SWAN sensitivity example

In this notebook we will load the base config options from yaml file and define different SWAN workspaces for different source terms to simulate sensitivity testing

%load_ext autoreload
%autoreload 2

import os
from copy import deepcopy
from pathlib import Path
import yaml
import shutil

import warnings
warnings.filterwarnings('ignore')

Workspace basepath

workdir = Path("example_sensitivity")
shutil.rmtree(workdir, ignore_errors=True)
workdir.mkdir()

Instantiate model

Use a fully-defined config from yaml to instantiate ModelRun with the runtime parameters and the config definition

# Uncoment below to view the contents of the yaml file

# !cat example_sensitivity.yml

from rompy.swan.config import SwanConfigComponents

conf_dict = yaml.load(open("example_sensitivity.yml"), Loader=yaml.Loader)
config = SwanConfigComponents(**conf_dict)
config

SwanConfigComponents(model_type='swanconfig', template='/source/csiro/rompy/rompy/templates/swancomp', checkout='main', cgrid=REGULAR(model_type='regular', spectrum=SPECTRUM(model_type='spectrum', mdc=36, flow=0.04, fhigh=1.0, msc=None, dir1=None, dir2=None), grid=GRIDREGULAR(model_type='gridregular', xp=110.0, yp=-35.2, alp=4.0, xlen=7.5, ylen=12.5, mx=14, my=24, suffix='c')), startup=STARTUP(model_type='startup', project=PROJECT(model_type='project', name='Test sensitivity', nr='run1', title1='Source terms sensitivity testing', title2=None, title3=None), set=SET(model_type='set', level=0.0, nor=None, depmin=0.05, maxmes=None, maxerr=None, grav=None, rho=None, cdcap=None, inrhog=None, hsrerr=None, direction_convention='nautical', pwtail=None, froudmax=None, icewind=None), mode=MODE(model_type='mode', kind='nonstationary', dim='twodimensional'), coordinates=COORDINATES(model_type='coordinates', kind=SPHERICAL(model_type='spherical', projection='ccm'), reapeating=False)), inpgrid=DataInterface(model_type='data_interface', bottom=SwanDataGrid(model_type='data_grid', id='data', source=SourceIntake(model_type='intake', dataset_id='gebco', catalog_uri='../../tests/data/catalog.yaml', kwargs={}), filter=Filter(sort={}, subset={}, crop={}, timenorm={}, rename={}, derived={}), variables=['elevation'], coords=DatasetCoords(t='time', x='lon', y='lat', z='depth'), crop_data=True, buffer=1.0, z1='elevation', z2=None, var=<GridOptions.BOTTOM: 'bottom'>, fac=-1.0), input=[SwanDataGrid(model_type='data_grid', id='data', source=SourceIntake(model_type='intake', dataset_id='era5', catalog_uri='../../tests/data/catalog.yaml', kwargs={}), filter=Filter(sort={'coords': ['latitude']}, subset={}, crop={}, timenorm={}, rename={}, derived={}), variables=['u10', 'v10'], coords=DatasetCoords(t='time', x='longitude', y='latitude', z='depth'), crop_data=True, buffer=2.0, z1='u10', z2='v10', var=<GridOptions.WIND: 'wind'>, fac=1.0)]), boundary=BOUNDSPEC(model_type='boundspec', shapespec=SHAPESPEC(model_type='shapespec', shape=TMA(model_type='tma', gamma=3.3, d=12.0), per_type='peak', dspr_type='degrees'), location=SIDE(model_type='side', side='west', direction='ccw'), data=CONSTANTPAR(model_type='constantpar', hs=2.0, per=12.0, dir=255.0, dd=25.0)), initial=INITIAL(model_type='initial', kind=DEFAULT(model_type='default')), physics=PHYSICS(model_type='physics', gen=GEN3(model_type='gen3', source_terms=KOMEN(model_type='komen', wind_drag='wu', agrow=False, a=None, cds2=2.3e-05, stpm=0.00302)), sswell=None, negatinp=None, wcapping=None, quadrupl=None, breaking=None, friction=FRICTION_JONSWAP(model_type='jonswap', cfjon=0.038), triad=None, vegetation=None, mud=None, sice=None, turbulence=None, bragg=None, limiter=None, obstacle=None, setup=None, diffraction=None, surfbeat=None, scat=None, deactivate=None), prop=PROP(model_type='prop', scheme=BSBT(model_type='bsbt')), numeric=NUMERIC(model_type='numeric', stop=STOPC(model_type='stopc', dabs=0.02, drel=0.02, curvat=0.02, npnts=98.0, mode=STAT(model_type='stat', mxitst=3, alfa=None), limiter=None), dirimpl=None, sigimpl=None, ctheta=None, csigma=None, setup=None), output=OUTPUT(model_type='output', frame=None, group=None, curve=None, ray=None, isoline=None, points=POINTS(model_type='points', sname='pts', xp=[114.0, 112.5, 115.0], yp=[-34.0, -26.0, -30.0]), ngrid=None, quantity=QUANTITIES(model_type='quantities', quantities=[QUANTITY(model_type='quantity', output=[<BlockOptions.DEPTH: 'depth'>, <BlockOptions.HSIGN: 'hsign'>, <BlockOptions.TPS: 'tps'>, <BlockOptions.DIR: 'dir'>, <BlockOptions.TM01: 'tm01'>], short=None, long=None, lexp=None, hexp=None, excv=-9.0, power=None, ref=None, fswell=None, noswll=None, fmin=None, fmax=None, coord=None), QUANTITY(model_type='quantity', output=[<BlockOptions.HSWELL: 'hswell'>], short=None, long=None, lexp=None, hexp=None, excv=None, power=None, ref=None, fswell=0.125, noswll=None, fmin=None, fmax=None, coord=None)]), output_options=None, block=BLOCK(model_type='block', sname='COMPGRID', fname='swangrid.nc', times=TimeRangeOpen(model_type='open', tbeg=datetime.datetime(1970, 1, 1, 0, 0), delt=datetime.timedelta(seconds=3600), tfmt=1, dfmt='hr', suffix='blk'), header=None, idla=None, output=[<BlockOptions.DEPTH: 'depth'>, <BlockOptions.WIND: 'wind'>, <BlockOptions.HSIGN: 'hsign'>, <BlockOptions.TPS: 'tps'>, <BlockOptions.DIR: 'dir'>], unit=None), table=TABLE(model_type='table', sname='pts', fname='swantable.txt', times=TimeRangeOpen(model_type='open', tbeg=datetime.datetime(1970, 1, 1, 0, 0), delt=datetime.timedelta(seconds=3600), tfmt=1, dfmt='hr', suffix='tbl'), format='header', output=[<BlockOptions.TIME: 'time'>, <BlockOptions.HSIGN: 'hsign'>, <BlockOptions.HSWELL: 'hswell'>, <BlockOptions.DIR: 'dir'>, <BlockOptions.TPS: 'tps'>, <BlockOptions.TM01: 'tm01'>]), specout=SPECOUT(model_type='specout', sname='pts', fname='swanspec.nc', times=TimeRangeOpen(model_type='open', tbeg=datetime.datetime(1970, 1, 1, 0, 0), delt=datetime.timedelta(seconds=3600), tfmt=1, dfmt='hr', suffix='spc'), dim=SPEC2D(model_type='spec2d'), freq=ABS(model_type='abs')), nestout=None, test=None), lockup=LOCKUP(model_type='lockup', compute=COMPUTE_STAT(model_type='stat', times=NONSTATIONARY(model_type='nonstationary', tbeg=datetime.datetime(1970, 1, 1, 0, 0), delt=datetime.timedelta(seconds=3600), tfmt=1, dfmt='sec', suffix='', tend=datetime.datetime(1970, 1, 2, 0, 0)), hotfile=HOTFILE(model_type='hotfile', fname=PosixPath('hotfile.txt'), format='free'), hottimes=[1, -1], suffix='_%Y%m%dT%H%M%S')))

Examine components

# Project

print(config.startup.project.render())

PROJECT name='Test sensitivity' nr='run1' title1='Source terms sensitivity testing'

# Source terms

print(config.physics.gen.render())

GEN3 KOMEN cds2=2.3e-05 stpm=0.00302 DRAG WU

Sensitivity config

def set_experiment(config, source_terms):
    """Return a new config object for a given experiment"""
    new_config = deepcopy(config)
    new_config.startup.project.title2 = f"Experiment {source_terms.model_type.upper()}"
    new_config.physics.gen.source_terms = source_terms
    return new_config

from rompy.core.time import TimeRange

period = TimeRange(
    start="2023-01-01T00:00:00",
    end="2023-01-02T00:00:00",
    interval="1h"
)

period

TimeRange(start=datetime.datetime(2023, 1, 1, 0, 0), end=datetime.datetime(2023, 1, 2, 0, 0), duration=datetime.timedelta(days=1), interval=datetime.timedelta(seconds=3600), include_end=True)

from rompy.model import ModelRun
from rompy.swan.subcomponents.physics import KOMEN, JANSSEN, WESTHUYSEN, ST6C1, ST6C2, ST6C3, ST6C4, ST6C5
runs = []
for component in [KOMEN, JANSSEN, WESTHUYSEN, ST6C1, ST6C2, ST6C3, ST6C4, ST6C5]:
    source_terms = component()
    run_id = f"{source_terms.model_type.lower()}"
    new_config = set_experiment(config, source_terms=source_terms)

    print(f"\n{new_config.startup.project.render()}")
    print(f"{new_config.physics.gen.source_terms.render()}")

    runs.append(ModelRun(
        run_id=run_id,
        config=new_config,
        period=period,
        output_dir=str(workdir)),
    )

PROJECT name='Test sensitivity' nr='run1' title1='Source terms sensitivity testing' title2='Experiment KOMEN'
KOMEN DRAG WU

PROJECT name='Test sensitivity' nr='run1' title1='Source terms sensitivity testing' title2='Experiment JANSSEN'
JANSSEN DRAG WU

PROJECT name='Test sensitivity' nr='run1' title1='Source terms sensitivity testing' title2='Experiment WESTHUYSEN'
WESTHUYSEN DRAG WU

PROJECT name='Test sensitivity' nr='run1' title1='Source terms sensitivity testing' title2='Experiment ST6C1'
ST6 a1sds=4.7e-07 a2sds=6.6e-06 p1sds=4.0 p2sds=4.0 UP HWANG VECTAU U10PROXY windscaling=28.0 AGROW

PROJECT name='Test sensitivity' nr='run1' title1='Source terms sensitivity testing' title2='Experiment ST6C2'
ST6 a1sds=4.7e-07 a2sds=6.6e-06 p1sds=4.0 p2sds=4.0 UP FAN VECTAU U10PROXY windscaling=28.0 AGROW

PROJECT name='Test sensitivity' nr='run1' title1='Source terms sensitivity testing' title2='Experiment ST6C3'
ST6 a1sds=2.8e-06 a2sds=3.5e-05 p1sds=4.0 p2sds=4.0 UP HWANG VECTAU U10PROXY windscaling=32.0 AGROW

PROJECT name='Test sensitivity' nr='run1' title1='Source terms sensitivity testing' title2='Experiment ST6C4'
ST6 a1sds=2.8e-06 a2sds=3.5e-05 p1sds=4.0 p2sds=4.0 UP HWANG VECTAU U10PROXY windscaling=32.0 DEBIAS cdfac=0.89 AGROW

PROJECT name='Test sensitivity' nr='run1' title1='Source terms sensitivity testing' title2='Experiment ST6C5'
ST6 a1sds=6.5e-06 a2sds=8.5e-05 p1sds=4.0 p2sds=4.0 UP HWANG VECTAU U10PROXY windscaling=35.0 DEBIAS cdfac=0.89 AGROW

Generate workspaces

for run in runs:
    run()

INFO:rompy.model:
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Model settings:
INFO:rompy.model:
run_id: komen
period:
        Start: 2023-01-01 00:00:00
        End: 2023-01-02 00:00:00
        Duration: 1 day, 0:00:00
        Interval: 1:00:00
        Include End: True

output_dir: example_sensitivity
config: <class 'rompy.swan.config.SwanConfigComponents'>

INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Generating model input files in example_sensitivity
INFO:rompy.swan.data:   Writing bottom to example_sensitivity/komen/bottom.grd
INFO:rompy.swan.data:   Writing wind to example_sensitivity/komen/wind.grd
INFO:rompy.model:
INFO:rompy.model:Successfully generated project in example_sensitivity
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Model settings:
INFO:rompy.model:
run_id: janssen
period:
        Start: 2023-01-01 00:00:00
        End: 2023-01-02 00:00:00
        Duration: 1 day, 0:00:00
        Interval: 1:00:00
        Include End: True

output_dir: example_sensitivity
config: <class 'rompy.swan.config.SwanConfigComponents'>

INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Generating model input files in example_sensitivity
INFO:rompy.swan.data:   Writing bottom to example_sensitivity/janssen/bottom.grd
INFO:rompy.swan.data:   Writing wind to example_sensitivity/janssen/wind.grd
INFO:rompy.model:
INFO:rompy.model:Successfully generated project in example_sensitivity
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Model settings:
INFO:rompy.model:
run_id: westhuysen
period:
        Start: 2023-01-01 00:00:00
        End: 2023-01-02 00:00:00
        Duration: 1 day, 0:00:00
        Interval: 1:00:00
        Include End: True

output_dir: example_sensitivity
config: <class 'rompy.swan.config.SwanConfigComponents'>

INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Generating model input files in example_sensitivity
INFO:rompy.swan.data:   Writing bottom to example_sensitivity/westhuysen/bottom.grd
INFO:rompy.swan.data:   Writing wind to example_sensitivity/westhuysen/wind.grd
INFO:rompy.model:
INFO:rompy.model:Successfully generated project in example_sensitivity
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Model settings:
INFO:rompy.model:
run_id: st6c1
period:
        Start: 2023-01-01 00:00:00
        End: 2023-01-02 00:00:00
        Duration: 1 day, 0:00:00
        Interval: 1:00:00
        Include End: True

output_dir: example_sensitivity
config: <class 'rompy.swan.config.SwanConfigComponents'>

INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Generating model input files in example_sensitivity
INFO:rompy.swan.data:   Writing bottom to example_sensitivity/st6c1/bottom.grd
INFO:rompy.swan.data:   Writing wind to example_sensitivity/st6c1/wind.grd
INFO:rompy.model:
INFO:rompy.model:Successfully generated project in example_sensitivity
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Model settings:
INFO:rompy.model:
run_id: st6c2
period:
        Start: 2023-01-01 00:00:00
        End: 2023-01-02 00:00:00
        Duration: 1 day, 0:00:00
        Interval: 1:00:00
        Include End: True

output_dir: example_sensitivity
config: <class 'rompy.swan.config.SwanConfigComponents'>

INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Generating model input files in example_sensitivity
INFO:rompy.swan.data:   Writing bottom to example_sensitivity/st6c2/bottom.grd
INFO:rompy.swan.data:   Writing wind to example_sensitivity/st6c2/wind.grd
INFO:rompy.model:
INFO:rompy.model:Successfully generated project in example_sensitivity
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Model settings:
INFO:rompy.model:
run_id: st6c3
period:
        Start: 2023-01-01 00:00:00
        End: 2023-01-02 00:00:00
        Duration: 1 day, 0:00:00
        Interval: 1:00:00
        Include End: True

output_dir: example_sensitivity
config: <class 'rompy.swan.config.SwanConfigComponents'>

INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Generating model input files in example_sensitivity
INFO:rompy.swan.data:   Writing bottom to example_sensitivity/st6c3/bottom.grd
INFO:rompy.swan.data:   Writing wind to example_sensitivity/st6c3/wind.grd
INFO:rompy.model:
INFO:rompy.model:Successfully generated project in example_sensitivity
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Model settings:
INFO:rompy.model:
run_id: st6c4
period:
        Start: 2023-01-01 00:00:00
        End: 2023-01-02 00:00:00
        Duration: 1 day, 0:00:00
        Interval: 1:00:00
        Include End: True

output_dir: example_sensitivity
config: <class 'rompy.swan.config.SwanConfigComponents'>

INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Generating model input files in example_sensitivity
INFO:rompy.swan.data:   Writing bottom to example_sensitivity/st6c4/bottom.grd
INFO:rompy.swan.data:   Writing wind to example_sensitivity/st6c4/wind.grd
INFO:rompy.model:
INFO:rompy.model:Successfully generated project in example_sensitivity
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:
INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Model settings:
INFO:rompy.model:
run_id: st6c5
period:
        Start: 2023-01-01 00:00:00
        End: 2023-01-02 00:00:00
        Duration: 1 day, 0:00:00
        Interval: 1:00:00
        Include End: True

output_dir: example_sensitivity
config: <class 'rompy.swan.config.SwanConfigComponents'>

INFO:rompy.model:-----------------------------------------------------
INFO:rompy.model:Generating model input files in example_sensitivity
INFO:rompy.swan.data:   Writing bottom to example_sensitivity/st6c5/bottom.grd
INFO:rompy.swan.data:   Writing wind to example_sensitivity/st6c5/wind.grd
INFO:rompy.model:
INFO:rompy.model:Successfully generated project in example_sensitivity
INFO:rompy.model:-----------------------------------------------------

Check the workspace

modeldirs = sorted(workdir.glob("*"))
modeldirs

[PosixPath('example_sensitivity/janssen'),
 PosixPath('example_sensitivity/komen'),
 PosixPath('example_sensitivity/st6c1'),
 PosixPath('example_sensitivity/st6c2'),
 PosixPath('example_sensitivity/st6c3'),
 PosixPath('example_sensitivity/st6c4'),
 PosixPath('example_sensitivity/st6c5'),
 PosixPath('example_sensitivity/westhuysen')]

sorted(modeldirs[0].glob("*"))

[PosixPath('example_sensitivity/janssen/INPUT'),
 PosixPath('example_sensitivity/janssen/bottom.grd'),
 PosixPath('example_sensitivity/janssen/wind.grd')]

input = modeldirs[0] / "INPUT"
print(input.read_text())

! Rompy SwanConfig
! Template: /source/csiro/rompy/rompy/templates/swancomp
! Generated: 2023-11-09 19:10:43.112490 on rafael-XPS by rguedes


! Startup -------------------------------------------------------------------------------------------------------------------------------------------------------------------------

PROJECT name='Test sensitivity' nr='run1' title1='Source terms sensitivity testing' title2='Experiment JANSSEN'

SET level=0.0 depmin=0.05 NAUTICAL

MODE NONSTATIONARY TWODIMENSIONAL

COORDINATES SPHERICAL CCM

! Computational Grid --------------------------------------------------------------------------------------------------------------------------------------------------------------


CGRID REGULAR xpc=110.0 ypc=-35.2 alpc=4.0 xlenc=7.5 ylenc=12.5 mxc=14 myc=24 CIRCLE mdc=36 flow=0.04 fhigh=1.0

! Input Grids ---------------------------------------------------------------------------------------------------------------------------------------------------------------------

INPGRID BOTTOM REG 109.0 -36.0 0.0 9 14 1.0 1.0 EXC -99.0
READINP BOTTOM -1.0 'bottom.grd' 3 FREE

INPGRID WIND REG 110.0 -35.0 0.0 1 2 5.0 5.0 EXC -99.0 NONSTATION 20230101.000000 6.0 HR
READINP WIND 1.0 'wind.grd' 3 0 1 0 FREE



! Boundary and Initial conditions -------------------------------------------------------------------------------------------------------------------------------------------------

BOUND SHAPESPEC TMA gamma=3.3 d=12.0 PEAK DSPR DEGREES
BOUNDSPEC SIDE WEST CCW CONSTANT PAR hs=2.0 per=12.0 dir=255.0 dd=25.0

INITIAL DEFAULT


! Physics -------------------------------------------------------------------------------------------------------------------------------------------------------------------------

GEN3 JANSSEN DRAG WU

FRICTION JONSWAP CONSTANT cfjon=0.038


! Numerics ------------------------------------------------------------------------------------------------------------------------------------------------------------------------

PROP BSBT

NUMERIC STOPC dabs=0.02 drel=0.02 curvat=0.02 npnts=98.0 STATIONARY mxitst=3


! Output --------------------------------------------------------------------------------------------------------------------------------------------------------------------------

POINTS sname='pts' &
    xp=114.0 yp=-34.0 &
    xp=112.5 yp=-26.0 &
    xp=115.0 yp=-30.0

QUANTITY DEPTH HSIGN TPS DIR TM01 excv=-9.0

QUANTITY HSWELL fswell=0.125

BLOCK sname='COMPGRID' fname='swangrid.nc' &
    DEPTH &
    WIND &
    HSIGN &
    TPS &
    DIR &
    OUTPUT tbegblk=20230101.000000 deltblk=1.0 HR

TABLE sname='pts' HEADER fname='swantable.txt' &
    TIME &
    HSIGN &
    HSWELL &
    DIR &
    TPS &
    TM01 &
    OUTPUT tbegtbl=20230101.000000 delttbl=1.0 HR

SPECOUT sname='pts' SPEC2D ABS fname='swanspec.nc' OUTPUT tbegspc=20230101.000000 deltspc=1.0 HR


! Lockup --------------------------------------------------------------------------------------------------------------------------------------------------------------------------

COMPUTE STATIONARY time=20230101.000000
COMPUTE STATIONARY time=20230101.010000
HOTFILE fname='hotfile_20230101T010000.txt' FREE
COMPUTE STATIONARY time=20230101.020000
COMPUTE STATIONARY time=20230101.030000
COMPUTE STATIONARY time=20230101.040000
COMPUTE STATIONARY time=20230101.050000
COMPUTE STATIONARY time=20230101.060000
COMPUTE STATIONARY time=20230101.070000
COMPUTE STATIONARY time=20230101.080000
COMPUTE STATIONARY time=20230101.090000
COMPUTE STATIONARY time=20230101.100000
COMPUTE STATIONARY time=20230101.110000
COMPUTE STATIONARY time=20230101.120000
COMPUTE STATIONARY time=20230101.130000
COMPUTE STATIONARY time=20230101.140000
COMPUTE STATIONARY time=20230101.150000
COMPUTE STATIONARY time=20230101.160000
COMPUTE STATIONARY time=20230101.170000
COMPUTE STATIONARY time=20230101.180000
COMPUTE STATIONARY time=20230101.190000
COMPUTE STATIONARY time=20230101.200000
COMPUTE STATIONARY time=20230101.210000
COMPUTE STATIONARY time=20230101.220000
COMPUTE STATIONARY time=20230101.230000
COMPUTE STATIONARY time=20230102.000000
HOTFILE fname='hotfile_20230102T000000.txt' FREE
STOP

Run the model

for modeldir in modeldirs:
    cmd = ["docker", "run", "-v", f"./{modeldir}:/home", "oceanum/swan:4141", "swan.exe", ">", f"{modeldir}/swan.log"]
    print(" ".join(cmd))
    os.system(" ".join(cmd))

docker run -v ./example_sensitivity/janssen:/home oceanum/swan:4141 swan.exe > example_sensitivity/janssen/swan.log
docker run -v ./example_sensitivity/komen:/home oceanum/swan:4141 swan.exe > example_sensitivity/komen/swan.log
docker run -v ./example_sensitivity/st6c1:/home oceanum/swan:4141 swan.exe > example_sensitivity/st6c1/swan.log
docker run -v ./example_sensitivity/st6c2:/home oceanum/swan:4141 swan.exe > example_sensitivity/st6c2/swan.log
docker run -v ./example_sensitivity/st6c3:/home oceanum/swan:4141 swan.exe > example_sensitivity/st6c3/swan.log
docker run -v ./example_sensitivity/st6c4:/home oceanum/swan:4141 swan.exe > example_sensitivity/st6c4/swan.log
docker run -v ./example_sensitivity/st6c5:/home oceanum/swan:4141 swan.exe > example_sensitivity/st6c5/swan.log
docker run -v ./example_sensitivity/westhuysen:/home oceanum/swan:4141 swan.exe > example_sensitivity/westhuysen/swan.log

# Check for output files
for modeldir in modeldirs:
    print(sorted(modeldir.glob("*.nc")))

[PosixPath('example_sensitivity/janssen/swangrid.nc'), PosixPath('example_sensitivity/janssen/swanspec.nc')]
[PosixPath('example_sensitivity/komen/swangrid.nc'), PosixPath('example_sensitivity/komen/swanspec.nc')]
[PosixPath('example_sensitivity/st6c1/swangrid.nc'), PosixPath('example_sensitivity/st6c1/swanspec.nc')]
[PosixPath('example_sensitivity/st6c2/swangrid.nc'), PosixPath('example_sensitivity/st6c2/swanspec.nc')]
[PosixPath('example_sensitivity/st6c3/swangrid.nc'), PosixPath('example_sensitivity/st6c3/swanspec.nc')]
[PosixPath('example_sensitivity/st6c4/swangrid.nc'), PosixPath('example_sensitivity/st6c4/swanspec.nc')]
[PosixPath('example_sensitivity/st6c5/swangrid.nc'), PosixPath('example_sensitivity/st6c5/swanspec.nc')]
[PosixPath('example_sensitivity/westhuysen/swangrid.nc'), PosixPath('example_sensitivity/westhuysen/swanspec.nc')]

Plot outputs

import os
import numpy as np
import pandas as pd
import xarray as xr
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
from wavespectra import read_ncswan, read_swan
from wavespectra.core.swan import read_tab

pd.set_option("display.notebook_repr_html", False)

def read_gridded_output(run):
    """Read mean gridded output from a model run"""
    modeldir = Path(run.output_dir) / run.run_id
    dset = xr.open_dataset(modeldir / run.config.output.block.fname)
    return dset.mean("time")


def read_spectra_output(run):
    """Read mean spectra output from a model run"""
    modeldir = Path(run.output_dir) / run.run_id
    dset = read_ncswan(modeldir / run.config.output.specout.fname)
    return dset.mean("time")

# Gridded parameters

dsgrid = xr.concat([read_gridded_output(run) for run in runs], dim="source_terms")
dsgrid["source_terms"] = [run.run_id for run in runs]
dsgrid

<xarray.Dataset>
Dimensions:       (yc: 25, xc: 15, source_terms: 8)
Coordinates:
    longitude     (yc, xc) float32 110.0 110.5 111.1 111.6 ... 115.5 116.1 116.6
    latitude      (yc, xc) float32 -35.2 -35.16 -35.13 ... -22.28 -22.24 -22.21
  * source_terms  (source_terms) <U10 'komen' 'janssen' ... 'st6c4' 'st6c5'
Dimensions without coordinates: yc, xc
Data variables:
    depth         (source_terms, yc, xc) float32 4.824e+03 4.16e+03 ... nan nan
    xwnd          (source_terms, yc, xc) float32 -0.8986 -1.029 ... nan nan
    ywnd          (source_terms, yc, xc) float32 6.718 6.65 6.582 ... nan nan
    hs            (source_terms, yc, xc) float32 1.019 0.6307 0.6288 ... nan nan
    tps           (source_terms, yc, xc) float32 11.66 11.66 11.66 ... nan nan
    theta0        (source_terms, yc, xc) float32 255.5 291.2 291.5 ... nan nan

xarray.Dataset

• Dimensions:
  • yc: 25
  • xc: 15
  • source_terms: 8
• Coordinates: (3)
  • longitude
    (yc, xc)
    float32
    110.0 110.5 111.1 ... 116.1 116.6

    units :

    degrees_east

    long_name :

    longitude

    standard_name :

    longitude

    array([[110.      , 110.53441 , 111.06882 , 111.603226, 112.137634,
            112.67204 , 113.20646 , 113.74087 , 114.275276, 114.809685,
            115.34409 , 115.8785  , 116.41291 , 116.94732 , 117.48173 ],
           [109.96367 , 110.49808 , 111.032486, 111.566895, 112.1013  ,
            112.63571 , 113.17013 , 113.70454 , 114.238945, 114.77335 ,
            115.30776 , 115.84217 , 116.37658 , 116.91099 , 117.4454  ],
           [109.92734 , 110.46175 , 110.996155, 111.53056 , 112.06497 ,
            112.59938 , 113.13379 , 113.668205, 114.202614, 114.73702 ,
            115.27143 , 115.80584 , 116.34025 , 116.87466 , 117.409065],
           [109.89101 , 110.425415, 110.95982 , 111.49423 , 112.02864 ,
            112.56305 , 113.09746 , 113.631874, 114.16628 , 114.70069 ,
            115.2351  , 115.76951 , 116.30392 , 116.838326, 117.372734],
           [109.854675, 110.389084, 110.92349 , 111.4579  , 111.99231 ,
            112.52672 , 113.06113 , 113.59554 , 114.12995 , 114.66436 ,
            115.19877 , 115.73318 , 116.267586, 116.801994, 117.3364  ],
           [109.818344, 110.35275 , 110.88716 , 111.42157 , 111.95598 ,
            112.49039 , 113.024796, 113.559204, 114.09362 , 114.62803 ,
            115.16244 , 115.696846, 116.231255, 116.76566 , 117.30007 ],
           [109.78201 , 110.31642 , 110.85083 , 111.38524 , 111.91965 ,
            112.454056, 112.988464, 113.52287 , 114.05728 , 114.5917  ,
    ...
            114.690125, 115.22453 , 115.75894 , 116.29335 , 116.82777 ],
           [109.3097  , 109.84411 , 110.37852 , 110.91293 , 111.44734 ,
            111.98175 , 112.51616 , 113.05057 , 113.58498 , 114.119385,
            114.65379 , 115.1882  , 115.72261 , 116.25702 , 116.791435],
           [109.27337 , 109.80778 , 110.342186, 110.876595, 111.41101 ,
            111.94542 , 112.47983 , 113.01424 , 113.548645, 114.08305 ,
            114.61746 , 115.15187 , 115.68628 , 116.22069 , 116.755104],
           [109.23704 , 109.77145 , 110.305855, 110.84026 , 111.37467 ,
            111.90909 , 112.4435  , 112.977905, 113.512314, 114.04672 ,
            114.58113 , 115.11554 , 115.64995 , 116.18436 , 116.718765],
           [109.20071 , 109.735115, 110.26952 , 110.80393 , 111.33834 ,
            111.87276 , 112.407166, 112.941574, 113.47598 , 114.01039 ,
            114.5448  , 115.07921 , 115.61362 , 116.148026, 116.682434],
           [109.164375, 109.698784, 110.23319 , 110.7676  , 111.30201 ,
            111.836426, 112.370834, 112.90524 , 113.43965 , 113.97406 ,
            114.50847 , 115.04288 , 115.577286, 116.111694, 116.6461  ],
           [109.128044, 109.66245 , 110.19686 , 110.73127 , 111.26568 ,
            111.80009 , 112.3345  , 112.86891 , 113.40332 , 113.93773 ,
            114.47214 , 115.006546, 115.540955, 116.07536 , 116.60977 ]],
          dtype=float32)

  • latitude
    (yc, xc)
    float32
    -35.2 -35.16 ... -22.24 -22.21

    units :

    degrees_north

    long_name :

    latitude

    standard_name :

    latitude

    array([[-35.2     , -35.162632, -35.125263, -35.08789 , -35.05052 ,
            -35.013153, -34.975784, -34.938416, -34.901043, -34.863674,
            -34.826305, -34.788937, -34.751568, -34.714195, -34.676826],
           [-34.680435, -34.643066, -34.605698, -34.56833 , -34.530956,
            -34.493587, -34.45622 , -34.41885 , -34.38148 , -34.34411 ,
            -34.30674 , -34.26937 , -34.232002, -34.194633, -34.15726 ],
           [-34.160873, -34.1235  , -34.086132, -34.048763, -34.011395,
            -33.974022, -33.936653, -33.899284, -33.861916, -33.824547,
            -33.787178, -33.749805, -33.712437, -33.675068, -33.6377  ],
           [-33.641308, -33.60394 , -33.566566, -33.529198, -33.49183 ,
            -33.45446 , -33.41709 , -33.37972 , -33.34235 , -33.30498 ,
            -33.267612, -33.230244, -33.19287 , -33.155502, -33.118134],
           [-33.121742, -33.084373, -33.047005, -33.009632, -32.972263,
            -32.934895, -32.897526, -32.860157, -32.822784, -32.785416,
            -32.748047, -32.71068 , -32.67331 , -32.635937, -32.598568],
           [-32.602177, -32.564808, -32.52744 , -32.49007 , -32.452698,
            -32.41533 , -32.37796 , -32.34059 , -32.303223, -32.265854,
            -32.22848 , -32.191113, -32.153744, -32.116375, -32.079002],
           [-32.08261 , -32.045242, -32.007874, -31.970505, -31.933134,
            -31.895765, -31.858397, -31.821026, -31.783657, -31.746286,
    ...
            -25.474142, -25.436771, -25.399403, -25.362034, -25.324665],
           [-25.328274, -25.290903, -25.253532, -25.216164, -25.178795,
            -25.141426, -25.104055, -25.066685, -25.029316, -24.991947,
            -24.954578, -24.917208, -24.879837, -24.842468, -24.8051  ],
           [-24.808708, -24.77134 , -24.73397 , -24.696602, -24.659231,
            -24.62186 , -24.584492, -24.547123, -24.509754, -24.472383,
            -24.435013, -24.397644, -24.360275, -24.322906, -24.285536],
           [-24.289143, -24.251774, -24.214405, -24.177036, -24.139666,
            -24.102295, -24.064926, -24.027557, -23.990189, -23.952818,
            -23.915447, -23.878078, -23.84071 , -23.80334 , -23.76597 ],
           [-23.769579, -23.732208, -23.69484 , -23.65747 , -23.620102,
            -23.582731, -23.54536 , -23.507992, -23.470623, -23.433254,
            -23.395884, -23.358513, -23.321144, -23.283775, -23.246407],
           [-23.250015, -23.212646, -23.175276, -23.137907, -23.100536,
            -23.063168, -23.025799, -22.988428, -22.95106 , -22.913689,
            -22.87632 , -22.838951, -22.80158 , -22.764212, -22.726841],
           [-22.73045 , -22.69308 , -22.65571 , -22.618341, -22.58097 ,
            -22.543602, -22.506233, -22.468863, -22.431494, -22.394123,
            -22.356754, -22.319386, -22.282015, -22.244646, -22.207275]],
          dtype=float32)

  • source_terms
    (source_terms)
    <U10
    'komen' 'janssen' ... 'st6c5'

    array(['komen', 'janssen', 'westhuysen', 'st6c1', 'st6c2', 'st6c3', 'st6c4',
           'st6c5'], dtype='<U10')

• Data variables: (6)
  • depth
    (source_terms, yc, xc)
    float32
    4.824e+03 4.16e+03 ... nan nan

    array([[[4823.951 , 4160.235 , 3517.904 , ...,       nan,       nan,
                   nan],
            [4081.297 , 3441.2422, 2892.3357, ...,       nan,       nan,
                   nan],
            [3056.671 , 2631.195 , 2384.4294, ...,       nan,       nan,
                   nan],
            ...,
            [3246.6487, 4145.945 , 4225.1567, ...,       nan,       nan,
                   nan],
            [3510.1592, 4227.9146, 4563.9614, ...,       nan,       nan,
                   nan],
            [3835.8284, 4350.438 , 4695.601 , ...,       nan,       nan,
                   nan]],
    
           [[4823.951 , 4160.235 , 3517.904 , ...,       nan,       nan,
                   nan],
            [4081.297 , 3441.2422, 2892.3357, ...,       nan,       nan,
                   nan],
            [3056.671 , 2631.195 , 2384.4294, ...,       nan,       nan,
                   nan],
    ...
            [3246.6487, 4145.945 , 4225.1567, ...,       nan,       nan,
                   nan],
            [3510.1592, 4227.9146, 4563.9614, ...,       nan,       nan,
                   nan],
            [3835.8284, 4350.438 , 4695.601 , ...,       nan,       nan,
                   nan]],
    
           [[4823.951 , 4160.235 , 3517.904 , ...,       nan,       nan,
                   nan],
            [4081.297 , 3441.2422, 2892.3357, ...,       nan,       nan,
                   nan],
            [3056.671 , 2631.195 , 2384.4294, ...,       nan,       nan,
                   nan],
            ...,
            [3246.6487, 4145.945 , 4225.1567, ...,       nan,       nan,
                   nan],
            [3510.1592, 4227.9146, 4563.9614, ...,       nan,       nan,
                   nan],
            [3835.8284, 4350.438 , 4695.601 , ...,       nan,       nan,
                   nan]]], dtype=float32)

  • xwnd
    (source_terms, yc, xc)
    float32
    -0.8986 -1.029 -1.157 ... nan nan

    array([[[-0.8985871, -1.0285959, -1.157384 , ...,        nan,
                    nan,        nan],
            [-1.1927854, -1.3132724, -1.432905 , ...,        nan,
                    nan,        nan],
            [-1.6694846, -1.7384562, -1.8047427, ...,        nan,
                    nan,        nan],
            ...,
            [       nan,        nan,        nan, ...,        nan,
                    nan,        nan],
            [       nan,        nan,        nan, ...,        nan,
                    nan,        nan],
            [       nan,        nan,        nan, ...,        nan,
                    nan,        nan]],
    
           [[-0.8985871, -1.0285959, -1.157384 , ...,        nan,
                    nan,        nan],
            [-1.1927854, -1.3132724, -1.432905 , ...,        nan,
                    nan,        nan],
            [-1.6694846, -1.7384562, -1.8047427, ...,        nan,
                    nan,        nan],
    ...
            [       nan,        nan,        nan, ...,        nan,
                    nan,        nan],
            [       nan,        nan,        nan, ...,        nan,
                    nan,        nan],
            [       nan,        nan,        nan, ...,        nan,
                    nan,        nan]],
    
           [[-0.8985871, -1.0285959, -1.157384 , ...,        nan,
                    nan,        nan],
            [-1.1927854, -1.3132724, -1.432905 , ...,        nan,
                    nan,        nan],
            [-1.6694846, -1.7384562, -1.8047427, ...,        nan,
                    nan,        nan],
            ...,
            [       nan,        nan,        nan, ...,        nan,
                    nan,        nan],
            [       nan,        nan,        nan, ...,        nan,
                    nan,        nan],
            [       nan,        nan,        nan, ...,        nan,
                    nan,        nan]]], dtype=float32)

  • ywnd
    (source_terms, yc, xc)
    float32
    6.718 6.65 6.582 ... nan nan nan

    array([[[6.7184663, 6.650105 , 6.5822325, ...,       nan,       nan,
                   nan],
            [6.903531 , 6.849573 , 6.785363 , ...,       nan,       nan,
                   nan],
            [7.2056627, 7.13828  , 7.054905 , ...,       nan,       nan,
                   nan],
            ...,
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan]],
    
           [[6.7184663, 6.650105 , 6.5822325, ...,       nan,       nan,
                   nan],
            [6.903531 , 6.849573 , 6.785363 , ...,       nan,       nan,
                   nan],
            [7.2056627, 7.13828  , 7.054905 , ...,       nan,       nan,
                   nan],
    ...
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan]],
    
           [[6.7184663, 6.650105 , 6.5822325, ...,       nan,       nan,
                   nan],
            [6.903531 , 6.849573 , 6.785363 , ...,       nan,       nan,
                   nan],
            [7.2056627, 7.13828  , 7.054905 , ...,       nan,       nan,
                   nan],
            ...,
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan]]], dtype=float32)

  • hs
    (source_terms, yc, xc)
    float32
    1.019 0.6307 0.6288 ... nan nan nan

    array([[[1.0192268 , 0.63066536, 0.6288341 , ...,        nan,
                    nan,        nan],
            [1.1814324 , 1.3336895 , 1.2929169 , ...,        nan,
                    nan,        nan],
            [1.2695091 , 1.4816737 , 1.4532303 , ...,        nan,
                    nan,        nan],
            ...,
            [1.7042453 , 1.9786367 , 1.9581891 , ...,        nan,
                    nan,        nan],
            [1.6415908 , 1.8393509 , 1.8341626 , ...,        nan,
                    nan,        nan],
            [1.5887021 , 1.671926  , 1.694815  , ...,        nan,
                    nan,        nan]],
    
           [[1.0107424 , 0.6126289 , 0.60542625, ...,        nan,
                    nan,        nan],
            [1.1889399 , 1.32725   , 1.2820215 , ...,        nan,
                    nan,        nan],
            [1.2861719 , 1.4874724 , 1.4557636 , ...,        nan,
                    nan,        nan],
    ...
            [1.6818448 , 1.9637436 , 1.9407938 , ...,        nan,
                    nan,        nan],
            [1.6280103 , 1.8407547 , 1.8310803 , ...,        nan,
                    nan,        nan],
            [1.574511  , 1.67745   , 1.6956695 , ...,        nan,
                    nan,        nan]],
    
           [[1.0049133 , 0.5968502 , 0.5881523 , ...,        nan,
                    nan,        nan],
            [1.1108131 , 1.1534166 , 1.10535   , ...,        nan,
                    nan,        nan],
            [1.1872003 , 1.3097018 , 1.2791528 , ...,        nan,
                    nan,        nan],
            ...,
            [1.7535931 , 2.0571308 , 2.0438855 , ...,        nan,
                    nan,        nan],
            [1.6953642 , 1.9304483 , 1.9248636 , ...,        nan,
                    nan,        nan],
            [1.6400958 , 1.7745602 , 1.7801449 , ...,        nan,
                    nan,        nan]]], dtype=float32)

  • tps
    (source_terms, yc, xc)
    float32
    11.66 11.66 11.66 ... nan nan nan

    array([[[11.661121 , 11.661121 , 11.661732 , ...,        nan,
                    nan,        nan],
            [11.661121 , 11.661793 , 11.66222  , ...,        nan,
                    nan,        nan],
            [11.661121 , 11.662037 , 11.662708 , ...,        nan,
                    nan,        nan],
            ...,
            [ 7.6884065,  7.8873553,  7.903043 , ...,        nan,
                    nan,        nan],
            [ 7.7627187,  7.927702 ,  7.9547405, ...,        nan,
                    nan,        nan],
            [ 7.8102965,  7.9473553,  7.978271 , ...,        nan,
                    nan,        nan]],
    
           [[11.661121 , 11.66164  , 11.662373 , ...,        nan,
                    nan,        nan],
            [11.661121 , 11.662556 , 11.663898 , ...,        nan,
                    nan,        nan],
            [11.661121 , 11.663197 , 10.905086 , ...,        nan,
                    nan,        nan],
    ...
            [ 7.538561 ,  7.665639 ,  7.6623135, ...,        nan,
                    nan,        nan],
            [ 8.1478   ,  7.7109585,  7.7162695, ...,        nan,
                    nan,        nan],
            [ 8.539263 ,  7.7229834,  7.735404 , ...,        nan,
                    nan,        nan]],
    
           [[11.661121 , 11.661884 , 11.662403 , ...,        nan,
                    nan,        nan],
            [11.661121 , 11.661884 , 11.66222  , ...,        nan,
                    nan,        nan],
            [11.661121 , 11.661945 , 11.6628   , ...,        nan,
                    nan,        nan],
            ...,
            [ 7.7295146,  7.864436 ,  7.868037 , ...,        nan,
                    nan,        nan],
            [ 7.7735524,  7.9105506,  7.9117393, ...,        nan,
                    nan,        nan],
            [ 7.8086786,  7.9306006,  7.932705 , ...,        nan,
                    nan,        nan]]], dtype=float32)

  • theta0
    (source_terms, yc, xc)
    float32
    255.5 291.2 291.5 ... nan nan nan

    array([[[255.51137, 291.2079 , 291.5412 , ...,       nan,       nan,
                   nan],
            [232.16513, 207.59586, 205.65694, ...,       nan,       nan,
                   nan],
            [215.15535, 197.54132, 198.0902 , ...,       nan,       nan,
                   nan],
            ...,
            [178.59105, 182.74272, 189.30594, ...,       nan,       nan,
                   nan],
            [183.33075, 184.87103, 189.97305, ...,       nan,       nan,
                   nan],
            [187.59137, 180.92574, 186.74869, ...,       nan,       nan,
                   nan]],
    
           [[255.24213, 287.9488 , 287.68384, ...,       nan,       nan,
                   nan],
            [229.47887, 206.4798 , 204.27303, ...,       nan,       nan,
                   nan],
            [212.41219, 196.26465, 195.89618, ...,       nan,       nan,
                   nan],
    ...
            [178.39902, 182.91827, 189.82843, ...,       nan,       nan,
                   nan],
            [182.74205, 184.25159, 189.59729, ...,       nan,       nan,
                   nan],
            [187.41913, 180.35092, 186.54213, ...,       nan,       nan,
                   nan]],
    
           [[255.1523 , 286.08612, 285.77368, ...,       nan,       nan,
                   nan],
            [242.54309, 226.48305, 225.45906, ...,       nan,       nan,
                   nan],
            [229.49602, 212.3399 , 212.71413, ...,       nan,       nan,
                   nan],
            ...,
            [175.19928, 180.99101, 187.77765, ...,       nan,       nan,
                   nan],
            [179.3098 , 182.44803, 187.57178, ...,       nan,       nan,
                   nan],
            [183.65086, 178.93758, 185.23143, ...,       nan,       nan,
                   nan]]], dtype=float32)

• Indexes: (1)
  • source_terms
    PandasIndex

    PandasIndex(Index(['komen', 'janssen', 'westhuysen', 'st6c1', 'st6c2', 'st6c3', 'st6c4',
           'st6c5'],
          dtype='object', name='source_terms'))

• Attributes: (0)

# Wave spectra

dspec = xr.concat([read_spectra_output(run) for run in runs], dim="source_terms")
dspec["source_terms"] = [run.run_id for run in runs]
dspec

<xarray.Dataset>
Dimensions:       (source_terms: 8, site: 3, freq: 35, dir: 36)
Coordinates:
  * freq          (freq) float32 0.04 0.04397 0.04834 ... 0.8275 0.9097 1.0
  * dir           (dir) float32 261.0 251.0 241.0 231.0 ... 291.0 281.0 271.0
  * site          (site) int64 1 2 3
  * source_terms  (source_terms) <U10 'komen' 'janssen' ... 'st6c4' 'st6c5'
Data variables:
    lon           (source_terms, site) float32 dask.array<chunksize=(1, 3), meta=np.ndarray>
    lat           (source_terms, site) float32 dask.array<chunksize=(1, 3), meta=np.ndarray>
    efth          (source_terms, site, freq, dir) float32 dask.array<chunksize=(1, 3, 35, 36), meta=np.ndarray>
    dpt           (source_terms, site) float32 dask.array<chunksize=(1, 3), meta=np.ndarray>
    wspd          (source_terms, site) float32 dask.array<chunksize=(1, 3), meta=np.ndarray>
    wdir          (source_terms, site) float32 dask.array<chunksize=(1, 3), meta=np.ndarray>

xarray.Dataset

• Dimensions:
  • source_terms: 8
  • site: 3
  • freq: 35
  • dir: 36
• Coordinates: (4)
  • freq
    (freq)
    float32
    0.04 0.04397 0.04834 ... 0.9097 1.0

    standard_name :

    sea_surface_wave_frequency

    units :

    Hz

    array([0.04    , 0.043972, 0.048338, 0.053138, 0.058415, 0.064215, 0.070592,
           0.077602, 0.085307, 0.093778, 0.103091, 0.113327, 0.124581, 0.136951,
           0.15055 , 0.1655  , 0.181934, 0.2     , 0.21986 , 0.241692, 0.265691,
           0.292074, 0.321077, 0.35296 , 0.388008, 0.426537, 0.468892, 0.515452,
           0.566636, 0.622902, 0.684756, 0.752752, 0.827499, 0.909669, 0.999999],
          dtype=float32)

  • dir
    (dir)
    float32
    261.0 251.0 241.0 ... 281.0 271.0

    standard_name :

    sea_surface_wave_from_direction

    units :

    degree

    array([261.      , 251.      , 241.      , 231.      , 221.      , 211.      ,
           201.      , 191.      , 181.      , 171.      , 160.99998 , 151.      ,
           141.      , 131.      , 120.999985, 110.999985, 100.99999 ,  90.99999 ,
            80.99999 ,  70.999985,  60.999985,  50.999985,  40.99999 ,  30.999989,
            20.99999 ,  10.999992,   0.999994, 350.99997 , 340.99997 , 330.99997 ,
           320.99997 , 310.99997 , 300.99997 , 290.99997 , 281.      , 271.      ],
          dtype=float32)

  • site
    (site)
    int64
    1 2 3

    standard_name :

    site

    units :

    array([1, 2, 3])

  • source_terms
    (source_terms)
    <U10
    'komen' 'janssen' ... 'st6c5'

    array(['komen', 'janssen', 'westhuysen', 'st6c1', 'st6c2', 'st6c3', 'st6c4',
           'st6c5'], dtype='<U10')

• Data variables: (6)
  • lon
    (source_terms, site)
    float32
    dask.array<chunksize=(1, 3), meta=np.ndarray>

    Array Chunk Bytes 96 B 12 B Shape (8, 3) (1, 3) Dask graph 8 chunks in 25 graph layers Data type float32 numpy.ndarray

  • lat
    (source_terms, site)
    float32
    dask.array<chunksize=(1, 3), meta=np.ndarray>

    Array Chunk Bytes 96 B 12 B Shape (8, 3) (1, 3) Dask graph 8 chunks in 25 graph layers Data type float32 numpy.ndarray

  • efth
    (source_terms, site, freq, dir)
    float32
    dask.array<chunksize=(1, 3, 35, 36), meta=np.ndarray>

    Array Chunk Bytes 118.12 kiB 14.77 kiB Shape (8, 3, 35, 36) (1, 3, 35, 36) Dask graph 8 chunks in 49 graph layers Data type float32 numpy.ndarray

  • dpt
    (source_terms, site)
    float32
    dask.array<chunksize=(1, 3), meta=np.ndarray>

    Array Chunk Bytes 96 B 12 B Shape (8, 3) (1, 3) Dask graph 8 chunks in 41 graph layers Data type float32 numpy.ndarray

  • wspd
    (source_terms, site)
    float32
    dask.array<chunksize=(1, 3), meta=np.ndarray>

    Array Chunk Bytes 96 B 12 B Shape (8, 3) (1, 3) Dask graph 8 chunks in 89 graph layers Data type float32 numpy.ndarray

  • wdir
    (source_terms, site)
    float32
    dask.array<chunksize=(1, 3), meta=np.ndarray>

    Array Chunk Bytes 96 B 12 B Shape (8, 3) (1, 3) Dask graph 8 chunks in 89 graph layers Data type float32 numpy.ndarray

• Indexes: (4)
  • freq
    PandasIndex

    PandasIndex(Index([ 0.03999999910593033,   0.0439719632267952,  0.04833833873271942,
            0.05313829332590103, 0.058414872735738754,  0.06421541422605515,
            0.07059194892644882,  0.07760166376829147,  0.08530744165182114,
            0.09377838671207428,  0.10309050232172012,  0.11332729458808899,
            0.12458059191703796,  0.13695132732391357,   0.1505504697561264,
             0.1655000001192093,  0.18193399906158447,   0.1999998688697815,
            0.21985965967178345,  0.24169152975082397,  0.26569128036499023,
            0.29207417368888855,   0.3210768699645996,   0.3529595136642456,
             0.3880080580711365,     0.42653688788414,  0.46889159083366394,
             0.5154520869255066,   0.5666360259056091,   0.6229023933410645,
             0.6847560405731201,   0.7527517080307007,    0.827499270439148,
             0.9096691608428955,   0.9999985098838806],
          dtype='float32', name='freq'))

  • dir
    PandasIndex

    PandasIndex(Index([             261.0,              251.0,              241.0,
                        231.0,              221.0,              211.0,
                        201.0,              191.0,              181.0,
                        171.0, 160.99998474121094,              151.0,
                        141.0,              131.0, 120.99998474121094,
           110.99998474121094, 100.99999237060547,  90.99999237060547,
            80.99999237060547,  70.99998474121094,  60.99998474121094,
            50.99998474121094,   40.9999885559082, 30.999988555908203,
           20.999990463256836, 10.999992370605469, 0.9999943375587463,
            350.9999694824219,  340.9999694824219,  330.9999694824219,
            320.9999694824219,  310.9999694824219,  300.9999694824219,
            290.9999694824219,              281.0,              271.0],
          dtype='float32', name='dir'))

  • site
    PandasIndex

    PandasIndex(Index([1, 2, 3], dtype='int64', name='site'))

  • source_terms
    PandasIndex

    PandasIndex(Index(['komen', 'janssen', 'westhuysen', 'st6c1', 'st6c2', 'st6c3', 'st6c4',
           'st6c5'],
          dtype='object', name='source_terms'))

• Attributes: (0)

Gridded parameters

f = dsgrid.hs.plot(
    x="longitude",
    y="latitude",
    col="source_terms",
    col_wrap=4,
    vmin=0.5,
    vmax=3.0,
    cmap="turbo",
    subplot_kws=dict(projection=ccrs.PlateCarree()),
    cbar_kwargs=dict(label="Hs (m)"),
)
f.map(lambda: plt.gca().coastlines());

Wave spectra

p = dspec.isel(site=0).spec.plot(col="source_terms", col_wrap=4, cbar_kwargs={"label": "Ed (m2/Hz/deg)"})