From 2eea373e7902c01e2fae3af32344323b3206d187 Mon Sep 17 00:00:00 2001 From: "Edgar P. Burkhart" Date: Thu, 7 Apr 2022 11:04:51 +0200 Subject: [PATCH] Post-processing using mat output --- swash/processing/animate.py | 4 ++-- swash/processing/post.py | 24 ++++++++++++------------ 2 files changed, 14 insertions(+), 14 deletions(-) diff --git a/swash/processing/animate.py b/swash/processing/animate.py index cad5361..fd0b565 100644 --- a/swash/processing/animate.py +++ b/swash/processing/animate.py @@ -29,8 +29,8 @@ def data(var): return np.load(inp.joinpath(f"{var}.npy")) -x = data("xp") -t = data("tsec") +x = data("x") +#t = data("t") watl = data("watl") botl = data("botl") diff --git a/swash/processing/post.py b/swash/processing/post.py index 39b8aed..3315721 100644 --- a/swash/processing/post.py +++ b/swash/processing/post.py @@ -25,25 +25,25 @@ 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("xp.npy")) -t = np.load(inp.joinpath("tsec.npy")) +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.npy")) +vel = np.load(inp.joinpath("vel_x.npy")) # Cospectral calculations x0 = config.getint("post", "x0") arg_x0 = np.abs(x - x0).argmin() -t0 = config.getfloat("post", "t0") +t0 = int(config.getfloat("post", "t0")*1e3) arg_t0 = np.abs(t - t0).argmin() -dt = np.diff(t).mean() +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, 0, arg_x0] +u = vel[t > t0, arg_x0] phi_eta = sgl.welch(eta, f, nperseg=nperseg) phi_u = sgl.welch(u, f, nperseg=nperseg) @@ -70,13 +70,13 @@ if config.has_option("post", "compare"): botl_ = np.load(inp_comp.joinpath("botl.npy")) watl_ = np.load(inp_comp.joinpath("watl.npy")) - vel_ = np.load(inp_comp.joinpath("vel.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, 0, arg_x0_] + u_ = vel_[t_ > t0, arg_x0_] phi_eta_ = sgl.welch(eta_, f, nperseg=nperseg) phi_u_ = sgl.welch(u_, f, nperseg=nperseg) @@ -101,17 +101,17 @@ if config.has_option("post", "compare"): log.info("Plotting results") fig, (ax_watl, ax_vel) = plt.subplots(2) -ax_watl.plot(t, watl[:, arg_x0], lw=1, label="watl") +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, c="k", alpha=0.2) +ax_watl.axvline(t0*1e-3, c="k", alpha=0.2) -ax_vel.plot(t, vel[:, 0, arg_x0], lw=1, label="vel") +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, c="k", alpha=0.2) +ax_vel.axvline(t0*1e-3, c="k", alpha=0.2) fig.tight_layout()