diff --git a/src/optimierung/allgemeiner_newton_verfahren.py b/src/optimierung/allgemeiner_newton_verfahren.py
index 4b26a95..f98b2b8 100644
--- a/src/optimierung/allgemeiner_newton_verfahren.py
+++ b/src/optimierung/allgemeiner_newton_verfahren.py
@@ -8,7 +8,8 @@ N = 200
 x = sp.Symbol("x")
 
 # Funktion
-f_sym = x**4 - 10 * x**2 + x
+# f_sym = x**4 - 10 * x**2 + x
+f_sym = -sp.cos(2 * sp.pi * x)
 
 # Ableitungen
 f = sp.lambdify(x, f_sym, "numpy")
@@ -16,7 +17,8 @@ f_prime = sp.lambdify(x, sp.diff(f_sym, x), "numpy")
 f_second = sp.lambdify(x, sp.diff(f_sym, x, 2), "numpy")
 
 # Daten
-x_data = np.linspace(-4, 4, N)
+# x_data = np.linspace(-4, 4, N)
+x_data = np.linspace(-3, 3, N)
 f_data = f(x_data)
 
 # Plot
@@ -29,11 +31,12 @@ plt.show()
 
 # Newton Verfahren
 # Startwert
-startwerte = [0.1]
+startwerte = [0.01, 0.02, 0.05, 0.1, 0.2, 0.23, 0.24, 0.245, 0.248, 0.249, 0.2499]
 
 # Iterationsformel
 x_n = lambda x: x - f_prime(x) / np.abs(f_second(x))
 
+print(60 * "-")
 # Iteration
 for x_0 in startwerte:
     n = 0
@@ -51,4 +54,5 @@ for x_0 in startwerte:
         f_x_second = f_second(x_i)
         print(f"x_{n}: {x_i}\nf'(x_{n}): {f_x_prime}\nf''(x_{n}): {f_x_second}\n")
         limit -= 1
+    print(60 * "-")
 # %%