Swash processing for article
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2 changed files with 9 additions and 3 deletions
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@ -4,6 +4,7 @@ import logging
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import pathlib
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import pathlib
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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from matplotlib.ticker import MultipleLocator, LogLocator, NullFormatter
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import numpy as np
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import numpy as np
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import scipy.signal as sgl
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import scipy.signal as sgl
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@ -49,12 +50,13 @@ J = 1 / dj * np.log2(N * dt / s0)
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j = np.arange(0, J)
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j = np.arange(0, J)
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sj = s0 * 2 ** (j * dj)
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sj = s0 * 2 ** (j * dj)
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Mw = sj / dt
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Mw = sj / dt
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sig = np.var(watl[:, i0])
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sig = np.std(watl[:, i0])
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M = np.stack([(np.abs(sgl.cwt(watl[:, i], sgl.morlet2, Mw))/sig)**2 for i in i0])
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M = np.stack([(np.abs(sgl.cwt(watl[:, i], sgl.morlet2, Mw))/sig)**2 for i in i0])
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v = np.max(M)
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v = np.max(M)
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T = 2 * sj * np.pi / 5
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for ax_x, M_, x_ in zip(ax.reshape(-1), M, x[i0]):
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for ax_x, M_, x_ in zip(ax.reshape(-1), M, x[i0]):
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c = ax_x.contourf(t, sj, M_, cmap="Greys", vmin=0, levels=[1, 2.5, 5, 10, 20, 40], extend="both")
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c = ax_x.contourf(t, T, M_, cmap="Greys", vmin=0, levels=[1, 2.5, 5, 10, 20, 40], extend="both")
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fig_x.colorbar(c, ax=ax_x, label="NWPS")
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fig_x.colorbar(c, ax=ax_x, label="NWPS")
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ax_x.grid(color="k", alpha=0.2)
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ax_x.grid(color="k", alpha=0.2)
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ax_x.text(
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ax_x.text(
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@ -71,6 +73,10 @@ for ax_x, M_, x_ in zip(ax.reshape(-1), M, x[i0]):
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ax_x.set_rasterization_zorder(1.5)
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ax_x.set_rasterization_zorder(1.5)
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ax_x.set(ylabel="T (s)", ylim=(sj[0], sj[-1]))
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ax_x.set(ylabel="T (s)", ylim=(sj[0], sj[-1]))
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ax_x.xaxis.set_minor_locator(MultipleLocator(100))
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ax_x.yaxis.set_major_locator(LogLocator(10, numticks=2**10))
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ax_x.yaxis.set_minor_locator(LogLocator(10, subs=np.arange(10), numticks=2**10))
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ax_x.yaxis.set_minor_formatter(NullFormatter())
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if ax_x != ax.reshape(-1)[-1]:
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if ax_x != ax.reshape(-1)[-1]:
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ax_x.axes.set_xticklabels([])
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ax_x.axes.set_xticklabels([])
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else:
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else:
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@ -76,7 +76,7 @@ ax.grid()
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fig.savefig(out.joinpath("wsize.pdf"))
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fig.savefig(out.joinpath("wsize.pdf"))
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fig2, ax2 = plt.subplots(
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fig2, ax2 = plt.subplots(
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figsize=(10 / 2.54, 2 / 3 * 10 / 2.54), constrained_layout=True
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figsize=(10 / 2.54, 4 / 2.54), constrained_layout=True
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)
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)
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ax2.plot(
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ax2.plot(
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t[cr0[i0 - 5] : cr0[i0 + 7]] * 1e-3,
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t[cr0[i0 - 5] : cr0[i0 + 7]] * 1e-3,
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