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