import argparse import configparser import logging import pathlib import matplotlib.pyplot as plt import numpy as np 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) 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")) botl = np.load(inp.joinpath("botl.npy")) watl = np.load(inp.joinpath("watl.npy")) vel = np.load(inp.joinpath("vel_x.npy")) # Cospectral calculations x0 = config.getint("post", "x0") arg_x0 = np.abs(x - x0).argmin() t0 = int(config.getfloat("post", "t0") * 1e3) arg_t0 = np.abs(t - t0).argmin() dt = np.diff(t).mean() * 1e-3 f = 1 / dt nperseg = config.getint("post", "nperseg", fallback=None) log.info(f"Computing reflection coefficient at x={x0}") eta = watl[t > t0, arg_x0] u = vel[t > t0, arg_x0] phi_eta = sgl.welch(eta, f, nperseg=nperseg) phi_u = sgl.welch(u, f, nperseg=nperseg) phi_eta_u = sgl.csd(eta, u, f, nperseg=nperseg) H = np.sqrt(np.abs(phi_eta[1])) U = np.sqrt(np.abs(phi_u[1])) G = H / U th_eta_u = np.angle(phi_eta_u[1]) R = np.sqrt( (np.abs(phi_eta[1]) + np.abs(phi_u[1]) - 2 * phi_eta_u[1].real) / (np.abs(phi_eta[1]) + np.abs(phi_u[1]) + 2 * phi_eta_u[1].real) ) # R = np.sqrt( # (1 + G**2 - 2 * G * np.cos(th_eta_u)) # / (1 + G**2 + 2 * G * np.cos(th_eta_u)) # ) if config.has_option("post", "compare"): inp_comp = pathlib.Path(config.get("post", "compare")) x_ = np.load(inp_comp.joinpath("xp.npy")) t_ = np.load(inp_comp.joinpath("tsec.npy")) botl_ = np.load(inp_comp.joinpath("botl.npy")) watl_ = np.load(inp_comp.joinpath("watl.npy")) vel_ = np.load(inp_comp.joinpath("vel_x.npy")) arg_x0_ = np.abs(x_ - x0).argmin() arg_t0_ = np.abs(t_ - t0).argmin() eta_ = watl_[t_ > t0, arg_x0_] u_ = vel_[t_ > t0, arg_x0_] phi_eta_ = sgl.welch(eta_, f, nperseg=nperseg) phi_u_ = sgl.welch(u_, f, nperseg=nperseg) phi_eta_u_ = sgl.csd(eta_, u_, f, nperseg=nperseg) H_ = np.sqrt(np.abs(phi_eta_[1])) U_ = np.sqrt(np.abs(phi_u_[1])) G_ = H_ / U_ th_eta_u_ = np.angle(phi_eta_u_[1]) R_ = np.sqrt( (np.abs(phi_eta_[1]) + np.abs(phi_u_[1]) - 2 * phi_eta_u_[1].real) / (np.abs(phi_eta_[1]) + np.abs(phi_u_[1]) + 2 * phi_eta_u_[1].real) ) # R_ = np.sqrt( # (1 + G_**2 - 2 * G_ * np.cos(th_eta_u_)) # / (1 + G_**2 + 2 * G_ * np.cos(th_eta_u_)) # ) # Plotting log.info("Plotting results") fig, (ax_watl, ax_vel) = plt.subplots(2) ax_watl.plot(t * 1e-3, watl[:, arg_x0], lw=1, label="watl") ax_watl.set(xlabel="t (s)", ylabel="z (m)") ax_watl.autoscale(axis="x", tight=True) ax_watl.grid() ax_watl.axvline(t0 * 1e-3, c="k", alpha=0.2) ax_vel.plot(t * 1e-3, vel[:, arg_x0], lw=1, 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 * 1e-3, c="k", alpha=0.2) fig.tight_layout() fig_r, ax_r = plt.subplots() ax_fft = ax_r.twinx() ax_fft.plot( *sgl.welch(eta, 1 / dt, nperseg=nperseg), lw=1, c="k", alpha=0.2, label="PSD ($\\eta$, cas 1)", ) ax_r.plot(phi_eta[0], R, marker="+", label="R (cas 1)") if config.has_option("post", "compare"): ax_fft.plot( *sgl.welch(eta_, 1 / dt, nperseg=nperseg), lw=1, c="k", alpha=0.2, label="PSD ($\\eta$, cas 2)", ) ax_r.plot(phi_eta[0], R_, marker="+", label="R (cas 2)") ax_r.set(xlim=(0, 0.3), ylim=(0, 1), xlabel="f (Hz)", ylabel="R") ax_fft.set(ylim=0, ylabel="PSD (m²/Hz)") ax_r.grid() ax_r.legend(loc="upper left") ax_fft.legend(loc="upper right") fig_r.tight_layout() fig_x, ax_x = plt.subplots() ax_x.plot(x, -botl, color="k") ax_x.plot( x, np.maximum(watl[arg_t0, :], -botl), ) if config.has_option("post", "compare"): ax_x.plot(x, -botl_, color="k", ls="-.") ax_x.plot( x, np.maximum(watl_[arg_t0, :], -botl_), ls="-.", ) 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) fig_x.tight_layout() out = pathlib.Path(config.get("post", "out")).joinpath(f"t{t0}x{x0}") log.info(f"Saving plots in '{out}'") out.mkdir(parents=True, exist_ok=True) fig.savefig(out.joinpath("t.pdf")) fig_r.savefig(out.joinpath("R.pdf")) fig_x.savefig(out.joinpath("x.pdf")) log.info("Finished post-processing")