added GUI for visualizing the normal distribution (by Leon Stier)

U05 Spezielle Verteilungen und Anwendungen/U05b Spezielle Verteilungen stetiger Zufallsvariablen/gui_normal_distribution.py

+import PySimpleGUI as sg
+import numpy as np
+import math
+import matplotlib.pyplot as plt
+
+sg.theme('DarkAmber')
+
+layout = [
+        #[sg.Canvas(size=(640, 480), key='canvas')],
+        [sg.Frame('Erwartungswert',[[
+            sg.Slider(range=(-5, 5), orientation='h', size=(40, 20), default_value=0, resolution = .5, enable_events=True),
+        ]]),
+        sg.Frame('Varianz',[[
+            sg.Slider(range=(0.1, 5), orientation='h', size=(40, 20), default_value=0.5, resolution= .1, enable_events=True),
+        ]])],
+        [sg.Checkbox('Track'), sg.Button('Clear'), sg.Button('Close')]
+         ]
+
+
+# Create the Window
+window = sg.Window('Gaußverteilung', layout , keep_on_top = True, finalize = True) #, no_titlebar=True
+# Event Loop to process "events" and get the "values" of the inputs
+
+while True:
+    event, values = window.read()
+    if event == sg.WIN_CLOSED or event == 'Close':	# if user closes window or clicks cancel
+        break
+    if event == 'Clear':
+        plt.clf()
+    if values[2] == False:
+        plt.clf()
+    #print('Erwartungswert: ', values[0])
+    #print("Varianz: ", values[1])
+    mue = values[0]  # Erwartungswert
+    var = values[1]  # Varianz
+    dev = math.sqrt(var)  # Standardabweichung
+    X = np.linspace(mue - 5, mue + 5, 500, endpoint=True)  # Berechnung x-Werte
+    F = (1 / (dev * math.sqrt(2 * np.pi))) * np.e ** ((-1 / 2) * (((X - mue) / dev) ** 2))  # Berechnung Gaussverteilung
+    plt.plot(X, F)
+    startx, endx = mue - 5, mue + 5
+    starty, endy = -0.1, 1
+    plt.axis([startx, endx, starty, endy])
+
+    fig = plt.gcf()  # Grabs the current figure
+    fig.show()
+
+window.close()