33 lines
1.0 KiB
Python
33 lines
1.0 KiB
Python
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import numpy as np
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from Schenk_Brandenberger_S9_Aufg2 import *
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import matplotlib.pyplot as plt
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all_dxmax = np.array([])
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all_dxobs = np.array([])
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dxmax_dxobs_ratio = np.array([])
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index = np.arange(0,1000,1)
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for i in range(1000):
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A = np.random.rand(100,100)
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b = np.random.rand(100,1)
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A_approx = A + np.random.rand(100,100)/1e5
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b_approx = b + np.random.rand(100,1)/1e5
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[x, x_approx, dxmax, dxobs] = Schenk_Brandenberger_S9_Aufg2(A, A_approx, b, b_approx)
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all_dxmax = np.append(all_dxmax, [dxmax], axis=0)
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all_dxobs = np.append(all_dxobs, [dxobs], axis=0)
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dxmax_dxobs_ratio = np.append(dxmax_dxobs_ratio, [dxmax/dxobs], axis=0)
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plt.figure(1)
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plt.semilogy(all_dxmax)
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plt.semilogy(all_dxobs)
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plt.semilogy(dxmax_dxobs_ratio)
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plt.legend(["dxmax", "dxob", "dxmax/dxobs"])
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plt.grid()
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plt.xlabel("x")
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plt.ylabel("f(x)")
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plt.title("Aufgabe 3 Serie 9")
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plt.show()
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#Die obere Schranke dxmax liegt immer dxobs, deshalb ist sie sicher realistisch und korrekt
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#Jedoch liegt die obere Schranke immer etwa den Faktor 1e3 über dxobs
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