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refactor: создана функция generate_x_values

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This commit is contained in:
Maxim Slipenko 2023-10-01 22:37:08 +03:00
parent 6da0487500
commit 6879747938
2 changed files with 28 additions and 26 deletions
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25
statapp/calculations.py
View File

@ -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([

29
statapp/main_window.py
View File

@ -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