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Bathymetry processing (subdomain + 1d interpolation)

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This commit is contained in:
Edgar P. Burkhart 2022-03-11 13:04:55 +01:00
parent d69a39f25b
commit f42edfb8f8
Signed by: edpibu
GPG key ID: 9833D3C5A25BD227
4 changed files with 244 additions and 0 deletions
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12
data/config.ini Normal file
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[bathy]
inp=Database_20220224.xyz
sub=bathy_sub.npy
out=bathy.npy
[artha]
lat=43.398450
lon=-1.673097
[buoy]
lat=43.408333
lon=-1.681667

100
data/processing/lambert.py Normal file
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import numpy as np
class Lambert:
def __init__(
self,
X0=1.7e6,
Y0=2.2e6,
lambda0=3,
phi0=43,
phi1=42.25,
phi2=43.75,
a=6378137,
e=0.081819190842622,
):
self._X0 = X0
self._Y0 = Y0
self._lambda0 = np.radians(lambda0)
self._phi0 = np.radians(phi0)
self._phi1 = np.radians(phi1)
self._phi2 = np.radians(phi2)
self._a = a
self._e = e
self._set_n()
self._set_rho0()
def cartesian(self, lam, phi):
lam = np.radians(lam)
phi = np.radians(phi)
theta = self._n * (lam - self._lambda0)
rho = self._rho(phi)
rho0 = self._rho(self._phi0)
X = self._X0 + rho * np.sin(theta)
Y = self._Y0 + rho0 - rho * np.cos(theta)
return X, Y
def _set_n(self):
self._n = (
np.log(np.cos(self._phi2) / np.cos(self._phi1))
+ (
np.log(
(1 - (self._e * np.sin(self._phi1) ** 2))
/ (1 - (self._e * np.sin(self._phi2) ** 2))
)
/ 2
)
) / (
np.log(
(
np.tan(self._phi1 / 2 + np.pi / 4)
* (
(1 - self._e * np.sin(self._phi2))
* (1 + self._e * np.sin(self._phi1))
)
** (self._e / 2)
)
/ (
np.tan(self._phi2 / 2 + np.pi / 4)
* (
(1 + self._e * np.sin(self._phi2))
* (1 - self._e * np.sin(self._phi1))
)
** (self._e / 2)
)
)
)
def _set_rho0(self):
self._rho0 = (
self._a
* np.cos(self._phi1)
/ (self._n * np.sqrt(1 - self._e**2 * np.sin(self._phi1) ** 2))
* (
np.tan(self._phi1 / 2 + np.pi / 4)
* (
(1 - self._e * np.sin(self._phi1))
/ (1 + self._e * np.sin(self._phi1))
)
** (self._e / 2)
)
** self._n
)
def _rho(self, phi):
return (
self._rho0
* (
1
/ np.tan(phi / 2 + np.pi / 4)
* ((1 + self._e * np.sin(phi)) / (1 - self._e * np.sin(phi)))
** (self._e / 2)
)
** self._n
)

82
data/processing/projection.py Normal file
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import argparse
import configparser
import logging
import pathlib
import matplotlib.pyplot as plt
import numpy as np
from scipy import interpolate
from .lambert import Lambert
parser = argparse.ArgumentParser(description="Pre-process bathymetry")
parser.add_argument("-v", "--verbose", action="count", default=0)
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("config.ini")
bathy_inp = pathlib.Path(config.get("bathy", "sub"))
bathy_out = pathlib.Path(config.get("bathy", "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))
def display():
x = np.linspace(bathy[:, 0].min(), bathy[:, 0].max())
y = np.linspace(bathy[:, 1].min(), bathy[:, 1].max())
X, Y = np.meshgrid(x, y)
Z = interpolate.griddata(
bathy[:, :2], bathy[:, 2], (X, Y), method="nearest"
)
fix, ax = plt.subplots()
ax.pcolormesh(X, Y, Z)
ax.scatter(*artha, c="k")
ax.scatter(*buoy, c="k")
ax.axis("equal")
return ax
D = np.diff(np.stack((artha, buoy)), axis=0)
x = np.arange(-150, np.sqrt((D**2).sum()) + 150)
theta = np.angle(D.dot((1, 1j)))
coords = artha + (x * np.stack((np.cos(theta), np.sin(theta)))).T
z = interpolate.griddata(bathy[:,:2], bathy[:,2], coords)
ax = display()
ax.scatter(*coords.T, c="k", marker=".")
fig_1d, ax_1d = plt.subplots()
ax_1d.plot(x, z)
plt.show(block=True)

50
data/processing/subdomain.py Normal file
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import argparse
import configparser
import logging
import pathlib
import numpy as np
parser = argparse.ArgumentParser(description="Pre-process bathymetry")
parser.add_argument("-v", "--verbose", action="count", default=0)
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("config.ini")
artha = np.array(
(config.getfloat("artha", "lon"), config.getfloat("artha", "lat"))
)
buoy = np.array(
(config.getfloat("buoy", "lon"), config.getfloat("buoy", "lat"))
)
log.debug(f"artha: {artha}")
log.debug(f"buoy: {buoy}")
domain = np.stack((artha, buoy))
domain.sort(axis=0)
log.debug(f"domain: {domain}")
domain[0] -= 0.002
domain[1] += 0.002
log.debug(f"domain: {domain}")
bathy_inp = pathlib.Path(config.get("bathy", "inp"))
bathy_out = pathlib.Path(config.get("bathy", "sub"))
log.info(f"Reading bathymetry from '{bathy_inp}'")
raw_bathy = np.genfromtxt(bathy_inp)
log.debug(f"Initial size: {raw_bathy.shape}")
bathy = raw_bathy[
((raw_bathy[:, :2] > domain[0]) & (raw_bathy[:, :2] < domain[1])).all(
axis=1
)
]
log.debug(f"Final size: {bathy.shape}")
log.info(f"Saving subdomain to 'bathy'")
np.save(bathy_out, bathy)