Serie 03
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45
Kuengjoe_S03/Kuengjoe_S03_Aufg3b.py
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Kuengjoe_S03/Kuengjoe_S03_Aufg3b.py
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import numpy as np
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import matplotlib.pyplot as plt
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def f(x):
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return 5.0 * (2.0 * x**2)**(-1.0/3.0)
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def g(x):
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return 10.0**5 * (2.0 * np.e)**(-x/100.0)
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def h_exp(x):
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return (625.0/64.0)**x
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# (i)
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x1 = np.logspace(-3, 2, 4000) # 0.001 ... 100
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y1 = f(x1)
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plt.figure()
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plt.loglog(x1, y1)
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plt.title("Aufg. 3b (i) – f(x) as straight line in log-log")
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plt.xlabel("x")
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plt.ylabel("f(x)")
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plt.grid(True, which="both")
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# (ii)
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x2 = np.linspace(1e-6, 100.0, 4000)
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y2 = g(x2)
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plt.figure()
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plt.semilogy(x2, y2)
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plt.title("Aufg. 3b (ii) – g(x) as straight line in semilog-y")
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plt.xlabel("x")
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plt.ylabel("g(x)")
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plt.grid(True, which="both")
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# (iii)
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x3 = np.linspace(1e-6, 100.0, 4000)
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y3 = h_exp(x3)
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plt.figure()
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plt.semilogy(x3, y3)
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plt.title("Aufg. 3b (iii) – h(x) as straight line in semilog-y")
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plt.xlabel("x")
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plt.ylabel("h(x)")
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plt.grid(True, which="both")
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plt.show()
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42
Kuengjoe_S03/Kuengjoe_S03_Aufg4.py
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Kuengjoe_S03/Kuengjoe_S03_Aufg4.py
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import numpy as np
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import matplotlib.pyplot as plt
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def g(x):
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# Naive Form des Polynoms 100 x² − 200 x + 99
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return 100*x**2 - 200*x + 99
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def g_fact(x):
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# Faktorisierte Form 100 (x − 1.1)(x − 0.9) – vermeidet Auslöschung
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return 100*(x-1.1)*(x-0.9)
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def h(x, factored=False):
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# Liefert h(x) = sqrt(g(x)); bei factored=True wird die stabile Variante
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# g_fact(x) verwendet
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return np.sqrt(g_fact(x) if factored else g(x))
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def kappa_h(x):
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# Konditionszahl κ_h(x) = |x * h'(x) / h(x)|
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# mit h'(x) = 100 (x − 1) / h(x)
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return np.abs(x * 100*(x-1) / (h(x)**2))
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# a) Vergleich der Auswertungen
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x_test = 1.1 + np.array([1e-8, 1e-7, 1e-6, 1e-5])
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print("x h_naiv h_fakt relFehler")
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for x in x_test:
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# instabile Auswertung
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h_naiv = h(x)
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# stabile Auswertungm
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h_fakt = h(x, factored=True)
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relerr = abs(h_naiv - h_fakt)/abs(h_fakt)
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print(f"{x:.10f} {h_naiv:.12e} {h_fakt:.12e} {relerr:.2e}")
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# b) Plot der Konditionszahl κ_h(x) auf [1.1, 1.3]
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dx = 1e-7
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x_vals = np.arange(1.1 + dx, 1.3 + dx, dx)
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plt.semilogy(x_vals, kappa_h(x_vals))
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plt.xlabel("x")
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plt.ylabel(r"$\kappa_h(x)$")
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plt.title("Konditionszahl von $h(x)$ auf [1.1, 1.3]")
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plt.grid(True, which="both", ls="--", alpha=0.6)
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plt.tight_layout()
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plt.show()
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