Bathymetry generator

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Edgar P. Burkhart 2022-01-23 08:55:28 +01:00
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/1_scad
/2_stl
/3_pd

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translate([150, 0, 0])
mirror([1, 0, 0])
rotate([90, 0, 0])
translate([0, 0, -10])
linear_extrude(20)
polygon({});

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lat,lon
43.398489,-1.672400
1 lat lon
2 43.398489 -1.672400

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rotate([90, 0, 0])
translate([0, 0, -10])
linear_extrude(20)
polygon({});

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x,z
-4,-0.5
11.7,-0.5
11.7,2.5
9.25,8.2
0,8.2
0,2.5
-4,2.5
1 x z
2 -4 -0.5
3 11.7 -0.5
4 11.7 2.5
5 9.25 8.2
6 0 8.2
7 0 2.5
8 -4 2.5

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x,z
9.25,-0.5
9.25,4.75
16.70,4.75
16.6,-0.5
1 x z
2 9.25 -0.5
3 9.25 4.75
4 16.70 4.75
5 16.6 -0.5

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lat,lon
43.398133,-1.672285
43.400464,-1.67302
1 lat lon
2 43.398133 -1.672285
3 43.400464 -1.67302

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bathymetry/config.ini Normal file
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[main]
logging = INFO
plot = False
N = 1024
L0 = 120
L1 = 30
dir = 350
bathy_max=-15
[data]
root = 0_data
bathy = MNT_COTIER_BAIE_SJL_TANDEM_20m_WGS84_NM_ZNEG.glz
artha = artha_coords.csv
base_scad = base.scad
points = points.csv
blocs = bloc0.csv,bloc1.csv
[scad]
root = 1_scad
bathy = bathy.scad
bloc0 = bloc0.scad
bloc1 = bloc1.scad
rubble = rub.scad
[stl]
root = 2_stl
bathy = bathy.stl
bloc0 = bloc0.stl
bloc1 = bloc1.stl
rubble = rub.stl
[pandas]
root = 3_pd
file = data.hdf

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from pprint import pp
import logging
import configparser
import pathlib
import subprocess
from time import time
import pandas as pd
import numpy as np
from scipy.interpolate import griddata
_t0 = time()
config = configparser.ConfigParser()
config.read('config.ini')
if config['main']['plot'] == 'True': import matplotlib.pyplot as plt
logging.basicConfig(level=config['main']['logging'])
log = logging.getLogger('bathymetry')
# --- Initialization
log.info('Initialization')
folders = {
'data': pathlib.Path(config['data']['root']),
'scad': pathlib.Path(config['scad']['root']),
'stl': pathlib.Path(config['stl']['root']),
'pandas': pathlib.Path(config['pandas']['root']),
}
for path in folders.values():
path.mkdir(exist_ok=True)
bathy = pd.read_csv(
folders['data'].joinpath(config['data']['bathy']),
sep=' ',
names=('lon', 'lat', 'z'),
)
artha = pd.read_csv(
folders['data'].joinpath(config['data']['artha']),
)
earth_radius = 6371e3
L0 = float(config['main']['L0'])
L1 = float(config['main']['L1'])
direction = float(config['main']['dir'])
artha = artha.append(pd.DataFrame([
{
'lat': artha.lat.at[0] \
+ np.cos(direction*np.pi/180) * L0/earth_radius * 180/np.pi,
'lon': artha.lon.at[0] \
+ np.sin(direction*np.pi/180) * L0/earth_radius * 180/np.pi \
/ np.cos(artha.lat.at[0] * np.pi/180),
},
{
'lat': artha.lat.at[0] \
- np.cos(direction*np.pi/180) * L1/earth_radius * 180/np.pi,
'lon': artha.lon.at[0] \
- np.sin(direction*np.pi/180) * L1/earth_radius * 180/np.pi \
/ np.cos(artha.lat.at[0] * np.pi/180),
},
], index=[-1, 1]))
# --- Interpolation
log.info('Interpolating data')
N = int(config['main']['N'])
line = pd.DataFrame({
'x': np.linspace(0, L0+L1, N),
'lat': np.linspace(artha.lat.at[-1], artha.lat.at[1], N),
'lon': np.linspace(artha.lon.at[-1], artha.lon.at[1], N),
})
line.set_index('x', inplace=True)
line['z'] = griddata(
bathy[['lon','lat']],
bathy.z,
line[['lon','lat']],
method='linear',
)
# --- Adding blocs
log.info('Adding blocs')
b = config['data']['blocs'].split(',')
blocs = pd.Series([
pd.read_csv(
folders['data'].joinpath(path),
index_col='x',
) for path in b
])
for bloc in blocs:
bloc.index = L0 - bloc.index
#line.z = all_blocs.z.fillna(line.z)
lim = float(config['main']['bathy_max'])
bathy_line = line.z.clip(upper=lim)
rubble_line = line.z[line.z > lim]
data_dict = {}
for i in range(blocs.size):
data_dict[f'bloc{i}'] = blocs.iat[i].reset_index().values
for name, data in (
('bathy', bathy_line),
('rubble', rubble_line),
):
data_dict[name] = np.concatenate((
data.reset_index().values,
[[data.index.max(), data.min()],
[data.index.min(),data.min()]]
))
# --- Generating SCAD
with open(folders['data'].joinpath(config['data']['base_scad'])) as bsf:
base_scad = bsf.read()
for (name, data) in data_dict.items():
log.info(f'Generating {name}')
log.info('\tGenerating SCAD file')
scad_file = folders['scad'].joinpath(config['scad'][name])
with open(scad_file, 'w') as osf:
osf.write(base_scad.format(
np.array2string(
data,
threshold=np.inf,
separator=','
)
))
log.info('\tGenerating STL file')
subprocess.run(('openscad', scad_file, '-o',
folders['stl'].joinpath(config['stl'][name])),
check=True,
capture_output=True)
# --- Saving pandas
log.info('Saving Pandas')
with pd.HDFStore(
folders['pandas'].joinpath(config['pandas']['file']),
mode='w',
complib='blosc',
) as hdf:
for name, data in (
('bathy', bathy_line),
('rubble', rubble_line),
):
hdf.put(name, data)
for i, bloc in blocs.items():
hdf.put(f'bloc{i}', bloc)
_t1 = time()
log.info(f'Program ended successfully after {_t1-_t0:.2f}s')
# --- Plotting
if config['main']['plot'] == 'True':
log.info('Plotting data')
flt = (
((bathy.lon-artha.lon.at[0]).abs() < 0.002) & \
((bathy.lat-artha.lat.at[0]).abs() < 0.002)
)
fig, ax = plt.subplots()
ax.scatter(
bathy.lon[flt],
bathy.lat[flt],
c=bathy.z[flt],
marker='1',
lw=1,
)
ax.scatter(
artha.lon,
artha.lat,
color='k',
marker='+',
lw=1,
)
ax.set(
aspect='equal',
)
fig, ax = plt.subplots()
ax.plot(
bathy_line.index,
bathy_line,
color='k',
lw=1,
zorder=10,
label='Bathymetry',
)
ax.plot(
rubble_line.index,
rubble_line,
color='r',
lw=1,
zorder=11,
label='Rubble',
)
blocs.apply(lambda bloc: ax.fill_between(
bloc.index,
bloc.z,
color='k',
zorder=9,
alpha=.1,
label='Caisson',
))
ax.set(
aspect='equal',
xlim=(bathy_line.index.min(), bathy_line.index.max()),
)
ax.grid()
fig.legend()
plt.show(block=True)