102 lines
2.7 KiB
Python
102 lines
2.7 KiB
Python
import argparse
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import configparser
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import logging
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import pathlib
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import matplotlib.pyplot as plt
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import numpy as np
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from scipy import interpolate
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from .lambert import Lambert
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parser = argparse.ArgumentParser(description="Pre-process bathymetry")
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parser.add_argument("-v", "--verbose", action="count", default=0)
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args = parser.parse_args()
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logging.basicConfig(level=max((10, 20 - 10 * args.verbose)))
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log = logging.getLogger("bathy")
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log.info("Starting bathymetry pre-processing")
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config = configparser.ConfigParser()
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config.read("config.ini")
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inp_root = pathlib.Path(config.get("inp", "root"))
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out_root = pathlib.Path(config.get("out", "root"))
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bathy_inp = out_root.joinpath(config.get("out", "sub"))
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hires_inp = inp_root.joinpath(config.get("inp", "hires"))
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bathy_out = inp_root.joinpath(config.get("out", "out"))
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log.info(f"Loading bathymetry from {bathy_inp}")
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bathy_curvi = np.load(bathy_inp)
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projection = Lambert()
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bathy = np.stack(
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(
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*projection.cartesian(bathy_curvi[:, 0], bathy_curvi[:, 1]),
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bathy_curvi[:, 2],
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),
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axis=1,
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)
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log.debug(f"Cartesian bathy: {bathy}")
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artha_curvi = np.array(
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(config.getfloat("artha", "lon"), config.getfloat("artha", "lat"))
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)
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buoy_curvi = np.array(
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(config.getfloat("buoy", "lon"), config.getfloat("buoy", "lat"))
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)
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artha = np.asarray(projection.cartesian(*artha_curvi))
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buoy = np.asarray(projection.cartesian(*buoy_curvi))
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D = np.diff(np.stack((artha, buoy)), axis=0)
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x = np.arange(
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-150,
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np.sqrt((D**2).sum()) + 150,
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config.getfloat("out", "step", fallback=1),
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)
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theta = np.angle(D.dot((1, 1j)))
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coords = artha + (x * np.stack((np.cos(theta), np.sin(theta)))).T
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log.info("Interpolating bathymetry in 1D")
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z = interpolate.griddata(bathy[:, :2], bathy[:, 2], coords)
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log.debug(f"z: {z}")
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_hires = np.genfromtxt(hires_inp)[::-1]
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bathy_hires = np.stack(
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(
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np.linspace(
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0,
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(_hires.size - 1) * config.getfloat("inp", "hires_step"),
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_hires.size,
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),
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_hires,
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),
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axis=1,
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)
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del _hires
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log.debug(f"Bathy hires: {bathy_hires}")
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z_cr = 5
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hires_crossing = np.diff(np.signbit(bathy_hires[:, 1] - z_cr)).nonzero()[0][-1]
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log.debug(f"Hires crossing: {hires_crossing}")
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z_crossing = np.diff(np.signbit(z - z_cr)).nonzero()[0][-1]
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log.debug(f"Z crossing: {z_crossing}")
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x_min_hires = x[z_crossing] + (
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bathy_hires[:, 0].min() - bathy_hires[hires_crossing, 0]
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)
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x_max_hires = x[z_crossing] + (
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bathy_hires[:, 0].max() - bathy_hires[hires_crossing, 0]
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)
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log.debug(f"Replacing range: [{x_min_hires},{x_max_hires}]")
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flt_x = (x > x_min_hires) & (x < x_max_hires)
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z[flt_x] = interpolate.griddata(
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(bathy_hires[:, 0],),
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bathy_hires[:, 1],
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(x[flt_x] - x[z_crossing] + bathy_hires[hires_crossing, 0]),
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)
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