameter: parent
| node.parent = None | ||
| node.marked = False | ||
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| def cascading_cut(self, node): |
There was a problem hiding this comment.
Please provide return type hint for the function: cascading_cut. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function cascading_cut
Please provide type hint for the parameter: node
There was a problem hiding this comment.
class FibonacciNode:
def init(self, key) -> None:
self.key = key
self.children = []
self.marked = False
self.degree = 0
self.parent = None
class FibonacciHeap:
def init(self) -> None:
self.trees = []
self.least = None
self.count = 0
# ... (other methods)
def cascading_cut(self, node: FibonacciNode) -> None:
"""
Perform cascading cuts to handle marked nodes and maintain heap properties.
:param node: The node on which cascading cuts are applied.
"""
parent = node.parent
if parent is not None:
if not node.marked:
node.marked = True
else:
self.cut(node, parent)
self.cascading_cut(parent)
| self.cut(node, parent) | ||
| self.cascading_cut(parent) | ||
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| def update_least(self): |
There was a problem hiding this comment.
Please provide return type hint for the function: update_least. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function update_least
for more information, see https://pre-commit.ci
| self.parent = None | ||
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| class FibonacciHeap: | ||
| def __init__(self): |
There was a problem hiding this comment.
class FibonacciNode:
def init(self, key) -> None:
self.key = key
self.children = []
self.marked = False
self.degree = 0
self.parent = None
class FibonacciHeap:
def init(self) -> None:
self.trees = []
self.least = None
self.count = 0
| node.parent = None | ||
| node.marked = False | ||
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| def cascading_cut(self, node): |
There was a problem hiding this comment.
class FibonacciNode:
def init(self, key) -> None:
self.key = key
self.children = []
self.marked = False
self.degree = 0
self.parent = None
class FibonacciHeap:
def init(self) -> None:
self.trees = []
self.least = None
self.count = 0
# ... (other methods)
def cascading_cut(self, node: FibonacciNode) -> None:
"""
Perform cascading cuts to handle marked nodes and maintain heap properties.
:param node: The node on which cascading cuts are applied.
"""
parent = node.parent
if parent is not None:
if not node.marked:
node.marked = True
else:
self.cut(node, parent)
self.cascading_cut(parent)
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| @@ -0,0 +1,101 @@ | |||
| class FibonacciNode: | |||
| def __init__(self, key): | |||
There was a problem hiding this comment.
Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: key
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| class FibonacciHeap: | ||
| def __init__(self): |
There was a problem hiding this comment.
Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:
| self.least = None | ||
| self.count = 0 | ||
|
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||
| def insert(self, key): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function insert
Please provide return type hint for the function: insert. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: key
| if self.least is None or key < self.least.key: | ||
| self.least = new_node | ||
|
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||
| def extract_min(self): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function extract_min
Please provide return type hint for the function: extract_min. If the function does not return a value, please provide the type hint as: def function() -> None:
| self.consolidate() | ||
| return min_node.key | ||
|
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| def consolidate(self): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function consolidate
Please provide return type hint for the function: consolidate. If the function does not return a value, please provide the type hint as: def function() -> None:
| node.parent = None | ||
| node.marked = False | ||
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| def cascading_cut(self, node): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function cascading_cut
Please provide return type hint for the function: cascading_cut. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: node
| self.cut(node, parent) | ||
| self.cascading_cut(parent) | ||
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| def update_least(self): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function update_least
Please provide return type hint for the function: update_least. If the function does not return a value, please provide the type hint as: def function() -> None:
| @@ -0,0 +1,28 @@ | |||
| import numpy as np | |||
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| def metropolis_hastings(target_distribution, proposal_distribution, num_samples, initial_state): | |||
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file dynamic_programming/Metropolis_Hasting.py, please provide doctest for the function metropolis_hastings
Please provide return type hint for the function: metropolis_hastings. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: target_distribution
Please provide type hint for the parameter: proposal_distribution
Please provide type hint for the parameter: num_samples
Please provide type hint for the parameter: initial_state
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| return samples[1:] | ||
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| def target_distribution(x): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file dynamic_programming/Metropolis_Hasting.py, please provide doctest for the function target_distribution
Please provide return type hint for the function: target_distribution. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: x
Please provide descriptive name for the parameter: x
| def target_distribution(x): | ||
| return np.exp(-x**2 / 2) / np.sqrt(2 * np.pi) | ||
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| def proposal_distribution(x): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file dynamic_programming/Metropolis_Hasting.py, please provide doctest for the function proposal_distribution
Please provide return type hint for the function: proposal_distribution. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: x
Please provide descriptive name for the parameter: x
for more information, see https://pre-commit.ci
There was a problem hiding this comment.
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Repository:
Python:
Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.
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algorithms-keeper actions can be triggered by commenting on this PR:
@algorithms-keeper reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.
| @@ -0,0 +1,101 @@ | |||
| class FibonacciNode: | |||
| def __init__(self, key): | |||
There was a problem hiding this comment.
Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: key
|
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||
|
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| class FibonacciHeap: | ||
| def __init__(self): |
There was a problem hiding this comment.
Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:
| self.least = None | ||
| self.count = 0 | ||
|
|
||
| def insert(self, key): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function insert
Please provide return type hint for the function: insert. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: key
| if self.least is None or key < self.least.key: | ||
| self.least = new_node | ||
|
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||
| def extract_min(self): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function extract_min
Please provide return type hint for the function: extract_min. If the function does not return a value, please provide the type hint as: def function() -> None:
| self.consolidate() | ||
| return min_node.key | ||
|
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||
| def consolidate(self): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function consolidate
Please provide return type hint for the function: consolidate. If the function does not return a value, please provide the type hint as: def function() -> None:
| node.parent = None | ||
| node.marked = False | ||
|
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||
| def cascading_cut(self, node): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function cascading_cut
Please provide return type hint for the function: cascading_cut. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: node
| self.cut(node, parent) | ||
| self.cascading_cut(parent) | ||
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| def update_least(self): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/fibonacci_heap.py, please provide doctest for the function update_least
Please provide return type hint for the function: update_least. If the function does not return a value, please provide the type hint as: def function() -> None:
| @@ -0,0 +1,28 @@ | |||
| import numpy as np | |||
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| def metropolis_hastings(target_distribution, proposal_distribution, num_samples, initial_state): | |||
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/metropolish_hasting.py, please provide doctest for the function metropolis_hastings
Please provide return type hint for the function: metropolis_hastings. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: target_distribution
Please provide type hint for the parameter: proposal_distribution
Please provide type hint for the parameter: num_samples
Please provide type hint for the parameter: initial_state
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| return samples[1:] | ||
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| def target_distribution(x): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/metropolish_hasting.py, please provide doctest for the function target_distribution
Please provide return type hint for the function: target_distribution. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: x
Please provide descriptive name for the parameter: x
| def target_distribution(x): | ||
| return np.exp(-x**2 / 2) / np.sqrt(2 * np.pi) | ||
|
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| def proposal_distribution(x): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file data_structures/heap/metropolish_hasting.py, please provide doctest for the function proposal_distribution
Please provide return type hint for the function: proposal_distribution. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: x
Please provide descriptive name for the parameter: x
for more information, see https://pre-commit.ci
algorithms-keeper
bot
added
tests are failing
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Do not contribute multiple algorithms in one PR. Why did you check the checkbox if you didn't follow the instructions?
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tianyizheng02
added
invalid
multiple algorithms not allowed
Describe your change:
Added the Fibonacci heap in the DSA section
Checklist: