Black reformat post-process

swash/processing/post.py

@@ -0,0 +1,100 @@
+import configparser
+import pathlib
+import argparse
+import logging
+
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+import scipy.signal as sgl
+
+from .read_swash import *
+
+
+parser = argparse.ArgumentParser(description="Post-process swash output")
+parser.add_argument("-v", "--verbose", action="count", default=0)
+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("config.ini")
+
+cache = pathlib.Path(config.get("data", "out"))
+root = pathlib.Path(config.get("swash", "out"))
+
+log.info(f"Reading bathymetry from '{cache}'")
+bathy = pd.read_hdf(cache.joinpath("bathy.h5"), "bathy")
+n = bathy.index.size
+
+log.info(f"Reading swash output from '{root}'")
+botl = read_nohead_scalar(root.joinpath("botl.dat"), n)
+dep = np.maximum(0, read_nohead_scalar(root.joinpath("dep.dat"), n))
+vel = read_nohead_vect(root.joinpath("vel.dat"), n)
+
+dt = config.getfloat("post", "dt")
+n_t = botl.shape[0]
+t = np.arange(0, n_t * dt, dt)
+
+# Cospectral calculations
+x0 = config.getint("post", "x0")
+t0 = config.getint("post", "t0")
+f = 1 / dt
+log.info(f"Computing reflection coefficient at x={x0}")
+
+eta = (dep - botl)[t > t0, x0]
+u = vel[t > t0, 0, x0]
+
+phi_eta = np.abs(sgl.csd(eta, eta, f))
+phi_u = np.abs(sgl.csd(u, u, f))
+phi_eta_u = np.abs(sgl.csd(eta, u, f))
+
+R = np.sqrt(
+    (phi_eta[1] + phi_u[1] - 2 * phi_eta_u[1])
+    / (phi_eta[1] + phi_u[1] + 2 * phi_eta_u[1])
+)
+
+# Plotting
+log.info("Plotting results")
+fig, (ax_dep, ax_vel) = plt.subplots(2)
+
+ax_dep.plot(t, (dep - botl)[:, x0], label="dep")
+ax_dep.set(xlabel="t (s)", ylabel="z (m)")
+ax_dep.autoscale(axis="x", tight=True)
+ax_dep.grid()
+ax_dep.axvline(t0, c="k", alpha=0.2)
+
+ax_vel.plot(t, vel[:, 0, x0], label="vel")
+ax_vel.set(xlabel="t (s)", ylabel="U (m/s)")
+ax_vel.autoscale(axis="x", tight=True)
+ax_vel.grid()
+ax_vel.axvline(t0, c="k", alpha=0.2)
+
+fig.tight_layout()
+
+fig_r, ax_r = plt.subplots()
+
+ax_r.plot(phi_eta[0], R)
+ax_r.autoscale(axis="x", tight=True)
+ax_r.set(ylim=(0, 1), xlabel="f (Hz)", ylabel="R")
+ax_r.grid()
+
+fig_x, ax_x = plt.subplots()
+ax_x.plot(-botl[0, :], color="k")
+ax_x.plot((dep - botl)[t == t0, :].T)
+ax_x.axvline(x0, c="k", alpha=0.2)
+ax_x.set(xlabel="x (m)", ylabel="z (m)")
+ax_x.autoscale(axis="x", tight=True)
+ax_x.grid()
+
+out = pathlib.Path(config.get("post", "out"))
+log.info(f"Saving plots in '{out}'")
+out.mkdir(exist_ok=True)
+
+fig.savefig(out.joinpath(f"t{x0}.png"))
+fig_r.savefig(out.joinpath(f"R{x0}.png"))
+fig_x.savefig(out.joinpath(f"x{t0}.png"))
+
+log.info("Finished post-processing")