Б12-513 Беляков Владислав Андреевич

deprecated_tests/sem01/tests/test_lesson04_tasks.py

@@ -1,13 +1,15 @@
-import pytest 
 import random
 
+import pytest
+
 from solutions.sem01.lesson04.task1 import is_arithmetic_progression
 from solutions.sem01.lesson04.task2 import merge_intervals
 from solutions.sem01.lesson04.task3 import find_single_number
 from solutions.sem01.lesson04.task4 import move_zeros_to_end
 from solutions.sem01.lesson04.task5 import find_row_with_most_ones
 from solutions.sem01.lesson04.task6 import count_cycles
 
+
 @pytest.mark.parametrize("lst, expected", [
     pytest.param([], True, id="empty_list"),
     pytest.param([5], True, id="single_element"),

deprecated_tests/sem01/tests/test_lesson05_tasks.py

@@ -1,4 +1,4 @@
-import pytest 
+import pytest
 
 from solutions.sem01.lesson05.task1 import is_palindrome
 from solutions.sem01.lesson05.task2 import are_anagrams
@@ -7,6 +7,7 @@
 from solutions.sem01.lesson05.task5 import reg_validator
 from solutions.sem01.lesson05.task6 import simplify_path
 
+
 @pytest.mark.parametrize("s, expected", [
     pytest.param("", True, id="empty_string"),
     pytest.param("a", True, id="single_char"),

deprecated_tests/sem01/tests/test_lesson06_tasks.py

@@ -1,4 +1,4 @@
-import pytest 
+import pytest
 
 from solutions.sem01.lesson06.task1 import int_to_roman
 from solutions.sem01.lesson06.task2 import get_len_of_longest_substring
@@ -88,6 +88,7 @@ def test_is_there_any_good_subarray(nums, k, expected):
 
 import pytest
 
+
 @pytest.mark.parametrize("text, expected", [
     pytest.param("", 0, id="empty_string"),
     pytest.param("   ", 0, id="only_spaces"),

deprecated_tests/sem01/tests/test_lesson08_tasks.py

@@ -1,10 +1,10 @@
-import pytest 
 import math
 import time
 
 from solutions.sem01.lesson08.task1 import make_averager
 from solutions.sem01.lesson08.task2 import collect_statistic
 
+
 def test_make_averager():
     get_avg = make_averager(2)
 

deprecated_tests/sem01/tests/test_lesson11_tasks.py

@@ -1,9 +1,8 @@
-import pytest
-
 import math
 import sys
 from io import StringIO
 
+import pytest
 
 from solutions.sem01.lesson11.task1 import Vector2D
 

deprecated_tests/sem01/tests_hw/test_hw1_tasks.py

@@ -1,15 +1,12 @@
-import pytest
 import uuid
-from unittest.mock import MagicMock, patch, Mock
+from unittest.mock import MagicMock, Mock, patch
+
+import pytest
 
-from homeworks.sem01.hw1.aggregate_segmentation import aggregate_segmentation, ALLOWED_TYPES
+from homeworks.sem01.hw1.aggregate_segmentation import ALLOWED_TYPES, aggregate_segmentation
 from homeworks.sem01.hw1.backoff import backoff
 from homeworks.sem01.hw1.cache import lru_cache
 from homeworks.sem01.hw1.convert_exception import convert_exceptions_to_api_compitable_ones
-from .hw1_test_data.cache_test_data import (
-    TESTCASE_DATA,
-    TESTCASE_IDS,
-)
 
 NAME_BACKOFF_MODULE = "homeworks.hw1.backoff" # название модуля с backoff
 

homeworks/sem01/hw1/backoff.py

@@ -1,5 +1,3 @@
-from random import uniform
-from time import sleep
 from typing import (
     Callable,
     ParamSpec,

solutions/sem01/lesson02/task3.py

@@ -1,4 +1,4 @@
 def get_amount_of_ways_to_climb(stair_amount: int) -> int:
-    step_prev, step_curr = 1, 1
+    _step_prev, step_curr = 1, 1
     # ваш код
     return step_curr

solutions/sem01/lesson03/task1.py

@@ -1,3 +1,3 @@
 def flip_bits_in_range(num: int, left_bit: int, right_bit: int) -> int:
     # ваш код
-    return num
+    return num

solutions/sem01/lesson03/task2.py

@@ -1,3 +1,3 @@
 def get_cube_root(n: float, eps: float) -> float:
     # ваш код
-    return n
+    return n

solutions/sem01/lesson04/task1.py

@@ -1,3 +1,3 @@
 def is_arithmetic_progression(lst: list[list[int]]) -> bool:
     # ваш код
-    return False
+    return False

solutions/sem01/lesson04/task2.py

@@ -1,3 +1,3 @@
 def merge_intervals(intervals: list[list[int, int]]) -> list[list[int, int]]:
     # ваш код
-    return [[0,0]]
+    return [[0, 0]]

solutions/sem01/lesson04/task4.py

@@ -1,3 +1,3 @@
 def move_zeros_to_end(nums: list[int]) -> list[int]:
     # ваш код
-    return 0
+    return 0

solutions/sem01/lesson04/task5.py

@@ -1,3 +1,3 @@
 def find_row_with_most_ones(matrix: list[list[int]]) -> int:
     # ваш код
-    return 0
+    return 0

solutions/sem01/lesson04/task6.py

@@ -1,3 +1,3 @@
-def count_cycles(arr: list[int]) -> int: 
+def count_cycles(arr: list[int]) -> int:
     # ваш код
-    return 0
+    return 0

solutions/sem01/lesson05/task1.py

@@ -1,3 +1,3 @@
 def is_palindrome(text: str) -> bool:
     # ваш код
-    return False
+    return False

solutions/sem01/lesson05/task2.py

@@ -1,3 +1,3 @@
 def are_anagrams(word1: str, word2: str) -> bool:
     # ваш код
-    return False
+    return False

solutions/sem01/lesson05/task4.py

@@ -1,3 +1,3 @@
 def unzip(compress_text: str) -> str:
     # ваш код
-    return compress_text
+    return compress_text

solutions/sem01/lesson05/task5.py

@@ -1,3 +1,3 @@
-def reg_validator(reg_expr: str, text: str) -> bool:  
+def reg_validator(reg_expr: str, text: str) -> bool:
     # ваш код
-    return False
+    return False

solutions/sem01/lesson05/task6.py

@@ -1,3 +1,3 @@
 def simplify_path(path: str) -> str:
     # ваш код
-    return path
+    return path

solutions/sem01/lesson06/task1.py

@@ -1,3 +1,3 @@
 def int_to_roman(num: int) -> str:
     # ваш код
-    return ""
+    return ""

solutions/sem01/lesson06/task2.py

@@ -1,3 +1,3 @@
 def get_len_of_longest_substring(text: str) -> int:
     # ваш код
-    return 0
+    return 0

solutions/sem01/lesson06/task3.py

@@ -2,6 +2,5 @@ def is_there_any_good_subarray(
     nums: list[int],
     k: int,
 ) -> bool:
-
     # ваш код
     return False

solutions/sem01/lesson06/task4.py

@@ -1,3 +1,3 @@
 def count_unique_words(text: str) -> int:
     # ваш код
-    return 0
+    return 0

solutions/sem01/lesson08/task1.py

@@ -1,5 +1,6 @@
 from typing import Callable
 
+
 def make_averager(accumulation_period: int) -> Callable[[float], float]:
     # ваш код
-    pass
+    pass

solutions/sem01/lesson08/task2.py

@@ -2,9 +2,7 @@
 
 T = TypeVar("T")
 
-def collect_statistic(
-    statistics: dict[str, list[float, int]]
-) -> Callable[[T], T]:
-
+
+def collect_statistic(statistics: dict[str, list[float, int]]) -> Callable[[T], T]:
     # ваш код
-    pass
+    pass

solutions/sem01/lesson12/task3.py

@@ -1,6 +1,3 @@
-import sys
-
-
 class FileOut:
     def __init__(
         self,

solutions/sem02/lesson03/task1.py

@@ -5,16 +5,20 @@ class ShapeMismatchError(Exception):
     pass
 
 
-def sum_arrays_vectorized(
-    lhs: np.ndarray,
-    rhs: np.ndarray,
-) -> np.ndarray: ...
+def sum_arrays_vectorized(lhs: np.ndarray, rhs: np.ndarray) -> np.ndarray:
+    if len(lhs) != len(rhs):
+        raise ShapeMismatchError
+    return np.add(lhs, rhs)
 
 
-def compute_poly_vectorized(abscissa: np.ndarray) -> np.ndarray: ...
+def compute_poly_vectorized(abscissa: np.ndarray) -> np.ndarray:
+    return 3 * (abscissa**2) + 2 * abscissa + 1
 
 
-def get_mutual_l2_distances_vectorized(
-    lhs: np.ndarray,
-    rhs: np.ndarray,
-) -> np.ndarray: ...
+def get_mutual_l2_distances_vectorized(lhs: np.ndarray, rhs: np.ndarray) -> np.ndarray:
+    if lhs.shape[1] != rhs.shape[1]:
+        raise ShapeMismatchError
+
+    cube = lhs[:, np.newaxis, :] - rhs[np.newaxis, :, :]
+    distances = np.sqrt(np.sum(cube**2, axis=2))
+    return distances

solutions/sem02/lesson03/task2.py

@@ -9,11 +9,28 @@ def convert_from_sphere(
     distances: np.ndarray,
     azimuth: np.ndarray,
     inclination: np.ndarray,
-) -> tuple[np.ndarray, np.ndarray, np.ndarray]: ...
+) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
+    if not (distances.shape == azimuth.shape == inclination.shape):
+        raise ShapeMismatchError
+
+    x = distances * np.sin(inclination) * np.cos(azimuth)
+    y = distances * np.sin(inclination) * np.sin(azimuth)
+    z = distances * np.cos(inclination)
+
+    return x, y, z
 
 
 def convert_to_sphere(
     abscissa: np.ndarray,
     ordinates: np.ndarray,
     applicates: np.ndarray,
-) -> tuple[np.ndarray, np.ndarray, np.ndarray]: ...
+) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
+    if not (abscissa.shape == ordinates.shape == applicates.shape):
+        raise ShapeMismatchError
+
+    rad = np.sqrt(abscissa**2 + ordinates**2 + applicates**2)
+    azim = np.arctan2(ordinates, abscissa)
+    inc = np.arccos(applicates / rad)
+    inc = np.where(rad == 0, 0.0, inc)
+
+    return rad, azim, inc

solutions/sem02/lesson03/task3.py

@@ -3,4 +3,17 @@
 
 def get_extremum_indices(
     ordinates: np.ndarray,
-) -> tuple[np.ndarray, np.ndarray]: ...
+) -> tuple[np.ndarray, np.ndarray]:
+    if ordinates.ndim > 1 or len(ordinates) < 3:
+        raise ValueError
+
+    left = ordinates[:-2]
+    center = ordinates[1:-1]
+    right = ordinates[2:]
+
+    max = (left < center) & (center > right)
+    min = (left > center) & (center < right)
+
+    index = np.arange(1, len(ordinates) - 1)
+
+    return index[min], index[max]

solutions/sem02/lesson04/task1.py

@@ -1,17 +1,42 @@
 import numpy as np
+from matplotlib import image
 
 
 def pad_image(image: np.ndarray, pad_size: int) -> np.ndarray:
-    # ваш код
-    return image
+    H, W = image.shape[:2]
+
+    if pad_size < 1:
+        raise ValueError
+
+    if image.ndim == 2:
+        zer = np.zeros((H + 2 * pad_size, W + 2 * pad_size), dtype=image.dtype)
+        zer[pad_size : pad_size + H, pad_size : pad_size + W] = image
+    else:
+        zer = np.zeros((H + 2 * pad_size, W + 2 * pad_size, image.shape[2]), dtype=image.dtype)
+        zer[pad_size : pad_size + H, pad_size : pad_size + W, :] = image
+
+    return zer
 
 
 def blur_image(
     image: np.ndarray,
     kernel_size: int,
 ) -> np.ndarray:
-    # ваш код
-    return image
+    if kernel_size <= 0 or kernel_size % 2 == 0:
+        raise ValueError
+
+    if kernel_size == 1:
+        return image.copy()
+
+    padded_image = pad_image(image, kernel_size // 2)
+    res = np.zeros(image.shape, dtype=float)
+
+    for i in range(kernel_size):
+        for j in range(kernel_size):
+            res += padded_image[i : i + image.shape[0], j : j + image.shape[1]]
+
+    res /= kernel_size**2
+    return res.astype(np.uint8)
 
 
 if __name__ == "__main__":

solutions/sem02/lesson04/task2.py

@@ -5,6 +5,17 @@ def get_dominant_color_info(
     image: np.ndarray[np.uint8],
     threshold: int = 5,
 ) -> tuple[np.uint8, float]:
-    # ваш код
+    if threshold < 1:
+        raise ValueError("threshold must be positive")
 
-    return 0, 0
+    img = image.astype(np.int64)
+    uniq, counts = np.unique(img, return_counts=True)
+    delta = uniq[:, np.newaxis] - uniq
+    res = np.abs(delta) < threshold
+    result = np.sum(res * counts, axis=1)
+    index = np.argmax(result)
+
+    color = uniq[index]
+    percentage = result[index] / image.size
+
+    return np.uint8(color), float(percentage)

solutions/sem02/lesson05/task1.py

@@ -9,4 +9,13 @@ def can_satisfy_demand(
     costs: np.ndarray,
     resource_amounts: np.ndarray,
     demand_expected: np.ndarray,
-) -> bool: ...
+) -> bool:
+    if costs.shape[0] != len(resource_amounts):
+        raise ShapeMismatchError()
+    if costs.shape[1] != len(demand_expected):
+        raise ShapeMismatchError()
+
+    matrix = costs @ demand_expected
+    answer = (matrix <= resource_amounts).all()
+
+    return answer