refactor: создана функция generate_x_values

statapp/calculations.py

@@ -1,5 +1,30 @@
 import numpy as np
 
+DIRECT_LINK = 0
+INDIRECT_LINK = 1
+
+def generate_x_values(mean, std, typeConnection, y):
+    yMean = np.mean(y)
+    values = []
+    for cur_y in y:
+        k = np.abs(cur_y / yMean)
+        if k > 1:
+            k = 2 - 1 / k
+        if typeConnection == INDIRECT_LINK:
+            k = 1 / k
+        if std == 0:
+            k = 1
+
+        x = np.random.normal(mean * (k ** 3), std * k)
+        values.append(x)
+        # if (x > gfw.mat and cur_y > yMat) or (x < gfw.mat and cur_y < yMat):
+        #     dd = np.append(dd, 1)
+        # else:
+        #     dd = np.append(dd, 0)
+
+    # x_arr = x_arr.reshape(len(x_arr), 1)
+
+    return np.array(values)
 
 def variance_analysis(data):
     return np.array([

statapp/main_window.py

@@ -3,6 +3,7 @@ from PySide2.QtCore import Slot, QLocale, QSize
 from PySide2.QtGui import QIcon
 from PySide2.QtWidgets import QMainWindow, QMessageBox, QApplication
 
+from statapp.calculations import generate_x_values
 from statapp.generate_factor_window import GenerateFactorWindow, INDIRECT_LINK
 from statapp.models.input_values_model import InputValuesModel
 from statapp.generate_window import GenerateWindow
@@ -81,36 +82,12 @@ class MainWindow(QMainWindow):
     def on_generateXaction_triggered(self):
         gfw = GenerateFactorWindow()
 
-        # dd = np.array([])
-
         if gfw.exec():
-            y = self.model.getY()
-            yMat = np.mean(y)
-
-            x_arr = np.array([])
-
-            for cur_y in y:
-                k = np.abs(cur_y / yMat)
-                if k > 1:
-                    k = 2 - 1 / k
-                if gfw.typeConnection == INDIRECT_LINK:
-                    k = 1 / k
-                if gfw.deviation == 0:
-                    k = 1
-
-                x = np.random.normal(gfw.mat * (k ** 3), gfw.deviation * k, size=1)
-                x_arr = np.append(x_arr, x)
-                # if (x > gfw.mat and cur_y > yMat) or (x < gfw.mat and cur_y < yMat):
-                #     dd = np.append(dd, 1)
-                # else:
-                #     dd = np.append(dd, 0)
-
             data = self.model.getData()
-
+            y = self.model.getY()
+            x_arr = generate_x_values(gfw.mat, gfw.deviation, gfw.typeConnection, y)
             x_arr = x_arr.reshape(len(x_arr), 1)
-            # dd = dd.reshape(len(dd), 1)
             data = np.concatenate((data, x_arr), axis=1)
-            # data = np.concatenate((data, dd), axis=1)
             self.model.updateAllData(data)
             self.isDataChanged = True