HM1_Aufgabenserie1/roman_schenk_S1_Aufg1.py

50 lines
1.2 KiB
Python
Raw Permalink Normal View History

2022-09-24 19:18:32 +02:00
import numpy as np
import matplotlib.pyplot as plt
2022-09-24 19:55:14 +02:00
xmin, xmax, xsteps = -10, 10, 0.1
plotLegend = []
2022-09-24 19:18:32 +02:00
2022-09-24 19:55:14 +02:00
def showPlot():
2022-09-24 19:18:32 +02:00
plt.xlim(-11, 11)
2022-09-24 19:22:58 +02:00
plt.xticks(np.arange(xmin, xmax + xsteps, 1.0))
2022-09-24 19:55:14 +02:00
plt.xlabel("x")
2022-09-24 19:18:32 +02:00
plt.ylim(-1300, 1300)
2022-09-24 19:55:14 +02:00
plt.ylabel("y")
2022-09-24 19:18:32 +02:00
plt.grid(markevery=1)
2022-09-24 19:55:14 +02:00
plt.legend(plotLegend)
plt.title("Aufgabe 1")
2022-09-24 19:18:32 +02:00
plt.show()
2022-09-24 19:55:14 +02:00
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()