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%load_ext autoreload
%autoreload 2
%load_ext autoreload
%autoreload 2
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import warnings
warnings.filterwarnings("ignore")
import warnings
warnings.filterwarnings("ignore")
XBeach sourceĀ¶
Source objects in rompy-xbeach are an extension of the core sources
available in rompy with support to coordinate reference system (CRS): the ._open() method must return an
xarray Dataset object with the rio accessor available and the crs attribute set.
Three modified source objects are available in rompy-xbeach, SourceCRSFile, SourceCRSIntake and SourceCRSDataset.
They are similar to their core counterparts but requite a CRS field to be provided.
SourceCRSFileĀ¶
Can be used with any file format on disk supported by xarray
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from rompy_xbeach.source import SourceCRSFile
# Assumes rompy-xbeach is cloned in the same parent directory as rompy-notebooks
source = SourceCRSFile(
uri="../../../rompy-xbeach/tests/data/bathy.nc",
kwargs=dict(engine="netcdf"),
crs="EPSG:4326",
x_dim="x",
y_dim="y",
)
ds = source._open()
ds
from rompy_xbeach.source import SourceCRSFile
# Assumes rompy-xbeach is cloned in the same parent directory as rompy-notebooks
source = SourceCRSFile(
uri="../../../rompy-xbeach/tests/data/bathy.nc",
kwargs=dict(engine="netcdf"),
crs="EPSG:4326",
x_dim="x",
y_dim="y",
)
ds = source._open()
ds
Out[3]:
<xarray.Dataset> Size: 130kB
Dimensions: (y: 180, x: 176)
Coordinates:
* x (x) float64 1kB 115.6 115.6 115.6 115.6 ... 115.6 115.6 115.6 115.6
* y (y) float64 1kB -32.65 -32.65 -32.65 ... -32.61 -32.61 -32.61
Data variables:
depth (y, x) float32 127kB ...InĀ [4]:
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ds.rio.crs
ds.rio.crs
SourceCRSIntakeĀ¶
Intake based source with CRS support
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from rompy_xbeach.source import SourceCRSIntake
source = SourceCRSIntake(
catalog_uri="../../../rompy-xbeach/tests/data/catalog.yaml",
dataset_id="bathy_netcdf",
crs="EPSG:4326",
)
from rompy_xbeach.source import SourceCRSIntake
source = SourceCRSIntake(
catalog_uri="../../../rompy-xbeach/tests/data/catalog.yaml",
dataset_id="bathy_netcdf",
crs="EPSG:4326",
)
SourceCRSDatasetĀ¶
Allow using an existing xarray object
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from rompy_xbeach.source import SourceCRSDataset
source = SourceCRSDataset(obj=ds, crs="EPSG:4326")
from rompy_xbeach.source import SourceCRSDataset
source = SourceCRSDataset(obj=ds, crs="EPSG:4326")
SourceGeotiffĀ¶
Geotiff files have typically have the CRS information available, a special Source is available to easily use these files
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from rompy_xbeach.source import SourceGeotiff
source = SourceGeotiff(filename="../../../rompy-xbeach/tests/data/bathy.tif")
source
from rompy_xbeach.source import SourceGeotiff
source = SourceGeotiff(filename="../../../rompy-xbeach/tests/data/bathy.tif")
source
Out[7]:
SourceGeotiff(model_type='geotiff', filename='../../../rompy-xbeach/tests/data/bathy.tif', band=1, kwargs={})
SourceXYZĀ¶
Define a source from XYZ, point-cloud file. Parameters for opening the file with pandas and to interpolate into a regular grid with scipy can be prescribed in this source
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from rompy_xbeach.source import SourceXYZ
source = SourceXYZ(
filename="../../../rompy-xbeach/tests/data/bathy_xyz.zip",
res=0.0005,
read_csv_kwargs=dict(sep="\t"),
griddata_kwargs=dict(method="linear"),
xcol="easting",
ycol="northing",
zcol="elevation",
crs="EPSG:4326",
)
source
from rompy_xbeach.source import SourceXYZ
source = SourceXYZ(
filename="../../../rompy-xbeach/tests/data/bathy_xyz.zip",
res=0.0005,
read_csv_kwargs=dict(sep="\t"),
griddata_kwargs=dict(method="linear"),
xcol="easting",
ycol="northing",
zcol="elevation",
crs="EPSG:4326",
)
source
Out[8]:
SourceXYZ(model_type='xyz', filename='../../../rompy-xbeach/tests/data/bathy_xyz.zip', crs='EPSG:4326', res=0.0005, xcol='easting', ycol='northing', zcol='elevation', read_csv_kwargs={'sep': '\t'}, griddata_kwargs={'method': 'linear'})
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ds = source._open()
ds
ds = source._open()
ds
2025-10-02 18:24:53 [INFO] rompy_xbeach.source : Interpolating onto a grid of shape (78, 76)
Out[9]:
<xarray.Dataset> Size: 49kB
Dimensions: (y: 78, x: 76)
Coordinates:
* y (y) float64 624B -32.65 -32.65 -32.65 ... -32.61 -32.61 -32.61
* x (x) float64 608B 115.6 115.6 115.6 115.6 ... 115.6 115.6 115.6
spatial_ref int64 8B 0
Data variables:
data (y, x) float64 47kB -13.21 -13.19 -13.28 -13.17 ... nan nan nanInĀ [10]:
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ds.data.plot()
ds.data.plot()
Out[10]:
<matplotlib.collections.QuadMesh at 0x7774b00d3e30>
