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author | Nao Pross <np@0hm.ch> | 2022-05-28 20:32:55 +0200 |
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committer | Nao Pross <np@0hm.ch> | 2022-05-28 20:32:55 +0200 |
commit | e40d26d336a353834461cbd8a86da00f1eb980cb (patch) | |
tree | 48150542404870b1e1cf0fca797660fdaceeb189 /presentation/figures | |
parent | Update slides (diff) | |
download | FourierOnS2-e40d26d336a353834461cbd8a86da00f1eb980cb.tar.gz FourierOnS2-e40d26d336a353834461cbd8a86da00f1eb980cb.zip |
Diffstat (limited to 'presentation/figures')
-rw-r--r-- | presentation/figures/polynomials.py | 71 |
1 files changed, 71 insertions, 0 deletions
diff --git a/presentation/figures/polynomials.py b/presentation/figures/polynomials.py new file mode 100644 index 0000000..f622afe --- /dev/null +++ b/presentation/figures/polynomials.py @@ -0,0 +1,71 @@ +import numpy as np +import pandas as pd +import scipy.special + +import seaborn as sns +import seaborn_image as isns +import matplotlib.pyplot as plt + +import toolz + +# Basis functions for 2D Fourier + +@np.vectorize +@toolz.curry +def b(m, n, mu, nu): + return np.exp(2j * np.pi * (m * mu + n * nu)) + +N = 100 +H = 4 + +basis = [] +for m in range(H): + for n in range(H + 1): + mu = np.linspace(0, 1, N) + nu = np.linspace(0, 1, N) + muv, nuv = np.meshgrid(mu, nu) + + bs = np.real(b(m, n, muv, nuv)) + basis.append(bs) + +g = isns.ImageGrid(basis, col_wrap=(H + 1), cbar=False) +g.fig.savefig("flat-basis-functions.pdf") + +plt.tight_layout() +plt.show() + +# Legendre Polynomials + +N = 100 + +sns.set_theme("talk", "darkgrid", font_scale=.75) +fig, axes = plt.subplots(3, 4, figsize=(12, 8)) + +x = np.linspace(-1, 1, N) +for n in range(np.prod(axes.shape)): + p = scipy.special.lpmv(0, n, x) + # axes.ravel()[n].plot(x, p) + sns.lineplot(ax=axes.ravel()[n], x=x, y=p) + +plt.tight_layout() +fig.savefig("legendre-polynomials.pdf") +plt.show() + +# Associated Legendre Polynomials + +N = 100 + +sns.set_theme("talk", "darkgrid", font_scale=.75) +fig, axes = plt.subplots(2, 3, figsize=(12, 8)) + +x = np.linspace(-1, 1, N) + +for m in range(3 * 2): + for n in range(5): + p = scipy.special.lpmv(m, m + n, x) + sns.lineplot(ax=axes.ravel()[m], x=x, y=p) + # sns.lineplot(x=x, y=p) + +plt.tight_layout() +fig.savefig("associated-legendre-polynomials.pdf") +plt.show() |