rompy.swan.boundary.Boundnest1#
- pydantic model rompy.swan.boundary.Boundnest1[source]#
SWAN BOUNDNEST1 NEST data class.
Show JSON schema
{ "title": "Boundnest1", "description": "SWAN BOUNDNEST1 NEST data class.", "type": "object", "properties": { "model_type": { "default": "boundnest1", "description": "Model type discriminator", "enum": [ "boundnest1", "BOUNDNEST1" ], "title": "Model Type", "type": "string" }, "id": { "description": "Unique identifier for this data source", "title": "Id", "type": "string" }, "source": { "description": "Dataset source reader, must return a wavespectra-enabled xarray dataset in the open method", "discriminator": { "mapping": { "csv": "#/$defs/SourceTimeseriesCSV", "datamesh": "#/$defs/SourceDatamesh", "file": "#/$defs/SourceFile", "intake": "#/$defs/SourceIntake", "wavespectra": "#/$defs/SourceWavespectra" }, "propertyName": "model_type" }, "oneOf": [ { "$ref": "#/$defs/SourceTimeseriesCSV" }, { "$ref": "#/$defs/SourceDatamesh" }, { "$ref": "#/$defs/SourceFile" }, { "$ref": "#/$defs/SourceIntake" }, { "$ref": "#/$defs/SourceWavespectra" } ], "title": "Source" }, "link": { "default": false, "description": "Whether to create a symbolic link instead of copying the file", "title": "Link", "type": "boolean" }, "filter": { "anyOf": [ { "$ref": "#/$defs/Filter" }, { "type": "null" } ], "description": "Optional filter specification to apply to the dataset" }, "variables": { "anyOf": [ { "items": { "type": "string" }, "type": "array" }, { "type": "null" } ], "default": [], "description": "Subset of variables to extract from the dataset", "title": "Variables" }, "coords": { "anyOf": [ { "$ref": "#/$defs/DatasetCoords" }, { "type": "null" } ], "default": { "t": "time", "x": "longitude", "y": "latitude", "z": "depth", "s": "site" }, "description": "Names of the coordinates in the dataset" }, "crop_data": { "default": true, "description": "Update crop filter from Time object if passed to get method", "title": "Crop Data", "type": "boolean" }, "buffer": { "default": 2.0, "description": "Space to buffer the grid bounding box if `filter_grid` is True", "title": "Buffer", "type": "number" }, "time_buffer": { "default": [ 0, 0 ], "description": "Number of source data timesteps to buffer the time range if `filter_time` is True", "items": { "type": "integer" }, "title": "Time Buffer", "type": "array" }, "spacing": { "anyOf": [ { "type": "number" }, { "const": "parent", "type": "string" }, { "type": "null" } ], "default": null, "description": "Spacing between points along the grid boundary to retrieve data for. If None (default), points are defined from the the actual grid object passed to the `get` method. If 'parent', the resolution of the parent dataset is used to define the spacing.", "title": "Spacing" }, "sel_method": { "default": "idw", "description": "Wavespectra method to use for selecting boundary points from the dataset", "enum": [ "idw", "nearest" ], "title": "Sel Method", "type": "string" }, "sel_method_kwargs": { "additionalProperties": true, "default": {}, "description": "Keyword arguments for sel_method", "title": "Sel Method Kwargs", "type": "object" }, "grid_type": { "const": "boundary_wave_station", "default": "boundary_wave_station", "description": "Model type discriminator", "title": "Grid Type", "type": "string" }, "rectangle": { "default": "closed", "description": "Defines whether boundary is defined over an closed or open rectangle", "enum": [ "closed", "open" ], "title": "Rectangle", "type": "string" } }, "$defs": { "DatasetCoords": { "additionalProperties": false, "description": "Coordinates representation.", "properties": { "t": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": "time", "description": "Name of the time coordinate", "title": "T" }, "x": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": "longitude", "description": "Name of the x coordinate", "title": "X" }, "y": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": "latitude", "description": "Name of the y coordinate", "title": "Y" }, "z": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": "depth", "description": "Name of the z coordinate", "title": "Z" }, "s": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": "site", "description": "Name of the site coordinate", "title": "S" } }, "title": "DatasetCoords", "type": "object" }, "Filter": { "additionalProperties": false, "properties": { "sort": { "anyOf": [ { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "default": {}, "title": "Sort" }, "subset": { "anyOf": [ { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "default": {}, "title": "Subset" }, "crop": { "anyOf": [ { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "default": {}, "title": "Crop" }, "timenorm": { "anyOf": [ { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "default": {}, "title": "Timenorm" }, "rename": { "anyOf": [ { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "default": {}, "title": "Rename" }, "derived": { "anyOf": [ { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "default": {}, "title": "Derived" } }, "title": "Filter", "type": "object" }, "SourceDatamesh": { "additionalProperties": false, "description": "Source dataset from Datamesh.\n\nDatamesh documentation: https://docs.oceanum.io/datamesh/index.html", "properties": { "model_type": { "const": "datamesh", "default": "datamesh", "description": "Model type discriminator", "title": "Model Type", "type": "string" }, "datasource": { "description": "The id of the datasource on Datamesh", "title": "Datasource", "type": "string" }, "token": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "description": "Datamesh API token, taken from the environment if not provided", "title": "Token" }, "kwargs": { "additionalProperties": true, "default": {}, "description": "Keyword arguments to pass to `oceanum.datamesh.Connector`", "title": "Kwargs", "type": "object" } }, "required": [ "datasource", "token" ], "title": "SourceDatamesh", "type": "object" }, "SourceFile": { "additionalProperties": false, "description": "Source dataset from file to open with xarray.open_dataset.", "properties": { "model_type": { "const": "file", "default": "file", "description": "Model type discriminator", "title": "Model Type", "type": "string" }, "uri": { "anyOf": [ { "type": "string" }, { "format": "path", "type": "string" } ], "description": "Path to the dataset", "title": "Uri" }, "kwargs": { "additionalProperties": true, "default": {}, "description": "Keyword arguments to pass to xarray.open_dataset", "title": "Kwargs", "type": "object" } }, "required": [ "uri" ], "title": "SourceFile", "type": "object" }, "SourceIntake": { "additionalProperties": false, "description": "Source dataset from intake catalog.\n\nnote\n----\nThe intake catalog can be prescribed either by the URI of an existing catalog file\nor by a YAML string defining the catalog. The YAML string can be obtained from\ncalling the `yaml()` method on an intake dataset instance.", "properties": { "model_type": { "const": "intake", "default": "intake", "description": "Model type discriminator", "title": "Model Type", "type": "string" }, "dataset_id": { "description": "The id of the dataset to read in the catalog", "title": "Dataset Id", "type": "string" }, "catalog_uri": { "anyOf": [ { "type": "string" }, { "format": "path", "type": "string" }, { "type": "null" } ], "default": null, "description": "The URI of the catalog to read from", "title": "Catalog Uri" }, "catalog_yaml": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "The YAML string of the catalog to read from", "title": "Catalog Yaml" }, "kwargs": { "additionalProperties": true, "default": {}, "description": "Keyword arguments to define intake dataset parameters", "title": "Kwargs", "type": "object" } }, "required": [ "dataset_id" ], "title": "SourceIntake", "type": "object" }, "SourceTimeseriesCSV": { "additionalProperties": false, "description": "Timeseries source class from CSV file.\n\nThis class should return a timeseries from a CSV file. The dataset variables are\ndefined from the column headers, therefore the appropriate read_csv kwargs must be\npassed to allow defining the columns. The time index is defined from column name\nidentified by the tcol field.", "properties": { "model_type": { "const": "csv", "default": "csv", "description": "Model type discriminator", "title": "Model Type", "type": "string" }, "filename": { "anyOf": [ { "type": "string" }, { "format": "path", "type": "string" } ], "description": "Path to the csv file", "title": "Filename" }, "tcol": { "default": "time", "description": "Name of the column containing the time data", "title": "Tcol", "type": "string" }, "read_csv_kwargs": { "additionalProperties": true, "default": {}, "description": "Keyword arguments to pass to pandas.read_csv", "title": "Read Csv Kwargs", "type": "object" } }, "required": [ "filename" ], "title": "SourceTimeseriesCSV", "type": "object" }, "SourceWavespectra": { "additionalProperties": false, "description": "Wavespectra dataset from wavespectra reader.", "properties": { "model_type": { "const": "wavespectra", "default": "wavespectra", "description": "Model type discriminator", "title": "Model Type", "type": "string" }, "uri": { "anyOf": [ { "type": "string" }, { "format": "path", "type": "string" } ], "description": "Path to the dataset", "title": "Uri" }, "reader": { "description": "Name of the wavespectra reader to use, e.g., read_swan", "title": "Reader", "type": "string" }, "kwargs": { "additionalProperties": true, "default": {}, "description": "Keyword arguments to pass to the wavespectra reader", "title": "Kwargs", "type": "object" } }, "required": [ "uri", "reader" ], "title": "SourceWavespectra", "type": "object" } }, "additionalProperties": false, "required": [ "id", "source" ] }
- Fields:
- Validators:
spacing_gt_zero»spacing
- field buffer: float = 2.0#
Space to buffer the grid bounding box if filter_grid is True
- field coords: DatasetCoords | None = DatasetCoords(t='time', x='longitude', y='latitude', z='depth', s='site')#
Names of the coordinates in the dataset
- field crop_data: bool = True#
Update crop filter from Time object if passed to get method
- field filter: Filter | None [Optional]#
Optional filter specification to apply to the dataset
- field grid_type: Literal['boundary_wave_station'] = 'boundary_wave_station'#
Model type discriminator
- field id: str [Required]#
Unique identifier for this data source
- field link: bool = False#
Whether to create a symbolic link instead of copying the file
- field model_type: Literal['boundnest1', 'BOUNDNEST1'] = 'boundnest1'#
Model type discriminator
- field rectangle: Literal['closed', 'open'] = 'closed'#
Defines whether boundary is defined over an closed or open rectangle
- field sel_method: Literal['idw', 'nearest'] = 'idw'#
Wavespectra method to use for selecting boundary points from the dataset
- field sel_method_kwargs: dict = {}#
Keyword arguments for sel_method
- field source: SOURCE_TYPES [Required]#
Dataset source reader, must return a wavespectra-enabled xarray dataset in the open method
- field spacing: float | Literal['parent'] | None = None#
Spacing between points along the grid boundary to retrieve data for. If None (default), points are defined from the the actual grid object passed to the get method. If ‘parent’, the resolution of the parent dataset is used to define the spacing.
- Validated by:
spacing_gt_zero
- field time_buffer: list[int] = [0, 0]#
Number of source data timesteps to buffer the time range if filter_time is True
- field variables: list[str] | None = []#
Subset of variables to extract from the dataset
- get(destdir: str, grid: SwanGrid, time: TimeRange | None = None) str[source]#
Write the data source to a new location.
- Parameters:
destdir (str | Path) – Destination directory for the SWAN ASCII file.
grid (RegularGrid) – Grid instance to use for selecting the boundary points.
time (TimeRange, optional) – The times to filter the data to, only used if self.crop_data is True.
- Returns:
filename (Path) – The filename of the written boundary file.
cmd (str) – Boundary command string to render in the SWAN INPUT file
- model_post_init(_BoundaryWaveStation__context)#
This function is meant to behave like a BaseModel method to initialise private attributes.
It takes context as an argument since that’s what pydantic-core passes when calling it.
- Parameters:
self – The BaseModel instance.
context – The context.