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120 lines
5.0 KiB
Python
120 lines
5.0 KiB
Python
#
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# Copyright (c) 2024 Maxim Slipenko, Eugene Lazurenko.
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#
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# This file is part of Statapp
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# (see https://github.com/shizand/statapp).
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program. If not, see <http://www.gnu.org/licenses/>.
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#
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import numpy as np
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from PySide2.QtCore import Qt
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from PySide2.QtWidgets import QDialog, QHeaderView
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from statapp.calculations import linearPolynom, prediction
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from statapp.combo_delegate import ComboDelegate
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from statapp.mathtex_header_view import MathTexHeaderView
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from statapp.models.prediction_table_model import PreditionTableModel
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from statapp.models.transform_polynom_model import TransformPolynomModel, TRANSFORMS
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from statapp.polynoms.polynom_window import MplCanvas
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from statapp.ui.ui_polynom_window import Ui_PolynomWindow
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from statapp.utils import addIcon, onError
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class TransformPolynomWindow(QDialog):
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def __init__(self, data):
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super().__init__()
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self.ui = Ui_PolynomWindow()
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self.ui.setupUi(self)
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addIcon(self)
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self.setWindowTitle("Преобразования")
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self.data = data
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result = linearPolynom(data)
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try:
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predictionResult = prediction(data, result)
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except Exception as error:
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onError(error)
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self.predictionModel = PreditionTableModel(predictionResult)
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self.ui.predictionTableView.setModel(self.predictionModel)
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header = self.ui.predictionTableView.horizontalHeader()
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header.setSectionResizeMode(QHeaderView.ResizeMode.Stretch)
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self.sc = MplCanvas(self, width=5, height=4, dpi=100)
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xAxes = np.array(range(len(data[:, 0])))
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realY = predictionResult[:, 0]
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calculatedY = predictionResult[:, 1]
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self.sc.axes.scatter(xAxes, realY)
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self.sc.axes.plot(xAxes, calculatedY)
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self.ui.plotContainer.addWidget(self.sc)
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# Создание столбца из нулей
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zeroCol = np.zeros((result.paramsAndImportance.shape[0], 1))
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# Добавление столбца к исходному массиву
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result.paramsAndImportance = np.column_stack((zeroCol, result.paramsAndImportance))
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# self.ui.tableView.setItemDelegate(FloatDelegate())
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self.ui.tableView.setItemDelegate(
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ComboDelegate(
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self.ui.tableView,
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list(TRANSFORMS.keys()),
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list(TRANSFORMS.keys()),
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)
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)
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self.model = TransformPolynomModel(result)
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self.ui.tableView.setModel(self.model)
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self.ui.tableView.setVerticalHeader(MathTexHeaderView(self.ui.tableView))
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header = self.ui.tableView.horizontalHeader()
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header.setSectionResizeMode(QHeaderView.ResizeMode.Stretch)
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self.ui.residualVarianceValueLabel.setText(str(result.residualVariance))
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self.ui.scaledResidualVarianceValueLabel.setText(str(result.scaledResidualVariance))
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self.ui.fStatisticValueLabel.setText(str(result.fStatistic))
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self.ui.rSquaredValueLabel.setText(str(result.rSquared))
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self.model.dataChanged.connect(self.on_data_changed)
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def on_data_changed(self):
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data = np.copy(self.data)
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for i in range(len(data[0:])):
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for j in range(1, len(data[i])):
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tr = self.model.data(self.model.createIndex(j, 0), Qt.DisplayRole)
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data[i][j] = TRANSFORMS[tr](data[i][j])
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try:
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self.rebuildData(data)
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except Exception as error:
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onError(error)
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def rebuildData(self, data):
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result = linearPolynom(data)
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predictionResult = prediction(data, result)
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self.predictionModel.updateAllData(predictionResult)
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self.ui.plotContainer.removeWidget(self.sc)
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self.sc = MplCanvas(self, width=5, height=4, dpi=100)
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xAxes = np.array(range(len(data[:, 0])))
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realY = predictionResult[:, 0]
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calculatedY = predictionResult[:, 1]
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self.sc.axes.scatter(xAxes, realY)
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self.sc.axes.plot(xAxes, calculatedY)
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self.ui.plotContainer.addWidget(self.sc)
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zeroCol = np.zeros((result.paramsAndImportance.shape[0], 1))
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result.paramsAndImportance = np.column_stack((zeroCol, result.paramsAndImportance))
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self.model.updateAllData(result)
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self.ui.residualVarianceValueLabel.setText(str(result.residualVariance))
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self.ui.scaledResidualVarianceValueLabel.setText(str(result.scaledResidualVariance))
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self.ui.fStatisticValueLabel.setText(str(result.fStatistic))
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self.ui.rSquaredValueLabel.setText(str(result.rSquared))
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