From 2eea373e7902c01e2fae3af32344323b3206d187 Mon Sep 17 00:00:00 2001
From: "Edgar P. Burkhart" <git@edgarpierre.fr>
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()