Solved Task 1

roman_schenk_S1_Aufg1.py

@@ -1,17 +1,50 @@
 import numpy as np
 import matplotlib.pyplot as plt
 
-def fun_f(x):
+xmin, xmax, xsteps = -10, 10, 0.1
-    return x ** 5 - 5 * x ** 4 - 30 * x ** 3 + 110 * x ** 2 + 29 * x - 105
+plotLegend = []
 
-def plot_f(xmin, xmax, xsteps):
+def showPlot():
-    x = np.arange(xmin, xmax + xsteps, xsteps)
-    f = np.array(fun_f(x))
-    plt.plot(x, f)
     plt.xlim(-11, 11)
     plt.xticks(np.arange(xmin, xmax + xsteps, 1.0))
+    plt.xlabel("x")
     plt.ylim(-1300, 1300)
+    plt.ylabel("y")
     plt.grid(markevery=1)
+    plt.legend(plotLegend)
+    plt.title("Aufgabe 1")
     plt.show()
 
-#plot_f(-10, 10, 0.1)
+def function_f(x):
+    return x ** 5 - 5 * x ** 4 - 30 * x ** 3 + 110 * x ** 2 + 29 * x - 105
+
+def derivative_f(x):
+    return 5 * x ** 4 - 20 * x ** 3 - 90 * x ** 2 + 220 * x + 29
+
+def integral_f(x):
+    c = 0
+    return (1/6) * x ** 6 - x ** 5 - (30/4) * x ** 4 + (110/3) * x ** 3 + (29/2) * x ** 2 - 105 * x + c
+
+def plot_function_f():
+    x = np.arange(xmin, xmax + xsteps, xsteps)
+    f = np.array(function_f(x))
+    plt.plot(x, f)
+    plotLegend.append('f(x)')
+
+def plot_derivative_f():
+    x = np.arange(xmin, xmax + xsteps, xsteps)
+    f = np.array(derivative_f(x))
+    plt.plot(x, f)
+    plotLegend.append('f\'(x)')
+
+def plot_integral_f():
+    x = np.arange(xmin, xmax + xsteps, xsteps)
+    f = np.array(integral_f(x))
+    plt.plot(x, f)
+    plotLegend.append('F(x)')
+
+if __name__ == "__main__":
+    plot_function_f()
+    plot_derivative_f()
+    plot_integral_f()
+    showPlot()