Use npz in post
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a51c727349
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2 changed files with 11 additions and 17 deletions
1
swash/.gitignore
vendored
1
swash/.gitignore
vendored
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@ -1,2 +1,3 @@
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/inp*
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/out*
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/swash_buoytoartha
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@ -27,25 +27,18 @@ root = pathlib.Path(config.get("swash", "out"))
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log.info(f"Reading bathymetry from '{cache}'")
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bathy = pd.read_hdf(cache.joinpath("bathy.h5"), "bathy")
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n = bathy.index.size
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log.info(f"Reading swash output from '{root}'")
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botl = read_nohead_scalar(root.joinpath("botl.dat"), n)
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dep = np.maximum(0, read_nohead_scalar(root.joinpath("dep.dat"), n))
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vel = read_nohead_vect(root.joinpath("vel.dat"), n)
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dt = config.getfloat("post", "dt")
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n_t = botl.shape[0]
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t = np.arange(0, n_t * dt, dt)
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data = np.load(pathlib.Path(config.get("post", "inp")).joinpath("sws.npz"))
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x, t = data["x"], data["t"]
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# Cospectral calculations
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x0 = config.getint("post", "x0")
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t0 = config.getint("post", "t0")
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t0 = config.getfloat("post", "t0")
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dt = config.getfloat("post", "dt")
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f = 1 / dt
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log.info(f"Computing reflection coefficient at x={x0}")
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eta = (dep - botl)[t > t0, x0]
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u = vel[t > t0, 0, x0]
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eta = (data["dep"] - data["botl"])[t > t0, x0]
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u = data["vel"][t > t0, 0, x0]
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phi_eta = np.abs(sgl.csd(eta, eta, f))
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phi_u = np.abs(sgl.csd(u, u, f))
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@ -60,13 +53,13 @@ R = np.sqrt(
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log.info("Plotting results")
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fig, (ax_dep, ax_vel) = plt.subplots(2)
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ax_dep.plot(t, (dep - botl)[:, x0], label="dep")
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ax_dep.plot(t, data["dep"][:, x0] - data["botl"][x0], label="dep")
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ax_dep.set(xlabel="t (s)", ylabel="z (m)")
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ax_dep.autoscale(axis="x", tight=True)
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ax_dep.grid()
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ax_dep.axvline(t0, c="k", alpha=0.2)
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ax_vel.plot(t, vel[:, 0, x0], label="vel")
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ax_vel.plot(t, data["vel"][:, 0, x0], label="vel")
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ax_vel.set(xlabel="t (s)", ylabel="U (m/s)")
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ax_vel.autoscale(axis="x", tight=True)
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ax_vel.grid()
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@ -82,8 +75,8 @@ ax_r.set(ylim=(0, 1), xlabel="f (Hz)", ylabel="R")
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ax_r.grid()
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fig_x, ax_x = plt.subplots()
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ax_x.plot(-botl[0, :], color="k")
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ax_x.plot((dep - botl)[t == t0, :].T)
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ax_x.plot(-data["botl"], color="k")
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ax_x.plot(data["dep"][t == t0, :] - data["botl"])
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ax_x.axvline(x0, c="k", alpha=0.2)
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ax_x.set(xlabel="x (m)", ylabel="z (m)")
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ax_x.autoscale(axis="x", tight=True)
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