Use high res smoothed bathymetry for breakwater

data/config.ini

@@ -1,5 +1,7 @@
 [bathy]
 inp=data/Database_20220224.xyz
+hires=data/bathyhires.dat
+hires_step=0.5
 sub=out/bathy_sub.npy
 out=out/bathy.npy
 step=1

data/processing/projection.py

@@ -21,6 +21,7 @@ config = configparser.ConfigParser()
 config.read("config.ini")
 
 bathy_inp = pathlib.Path(config.get("bathy", "sub"))
+hires_inp = pathlib.Path(config.get("bathy", "hires"))
 bathy_out = pathlib.Path(config.get("bathy", "out"))
 
 log.info(f"Loading bathymetry from {bathy_inp}")
@@ -58,6 +59,40 @@ coords = artha + (x * np.stack((np.cos(theta), np.sin(theta)))).T
 
 log.info("Interpolating bathymetry in 1D")
 z = interpolate.griddata(bathy[:, :2], bathy[:, 2], coords)
-log.debug(z)
+log.debug(f"z: {z}")
 
+_hires = np.genfromtxt(hires_inp)[::-1]
+bathy_hires = np.stack(
+    (
+        np.linspace(
+            0,
+            (_hires.size - 1) * config.getfloat("bathy", "hires_step"),
+            _hires.size,
+        ),
+        _hires,
+    ),
+    axis=1,
+)
+del _hires
+log.debug(f"Bathy hires: {bathy_hires}")
 
+z_cr = 5
+hires_crossing = np.diff(np.signbit(bathy_hires[:, 1] - z_cr)).nonzero()[0][-1]
+log.debug(f"Hires crossing: {hires_crossing}")
+z_crossing = np.diff(np.signbit(z - z_cr)).nonzero()[0][-1]
+log.debug(f"Z crossing: {z_crossing}")
+
+x_min_hires = x[z_crossing] + (
+    bathy_hires[:, 0].min() - bathy_hires[hires_crossing, 0]
+)
+x_max_hires = x[z_crossing] + (
+    bathy_hires[:, 0].max() - bathy_hires[hires_crossing, 0]
+)
+log.debug(f"Replacing range: [{x_min_hires},{x_max_hires}]")
+
+flt_x = (x > x_min_hires) & (x < x_max_hires)
+z[flt_x] = interpolate.griddata(
+    (bathy_hires[:, 0],),
+    bathy_hires[:, 1],
+    (x[flt_x] - x[z_crossing] + bathy_hires[hires_crossing, 0]),
+)