feat: добавлен график (#94)

Closes #86

statapp/polynoms/polynom_window.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2023 Maxim Slipenko, Eugene Lazurenko.
+# Copyright (c) 2024 Maxim Slipenko, Eugene Lazurenko.
 #
 # This file is part of Statapp
 # (see https://github.com/shizand/statapp).
@@ -17,7 +17,11 @@
 # You should have received a copy of the GNU General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 #
+import numpy as np
 from PySide2.QtWidgets import QDialog, QHeaderView
+import matplotlib
+from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg
+from matplotlib.figure import Figure
 
 from statapp.calculations import prediction
 from statapp.mathtex_header_view import MathTexHeaderView
@@ -27,6 +31,15 @@ from statapp.ui.ui_polynom_window import Ui_PolynomWindow
 from statapp.utils import addIcon, FloatDelegate
 
 
+matplotlib.use('Qt5Agg')
+
+class MplCanvas(FigureCanvasQTAgg):
+
+    def __init__(self, parent=None, width=5, height=4, dpi=100):
+        fig = Figure(figsize=(width, height), dpi=dpi)
+        self.axes = fig.add_subplot()
+        super().__init__(fig)
+
 class PolynomWindow(QDialog):
     def __init__(self, data, result, windowTitle):
         super().__init__()
@@ -47,7 +60,30 @@ class PolynomWindow(QDialog):
         self.ui.fStatisticValueLabel.setText(str(result.fStatistic))
         self.ui.rSquaredValueLabel.setText(str(result.scaledResidualVariance))
 
-        self.predictionModel = PreditionTableModel(prediction(data, result))
+        predictionResult = prediction(data, result)
+
+        self.predictionModel = PreditionTableModel(predictionResult)
         self.ui.predictionTableView.setModel(self.predictionModel)
         header = self.ui.predictionTableView.horizontalHeader()
         header.setSectionResizeMode(QHeaderView.ResizeMode.Stretch)
+
+        sc = MplCanvas(self, width=5, height=4, dpi=100)
+
+        xAxes = np.array(range(len(data[:, 0])))
+
+        realY = predictionResult[:, 0]
+        calculatedY = predictionResult[:, 1]
+
+        print(xAxes)
+        print(realY)
+        print(calculatedY)
+
+        sc.axes.scatter(xAxes, realY)
+
+        # xnew = np.linspace(xAxes.min(), xAxes.max(), 300)
+        # gfg = scipy.interpolate.make_interp_spline(xAxes, y, k=3)
+        # y_new = gfg(xnew)
+
+        sc.axes.plot(xAxes, calculatedY)
+
+        self.ui.plotContainer.addWidget(sc)