136 lines
4.2 KiB
Python
136 lines
4.2 KiB
Python
import argparse
|
|
import configparser
|
|
import logging
|
|
import pathlib
|
|
|
|
import numpy as np
|
|
from scipy import interpolate
|
|
|
|
import matplotlib.pyplot as plt
|
|
|
|
from .lambert import Lambert
|
|
|
|
parser = argparse.ArgumentParser(description="Pre-process bathymetry")
|
|
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("bathy")
|
|
|
|
log.info("Starting bathymetry pre-processing")
|
|
config = configparser.ConfigParser()
|
|
config.read(args.config)
|
|
|
|
inp_root = pathlib.Path(config.get("inp", "root"))
|
|
out_root = pathlib.Path(config.get("out", "root"))
|
|
bathy_inp = out_root.joinpath(config.get("out", "sub"))
|
|
hires_inp = inp_root.joinpath(config.get("inp", "hires"))
|
|
hstru_inp = inp_root.joinpath(config.get("inp", "hstru"))
|
|
poro_inp = inp_root.joinpath(config.get("inp", "poro"))
|
|
psize_inp = inp_root.joinpath(config.get("inp", "psize"))
|
|
bathy_out = inp_root.joinpath(config.get("out", "out"))
|
|
|
|
log.info(f"Loading bathymetry from {bathy_inp}")
|
|
bathy_curvi = np.load(bathy_inp)
|
|
|
|
projection = Lambert()
|
|
bathy = np.stack(
|
|
(
|
|
*projection.cartesian(bathy_curvi[:, 0], bathy_curvi[:, 1]),
|
|
bathy_curvi[:, 2],
|
|
),
|
|
axis=1,
|
|
)
|
|
log.debug(f"Cartesian bathy: {bathy}")
|
|
|
|
artha_curvi = np.array(
|
|
(config.getfloat("artha", "lon"), config.getfloat("artha", "lat"))
|
|
)
|
|
buoy_curvi = np.array((config.getfloat("buoy", "lon"), config.getfloat("buoy", "lat")))
|
|
|
|
artha = np.asarray(projection.cartesian(*artha_curvi))
|
|
buoy = np.asarray(projection.cartesian(*buoy_curvi))
|
|
|
|
D = np.diff(np.stack((artha, buoy)), axis=0)
|
|
x = np.arange(
|
|
config.getfloat("out", "left", fallback=0),
|
|
np.sqrt((D**2).sum()) + config.getfloat("out", "right", fallback=0),
|
|
config.getfloat("out", "step", fallback=1),
|
|
)
|
|
theta = np.angle(D.dot((1, 1j)))
|
|
|
|
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(f"z: {z}")
|
|
|
|
_hires = np.loadtxt(hires_inp)[::-1]
|
|
bathy_hires = np.stack(
|
|
(
|
|
np.linspace(
|
|
0,
|
|
(_hires.size - 1) * config.getfloat("inp", "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)
|
|
hstru = np.zeros(z.shape)
|
|
poro = np.zeros(z.shape)
|
|
psize = np.zeros(z.shape)
|
|
if config.getboolean("out", "no_breakwater", fallback=False):
|
|
z[flt_x] = z[flt_x][-1]
|
|
else:
|
|
z[flt_x] = interpolate.griddata(
|
|
(bathy_hires[:, 0],),
|
|
bathy_hires[:, 1],
|
|
(x[flt_x] - x[z_crossing] + bathy_hires[hires_crossing, 0]),
|
|
)
|
|
|
|
hstru_in = np.loadtxt(hstru_inp)[::-1]
|
|
hstru[flt_x] = interpolate.griddata(
|
|
(bathy_hires[:, 0],),
|
|
hstru_in,
|
|
(x[flt_x] - x[z_crossing] + bathy_hires[hires_crossing, 0]),
|
|
)
|
|
|
|
poro_in = np.loadtxt(poro_inp)[::-1]
|
|
poro[flt_x] = interpolate.griddata(
|
|
(bathy_hires[:, 0],),
|
|
poro_in,
|
|
(x[flt_x] - x[z_crossing] + bathy_hires[hires_crossing, 0]),
|
|
)
|
|
|
|
psize_in = np.loadtxt(psize_inp)[::-1]
|
|
psize[flt_x] = interpolate.griddata(
|
|
(bathy_hires[:, 0],),
|
|
psize_in,
|
|
(x[flt_x] - x[z_crossing] + bathy_hires[hires_crossing, 0]),
|
|
)
|
|
|
|
np.savetxt(out_root.joinpath("bathy.dat"), z[::-1], newline=" ")
|
|
np.savetxt(out_root.joinpath("hstru.dat"), hstru[::-1], newline=" ")
|
|
np.savetxt(out_root.joinpath("poro.dat"), poro[::-1], newline=" ")
|
|
np.savetxt(out_root.joinpath("psize.dat"), psize[::-1], newline=" ")
|
|
|
|
fig, ax = plt.subplots()
|
|
ax.plot(-x, z, color="k")
|
|
ax.fill_between(-x, z + hstru, z, color="k", alpha=0.2)
|
|
fig.savefig(out_root.joinpath("bathy.pdf"))
|