Merge branch 'TheAlgorithms:master' into master

This commit is contained in:
Maxim Smolskiy 2024-05-06 22:36:48 +03:00 committed by GitHub
commit 1e66d4be16
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5 changed files with 59 additions and 31 deletions

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@ -1,5 +1,6 @@
from __future__ import annotations
from abc import abstractmethod
from math import pi
from typing import Protocol
@ -8,6 +9,7 @@ import numpy as np
class FilterType(Protocol):
@abstractmethod
def process(self, sample: float) -> float:
"""
Calculate y[n]
@ -15,7 +17,6 @@ class FilterType(Protocol):
>>> issubclass(FilterType, Protocol)
True
"""
return 0.0
def get_bounds(

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@ -1,4 +1,6 @@
#!/usr/bin/env python3
from abc import abstractmethod
from .number_theory.prime_numbers import next_prime
@ -173,6 +175,7 @@ class HashTable:
self.values[key] = data
self._keys[key] = data
@abstractmethod
def _collision_resolution(self, key, data=None):
"""
This method is a type of open addressing which is used for handling collision.

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@ -11,7 +11,7 @@ class QuadraticProbing(HashTable):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
def _collision_resolution(self, key, data=None):
def _collision_resolution(self, key, data=None): # noqa: ARG002
"""
Quadratic probing is an open addressing scheme used for resolving
collisions in hash table.

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@ -76,11 +76,8 @@ max-complexity = 17 # default: 10
[tool.ruff.lint.per-file-ignores]
"arithmetic_analysis/newton_raphson.py" = ["PGH001"]
"audio_filters/show_response.py" = ["ARG002"]
"data_structures/binary_tree/binary_search_tree_recursive.py" = ["BLE001"]
"data_structures/binary_tree/treap.py" = ["SIM114"]
"data_structures/hashing/hash_table.py" = ["ARG002"]
"data_structures/hashing/quadratic_probing.py" = ["ARG002"]
"data_structures/hashing/tests/test_hash_map.py" = ["BLE001"]
"data_structures/heap/max_heap.py" = ["SIM114"]
"graphs/minimum_spanning_tree_prims.py" = ["SIM114"]

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@ -11,11 +11,11 @@ They are synchronized with locks and message passing but other forms of
synchronization could be used.
"""
from multiprocessing import Lock, Pipe, Process
import multiprocessing as mp
# lock used to ensure that two processes do not access a pipe at the same time
# NOTE This breaks testing on build runner. May work better locally
# process_lock = Lock()
# process_lock = mp.Lock()
"""
The function run by the processes that sorts the list
@ -29,8 +29,17 @@ resultPipe = the pipe used to send results back to main
"""
def oe_process(position, value, l_send, r_send, lr_cv, rr_cv, result_pipe):
process_lock = Lock()
def oe_process(
position,
value,
l_send,
r_send,
lr_cv,
rr_cv,
result_pipe,
multiprocessing_context,
):
process_lock = multiprocessing_context.Lock()
# we perform n swaps since after n swaps we know we are sorted
# we *could* stop early if we are sorted already, but it takes as long to
@ -38,27 +47,23 @@ def oe_process(position, value, l_send, r_send, lr_cv, rr_cv, result_pipe):
for i in range(10):
if (i + position) % 2 == 0 and r_send is not None:
# send your value to your right neighbor
process_lock.acquire()
r_send[1].send(value)
process_lock.release()
with process_lock:
r_send[1].send(value)
# receive your right neighbor's value
process_lock.acquire()
temp = rr_cv[0].recv()
process_lock.release()
with process_lock:
temp = rr_cv[0].recv()
# take the lower value since you are on the left
value = min(value, temp)
elif (i + position) % 2 != 0 and l_send is not None:
# send your value to your left neighbor
process_lock.acquire()
l_send[1].send(value)
process_lock.release()
with process_lock:
l_send[1].send(value)
# receive your left neighbor's value
process_lock.acquire()
temp = lr_cv[0].recv()
process_lock.release()
with process_lock:
temp = lr_cv[0].recv()
# take the higher value since you are on the right
value = max(value, temp)
@ -94,39 +99,60 @@ def odd_even_transposition(arr):
>>> odd_even_transposition(unsorted_list) == sorted(unsorted_list + [1])
False
"""
# spawn method is considered safer than fork
multiprocessing_context = mp.get_context("spawn")
process_array_ = []
result_pipe = []
# initialize the list of pipes where the values will be retrieved
for _ in arr:
result_pipe.append(Pipe())
result_pipe.append(multiprocessing_context.Pipe())
# creates the processes
# the first and last process only have one neighbor so they are made outside
# of the loop
temp_rs = Pipe()
temp_rr = Pipe()
temp_rs = multiprocessing_context.Pipe()
temp_rr = multiprocessing_context.Pipe()
process_array_.append(
Process(
multiprocessing_context.Process(
target=oe_process,
args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0]),
args=(
0,
arr[0],
None,
temp_rs,
None,
temp_rr,
result_pipe[0],
multiprocessing_context,
),
)
)
temp_lr = temp_rs
temp_ls = temp_rr
for i in range(1, len(arr) - 1):
temp_rs = Pipe()
temp_rr = Pipe()
temp_rs = multiprocessing_context.Pipe()
temp_rr = multiprocessing_context.Pipe()
process_array_.append(
Process(
multiprocessing_context.Process(
target=oe_process,
args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i]),
args=(
i,
arr[i],
temp_ls,
temp_rs,
temp_lr,
temp_rr,
result_pipe[i],
multiprocessing_context,
),
)
)
temp_lr = temp_rs
temp_ls = temp_rr
process_array_.append(
Process(
multiprocessing_context.Process(
target=oe_process,
args=(
len(arr) - 1,
@ -136,6 +162,7 @@ def odd_even_transposition(arr):
temp_lr,
None,
result_pipe[len(arr) - 1],
multiprocessing_context,
),
)
)