SWAN BOUNDSPEC SEGMENT¶

This notebooks shows examples of how to prescribe BOUNDSPEC SEGMENT spectral boundaries using rompy boundary data objects.

Boundary of type BOUNDSPEC SEGMENT can be specified from existing spectral data using the rompy_swan.boundary.BoundspecSegmentXY object. The boundary locations can be defined in three different ways:

Type	Description
SIDE	Define boundary segment along one side of computational grid
SIDES	Define boundary segment along multiple, contiguous sides of computational grid
XY	Define boundary segment from a sequency of points explicitly provided

The boundary spectra are defined by interpolating or nearest-selecting from the source spectra data at the selected boundary locations.

This class only supports FILE type boundary since the PAR type does not allow for nonstationary boundary specification (the user can prescribe PAR type boundary by using the SWAN components if required).

We currently support TPAR and SPEC2D file types to write the boundary data.

In [1]:

%load_ext autoreload
%autoreload 2

import os
from pathlib import Path
from tempfile import mkdtemp
import matplotlib.pyplot as plt
import matplotlib
from matplotlib import colors
import cartopy.crs as ccrs
import pandas as pd
import wavespectra

from rompy.core.source import SourceFile
from rompy.core.time import TimeRange
from rompy_swan.grid import SwanGrid
from rompy_swan.boundary import BoundspecSegmentXY
from rompy_swan.subcomponents.boundary import SIDE, SIDES, XY

import warnings
warnings.filterwarnings('ignore')

%load_ext autoreload %autoreload 2 import os from pathlib import Path from tempfile import mkdtemp import matplotlib.pyplot as plt import matplotlib from matplotlib import colors import cartopy.crs as ccrs import pandas as pd import wavespectra from rompy.core.source import SourceFile from rompy.core.time import TimeRange from rompy_swan.grid import SwanGrid from rompy_swan.boundary import BoundspecSegmentXY from rompy_swan.subcomponents.boundary import SIDE, SIDES, XY import warnings warnings.filterwarnings('ignore')

Helper functions¶

In [2]:

def read_tpar(tparfile):
    """Read SWAN TPAR files as a Dataframe."""
    df = pd.read_csv(
        tparfile,
        sep=" ",
        header=None,
        skiprows=1,
        parse_dates=[0],
        date_format="%Y%m%d.%H%M%S",
        index_col=0,
    )
    df.columns = ["hs", "tp", "dpm", "dspr"]
    return df


def get_color(cmap, value, vmin, vmax):
    """Return the HEX color for a value in a colormap."""
    cmap = matplotlib.cm.get_cmap(cmap)
    norm = colors.Normalize(vmin=vmin, vmax=vmax, clip=True)
    return colors.rgb2hex(cmap(norm(value)))


def plot_boundary_side(dset, tpars, grid, time):
    """Plot side boundary stats.

    This function plots a snapshot of wave statistics from the source spectra dataset
    and the boundary wave stats generated for a grid from those spectra points.

    Parameters
    ----------
    dset: xr.Dataset
        Source spectra dataset used to define the boundary.
    tpars: list[pd.DataFrame]
        Boundary time series defined from TPAR or SWAN ASCII file for each segment.
    grid: SwanGrid
        Grid object defining the SWAN domain.
    time: Datatime | str
        Time to plot.

    """
    # xb, yb = bnd._boundary_points(grid)
    xb = grid.x[:, 0]
    yb = grid.y[:, 0]

    fig, axs = plt.subplots(1, 3, subplot_kw=dict(projection=ccrs.PlateCarree()), figsize=(15, 3.5))

    # Hs
    ax = axs[0]
    p = ax.scatter(dset.lon, dset.lat, s=65, c=dset.sel(time=time).spec.hs(), cmap="turbo", vmin=2.0, vmax=3.5)
    plt.colorbar(p, label="Hs (m)")
    for df in tpars:
        xb = [df.loc[time]["x0"], df.loc[time]["x1"]]
        yb = [df.loc[time]["y0"], df.loc[time]["y1"]]
        color = get_color("turbo", df.loc[time]["hs"], 2.0, 3.5)
        ax.plot(xb, yb, color=color, linewidth=4, zorder=10)

    # Tp
    ax = axs[1]
    p = ax.scatter(dset.lon, dset.lat, s=65, c=dset.sel(time=time).spec.tp(), cmap="viridis", vmin=13.8, vmax=14.5)
    plt.colorbar(p, label="Tp (s)")
    for df in tpars:
        xb = [df.loc[time]["x0"], df.loc[time]["x1"]]
        yb = [df.loc[time]["y0"], df.loc[time]["y1"]]
        color = get_color("viridis", df.loc[time]["tp"], 13.8, 14.5)
        ax.plot(xb, yb, color=color, linewidth=4, zorder=10)

    # Dpm
    ax = axs[2]
    p = ax.scatter(dset.lon, dset.lat, s=65, c=dset.sel(time=time).spec.dpm(), cmap="hsv", vmin=220, vmax=225)
    plt.colorbar(p, label="Dpm (deg)")
    for df in tpars:
        xb = [df.loc[time]["x0"], df.loc[time]["x1"]]
        yb = [df.loc[time]["y0"], df.loc[time]["y1"]]
        color = get_color("hsv", df.loc[time]["dpm"], 220, 225)
        ax.plot(xb, yb, color=color, linewidth=4, zorder=10)
    # ax.scatter(xb, yb, s=200, c=df.loc[time]["dpm"], marker=">", edgecolor="k", cmap="hsv", vmin=220, vmax=225)

    for ax in axs:
        grid.plot(ax=ax, fscale=5)
        ax.set_extent([110.5, 115.5, -29.5, -23.5])
        ax.set_title(time)
        ax.coastlines()

def read_tpar(tparfile): """Read SWAN TPAR files as a Dataframe.""" df = pd.read_csv( tparfile, sep=" ", header=None, skiprows=1, parse_dates=[0], date_format="%Y%m%d.%H%M%S", index_col=0, ) df.columns = ["hs", "tp", "dpm", "dspr"] return df def get_color(cmap, value, vmin, vmax): """Return the HEX color for a value in a colormap.""" cmap = matplotlib.cm.get_cmap(cmap) norm = colors.Normalize(vmin=vmin, vmax=vmax, clip=True) return colors.rgb2hex(cmap(norm(value))) def plot_boundary_side(dset, tpars, grid, time): """Plot side boundary stats. This function plots a snapshot of wave statistics from the source spectra dataset and the boundary wave stats generated for a grid from those spectra points. Parameters ---------- dset: xr.Dataset Source spectra dataset used to define the boundary. tpars: list[pd.DataFrame] Boundary time series defined from TPAR or SWAN ASCII file for each segment. grid: SwanGrid Grid object defining the SWAN domain. time: Datatime | str Time to plot. """ # xb, yb = bnd._boundary_points(grid) xb = grid.x[:, 0] yb = grid.y[:, 0] fig, axs = plt.subplots(1, 3, subplot_kw=dict(projection=ccrs.PlateCarree()), figsize=(15, 3.5)) # Hs ax = axs[0] p = ax.scatter(dset.lon, dset.lat, s=65, c=dset.sel(time=time).spec.hs(), cmap="turbo", vmin=2.0, vmax=3.5) plt.colorbar(p, label="Hs (m)") for df in tpars: xb = [df.loc[time]["x0"], df.loc[time]["x1"]] yb = [df.loc[time]["y0"], df.loc[time]["y1"]] color = get_color("turbo", df.loc[time]["hs"], 2.0, 3.5) ax.plot(xb, yb, color=color, linewidth=4, zorder=10) # Tp ax = axs[1] p = ax.scatter(dset.lon, dset.lat, s=65, c=dset.sel(time=time).spec.tp(), cmap="viridis", vmin=13.8, vmax=14.5) plt.colorbar(p, label="Tp (s)") for df in tpars: xb = [df.loc[time]["x0"], df.loc[time]["x1"]] yb = [df.loc[time]["y0"], df.loc[time]["y1"]] color = get_color("viridis", df.loc[time]["tp"], 13.8, 14.5) ax.plot(xb, yb, color=color, linewidth=4, zorder=10) # Dpm ax = axs[2] p = ax.scatter(dset.lon, dset.lat, s=65, c=dset.sel(time=time).spec.dpm(), cmap="hsv", vmin=220, vmax=225) plt.colorbar(p, label="Dpm (deg)") for df in tpars: xb = [df.loc[time]["x0"], df.loc[time]["x1"]] yb = [df.loc[time]["y0"], df.loc[time]["y1"]] color = get_color("hsv", df.loc[time]["dpm"], 220, 225) ax.plot(xb, yb, color=color, linewidth=4, zorder=10) # ax.scatter(xb, yb, s=200, c=df.loc[time]["dpm"], marker=">", edgecolor="k", cmap="hsv", vmin=220, vmax=225) for ax in axs: grid.plot(ax=ax, fscale=5) ax.set_extent([110.5, 115.5, -29.5, -23.5]) ax.set_title(time) ax.coastlines()

In [3]:

datadir = Path("../../../../rompy-swan/tests/data")
modeldir = Path("model")
modeldir.mkdir(exist_ok=True)

datadir = Path("../../../../rompy-swan/tests/data") modeldir = Path("model") modeldir.mkdir(exist_ok=True)

Define rompy objects¶

Create instances of source, time and grid objects to use with the boundary classes

In [4]:

# source defines the dataset to be used to create the model boundary

source = SourceFile(
    uri=datadir / "aus-20230101.nc",
    kwargs=dict(engine="netcdf4"),
)
dset = source.open()
dset

# source defines the dataset to be used to create the model boundary source = SourceFile( uri=datadir / "aus-20230101.nc", kwargs=dict(engine="netcdf4"), ) dset = source.open() dset

Out[4]:

<xarray.Dataset> Size: 1MB
Dimensions:  (site: 412, time: 5, freq: 11, dir: 8)
Coordinates:
  * time     (time) datetime64[ns] 40B 2023-01-01 ... 2023-01-02
  * site     (site) int64 3kB 0 4 8 12 16 20 ... 1624 1628 1632 1636 1640 1644
  * freq     (freq) float32 44B 0.05417 0.05959 0.06555 ... 0.1161 0.1277 0.1405
  * dir      (dir) float32 32B 0.0 45.0 90.0 135.0 180.0 225.0 270.0 315.0
Data variables:
    lon      (site) float32 2kB ...
    lat      (site) float32 2kB ...
    efth     (time, site, freq, dir) float64 1MB ...
    dpt      (time, site) float32 8kB ...
    wspd     (time, site) float32 8kB ...
    wdir     (time, site) float32 8kB ...
Attributes: (12/16)
    product_name:           ww3.all_spec.nc
    area:                   Global 0.5 x 0.5 degree
    data_type:              OCO spectra 2D
    format_version:         1.1
    southernmost_latitude:  n/a
    northernmost_latitude:  n/a
    ...                     ...
    minimum_altitude:       n/a
    maximum_altitude:       n/a
    altitude_resolution:    n/a
    start_date:             2023-01-01 00:00:00
    stop_date:              2023-02-01 00:00:00
    field_type:             3-hourly

xarray.Dataset

• Dimensions:
  • site: 412
  • time: 5
  • freq: 11
  • dir: 8
• Coordinates: (4)
  • time
    (time)
    datetime64[ns]
    2023-01-01 ... 2023-01-02

    standard_name :

    time

    array(['2023-01-01T00:00:00.000000000', '2023-01-01T06:00:00.000000000',
           '2023-01-01T12:00:00.000000000', '2023-01-01T18:00:00.000000000',
           '2023-01-02T00:00:00.000000000'], dtype='datetime64[ns]')

  • site
    (site)
    int64
    0 4 8 12 16 ... 1632 1636 1640 1644

    array([   0,    4,    8, ..., 1636, 1640, 1644], shape=(412,))

  • freq
    (freq)
    float32
    0.05417 0.05959 ... 0.1277 0.1405

    standard_name :

    sea_surface_wave_frequency

    units :

    Hz

    array([0.054172, 0.059589, 0.065548, 0.072103, 0.079313, 0.087244, 0.095968,
           0.105565, 0.116122, 0.127734, 0.140507], dtype=float32)

  • dir
    (dir)
    float32
    0.0 45.0 90.0 ... 225.0 270.0 315.0

    standard_name :

    sea_surface_wave_from_direction

    units :

    degree

    array([  0.,  45.,  90., 135., 180., 225., 270., 315.], dtype=float32)

• Data variables: (6)
  • lon
    (site)
    float32
    ...

    standard_name :

    longitude

    units :

    degrees_east

    [412 values with dtype=float32]

  • lat
    (site)
    float32
    ...

    standard_name :

    latitude

    units :

    degrees_north

    [412 values with dtype=float32]

  • efth
    (time, site, freq, dir)
    float64
    ...

    standard_name :

    sea_surface_wave_directional_variance_spectral_density

    units :

    m2 s degree-1

    [181280 values with dtype=float64]

  • dpt
    (time, site)
    float32
    ...

    standard_name :

    sea_floor_depth_below_sea_surface

    units :

    m

    [2060 values with dtype=float32]

  • wspd
    (time, site)
    float32
    ...

    standard_name :

    wind_speed_at_10m_above_ground_level

    units :

    m s-1

    [2060 values with dtype=float32]

  • wdir
    (time, site)
    float32
    ...

    standard_name :

    wind_from_direction_at_10m_above_ground_level

    units :

    degree

    [2060 values with dtype=float32]

• Indexes: (4)
  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2023-01-01 00:00:00', '2023-01-01 06:00:00',
                   '2023-01-01 12:00:00', '2023-01-01 18:00:00',
                   '2023-01-02 00:00:00'],
                  dtype='datetime64[ns]', name='time', freq=None))

  • site
    PandasIndex

    PandasIndex(Index([   0,    4,    8,   12,   16,   20,   24,   28,   32,   36,
           ...
           1608, 1612, 1616, 1620, 1624, 1628, 1632, 1636, 1640, 1644],
          dtype='int64', name='site', length=412))

  • freq
    PandasIndex

    PandasIndex(Index([0.05417170003056526, 0.05958886817097664, 0.06554775685071945,
           0.07210253179073334, 0.07931278645992279, 0.08724407106637955,
           0.09596847742795944, 0.10556533187627792, 0.11612186580896378,
           0.12773405015468597, 0.14050745964050293],
          dtype='float32', name='freq'))

  • dir
    PandasIndex

    PandasIndex(Index([0.0, 45.0, 90.0, 135.0, 180.0, 225.0, 270.0, 315.0], dtype='float32', name='dir'))

• Attributes: (16)

  product_name :

  ww3.all_spec.nc

  area :

  Global 0.5 x 0.5 degree

  data_type :

  OCO spectra 2D

  format_version :

  1.1

  southernmost_latitude :

  n/a

  northernmost_latitude :

  n/a

  latitude_resolution :

  n/a

  westernmost_longitude :

  n/a

  easternmost_longitude :

  n/a

  longitude_resolution :

  n/a

  minimum_altitude :

  n/a

  maximum_altitude :

  n/a

  altitude_resolution :

  n/a

  start_date :

  2023-01-01 00:00:00

  stop_date :

  2023-02-01 00:00:00

  field_type :

  3-hourly

In [5]:

# times prescribe the times over which the model will run

times = TimeRange(start="2023-01-01T00", end="2023-01-02T00", interval="6h")
print(times)

# times prescribe the times over which the model will run times = TimeRange(start="2023-01-01T00", end="2023-01-02T00", interval="6h") print(times)

	Start: 2023-01-01 00:00:00
	End: 2023-01-02 00:00:00
	Duration: 1 day
	Interval: 6:00:00
	Include End: True

In [6]:

# grid defines the model grid

grid = SwanGrid(x0=112, y0=-29, dx=0.5, dy=0.5, nx=8, ny=9, rot=20)
grid

# grid defines the model grid grid = SwanGrid(x0=112, y0=-29, dx=0.5, dy=0.5, nx=8, ny=9, rot=20) grid

Out[6]:

SwanGrid: REG, 8x9

In [7]:

# Plot model grid and boundary points in the source spectra

fig, ax = grid.plot(fscale=5)
ax.plot(dset.lon, dset.lat, "ok")
ax.set_extent([108, 120, -35.5, -19])

# Plot model grid and boundary points in the source spectra fig, ax = grid.plot(fscale=5) ax.plot(dset.lon, dset.lat, "ok") ax.set_extent([108, 120, -35.5, -19])

Boundary segment along one side¶

Create BOUNDSPEC SEGMENT type SWAN boundary with the points defined along one side of the computational grid.

The boundary is defined as TPAR files by interpolating from the source spectra dataset along the grid side. The Inverse Distance Weighting (idw) sel method from wavespectra will be used to interpolate from the source spectra at each boundary point.

In [8]:

workspace = Path(mkdtemp(dir="model"))

bnd = BoundspecSegmentXY(
    id="wa",
    source=source,
    sel_method="idw",
    sel_method_kwargs={"tolerance": 2.0},
    location=SIDE(side="west", direction="ccw"),
)

filenames, cmd = bnd.get(destdir=workspace, grid=grid, time=times)

display(cmd)
os.system(f"ls -l {workspace}");

workspace = Path(mkdtemp(dir="model")) bnd = BoundspecSegmentXY( id="wa", source=source, sel_method="idw", sel_method_kwargs={"tolerance": 2.0}, location=SIDE(side="west", direction="ccw"), ) filenames, cmd = bnd.get(destdir=workspace, grid=grid, time=times) display(cmd) os.system(f"ls -l {workspace}");

"BOUNDSPEC SEGMENT XY 110.63191943 -25.24122952 110.80292950 -25.71107583 CONSTANT FILE fname='wa_tpar_000.bnd' seq=1\nBOUNDSPEC SEGMENT XY 110.80292950 -25.71107583 110.97393957 -26.18092214 CONSTANT FILE fname='wa_tpar_001.bnd' seq=1\nBOUNDSPEC SEGMENT XY 110.97393957 -26.18092214 111.14494964 -26.65076845 CONSTANT FILE fname='wa_tpar_002.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.14494964 -26.65076845 111.31595971 -27.12061476 CONSTANT FILE fname='wa_tpar_003.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.31595971 -27.12061476 111.48696979 -27.59046107 CONSTANT FILE fname='wa_tpar_004.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.48696979 -27.59046107 111.65797986 -28.06030738 CONSTANT FILE fname='wa_tpar_005.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.65797986 -28.06030738 111.82898993 -28.53015369 CONSTANT FILE fname='wa_tpar_006.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.82898993 -28.53015369 112.00000000 -29.00000000 CONSTANT FILE fname='wa_tpar_007.bnd' seq=1"

total 32
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_000.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_001.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_002.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_003.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_004.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_005.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_006.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_007.bnd

In [9]:

tpars = []
for filename, cmdrow in zip(filenames, cmd.split("\n")):
    parts = cmdrow.split()
    df = read_tpar(filename)
    df["x0"] = float(parts[3].split("=")[-1])
    df["x1"] = float(parts[5].split("=")[-1])
    df["y0"] = float(parts[4].split("=")[-1])
    df["y1"] = float(parts[6].split("=")[-1])
    tpars.append(df)

with pd.option_context("display.max_columns", 999):
    display(df)

tpars = [] for filename, cmdrow in zip(filenames, cmd.split("\n")): parts = cmdrow.split() df = read_tpar(filename) df["x0"] = float(parts[3].split("=")[-1]) df["x1"] = float(parts[5].split("=")[-1]) df["y0"] = float(parts[4].split("=")[-1]) df["y1"] = float(parts[6].split("=")[-1]) tpars.append(df) with pd.option_context("display.max_columns", 999): display(df)

	hs	tp	dpm	dspr	x0	x1	y0	y1
0
2023-01-01 00:00:00	2.91	14.14	224.35	25.31	111.82899	112.0	-28.530154	-29.0
2023-01-01 06:00:00	2.99	14.11	224.08	26.31	111.82899	112.0	-28.530154	-29.0
2023-01-01 12:00:00	3.35	14.25	223.91	28.19	111.82899	112.0	-28.530154	-29.0
2023-01-01 18:00:00	3.62	14.31	224.13	29.76	111.82899	112.0	-28.530154	-29.0
2023-01-02 00:00:00	3.59	14.18	224.47	30.52	111.82899	112.0	-28.530154	-29.0

Plot boundary stats, note the values weighted by the four nearest neighbours at each site along the WEST boundary

In [10]:

for time in df.index[::2]:
    plot_boundary_side(dset, tpars, grid, time)

for time in df.index[::2]: plot_boundary_side(dset, tpars, grid, time)

Boundary segment along multiple sides¶

Create BOUNDSPEC SEGMENT type SWAN boundary with the points defined along multiple, contiguous sides of the computational grid.

The boundary is defined as TPAR files by selecting from the nearest points in the source spectra dataset along the sides at the resolution defined by the spacing parameter which by default corresponds to the grid spacing itself (use "parent" to define the spacing based on spacing of points in the source spectra dataset, or set a custom spacing if desired).

⚠️ When using SIDES, the order at which each side is provided matters. Ensure the order and direction of each side are such that segments defined by each pair of points will all be contiguous.

In [11]:

workspace = Path(mkdtemp(dir="model"))

bnd = BoundspecSegmentXY(
    id="wa",
    source=source,
    sel_method="nearest",
    sel_method_kwargs={"tolerance": 2.0},
    location=SIDES(
        sides=[
            SIDE(side="south", direction="clockwise"),
            SIDE(side="west", direction="clockwise"),
            SIDE(side="north", direction="clockwise"),
        ],
    ),
)

filenames, cmd = bnd.get(destdir=workspace, grid=grid, time=times)

display(cmd)
os.system(f"ls -l {workspace}");

workspace = Path(mkdtemp(dir="model")) bnd = BoundspecSegmentXY( id="wa", source=source, sel_method="nearest", sel_method_kwargs={"tolerance": 2.0}, location=SIDES( sides=[ SIDE(side="south", direction="clockwise"), SIDE(side="west", direction="clockwise"), SIDE(side="north", direction="clockwise"), ], ), ) filenames, cmd = bnd.get(destdir=workspace, grid=grid, time=times) display(cmd) os.system(f"ls -l {workspace}");

"BOUNDSPEC SEGMENT XY 115.28892417 -27.80292950 114.81907786 -27.97393957 CONSTANT FILE fname='wa_tpar_000.bnd' seq=1\nBOUNDSPEC SEGMENT XY 114.81907786 -27.97393957 114.34923155 -28.14494964 CONSTANT FILE fname='wa_tpar_001.bnd' seq=1\nBOUNDSPEC SEGMENT XY 114.34923155 -28.14494964 113.87938524 -28.31595971 CONSTANT FILE fname='wa_tpar_002.bnd' seq=1\nBOUNDSPEC SEGMENT XY 113.87938524 -28.31595971 113.40953893 -28.48696979 CONSTANT FILE fname='wa_tpar_003.bnd' seq=1\nBOUNDSPEC SEGMENT XY 113.40953893 -28.48696979 112.93969262 -28.65797986 CONSTANT FILE fname='wa_tpar_004.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.93969262 -28.65797986 112.46984631 -28.82898993 CONSTANT FILE fname='wa_tpar_005.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.46984631 -28.82898993 112.00000000 -29.00000000 CONSTANT FILE fname='wa_tpar_006.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.00000000 -29.00000000 111.82898993 -28.53015369 CONSTANT FILE fname='wa_tpar_007.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.82898993 -28.53015369 111.65797986 -28.06030738 CONSTANT FILE fname='wa_tpar_008.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.65797986 -28.06030738 111.48696979 -27.59046107 CONSTANT FILE fname='wa_tpar_009.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.48696979 -27.59046107 111.31595971 -27.12061476 CONSTANT FILE fname='wa_tpar_010.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.31595971 -27.12061476 111.14494964 -26.65076845 CONSTANT FILE fname='wa_tpar_011.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.14494964 -26.65076845 110.97393957 -26.18092214 CONSTANT FILE fname='wa_tpar_012.bnd' seq=1\nBOUNDSPEC SEGMENT XY 110.97393957 -26.18092214 110.80292950 -25.71107583 CONSTANT FILE fname='wa_tpar_013.bnd' seq=1\nBOUNDSPEC SEGMENT XY 110.80292950 -25.71107583 110.63191943 -25.24122952 CONSTANT FILE fname='wa_tpar_014.bnd' seq=1\nBOUNDSPEC SEGMENT XY 110.63191943 -25.24122952 111.10176574 -25.07021945 CONSTANT FILE fname='wa_tpar_015.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.10176574 -25.07021945 111.57161205 -24.89920937 CONSTANT FILE fname='wa_tpar_016.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.57161205 -24.89920937 112.04145836 -24.72819930 CONSTANT FILE fname='wa_tpar_017.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.04145836 -24.72819930 112.51130467 -24.55718923 CONSTANT FILE fname='wa_tpar_018.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.51130467 -24.55718923 112.98115098 -24.38617916 CONSTANT FILE fname='wa_tpar_019.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.98115098 -24.38617916 113.45099729 -24.21516909 CONSTANT FILE fname='wa_tpar_020.bnd' seq=1\nBOUNDSPEC SEGMENT XY 113.45099729 -24.21516909 113.92084360 -24.04415902 CONSTANT FILE fname='wa_tpar_021.bnd' seq=1"

total 88
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_000.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_001.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_002.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_003.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_004.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_005.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_006.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_007.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_008.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_009.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_010.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_011.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_012.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_013.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_014.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_015.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_016.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_017.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_018.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_019.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_020.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_021.bnd

In [12]:

# Load boundaries for each segment into dataframes

tpars = []
for filename, row in zip(filenames, cmd.split("\n")):
    parts = row.split()
    df = read_tpar(filename)
    df["x0"] = float(parts[3].split("=")[-1])
    df["x1"] = float(parts[5].split("=")[-1])
    df["y0"] = float(parts[4].split("=")[-1])
    df["y1"] = float(parts[6].split("=")[-1])
    tpars.append(df)

with pd.option_context("display.max_columns", 999):
    display(df)

# Load boundaries for each segment into dataframes tpars = [] for filename, row in zip(filenames, cmd.split("\n")): parts = row.split() df = read_tpar(filename) df["x0"] = float(parts[3].split("=")[-1]) df["x1"] = float(parts[5].split("=")[-1]) df["y0"] = float(parts[4].split("=")[-1]) df["y1"] = float(parts[6].split("=")[-1]) tpars.append(df) with pd.option_context("display.max_columns", 999): display(df)

	hs	tp	dpm	dspr	x0	x1	y0	y1
0
2023-01-01 00:00:00	1.31	14.08	241.64	20.66	113.450997	113.920844	-24.215169	-24.044159
2023-01-01 06:00:00	1.31	13.89	241.93	21.96	113.450997	113.920844	-24.215169	-24.044159
2023-01-01 12:00:00	1.37	13.93	242.71	22.38	113.450997	113.920844	-24.215169	-24.044159
2023-01-01 18:00:00	1.43	14.17	243.00	21.91	113.450997	113.920844	-24.215169	-24.044159
2023-01-02 00:00:00	1.56	14.33	243.23	21.32	113.450997	113.920844	-24.215169	-24.044159

In [13]:

# Plot boundary stats

for time in df.index[::2]:
    plot_boundary_side(dset, tpars, grid, time)

# Plot boundary stats for time in df.index[::2]: plot_boundary_side(dset, tpars, grid, time)

Boundary segment along multiple sides with custom spacing¶

Use a custom spacing of 1.0 degree to set the segment sizes. Notice the last segment is adjsted to ensure the grid length is respected.

⚠️ In this example, sides are specified in the opposite order north-west-south with an appropriate direction `ccw` that ensures contiguous segments.

In [14]:

workspace = Path(mkdtemp(dir="model"))

bnd = BoundspecSegmentXY(
    id="wa",
    source=source,
    sel_method="nearest",
    sel_method_kwargs={"tolerance": 2.0},
    spacing=1.0,
    location=SIDES(
        sides=[
            SIDE(side="north", direction="ccw"),
            SIDE(side="west", direction="ccw"),
            SIDE(side="south", direction="ccw"),
        ],
    ),
)

filenames, cmd = bnd.get(destdir=workspace, grid=grid, time=times)

display(cmd)
os.system(f"ls -l {workspace}");

workspace = Path(mkdtemp(dir="model")) bnd = BoundspecSegmentXY( id="wa", source=source, sel_method="nearest", sel_method_kwargs={"tolerance": 2.0}, spacing=1.0, location=SIDES( sides=[ SIDE(side="north", direction="ccw"), SIDE(side="west", direction="ccw"), SIDE(side="south", direction="ccw"), ], ), ) filenames, cmd = bnd.get(destdir=workspace, grid=grid, time=times) display(cmd) os.system(f"ls -l {workspace}");

"BOUNDSPEC SEGMENT XY 113.92084360 -24.04415902 112.98115098 -24.38617916 CONSTANT FILE fname='wa_tpar_000.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.98115098 -24.38617916 112.04145836 -24.72819930 CONSTANT FILE fname='wa_tpar_001.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.04145836 -24.72819930 111.10176574 -25.07021945 CONSTANT FILE fname='wa_tpar_002.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.10176574 -25.07021945 110.63191943 -25.24122952 CONSTANT FILE fname='wa_tpar_003.bnd' seq=1\nBOUNDSPEC SEGMENT XY 110.63191943 -25.24122952 110.97393957 -26.18092214 CONSTANT FILE fname='wa_tpar_004.bnd' seq=1\nBOUNDSPEC SEGMENT XY 110.97393957 -26.18092214 111.31595971 -27.12061476 CONSTANT FILE fname='wa_tpar_005.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.31595971 -27.12061476 111.65797986 -28.06030738 CONSTANT FILE fname='wa_tpar_006.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.65797986 -28.06030738 112.00000000 -29.00000000 CONSTANT FILE fname='wa_tpar_007.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.00000000 -29.00000000 112.00000000 -29.00000000 CONSTANT FILE fname='wa_tpar_008.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.00000000 -29.00000000 112.93969262 -28.65797986 CONSTANT FILE fname='wa_tpar_009.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.93969262 -28.65797986 113.87938524 -28.31595971 CONSTANT FILE fname='wa_tpar_010.bnd' seq=1\nBOUNDSPEC SEGMENT XY 113.87938524 -28.31595971 114.81907786 -27.97393957 CONSTANT FILE fname='wa_tpar_011.bnd' seq=1\nBOUNDSPEC SEGMENT XY 114.81907786 -27.97393957 115.28892417 -27.80292950 CONSTANT FILE fname='wa_tpar_012.bnd' seq=1"

total 52
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_000.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_001.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_002.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_003.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_004.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_005.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_006.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_007.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_008.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_009.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_010.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_011.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_012.bnd

In [15]:

# Load boundaries for each segment and plot boundary stats

tpars = []
for filename, row in zip(filenames, cmd.split("\n")):
    parts = row.split()
    df = read_tpar(filename)
    df["x0"] = float(parts[3].split("=")[-1])
    df["x1"] = float(parts[5].split("=")[-1])
    df["y0"] = float(parts[4].split("=")[-1])
    df["y1"] = float(parts[6].split("=")[-1])
    tpars.append(df)

with pd.option_context("display.max_columns", 999):
    display(df)

for time in df.index[::2]:
    plot_boundary_side(dset, tpars, grid, time)

# Load boundaries for each segment and plot boundary stats tpars = [] for filename, row in zip(filenames, cmd.split("\n")): parts = row.split() df = read_tpar(filename) df["x0"] = float(parts[3].split("=")[-1]) df["x1"] = float(parts[5].split("=")[-1]) df["y0"] = float(parts[4].split("=")[-1]) df["y1"] = float(parts[6].split("=")[-1]) tpars.append(df) with pd.option_context("display.max_columns", 999): display(df) for time in df.index[::2]: plot_boundary_side(dset, tpars, grid, time)

	hs	tp	dpm	dspr	x0	x1	y0	y1
0
2023-01-01 00:00:00	1.94	13.82	225.0	14.52	114.819078	115.288924	-27.97394	-27.80293
2023-01-01 06:00:00	1.95	14.09	225.0	14.38	114.819078	115.288924	-27.97394	-27.80293
2023-01-01 12:00:00	2.34	14.06	225.0	18.83	114.819078	115.288924	-27.97394	-27.80293
2023-01-01 18:00:00	2.22	13.91	225.0	16.48	114.819078	115.288924	-27.97394	-27.80293
2023-01-02 00:00:00	2.05	13.85	225.0	13.39	114.819078	115.288924	-27.97394	-27.80293

Boundary segment along multiple sides with parent spacing¶

Set spacing from the minimum distance between spectral points in the source dataset.

In [16]:

workspace = Path(mkdtemp(dir="model"))

bnd = BoundspecSegmentXY(
    id="wa",
    source=source,
    sel_method="nearest",
    sel_method_kwargs={"tolerance": 2.0},
    spacing="parent",
    location=SIDES(
        sides=[
            SIDE(side="north", direction="ccw"),
            SIDE(side="west", direction="ccw"),
            SIDE(side="south", direction="ccw"),
        ],
    ),
)

filenames, cmd = bnd.get(destdir=workspace, grid=grid, time=times)

display(cmd)
os.system(f"ls -l {workspace}");

workspace = Path(mkdtemp(dir="model")) bnd = BoundspecSegmentXY( id="wa", source=source, sel_method="nearest", sel_method_kwargs={"tolerance": 2.0}, spacing="parent", location=SIDES( sides=[ SIDE(side="north", direction="ccw"), SIDE(side="west", direction="ccw"), SIDE(side="south", direction="ccw"), ], ), ) filenames, cmd = bnd.get(destdir=workspace, grid=grid, time=times) display(cmd) os.system(f"ls -l {workspace}");

"BOUNDSPEC SEGMENT XY 113.92084360 -24.04415902 113.25638059 -24.28600377 CONSTANT FILE fname='wa_tpar_000.bnd' seq=1\nBOUNDSPEC SEGMENT XY 113.25638059 -24.28600377 112.59191757 -24.52784853 CONSTANT FILE fname='wa_tpar_001.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.59191757 -24.52784853 111.92745462 -24.76969327 CONSTANT FILE fname='wa_tpar_002.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.92745462 -24.76969327 111.26299155 -25.01153805 CONSTANT FILE fname='wa_tpar_003.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.26299155 -25.01153805 110.63191943 -25.24122952 CONSTANT FILE fname='wa_tpar_004.bnd' seq=1\nBOUNDSPEC SEGMENT XY 110.63191943 -25.24122952 110.87376419 -25.90569253 CONSTANT FILE fname='wa_tpar_005.bnd' seq=1\nBOUNDSPEC SEGMENT XY 110.87376419 -25.90569253 111.11560894 -26.57015554 CONSTANT FILE fname='wa_tpar_006.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.11560894 -26.57015554 111.35745368 -27.23461850 CONSTANT FILE fname='wa_tpar_007.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.35745368 -27.23461850 111.59929846 -27.89908157 CONSTANT FILE fname='wa_tpar_008.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.59929846 -27.89908157 111.84114324 -28.56354464 CONSTANT FILE fname='wa_tpar_009.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.84114324 -28.56354464 112.00000000 -29.00000000 CONSTANT FILE fname='wa_tpar_010.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.00000000 -29.00000000 112.66446301 -28.75815524 CONSTANT FILE fname='wa_tpar_011.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.66446301 -28.75815524 113.32892603 -28.51631048 CONSTANT FILE fname='wa_tpar_012.bnd' seq=1\nBOUNDSPEC SEGMENT XY 113.32892603 -28.51631048 113.99338898 -28.27446574 CONSTANT FILE fname='wa_tpar_013.bnd' seq=1\nBOUNDSPEC SEGMENT XY 113.99338898 -28.27446574 114.65785205 -28.03262097 CONSTANT FILE fname='wa_tpar_014.bnd' seq=1\nBOUNDSPEC SEGMENT XY 114.65785205 -28.03262097 115.28892417 -27.80292950 CONSTANT FILE fname='wa_tpar_015.bnd' seq=1"

total 64
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_000.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_001.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_002.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_003.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_004.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_005.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_006.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_007.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_008.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_009.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_010.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_011.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_012.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_013.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_014.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_015.bnd

In [17]:

# Load boundaries for each segment and plot boundary stats

tpars = []
for filename, row in zip(filenames, cmd.split("\n")):
    parts = row.split()
    df = read_tpar(filename)
    df["x0"] = float(parts[3].split("=")[-1])
    df["x1"] = float(parts[5].split("=")[-1])
    df["y0"] = float(parts[4].split("=")[-1])
    df["y1"] = float(parts[6].split("=")[-1])
    tpars.append(df)

with pd.option_context("display.max_columns", 999):
    display(df)

for time in df.index[::2]:
    plot_boundary_side(dset, tpars, grid, time)

# Load boundaries for each segment and plot boundary stats tpars = [] for filename, row in zip(filenames, cmd.split("\n")): parts = row.split() df = read_tpar(filename) df["x0"] = float(parts[3].split("=")[-1]) df["x1"] = float(parts[5].split("=")[-1]) df["y0"] = float(parts[4].split("=")[-1]) df["y1"] = float(parts[6].split("=")[-1]) tpars.append(df) with pd.option_context("display.max_columns", 999): display(df) for time in df.index[::2]: plot_boundary_side(dset, tpars, grid, time)

	hs	tp	dpm	dspr	x0	x1	y0	y1
0
2023-01-01 00:00:00	1.94	13.82	225.0	14.52	114.657852	115.288924	-28.032621	-27.80293
2023-01-01 06:00:00	1.95	14.09	225.0	14.38	114.657852	115.288924	-28.032621	-27.80293
2023-01-01 12:00:00	2.34	14.06	225.0	18.83	114.657852	115.288924	-28.032621	-27.80293
2023-01-01 18:00:00	2.22	13.91	225.0	16.48	114.657852	115.288924	-28.032621	-27.80293
2023-01-02 00:00:00	2.05	13.85	225.0	13.39	114.657852	115.288924	-28.032621	-27.80293

User-specified boundary points¶

Users are free to set segments explicitly using the XY type

In [18]:

workspace = Path(mkdtemp(dir="model"))

# Define the grid vertices as boundary points
xb, yb = grid.boundary_points()
for point in zip(xb, yb):
    print(point)

bnd = BoundspecSegmentXY(
    id="wa",
    source=source,
    sel_method="idw",
    sel_method_kwargs={"tolerance": 2.0},
    location=XY(x=xb, y=yb)
)

filenames, cmd = bnd.get(destdir=workspace, grid=grid, time=times)

display(cmd)
os.system(f"ls -l {workspace}");

workspace = Path(mkdtemp(dir="model")) # Define the grid vertices as boundary points xb, yb = grid.boundary_points() for point in zip(xb, yb): print(point) bnd = BoundspecSegmentXY( id="wa", source=source, sel_method="idw", sel_method_kwargs={"tolerance": 2.0}, location=XY(x=xb, y=yb) ) filenames, cmd = bnd.get(destdir=workspace, grid=grid, time=times) display(cmd) os.system(f"ls -l {workspace}");

(np.float64(112.0), np.float64(-29.0))
(np.float64(112.46984631039295), np.float64(-28.828989928337165))
(np.float64(112.9396926207859), np.float64(-28.65797985667433))
(np.float64(113.40953893117886), np.float64(-28.486969785011496))
(np.float64(113.87938524157181), np.float64(-28.31595971334866))
(np.float64(114.34923155196478), np.float64(-28.144949641685827))
(np.float64(114.81907786235773), np.float64(-27.973939570022992))
(np.float64(115.28892417275068), np.float64(-27.80292949836016))
(np.float64(115.11791410108785), np.float64(-27.333083187967205))
(np.float64(114.94690402942501), np.float64(-26.863236877574252))
(np.float64(114.77589395776218), np.float64(-26.393390567181296))
(np.float64(114.60488388609934), np.float64(-25.923544256788343))
(np.float64(114.43387381443651), np.float64(-25.453697946395387))
(np.float64(114.26286374277367), np.float64(-24.983851636002434))
(np.float64(114.09185367111084), np.float64(-24.51400532560948))
(np.float64(113.920843599448), np.float64(-24.044159015216525))
(np.float64(113.45099728905505), np.float64(-24.21516908687936))
(np.float64(112.9811509786621), np.float64(-24.386179158542195))
(np.float64(112.51130466826915), np.float64(-24.55718923020503))
(np.float64(112.0414583578762), np.float64(-24.728199301867864))
(np.float64(111.57161204748323), np.float64(-24.8992093735307))
(np.float64(111.10176573709028), np.float64(-25.070219445193533))
(np.float64(110.63191942669732), np.float64(-25.241229516856365))
(np.float64(110.80292949836016), np.float64(-25.71107582724932))
(np.float64(110.97393957002299), np.float64(-26.180922137642273))
(np.float64(111.14494964168583), np.float64(-26.65076844803523))
(np.float64(111.31595971334866), np.float64(-27.120614758428182))
(np.float64(111.4869697850115), np.float64(-27.59046106882114))
(np.float64(111.65797985667433), np.float64(-28.06030737921409))
(np.float64(111.82898992833717), np.float64(-28.530153689607047))
(np.float64(112.0), np.float64(-29.0))

"BOUNDSPEC SEGMENT XY 112.00000000 -29.00000000 112.46984631 -28.82898993 CONSTANT FILE fname='wa_tpar_000.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.46984631 -28.82898993 112.93969262 -28.65797986 CONSTANT FILE fname='wa_tpar_001.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.93969262 -28.65797986 113.40953893 -28.48696979 CONSTANT FILE fname='wa_tpar_002.bnd' seq=1\nBOUNDSPEC SEGMENT XY 113.40953893 -28.48696979 113.87938524 -28.31595971 CONSTANT FILE fname='wa_tpar_003.bnd' seq=1\nBOUNDSPEC SEGMENT XY 113.87938524 -28.31595971 114.34923155 -28.14494964 CONSTANT FILE fname='wa_tpar_004.bnd' seq=1\nBOUNDSPEC SEGMENT XY 114.34923155 -28.14494964 114.81907786 -27.97393957 CONSTANT FILE fname='wa_tpar_005.bnd' seq=1\nBOUNDSPEC SEGMENT XY 114.81907786 -27.97393957 115.28892417 -27.80292950 CONSTANT FILE fname='wa_tpar_006.bnd' seq=1\nBOUNDSPEC SEGMENT XY 115.28892417 -27.80292950 115.11791410 -27.33308319 CONSTANT FILE fname='wa_tpar_007.bnd' seq=1\nBOUNDSPEC SEGMENT XY 115.11791410 -27.33308319 114.94690403 -26.86323688 CONSTANT FILE fname='wa_tpar_008.bnd' seq=1\nBOUNDSPEC SEGMENT XY 114.94690403 -26.86323688 114.77589396 -26.39339057 CONSTANT FILE fname='wa_tpar_009.bnd' seq=1\nBOUNDSPEC SEGMENT XY 114.77589396 -26.39339057 114.60488389 -25.92354426 CONSTANT FILE fname='wa_tpar_010.bnd' seq=1\nBOUNDSPEC SEGMENT XY 114.60488389 -25.92354426 114.43387381 -25.45369795 CONSTANT FILE fname='wa_tpar_011.bnd' seq=1\nBOUNDSPEC SEGMENT XY 114.43387381 -25.45369795 114.26286374 -24.98385164 CONSTANT FILE fname='wa_tpar_012.bnd' seq=1\nBOUNDSPEC SEGMENT XY 114.26286374 -24.98385164 114.09185367 -24.51400533 CONSTANT FILE fname='wa_tpar_013.bnd' seq=1\nBOUNDSPEC SEGMENT XY 114.09185367 -24.51400533 113.92084360 -24.04415902 CONSTANT FILE fname='wa_tpar_014.bnd' seq=1\nBOUNDSPEC SEGMENT XY 113.92084360 -24.04415902 113.45099729 -24.21516909 CONSTANT FILE fname='wa_tpar_015.bnd' seq=1\nBOUNDSPEC SEGMENT XY 113.45099729 -24.21516909 112.98115098 -24.38617916 CONSTANT FILE fname='wa_tpar_016.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.98115098 -24.38617916 112.51130467 -24.55718923 CONSTANT FILE fname='wa_tpar_017.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.51130467 -24.55718923 112.04145836 -24.72819930 CONSTANT FILE fname='wa_tpar_018.bnd' seq=1\nBOUNDSPEC SEGMENT XY 112.04145836 -24.72819930 111.57161205 -24.89920937 CONSTANT FILE fname='wa_tpar_019.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.57161205 -24.89920937 111.10176574 -25.07021945 CONSTANT FILE fname='wa_tpar_020.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.10176574 -25.07021945 110.63191943 -25.24122952 CONSTANT FILE fname='wa_tpar_021.bnd' seq=1\nBOUNDSPEC SEGMENT XY 110.63191943 -25.24122952 110.80292950 -25.71107583 CONSTANT FILE fname='wa_tpar_022.bnd' seq=1\nBOUNDSPEC SEGMENT XY 110.80292950 -25.71107583 110.97393957 -26.18092214 CONSTANT FILE fname='wa_tpar_023.bnd' seq=1\nBOUNDSPEC SEGMENT XY 110.97393957 -26.18092214 111.14494964 -26.65076845 CONSTANT FILE fname='wa_tpar_024.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.14494964 -26.65076845 111.31595971 -27.12061476 CONSTANT FILE fname='wa_tpar_025.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.31595971 -27.12061476 111.48696979 -27.59046107 CONSTANT FILE fname='wa_tpar_026.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.48696979 -27.59046107 111.65797986 -28.06030738 CONSTANT FILE fname='wa_tpar_027.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.65797986 -28.06030738 111.82898993 -28.53015369 CONSTANT FILE fname='wa_tpar_028.bnd' seq=1\nBOUNDSPEC SEGMENT XY 111.82898993 -28.53015369 112.00000000 -29.00000000 CONSTANT FILE fname='wa_tpar_029.bnd' seq=1"

total 120
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_000.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_001.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_002.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_003.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_004.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_005.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_006.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_007.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_008.bnd
-rw-rw-r-- 1 rguedes rguedes 170 Sep 18 21:43 wa_tpar_009.bnd
-rw-rw-r-- 1 rguedes rguedes 170 Sep 18 21:43 wa_tpar_010.bnd
-rw-rw-r-- 1 rguedes rguedes 170 Sep 18 21:43 wa_tpar_011.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_012.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_013.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_014.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_015.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_016.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_017.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_018.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_019.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_020.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_021.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_022.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_023.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_024.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_025.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_026.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_027.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_028.bnd
-rw-rw-r-- 1 rguedes rguedes 205 Sep 18 21:43 wa_tpar_029.bnd

In [19]:

# Load boundaries for each segment and plot boundary stats

tpars = []
for filename, row in zip(filenames, cmd.split("\n")):
    parts = row.split()
    df = read_tpar(filename)
    df["x0"] = float(parts[3].split("=")[-1])
    df["x1"] = float(parts[5].split("=")[-1])
    df["y0"] = float(parts[4].split("=")[-1])
    df["y1"] = float(parts[6].split("=")[-1])
    tpars.append(df)

# Display the contents of one of the TPAR files
with pd.option_context("display.max_columns", 999):
    display(df)

# Plot source and boundary stats
for time in df.index[::2]:
    plot_boundary_side(dset, tpars, grid, time)

# Load boundaries for each segment and plot boundary stats tpars = [] for filename, row in zip(filenames, cmd.split("\n")): parts = row.split() df = read_tpar(filename) df["x0"] = float(parts[3].split("=")[-1]) df["x1"] = float(parts[5].split("=")[-1]) df["y0"] = float(parts[4].split("=")[-1]) df["y1"] = float(parts[6].split("=")[-1]) tpars.append(df) # Display the contents of one of the TPAR files with pd.option_context("display.max_columns", 999): display(df) # Plot source and boundary stats for time in df.index[::2]: plot_boundary_side(dset, tpars, grid, time)

	hs	tp	dpm	dspr	x0	x1	y0	y1
0
2023-01-01 00:00:00	2.91	14.14	224.35	25.31	111.82899	112.0	-28.530154	-29.0
2023-01-01 06:00:00	2.99	14.11	224.08	26.31	111.82899	112.0	-28.530154	-29.0
2023-01-01 12:00:00	3.35	14.25	223.91	28.19	111.82899	112.0	-28.530154	-29.0
2023-01-01 18:00:00	3.62	14.31	224.13	29.76	111.82899	112.0	-28.530154	-29.0
2023-01-02 00:00:00	3.59	14.18	224.47	30.52	111.82899	112.0	-28.530154	-29.0