pie: apply some fixes

pie/Matrix_dz.py

@@ -79,7 +79,7 @@ def __rmul__(self, m: int | Matrix) -> Matrix | None:
         return res
 
     @staticmethod
-    def findpivot(matr: list, r: int, c: int) -> tuple:  # нахождение "опорного элемента"
+    def findpivot(matr: list, r: int, c: int) -> tuple | None:  # нахождение "опорного элемента"
         for i in range(c, len(matr[0])):
             for j in range(r, len(matr)):
                 if matr[j][i] != 0:
@@ -170,7 +170,7 @@ def transposition_new(self) -> Matrix:
     def __str__(self) -> str:
         res = ""
         for i in range(self.rows):
-            res += str(self.matr[i]) + "\n"
+            res += f"{self.matr[i]}\n"
         return res
 
 
@@ -179,13 +179,13 @@ def __str__(self) -> str:
 
 # генерация наших точек, для удобства ограничиваем область, в которой можно получить эти точки
 for i in range(10):
-    x = secrets.randbelow(0, 30) / 10
-    y = secrets.randbelow(0, 30) / 10
+    x = secrets.randbelow(30) / 10
+    y = secrets.randbelow(30) / 10
 
     while True:
         if x / sqrt(x**2 + y**2) < cos(pi / 4):
-            x = secrets.randbelow(0, 30) / 10
-            y = secrets.randbelow(0, 30) / 10
+            x = secrets.randbelow(30) / 10
+            y = secrets.randbelow(30) / 10
         else:
             break
     matrix_array.append(Matrix(2, 1, [[x], [y]]))

pie/complex_dz.py

@@ -7,23 +7,27 @@ class CNumb:
     def __init__(self, real: float = 1.0, im: float = 0.0) -> None:
         self.real = real
         self.im = im
-        self.mod: float = sqrt(real**2 + im**2)
 
-        if real > 0 and im >= 0:
-            self.arg: float = atan(im / real)
+    def mod(self) -> float:
+        return sqrt(self.real**2 + self.im**2)
 
-        elif real > 0 and im < 0:
-            self.arg: float = atan(im / real) + 2 * pi
+    def arg(self) -> float:
+        if self.real > 0 and self.im >= 0:
+            return atan(self.im / self.real)
 
-        elif real < 0:
-            self.arg: float = atan(im / real) + pi
+        if self.real > 0 and self.im < 0:
+            return atan(self.im / self.real) + 2 * pi
 
-        elif real == 0:
-            if im < 0:
-                self.arg: float = 2 * pi - 0
+        if self.real < 0:
+            return atan(self.im / self.real) + pi
 
-            elif im > 0:
-                self.arg: float = pi * 0
+        if self.im < 0:
+            return 1.5 * pi
+
+        if self.im > 0:
+            return pi * 0.5
+
+        return 0.0
 
     def __add__(self, a: float | CNumb) -> CNumb:
         if isinstance(a, CNumb):
@@ -74,23 +78,21 @@ def __rsub__(self, a: float | CNumb) -> CNumb:
 
     def __pow__(self, a: float) -> CNumb:
         return CNumb(
-            (self.mod**a) * (cos(atan(a * self.arg))),
-            (self.mod**a) * (sin(atan(a * self.arg))),
+            (self.mod() ** a) * (cos(atan(a * self.arg()))),
+            (self.mod() ** a) * (sin(atan(a * self.arg()))),
         )
 
     def rad(self, a: int) -> list[str]:
-        resultc = []
-        for j in range(a):
-            resultc += [
-                str((self.mod ** (1 / a)) * (cos(atan((self.arg + 2 * pi * j) / a))))
-                + "+"
-                + str((self.mod ** (1 / a)) * (sin(atan((self.arg + 2 * pi * j) / a))))
-                + "i",
-            ]
-        return resultc
+        return [
+            str((self.mod() ** (1 / a)) * (cos(atan((self.arg() + 2 * pi * j) / a))))
+            + "+"
+            + str((self.mod() ** (1 / a)) * (sin(atan((self.arg() + 2 * pi * j) / a))))
+            + "i"
+            for j in range(a)
+        ]
 
     def __str__(self) -> str:
-        return str(self.real) + "+" + str(self.im) + "i"
+        return f"{self.real}+{self.im}i"
 
 
 n = CNumb(1, 2)

pie/merge_parallel.py

@@ -41,11 +41,11 @@ def merge_sort(arr: list[int]) -> list[int]:
 
 
 def generation(length: int) -> list[int]:
-    return [randbelow(10000) for _ in range(length)]
+    return [(randbelow(1000) + 1) * 10 for _ in range(length)]
 
 
 if __name__ == "__main__":
-    data1 = map(generation, [randbelow(100000) for _ in range(100)])
+    data1 = map(generation, [(randbelow(10000) + 1) * 10 for _ in range(100)])
     data2 = copy.deepcopy(data1)
     start = perf_counter()
     with mlp.Pool(processes=mlp.cpu_count()) as pool: