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[NumCS] Add code (2d quad)
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@@ -22,7 +22,47 @@ und für beliebige $d$ haben wir
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Was dasselbe ist, wie oben, aber mit $d$ Summen und $d$-mal ein $w_{j_k}$ und eine $d$-dimensionale Funktion $f$
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% https://www.slingacademy.com/article/scipy-integrate-simpson-function-4-examples/ explains scipy's n-d integration well
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% TODO: Insert code for multi dimensional quadrature from exercise
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\newpage
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\innumpy Lassen sich so die bekannten Verfahren wie die Trapez-Regel oder Simpson-Regel leicht auf höhere Dimensionen anwenden
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\begin{code}{python}
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def trapezoid_2d_mesh(f, a: float, b: float, Nx: int, c: float, d: float, Ny: int):
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""" Trapezoidal rule on a 2d function via np.meshgrid """
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x, hx = np.linspace(a, b, Nx+1, retstep=True)
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y, hy = np.linspace(c, d, Ny+1, retstep=True)
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X, Y = np.meshgrid(x, y)
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F = f(X, Y)
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# Apply once along x-axis, once along y-axis
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Q_x = hx/2 * ( 2.0 * np.sum(F[:, 1:-1], axis=1) + F[:, 0] + F[:, -1] )
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Q_y = hy/2 * ( 2.0 * np.sum( Q_x[1:-1] ) + Q_x[0] + Q_x[-1] )
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return Q_y
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def simpson_2d_weights(N: int):
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""" Generate weights for simpson rule """
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w = np.zeros(N+1)
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w[0] = 1.0; w[-1] = 1.0
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for i in range(1, N): w[i] = 2.0 if i % 2 == 0 else 4.0
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return w
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def simpson_2d_mesh(f, a: float, b: float, Nx: int, c: float, d: float, Ny: int):
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""" Simpson rule on a 2d function via np.meshrgdi """
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x, hx = np.linspace(a, b, Nx+1, retstep=True)
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y, hy = np.linspace(c, d, Ny+1, retstep=True)
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X, Y = np.meshgrid(x, y)
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F = f(X, Y)
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wx, wy = simpson_2d_weights(Nx), simpson_2d_weights(Ny)
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W = np.outer(wx, wy)
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scale = hx*hy / 3**2
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Q = scale * np.sum( W * F )
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return Q
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\end{code}
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\begin{recall}[]{Tensor-Produkt}
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\TODO Write this section
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