87 lines
2.4 KiB
Python
87 lines
2.4 KiB
Python
import argparse
|
|
import configparser
|
|
import logging
|
|
import pathlib
|
|
|
|
import matplotlib.pyplot as plt
|
|
import numpy as np
|
|
import scipy.signal as sgl
|
|
|
|
parser = argparse.ArgumentParser(description="Post-process swash output")
|
|
parser.add_argument("-v", "--verbose", action="count", default=0)
|
|
parser.add_argument("-c", "--config", default="config.ini")
|
|
args = parser.parse_args()
|
|
|
|
logging.basicConfig(level=max((10, 20 - 10 * args.verbose)))
|
|
log = logging.getLogger("post")
|
|
|
|
log.info("Starting post-processing")
|
|
config = configparser.ConfigParser()
|
|
config.read(args.config)
|
|
|
|
inp = pathlib.Path(config.get("post", "inp"))
|
|
root = pathlib.Path(config.get("swash", "out"))
|
|
|
|
log.info(f"Reading data from '{inp}'")
|
|
x = np.load(inp.joinpath("x.npy"))
|
|
t = np.load(inp.joinpath("t.npy")) * 1e-3
|
|
|
|
botl = np.load(inp.joinpath("botl.npy"))
|
|
watl = np.load(inp.joinpath("watl.npy"))
|
|
vel = np.load(inp.joinpath("vel.npy"))[0]
|
|
|
|
# Plotting
|
|
log.info("Plotting results")
|
|
|
|
vlim = np.nanmin(np.maximum(watl, -botl)), np.nanmax(np.maximum(watl, -botl))
|
|
|
|
x0 = np.linspace(-600, -200, 5)
|
|
i0 = np.argmin(np.abs(x[:, None] - x0), axis=0)
|
|
|
|
fig_x, ax = plt.subplots(
|
|
5, 1, figsize=(15 / 2.54, 15/ 2.54), constrained_layout=True
|
|
)
|
|
dt = np.mean(np.diff(t))
|
|
N = t.size
|
|
s0 = 2 * dt
|
|
dj = 0.5
|
|
J = 1 / dj * np.log2(N * dt / s0)
|
|
j = np.arange(0, J)
|
|
sj = s0 * 2 ** (j * dj)
|
|
Mw = sj / dt
|
|
sig = np.var(watl[:, i0])
|
|
M = np.stack([(np.abs(sgl.cwt(watl[:, i], sgl.morlet2, Mw))/sig)**2 for i in i0])
|
|
v = np.max(M)
|
|
|
|
for ax_x, M_, x_ in zip(ax.reshape(-1), M, x[i0]):
|
|
c = ax_x.contourf(t, sj, M_, cmap="Greys", vmin=0, levels=[1, 2.5, 5, 10, 20, 40], extend="both")
|
|
fig_x.colorbar(c, ax=ax_x, label="NWPS")
|
|
ax_x.grid(color="k", alpha=0.2)
|
|
ax_x.text(
|
|
0.95,
|
|
0.95,
|
|
f"x={x_:.0f}m",
|
|
horizontalalignment="right",
|
|
verticalalignment="top",
|
|
transform=ax_x.transAxes,
|
|
#c="w",
|
|
)
|
|
ax_x.semilogy()
|
|
ax_x.autoscale(True, "both", True)
|
|
ax_x.set_rasterization_zorder(1.5)
|
|
ax_x.set(ylabel="T (s)", ylim=(sj[0], sj[-1]))
|
|
|
|
if ax_x != ax.reshape(-1)[-1]:
|
|
ax_x.axes.set_xticklabels([])
|
|
else:
|
|
ax_x.set(xlabel="t (s)")
|
|
|
|
out = pathlib.Path(config.get("post", "out")).joinpath(f"trans")
|
|
log.info(f"Saving plots in '{out}'")
|
|
out.mkdir(parents=True, exist_ok=True)
|
|
|
|
fig_x.savefig(out.joinpath("wavelet.pdf"), dpi=300)
|
|
fig_x.savefig(out.joinpath("wavelet.jpg"), dpi=200)
|
|
fig_x.savefig(out.joinpath("wavelet.png"), dpi=200)
|
|
|
|
log.info("Finished post-processing")
|