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API reference

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+ eo_tides.model + + +

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+ model_tides + + +

+
model_tides(
+    x,
+    y,
+    time,
+    model="FES2014",
+    directory=None,
+    crs="EPSG:4326",
+    crop=True,
+    method="spline",
+    extrapolate=True,
+    cutoff=None,
+    mode="one-to-many",
+    parallel=True,
+    parallel_splits=5,
+    output_units="m",
+    output_format="long",
+    ensemble_models=None,
+    **ensemble_kwargs
+)
+
+ +
+ +

Compute tides at multiple points and times using tidal harmonics.

+

This function supports all tidal models supported by pyTMD, +including FES Finite Element Solution models, TPXO TOPEX/POSEIDON +models, EOT Empirical Ocean Tide models, GOT Global Ocean Tide +models, and HAMTIDE Hamburg direct data Assimilation Methods for +Tides models.

+

This function requires access to tide model data files. +These should be placed in a folder with subfolders matching +the formats specified by pyTMD: +https://pytmd.readthedocs.io/en/latest/getting_started/Getting-Started.html#directories

+

For FES2014 (https://www.aviso.altimetry.fr/es/data/products/auxiliary-products/global-tide-fes/description-fes2014.html):

+
    +
  • {directory}/fes2014/ocean_tide/
    • +
+

For FES2022 (https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/global-tide-fes.html):

+
    +
  • {directory}/fes2022b/ocean_tide/
    • +
+

For TPXO8-atlas (https://www.tpxo.net/tpxo-products-and-registration):

+
    +
  • {directory}/tpxo8_atlas/
    • +
+

For TPXO9-atlas-v5 (https://www.tpxo.net/tpxo-products-and-registration):

+
    +
  • {directory}/TPXO9_atlas_v5/
    • +
+

For EOT20 (https://www.seanoe.org/data/00683/79489/):

+
    +
  • {directory}/EOT20/ocean_tides/
    • +
+

For GOT4.10c (https://earth.gsfc.nasa.gov/geo/data/ocean-tide-models):

+
    +
  • {directory}/GOT4.10c/grids_oceantide_netcdf/
    • +
+

For HAMTIDE (https://www.cen.uni-hamburg.de/en/icdc/data/ocean/hamtide.html):

+
    +
  • {directory}/hamtide/
    • +
+

This function is a modification of the pyTMD package's +compute_tide_corrections function. For more info: +https://pytmd.readthedocs.io/en/stable/user_guide/compute_tide_corrections.html

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
x + float or list of floats + +
+

One or more x and y coordinates used to define +the location at which to model tides. By default these +coordinates should be lat/lon; use "crs" if they +are in a custom coordinate reference system.

+
+ 		+ required +
y + float or list of floats + +
+

One or more x and y coordinates used to define +the location at which to model tides. By default these +coordinates should be lat/lon; use "crs" if they +are in a custom coordinate reference system.

+
+ 		+ required +
time + A datetime array or pandas.DatetimeIndex + +
+

An array containing datetime64[ns] values or a +pandas.DatetimeIndex providing the times at which to +model tides in UTC time.

+
+ 		+ required +
model + string + +
+

The tide model used to model tides. Options include:

+
    +
  • "FES2014" (pre-configured on DEA Sandbox)
    • +
  • "FES2022"
    • +
  • "TPXO9-atlas-v5"
    • +
  • "TPXO8-atlas"
    • +
  • "EOT20"
    • +
  • "HAMTIDE11"
    • +
  • "GOT4.10"
    • +
  • "ensemble" (advanced ensemble tide model functionality; + combining multiple models based on external model rankings)
    • +
+
+ 		+ 'FES2014' +
directory + string + +
+

The directory containing tide model data files. If no path is +provided, this will default to the environment variable +DEA_TOOLS_TIDE_MODELS if set, otherwise "/var/share/tide_models". +Tide modelling files should be stored in sub-folders for each +model that match the structure provided by pyTMD.

+

For example:

+
    +
  • {directory}/fes2014/ocean_tide/
    • +
  • {directory}/tpxo8_atlas/
    • +
  • {directory}/TPXO9_atlas_v5/
    • +
+
+ 		+ None +
crs + str + +
+

Input coordinate reference system for x and y coordinates. +Defaults to "EPSG:4326" (WGS84; degrees latitude, longitude).

+
+ 		+ 'EPSG:4326' +
crop + bool optional + +
+

Whether to crop tide model constituent files on-the-fly to +improve performance. Cropping will be performed based on a +1 degree buffer around all input points. Defaults to True.

+
+ 		+ True +
method + string + +
+

Method used to interpolate tidal constituents +from model files. Options include:

+
    +
  • "spline": scipy bivariate spline interpolation (default)
    • +
  • "bilinear": quick bilinear interpolation
    • +
  • "linear", "nearest": scipy regular grid interpolations
    • +
+
+ 		+ 'spline' +
extrapolate + bool + +
+

Whether to extrapolate tides for x and y coordinates outside of +the valid tide modelling domain using nearest-neighbor.

+
+ 		+ True +
cutoff + int or float + +
+

Extrapolation cutoff in kilometers. The default is None, which +will extrapolate for all points regardless of distance from the +valid tide modelling domain.

+
+ 		+ None +
mode + string + +
+

The analysis mode to use for tide modelling. Supports two options:

+
    +
  • "one-to-many": Models tides for every timestep in "time" at +every input x and y coordinate point. This is useful if you +want to model tides for a specific list of timesteps across +multiple spatial points (e.g. for the same set of satellite +acquisition times at various locations across your study area).
    • +
  • "one-to-one": Model tides using a different timestep for each +x and y coordinate point. In this mode, the number of x and +y points must equal the number of timesteps provided in "time".
    • +
+
+ 		+ 'one-to-many' +
parallel + boolean + +
+

Whether to parallelise tide modelling using concurrent.futures. +If multiple tide models are requested, these will be run in +parallel. Optionally, tide modelling can also be run in parallel +across input x and y coordinates (see "parallel_splits" below). +Default is True.

+
+ 		+ True +
parallel_splits + int + +
+

Whether to split the input x and y coordinates into smaller, +evenly-sized chunks that are processed in parallel. This can +provide a large performance boost when processing large numbers +of coordinates. The default is 5 chunks, which will split +coordinates into 5 parallelised chunks.

+
+ 		+ 5 +
output_units + str + +
+

Whether to return modelled tides in floating point metre units, +or integer centimetre units (i.e. scaled by 100) or integer +millimetre units (i.e. scaled by 1000. Returning outputs in +integer units can be useful for reducing memory usage. +Defaults to "m" for metres; set to "cm" for centimetres or "mm" +for millimetres.

+
+ 		+ 'm' +
output_format + str + +
+

Whether to return the output dataframe in long format (with +results stacked vertically along "tide_model" and "tide_m" +columns), or wide format (with a column for each tide model). +Defaults to "long".

+
+ 		+ 'long' +
ensemble_models + list + +
+

An optional list of models used to generate the ensemble tide +model if "ensemble" tide modelling is requested. Defaults to +["FES2014", "TPXO9-atlas-v5", "EOT20", "HAMTIDE11", "GOT4.10", +"FES2012", "TPXO8-atlas-v1"].

+
+ 		+ None +
**ensemble_kwargs + +
+

Keyword arguments used to customise the generation of optional +ensemble tide models if "ensemble" modelling are requested. +These are passed to the underlying _ensemble_model function. +Useful parameters include ranking_points (path to model +rankings data), k (for controlling how model rankings are +interpolated), and ensemble_top_n (how many top models to use +in the ensemble calculation).

+
+ 		+ {} +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ DataFrame + +
+

A dataframe containing modelled tide heights.

+
+
+ +
+ Source code in eo_tides/model.py + 
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def model_tides(
+    x,
+    y,
+    time,
+    model="FES2014",
+    directory=None,
+    crs="EPSG:4326",
+    crop=True,
+    method="spline",
+    extrapolate=True,
+    cutoff=None,
+    mode="one-to-many",
+    parallel=True,
+    parallel_splits=5,
+    output_units="m",
+    output_format="long",
+    ensemble_models=None,
+    **ensemble_kwargs,
+):
+    """Compute tides at multiple points and times using tidal harmonics.
+
+    This function supports all tidal models supported by `pyTMD`,
+    including FES Finite Element Solution models, TPXO TOPEX/POSEIDON
+    models, EOT Empirical Ocean Tide models, GOT Global Ocean Tide
+    models, and HAMTIDE Hamburg direct data Assimilation Methods for
+    Tides models.
+
+    This function requires access to tide model data files.
+    These should be placed in a folder with subfolders matching
+    the formats specified by `pyTMD`:
+    <https://pytmd.readthedocs.io/en/latest/getting_started/Getting-Started.html#directories>
+
+    For FES2014 (<https://www.aviso.altimetry.fr/es/data/products/auxiliary-products/global-tide-fes/description-fes2014.html>):
+
+    - `{directory}/fes2014/ocean_tide/`
+
+    For FES2022 (<https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/global-tide-fes.html>):
+
+    - `{directory}/fes2022b/ocean_tide/`
+
+    For TPXO8-atlas (<https://www.tpxo.net/tpxo-products-and-registration>):
+
+    - `{directory}/tpxo8_atlas/`
+
+    For TPXO9-atlas-v5 (<https://www.tpxo.net/tpxo-products-and-registration>):
+
+    - `{directory}/TPXO9_atlas_v5/`
+
+    For EOT20 (<https://www.seanoe.org/data/00683/79489/>):
+
+    - `{directory}/EOT20/ocean_tides/`
+
+    For GOT4.10c (<https://earth.gsfc.nasa.gov/geo/data/ocean-tide-models>):
+
+    - `{directory}/GOT4.10c/grids_oceantide_netcdf/`
+
+    For HAMTIDE (<https://www.cen.uni-hamburg.de/en/icdc/data/ocean/hamtide.html>):
+
+    - `{directory}/hamtide/`
+
+    This function is a modification of the `pyTMD` package's
+    `compute_tide_corrections` function. For more info:
+    <https://pytmd.readthedocs.io/en/stable/user_guide/compute_tide_corrections.html>
+
+    Parameters
+    ----------
+    x, y : float or list of floats
+        One or more x and y coordinates used to define
+        the location at which to model tides. By default these
+        coordinates should be lat/lon; use "crs" if they
+        are in a custom coordinate reference system.
+    time : A datetime array or pandas.DatetimeIndex
+        An array containing `datetime64[ns]` values or a
+        `pandas.DatetimeIndex` providing the times at which to
+        model tides in UTC time.
+    model : string, optional
+        The tide model used to model tides. Options include:
+
+        - "FES2014" (pre-configured on DEA Sandbox)
+        - "FES2022"
+        - "TPXO9-atlas-v5"
+        - "TPXO8-atlas"
+        - "EOT20"
+        - "HAMTIDE11"
+        - "GOT4.10"
+        - "ensemble" (advanced ensemble tide model functionality;
+          combining multiple models based on external model rankings)
+    directory : string, optional
+        The directory containing tide model data files. If no path is
+        provided, this will default to the environment variable
+        `DEA_TOOLS_TIDE_MODELS` if set, otherwise "/var/share/tide_models".
+        Tide modelling files should be stored in sub-folders for each
+        model that match the structure provided by `pyTMD`.
+
+        For example:
+
+        - `{directory}/fes2014/ocean_tide/`
+        - `{directory}/tpxo8_atlas/`
+        - `{directory}/TPXO9_atlas_v5/`
+    crs : str, optional
+        Input coordinate reference system for x and y coordinates.
+        Defaults to "EPSG:4326" (WGS84; degrees latitude, longitude).
+    crop : bool optional
+        Whether to crop tide model constituent files on-the-fly to
+        improve performance. Cropping will be performed based on a
+        1 degree buffer around all input points. Defaults to True.
+    method : string, optional
+        Method used to interpolate tidal constituents
+        from model files. Options include:
+
+        - "spline": scipy bivariate spline interpolation (default)
+        - "bilinear": quick bilinear interpolation
+        - "linear", "nearest": scipy regular grid interpolations
+    extrapolate : bool, optional
+        Whether to extrapolate tides for x and y coordinates outside of
+        the valid tide modelling domain using nearest-neighbor.
+    cutoff : int or float, optional
+        Extrapolation cutoff in kilometers. The default is None, which
+        will extrapolate for all points regardless of distance from the
+        valid tide modelling domain.
+    mode : string, optional
+        The analysis mode to use for tide modelling. Supports two options:
+
+        - "one-to-many": Models tides for every timestep in "time" at
+        every input x and y coordinate point. This is useful if you
+        want to model tides for a specific list of timesteps across
+        multiple spatial points (e.g. for the same set of satellite
+        acquisition times at various locations across your study area).
+        - "one-to-one": Model tides using a different timestep for each
+        x and y coordinate point. In this mode, the number of x and
+        y points must equal the number of timesteps provided in "time".
+    parallel : boolean, optional
+        Whether to parallelise tide modelling using `concurrent.futures`.
+        If multiple tide models are requested, these will be run in
+        parallel. Optionally, tide modelling can also be run in parallel
+        across input x and y coordinates (see "parallel_splits" below).
+        Default is True.
+    parallel_splits : int, optional
+        Whether to split the input x and y coordinates into smaller,
+        evenly-sized chunks that are processed in parallel. This can
+        provide a large performance boost when processing large numbers
+        of coordinates. The default is 5 chunks, which will split
+        coordinates into 5 parallelised chunks.
+    output_units : str, optional
+        Whether to return modelled tides in floating point metre units,
+        or integer centimetre units (i.e. scaled by 100) or integer
+        millimetre units (i.e. scaled by 1000. Returning outputs in
+        integer units can be useful for reducing memory usage.
+        Defaults to "m" for metres; set to "cm" for centimetres or "mm"
+        for millimetres.
+    output_format : str, optional
+        Whether to return the output dataframe in long format (with
+        results stacked vertically along "tide_model" and "tide_m"
+        columns), or wide format (with a column for each tide model).
+        Defaults to "long".
+    ensemble_models : list, optional
+        An optional list of models used to generate the ensemble tide
+        model if "ensemble" tide modelling is requested. Defaults to
+        ["FES2014", "TPXO9-atlas-v5", "EOT20", "HAMTIDE11", "GOT4.10",
+        "FES2012", "TPXO8-atlas-v1"].
+    **ensemble_kwargs :
+        Keyword arguments used to customise the generation of optional
+        ensemble tide models if "ensemble" modelling are requested.
+        These are passed to the underlying `_ensemble_model` function.
+        Useful parameters include `ranking_points` (path to model
+        rankings data), `k` (for controlling how model rankings are
+        interpolated), and `ensemble_top_n` (how many top models to use
+        in the ensemble calculation).
+
+    Returns
+    -------
+    pandas.DataFrame
+        A dataframe containing modelled tide heights.
+
+    """
+    # Set tide modelling files directory. If no custom path is provided,
+    # first try global environmental var, then "/var/share/tide_models"
+    if directory is None:
+        if "DEA_TOOLS_TIDE_MODELS" in os.environ:
+            directory = os.environ["DEA_TOOLS_TIDE_MODELS"]
+        else:
+            directory = "/var/share/tide_models"
+
+    # Verify path exists
+    directory = pathlib.Path(directory).expanduser()
+    if not directory.exists():
+        raise FileNotFoundError("Invalid tide directory")
+
+    # If time passed as a single Timestamp, convert to datetime64
+    if isinstance(time, pd.Timestamp):
+        time = time.to_datetime64()
+
+    # Turn inputs into arrays for consistent handling
+    models_requested = np.atleast_1d(model)
+    x = np.atleast_1d(x)
+    y = np.atleast_1d(y)
+    time = np.atleast_1d(time)
+
+    # Validate input arguments
+    assert method in ("bilinear", "spline", "linear", "nearest")
+    assert output_units in (
+        "m",
+        "cm",
+        "mm",
+    ), "Output units must be either 'm', 'cm', or 'mm'."
+    assert output_format in (
+        "long",
+        "wide",
+    ), "Output format must be either 'long' or 'wide'."
+    assert len(x) == len(y), "x and y must be the same length."
+    if mode == "one-to-one":
+        assert len(x) == len(time), (
+            "The number of supplied x and y points and times must be "
+            "identical in 'one-to-one' mode. Use 'one-to-many' mode if "
+            "you intended to model multiple timesteps at each point."
+        )
+
+    # Verify that all provided models are supported
+    valid_models = [
+        # Standard built-in pyTMD models
+        "EOT20",
+        "FES2014",
+        "FES2022",
+        "GOT4.10",
+        "HAMTIDE11",
+        "TPXO8-atlas",  # binary version, not suitable for clipping
+        "TPXO9-atlas-v5",
+        # Non-standard models, defined internally
+        "FES2012",
+        "FES2014_extrapolated",
+        "FES2022_extrapolated",
+        "GOT5.6",
+        "GOT5.6_extrapolated",
+        "TPXO8-atlas-v1",  # netCDF version
+        # Advanced ensemble model functionality
+        "ensemble",
+    ]
+    if not all(m in valid_models for m in models_requested):
+        raise ValueError(
+            f"One or more of the models requested {models_requested} is "
+            f"not valid. The following models are currently supported: "
+            f"{valid_models}",
+        )
+
+    # If ensemble modelling is requested, use a custom list of models
+    # for subsequent processing
+    if "ensemble" in models_requested:
+        print("Running ensemble tide modelling")
+        models_to_process = (
+            ensemble_models
+            if ensemble_models is not None
+            else [
+                "FES2014",
+                "TPXO9-atlas-v5",
+                "EOT20",
+                "HAMTIDE11",
+                "GOT4.10",
+                "FES2012",
+                "TPXO8-atlas-v1",
+            ]
+        )
+
+    # Otherwise, models to process are the same as those requested
+    else:
+        models_to_process = models_requested
+
+    # Update tide modelling func to add default keyword arguments that
+    # are used for every iteration during parallel processing
+    iter_func = partial(
+        _model_tides,
+        directory=directory,
+        crs=crs,
+        crop=crop,
+        method=method,
+        extrapolate=extrapolate,
+        cutoff=np.inf if cutoff is None else cutoff,
+        output_units=output_units,
+        mode=mode,
+    )
+
+    # Ensure requested parallel splits is not smaller than number of points
+    parallel_splits = min(parallel_splits, len(x))
+
+    # Parallelise if either multiple models or multiple splits requested
+    if parallel & ((len(models_to_process) > 1) | (parallel_splits > 1)):
+        with ProcessPoolExecutor() as executor:
+            print(f"Modelling tides using {', '.join(models_to_process)} in parallel")
+
+            # Optionally split lon/lat points into `splits_n` chunks
+            # that will be applied in parallel
+            x_split = np.array_split(x, parallel_splits)
+            y_split = np.array_split(y, parallel_splits)
+
+            # Get every combination of models and lat/lon points, and
+            # extract as iterables that can be passed to `executor.map()`
+            # In "one-to-many" mode, pass entire set of timesteps to each
+            # parallel iteration by repeating timesteps by number of total
+            # parallel iterations. In "one-to-one" mode, split up
+            # timesteps into smaller parallel chunks too.
+            if mode == "one-to-many":
+                model_iters, x_iters, y_iters = zip(
+                    *[(m, x_split[i], y_split[i]) for m in models_to_process for i in range(parallel_splits)],
+                )
+                time_iters = [time] * len(model_iters)
+            elif mode == "one-to-one":
+                time_split = np.array_split(time, parallel_splits)
+                model_iters, x_iters, y_iters, time_iters = zip(
+                    *[
+                        (m, x_split[i], y_split[i], time_split[i])
+                        for m in models_to_process
+                        for i in range(parallel_splits)
+                    ],
+                )
+
+            # Apply func in parallel, iterating through each input param
+            model_outputs = list(
+                tqdm(
+                    executor.map(iter_func, model_iters, x_iters, y_iters, time_iters),
+                    total=len(model_iters),
+                ),
+            )
+
+    # Model tides in series if parallelisation is off
+    else:
+        model_outputs = []
+
+        for model_i in models_to_process:
+            print(f"Modelling tides using {model_i}")
+            tide_df = iter_func(model_i, x, y, time)
+            model_outputs.append(tide_df)
+
+    # Combine outputs into a single dataframe
+    tide_df = pd.concat(model_outputs, axis=0)
+
+    # Optionally compute ensemble model and add to dataframe
+    if "ensemble" in models_requested:
+        ensemble_df = _ensemble_model(x, y, crs, tide_df, models_to_process, **ensemble_kwargs)
+
+        # Update requested models with any custom ensemble models, then
+        # filter the dataframe to keep only models originally requested
+        models_requested = np.union1d(models_requested, ensemble_df.tide_model.unique())
+        tide_df = pd.concat([tide_df, ensemble_df]).query("tide_model in @models_requested")
+
+    # Optionally convert to a wide format dataframe with a tide model in
+    # each dataframe column
+    if output_format == "wide":
+        # Pivot into wide format with each time model as a column
+        print("Converting to a wide format dataframe")
+        tide_df = tide_df.pivot(columns="tide_model", values="tide_m")
+
+        # If in 'one-to-one' mode, reindex using our input time/x/y
+        # values to ensure the output is sorted the same as our inputs
+        if mode == "one-to-one":
+            output_indices = pd.MultiIndex.from_arrays([time, x, y], names=["time", "x", "y"])
+            tide_df = tide_df.reindex(output_indices)
+
+    return tide_df
+
+
+
+ +
+ +
+ + +

+ pixel_tides + + +

+
pixel_tides(
+    ds,
+    times=None,
+    resample=True,
+    calculate_quantiles=None,
+    resolution=None,
+    buffer=None,
+    resample_method="bilinear",
+    model="FES2014",
+    dask_chunks="auto",
+    dask_compute=True,
+    **model_tides_kwargs
+)
+
+ +
+ +

Obtain tide heights for each pixel in a dataset by modelling +tides into a low-resolution grid surrounding the dataset, +then (optionally) spatially resample this low-res data back +into the original higher resolution dataset extent and resolution.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
ds + Dataset + +
+

A dataset whose geobox (ds.odc.geobox) will be used to define +the spatial extent of the low resolution tide modelling grid.

+
+ 		+ required +
times + pandas.DatetimeIndex or list of pandas.Timestamps + +
+

By default, the function will model tides using the times +contained in the time dimension of ds. Alternatively, this +param can be used to model tides for a custom set of times +instead. For example: +times=pd.date_range(start="2000", end="2001", freq="5h")

+
+ 		+ None +
resample + bool + +
+

Whether to resample low resolution tides back into ds's original +higher resolution grid. Set this to False if you do not want +low resolution tides to be re-projected back to higher resolution.

+
+ 		+ True +
calculate_quantiles + list or array + +
+

Rather than returning all individual tides, low-resolution tides +can be first aggregated using a quantile calculation by passing in +a list or array of quantiles to compute. For example, this could +be used to calculate the min/max tide across all times: +calculate_quantiles=[0.0, 1.0].

+
+ 		+ None +
resolution + int + +
+

The desired resolution of the low-resolution grid used for tide +modelling. The default None will create a 5000 m resolution grid +if ds has a projected CRS (i.e. metre units), or a 0.05 degree +resolution grid if ds has a geographic CRS (e.g. degree units). +Note: higher resolutions do not necessarily provide better +tide modelling performance, as results will be limited by the +resolution of the underlying global tide model (e.g. 1/16th +degree / ~5 km resolution grid for FES2014).

+
+ 		+ None +
buffer + int + +
+

The amount by which to buffer the higher resolution grid extent +when creating the new low resolution grid. This buffering is +important as it ensures that ensure pixel-based tides are seamless +across dataset boundaries. This buffer will eventually be clipped +away when the low-resolution data is re-projected back to the +resolution and extent of the higher resolution dataset. To +ensure that at least two pixels occur outside of the dataset +bounds, the default None applies a 12000 m buffer if ds has a +projected CRS (i.e. metre units), or a 0.12 degree buffer if +ds has a geographic CRS (e.g. degree units).

+
+ 		+ None +
resample_method + string + +
+

If resampling is requested (see resample above), use this +resampling method when converting from low resolution to high +resolution pixels. Defaults to "bilinear"; valid options include +"nearest", "cubic", "min", "max", "average" etc.

+
+ 		+ 'bilinear' +
model + string or list of strings + +
+

The tide model or a list of models used to model tides, as +supported by the pyTMD Python package. Options include: +- "FES2014" (default; pre-configured on DEA Sandbox) +- "FES2022" +- "TPXO8-atlas" +- "TPXO9-atlas-v5" +- "EOT20" +- "HAMTIDE11" +- "GOT4.10"

+
+ 		+ 'FES2014' +
dask_chunks + str or tuple + +
+

Can be used to configure custom Dask chunking for the final +resampling step. The default of "auto" will automatically set +x/y chunks to match those in ds if they exist, otherwise will +set x/y chunks that cover the entire extent of the dataset. +For custom chunks, provide a tuple in the form (y, x), e.g. +(2048, 2048).

+
+ 		+ 'auto' +
dask_compute + bool + +
+

Whether to compute results of the resampling step using Dask. +If False, this will return tides_highres as a Dask array.

+
+ 		+ True +
**model_tides_kwargs + +
+

Optional parameters passed to the dea_tools.coastal.model_tides +function. Important parameters include "directory" (used to +specify the location of input tide modelling files) and "cutoff" +(used to extrapolate modelled tides away from the coast; if not +specified here, cutoff defaults to np.inf).

+
+ 		+ {} +
+ + +

Returns:

+ + + + + + + + + + + + + + + + + +
TypeDescription
+ If `resample` is False: + +
+

tides_lowres : xr.DataArray + A low resolution data array giving either tide heights every + timestep in ds (if times is None), tide heights at every + time in times (if times is not None), or tide height quantiles + for every quantile provided by calculate_quantiles.

+
+
+ If `resample` is True: + +
+

tides_highres, tides_lowres : tuple of xr.DataArrays + In addition to tides_lowres (see above), a high resolution + array of tide heights will be generated that matches the + exact spatial resolution and extent of ds. This will contain + either tide heights every timestep in ds (if times is None), + tide heights at every time in times (if times is not None), + or tide height quantiles for every quantile provided by + calculate_quantiles.

+
+
+ +
+ Source code in eo_tides/model.py + 
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def pixel_tides(
+    ds,
+    times=None,
+    resample=True,
+    calculate_quantiles=None,
+    resolution=None,
+    buffer=None,
+    resample_method="bilinear",
+    model="FES2014",
+    dask_chunks="auto",
+    dask_compute=True,
+    **model_tides_kwargs,
+):
+    """Obtain tide heights for each pixel in a dataset by modelling
+    tides into a low-resolution grid surrounding the dataset,
+    then (optionally) spatially resample this low-res data back
+    into the original higher resolution dataset extent and resolution.
+
+    Parameters
+    ----------
+    ds : xarray.Dataset
+        A dataset whose geobox (`ds.odc.geobox`) will be used to define
+        the spatial extent of the low resolution tide modelling grid.
+    times : pandas.DatetimeIndex or list of pandas.Timestamps, optional
+        By default, the function will model tides using the times
+        contained in the `time` dimension of `ds`. Alternatively, this
+        param can be used to model tides for a custom set of times
+        instead. For example:
+        `times=pd.date_range(start="2000", end="2001", freq="5h")`
+    resample : bool, optional
+        Whether to resample low resolution tides back into `ds`'s original
+        higher resolution grid. Set this to `False` if you do not want
+        low resolution tides to be re-projected back to higher resolution.
+    calculate_quantiles : list or np.array, optional
+        Rather than returning all individual tides, low-resolution tides
+        can be first aggregated using a quantile calculation by passing in
+        a list or array of quantiles to compute. For example, this could
+        be used to calculate the min/max tide across all times:
+        `calculate_quantiles=[0.0, 1.0]`.
+    resolution : int, optional
+        The desired resolution of the low-resolution grid used for tide
+        modelling. The default None will create a 5000 m resolution grid
+        if `ds` has a projected CRS (i.e. metre units), or a 0.05 degree
+        resolution grid if `ds` has a geographic CRS (e.g. degree units).
+        Note: higher resolutions do not necessarily provide better
+        tide modelling performance, as results will be limited by the
+        resolution of the underlying global tide model (e.g. 1/16th
+        degree / ~5 km resolution grid for FES2014).
+    buffer : int, optional
+        The amount by which to buffer the higher resolution grid extent
+        when creating the new low resolution grid. This buffering is
+        important as it ensures that ensure pixel-based tides are seamless
+        across dataset boundaries. This buffer will eventually be clipped
+        away when the low-resolution data is re-projected back to the
+        resolution and extent of the higher resolution dataset. To
+        ensure that at least two pixels occur outside of the dataset
+        bounds, the default None applies a 12000 m buffer if `ds` has a
+        projected CRS (i.e. metre units), or a 0.12 degree buffer if
+        `ds` has a geographic CRS (e.g. degree units).
+    resample_method : string, optional
+        If resampling is requested (see `resample` above), use this
+        resampling method when converting from low resolution to high
+        resolution pixels. Defaults to "bilinear"; valid options include
+        "nearest", "cubic", "min", "max", "average" etc.
+    model : string or list of strings
+        The tide model or a list of models used to model tides, as
+        supported by the `pyTMD` Python package. Options include:
+        - "FES2014" (default; pre-configured on DEA Sandbox)
+        - "FES2022"
+        - "TPXO8-atlas"
+        - "TPXO9-atlas-v5"
+        - "EOT20"
+        - "HAMTIDE11"
+        - "GOT4.10"
+    dask_chunks : str or tuple, optional
+        Can be used to configure custom Dask chunking for the final
+        resampling step. The default of "auto" will automatically set
+        x/y chunks to match those in `ds` if they exist, otherwise will
+        set x/y chunks that cover the entire extent of the dataset.
+        For custom chunks, provide a tuple in the form `(y, x)`, e.g.
+        `(2048, 2048)`.
+    dask_compute : bool, optional
+        Whether to compute results of the resampling step using Dask.
+        If False, this will return `tides_highres` as a Dask array.
+    **model_tides_kwargs :
+        Optional parameters passed to the `dea_tools.coastal.model_tides`
+        function. Important parameters include "directory" (used to
+        specify the location of input tide modelling files) and "cutoff"
+        (used to extrapolate modelled tides away from the coast; if not
+        specified here, cutoff defaults to `np.inf`).
+
+    Returns
+    -------
+    If `resample` is False:
+
+        tides_lowres : xr.DataArray
+            A low resolution data array giving either tide heights every
+            timestep in `ds` (if `times` is None), tide heights at every
+            time in `times` (if `times` is not None), or tide height quantiles
+            for every quantile provided by `calculate_quantiles`.
+
+    If `resample` is True:
+
+        tides_highres, tides_lowres : tuple of xr.DataArrays
+            In addition to `tides_lowres` (see above), a high resolution
+            array of tide heights will be generated that matches the
+            exact spatial resolution and extent of `ds`. This will contain
+            either tide heights every timestep in `ds` (if `times` is None),
+            tide heights at every time in `times` (if `times` is not None),
+            or tide height quantiles for every quantile provided by
+            `calculate_quantiles`.
+
+    """
+    from odc.geo.geobox import GeoBox
+
+    # First test if no time dimension and nothing passed to `times`
+    if ("time" not in ds.dims) & (times is None):
+        raise ValueError(
+            "`ds` does not contain a 'time' dimension. Times are required "
+            "for modelling tides: please pass in a set of custom tides "
+            "using the `times` parameter. For example: "
+            "`times=pd.date_range(start='2000', end='2001', freq='5h')`",
+        )
+
+    # If custom times are provided, convert them to a consistent
+    # pandas.DatatimeIndex format
+    if times is not None:
+        if isinstance(times, list):
+            time_coords = pd.DatetimeIndex(times)
+        elif isinstance(times, pd.Timestamp):
+            time_coords = pd.DatetimeIndex([times])
+        else:
+            time_coords = times
+
+    # Otherwise, use times from `ds` directly
+    else:
+        time_coords = ds.coords["time"]
+
+    # Set defaults passed to `model_tides`
+    model_tides_kwargs.setdefault("cutoff", np.inf)
+
+    # Standardise model into a list for easy handling
+    model = [model] if isinstance(model, str) else model
+
+    # Test if no time dimension and nothing passed to `times`
+    if ("time" not in ds.dims) & (times is None):
+        raise ValueError(
+            "`ds` does not contain a 'time' dimension. Times are required "
+            "for modelling tides: please pass in a set of custom tides "
+            "using the `times` parameter. For example: "
+            "`times=pd.date_range(start='2000', end='2001', freq='5h')`",
+        )
+
+    # If custom times are provided, convert them to a consistent
+    # pandas.DatatimeIndex format
+    if times is not None:
+        if isinstance(times, list):
+            time_coords = pd.DatetimeIndex(times)
+        elif isinstance(times, pd.Timestamp):
+            time_coords = pd.DatetimeIndex([times])
+        else:
+            time_coords = times
+
+    # Otherwise, use times from `ds` directly
+    else:
+        time_coords = ds.coords["time"]
+
+    # Determine spatial dimensions
+    y_dim, x_dim = ds.odc.spatial_dims
+
+    # Determine resolution and buffer, using different defaults for
+    # geographic (i.e. degrees) and projected (i.e. metres) CRSs:
+    crs_units = ds.odc.geobox.crs.units[0][0:6]
+    if ds.odc.geobox.crs.geographic:
+        if resolution is None:
+            resolution = 0.05
+        elif resolution > 360:
+            raise ValueError(
+                f"A resolution of greater than 360 was "
+                f"provided, but `ds` has a geographic CRS "
+                f"in {crs_units} units. Did you accidently "
+                f"provide a resolution in projected "
+                f"(i.e. metre) units?",
+            )
+        if buffer is None:
+            buffer = 0.12
+    else:
+        if resolution is None:
+            resolution = 5000
+        elif resolution < 1:
+            raise ValueError(
+                f"A resolution of less than 1 was provided, "
+                f"but `ds` has a projected CRS in "
+                f"{crs_units} units. Did you accidently "
+                f"provide a resolution in geographic "
+                f"(degree) units?",
+            )
+        if buffer is None:
+            buffer = 12000
+
+    # Raise error if resolution is less than dataset resolution
+    dataset_res = ds.odc.geobox.resolution.x
+    if resolution < dataset_res:
+        raise ValueError(
+            f"The resolution of the low-resolution tide "
+            f"modelling grid ({resolution:.2f}) is less "
+            f"than `ds`'s pixel resolution ({dataset_res:.2f}). "
+            f"This can cause extremely slow tide modelling "
+            f"performance. Please select provide a resolution "
+            f"greater than {dataset_res:.2f} using "
+            f"`pixel_tides`'s 'resolution' parameter.",
+        )
+
+    # Create a new reduced resolution tide modelling grid after
+    # first buffering the grid
+    print(f"Creating reduced resolution {resolution} x {resolution} {crs_units} tide modelling array")
+    buffered_geobox = ds.odc.geobox.buffered(buffer)
+    rescaled_geobox = GeoBox.from_bbox(bbox=buffered_geobox.boundingbox, resolution=resolution)
+    rescaled_ds = odc.geo.xr.xr_zeros(rescaled_geobox)
+
+    # Flatten grid to 1D, then add time dimension
+    flattened_ds = rescaled_ds.stack(z=(x_dim, y_dim))
+    flattened_ds = flattened_ds.expand_dims(dim={"time": time_coords.values})
+
+    # Model tides in parallel, returning a pandas.DataFrame
+    tide_df = model_tides(
+        x=flattened_ds[x_dim],
+        y=flattened_ds[y_dim],
+        time=flattened_ds.time,
+        crs=f"EPSG:{ds.odc.geobox.crs.epsg}",
+        model=model,
+        **model_tides_kwargs,
+    )
+
+    # Convert our pandas.DataFrame tide modelling outputs to xarray
+    tides_lowres = (
+        # Rename x and y dataframe indexes to match x and y xarray dims
+        tide_df.rename_axis(["time", x_dim, y_dim])
+        # Add tide model column to dataframe indexes so we can convert
+        # our dataframe to a multidimensional xarray
+        .set_index("tide_model", append=True)
+        # Convert to xarray and select our tide modelling xr.DataArray
+        .to_xarray()
+        .tide_m
+        # Re-index and transpose into our input coordinates and dim order
+        .reindex_like(rescaled_ds)
+        .transpose("tide_model", "time", y_dim, x_dim)
+    )
+
+    # Optionally calculate and return quantiles rather than raw data.
+    # Set dtype to dtype of the input data as quantile always returns
+    # float64 (memory intensive)
+    if calculate_quantiles is not None:
+        print("Computing tide quantiles")
+        tides_lowres = tides_lowres.quantile(q=calculate_quantiles, dim="time").astype(tides_lowres.dtype)
+
+    # If only one tidal model exists, squeeze out "tide_model" dim
+    if len(tides_lowres.tide_model) == 1:
+        tides_lowres = tides_lowres.squeeze("tide_model")
+
+    # Ensure CRS is present before we apply any resampling
+    tides_lowres = tides_lowres.odc.assign_crs(ds.odc.geobox.crs)
+
+    # Reproject into original high resolution grid
+    if resample:
+        print("Reprojecting tides into original array")
+        tides_highres, tides_lowres = _pixel_tides_resample(
+            tides_lowres,
+            ds,
+            resample_method,
+            dask_chunks,
+            dask_compute,
+        )
+        return tides_highres, tides_lowres
+
+    print("Returning low resolution tide array")
+    return tides_lowres
+
+
+
+ +
+ + + +
+ +
+ +
+ +
+ + + +

+ eo_tides.stats + + +

+ +
+ + + +
+ + + + + + + + + +
+ + +

+ tide_stats + + +

+
tide_stats(a)
+
+ +
+ +

Test function.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
a + int + +
+

Test

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ Test + +
+ +
+
+ +
+ Source code in eo_tides/stats.py + 
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+ 2
+ 3
+ 4
+ 5
+ 6
+ 7
+ 8
+ 9
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def tide_stats(a):
+    """
+    Test function.
+
+    Parameters
+    ----------
+    a : int
+        Test
+
+    Returns
+    -------
+    Test
+
+    """
+    return a
+
+
+
+ +
+ + + +
+ +
+ +
+ +
+ + + +

+ eo_tides.validation + + +

+ +
+ + + +
+ + + + + + + + + +
+ + +

+ eval_metrics + + +

+
eval_metrics(x, y, round=3, all_regress=False)
+
+ +
+ +

Calculate a set of common statistical metrics +based on two input actual and predicted vectors.

+

These include:

+
    +
  • Pearson correlation
    • +
  • Root Mean Squared Error
    • +
  • Mean Absolute Error
    • +
  • R-squared
    • +
  • Bias
    • +
  • Linear regression parameters (slope, p-value, intercept, standard error)
    • +
+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
x + array + +
+

An array providing "actual" variable values.

+
+ 		+ required +
y + array + +
+

An array providing "predicted" variable values.

+
+ 		+ required +
round + int + +
+

Number of decimal places to round each metric +to. Defaults to 3.

+
+ 		+ 3 +
all_regress + bool + +
+

Whether to return linear regression p-value, +intercept and standard error (in addition to +only regression slope). Defaults to False.

+
+ 		+ False +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ Series + +
+

A pd.Series containing all calculated metrics.

+
+
+ +
+ Source code in eo_tides/validation.py + 
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def eval_metrics(x, y, round=3, all_regress=False):
+    """
+    Calculate a set of common statistical metrics
+    based on two input actual and predicted vectors.
+
+    These include:
+
+    * Pearson correlation
+    * Root Mean Squared Error
+    * Mean Absolute Error
+    * R-squared
+    * Bias
+    * Linear regression parameters (slope, p-value, intercept, standard error)
+
+    Parameters
+    ----------
+    x : numpy.array
+        An array providing "actual" variable values.
+    y : numpy.array
+        An array providing "predicted" variable values.
+    round : int
+        Number of decimal places to round each metric
+        to. Defaults to 3.
+    all_regress : bool
+        Whether to return linear regression p-value,
+        intercept and standard error (in addition to
+        only regression slope). Defaults to False.
+
+    Returns
+    -------
+    pandas.Series
+        A `pd.Series` containing all calculated metrics.
+    """
+
+    # Create dataframe to drop na
+    xy_df = pd.DataFrame({"x": x, "y": y}).dropna()
+
+    # Compute linear regression
+    lin_reg = stats.linregress(x=xy_df.x, y=xy_df.y)
+
+    # Calculate statistics
+    stats_dict = {
+        "Correlation": xy_df.corr().iloc[0, 1],
+        "RMSE": sqrt(mean_squared_error(xy_df.x, xy_df.y)),
+        "MAE": mean_absolute_error(xy_df.x, xy_df.y),
+        "R-squared": lin_reg.rvalue**2,
+        "Bias": (xy_df.y - xy_df.x).mean(),
+        "Regression slope": lin_reg.slope,
+    }
+
+    # Additional regression params
+    if all_regress:
+        stats_dict.update({
+            "Regression p-value": lin_reg.pvalue,
+            "Regression intercept": lin_reg.intercept,
+            "Regression standard error": lin_reg.stderr,
+        })
+
+    # Return as
+    return pd.Series(stats_dict).round(round)
+
+
+
+ +
+ +
+ + +

+ load_gauge_gesla + + +

+
load_gauge_gesla(
+    x=None,
+    y=None,
+    site_code=None,
+    time=("2018", "2020"),
+    max_distance=None,
+    correct_mean=False,
+    filter_use_flag=True,
+    site_metadata=True,
+    data_path="/gdata1/data/sea_level/gesla/",
+    metadata_path="/gdata1/data/sea_level/GESLA3_ALL 2.csv",
+)
+
+ +
+ +

Load and process all available Global Extreme Sea Level Analysis +(GESLA) tide gauge data with an x, y, time spatiotemporal query, +or from a list of specific tide gauges.

+

Can optionally filter by gauge quality and append detailed gauge metadata.

+

Modified from original code in https://github.com/philiprt/GeslaDataset.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
x + numeric or list / tuple + +
+

Coordinates (in degrees longitude, latitude) used to load GESLA +tide gauge observations. If provided as singular values +(e.g. x=150, y=-32), then the nearest tide gauge will be returned. +If provided as a list or tuple (e.g. x=(150, 152), y=(-32, -30)), +then all gauges within the provided bounding box will be loaded. +Leave as None to return all available gauges, or if providing a +list of site codes using site_code.

+
+ 		+ None +
y + numeric or list / tuple + +
+

Coordinates (in degrees longitude, latitude) used to load GESLA +tide gauge observations. If provided as singular values +(e.g. x=150, y=-32), then the nearest tide gauge will be returned. +If provided as a list or tuple (e.g. x=(150, 152), y=(-32, -30)), +then all gauges within the provided bounding box will be loaded. +Leave as None to return all available gauges, or if providing a +list of site codes using site_code.

+
+ 		+ None +
site_code + str or list of str + +
+

GESLA site code(s) for which to load data (e.g. site_code="62650"). +If site_code is provided, x and y will be ignored.

+
+ 		+ None +
time + tuple or list of str + +
+

Time range to consider, given as a tuple of start and end dates, +e.g. time=("2020", "2021"). The default of None will return all +tide observations from the year 1800 onward.

+
+ 		+ ('2018', '2020') +
max_distance + numeric + +
+

Optional max distance within which to return the nearest tide gauge +when x and y are provided as singular coordinates. Defaults to +None, which will always return a tide gauge no matter how far away +it is located from x and y.

+
+ 		+ None +
correct_mean + bool + +
+

Whether to correct sea level measurements to a standardised mean +sea level by subtracting the mean of all observed sea level +observations. This can be useful when GESLA tide heights come +from different or unknown tide datums. Note: the observed mean +sea level calculated here may differ from true long-term/ +astronomical Mean Sea Level (MSL) datum.

+
+ 		+ False +
filter_use_flag + bool + +
+

Whether to filter out low quality observations with a "use_flag" +value of 0 (do not use). Defaults to True.

+
+ 		+ True +
site_metadata + bool + +
+

Whether to add tide gauge station metadata as additional columns +in the output DataFrame. Defaults to True.

+
+ 		+ True +
data_path + str + +
+

Path to the raw GESLA data files. Default is +/gdata1/data/sea_level/gesla/.

+
+ 		+ '/gdata1/data/sea_level/gesla/' +
metadata_path + str + +
+

Path to the GESLA station metadata file. +Default is /gdata1/data/sea_level/GESLA3_ALL 2.csv.

+
+ 		+ '/gdata1/data/sea_level/GESLA3_ALL 2.csv' +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ DataFrame + +
+

Processed GESLA data as a DataFrame with columns including:

+
    +
  • "time": Timestamps,
    • +
  • "sea_level": Observed sea level (m),
    • +
  • "qc_flag": Observed sea level QC flag,
    • +
  • "use_flag": Use-in-analysis flag (1 = use, 0 = do not use),
    • +
+

...and additional columns from station metadata.

+
+
+ +
+ Source code in eo_tides/validation.py + 
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def load_gauge_gesla(
+    x=None,
+    y=None,
+    site_code=None,
+    time=("2018", "2020"),
+    max_distance=None,
+    correct_mean=False,
+    filter_use_flag=True,
+    site_metadata=True,
+    data_path="/gdata1/data/sea_level/gesla/",
+    metadata_path="/gdata1/data/sea_level/GESLA3_ALL 2.csv",
+):
+    """
+    Load and process all available Global Extreme Sea Level Analysis
+    (GESLA) tide gauge data with an `x, y, time` spatiotemporal query,
+    or from a list of specific tide gauges.
+
+    Can optionally filter by gauge quality and append detailed gauge metadata.
+
+    Modified from original code in <https://github.com/philiprt/GeslaDataset>.
+
+    Parameters
+    ----------
+    x, y : numeric or list/tuple, optional
+        Coordinates (in degrees longitude, latitude) used to load GESLA
+        tide gauge observations. If provided as singular values
+        (e.g. `x=150, y=-32`), then the nearest tide gauge will be returned.
+        If provided as a list or tuple (e.g. `x=(150, 152), y=(-32, -30)`),
+        then all gauges within the provided bounding box will be loaded.
+        Leave as `None` to return all available gauges, or if providing a
+        list of site codes using `site_code`.
+    site_code : str or list of str, optional
+        GESLA site code(s) for which to load data (e.g. `site_code="62650"`).
+        If `site_code` is provided, `x` and `y` will be ignored.
+    time : tuple or list of str, optional
+        Time range to consider, given as a tuple of start and end dates,
+        e.g. `time=("2020", "2021")`. The default of None will return all
+        tide observations from the year 1800 onward.
+    max_distance : numeric, optional
+        Optional max distance within which to return the nearest tide gauge
+        when `x` and `y` are provided as singular coordinates. Defaults to
+        None, which will always return a tide gauge no matter how far away
+        it is located from `x` and `y`.
+    correct_mean : bool, optional
+        Whether to correct sea level measurements to a standardised mean
+        sea level by subtracting the mean of all observed sea level
+        observations. This can be useful when GESLA tide heights come
+        from different or unknown tide datums. Note: the observed mean
+        sea level calculated here may differ from true long-term/
+        astronomical Mean Sea Level (MSL) datum.
+    filter_use_flag : bool, optional
+        Whether to filter out low quality observations with a "use_flag"
+        value of 0 (do not use). Defaults to True.
+    site_metadata : bool, optional
+        Whether to add tide gauge station metadata as additional columns
+        in the output DataFrame. Defaults to True.
+    data_path : str, optional
+        Path to the raw GESLA data files. Default is
+        `/gdata1/data/sea_level/gesla/`.
+    metadata_path : str, optional
+        Path to the GESLA station metadata file.
+        Default is `/gdata1/data/sea_level/GESLA3_ALL 2.csv`.
+
+    Returns
+    -------
+    pd.DataFrame
+        Processed GESLA data as a DataFrame with columns including:
+
+        - "time": Timestamps,
+        - "sea_level": Observed sea level (m),
+        - "qc_flag": Observed sea level QC flag,
+        - "use_flag": Use-in-analysis flag (1 = use, 0 = do not use),
+
+        ...and additional columns from station metadata.
+    """
+    # Load tide gauge metadata
+    metadata_df, metadata_gdf = _load_gauge_metadata(metadata_path)
+
+    # Use supplied site codes if available
+    if site_code is not None:
+        site_code = [site_code] if not isinstance(site_code, list) else site_code
+
+    # If x and y are tuples, use xy bounds to identify sites
+    elif isinstance(x, (tuple, list)) & isinstance(y, (tuple, list)):
+        bbox = BoundingBox.from_xy(x, y)
+        site_code = metadata_gdf.cx[bbox.left : bbox.right, bbox.top : bbox.bottom].index
+
+    # If x and y are single numbers, select nearest row
+    elif isinstance(x, Number) & isinstance(y, Number):
+        site_code = _nearest_row(metadata_gdf, x, y, max_distance).site_code
+
+        # Raise exception if no valid tide gauges are found
+        if site_code.isnull().all():
+            raise Exception(f"No tide gauge found within {max_distance} degrees of {x}, {y}.")
+
+    # Otherwise if all are None, return all available site codes
+    elif (site_code is None) & (x is None) & (y is None):
+        site_code = metadata_df.index.to_list()
+
+    else:
+        raise TypeError(
+            "`x` and `y` must be provided as either singular coordinates (e.g. `x=150`), or as a tuple bounding box (e.g. `x=(150, 152)`)."
+        )
+
+    # Prepare times
+    if time is None:
+        time = ["1800", str(datetime.datetime.now().year)]
+    time = [time] if not isinstance(time, (list, tuple)) else time
+    start_time = round_date_strings(time[0], round_type="start")
+    end_time = round_date_strings(time[-1], round_type="end")
+
+    # Identify paths to load and nodata values for each site
+    metadata_df["file_name"] = data_path + metadata_df["file_name"]
+    paths_na = metadata_df.loc[site_code, ["file_name", "null_value"]]
+
+    # Load and combine into a single dataframe
+    data_df = (
+        pd.concat([_load_gesla_dataset(s, p, na_value=na) for s, p, na in paths_na.itertuples()])
+        .sort_index()
+        .loc[slice(start_time, end_time)]
+        .reset_index()
+        .set_index("site_code")
+    )
+
+    # Optionally filter by use flag column
+    if filter_use_flag:
+        data_df = data_df.loc[data_df.use_flag == 1]
+
+    # Optionally insert metadata into dataframe
+    if site_metadata:
+        data_df[metadata_df.columns] = metadata_df.loc[site_code]
+
+    # Add time to index and remove duplicates
+    data_df = data_df.set_index("time", append=True)
+    duplicates = data_df.index.duplicated()
+    if duplicates.sum() > 0:
+        warnings.warn("Duplicate timestamps were removed.")
+        data_df = data_df.loc[~duplicates]
+
+    # Remove observed mean sea level if requested
+    if correct_mean:
+        data_df["sea_level"] = data_df["sea_level"].sub(data_df.groupby("site_code")["sea_level"].transform("mean"))
+
+    # Return data
+    return data_df
+
+
+
+ +
+ +
+ + +

+ round_date_strings + + +

+
round_date_strings(date, round_type='end')
+
+ +
+ +

Round a date string up or down to the start or end of a given time +period.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
date + str + +
+

Date string of variable precision (e.g. "2020", "2020-01", +"2020-01-01").

+
+ 		+ required +
round_type + str + +
+

Type of rounding to perform. Valid options are "start" or "end". +If "start", date is rounded down to the start of the time period. +If "end", date is rounded up to the end of the time period. +Default is "end".

+
+ 		+ 'end' +
+ + +

Returns:

+ + + + + + + + + + + + + +
Name TypeDescription
date_rounded + str + +
+

The rounded date string.

+
+
+ + +

Examples:

+ 
>>> round_date_strings('2020')
+'2020-12-31 00:00:00'
+
+ 
>>> round_date_strings('2020-01', round_type='start')
+'2020-01-01 00:00:00'
+
+ 
>>> round_date_strings('2020-01', round_type='end')
+'2020-01-31 00:00:00'
+
+ +
+ Source code in eo_tides/validation.py + 
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def round_date_strings(date, round_type="end"):
+    """
+    Round a date string up or down to the start or end of a given time
+    period.
+
+    Parameters
+    ----------
+    date : str
+        Date string of variable precision (e.g. "2020", "2020-01",
+        "2020-01-01").
+    round_type : str, optional
+        Type of rounding to perform. Valid options are "start" or "end".
+        If "start", date is rounded down to the start of the time period.
+        If "end", date is rounded up to the end of the time period.
+        Default is "end".
+
+    Returns
+    -------
+    date_rounded : str
+        The rounded date string.
+
+    Examples
+    --------
+    >>> round_date_strings('2020')
+    '2020-12-31 00:00:00'
+
+    >>> round_date_strings('2020-01', round_type='start')
+    '2020-01-01 00:00:00'
+
+    >>> round_date_strings('2020-01', round_type='end')
+    '2020-01-31 00:00:00'
+    """
+
+    # Determine precision of input date string
+    date_segments = len(date.split("-"))
+
+    # If provided date has no "-", treat it as having year precision
+    if date_segments == 1 and round_type == "start":
+        date_rounded = str(pd.to_datetime(date) + YearBegin(0))
+    elif date_segments == 1 and round_type == "end":
+        date_rounded = str(pd.to_datetime(date) + YearEnd(0))
+
+    # If provided date has one "-", treat it as having month precision
+    elif date_segments == 2 and round_type == "start":
+        date_rounded = str(pd.to_datetime(date) + MonthBegin(0))
+    elif date_segments == 2 and round_type == "end":
+        date_rounded = str(pd.to_datetime(date) + MonthEnd(0))
+
+    # If more than one "-", then return date as-is
+    elif date_segments > 2:
+        date_rounded = date
+
+    return date_rounded
+
+
+
+ +
+ + + +
+ +
+ +
+ +
+ + + +

+ eo_tides.utils + + +

+ +
+ + + +
+ + + + + + + + + +
+ + +

+ idw + + +

+
idw(
+    input_z,
+    input_x,
+    input_y,
+    output_x,
+    output_y,
+    p=1,
+    k=10,
+    max_dist=None,
+    k_min=1,
+    epsilon=1e-12,
+)
+
+ +
+ +

Perform Inverse Distance Weighting (IDW) interpolation.

+

This function performs fast IDW interpolation by creating a KDTree +from the input coordinates then uses it to find the k nearest +neighbors for each output point. Weights are calculated based on the +inverse distance to each neighbor, with weights descreasing with +increasing distance.

+

Code inspired by: https://github.com/DahnJ/REM-xarray

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
input_z + array - like + +
+

Array of values at the input points. This can be either a +1-dimensional array, or a 2-dimensional array where each column +(axis=1) represents a different set of values to be interpolated.

+
+ 		+ required +
input_x + array - like + +
+

Array of x-coordinates of the input points.

+
+ 		+ required +
input_y + array - like + +
+

Array of y-coordinates of the input points.

+
+ 		+ required +
output_x + array - like + +
+

Array of x-coordinates where the interpolation is to be computed.

+
+ 		+ required +
output_y + array - like + +
+

Array of y-coordinates where the interpolation is to be computed.

+
+ 		+ required +
p + int or float + +
+

Power function parameter defining how rapidly weightings should +decrease as distance increases. Higher values of p will cause +weights for distant points to decrease rapidly, resulting in +nearby points having more influence on predictions. Defaults to 1.

+
+ 		+ 1 +
k + int + +
+

Number of nearest neighbors to use for interpolation. k=1 is +equivalent to "nearest" neighbour interpolation. Defaults to 10.

+
+ 		+ 10 +
max_dist + int or float + +
+

Restrict neighbouring points to less than this distance. +By default, no distance limit is applied.

+
+ 		+ None +
k_min + int + +
+

If max_dist is provided, some points may end up with less than +k nearest neighbours, potentially producing less reliable +interpolations. Set k_min to set any points with less than +k_min neighbours to NaN. Defaults to 1.

+
+ 		+ 1 +
epsilon + float + +
+

Small value added to distances to prevent division by zero +errors in the case that output coordinates are identical to +input coordinates. Defaults to 1e-12.

+
+ 		+ 1e-12 +
+ + +

Returns:

+ + + + + + + + + + + + + +
Name TypeDescription
interp_values + ndarray + +
+

Interpolated values at the output coordinates. If input_z is +1-dimensional, interp_values will also be 1-dimensional. If +input_z is 2-dimensional, interp_values will have the same +number of rows as input_z, with each column (axis=1) +representing interpolated values for one set of input data.

+
+
+ + +

Examples:

+ 
>>> input_z = [1, 2, 3, 4, 5]
+>>> input_x = [0, 1, 2, 3, 4]
+>>> input_y = [0, 1, 2, 3, 4]
+>>> output_x = [0.5, 1.5, 2.5]
+>>> output_y = [0.5, 1.5, 2.5]
+>>> idw(input_z, input_x, input_y, output_x, output_y, k=2)
+array([1.5, 2.5, 3.5])
+
+ +
+ Source code in eo_tides/utils.py + 
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def idw(
+    input_z,
+    input_x,
+    input_y,
+    output_x,
+    output_y,
+    p=1,
+    k=10,
+    max_dist=None,
+    k_min=1,
+    epsilon=1e-12,
+):
+    """Perform Inverse Distance Weighting (IDW) interpolation.
+
+    This function performs fast IDW interpolation by creating a KDTree
+    from the input coordinates then uses it to find the `k` nearest
+    neighbors for each output point. Weights are calculated based on the
+    inverse distance to each neighbor, with weights descreasing with
+    increasing distance.
+
+    Code inspired by: https://github.com/DahnJ/REM-xarray
+
+    Parameters
+    ----------
+    input_z : array-like
+        Array of values at the input points. This can be either a
+        1-dimensional array, or a 2-dimensional array where each column
+        (axis=1) represents a different set of values to be interpolated.
+    input_x : array-like
+        Array of x-coordinates of the input points.
+    input_y : array-like
+        Array of y-coordinates of the input points.
+    output_x : array-like
+        Array of x-coordinates where the interpolation is to be computed.
+    output_y : array-like
+        Array of y-coordinates where the interpolation is to be computed.
+    p : int or float, optional
+        Power function parameter defining how rapidly weightings should
+        decrease as distance increases. Higher values of `p` will cause
+        weights for distant points to decrease rapidly, resulting in
+        nearby points having more influence on predictions. Defaults to 1.
+    k : int, optional
+        Number of nearest neighbors to use for interpolation. `k=1` is
+        equivalent to "nearest" neighbour interpolation. Defaults to 10.
+    max_dist : int or float, optional
+        Restrict neighbouring points to less than this distance.
+        By default, no distance limit is applied.
+    k_min : int, optional
+        If `max_dist` is provided, some points may end up with less than
+        `k` nearest neighbours, potentially producing less reliable
+        interpolations. Set `k_min` to set any points with less than
+        `k_min` neighbours to NaN. Defaults to 1.
+    epsilon : float, optional
+        Small value added to distances to prevent division by zero
+        errors in the case that output coordinates are identical to
+        input coordinates. Defaults to 1e-12.
+
+    Returns
+    -------
+    interp_values : numpy.ndarray
+        Interpolated values at the output coordinates. If `input_z` is
+        1-dimensional, `interp_values` will also be 1-dimensional. If
+        `input_z` is 2-dimensional, `interp_values` will have the same
+        number of rows as `input_z`, with each column (axis=1)
+        representing interpolated values for one set of input data.
+
+    Examples
+    --------
+    >>> input_z = [1, 2, 3, 4, 5]
+    >>> input_x = [0, 1, 2, 3, 4]
+    >>> input_y = [0, 1, 2, 3, 4]
+    >>> output_x = [0.5, 1.5, 2.5]
+    >>> output_y = [0.5, 1.5, 2.5]
+    >>> idw(input_z, input_x, input_y, output_x, output_y, k=2)
+    array([1.5, 2.5, 3.5])
+
+    """
+    # Convert to numpy arrays
+    input_x = np.atleast_1d(input_x)
+    input_y = np.atleast_1d(input_y)
+    input_z = np.atleast_1d(input_z)
+    output_x = np.atleast_1d(output_x)
+    output_y = np.atleast_1d(output_y)
+
+    # Verify input and outputs have matching lengths
+    if not (input_z.shape[0] == len(input_x) == len(input_y)):
+        raise ValueError("All of `input_z`, `input_x` and `input_y` must be the same length.")
+    if not (len(output_x) == len(output_y)):
+        raise ValueError("Both `output_x` and `output_y` must be the same length.")
+
+    # Verify k is smaller than total number of points, and non-zero
+    if k > input_z.shape[0]:
+        raise ValueError(
+            f"The requested number of nearest neighbours (`k={k}`) "
+            f"is smaller than the total number of points ({input_z.shape[0]}).",
+        )
+    if k == 0:
+        raise ValueError("Interpolation based on `k=0` nearest neighbours is not valid.")
+
+    # Create KDTree to efficiently find nearest neighbours
+    points_xy = np.column_stack((input_y, input_x))
+    tree = KDTree(points_xy)
+
+    # Determine nearest neighbours and distances to each
+    grid_stacked = np.column_stack((output_y, output_x))
+    distances, indices = tree.query(grid_stacked, k=k, workers=-1)
+
+    # If k == 1, add an additional axis for consistency
+    if k == 1:
+        distances = distances[..., np.newaxis]
+        indices = indices[..., np.newaxis]
+
+    # Add small epsilon to distances to prevent division by zero errors
+    # if output coordinates are the same as input coordinates
+    distances = np.maximum(distances, epsilon)
+
+    # Set distances above max to NaN if specified
+    if max_dist is not None:
+        distances[distances > max_dist] = np.nan
+
+    # Calculate weights based on distance to k nearest neighbours.
+    weights = 1 / np.power(distances, p)
+    weights = weights / np.nansum(weights, axis=1).reshape(-1, 1)
+
+    # 1D case: Compute weighted sum of input_z values for each output point
+    if input_z.ndim == 1:
+        interp_values = np.nansum(weights * input_z[indices], axis=1)
+
+    # 2D case: Compute weighted sum for each set of input_z values
+    # weights[..., np.newaxis] adds a dimension for broadcasting
+    else:
+        interp_values = np.nansum(
+            weights[..., np.newaxis] * input_z[indices],
+            axis=1,
+        )
+
+    # Set any points with less than `k_min` valid weights to NaN
+    interp_values[np.isfinite(weights).sum(axis=1) < k_min] = np.nan
+
+    return interp_values
+
+
+
+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/assets/_mkdocstrings.css b/assets/_mkdocstrings.css new file mode 100644 index 0000000..85449ec --- /dev/null +++ b/assets/_mkdocstrings.css @@ -0,0 +1,119 @@ + +/* Avoid breaking parameter names, etc. in table cells. */ +.doc-contents td code { + word-break: normal !important; +} + +/* No line break before first paragraph of descriptions. */ +.doc-md-description, +.doc-md-description>p:first-child { + display: inline; +} + +/* Max width for docstring sections tables. */ +.doc .md-typeset__table, +.doc .md-typeset__table table { + display: table !important; + width: 100%; +} + +.doc .md-typeset__table tr { + display: table-row; +} + +/* Defaults in Spacy table style. */ +.doc-param-default { + float: right; +} + +/* Backward-compatibility: docstring section titles in bold. */ +.doc-section-title { + font-weight: bold; +} + +/* Symbols in Navigation and ToC. */ +:root, +[data-md-color-scheme="default"] { + 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rect.divider{fill:var(--md-default-fg-color--lightest);stroke:var(--md-default-fg-color--lighter)}defs #statediagram-barbEnd{stroke:var(--md-mermaid-edge-color)}.attributeBoxEven,.attributeBoxOdd{fill:var(--md-mermaid-node-bg-color);stroke:var(--md-mermaid-node-fg-color)}.entityBox{fill:var(--md-mermaid-label-bg-color);stroke:var(--md-mermaid-node-fg-color)}.entityLabel{fill:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.relationshipLabelBox{fill:var(--md-mermaid-label-bg-color);fill-opacity:1;background-color:var(--md-mermaid-label-bg-color);opacity:1}.relationshipLabel{fill:var(--md-mermaid-label-fg-color)}.relationshipLine{stroke:var(--md-mermaid-edge-color)}defs #ONE_OR_MORE_END *,defs #ONE_OR_MORE_START *,defs #ONLY_ONE_END *,defs #ONLY_ONE_START *,defs #ZERO_OR_MORE_END *,defs #ZERO_OR_MORE_START *,defs #ZERO_OR_ONE_END *,defs #ZERO_OR_ONE_START *{stroke:var(--md-mermaid-edge-color)!important}defs #ZERO_OR_MORE_END circle,defs #ZERO_OR_MORE_START circle{fill:var(--md-mermaid-label-bg-color)}.actor{fill:var(--md-mermaid-sequence-actor-bg-color);stroke:var(--md-mermaid-sequence-actor-border-color)}text.actor>tspan{fill:var(--md-mermaid-sequence-actor-fg-color);font-family:var(--md-mermaid-font-family)}line{stroke:var(--md-mermaid-sequence-actor-line-color)}.actor-man circle,.actor-man line{fill:var(--md-mermaid-sequence-actorman-bg-color);stroke:var(--md-mermaid-sequence-actorman-line-color)}.messageLine0,.messageLine1{stroke:var(--md-mermaid-sequence-message-line-color)}.note{fill:var(--md-mermaid-sequence-note-bg-color);stroke:var(--md-mermaid-sequence-note-border-color)}.loopText,.loopText>tspan,.messageText,.noteText>tspan{stroke:none;font-family:var(--md-mermaid-font-family)!important}.messageText{fill:var(--md-mermaid-sequence-message-fg-color)}.loopText,.loopText>tspan{fill:var(--md-mermaid-sequence-loop-fg-color)}.noteText>tspan{fill:var(--md-mermaid-sequence-note-fg-color)}#arrowhead path{fill:var(--md-mermaid-sequence-message-line-color);stroke:none}.loopLine{fill:var(--md-mermaid-sequence-loop-bg-color);stroke:var(--md-mermaid-sequence-loop-border-color)}.labelBox{fill:var(--md-mermaid-sequence-label-bg-color);stroke:none}.labelText,.labelText>span{fill:var(--md-mermaid-sequence-label-fg-color);font-family:var(--md-mermaid-font-family)}.sequenceNumber{fill:var(--md-mermaid-sequence-number-fg-color)}rect.rect{fill:var(--md-mermaid-sequence-box-bg-color);stroke:none}rect.rect+text.text{fill:var(--md-mermaid-sequence-box-fg-color)}defs #sequencenumber{fill:var(--md-mermaid-sequence-number-bg-color)!important}";var Gr,za=0;function qa(){return typeof mermaid=="undefined"||mermaid instanceof Element?Tt("https://unpkg.com/mermaid@11/dist/mermaid.min.js"):I(void 0)}function Wn(e){return e.classList.remove("mermaid"),Gr||(Gr=qa().pipe(w(()=>mermaid.initialize({startOnLoad:!1,themeCSS:Fn,sequence:{actorFontSize:"16px",messageFontSize:"16px",noteFontSize:"16px"}})),m(()=>{}),G(1))),Gr.subscribe(()=>so(this,null,function*(){e.classList.add("mermaid");let t=`__mermaid_${za++}`,r=x("div",{class:"mermaid"}),o=e.textContent,{svg:n,fn:i}=yield mermaid.render(t,o),a=r.attachShadow({mode:"closed"});a.innerHTML=n,e.replaceWith(r),i==null||i(a)})),Gr.pipe(m(()=>({ref:e})))}var Un=x("table");function Dn(e){return e.replaceWith(Un),Un.replaceWith(_n(e)),I({ref:e})}function Qa(e){let t=e.find(r=>r.checked)||e[0];return O(...e.map(r=>h(r,"change").pipe(m(()=>R(`label[for="${r.id}"]`))))).pipe(Q(R(`label[for="${t.id}"]`)),m(r=>({active:r})))}function Vn(e,{viewport$:t,target$:r}){let o=R(".tabbed-labels",e),n=P(":scope > input",e),i=Kr("prev");e.append(i);let a=Kr("next");return e.append(a),C(()=>{let s=new g,p=s.pipe(Z(),ie(!0));z([s,ge(e),tt(e)]).pipe(U(p),Le(1,me)).subscribe({next([{active:c},l]){let f=Ve(c),{width:u}=ce(c);e.style.setProperty("--md-indicator-x",`${f.x}px`),e.style.setProperty("--md-indicator-width",`${u}px`);let d=pr(o);(f.xd.x+l.width)&&o.scrollTo({left:Math.max(0,f.x-16),behavior:"smooth"})},complete(){e.style.removeProperty("--md-indicator-x"),e.style.removeProperty("--md-indicator-width")}}),z([Ne(o),ge(o)]).pipe(U(p)).subscribe(([c,l])=>{let f=St(o);i.hidden=c.x<16,a.hidden=c.x>f.width-l.width-16}),O(h(i,"click").pipe(m(()=>-1)),h(a,"click").pipe(m(()=>1))).pipe(U(p)).subscribe(c=>{let{width:l}=ce(o);o.scrollBy({left:l*c,behavior:"smooth"})}),r.pipe(U(p),b(c=>n.includes(c))).subscribe(c=>c.click()),o.classList.add("tabbed-labels--linked");for(let c of n){let l=R(`label[for="${c.id}"]`);l.replaceChildren(x("a",{href:`#${l.htmlFor}`,tabIndex:-1},...Array.from(l.childNodes))),h(l.firstElementChild,"click").pipe(U(p),b(f=>!(f.metaKey||f.ctrlKey)),w(f=>{f.preventDefault(),f.stopPropagation()})).subscribe(()=>{history.replaceState({},"",`#${l.htmlFor}`),l.click()})}return B("content.tabs.link")&&s.pipe(Ce(1),re(t)).subscribe(([{active:c},{offset:l}])=>{let f=c.innerText.trim();if(c.hasAttribute("data-md-switching"))c.removeAttribute("data-md-switching");else{let u=e.offsetTop-l.y;for(let y of P("[data-tabs]"))for(let M of P(":scope > input",y)){let X=R(`label[for="${M.id}"]`);if(X!==c&&X.innerText.trim()===f){X.setAttribute("data-md-switching",""),M.click();break}}window.scrollTo({top:e.offsetTop-u});let d=__md_get("__tabs")||[];__md_set("__tabs",[...new Set([f,...d])])}}),s.pipe(U(p)).subscribe(()=>{for(let c of P("audio, video",e))c.pause()}),Qa(n).pipe(w(c=>s.next(c)),_(()=>s.complete()),m(c=>$({ref:e},c)))}).pipe(Ke(se))}function Nn(e,{viewport$:t,target$:r,print$:o}){return O(...P(".annotate:not(.highlight)",e).map(n=>$n(n,{target$:r,print$:o})),...P("pre:not(.mermaid) > code",e).map(n=>In(n,{target$:r,print$:o})),...P("pre.mermaid",e).map(n=>Wn(n)),...P("table:not([class])",e).map(n=>Dn(n)),...P("details",e).map(n=>jn(n,{target$:r,print$:o})),...P("[data-tabs]",e).map(n=>Vn(n,{viewport$:t,target$:r})),...P("[title]",e).filter(()=>B("content.tooltips")).map(n=>mt(n,{viewport$:t})))}function Ka(e,{alert$:t}){return t.pipe(v(r=>O(I(!0),I(!1).pipe(Ge(2e3))).pipe(m(o=>({message:r,active:o})))))}function zn(e,t){let r=R(".md-typeset",e);return C(()=>{let o=new g;return o.subscribe(({message:n,active:i})=>{e.classList.toggle("md-dialog--active",i),r.textContent=n}),Ka(e,t).pipe(w(n=>o.next(n)),_(()=>o.complete()),m(n=>$({ref:e},n)))})}var Ya=0;function Ba(e,t){document.body.append(e);let{width:r}=ce(e);e.style.setProperty("--md-tooltip-width",`${r}px`),e.remove();let o=cr(t),n=typeof o!="undefined"?Ne(o):I({x:0,y:0}),i=O(et(t),$t(t)).pipe(K());return z([i,n]).pipe(m(([a,s])=>{let{x:p,y:c}=Ve(t),l=ce(t),f=t.closest("table");return f&&t.parentElement&&(p+=f.offsetLeft+t.parentElement.offsetLeft,c+=f.offsetTop+t.parentElement.offsetTop),{active:a,offset:{x:p-s.x+l.width/2-r/2,y:c-s.y+l.height+8}}}))}function qn(e){let t=e.title;if(!t.length)return S;let r=`__tooltip_${Ya++}`,o=Rt(r,"inline"),n=R(".md-typeset",o);return n.innerHTML=t,C(()=>{let i=new g;return i.subscribe({next({offset:a}){o.style.setProperty("--md-tooltip-x",`${a.x}px`),o.style.setProperty("--md-tooltip-y",`${a.y}px`)},complete(){o.style.removeProperty("--md-tooltip-x"),o.style.removeProperty("--md-tooltip-y")}}),O(i.pipe(b(({active:a})=>a)),i.pipe(_e(250),b(({active:a})=>!a))).subscribe({next({active:a}){a?(e.insertAdjacentElement("afterend",o),e.setAttribute("aria-describedby",r),e.removeAttribute("title")):(o.remove(),e.removeAttribute("aria-describedby"),e.setAttribute("title",t))},complete(){o.remove(),e.removeAttribute("aria-describedby"),e.setAttribute("title",t)}}),i.pipe(Le(16,me)).subscribe(({active:a})=>{o.classList.toggle("md-tooltip--active",a)}),i.pipe(pt(125,me),b(()=>!!e.offsetParent),m(()=>e.offsetParent.getBoundingClientRect()),m(({x:a})=>a)).subscribe({next(a){a?o.style.setProperty("--md-tooltip-0",`${-a}px`):o.style.removeProperty("--md-tooltip-0")},complete(){o.style.removeProperty("--md-tooltip-0")}}),Ba(o,e).pipe(w(a=>i.next(a)),_(()=>i.complete()),m(a=>$({ref:e},a)))}).pipe(Ke(se))}function 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g;r.subscribe({next({active:n}){e.classList.toggle("md-header__title--active",n)},complete(){e.classList.remove("md-header__title--active")}});let o=fe(".md-content h1");return typeof o=="undefined"?S:Ja(o,t).pipe(w(n=>r.next(n)),_(()=>r.complete()),m(n=>$({ref:e},n)))})}function Bn(e,{viewport$:t,header$:r}){let o=r.pipe(m(({height:i})=>i),K()),n=o.pipe(v(()=>ge(e).pipe(m(({height:i})=>({top:e.offsetTop,bottom:e.offsetTop+i})),ee("bottom"))));return z([o,n,t]).pipe(m(([i,{top:a,bottom:s},{offset:{y:p},size:{height:c}}])=>(c=Math.max(0,c-Math.max(0,a-p,i)-Math.max(0,c+p-s)),{offset:a-i,height:c,active:a-i<=p})),K((i,a)=>i.offset===a.offset&&i.height===a.height&&i.active===a.active))}function Xa(e){let t=__md_get("__palette")||{index:e.findIndex(o=>matchMedia(o.getAttribute("data-md-color-media")).matches)},r=Math.max(0,Math.min(t.index,e.length-1));return I(...e).pipe(ne(o=>h(o,"change").pipe(m(()=>o))),Q(e[r]),m(o=>({index:e.indexOf(o),color:{media:o.getAttribute("data-md-color-media"),scheme:o.getAttribute("data-md-color-scheme"),primary:o.getAttribute("data-md-color-primary"),accent:o.getAttribute("data-md-color-accent")}})),G(1))}function Gn(e){let t=P("input",e),r=x("meta",{name:"theme-color"});document.head.appendChild(r);let o=x("meta",{name:"color-scheme"});document.head.appendChild(o);let n=Pt("(prefers-color-scheme: light)");return C(()=>{let i=new g;return i.subscribe(a=>{if(document.body.setAttribute("data-md-color-switching",""),a.color.media==="(prefers-color-scheme)"){let s=matchMedia("(prefers-color-scheme: light)"),p=document.querySelector(s.matches?"[data-md-color-media='(prefers-color-scheme: light)']":"[data-md-color-media='(prefers-color-scheme: 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Jr=Lt(Br());function Za(e){e.setAttribute("data-md-copying","");let t=e.closest("[data-copy]"),r=t?t.getAttribute("data-copy"):e.innerText;return e.removeAttribute("data-md-copying"),r.trimEnd()}function Xn({alert$:e}){Jr.default.isSupported()&&new j(t=>{new Jr.default("[data-clipboard-target], [data-clipboard-text]",{text:r=>r.getAttribute("data-clipboard-text")||Za(R(r.getAttribute("data-clipboard-target")))}).on("success",r=>t.next(r))}).pipe(w(t=>{t.trigger.focus()}),m(()=>Ee("clipboard.copied"))).subscribe(e)}function Zn(e,t){return e.protocol=t.protocol,e.hostname=t.hostname,e}function es(e,t){let r=new Map;for(let o of P("url",e)){let n=R("loc",o),i=[Zn(new URL(n.textContent),t)];r.set(`${i[0]}`,i);for(let a of P("[rel=alternate]",o)){let s=a.getAttribute("href");s!=null&&i.push(Zn(new URL(s),t))}}return r}function ur(e){return fn(new URL("sitemap.xml",e)).pipe(m(t=>es(t,new URL(e))),de(()=>I(new Map)))}function ts(e,t){if(!(e.target instanceof Element))return S;let r=e.target.closest("a");if(r===null)return S;if(r.target||e.metaKey||e.ctrlKey)return S;let o=new URL(r.href);return o.search=o.hash="",t.has(`${o}`)?(e.preventDefault(),I(new URL(r.href))):S}function ei(e){let t=new Map;for(let r of P(":scope > *",e.head))t.set(r.outerHTML,r);return t}function ti(e){for(let t of P("[href], [src]",e))for(let r of["href","src"]){let o=t.getAttribute(r);if(o&&!/^(?:[a-z]+:)?\/\//i.test(o)){t[r]=t[r];break}}return I(e)}function rs(e){for(let o of["[data-md-component=announce]","[data-md-component=container]","[data-md-component=header-topic]","[data-md-component=outdated]","[data-md-component=logo]","[data-md-component=skip]",...B("navigation.tabs.sticky")?["[data-md-component=tabs]"]:[]]){let n=fe(o),i=fe(o,e);typeof n!="undefined"&&typeof i!="undefined"&&n.replaceWith(i)}let t=ei(document);for(let[o,n]of ei(e))t.has(o)?t.delete(o):document.head.appendChild(n);for(let o of t.values()){let n=o.getAttribute("name");n!=="theme-color"&&n!=="color-scheme"&&o.remove()}let r=Se("container");return Ue(P("script",r)).pipe(v(o=>{let n=e.createElement("script");if(o.src){for(let i of o.getAttributeNames())n.setAttribute(i,o.getAttribute(i));return o.replaceWith(n),new j(i=>{n.onload=()=>i.complete()})}else return n.textContent=o.textContent,o.replaceWith(n),S}),Z(),ie(document))}function ri({location$:e,viewport$:t,progress$:r}){let o=xe();if(location.protocol==="file:")return S;let n=ur(o.base);I(document).subscribe(ti);let i=h(document.body,"click").pipe(He(n),v(([p,c])=>ts(p,c)),pe()),a=h(window,"popstate").pipe(m(ye),pe());i.pipe(re(t)).subscribe(([p,{offset:c}])=>{history.replaceState(c,""),history.pushState(null,"",p)}),O(i,a).subscribe(e);let s=e.pipe(ee("pathname"),v(p=>mn(p,{progress$:r}).pipe(de(()=>(lt(p,!0),S)))),v(ti),v(rs),pe());return O(s.pipe(re(e,(p,c)=>c)),s.pipe(v(()=>e),ee("pathname"),v(()=>e),ee("hash")),e.pipe(K((p,c)=>p.pathname===c.pathname&&p.hash===c.hash),v(()=>i),w(()=>history.back()))).subscribe(p=>{var c,l;history.state!==null||!p.hash?window.scrollTo(0,(l=(c=history.state)==null?void 0:c.y)!=null?l:0):(history.scrollRestoration="auto",cn(p.hash),history.scrollRestoration="manual")}),e.subscribe(()=>{history.scrollRestoration="manual"}),h(window,"beforeunload").subscribe(()=>{history.scrollRestoration="auto"}),t.pipe(ee("offset"),_e(100)).subscribe(({offset:p})=>{history.replaceState(p,"")}),s}var oi=Lt(qr());function ni(e){let t=e.separator.split("|").map(n=>n.replace(/(\(\?[!=<][^)]+\))/g,"").length===0?"\uFFFD":n).join("|"),r=new RegExp(t,"img"),o=(n,i,a)=>`${i}${a}`;return n=>{n=n.replace(/[\s*+\-:~^]+/g," ").trim();let i=new RegExp(`(^|${e.separator}|)(${n.replace(/[|\\{}()[\]^$+*?.-]/g,"\\$&").replace(r,"|")})`,"img");return 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r=`https://api.github.com/users/${e}`;return je(r).pipe(m(o=>({repositories:o.public_repos})),De({}))}}function di(e,t){let r=`https://${e}/api/v4/projects/${encodeURIComponent(t)}`;return st(je(`${r}/releases/permalink/latest`).pipe(de(()=>S),m(({tag_name:o})=>({version:o})),De({})),je(r).pipe(de(()=>S),m(({star_count:o,forks_count:n})=>({stars:o,forks:n})),De({}))).pipe(m(([o,n])=>$($({},o),n)))}function hi(e){let t=e.match(/^.+github\.com\/([^/]+)\/?([^/]+)?/i);if(t){let[,r,o]=t;return ui(r,o)}if(t=e.match(/^.+?([^/]*gitlab[^/]+)\/(.+?)\/?$/i),t){let[,r,o]=t;return di(r,o)}return S}var cs;function ps(e){return cs||(cs=C(()=>{let t=__md_get("__source",sessionStorage);if(t)return I(t);if(ae("consent").length){let o=__md_get("__consent");if(!(o&&o.github))return S}return hi(e.href).pipe(w(o=>__md_set("__source",o,sessionStorage)))}).pipe(de(()=>S),b(t=>Object.keys(t).length>0),m(t=>({facts:t})),G(1)))}function bi(e){let t=R(":scope > :last-child",e);return C(()=>{let r=new g;return 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rt=Qn(Se("header"),{viewport$:Oe}),Ft=ot.pipe(m(()=>Se("main")),v(e=>Bn(e,{viewport$:Oe,header$:rt})),G(1)),hs=O(...ae("consent").map(e=>xn(e,{target$:Mt})),...ae("dialog").map(e=>zn(e,{alert$:to})),...ae("header").map(e=>Kn(e,{viewport$:Oe,header$:rt,main$:Ft})),...ae("palette").map(e=>Gn(e)),...ae("progress").map(e=>Jn(e,{progress$:ro})),...ae("search").map(e=>mi(e,{index$:Li,keyboard$:eo})),...ae("source").map(e=>bi(e))),bs=C(()=>O(...ae("announce").map(e=>yn(e)),...ae("content").map(e=>Nn(e,{viewport$:Oe,target$:Mt,print$:Mi})),...ae("content").map(e=>B("search.highlight")?fi(e,{index$:Li,location$:Wt}):S),...ae("header-title").map(e=>Yn(e,{viewport$:Oe,header$:rt})),...ae("sidebar").map(e=>e.getAttribute("data-md-type")==="navigation"?Nr(Oi,()=>Xr(e,{viewport$:Oe,header$:rt,main$:Ft})):Nr(hr,()=>Xr(e,{viewport$:Oe,header$:rt,main$:Ft}))),...ae("tabs").map(e=>vi(e,{viewport$:Oe,header$:rt})),...ae("toc").map(e=>gi(e,{viewport$:Oe,header$:rt,main$:Ft,target$:Mt})),...ae("top").map(e=>yi(e,{viewport$:Oe,header$:rt,main$:Ft,target$:Mt})))),_i=ot.pipe(v(()=>bs),Re(hs),G(1));_i.subscribe();window.document$=ot;window.location$=Wt;window.target$=Mt;window.keyboard$=eo;window.viewport$=Oe;window.tablet$=hr;window.screen$=Oi;window.print$=Mi;window.alert$=to;window.progress$=ro;window.component$=_i;})(); 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"sourcesContent": ["(function (global, factory) {\n typeof exports === 'object' && typeof module !== 'undefined' ? factory() :\n typeof define === 'function' && define.amd ? define(factory) :\n (factory());\n}(this, (function () { 'use strict';\n\n /**\n * Applies the :focus-visible polyfill at the given scope.\n * A scope in this case is either the top-level Document or a Shadow Root.\n *\n * @param {(Document|ShadowRoot)} scope\n * @see https://github.com/WICG/focus-visible\n */\n function applyFocusVisiblePolyfill(scope) {\n var hadKeyboardEvent = true;\n var hadFocusVisibleRecently = false;\n var hadFocusVisibleRecentlyTimeout = null;\n\n var inputTypesAllowlist = {\n text: true,\n search: true,\n url: true,\n tel: true,\n email: true,\n password: true,\n number: true,\n date: true,\n month: true,\n week: true,\n time: true,\n datetime: true,\n 'datetime-local': true\n };\n\n /**\n * Helper function for legacy browsers and iframes which sometimes focus\n * elements like document, body, and non-interactive SVG.\n * @param {Element} el\n */\n function isValidFocusTarget(el) {\n if (\n el &&\n el !== document &&\n el.nodeName !== 'HTML' &&\n el.nodeName !== 'BODY' &&\n 'classList' in el &&\n 'contains' in el.classList\n ) {\n return true;\n }\n return false;\n }\n\n /**\n * Computes whether the given element should automatically trigger the\n * `focus-visible` class being added, i.e. whether it should always match\n * `:focus-visible` when focused.\n * @param {Element} el\n * @return {boolean}\n */\n function focusTriggersKeyboardModality(el) {\n var type = el.type;\n var tagName = el.tagName;\n\n if (tagName === 'INPUT' && inputTypesAllowlist[type] && !el.readOnly) {\n return true;\n }\n\n if (tagName === 'TEXTAREA' && !el.readOnly) {\n return true;\n }\n\n if (el.isContentEditable) {\n return true;\n }\n\n return false;\n }\n\n /**\n * Add the `focus-visible` class to the given element if it was not added by\n * the author.\n * @param {Element} el\n */\n function addFocusVisibleClass(el) {\n if (el.classList.contains('focus-visible')) {\n return;\n }\n el.classList.add('focus-visible');\n el.setAttribute('data-focus-visible-added', '');\n }\n\n /**\n * Remove the `focus-visible` class from the given element if it was not\n * originally added by the author.\n * @param {Element} el\n */\n function removeFocusVisibleClass(el) {\n if (!el.hasAttribute('data-focus-visible-added')) {\n return;\n }\n el.classList.remove('focus-visible');\n el.removeAttribute('data-focus-visible-added');\n }\n\n /**\n * If the most recent user interaction was via the keyboard;\n * and the key press did not include a meta, alt/option, or control key;\n * then the modality is keyboard. Otherwise, the modality is not keyboard.\n * Apply `focus-visible` to any current active element and keep track\n * of our keyboard modality state with `hadKeyboardEvent`.\n * @param {KeyboardEvent} e\n */\n function onKeyDown(e) {\n if (e.metaKey || e.altKey || e.ctrlKey) {\n return;\n }\n\n if (isValidFocusTarget(scope.activeElement)) {\n addFocusVisibleClass(scope.activeElement);\n }\n\n hadKeyboardEvent = true;\n }\n\n /**\n * If at any point a user clicks with a pointing device, ensure that we change\n * the modality away from keyboard.\n * This avoids the situation where a user presses a key on an already focused\n * element, and then clicks on a different element, focusing it with a\n * pointing device, while we still think we're in keyboard modality.\n * @param {Event} e\n */\n function onPointerDown(e) {\n hadKeyboardEvent = false;\n }\n\n /**\n * On `focus`, add the `focus-visible` class to the target if:\n * - the target received focus as a result of keyboard navigation, or\n * - the event target is an element that will likely require interaction\n * via the keyboard (e.g. a text box)\n * @param {Event} e\n */\n function onFocus(e) {\n // Prevent IE from focusing the document or HTML element.\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (hadKeyboardEvent || focusTriggersKeyboardModality(e.target)) {\n addFocusVisibleClass(e.target);\n }\n }\n\n /**\n * On `blur`, remove the `focus-visible` class from the target.\n * @param {Event} e\n */\n function onBlur(e) {\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (\n e.target.classList.contains('focus-visible') ||\n e.target.hasAttribute('data-focus-visible-added')\n ) {\n // To detect a tab/window switch, we look for a blur event followed\n // rapidly by a visibility change.\n // If we don't see a visibility change within 100ms, it's probably a\n // regular focus change.\n hadFocusVisibleRecently = true;\n window.clearTimeout(hadFocusVisibleRecentlyTimeout);\n hadFocusVisibleRecentlyTimeout = window.setTimeout(function() {\n hadFocusVisibleRecently = false;\n }, 100);\n removeFocusVisibleClass(e.target);\n }\n }\n\n /**\n * If the user changes tabs, keep track of whether or not the previously\n * focused element had .focus-visible.\n * @param {Event} e\n */\n function onVisibilityChange(e) {\n if (document.visibilityState === 'hidden') {\n // If the tab becomes active again, the browser will handle calling focus\n // on the element (Safari actually calls it twice).\n // If this tab change caused a blur on an element with focus-visible,\n // re-apply the class when the user switches back to the tab.\n if (hadFocusVisibleRecently) {\n hadKeyboardEvent = true;\n }\n addInitialPointerMoveListeners();\n }\n }\n\n /**\n * Add a group of listeners to detect usage of any pointing devices.\n * These listeners will be added when the polyfill first loads, and anytime\n * the window is blurred, so that they are active when the window regains\n * focus.\n */\n function addInitialPointerMoveListeners() {\n document.addEventListener('mousemove', onInitialPointerMove);\n document.addEventListener('mousedown', onInitialPointerMove);\n document.addEventListener('mouseup', onInitialPointerMove);\n document.addEventListener('pointermove', onInitialPointerMove);\n document.addEventListener('pointerdown', onInitialPointerMove);\n document.addEventListener('pointerup', onInitialPointerMove);\n document.addEventListener('touchmove', onInitialPointerMove);\n document.addEventListener('touchstart', onInitialPointerMove);\n document.addEventListener('touchend', onInitialPointerMove);\n }\n\n function removeInitialPointerMoveListeners() {\n document.removeEventListener('mousemove', onInitialPointerMove);\n document.removeEventListener('mousedown', onInitialPointerMove);\n document.removeEventListener('mouseup', onInitialPointerMove);\n document.removeEventListener('pointermove', onInitialPointerMove);\n document.removeEventListener('pointerdown', onInitialPointerMove);\n document.removeEventListener('pointerup', onInitialPointerMove);\n document.removeEventListener('touchmove', onInitialPointerMove);\n document.removeEventListener('touchstart', onInitialPointerMove);\n document.removeEventListener('touchend', onInitialPointerMove);\n }\n\n /**\n * When the polfyill first loads, assume the user is in keyboard modality.\n * If any event is received from a pointing device (e.g. mouse, pointer,\n * touch), turn off keyboard modality.\n * This accounts for situations where focus enters the page from the URL bar.\n * @param {Event} e\n */\n function onInitialPointerMove(e) {\n // Work around a Safari quirk that fires a mousemove on whenever the\n // window blurs, even if you're tabbing out of the page. \u00AF\\_(\u30C4)_/\u00AF\n if (e.target.nodeName && e.target.nodeName.toLowerCase() === 'html') {\n return;\n }\n\n hadKeyboardEvent = false;\n removeInitialPointerMoveListeners();\n }\n\n // For some kinds of state, we are interested in changes at the global scope\n // only. For example, global pointer input, global key presses and global\n // visibility change should affect the state at every scope:\n document.addEventListener('keydown', onKeyDown, true);\n document.addEventListener('mousedown', onPointerDown, true);\n document.addEventListener('pointerdown', onPointerDown, true);\n document.addEventListener('touchstart', onPointerDown, true);\n document.addEventListener('visibilitychange', onVisibilityChange, true);\n\n addInitialPointerMoveListeners();\n\n // For focus and blur, we specifically care about state changes in the local\n // scope. This is because focus / blur events that originate from within a\n // shadow root are not re-dispatched from the host element if it was already\n // the active element in its own scope:\n scope.addEventListener('focus', onFocus, true);\n scope.addEventListener('blur', onBlur, true);\n\n // We detect that a node is a ShadowRoot by ensuring that it is a\n // DocumentFragment and also has a host property. This check covers native\n // implementation and polyfill implementation transparently. If we only cared\n // about the native implementation, we could just check if the scope was\n // an instance of a ShadowRoot.\n if (scope.nodeType === Node.DOCUMENT_FRAGMENT_NODE && scope.host) {\n // Since a ShadowRoot is a special kind of DocumentFragment, it does not\n // have a root element to add a class to. So, we add this attribute to the\n // host element instead:\n scope.host.setAttribute('data-js-focus-visible', '');\n } else if (scope.nodeType === Node.DOCUMENT_NODE) {\n document.documentElement.classList.add('js-focus-visible');\n document.documentElement.setAttribute('data-js-focus-visible', '');\n }\n }\n\n // It is important to wrap all references to global window and document in\n // these checks to support server-side rendering use cases\n // @see https://github.com/WICG/focus-visible/issues/199\n if (typeof window !== 'undefined' && typeof document !== 'undefined') {\n // Make the polyfill helper globally available. This can be used as a signal\n // to interested libraries that wish to coordinate with the polyfill for e.g.,\n // applying the polyfill to a shadow root:\n window.applyFocusVisiblePolyfill = applyFocusVisiblePolyfill;\n\n // Notify interested libraries of the polyfill's presence, in case the\n // polyfill was loaded lazily:\n var event;\n\n try {\n event = new CustomEvent('focus-visible-polyfill-ready');\n } catch (error) {\n // IE11 does not support using CustomEvent as a constructor directly:\n event = document.createEvent('CustomEvent');\n event.initCustomEvent('focus-visible-polyfill-ready', false, false, {});\n }\n\n window.dispatchEvent(event);\n }\n\n if (typeof document !== 'undefined') {\n // Apply the polyfill to the global document, so that no JavaScript\n // coordination is required to use the polyfill in the top-level document:\n applyFocusVisiblePolyfill(document);\n }\n\n})));\n", "/*!\n * escape-html\n * Copyright(c) 2012-2013 TJ Holowaychuk\n * Copyright(c) 2015 Andreas Lubbe\n * Copyright(c) 2015 Tiancheng \"Timothy\" Gu\n * MIT Licensed\n */\n\n'use strict';\n\n/**\n * Module variables.\n * @private\n */\n\nvar matchHtmlRegExp = /[\"'&<>]/;\n\n/**\n * Module exports.\n * @public\n */\n\nmodule.exports = escapeHtml;\n\n/**\n * Escape special characters in the given string of html.\n *\n * @param {string} string The string to escape for inserting into HTML\n * @return {string}\n * @public\n */\n\nfunction escapeHtml(string) {\n var str = '' + string;\n var match = matchHtmlRegExp.exec(str);\n\n if (!match) {\n return str;\n }\n\n var escape;\n var html = '';\n var index = 0;\n var lastIndex = 0;\n\n for (index = match.index; index < str.length; index++) {\n switch (str.charCodeAt(index)) {\n case 34: // \"\n escape = '"';\n break;\n case 38: // &\n escape = '&';\n break;\n case 39: // '\n escape = ''';\n break;\n case 60: // <\n escape = '<';\n break;\n case 62: // >\n escape = '>';\n break;\n default:\n continue;\n }\n\n if (lastIndex !== index) {\n html += str.substring(lastIndex, index);\n }\n\n lastIndex = index + 1;\n html += escape;\n }\n\n return lastIndex !== index\n ? html + str.substring(lastIndex, index)\n : html;\n}\n", "/*!\n * clipboard.js v2.0.11\n * https://clipboardjs.com/\n *\n * Licensed MIT \u00A9 Zeno Rocha\n */\n(function webpackUniversalModuleDefinition(root, factory) {\n\tif(typeof exports === 'object' && typeof module === 'object')\n\t\tmodule.exports = factory();\n\telse if(typeof define === 'function' && define.amd)\n\t\tdefine([], factory);\n\telse if(typeof exports === 'object')\n\t\texports[\"ClipboardJS\"] = factory();\n\telse\n\t\troot[\"ClipboardJS\"] = factory();\n})(this, function() {\nreturn /******/ (function() { // webpackBootstrap\n/******/ \tvar __webpack_modules__ = ({\n\n/***/ 686:\n/***/ (function(__unused_webpack_module, __webpack_exports__, __webpack_require__) {\n\n\"use strict\";\n\n// EXPORTS\n__webpack_require__.d(__webpack_exports__, {\n \"default\": function() { return /* binding */ clipboard; }\n});\n\n// EXTERNAL MODULE: ./node_modules/tiny-emitter/index.js\nvar tiny_emitter = __webpack_require__(279);\nvar tiny_emitter_default = /*#__PURE__*/__webpack_require__.n(tiny_emitter);\n// EXTERNAL MODULE: ./node_modules/good-listener/src/listen.js\nvar listen = __webpack_require__(370);\nvar listen_default = /*#__PURE__*/__webpack_require__.n(listen);\n// EXTERNAL MODULE: ./node_modules/select/src/select.js\nvar src_select = __webpack_require__(817);\nvar select_default = /*#__PURE__*/__webpack_require__.n(src_select);\n;// CONCATENATED MODULE: ./src/common/command.js\n/**\n * Executes a given operation type.\n * @param {String} type\n * @return {Boolean}\n */\nfunction command(type) {\n try {\n return document.execCommand(type);\n } catch (err) {\n return false;\n }\n}\n;// CONCATENATED MODULE: ./src/actions/cut.js\n\n\n/**\n * Cut action wrapper.\n * @param {String|HTMLElement} target\n * @return {String}\n */\n\nvar ClipboardActionCut = function ClipboardActionCut(target) {\n var selectedText = select_default()(target);\n command('cut');\n return selectedText;\n};\n\n/* harmony default export */ var actions_cut = (ClipboardActionCut);\n;// CONCATENATED MODULE: ./src/common/create-fake-element.js\n/**\n * Creates a fake textarea element with a value.\n * @param {String} value\n * @return {HTMLElement}\n */\nfunction createFakeElement(value) {\n var isRTL = document.documentElement.getAttribute('dir') === 'rtl';\n var fakeElement = document.createElement('textarea'); // Prevent zooming on iOS\n\n fakeElement.style.fontSize = '12pt'; // Reset box model\n\n fakeElement.style.border = '0';\n fakeElement.style.padding = '0';\n fakeElement.style.margin = '0'; // Move element out of screen horizontally\n\n fakeElement.style.position = 'absolute';\n fakeElement.style[isRTL ? 'right' : 'left'] = '-9999px'; // Move element to the same position vertically\n\n var yPosition = window.pageYOffset || document.documentElement.scrollTop;\n fakeElement.style.top = \"\".concat(yPosition, \"px\");\n fakeElement.setAttribute('readonly', '');\n fakeElement.value = value;\n return fakeElement;\n}\n;// CONCATENATED MODULE: ./src/actions/copy.js\n\n\n\n/**\n * Create fake copy action wrapper using a fake element.\n * @param {String} target\n * @param {Object} options\n * @return {String}\n */\n\nvar fakeCopyAction = function fakeCopyAction(value, options) {\n var fakeElement = createFakeElement(value);\n options.container.appendChild(fakeElement);\n var selectedText = select_default()(fakeElement);\n command('copy');\n fakeElement.remove();\n return selectedText;\n};\n/**\n * Copy action wrapper.\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @return {String}\n */\n\n\nvar ClipboardActionCopy = function ClipboardActionCopy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n var selectedText = '';\n\n if (typeof target === 'string') {\n selectedText = fakeCopyAction(target, options);\n } else if (target instanceof HTMLInputElement && !['text', 'search', 'url', 'tel', 'password'].includes(target === null || target === void 0 ? void 0 : target.type)) {\n // If input type doesn't support `setSelectionRange`. Simulate it. https://developer.mozilla.org/en-US/docs/Web/API/HTMLInputElement/setSelectionRange\n selectedText = fakeCopyAction(target.value, options);\n } else {\n selectedText = select_default()(target);\n command('copy');\n }\n\n return selectedText;\n};\n\n/* harmony default export */ var actions_copy = (ClipboardActionCopy);\n;// CONCATENATED MODULE: ./src/actions/default.js\nfunction _typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { _typeof = function _typeof(obj) { return typeof obj; }; } else { _typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return _typeof(obj); }\n\n\n\n/**\n * Inner function which performs selection from either `text` or `target`\n * properties and then executes copy or cut operations.\n * @param {Object} options\n */\n\nvar ClipboardActionDefault = function ClipboardActionDefault() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n // Defines base properties passed from constructor.\n var _options$action = options.action,\n action = _options$action === void 0 ? 'copy' : _options$action,\n container = options.container,\n target = options.target,\n text = options.text; // Sets the `action` to be performed which can be either 'copy' or 'cut'.\n\n if (action !== 'copy' && action !== 'cut') {\n throw new Error('Invalid \"action\" value, use either \"copy\" or \"cut\"');\n } // Sets the `target` property using an element that will be have its content copied.\n\n\n if (target !== undefined) {\n if (target && _typeof(target) === 'object' && target.nodeType === 1) {\n if (action === 'copy' && target.hasAttribute('disabled')) {\n throw new Error('Invalid \"target\" attribute. Please use \"readonly\" instead of \"disabled\" attribute');\n }\n\n if (action === 'cut' && (target.hasAttribute('readonly') || target.hasAttribute('disabled'))) {\n throw new Error('Invalid \"target\" attribute. You can\\'t cut text from elements with \"readonly\" or \"disabled\" attributes');\n }\n } else {\n throw new Error('Invalid \"target\" value, use a valid Element');\n }\n } // Define selection strategy based on `text` property.\n\n\n if (text) {\n return actions_copy(text, {\n container: container\n });\n } // Defines which selection strategy based on `target` property.\n\n\n if (target) {\n return action === 'cut' ? actions_cut(target) : actions_copy(target, {\n container: container\n });\n }\n};\n\n/* harmony default export */ var actions_default = (ClipboardActionDefault);\n;// CONCATENATED MODULE: ./src/clipboard.js\nfunction clipboard_typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { clipboard_typeof = function _typeof(obj) { return typeof obj; }; } else { clipboard_typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return clipboard_typeof(obj); }\n\nfunction _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\nfunction _defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } }\n\nfunction _createClass(Constructor, protoProps, staticProps) { if (protoProps) _defineProperties(Constructor.prototype, protoProps); if (staticProps) _defineProperties(Constructor, staticProps); return Constructor; }\n\nfunction _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function\"); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, writable: true, configurable: true } }); if (superClass) _setPrototypeOf(subClass, superClass); }\n\nfunction _setPrototypeOf(o, p) { _setPrototypeOf = Object.setPrototypeOf || function _setPrototypeOf(o, p) { o.__proto__ = p; return o; }; return _setPrototypeOf(o, p); }\n\nfunction _createSuper(Derived) { var hasNativeReflectConstruct = _isNativeReflectConstruct(); return function _createSuperInternal() { var Super = _getPrototypeOf(Derived), result; if (hasNativeReflectConstruct) { var NewTarget = _getPrototypeOf(this).constructor; result = Reflect.construct(Super, arguments, NewTarget); } else { result = Super.apply(this, arguments); } return _possibleConstructorReturn(this, result); }; }\n\nfunction _possibleConstructorReturn(self, call) { if (call && (clipboard_typeof(call) === \"object\" || typeof call === \"function\")) { return call; } return _assertThisInitialized(self); }\n\nfunction _assertThisInitialized(self) { if (self === void 0) { throw new ReferenceError(\"this hasn't been initialised - super() hasn't been called\"); } return self; }\n\nfunction _isNativeReflectConstruct() { if (typeof Reflect === \"undefined\" || !Reflect.construct) return false; if (Reflect.construct.sham) return false; if (typeof Proxy === \"function\") return true; try { Date.prototype.toString.call(Reflect.construct(Date, [], function () {})); return true; } catch (e) { return false; } }\n\nfunction _getPrototypeOf(o) { _getPrototypeOf = Object.setPrototypeOf ? Object.getPrototypeOf : function _getPrototypeOf(o) { return o.__proto__ || Object.getPrototypeOf(o); }; return _getPrototypeOf(o); }\n\n\n\n\n\n\n/**\n * Helper function to retrieve attribute value.\n * @param {String} suffix\n * @param {Element} element\n */\n\nfunction getAttributeValue(suffix, element) {\n var attribute = \"data-clipboard-\".concat(suffix);\n\n if (!element.hasAttribute(attribute)) {\n return;\n }\n\n return element.getAttribute(attribute);\n}\n/**\n * Base class which takes one or more elements, adds event listeners to them,\n * and instantiates a new `ClipboardAction` on each click.\n */\n\n\nvar Clipboard = /*#__PURE__*/function (_Emitter) {\n _inherits(Clipboard, _Emitter);\n\n var _super = _createSuper(Clipboard);\n\n /**\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n * @param {Object} options\n */\n function Clipboard(trigger, options) {\n var _this;\n\n _classCallCheck(this, Clipboard);\n\n _this = _super.call(this);\n\n _this.resolveOptions(options);\n\n _this.listenClick(trigger);\n\n return _this;\n }\n /**\n * Defines if attributes would be resolved using internal setter functions\n * or custom functions that were passed in the constructor.\n * @param {Object} options\n */\n\n\n _createClass(Clipboard, [{\n key: \"resolveOptions\",\n value: function resolveOptions() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n this.action = typeof options.action === 'function' ? options.action : this.defaultAction;\n this.target = typeof options.target === 'function' ? options.target : this.defaultTarget;\n this.text = typeof options.text === 'function' ? options.text : this.defaultText;\n this.container = clipboard_typeof(options.container) === 'object' ? options.container : document.body;\n }\n /**\n * Adds a click event listener to the passed trigger.\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n */\n\n }, {\n key: \"listenClick\",\n value: function listenClick(trigger) {\n var _this2 = this;\n\n this.listener = listen_default()(trigger, 'click', function (e) {\n return _this2.onClick(e);\n });\n }\n /**\n * Defines a new `ClipboardAction` on each click event.\n * @param {Event} e\n */\n\n }, {\n key: \"onClick\",\n value: function onClick(e) {\n var trigger = e.delegateTarget || e.currentTarget;\n var action = this.action(trigger) || 'copy';\n var text = actions_default({\n action: action,\n container: this.container,\n target: this.target(trigger),\n text: this.text(trigger)\n }); // Fires an event based on the copy operation result.\n\n this.emit(text ? 'success' : 'error', {\n action: action,\n text: text,\n trigger: trigger,\n clearSelection: function clearSelection() {\n if (trigger) {\n trigger.focus();\n }\n\n window.getSelection().removeAllRanges();\n }\n });\n }\n /**\n * Default `action` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultAction\",\n value: function defaultAction(trigger) {\n return getAttributeValue('action', trigger);\n }\n /**\n * Default `target` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultTarget\",\n value: function defaultTarget(trigger) {\n var selector = getAttributeValue('target', trigger);\n\n if (selector) {\n return document.querySelector(selector);\n }\n }\n /**\n * Allow fire programmatically a copy action\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @returns Text copied.\n */\n\n }, {\n key: \"defaultText\",\n\n /**\n * Default `text` lookup function.\n * @param {Element} trigger\n */\n value: function defaultText(trigger) {\n return getAttributeValue('text', trigger);\n }\n /**\n * Destroy lifecycle.\n */\n\n }, {\n key: \"destroy\",\n value: function destroy() {\n this.listener.destroy();\n }\n }], [{\n key: \"copy\",\n value: function copy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n return actions_copy(target, options);\n }\n /**\n * Allow fire programmatically a cut action\n * @param {String|HTMLElement} target\n * @returns Text cutted.\n */\n\n }, {\n key: \"cut\",\n value: function cut(target) {\n return actions_cut(target);\n }\n /**\n * Returns the support of the given action, or all actions if no action is\n * given.\n * @param {String} [action]\n */\n\n }, {\n key: \"isSupported\",\n value: function isSupported() {\n var action = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : ['copy', 'cut'];\n var actions = typeof action === 'string' ? [action] : action;\n var support = !!document.queryCommandSupported;\n actions.forEach(function (action) {\n support = support && !!document.queryCommandSupported(action);\n });\n return support;\n }\n }]);\n\n return Clipboard;\n}((tiny_emitter_default()));\n\n/* harmony default export */ var clipboard = (Clipboard);\n\n/***/ }),\n\n/***/ 828:\n/***/ (function(module) {\n\nvar DOCUMENT_NODE_TYPE = 9;\n\n/**\n * A polyfill for Element.matches()\n */\nif (typeof Element !== 'undefined' && !Element.prototype.matches) {\n var proto = Element.prototype;\n\n proto.matches = proto.matchesSelector ||\n proto.mozMatchesSelector ||\n proto.msMatchesSelector ||\n proto.oMatchesSelector ||\n proto.webkitMatchesSelector;\n}\n\n/**\n * Finds the closest parent that matches a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @return {Function}\n */\nfunction closest (element, selector) {\n while (element && element.nodeType !== DOCUMENT_NODE_TYPE) {\n if (typeof element.matches === 'function' &&\n element.matches(selector)) {\n return element;\n }\n element = element.parentNode;\n }\n}\n\nmodule.exports = closest;\n\n\n/***/ }),\n\n/***/ 438:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar closest = __webpack_require__(828);\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction _delegate(element, selector, type, callback, useCapture) {\n var listenerFn = listener.apply(this, arguments);\n\n element.addEventListener(type, listenerFn, useCapture);\n\n return {\n destroy: function() {\n element.removeEventListener(type, listenerFn, useCapture);\n }\n }\n}\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element|String|Array} [elements]\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction delegate(elements, selector, type, callback, useCapture) {\n // Handle the regular Element usage\n if (typeof elements.addEventListener === 'function') {\n return _delegate.apply(null, arguments);\n }\n\n // Handle Element-less usage, it defaults to global delegation\n if (typeof type === 'function') {\n // Use `document` as the first parameter, then apply arguments\n // This is a short way to .unshift `arguments` without running into deoptimizations\n return _delegate.bind(null, document).apply(null, arguments);\n }\n\n // Handle Selector-based usage\n if (typeof elements === 'string') {\n elements = document.querySelectorAll(elements);\n }\n\n // Handle Array-like based usage\n return Array.prototype.map.call(elements, function (element) {\n return _delegate(element, selector, type, callback, useCapture);\n });\n}\n\n/**\n * Finds closest match and invokes callback.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Function}\n */\nfunction listener(element, selector, type, callback) {\n return function(e) {\n e.delegateTarget = closest(e.target, selector);\n\n if (e.delegateTarget) {\n callback.call(element, e);\n }\n }\n}\n\nmodule.exports = delegate;\n\n\n/***/ }),\n\n/***/ 879:\n/***/ (function(__unused_webpack_module, exports) {\n\n/**\n * Check if argument is a HTML element.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.node = function(value) {\n return value !== undefined\n && value instanceof HTMLElement\n && value.nodeType === 1;\n};\n\n/**\n * Check if argument is a list of HTML elements.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.nodeList = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return value !== undefined\n && (type === '[object NodeList]' || type === '[object HTMLCollection]')\n && ('length' in value)\n && (value.length === 0 || exports.node(value[0]));\n};\n\n/**\n * Check if argument is a string.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.string = function(value) {\n return typeof value === 'string'\n || value instanceof String;\n};\n\n/**\n * Check if argument is a function.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.fn = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return type === '[object Function]';\n};\n\n\n/***/ }),\n\n/***/ 370:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar is = __webpack_require__(879);\nvar delegate = __webpack_require__(438);\n\n/**\n * Validates all params and calls the right\n * listener function based on its target type.\n *\n * @param {String|HTMLElement|HTMLCollection|NodeList} target\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listen(target, type, callback) {\n if (!target && !type && !callback) {\n throw new Error('Missing required arguments');\n }\n\n if (!is.string(type)) {\n throw new TypeError('Second argument must be a String');\n }\n\n if (!is.fn(callback)) {\n throw new TypeError('Third argument must be a Function');\n }\n\n if (is.node(target)) {\n return listenNode(target, type, callback);\n }\n else if (is.nodeList(target)) {\n return listenNodeList(target, type, callback);\n }\n else if (is.string(target)) {\n return listenSelector(target, type, callback);\n }\n else {\n throw new TypeError('First argument must be a String, HTMLElement, HTMLCollection, or NodeList');\n }\n}\n\n/**\n * Adds an event listener to a HTML element\n * and returns a remove listener function.\n *\n * @param {HTMLElement} node\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNode(node, type, callback) {\n node.addEventListener(type, callback);\n\n return {\n destroy: function() {\n node.removeEventListener(type, callback);\n }\n }\n}\n\n/**\n * Add an event listener to a list of HTML elements\n * and returns a remove listener function.\n *\n * @param {NodeList|HTMLCollection} nodeList\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNodeList(nodeList, type, callback) {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.addEventListener(type, callback);\n });\n\n return {\n destroy: function() {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.removeEventListener(type, callback);\n });\n }\n }\n}\n\n/**\n * Add an event listener to a selector\n * and returns a remove listener function.\n *\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenSelector(selector, type, callback) {\n return delegate(document.body, selector, type, callback);\n}\n\nmodule.exports = listen;\n\n\n/***/ }),\n\n/***/ 817:\n/***/ (function(module) {\n\nfunction select(element) {\n var selectedText;\n\n if (element.nodeName === 'SELECT') {\n element.focus();\n\n selectedText = element.value;\n }\n else if (element.nodeName === 'INPUT' || element.nodeName === 'TEXTAREA') {\n var isReadOnly = element.hasAttribute('readonly');\n\n if (!isReadOnly) {\n element.setAttribute('readonly', '');\n }\n\n element.select();\n element.setSelectionRange(0, element.value.length);\n\n if (!isReadOnly) {\n element.removeAttribute('readonly');\n }\n\n selectedText = element.value;\n }\n else {\n if (element.hasAttribute('contenteditable')) {\n element.focus();\n }\n\n var selection = window.getSelection();\n var range = document.createRange();\n\n range.selectNodeContents(element);\n selection.removeAllRanges();\n selection.addRange(range);\n\n selectedText = selection.toString();\n }\n\n return selectedText;\n}\n\nmodule.exports = select;\n\n\n/***/ }),\n\n/***/ 279:\n/***/ (function(module) {\n\nfunction E () {\n // Keep this empty so it's easier to inherit from\n // (via https://github.com/lipsmack from https://github.com/scottcorgan/tiny-emitter/issues/3)\n}\n\nE.prototype = {\n on: function (name, callback, ctx) {\n var e = this.e || (this.e = {});\n\n (e[name] || (e[name] = [])).push({\n fn: callback,\n ctx: ctx\n });\n\n return this;\n },\n\n once: function (name, callback, ctx) {\n var self = this;\n function listener () {\n self.off(name, listener);\n callback.apply(ctx, arguments);\n };\n\n listener._ = callback\n return this.on(name, listener, ctx);\n },\n\n emit: function (name) {\n var data = [].slice.call(arguments, 1);\n var evtArr = ((this.e || (this.e = {}))[name] || []).slice();\n var i = 0;\n var len = evtArr.length;\n\n for (i; i < len; i++) {\n evtArr[i].fn.apply(evtArr[i].ctx, data);\n }\n\n return this;\n },\n\n off: function (name, callback) {\n var e = this.e || (this.e = {});\n var evts = e[name];\n var liveEvents = [];\n\n if (evts && callback) {\n for (var i = 0, len = evts.length; i < len; i++) {\n if (evts[i].fn !== callback && evts[i].fn._ !== callback)\n liveEvents.push(evts[i]);\n }\n }\n\n // Remove event from queue to prevent memory leak\n // Suggested by https://github.com/lazd\n // Ref: https://github.com/scottcorgan/tiny-emitter/commit/c6ebfaa9bc973b33d110a84a307742b7cf94c953#commitcomment-5024910\n\n (liveEvents.length)\n ? e[name] = liveEvents\n : delete e[name];\n\n return this;\n }\n};\n\nmodule.exports = E;\nmodule.exports.TinyEmitter = E;\n\n\n/***/ })\n\n/******/ \t});\n/************************************************************************/\n/******/ \t// The module cache\n/******/ \tvar __webpack_module_cache__ = {};\n/******/ \t\n/******/ \t// The require function\n/******/ \tfunction __webpack_require__(moduleId) {\n/******/ \t\t// Check if module is in cache\n/******/ \t\tif(__webpack_module_cache__[moduleId]) {\n/******/ \t\t\treturn __webpack_module_cache__[moduleId].exports;\n/******/ \t\t}\n/******/ \t\t// Create a new module (and put it into the cache)\n/******/ \t\tvar module = __webpack_module_cache__[moduleId] = {\n/******/ \t\t\t// no module.id needed\n/******/ \t\t\t// no module.loaded needed\n/******/ \t\t\texports: {}\n/******/ \t\t};\n/******/ \t\n/******/ \t\t// Execute the module function\n/******/ \t\t__webpack_modules__[moduleId](module, module.exports, __webpack_require__);\n/******/ \t\n/******/ \t\t// Return the exports of the module\n/******/ \t\treturn module.exports;\n/******/ \t}\n/******/ \t\n/************************************************************************/\n/******/ \t/* webpack/runtime/compat get default export */\n/******/ \t!function() {\n/******/ \t\t// getDefaultExport function for compatibility with non-harmony modules\n/******/ \t\t__webpack_require__.n = function(module) {\n/******/ \t\t\tvar getter = module && module.__esModule ?\n/******/ \t\t\t\tfunction() { return module['default']; } :\n/******/ \t\t\t\tfunction() { return module; };\n/******/ \t\t\t__webpack_require__.d(getter, { a: getter });\n/******/ \t\t\treturn getter;\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/define property getters */\n/******/ \t!function() {\n/******/ \t\t// define getter functions for harmony exports\n/******/ \t\t__webpack_require__.d = function(exports, definition) {\n/******/ \t\t\tfor(var key in definition) {\n/******/ \t\t\t\tif(__webpack_require__.o(definition, key) && !__webpack_require__.o(exports, key)) {\n/******/ \t\t\t\t\tObject.defineProperty(exports, key, { enumerable: true, get: definition[key] });\n/******/ \t\t\t\t}\n/******/ \t\t\t}\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/hasOwnProperty shorthand */\n/******/ \t!function() {\n/******/ \t\t__webpack_require__.o = function(obj, prop) { return Object.prototype.hasOwnProperty.call(obj, prop); }\n/******/ \t}();\n/******/ \t\n/************************************************************************/\n/******/ \t// module exports must be returned from runtime so entry inlining is disabled\n/******/ \t// startup\n/******/ \t// Load entry module and return exports\n/******/ \treturn __webpack_require__(686);\n/******/ })()\n.default;\n});", "/*\n * Copyright (c) 2016-2024 Martin Donath \n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport \"focus-visible\"\n\nimport {\n EMPTY,\n NEVER,\n Observable,\n Subject,\n defer,\n delay,\n filter,\n map,\n merge,\n mergeWith,\n shareReplay,\n switchMap\n} from \"rxjs\"\n\nimport { configuration, feature } from \"./_\"\nimport {\n at,\n getActiveElement,\n getOptionalElement,\n requestJSON,\n setLocation,\n setToggle,\n watchDocument,\n watchKeyboard,\n watchLocation,\n watchLocationTarget,\n watchMedia,\n watchPrint,\n watchScript,\n watchViewport\n} from \"./browser\"\nimport {\n getComponentElement,\n getComponentElements,\n mountAnnounce,\n mountBackToTop,\n mountConsent,\n mountContent,\n mountDialog,\n mountHeader,\n mountHeaderTitle,\n mountPalette,\n mountProgress,\n mountSearch,\n mountSearchHiglight,\n mountSidebar,\n mountSource,\n mountTableOfContents,\n mountTabs,\n watchHeader,\n watchMain\n} from \"./components\"\nimport {\n SearchIndex,\n setupClipboardJS,\n setupInstantNavigation,\n setupVersionSelector\n} from \"./integrations\"\nimport {\n patchEllipsis,\n patchIndeterminate,\n patchScrollfix,\n patchScrolllock\n} from \"./patches\"\nimport \"./polyfills\"\n\n/* ----------------------------------------------------------------------------\n * Functions - @todo refactor\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch search index\n *\n * @returns Search index observable\n */\nfunction fetchSearchIndex(): Observable {\n if (location.protocol === \"file:\") {\n return watchScript(\n `${new URL(\"search/search_index.js\", config.base)}`\n )\n .pipe(\n // @ts-ignore - @todo fix typings\n map(() => __index),\n shareReplay(1)\n )\n } else {\n return requestJSON(\n new URL(\"search/search_index.json\", config.base)\n )\n }\n}\n\n/* ----------------------------------------------------------------------------\n * Application\n * ------------------------------------------------------------------------- */\n\n/* Yay, JavaScript is available */\ndocument.documentElement.classList.remove(\"no-js\")\ndocument.documentElement.classList.add(\"js\")\n\n/* Set up navigation observables and subjects */\nconst document$ = watchDocument()\nconst location$ = watchLocation()\nconst target$ = watchLocationTarget(location$)\nconst keyboard$ = watchKeyboard()\n\n/* Set up media observables */\nconst viewport$ = watchViewport()\nconst tablet$ = watchMedia(\"(min-width: 960px)\")\nconst screen$ = watchMedia(\"(min-width: 1220px)\")\nconst print$ = watchPrint()\n\n/* Retrieve search index, if search is enabled */\nconst config = configuration()\nconst index$ = document.forms.namedItem(\"search\")\n ? fetchSearchIndex()\n : NEVER\n\n/* Set up Clipboard.js integration */\nconst alert$ = new Subject()\nsetupClipboardJS({ alert$ })\n\n/* Set up progress indicator */\nconst progress$ = new Subject()\n\n/* Set up instant navigation, if enabled */\nif (feature(\"navigation.instant\"))\n setupInstantNavigation({ location$, viewport$, progress$ })\n .subscribe(document$)\n\n/* Set up version selector */\nif (config.version?.provider === \"mike\")\n setupVersionSelector({ document$ })\n\n/* Always close drawer and search on navigation */\nmerge(location$, target$)\n .pipe(\n delay(125)\n )\n .subscribe(() => {\n setToggle(\"drawer\", false)\n setToggle(\"search\", false)\n })\n\n/* Set up global keyboard handlers */\nkeyboard$\n .pipe(\n filter(({ mode }) => mode === \"global\")\n )\n .subscribe(key => {\n switch (key.type) {\n\n /* Go to previous page */\n case \"p\":\n case \",\":\n const prev = getOptionalElement(\"link[rel=prev]\")\n if (typeof prev !== \"undefined\")\n setLocation(prev)\n break\n\n /* Go to next page */\n case \"n\":\n case \".\":\n const next = getOptionalElement(\"link[rel=next]\")\n if (typeof next !== \"undefined\")\n setLocation(next)\n break\n\n /* Expand navigation, see https://bit.ly/3ZjG5io */\n case \"Enter\":\n const active = getActiveElement()\n if (active instanceof HTMLLabelElement)\n active.click()\n }\n })\n\n/* Set up patches */\npatchEllipsis({ viewport$, document$ })\npatchIndeterminate({ document$, tablet$ })\npatchScrollfix({ document$ })\npatchScrolllock({ viewport$, tablet$ })\n\n/* Set up header and main area observable */\nconst header$ = watchHeader(getComponentElement(\"header\"), { viewport$ })\nconst main$ = document$\n .pipe(\n map(() => getComponentElement(\"main\")),\n switchMap(el => watchMain(el, { viewport$, header$ })),\n shareReplay(1)\n )\n\n/* Set up control component observables */\nconst control$ = merge(\n\n /* Consent */\n ...getComponentElements(\"consent\")\n .map(el => mountConsent(el, { target$ })),\n\n /* Dialog */\n ...getComponentElements(\"dialog\")\n .map(el => mountDialog(el, { alert$ })),\n\n /* Header */\n ...getComponentElements(\"header\")\n .map(el => mountHeader(el, { viewport$, header$, main$ })),\n\n /* Color palette */\n ...getComponentElements(\"palette\")\n .map(el => mountPalette(el)),\n\n /* Progress bar */\n ...getComponentElements(\"progress\")\n .map(el => mountProgress(el, { progress$ })),\n\n /* Search */\n ...getComponentElements(\"search\")\n .map(el => mountSearch(el, { index$, keyboard$ })),\n\n /* Repository information */\n ...getComponentElements(\"source\")\n .map(el => mountSource(el))\n)\n\n/* Set up content component observables */\nconst content$ = defer(() => merge(\n\n /* Announcement bar */\n ...getComponentElements(\"announce\")\n .map(el => mountAnnounce(el)),\n\n /* Content */\n ...getComponentElements(\"content\")\n .map(el => mountContent(el, { viewport$, target$, print$ })),\n\n /* Search highlighting */\n ...getComponentElements(\"content\")\n .map(el => feature(\"search.highlight\")\n ? mountSearchHiglight(el, { index$, location$ })\n : EMPTY\n ),\n\n /* Header title */\n ...getComponentElements(\"header-title\")\n .map(el => mountHeaderTitle(el, { viewport$, header$ })),\n\n /* Sidebar */\n ...getComponentElements(\"sidebar\")\n .map(el => el.getAttribute(\"data-md-type\") === \"navigation\"\n ? at(screen$, () => mountSidebar(el, { viewport$, header$, main$ }))\n : at(tablet$, () => mountSidebar(el, { viewport$, header$, main$ }))\n ),\n\n /* Navigation tabs */\n ...getComponentElements(\"tabs\")\n .map(el => mountTabs(el, { viewport$, header$ })),\n\n /* Table of contents */\n ...getComponentElements(\"toc\")\n .map(el => mountTableOfContents(el, {\n viewport$, header$, main$, target$\n })),\n\n /* Back-to-top button */\n ...getComponentElements(\"top\")\n .map(el => mountBackToTop(el, { viewport$, header$, main$, target$ }))\n))\n\n/* Set up component observables */\nconst component$ = document$\n .pipe(\n switchMap(() => content$),\n mergeWith(control$),\n shareReplay(1)\n )\n\n/* Subscribe to all components */\ncomponent$.subscribe()\n\n/* ----------------------------------------------------------------------------\n * Exports\n * ------------------------------------------------------------------------- */\n\nwindow.document$ = document$ /* Document observable */\nwindow.location$ = location$ /* Location subject */\nwindow.target$ = target$ /* Location target observable */\nwindow.keyboard$ = keyboard$ /* Keyboard observable */\nwindow.viewport$ = viewport$ /* Viewport observable */\nwindow.tablet$ = tablet$ /* Media tablet observable */\nwindow.screen$ = screen$ /* Media screen observable */\nwindow.print$ = print$ /* Media print observable */\nwindow.alert$ = alert$ /* Alert subject */\nwindow.progress$ = progress$ /* Progress indicator subject */\nwindow.component$ = component$ /* Component observable */\n", "/******************************************************************************\nCopyright (c) Microsoft Corporation.\n\nPermission to use, copy, modify, and/or distribute this software for any\npurpose with or without fee is hereby granted.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\nREGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\nAND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\nINDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\nLOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\nOTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\nPERFORMANCE OF THIS SOFTWARE.\n***************************************************************************** */\n/* global Reflect, Promise, SuppressedError, Symbol, Iterator */\n\nvar extendStatics = function(d, b) {\n extendStatics = Object.setPrototypeOf ||\n ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||\n function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };\n return extendStatics(d, b);\n};\n\nexport function __extends(d, b) {\n if (typeof b !== \"function\" && b !== null)\n throw new TypeError(\"Class extends value \" + String(b) + \" is not a constructor or null\");\n extendStatics(d, b);\n function __() { this.constructor = d; }\n d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());\n}\n\nexport var __assign = function() {\n __assign = Object.assign || function __assign(t) {\n for (var s, i = 1, n = arguments.length; i < n; i++) {\n s = arguments[i];\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p)) t[p] = s[p];\n }\n return t;\n }\n return __assign.apply(this, arguments);\n}\n\nexport function __rest(s, e) {\n var t = {};\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)\n t[p] = s[p];\n if (s != null && typeof Object.getOwnPropertySymbols === \"function\")\n for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {\n if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))\n t[p[i]] = s[p[i]];\n }\n return t;\n}\n\nexport function __decorate(decorators, target, key, desc) {\n var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;\n if (typeof Reflect === \"object\" && typeof Reflect.decorate === \"function\") r = Reflect.decorate(decorators, target, key, desc);\n else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;\n return c > 3 && r && Object.defineProperty(target, key, r), r;\n}\n\nexport function __param(paramIndex, decorator) {\n return function (target, key) { decorator(target, key, paramIndex); }\n}\n\nexport function __esDecorate(ctor, descriptorIn, decorators, contextIn, initializers, extraInitializers) {\n function accept(f) { if (f !== void 0 && typeof f !== \"function\") throw new TypeError(\"Function expected\"); return f; }\n var kind = contextIn.kind, key = kind === \"getter\" ? \"get\" : kind === \"setter\" ? \"set\" : \"value\";\n var target = !descriptorIn && ctor ? contextIn[\"static\"] ? ctor : ctor.prototype : null;\n var descriptor = descriptorIn || (target ? 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(function(o, m, k, k2) {\n if (k2 === undefined) k2 = k;\n var desc = Object.getOwnPropertyDescriptor(m, k);\n if (!desc || (\"get\" in desc ? !m.__esModule : desc.writable || desc.configurable)) {\n desc = { enumerable: true, get: function() { return m[k]; } };\n }\n Object.defineProperty(o, k2, desc);\n}) : (function(o, m, k, k2) {\n if (k2 === undefined) k2 = k;\n o[k2] = m[k];\n});\n\nexport function __exportStar(m, o) {\n for (var p in m) if (p !== \"default\" && !Object.prototype.hasOwnProperty.call(o, p)) __createBinding(o, m, p);\n}\n\nexport function __values(o) {\n var s = typeof Symbol === \"function\" && Symbol.iterator, m = s && o[s], i = 0;\n if (m) return m.call(o);\n if (o && typeof o.length === \"number\") return {\n next: function () {\n if (o && i >= o.length) o = void 0;\n return { value: o && o[i++], done: !o };\n }\n };\n throw new TypeError(s ? \"Object is not iterable.\" : \"Symbol.iterator is not defined.\");\n}\n\nexport function __read(o, n) {\n var m = typeof Symbol === \"function\" && o[Symbol.iterator];\n if (!m) return o;\n var i = m.call(o), r, ar = [], e;\n try {\n while ((n === void 0 || n-- > 0) && !(r = i.next()).done) ar.push(r.value);\n }\n catch (error) { e = { error: error }; }\n finally {\n try {\n if (r && !r.done && (m = i[\"return\"])) m.call(i);\n }\n finally { if (e) throw e.error; }\n }\n return ar;\n}\n\n/** @deprecated */\nexport function __spread() {\n for (var ar = [], i = 0; i < arguments.length; i++)\n ar = ar.concat(__read(arguments[i]));\n return ar;\n}\n\n/** @deprecated */\nexport function __spreadArrays() {\n for (var s = 0, i = 0, il = arguments.length; i < il; i++) s += arguments[i].length;\n for (var r = Array(s), k = 0, i = 0; i < il; i++)\n for (var a = arguments[i], j = 0, jl = a.length; j < jl; j++, k++)\n r[k] = a[j];\n return r;\n}\n\nexport function __spreadArray(to, from, pack) {\n if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {\n if (ar || !(i in from)) {\n if (!ar) ar = Array.prototype.slice.call(from, 0, i);\n ar[i] = from[i];\n }\n }\n return to.concat(ar || Array.prototype.slice.call(from));\n}\n\nexport function __await(v) {\n return this instanceof __await ? (this.v = v, this) : new __await(v);\n}\n\nexport function __asyncGenerator(thisArg, _arguments, generator) {\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\n var g = generator.apply(thisArg, _arguments || []), i, q = [];\n return i = Object.create((typeof AsyncIterator === \"function\" ? AsyncIterator : Object).prototype), verb(\"next\"), verb(\"throw\"), verb(\"return\", awaitReturn), i[Symbol.asyncIterator] = function () { return this; }, i;\n function awaitReturn(f) { return function (v) { return Promise.resolve(v).then(f, reject); }; }\n function verb(n, f) { if (g[n]) { i[n] = function (v) { return new Promise(function (a, b) { q.push([n, v, a, b]) > 1 || resume(n, v); }); }; if (f) i[n] = f(i[n]); } }\n function resume(n, v) { try { step(g[n](v)); } catch (e) { settle(q[0][3], e); } }\n function step(r) { r.value instanceof __await ? Promise.resolve(r.value.v).then(fulfill, reject) : settle(q[0][2], r); }\n function fulfill(value) { resume(\"next\", value); }\n function reject(value) { resume(\"throw\", value); }\n function settle(f, v) { if (f(v), q.shift(), q.length) resume(q[0][0], q[0][1]); }\n}\n\nexport function __asyncDelegator(o) {\n var i, p;\n return i = {}, verb(\"next\"), verb(\"throw\", function (e) { throw e; }), verb(\"return\"), i[Symbol.iterator] = function () { return this; }, i;\n function verb(n, f) { i[n] = o[n] ? function (v) { return (p = !p) ? { value: __await(o[n](v)), done: false } : f ? f(v) : v; } : f; }\n}\n\nexport function __asyncValues(o) {\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\n var m = o[Symbol.asyncIterator], i;\n return m ? m.call(o) : (o = typeof __values === \"function\" ? __values(o) : o[Symbol.iterator](), i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i);\n function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }\n function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }\n}\n\nexport function __makeTemplateObject(cooked, raw) {\n if (Object.defineProperty) { Object.defineProperty(cooked, \"raw\", { value: raw }); } else { cooked.raw = raw; }\n return cooked;\n};\n\nvar __setModuleDefault = Object.create ? (function(o, v) {\n Object.defineProperty(o, \"default\", { enumerable: true, value: v });\n}) : function(o, v) {\n o[\"default\"] = v;\n};\n\nexport function __importStar(mod) {\n if (mod && mod.__esModule) return mod;\n var result = {};\n if (mod != null) for (var k in mod) if (k !== \"default\" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);\n __setModuleDefault(result, mod);\n return result;\n}\n\nexport function __importDefault(mod) {\n return (mod && mod.__esModule) ? mod : { default: mod };\n}\n\nexport function __classPrivateFieldGet(receiver, state, kind, f) {\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a getter\");\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot read private member from an object whose class did not declare it\");\n return kind === \"m\" ? f : kind === \"a\" ? f.call(receiver) : f ? f.value : state.get(receiver);\n}\n\nexport function __classPrivateFieldSet(receiver, state, value, kind, f) {\n if (kind === \"m\") throw new TypeError(\"Private method is not writable\");\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a setter\");\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot write private member to an object whose class did not declare it\");\n return (kind === \"a\" ? f.call(receiver, value) : f ? f.value = value : state.set(receiver, value)), value;\n}\n\nexport function __classPrivateFieldIn(state, receiver) {\n if (receiver === null || (typeof receiver !== \"object\" && typeof receiver !== \"function\")) throw new TypeError(\"Cannot use 'in' operator on non-object\");\n return typeof state === \"function\" ? receiver === state : state.has(receiver);\n}\n\nexport function __addDisposableResource(env, value, async) {\n if (value !== null && value !== void 0) {\n if (typeof value !== \"object\" && typeof value !== \"function\") throw new TypeError(\"Object expected.\");\n var dispose, inner;\n if (async) {\n if (!Symbol.asyncDispose) throw new TypeError(\"Symbol.asyncDispose is not defined.\");\n dispose = value[Symbol.asyncDispose];\n }\n if (dispose === void 0) {\n if (!Symbol.dispose) throw new TypeError(\"Symbol.dispose is not defined.\");\n dispose = value[Symbol.dispose];\n if (async) inner = dispose;\n }\n if (typeof dispose !== \"function\") throw new TypeError(\"Object not disposable.\");\n if (inner) dispose = function() { try { inner.call(this); } catch (e) { return Promise.reject(e); } };\n env.stack.push({ value: value, dispose: dispose, async: async });\n }\n else if (async) {\n env.stack.push({ async: true });\n }\n return value;\n}\n\nvar _SuppressedError = typeof SuppressedError === \"function\" ? SuppressedError : function (error, suppressed, message) {\n var e = new Error(message);\n return e.name = \"SuppressedError\", e.error = error, e.suppressed = suppressed, e;\n};\n\nexport function __disposeResources(env) {\n function fail(e) {\n env.error = env.hasError ? new _SuppressedError(e, env.error, \"An error was suppressed during disposal.\") : e;\n env.hasError = true;\n }\n var r, s = 0;\n function next() {\n while (r = env.stack.pop()) {\n try {\n if (!r.async && s === 1) return s = 0, env.stack.push(r), Promise.resolve().then(next);\n if (r.dispose) {\n var result = r.dispose.call(r.value);\n if (r.async) return s |= 2, Promise.resolve(result).then(next, function(e) { fail(e); return next(); });\n }\n else s |= 1;\n }\n catch (e) {\n fail(e);\n }\n }\n if (s === 1) return env.hasError ? Promise.reject(env.error) : Promise.resolve();\n if (env.hasError) throw env.error;\n }\n return next();\n}\n\nexport default {\n __extends,\n __assign,\n __rest,\n __decorate,\n __param,\n __metadata,\n __awaiter,\n __generator,\n __createBinding,\n __exportStar,\n __values,\n __read,\n __spread,\n __spreadArrays,\n __spreadArray,\n __await,\n __asyncGenerator,\n __asyncDelegator,\n __asyncValues,\n __makeTemplateObject,\n __importStar,\n __importDefault,\n __classPrivateFieldGet,\n __classPrivateFieldSet,\n __classPrivateFieldIn,\n __addDisposableResource,\n __disposeResources,\n};\n", "/**\n * Returns true if the object is a function.\n * @param value The value to check\n */\nexport function isFunction(value: any): value is (...args: any[]) => any {\n return typeof value === 'function';\n}\n", "/**\n * Used to create Error subclasses until the community moves away from ES5.\n *\n * This is because compiling from TypeScript down to ES5 has issues with subclassing Errors\n * as well as other built-in types: https://github.com/Microsoft/TypeScript/issues/12123\n *\n * @param createImpl A factory function to create the actual constructor implementation. The returned\n * function should be a named function that calls `_super` internally.\n */\nexport function createErrorClass(createImpl: (_super: any) => any): T {\n const _super = (instance: any) => {\n Error.call(instance);\n instance.stack = new Error().stack;\n };\n\n const ctorFunc = createImpl(_super);\n ctorFunc.prototype = Object.create(Error.prototype);\n ctorFunc.prototype.constructor = ctorFunc;\n return ctorFunc;\n}\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface UnsubscriptionError extends Error {\n readonly errors: any[];\n}\n\nexport interface UnsubscriptionErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (errors: any[]): UnsubscriptionError;\n}\n\n/**\n * An error thrown when one or more errors have occurred during the\n * `unsubscribe` of a {@link Subscription}.\n */\nexport const UnsubscriptionError: UnsubscriptionErrorCtor = createErrorClass(\n (_super) =>\n function UnsubscriptionErrorImpl(this: any, errors: (Error | string)[]) {\n _super(this);\n this.message = errors\n ? `${errors.length} errors occurred during unsubscription:\n${errors.map((err, i) => `${i + 1}) ${err.toString()}`).join('\\n ')}`\n : '';\n this.name = 'UnsubscriptionError';\n this.errors = errors;\n }\n);\n", "/**\n * Removes an item from an array, mutating it.\n * @param arr The array to remove the item from\n * @param item The item to remove\n */\nexport function arrRemove(arr: T[] | undefined | null, item: T) {\n if (arr) {\n const index = arr.indexOf(item);\n 0 <= index && arr.splice(index, 1);\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { UnsubscriptionError } from './util/UnsubscriptionError';\nimport { SubscriptionLike, TeardownLogic, Unsubscribable } from './types';\nimport { arrRemove } from './util/arrRemove';\n\n/**\n * Represents a disposable resource, such as the execution of an Observable. A\n * Subscription has one important method, `unsubscribe`, that takes no argument\n * and just disposes the resource held by the subscription.\n *\n * Additionally, subscriptions may be grouped together through the `add()`\n * method, which will attach a child Subscription to the current Subscription.\n * When a Subscription is unsubscribed, all its children (and its grandchildren)\n * will be unsubscribed as well.\n *\n * @class Subscription\n */\nexport class Subscription implements SubscriptionLike {\n /** @nocollapse */\n public static EMPTY = (() => {\n const empty = new Subscription();\n empty.closed = true;\n return empty;\n })();\n\n /**\n * A flag to indicate whether this Subscription has already been unsubscribed.\n */\n public closed = false;\n\n private _parentage: Subscription[] | Subscription | null = null;\n\n /**\n * The list of registered finalizers to execute upon unsubscription. Adding and removing from this\n * list occurs in the {@link #add} and {@link #remove} methods.\n */\n private _finalizers: Exclude[] | null = null;\n\n /**\n * @param initialTeardown A function executed first as part of the finalization\n * process that is kicked off when {@link #unsubscribe} is called.\n */\n constructor(private initialTeardown?: () => void) {}\n\n /**\n * Disposes the resources held by the subscription. May, for instance, cancel\n * an ongoing Observable execution or cancel any other type of work that\n * started when the Subscription was created.\n * @return {void}\n */\n unsubscribe(): void {\n let errors: any[] | undefined;\n\n if (!this.closed) {\n this.closed = true;\n\n // Remove this from it's parents.\n const { _parentage } = this;\n if (_parentage) {\n this._parentage = null;\n if (Array.isArray(_parentage)) {\n for (const parent of _parentage) {\n parent.remove(this);\n }\n } else {\n _parentage.remove(this);\n }\n }\n\n const { initialTeardown: initialFinalizer } = this;\n if (isFunction(initialFinalizer)) {\n try {\n initialFinalizer();\n } catch (e) {\n errors = e instanceof UnsubscriptionError ? e.errors : [e];\n }\n }\n\n const { _finalizers } = this;\n if (_finalizers) {\n this._finalizers = null;\n for (const finalizer of _finalizers) {\n try {\n execFinalizer(finalizer);\n } catch (err) {\n errors = errors ?? [];\n if (err instanceof UnsubscriptionError) {\n errors = [...errors, ...err.errors];\n } else {\n errors.push(err);\n }\n }\n }\n }\n\n if (errors) {\n throw new UnsubscriptionError(errors);\n }\n }\n }\n\n /**\n * Adds a finalizer to this subscription, so that finalization will be unsubscribed/called\n * when this subscription is unsubscribed. If this subscription is already {@link #closed},\n * because it has already been unsubscribed, then whatever finalizer is passed to it\n * will automatically be executed (unless the finalizer itself is also a closed subscription).\n *\n * Closed Subscriptions cannot be added as finalizers to any subscription. Adding a closed\n * subscription to a any subscription will result in no operation. (A noop).\n *\n * Adding a subscription to itself, or adding `null` or `undefined` will not perform any\n * operation at all. (A noop).\n *\n * `Subscription` instances that are added to this instance will automatically remove themselves\n * if they are unsubscribed. Functions and {@link Unsubscribable} objects that you wish to remove\n * will need to be removed manually with {@link #remove}\n *\n * @param teardown The finalization logic to add to this subscription.\n */\n add(teardown: TeardownLogic): void {\n // Only add the finalizer if it's not undefined\n // and don't add a subscription to itself.\n if (teardown && teardown !== this) {\n if (this.closed) {\n // If this subscription is already closed,\n // execute whatever finalizer is handed to it automatically.\n execFinalizer(teardown);\n } else {\n if (teardown instanceof Subscription) {\n // We don't add closed subscriptions, and we don't add the same subscription\n // twice. Subscription unsubscribe is idempotent.\n if (teardown.closed || teardown._hasParent(this)) {\n return;\n }\n teardown._addParent(this);\n }\n (this._finalizers = this._finalizers ?? []).push(teardown);\n }\n }\n }\n\n /**\n * Checks to see if a this subscription already has a particular parent.\n * This will signal that this subscription has already been added to the parent in question.\n * @param parent the parent to check for\n */\n private _hasParent(parent: Subscription) {\n const { _parentage } = this;\n return _parentage === parent || (Array.isArray(_parentage) && _parentage.includes(parent));\n }\n\n /**\n * Adds a parent to this subscription so it can be removed from the parent if it\n * unsubscribes on it's own.\n *\n * NOTE: THIS ASSUMES THAT {@link _hasParent} HAS ALREADY BEEN CHECKED.\n * @param parent The parent subscription to add\n */\n private _addParent(parent: Subscription) {\n const { _parentage } = this;\n this._parentage = Array.isArray(_parentage) ? (_parentage.push(parent), _parentage) : _parentage ? [_parentage, parent] : parent;\n }\n\n /**\n * Called on a child when it is removed via {@link #remove}.\n * @param parent The parent to remove\n */\n private _removeParent(parent: Subscription) {\n const { _parentage } = this;\n if (_parentage === parent) {\n this._parentage = null;\n } else if (Array.isArray(_parentage)) {\n arrRemove(_parentage, parent);\n }\n }\n\n /**\n * Removes a finalizer from this subscription that was previously added with the {@link #add} method.\n *\n * Note that `Subscription` instances, when unsubscribed, will automatically remove themselves\n * from every other `Subscription` they have been added to. This means that using the `remove` method\n * is not a common thing and should be used thoughtfully.\n *\n * If you add the same finalizer instance of a function or an unsubscribable object to a `Subscription` instance\n * more than once, you will need to call `remove` the same number of times to remove all instances.\n *\n * All finalizer instances are removed to free up memory upon unsubscription.\n *\n * @param teardown The finalizer to remove from this subscription\n */\n remove(teardown: Exclude): void {\n const { _finalizers } = this;\n _finalizers && arrRemove(_finalizers, teardown);\n\n if (teardown instanceof Subscription) {\n teardown._removeParent(this);\n }\n }\n}\n\nexport const EMPTY_SUBSCRIPTION = Subscription.EMPTY;\n\nexport function isSubscription(value: any): value is Subscription {\n return (\n value instanceof Subscription ||\n (value && 'closed' in value && isFunction(value.remove) && isFunction(value.add) && isFunction(value.unsubscribe))\n );\n}\n\nfunction execFinalizer(finalizer: Unsubscribable | (() => void)) {\n if (isFunction(finalizer)) {\n finalizer();\n } else {\n finalizer.unsubscribe();\n }\n}\n", "import { Subscriber } from './Subscriber';\nimport { ObservableNotification } from './types';\n\n/**\n * The {@link GlobalConfig} object for RxJS. It is used to configure things\n * like how to react on unhandled errors.\n */\nexport const config: GlobalConfig = {\n onUnhandledError: null,\n onStoppedNotification: null,\n Promise: undefined,\n useDeprecatedSynchronousErrorHandling: false,\n useDeprecatedNextContext: false,\n};\n\n/**\n * The global configuration object for RxJS, used to configure things\n * like how to react on unhandled errors. Accessible via {@link config}\n * object.\n */\nexport interface GlobalConfig {\n /**\n * A registration point for unhandled errors from RxJS. These are errors that\n * cannot were not handled by consuming code in the usual subscription path. For\n * example, if you have this configured, and you subscribe to an observable without\n * providing an error handler, errors from that subscription will end up here. This\n * will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onUnhandledError: ((err: any) => void) | null;\n\n /**\n * A registration point for notifications that cannot be sent to subscribers because they\n * have completed, errored or have been explicitly unsubscribed. By default, next, complete\n * and error notifications sent to stopped subscribers are noops. However, sometimes callers\n * might want a different behavior. For example, with sources that attempt to report errors\n * to stopped subscribers, a caller can configure RxJS to throw an unhandled error instead.\n * This will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onStoppedNotification: ((notification: ObservableNotification, subscriber: Subscriber) => void) | null;\n\n /**\n * The promise constructor used by default for {@link Observable#toPromise toPromise} and {@link Observable#forEach forEach}\n * methods.\n *\n * @deprecated As of version 8, RxJS will no longer support this sort of injection of a\n * Promise constructor. If you need a Promise implementation other than native promises,\n * please polyfill/patch Promise as you see appropriate. Will be removed in v8.\n */\n Promise?: PromiseConstructorLike;\n\n /**\n * If true, turns on synchronous error rethrowing, which is a deprecated behavior\n * in v6 and higher. This behavior enables bad patterns like wrapping a subscribe\n * call in a try/catch block. It also enables producer interference, a nasty bug\n * where a multicast can be broken for all observers by a downstream consumer with\n * an unhandled error. DO NOT USE THIS FLAG UNLESS IT'S NEEDED TO BUY TIME\n * FOR MIGRATION REASONS.\n *\n * @deprecated As of version 8, RxJS will no longer support synchronous throwing\n * of unhandled errors. All errors will be thrown on a separate call stack to prevent bad\n * behaviors described above. Will be removed in v8.\n */\n useDeprecatedSynchronousErrorHandling: boolean;\n\n /**\n * If true, enables an as-of-yet undocumented feature from v5: The ability to access\n * `unsubscribe()` via `this` context in `next` functions created in observers passed\n * to `subscribe`.\n *\n * This is being removed because the performance was severely problematic, and it could also cause\n * issues when types other than POJOs are passed to subscribe as subscribers, as they will likely have\n * their `this` context overwritten.\n *\n * @deprecated As of version 8, RxJS will no longer support altering the\n * context of next functions provided as part of an observer to Subscribe. Instead,\n * you will have access to a subscription or a signal or token that will allow you to do things like\n * unsubscribe and test closed status. Will be removed in v8.\n */\n useDeprecatedNextContext: boolean;\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetTimeoutFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearTimeoutFunction = (handle: TimerHandle) => void;\n\ninterface TimeoutProvider {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n delegate:\n | {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n }\n | undefined;\n}\n\nexport const timeoutProvider: TimeoutProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setTimeout(handler: () => void, timeout?: number, ...args) {\n const { delegate } = timeoutProvider;\n if (delegate?.setTimeout) {\n return delegate.setTimeout(handler, timeout, ...args);\n }\n return setTimeout(handler, timeout, ...args);\n },\n clearTimeout(handle) {\n const { delegate } = timeoutProvider;\n return (delegate?.clearTimeout || clearTimeout)(handle as any);\n },\n delegate: undefined,\n};\n", "import { config } from '../config';\nimport { timeoutProvider } from '../scheduler/timeoutProvider';\n\n/**\n * Handles an error on another job either with the user-configured {@link onUnhandledError},\n * or by throwing it on that new job so it can be picked up by `window.onerror`, `process.on('error')`, etc.\n *\n * This should be called whenever there is an error that is out-of-band with the subscription\n * or when an error hits a terminal boundary of the subscription and no error handler was provided.\n *\n * @param err the error to report\n */\nexport function reportUnhandledError(err: any) {\n timeoutProvider.setTimeout(() => {\n const { onUnhandledError } = config;\n if (onUnhandledError) {\n // Execute the user-configured error handler.\n onUnhandledError(err);\n } else {\n // Throw so it is picked up by the runtime's uncaught error mechanism.\n throw err;\n }\n });\n}\n", "/* tslint:disable:no-empty */\nexport function noop() { }\n", "import { CompleteNotification, NextNotification, ErrorNotification } from './types';\n\n/**\n * A completion object optimized for memory use and created to be the\n * same \"shape\" as other notifications in v8.\n * @internal\n */\nexport const COMPLETE_NOTIFICATION = (() => createNotification('C', undefined, undefined) as CompleteNotification)();\n\n/**\n * Internal use only. Creates an optimized error notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function errorNotification(error: any): ErrorNotification {\n return createNotification('E', undefined, error) as any;\n}\n\n/**\n * Internal use only. Creates an optimized next notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function nextNotification(value: T) {\n return createNotification('N', value, undefined) as NextNotification;\n}\n\n/**\n * Ensures that all notifications created internally have the same \"shape\" in v8.\n *\n * TODO: This is only exported to support a crazy legacy test in `groupBy`.\n * @internal\n */\nexport function createNotification(kind: 'N' | 'E' | 'C', value: any, error: any) {\n return {\n kind,\n value,\n error,\n };\n}\n", "import { config } from '../config';\n\nlet context: { errorThrown: boolean; error: any } | null = null;\n\n/**\n * Handles dealing with errors for super-gross mode. Creates a context, in which\n * any synchronously thrown errors will be passed to {@link captureError}. Which\n * will record the error such that it will be rethrown after the call back is complete.\n * TODO: Remove in v8\n * @param cb An immediately executed function.\n */\nexport function errorContext(cb: () => void) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n const isRoot = !context;\n if (isRoot) {\n context = { errorThrown: false, error: null };\n }\n cb();\n if (isRoot) {\n const { errorThrown, error } = context!;\n context = null;\n if (errorThrown) {\n throw error;\n }\n }\n } else {\n // This is the general non-deprecated path for everyone that\n // isn't crazy enough to use super-gross mode (useDeprecatedSynchronousErrorHandling)\n cb();\n }\n}\n\n/**\n * Captures errors only in super-gross mode.\n * @param err the error to capture\n */\nexport function captureError(err: any) {\n if (config.useDeprecatedSynchronousErrorHandling && context) {\n context.errorThrown = true;\n context.error = err;\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { Observer, ObservableNotification } from './types';\nimport { isSubscription, Subscription } from './Subscription';\nimport { config } from './config';\nimport { reportUnhandledError } from './util/reportUnhandledError';\nimport { noop } from './util/noop';\nimport { nextNotification, errorNotification, COMPLETE_NOTIFICATION } from './NotificationFactories';\nimport { timeoutProvider } from './scheduler/timeoutProvider';\nimport { captureError } from './util/errorContext';\n\n/**\n * Implements the {@link Observer} interface and extends the\n * {@link Subscription} class. While the {@link Observer} is the public API for\n * consuming the values of an {@link Observable}, all Observers get converted to\n * a Subscriber, in order to provide Subscription-like capabilities such as\n * `unsubscribe`. Subscriber is a common type in RxJS, and crucial for\n * implementing operators, but it is rarely used as a public API.\n *\n * @class Subscriber\n */\nexport class Subscriber extends Subscription implements Observer {\n /**\n * A static factory for a Subscriber, given a (potentially partial) definition\n * of an Observer.\n * @param next The `next` callback of an Observer.\n * @param error The `error` callback of an\n * Observer.\n * @param complete The `complete` callback of an\n * Observer.\n * @return A Subscriber wrapping the (partially defined)\n * Observer represented by the given arguments.\n * @nocollapse\n * @deprecated Do not use. Will be removed in v8. There is no replacement for this\n * method, and there is no reason to be creating instances of `Subscriber` directly.\n * If you have a specific use case, please file an issue.\n */\n static create(next?: (x?: T) => void, error?: (e?: any) => void, complete?: () => void): Subscriber {\n return new SafeSubscriber(next, error, complete);\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected isStopped: boolean = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected destination: Subscriber | Observer; // this `any` is the escape hatch to erase extra type param (e.g. R)\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * There is no reason to directly create an instance of Subscriber. This type is exported for typings reasons.\n */\n constructor(destination?: Subscriber | Observer) {\n super();\n if (destination) {\n this.destination = destination;\n // Automatically chain subscriptions together here.\n // if destination is a Subscription, then it is a Subscriber.\n if (isSubscription(destination)) {\n destination.add(this);\n }\n } else {\n this.destination = EMPTY_OBSERVER;\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `next` from\n * the Observable, with a value. The Observable may call this method 0 or more\n * times.\n * @param {T} [value] The `next` value.\n * @return {void}\n */\n next(value?: T): void {\n if (this.isStopped) {\n handleStoppedNotification(nextNotification(value), this);\n } else {\n this._next(value!);\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `error` from\n * the Observable, with an attached `Error`. Notifies the Observer that\n * the Observable has experienced an error condition.\n * @param {any} [err] The `error` exception.\n * @return {void}\n */\n error(err?: any): void {\n if (this.isStopped) {\n handleStoppedNotification(errorNotification(err), this);\n } else {\n this.isStopped = true;\n this._error(err);\n }\n }\n\n /**\n * The {@link Observer} callback to receive a valueless notification of type\n * `complete` from the Observable. Notifies the Observer that the Observable\n * has finished sending push-based notifications.\n * @return {void}\n */\n complete(): void {\n if (this.isStopped) {\n handleStoppedNotification(COMPLETE_NOTIFICATION, this);\n } else {\n this.isStopped = true;\n this._complete();\n }\n }\n\n unsubscribe(): void {\n if (!this.closed) {\n this.isStopped = true;\n super.unsubscribe();\n this.destination = null!;\n }\n }\n\n protected _next(value: T): void {\n this.destination.next(value);\n }\n\n protected _error(err: any): void {\n try {\n this.destination.error(err);\n } finally {\n this.unsubscribe();\n }\n }\n\n protected _complete(): void {\n try {\n this.destination.complete();\n } finally {\n this.unsubscribe();\n }\n }\n}\n\n/**\n * This bind is captured here because we want to be able to have\n * compatibility with monoid libraries that tend to use a method named\n * `bind`. In particular, a library called Monio requires this.\n */\nconst _bind = Function.prototype.bind;\n\nfunction bind any>(fn: Fn, thisArg: any): Fn {\n return _bind.call(fn, thisArg);\n}\n\n/**\n * Internal optimization only, DO NOT EXPOSE.\n * @internal\n */\nclass ConsumerObserver implements Observer {\n constructor(private partialObserver: Partial>) {}\n\n next(value: T): void {\n const { partialObserver } = this;\n if (partialObserver.next) {\n try {\n partialObserver.next(value);\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n\n error(err: any): void {\n const { partialObserver } = this;\n if (partialObserver.error) {\n try {\n partialObserver.error(err);\n } catch (error) {\n handleUnhandledError(error);\n }\n } else {\n handleUnhandledError(err);\n }\n }\n\n complete(): void {\n const { partialObserver } = this;\n if (partialObserver.complete) {\n try {\n partialObserver.complete();\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n}\n\nexport class SafeSubscriber extends Subscriber {\n constructor(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((e?: any) => void) | null,\n complete?: (() => void) | null\n ) {\n super();\n\n let partialObserver: Partial>;\n if (isFunction(observerOrNext) || !observerOrNext) {\n // The first argument is a function, not an observer. The next\n // two arguments *could* be observers, or they could be empty.\n partialObserver = {\n next: (observerOrNext ?? undefined) as (((value: T) => void) | undefined),\n error: error ?? undefined,\n complete: complete ?? undefined,\n };\n } else {\n // The first argument is a partial observer.\n let context: any;\n if (this && config.useDeprecatedNextContext) {\n // This is a deprecated path that made `this.unsubscribe()` available in\n // next handler functions passed to subscribe. This only exists behind a flag\n // now, as it is *very* slow.\n context = Object.create(observerOrNext);\n context.unsubscribe = () => this.unsubscribe();\n partialObserver = {\n next: observerOrNext.next && bind(observerOrNext.next, context),\n error: observerOrNext.error && bind(observerOrNext.error, context),\n complete: observerOrNext.complete && bind(observerOrNext.complete, context),\n };\n } else {\n // The \"normal\" path. Just use the partial observer directly.\n partialObserver = observerOrNext;\n }\n }\n\n // Wrap the partial observer to ensure it's a full observer, and\n // make sure proper error handling is accounted for.\n this.destination = new ConsumerObserver(partialObserver);\n }\n}\n\nfunction handleUnhandledError(error: any) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n captureError(error);\n } else {\n // Ideal path, we report this as an unhandled error,\n // which is thrown on a new call stack.\n reportUnhandledError(error);\n }\n}\n\n/**\n * An error handler used when no error handler was supplied\n * to the SafeSubscriber -- meaning no error handler was supplied\n * do the `subscribe` call on our observable.\n * @param err The error to handle\n */\nfunction defaultErrorHandler(err: any) {\n throw err;\n}\n\n/**\n * A handler for notifications that cannot be sent to a stopped subscriber.\n * @param notification The notification being sent\n * @param subscriber The stopped subscriber\n */\nfunction handleStoppedNotification(notification: ObservableNotification, subscriber: Subscriber) {\n const { onStoppedNotification } = config;\n onStoppedNotification && timeoutProvider.setTimeout(() => onStoppedNotification(notification, subscriber));\n}\n\n/**\n * The observer used as a stub for subscriptions where the user did not\n * pass any arguments to `subscribe`. Comes with the default error handling\n * behavior.\n */\nexport const EMPTY_OBSERVER: Readonly> & { closed: true } = {\n closed: true,\n next: noop,\n error: defaultErrorHandler,\n complete: noop,\n};\n", "/**\n * Symbol.observable or a string \"@@observable\". Used for interop\n *\n * @deprecated We will no longer be exporting this symbol in upcoming versions of RxJS.\n * Instead polyfill and use Symbol.observable directly *or* use https://www.npmjs.com/package/symbol-observable\n */\nexport const observable: string | symbol = (() => (typeof Symbol === 'function' && Symbol.observable) || '@@observable')();\n", "/**\n * This function takes one parameter and just returns it. Simply put,\n * this is like `(x: T): T => x`.\n *\n * ## Examples\n *\n * This is useful in some cases when using things like `mergeMap`\n *\n * ```ts\n * import { interval, take, map, range, mergeMap, identity } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(5));\n *\n * const result$ = source$.pipe(\n * map(i => range(i)),\n * mergeMap(identity) // same as mergeMap(x => x)\n * );\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * Or when you want to selectively apply an operator\n *\n * ```ts\n * import { interval, take, identity } from 'rxjs';\n *\n * const shouldLimit = () => Math.random() < 0.5;\n *\n * const source$ = interval(1000);\n *\n * const result$ = source$.pipe(shouldLimit() ? take(5) : identity);\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * @param x Any value that is returned by this function\n * @returns The value passed as the first parameter to this function\n */\nexport function identity(x: T): T {\n return x;\n}\n", "import { identity } from './identity';\nimport { UnaryFunction } from '../types';\n\nexport function pipe(): typeof identity;\nexport function pipe(fn1: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction, fn3: UnaryFunction): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction,\n ...fns: UnaryFunction[]\n): UnaryFunction;\n\n/**\n * pipe() can be called on one or more functions, each of which can take one argument (\"UnaryFunction\")\n * and uses it to return a value.\n * It returns a function that takes one argument, passes it to the first UnaryFunction, and then\n * passes the result to the next one, passes that result to the next one, and so on. \n */\nexport function pipe(...fns: Array>): UnaryFunction {\n return pipeFromArray(fns);\n}\n\n/** @internal */\nexport function pipeFromArray(fns: Array>): UnaryFunction {\n if (fns.length === 0) {\n return identity as UnaryFunction;\n }\n\n if (fns.length === 1) {\n return fns[0];\n }\n\n return function piped(input: T): R {\n return fns.reduce((prev: any, fn: UnaryFunction) => fn(prev), input as any);\n };\n}\n", "import { Operator } from './Operator';\nimport { SafeSubscriber, Subscriber } from './Subscriber';\nimport { isSubscription, Subscription } from './Subscription';\nimport { TeardownLogic, OperatorFunction, Subscribable, Observer } from './types';\nimport { observable as Symbol_observable } from './symbol/observable';\nimport { pipeFromArray } from './util/pipe';\nimport { config } from './config';\nimport { isFunction } from './util/isFunction';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A representation of any set of values over any amount of time. This is the most basic building block\n * of RxJS.\n *\n * @class Observable\n */\nexport class Observable implements Subscribable {\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n source: Observable | undefined;\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n operator: Operator | undefined;\n\n /**\n * @constructor\n * @param {Function} subscribe the function that is called when the Observable is\n * initially subscribed to. This function is given a Subscriber, to which new values\n * can be `next`ed, or an `error` method can be called to raise an error, or\n * `complete` can be called to notify of a successful completion.\n */\n constructor(subscribe?: (this: Observable, subscriber: Subscriber) => TeardownLogic) {\n if (subscribe) {\n this._subscribe = subscribe;\n }\n }\n\n // HACK: Since TypeScript inherits static properties too, we have to\n // fight against TypeScript here so Subject can have a different static create signature\n /**\n * Creates a new Observable by calling the Observable constructor\n * @owner Observable\n * @method create\n * @param {Function} subscribe? the subscriber function to be passed to the Observable constructor\n * @return {Observable} a new observable\n * @nocollapse\n * @deprecated Use `new Observable()` instead. Will be removed in v8.\n */\n static create: (...args: any[]) => any = (subscribe?: (subscriber: Subscriber) => TeardownLogic) => {\n return new Observable(subscribe);\n };\n\n /**\n * Creates a new Observable, with this Observable instance as the source, and the passed\n * operator defined as the new observable's operator.\n * @method lift\n * @param operator the operator defining the operation to take on the observable\n * @return a new observable with the Operator applied\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * If you have implemented an operator using `lift`, it is recommended that you create an\n * operator by simply returning `new Observable()` directly. See \"Creating new operators from\n * scratch\" section here: https://rxjs.dev/guide/operators\n */\n lift(operator?: Operator): Observable {\n const observable = new Observable();\n observable.source = this;\n observable.operator = operator;\n return observable;\n }\n\n subscribe(observerOrNext?: Partial> | ((value: T) => void)): Subscription;\n /** @deprecated Instead of passing separate callback arguments, use an observer argument. Signatures taking separate callback arguments will be removed in v8. Details: https://rxjs.dev/deprecations/subscribe-arguments */\n subscribe(next?: ((value: T) => void) | null, error?: ((error: any) => void) | null, complete?: (() => void) | null): Subscription;\n /**\n * Invokes an execution of an Observable and registers Observer handlers for notifications it will emit.\n *\n * Use it when you have all these Observables, but still nothing is happening.\n *\n * `subscribe` is not a regular operator, but a method that calls Observable's internal `subscribe` function. It\n * might be for example a function that you passed to Observable's constructor, but most of the time it is\n * a library implementation, which defines what will be emitted by an Observable, and when it be will emitted. This means\n * that calling `subscribe` is actually the moment when Observable starts its work, not when it is created, as it is often\n * the thought.\n *\n * Apart from starting the execution of an Observable, this method allows you to listen for values\n * that an Observable emits, as well as for when it completes or errors. You can achieve this in two\n * of the following ways.\n *\n * The first way is creating an object that implements {@link Observer} interface. It should have methods\n * defined by that interface, but note that it should be just a regular JavaScript object, which you can create\n * yourself in any way you want (ES6 class, classic function constructor, object literal etc.). In particular, do\n * not attempt to use any RxJS implementation details to create Observers - you don't need them. Remember also\n * that your object does not have to implement all methods. If you find yourself creating a method that doesn't\n * do anything, you can simply omit it. Note however, if the `error` method is not provided and an error happens,\n * it will be thrown asynchronously. Errors thrown asynchronously cannot be caught using `try`/`catch`. Instead,\n * use the {@link onUnhandledError} configuration option or use a runtime handler (like `window.onerror` or\n * `process.on('error)`) to be notified of unhandled errors. Because of this, it's recommended that you provide\n * an `error` method to avoid missing thrown errors.\n *\n * The second way is to give up on Observer object altogether and simply provide callback functions in place of its methods.\n * This means you can provide three functions as arguments to `subscribe`, where the first function is equivalent\n * of a `next` method, the second of an `error` method and the third of a `complete` method. Just as in case of an Observer,\n * if you do not need to listen for something, you can omit a function by passing `undefined` or `null`,\n * since `subscribe` recognizes these functions by where they were placed in function call. When it comes\n * to the `error` function, as with an Observer, if not provided, errors emitted by an Observable will be thrown asynchronously.\n *\n * You can, however, subscribe with no parameters at all. This may be the case where you're not interested in terminal events\n * and you also handled emissions internally by using operators (e.g. using `tap`).\n *\n * Whichever style of calling `subscribe` you use, in both cases it returns a Subscription object.\n * This object allows you to call `unsubscribe` on it, which in turn will stop the work that an Observable does and will clean\n * up all resources that an Observable used. Note that cancelling a subscription will not call `complete` callback\n * provided to `subscribe` function, which is reserved for a regular completion signal that comes from an Observable.\n *\n * Remember that callbacks provided to `subscribe` are not guaranteed to be called asynchronously.\n * It is an Observable itself that decides when these functions will be called. For example {@link of}\n * by default emits all its values synchronously. Always check documentation for how given Observable\n * will behave when subscribed and if its default behavior can be modified with a `scheduler`.\n *\n * #### Examples\n *\n * Subscribe with an {@link guide/observer Observer}\n *\n * ```ts\n * import { of } from 'rxjs';\n *\n * const sumObserver = {\n * sum: 0,\n * next(value) {\n * console.log('Adding: ' + value);\n * this.sum = this.sum + value;\n * },\n * error() {\n * // We actually could just remove this method,\n * // since we do not really care about errors right now.\n * },\n * complete() {\n * console.log('Sum equals: ' + this.sum);\n * }\n * };\n *\n * of(1, 2, 3) // Synchronously emits 1, 2, 3 and then completes.\n * .subscribe(sumObserver);\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Subscribe with functions ({@link deprecations/subscribe-arguments deprecated})\n *\n * ```ts\n * import { of } from 'rxjs'\n *\n * let sum = 0;\n *\n * of(1, 2, 3).subscribe(\n * value => {\n * console.log('Adding: ' + value);\n * sum = sum + value;\n * },\n * undefined,\n * () => console.log('Sum equals: ' + sum)\n * );\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Cancel a subscription\n *\n * ```ts\n * import { interval } from 'rxjs';\n *\n * const subscription = interval(1000).subscribe({\n * next(num) {\n * console.log(num)\n * },\n * complete() {\n * // Will not be called, even when cancelling subscription.\n * console.log('completed!');\n * }\n * });\n *\n * setTimeout(() => {\n * subscription.unsubscribe();\n * console.log('unsubscribed!');\n * }, 2500);\n *\n * // Logs:\n * // 0 after 1s\n * // 1 after 2s\n * // 'unsubscribed!' after 2.5s\n * ```\n *\n * @param {Observer|Function} observerOrNext (optional) Either an observer with methods to be called,\n * or the first of three possible handlers, which is the handler for each value emitted from the subscribed\n * Observable.\n * @param {Function} error (optional) A handler for a terminal event resulting from an error. If no error handler is provided,\n * the error will be thrown asynchronously as unhandled.\n * @param {Function} complete (optional) A handler for a terminal event resulting from successful completion.\n * @return {Subscription} a subscription reference to the registered handlers\n * @method subscribe\n */\n subscribe(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((error: any) => void) | null,\n complete?: (() => void) | null\n ): Subscription {\n const subscriber = isSubscriber(observerOrNext) ? observerOrNext : new SafeSubscriber(observerOrNext, error, complete);\n\n errorContext(() => {\n const { operator, source } = this;\n subscriber.add(\n operator\n ? // We're dealing with a subscription in the\n // operator chain to one of our lifted operators.\n operator.call(subscriber, source)\n : source\n ? // If `source` has a value, but `operator` does not, something that\n // had intimate knowledge of our API, like our `Subject`, must have\n // set it. We're going to just call `_subscribe` directly.\n this._subscribe(subscriber)\n : // In all other cases, we're likely wrapping a user-provided initializer\n // function, so we need to catch errors and handle them appropriately.\n this._trySubscribe(subscriber)\n );\n });\n\n return subscriber;\n }\n\n /** @internal */\n protected _trySubscribe(sink: Subscriber): TeardownLogic {\n try {\n return this._subscribe(sink);\n } catch (err) {\n // We don't need to return anything in this case,\n // because it's just going to try to `add()` to a subscription\n // above.\n sink.error(err);\n }\n }\n\n /**\n * Used as a NON-CANCELLABLE means of subscribing to an observable, for use with\n * APIs that expect promises, like `async/await`. You cannot unsubscribe from this.\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * #### Example\n *\n * ```ts\n * import { interval, take } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(4));\n *\n * async function getTotal() {\n * let total = 0;\n *\n * await source$.forEach(value => {\n * total += value;\n * console.log('observable -> ' + value);\n * });\n *\n * return total;\n * }\n *\n * getTotal().then(\n * total => console.log('Total: ' + total)\n * );\n *\n * // Expected:\n * // 'observable -> 0'\n * // 'observable -> 1'\n * // 'observable -> 2'\n * // 'observable -> 3'\n * // 'Total: 6'\n * ```\n *\n * @param next a handler for each value emitted by the observable\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n */\n forEach(next: (value: T) => void): Promise;\n\n /**\n * @param next a handler for each value emitted by the observable\n * @param promiseCtor a constructor function used to instantiate the Promise\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n * @deprecated Passing a Promise constructor will no longer be available\n * in upcoming versions of RxJS. This is because it adds weight to the library, for very\n * little benefit. If you need this functionality, it is recommended that you either\n * polyfill Promise, or you create an adapter to convert the returned native promise\n * to whatever promise implementation you wanted. Will be removed in v8.\n */\n forEach(next: (value: T) => void, promiseCtor: PromiseConstructorLike): Promise;\n\n forEach(next: (value: T) => void, promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n const subscriber = new SafeSubscriber({\n next: (value) => {\n try {\n next(value);\n } catch (err) {\n reject(err);\n subscriber.unsubscribe();\n }\n },\n error: reject,\n complete: resolve,\n });\n this.subscribe(subscriber);\n }) as Promise;\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): TeardownLogic {\n return this.source?.subscribe(subscriber);\n }\n\n /**\n * An interop point defined by the es7-observable spec https://github.com/zenparsing/es-observable\n * @method Symbol.observable\n * @return {Observable} this instance of the observable\n */\n [Symbol_observable]() {\n return this;\n }\n\n /* tslint:disable:max-line-length */\n pipe(): Observable;\n pipe(op1: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction, op3: OperatorFunction): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction,\n ...operations: OperatorFunction[]\n ): Observable;\n /* tslint:enable:max-line-length */\n\n /**\n * Used to stitch together functional operators into a chain.\n * @method pipe\n * @return {Observable} the Observable result of all of the operators having\n * been called in the order they were passed in.\n *\n * ## Example\n *\n * ```ts\n * import { interval, filter, map, scan } from 'rxjs';\n *\n * interval(1000)\n * .pipe(\n * filter(x => x % 2 === 0),\n * map(x => x + x),\n * scan((acc, x) => acc + x)\n * )\n * .subscribe(x => console.log(x));\n * ```\n */\n pipe(...operations: OperatorFunction[]): Observable {\n return pipeFromArray(operations)(this);\n }\n\n /* tslint:disable:max-line-length */\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: typeof Promise): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: PromiseConstructorLike): Promise;\n /* tslint:enable:max-line-length */\n\n /**\n * Subscribe to this Observable and get a Promise resolving on\n * `complete` with the last emission (if any).\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * @method toPromise\n * @param [promiseCtor] a constructor function used to instantiate\n * the Promise\n * @return A Promise that resolves with the last value emit, or\n * rejects on an error. If there were no emissions, Promise\n * resolves with undefined.\n * @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise\n */\n toPromise(promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n let value: T | undefined;\n this.subscribe(\n (x: T) => (value = x),\n (err: any) => reject(err),\n () => resolve(value)\n );\n }) as Promise;\n }\n}\n\n/**\n * Decides between a passed promise constructor from consuming code,\n * A default configured promise constructor, and the native promise\n * constructor and returns it. If nothing can be found, it will throw\n * an error.\n * @param promiseCtor The optional promise constructor to passed by consuming code\n */\nfunction getPromiseCtor(promiseCtor: PromiseConstructorLike | undefined) {\n return promiseCtor ?? config.Promise ?? Promise;\n}\n\nfunction isObserver(value: any): value is Observer {\n return value && isFunction(value.next) && isFunction(value.error) && isFunction(value.complete);\n}\n\nfunction isSubscriber(value: any): value is Subscriber {\n return (value && value instanceof Subscriber) || (isObserver(value) && isSubscription(value));\n}\n", "import { Observable } from '../Observable';\nimport { Subscriber } from '../Subscriber';\nimport { OperatorFunction } from '../types';\nimport { isFunction } from './isFunction';\n\n/**\n * Used to determine if an object is an Observable with a lift function.\n */\nexport function hasLift(source: any): source is { lift: InstanceType['lift'] } {\n return isFunction(source?.lift);\n}\n\n/**\n * Creates an `OperatorFunction`. Used to define operators throughout the library in a concise way.\n * @param init The logic to connect the liftedSource to the subscriber at the moment of subscription.\n */\nexport function operate(\n init: (liftedSource: Observable, subscriber: Subscriber) => (() => void) | void\n): OperatorFunction {\n return (source: Observable) => {\n if (hasLift(source)) {\n return source.lift(function (this: Subscriber, liftedSource: Observable) {\n try {\n return init(liftedSource, this);\n } catch (err) {\n this.error(err);\n }\n });\n }\n throw new TypeError('Unable to lift unknown Observable type');\n };\n}\n", "import { Subscriber } from '../Subscriber';\n\n/**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional teardown logic here. This will only be called on teardown if the\n * subscriber itself is not already closed. This is called after all other teardown logic is executed.\n */\nexport function createOperatorSubscriber(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n onFinalize?: () => void\n): Subscriber {\n return new OperatorSubscriber(destination, onNext, onComplete, onError, onFinalize);\n}\n\n/**\n * A generic helper for allowing operators to be created with a Subscriber and\n * use closures to capture necessary state from the operator function itself.\n */\nexport class OperatorSubscriber extends Subscriber {\n /**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional finalization logic here. This will only be called on finalization if the\n * subscriber itself is not already closed. This is called after all other finalization logic is executed.\n * @param shouldUnsubscribe An optional check to see if an unsubscribe call should truly unsubscribe.\n * NOTE: This currently **ONLY** exists to support the strange behavior of {@link groupBy}, where unsubscription\n * to the resulting observable does not actually disconnect from the source if there are active subscriptions\n * to any grouped observable. (DO NOT EXPOSE OR USE EXTERNALLY!!!)\n */\n constructor(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n private onFinalize?: () => void,\n private shouldUnsubscribe?: () => boolean\n ) {\n // It's important - for performance reasons - that all of this class's\n // members are initialized and that they are always initialized in the same\n // order. This will ensure that all OperatorSubscriber instances have the\n // same hidden class in V8. This, in turn, will help keep the number of\n // hidden classes involved in property accesses within the base class as\n // low as possible. If the number of hidden classes involved exceeds four,\n // the property accesses will become megamorphic and performance penalties\n // will be incurred - i.e. inline caches won't be used.\n //\n // The reasons for ensuring all instances have the same hidden class are\n // further discussed in this blog post from Benedikt Meurer:\n // https://benediktmeurer.de/2018/03/23/impact-of-polymorphism-on-component-based-frameworks-like-react/\n super(destination);\n this._next = onNext\n ? function (this: OperatorSubscriber, value: T) {\n try {\n onNext(value);\n } catch (err) {\n destination.error(err);\n }\n }\n : super._next;\n this._error = onError\n ? function (this: OperatorSubscriber, err: any) {\n try {\n onError(err);\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._error;\n this._complete = onComplete\n ? function (this: OperatorSubscriber) {\n try {\n onComplete();\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._complete;\n }\n\n unsubscribe() {\n if (!this.shouldUnsubscribe || this.shouldUnsubscribe()) {\n const { closed } = this;\n super.unsubscribe();\n // Execute additional teardown if we have any and we didn't already do so.\n !closed && this.onFinalize?.();\n }\n }\n}\n", "import { Subscription } from '../Subscription';\n\ninterface AnimationFrameProvider {\n schedule(callback: FrameRequestCallback): Subscription;\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n delegate:\n | {\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n }\n | undefined;\n}\n\nexport const animationFrameProvider: AnimationFrameProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n schedule(callback) {\n let request = requestAnimationFrame;\n let cancel: typeof cancelAnimationFrame | undefined = cancelAnimationFrame;\n const { delegate } = animationFrameProvider;\n if (delegate) {\n request = delegate.requestAnimationFrame;\n cancel = delegate.cancelAnimationFrame;\n }\n const handle = request((timestamp) => {\n // Clear the cancel function. The request has been fulfilled, so\n // attempting to cancel the request upon unsubscription would be\n // pointless.\n cancel = undefined;\n callback(timestamp);\n });\n return new Subscription(() => cancel?.(handle));\n },\n requestAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.requestAnimationFrame || requestAnimationFrame)(...args);\n },\n cancelAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.cancelAnimationFrame || cancelAnimationFrame)(...args);\n },\n delegate: undefined,\n};\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface ObjectUnsubscribedError extends Error {}\n\nexport interface ObjectUnsubscribedErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (): ObjectUnsubscribedError;\n}\n\n/**\n * An error thrown when an action is invalid because the object has been\n * unsubscribed.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n *\n * @class ObjectUnsubscribedError\n */\nexport const ObjectUnsubscribedError: ObjectUnsubscribedErrorCtor = createErrorClass(\n (_super) =>\n function ObjectUnsubscribedErrorImpl(this: any) {\n _super(this);\n this.name = 'ObjectUnsubscribedError';\n this.message = 'object unsubscribed';\n }\n);\n", "import { Operator } from './Operator';\nimport { Observable } from './Observable';\nimport { Subscriber } from './Subscriber';\nimport { Subscription, EMPTY_SUBSCRIPTION } from './Subscription';\nimport { Observer, SubscriptionLike, TeardownLogic } from './types';\nimport { ObjectUnsubscribedError } from './util/ObjectUnsubscribedError';\nimport { arrRemove } from './util/arrRemove';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A Subject is a special type of Observable that allows values to be\n * multicasted to many Observers. Subjects are like EventEmitters.\n *\n * Every Subject is an Observable and an Observer. You can subscribe to a\n * Subject, and you can call next to feed values as well as error and complete.\n */\nexport class Subject extends Observable implements SubscriptionLike {\n closed = false;\n\n private currentObservers: Observer[] | null = null;\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n observers: Observer[] = [];\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n isStopped = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n hasError = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n thrownError: any = null;\n\n /**\n * Creates a \"subject\" by basically gluing an observer to an observable.\n *\n * @nocollapse\n * @deprecated Recommended you do not use. Will be removed at some point in the future. Plans for replacement still under discussion.\n */\n static create: (...args: any[]) => any = (destination: Observer, source: Observable): AnonymousSubject => {\n return new AnonymousSubject(destination, source);\n };\n\n constructor() {\n // NOTE: This must be here to obscure Observable's constructor.\n super();\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n lift(operator: Operator): Observable {\n const subject = new AnonymousSubject(this, this);\n subject.operator = operator as any;\n return subject as any;\n }\n\n /** @internal */\n protected _throwIfClosed() {\n if (this.closed) {\n throw new ObjectUnsubscribedError();\n }\n }\n\n next(value: T) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n if (!this.currentObservers) {\n this.currentObservers = Array.from(this.observers);\n }\n for (const observer of this.currentObservers) {\n observer.next(value);\n }\n }\n });\n }\n\n error(err: any) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.hasError = this.isStopped = true;\n this.thrownError = err;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.error(err);\n }\n }\n });\n }\n\n complete() {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.isStopped = true;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.complete();\n }\n }\n });\n }\n\n unsubscribe() {\n this.isStopped = this.closed = true;\n this.observers = this.currentObservers = null!;\n }\n\n get observed() {\n return this.observers?.length > 0;\n }\n\n /** @internal */\n protected _trySubscribe(subscriber: Subscriber): TeardownLogic {\n this._throwIfClosed();\n return super._trySubscribe(subscriber);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._checkFinalizedStatuses(subscriber);\n return this._innerSubscribe(subscriber);\n }\n\n /** @internal */\n protected _innerSubscribe(subscriber: Subscriber) {\n const { hasError, isStopped, observers } = this;\n if (hasError || isStopped) {\n return EMPTY_SUBSCRIPTION;\n }\n this.currentObservers = null;\n observers.push(subscriber);\n return new Subscription(() => {\n this.currentObservers = null;\n arrRemove(observers, subscriber);\n });\n }\n\n /** @internal */\n protected _checkFinalizedStatuses(subscriber: Subscriber) {\n const { hasError, thrownError, isStopped } = this;\n if (hasError) {\n subscriber.error(thrownError);\n } else if (isStopped) {\n subscriber.complete();\n }\n }\n\n /**\n * Creates a new Observable with this Subject as the source. You can do this\n * to create custom Observer-side logic of the Subject and conceal it from\n * code that uses the Observable.\n * @return {Observable} Observable that the Subject casts to\n */\n asObservable(): Observable {\n const observable: any = new Observable();\n observable.source = this;\n return observable;\n }\n}\n\n/**\n * @class AnonymousSubject\n */\nexport class AnonymousSubject extends Subject {\n constructor(\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n public destination?: Observer,\n source?: Observable\n ) {\n super();\n this.source = source;\n }\n\n next(value: T) {\n this.destination?.next?.(value);\n }\n\n error(err: any) {\n this.destination?.error?.(err);\n }\n\n complete() {\n this.destination?.complete?.();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n return this.source?.subscribe(subscriber) ?? EMPTY_SUBSCRIPTION;\n }\n}\n", "import { Subject } from './Subject';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\n\n/**\n * A variant of Subject that requires an initial value and emits its current\n * value whenever it is subscribed to.\n *\n * @class BehaviorSubject\n */\nexport class BehaviorSubject extends Subject {\n constructor(private _value: T) {\n super();\n }\n\n get value(): T {\n return this.getValue();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n const subscription = super._subscribe(subscriber);\n !subscription.closed && subscriber.next(this._value);\n return subscription;\n }\n\n getValue(): T {\n const { hasError, thrownError, _value } = this;\n if (hasError) {\n throw thrownError;\n }\n this._throwIfClosed();\n return _value;\n }\n\n next(value: T): void {\n super.next((this._value = value));\n }\n}\n", "import { TimestampProvider } from '../types';\n\ninterface DateTimestampProvider extends TimestampProvider {\n delegate: TimestampProvider | undefined;\n}\n\nexport const dateTimestampProvider: DateTimestampProvider = {\n now() {\n // Use the variable rather than `this` so that the function can be called\n // without being bound to the provider.\n return (dateTimestampProvider.delegate || Date).now();\n },\n delegate: undefined,\n};\n", "import { Subject } from './Subject';\nimport { TimestampProvider } from './types';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * A variant of {@link Subject} that \"replays\" old values to new subscribers by emitting them when they first subscribe.\n *\n * `ReplaySubject` has an internal buffer that will store a specified number of values that it has observed. Like `Subject`,\n * `ReplaySubject` \"observes\" values by having them passed to its `next` method. When it observes a value, it will store that\n * value for a time determined by the configuration of the `ReplaySubject`, as passed to its constructor.\n *\n * When a new subscriber subscribes to the `ReplaySubject` instance, it will synchronously emit all values in its buffer in\n * a First-In-First-Out (FIFO) manner. The `ReplaySubject` will also complete, if it has observed completion; and it will\n * error if it has observed an error.\n *\n * There are two main configuration items to be concerned with:\n *\n * 1. `bufferSize` - This will determine how many items are stored in the buffer, defaults to infinite.\n * 2. `windowTime` - The amount of time to hold a value in the buffer before removing it from the buffer.\n *\n * Both configurations may exist simultaneously. So if you would like to buffer a maximum of 3 values, as long as the values\n * are less than 2 seconds old, you could do so with a `new ReplaySubject(3, 2000)`.\n *\n * ### Differences with BehaviorSubject\n *\n * `BehaviorSubject` is similar to `new ReplaySubject(1)`, with a couple of exceptions:\n *\n * 1. `BehaviorSubject` comes \"primed\" with a single value upon construction.\n * 2. `ReplaySubject` will replay values, even after observing an error, where `BehaviorSubject` will not.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n * @see {@link shareReplay}\n */\nexport class ReplaySubject extends Subject {\n private _buffer: (T | number)[] = [];\n private _infiniteTimeWindow = true;\n\n /**\n * @param bufferSize The size of the buffer to replay on subscription\n * @param windowTime The amount of time the buffered items will stay buffered\n * @param timestampProvider An object with a `now()` method that provides the current timestamp. This is used to\n * calculate the amount of time something has been buffered.\n */\n constructor(\n private _bufferSize = Infinity,\n private _windowTime = Infinity,\n private _timestampProvider: TimestampProvider = dateTimestampProvider\n ) {\n super();\n this._infiniteTimeWindow = _windowTime === Infinity;\n this._bufferSize = Math.max(1, _bufferSize);\n this._windowTime = Math.max(1, _windowTime);\n }\n\n next(value: T): void {\n const { isStopped, _buffer, _infiniteTimeWindow, _timestampProvider, _windowTime } = this;\n if (!isStopped) {\n _buffer.push(value);\n !_infiniteTimeWindow && _buffer.push(_timestampProvider.now() + _windowTime);\n }\n this._trimBuffer();\n super.next(value);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._trimBuffer();\n\n const subscription = this._innerSubscribe(subscriber);\n\n const { _infiniteTimeWindow, _buffer } = this;\n // We use a copy here, so reentrant code does not mutate our array while we're\n // emitting it to a new subscriber.\n const copy = _buffer.slice();\n for (let i = 0; i < copy.length && !subscriber.closed; i += _infiniteTimeWindow ? 1 : 2) {\n subscriber.next(copy[i] as T);\n }\n\n this._checkFinalizedStatuses(subscriber);\n\n return subscription;\n }\n\n private _trimBuffer() {\n const { _bufferSize, _timestampProvider, _buffer, _infiniteTimeWindow } = this;\n // If we don't have an infinite buffer size, and we're over the length,\n // use splice to truncate the old buffer values off. Note that we have to\n // double the size for instances where we're not using an infinite time window\n // because we're storing the values and the timestamps in the same array.\n const adjustedBufferSize = (_infiniteTimeWindow ? 1 : 2) * _bufferSize;\n _bufferSize < Infinity && adjustedBufferSize < _buffer.length && _buffer.splice(0, _buffer.length - adjustedBufferSize);\n\n // Now, if we're not in an infinite time window, remove all values where the time is\n // older than what is allowed.\n if (!_infiniteTimeWindow) {\n const now = _timestampProvider.now();\n let last = 0;\n // Search the array for the first timestamp that isn't expired and\n // truncate the buffer up to that point.\n for (let i = 1; i < _buffer.length && (_buffer[i] as number) <= now; i += 2) {\n last = i;\n }\n last && _buffer.splice(0, last + 1);\n }\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Subscription } from '../Subscription';\nimport { SchedulerAction } from '../types';\n\n/**\n * A unit of work to be executed in a `scheduler`. An action is typically\n * created from within a {@link SchedulerLike} and an RxJS user does not need to concern\n * themselves about creating and manipulating an Action.\n *\n * ```ts\n * class Action extends Subscription {\n * new (scheduler: Scheduler, work: (state?: T) => void);\n * schedule(state?: T, delay: number = 0): Subscription;\n * }\n * ```\n *\n * @class Action\n */\nexport class Action extends Subscription {\n constructor(scheduler: Scheduler, work: (this: SchedulerAction, state?: T) => void) {\n super();\n }\n /**\n * Schedules this action on its parent {@link SchedulerLike} for execution. May be passed\n * some context object, `state`. May happen at some point in the future,\n * according to the `delay` parameter, if specified.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler.\n * @return {void}\n */\n public schedule(state?: T, delay: number = 0): Subscription {\n return this;\n }\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetIntervalFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearIntervalFunction = (handle: TimerHandle) => void;\n\ninterface IntervalProvider {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n delegate:\n | {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n }\n | undefined;\n}\n\nexport const intervalProvider: IntervalProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setInterval(handler: () => void, timeout?: number, ...args) {\n const { delegate } = intervalProvider;\n if (delegate?.setInterval) {\n return delegate.setInterval(handler, timeout, ...args);\n }\n return setInterval(handler, timeout, ...args);\n },\n clearInterval(handle) {\n const { delegate } = intervalProvider;\n return (delegate?.clearInterval || clearInterval)(handle as any);\n },\n delegate: undefined,\n};\n", "import { Action } from './Action';\nimport { SchedulerAction } from '../types';\nimport { Subscription } from '../Subscription';\nimport { AsyncScheduler } from './AsyncScheduler';\nimport { intervalProvider } from './intervalProvider';\nimport { arrRemove } from '../util/arrRemove';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncAction extends Action {\n public id: TimerHandle | undefined;\n public state?: T;\n // @ts-ignore: Property has no initializer and is not definitely assigned\n public delay: number;\n protected pending: boolean = false;\n\n constructor(protected scheduler: AsyncScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (this.closed) {\n return this;\n }\n\n // Always replace the current state with the new state.\n this.state = state;\n\n const id = this.id;\n const scheduler = this.scheduler;\n\n //\n // Important implementation note:\n //\n // Actions only execute once by default, unless rescheduled from within the\n // scheduled callback. This allows us to implement single and repeat\n // actions via the same code path, without adding API surface area, as well\n // as mimic traditional recursion but across asynchronous boundaries.\n //\n // However, JS runtimes and timers distinguish between intervals achieved by\n // serial `setTimeout` calls vs. a single `setInterval` call. An interval of\n // serial `setTimeout` calls can be individually delayed, which delays\n // scheduling the next `setTimeout`, and so on. `setInterval` attempts to\n // guarantee the interval callback will be invoked more precisely to the\n // interval period, regardless of load.\n //\n // Therefore, we use `setInterval` to schedule single and repeat actions.\n // If the action reschedules itself with the same delay, the interval is not\n // canceled. If the action doesn't reschedule, or reschedules with a\n // different delay, the interval will be canceled after scheduled callback\n // execution.\n //\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, delay);\n }\n\n // Set the pending flag indicating that this action has been scheduled, or\n // has recursively rescheduled itself.\n this.pending = true;\n\n this.delay = delay;\n // If this action has already an async Id, don't request a new one.\n this.id = this.id ?? this.requestAsyncId(scheduler, this.id, delay);\n\n return this;\n }\n\n protected requestAsyncId(scheduler: AsyncScheduler, _id?: TimerHandle, delay: number = 0): TimerHandle {\n return intervalProvider.setInterval(scheduler.flush.bind(scheduler, this), delay);\n }\n\n protected recycleAsyncId(_scheduler: AsyncScheduler, id?: TimerHandle, delay: number | null = 0): TimerHandle | undefined {\n // If this action is rescheduled with the same delay time, don't clear the interval id.\n if (delay != null && this.delay === delay && this.pending === false) {\n return id;\n }\n // Otherwise, if the action's delay time is different from the current delay,\n // or the action has been rescheduled before it's executed, clear the interval id\n if (id != null) {\n intervalProvider.clearInterval(id);\n }\n\n return undefined;\n }\n\n /**\n * Immediately executes this action and the `work` it contains.\n * @return {any}\n */\n public execute(state: T, delay: number): any {\n if (this.closed) {\n return new Error('executing a cancelled action');\n }\n\n this.pending = false;\n const error = this._execute(state, delay);\n if (error) {\n return error;\n } else if (this.pending === false && this.id != null) {\n // Dequeue if the action didn't reschedule itself. Don't call\n // unsubscribe(), because the action could reschedule later.\n // For example:\n // ```\n // scheduler.schedule(function doWork(counter) {\n // /* ... I'm a busy worker bee ... */\n // var originalAction = this;\n // /* wait 100ms before rescheduling the action */\n // setTimeout(function () {\n // originalAction.schedule(counter + 1);\n // }, 100);\n // }, 1000);\n // ```\n this.id = this.recycleAsyncId(this.scheduler, this.id, null);\n }\n }\n\n protected _execute(state: T, _delay: number): any {\n let errored: boolean = false;\n let errorValue: any;\n try {\n this.work(state);\n } catch (e) {\n errored = true;\n // HACK: Since code elsewhere is relying on the \"truthiness\" of the\n // return here, we can't have it return \"\" or 0 or false.\n // TODO: Clean this up when we refactor schedulers mid-version-8 or so.\n errorValue = e ? e : new Error('Scheduled action threw falsy error');\n }\n if (errored) {\n this.unsubscribe();\n return errorValue;\n }\n }\n\n unsubscribe() {\n if (!this.closed) {\n const { id, scheduler } = this;\n const { actions } = scheduler;\n\n this.work = this.state = this.scheduler = null!;\n this.pending = false;\n\n arrRemove(actions, this);\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, null);\n }\n\n this.delay = null!;\n super.unsubscribe();\n }\n }\n}\n", "import { Action } from './scheduler/Action';\nimport { Subscription } from './Subscription';\nimport { SchedulerLike, SchedulerAction } from './types';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * An execution context and a data structure to order tasks and schedule their\n * execution. Provides a notion of (potentially virtual) time, through the\n * `now()` getter method.\n *\n * Each unit of work in a Scheduler is called an `Action`.\n *\n * ```ts\n * class Scheduler {\n * now(): number;\n * schedule(work, delay?, state?): Subscription;\n * }\n * ```\n *\n * @class Scheduler\n * @deprecated Scheduler is an internal implementation detail of RxJS, and\n * should not be used directly. Rather, create your own class and implement\n * {@link SchedulerLike}. Will be made internal in v8.\n */\nexport class Scheduler implements SchedulerLike {\n public static now: () => number = dateTimestampProvider.now;\n\n constructor(private schedulerActionCtor: typeof Action, now: () => number = Scheduler.now) {\n this.now = now;\n }\n\n /**\n * A getter method that returns a number representing the current time\n * (at the time this function was called) according to the scheduler's own\n * internal clock.\n * @return {number} A number that represents the current time. May or may not\n * have a relation to wall-clock time. May or may not refer to a time unit\n * (e.g. milliseconds).\n */\n public now: () => number;\n\n /**\n * Schedules a function, `work`, for execution. May happen at some point in\n * the future, according to the `delay` parameter, if specified. May be passed\n * some context object, `state`, which will be passed to the `work` function.\n *\n * The given arguments will be processed an stored as an Action object in a\n * queue of actions.\n *\n * @param {function(state: ?T): ?Subscription} work A function representing a\n * task, or some unit of work to be executed by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler itself.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @return {Subscription} A subscription in order to be able to unsubscribe\n * the scheduled work.\n */\n public schedule(work: (this: SchedulerAction, state?: T) => void, delay: number = 0, state?: T): Subscription {\n return new this.schedulerActionCtor(this, work).schedule(state, delay);\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Action } from './Action';\nimport { AsyncAction } from './AsyncAction';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncScheduler extends Scheduler {\n public actions: Array> = [];\n /**\n * A flag to indicate whether the Scheduler is currently executing a batch of\n * queued actions.\n * @type {boolean}\n * @internal\n */\n public _active: boolean = false;\n /**\n * An internal ID used to track the latest asynchronous task such as those\n * coming from `setTimeout`, `setInterval`, `requestAnimationFrame`, and\n * others.\n * @type {any}\n * @internal\n */\n public _scheduled: TimerHandle | undefined;\n\n constructor(SchedulerAction: typeof Action, now: () => number = Scheduler.now) {\n super(SchedulerAction, now);\n }\n\n public flush(action: AsyncAction): void {\n const { actions } = this;\n\n if (this._active) {\n actions.push(action);\n return;\n }\n\n let error: any;\n this._active = true;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions.shift()!)); // exhaust the scheduler queue\n\n this._active = false;\n\n if (error) {\n while ((action = actions.shift()!)) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\n/**\n *\n * Async Scheduler\n *\n * Schedule task as if you used setTimeout(task, duration)\n *\n * `async` scheduler schedules tasks asynchronously, by putting them on the JavaScript\n * event loop queue. It is best used to delay tasks in time or to schedule tasks repeating\n * in intervals.\n *\n * If you just want to \"defer\" task, that is to perform it right after currently\n * executing synchronous code ends (commonly achieved by `setTimeout(deferredTask, 0)`),\n * better choice will be the {@link asapScheduler} scheduler.\n *\n * ## Examples\n * Use async scheduler to delay task\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * const task = () => console.log('it works!');\n *\n * asyncScheduler.schedule(task, 2000);\n *\n * // After 2 seconds logs:\n * // \"it works!\"\n * ```\n *\n * Use async scheduler to repeat task in intervals\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * function task(state) {\n * console.log(state);\n * this.schedule(state + 1, 1000); // `this` references currently executing Action,\n * // which we reschedule with new state and delay\n * }\n *\n * asyncScheduler.schedule(task, 3000, 0);\n *\n * // Logs:\n * // 0 after 3s\n * // 1 after 4s\n * // 2 after 5s\n * // 3 after 6s\n * ```\n */\n\nexport const asyncScheduler = new AsyncScheduler(AsyncAction);\n\n/**\n * @deprecated Renamed to {@link asyncScheduler}. Will be removed in v8.\n */\nexport const async = asyncScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { Subscription } from '../Subscription';\nimport { QueueScheduler } from './QueueScheduler';\nimport { SchedulerAction } from '../types';\nimport { TimerHandle } from './timerHandle';\n\nexport class QueueAction extends AsyncAction {\n constructor(protected scheduler: QueueScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (delay > 0) {\n return super.schedule(state, delay);\n }\n this.delay = delay;\n this.state = state;\n this.scheduler.flush(this);\n return this;\n }\n\n public execute(state: T, delay: number): any {\n return delay > 0 || this.closed ? super.execute(state, delay) : this._execute(state, delay);\n }\n\n protected requestAsyncId(scheduler: QueueScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n\n if ((delay != null && delay > 0) || (delay == null && this.delay > 0)) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n\n // Otherwise flush the scheduler starting with this action.\n scheduler.flush(this);\n\n // HACK: In the past, this was returning `void`. However, `void` isn't a valid\n // `TimerHandle`, and generally the return value here isn't really used. So the\n // compromise is to return `0` which is both \"falsy\" and a valid `TimerHandle`,\n // as opposed to refactoring every other instanceo of `requestAsyncId`.\n return 0;\n }\n}\n", "import { AsyncScheduler } from './AsyncScheduler';\n\nexport class QueueScheduler extends AsyncScheduler {\n}\n", "import { QueueAction } from './QueueAction';\nimport { QueueScheduler } from './QueueScheduler';\n\n/**\n *\n * Queue Scheduler\n *\n * Put every next task on a queue, instead of executing it immediately\n *\n * `queue` scheduler, when used with delay, behaves the same as {@link asyncScheduler} scheduler.\n *\n * When used without delay, it schedules given task synchronously - executes it right when\n * it is scheduled. However when called recursively, that is when inside the scheduled task,\n * another task is scheduled with queue scheduler, instead of executing immediately as well,\n * that task will be put on a queue and wait for current one to finish.\n *\n * This means that when you execute task with `queue` scheduler, you are sure it will end\n * before any other task scheduled with that scheduler will start.\n *\n * ## Examples\n * Schedule recursively first, then do something\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(() => {\n * queueScheduler.schedule(() => console.log('second')); // will not happen now, but will be put on a queue\n *\n * console.log('first');\n * });\n *\n * // Logs:\n * // \"first\"\n * // \"second\"\n * ```\n *\n * Reschedule itself recursively\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(function(state) {\n * if (state !== 0) {\n * console.log('before', state);\n * this.schedule(state - 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * console.log('after', state);\n * }\n * }, 0, 3);\n *\n * // In scheduler that runs recursively, you would expect:\n * // \"before\", 3\n * // \"before\", 2\n * // \"before\", 1\n * // \"after\", 1\n * // \"after\", 2\n * // \"after\", 3\n *\n * // But with queue it logs:\n * // \"before\", 3\n * // \"after\", 3\n * // \"before\", 2\n * // \"after\", 2\n * // \"before\", 1\n * // \"after\", 1\n * ```\n */\n\nexport const queueScheduler = new QueueScheduler(QueueAction);\n\n/**\n * @deprecated Renamed to {@link queueScheduler}. Will be removed in v8.\n */\nexport const queue = queueScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\nimport { SchedulerAction } from '../types';\nimport { animationFrameProvider } from './animationFrameProvider';\nimport { TimerHandle } from './timerHandle';\n\nexport class AnimationFrameAction extends AsyncAction {\n constructor(protected scheduler: AnimationFrameScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n protected requestAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay is greater than 0, request as an async action.\n if (delay !== null && delay > 0) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n // Push the action to the end of the scheduler queue.\n scheduler.actions.push(this);\n // If an animation frame has already been requested, don't request another\n // one. If an animation frame hasn't been requested yet, request one. Return\n // the current animation frame request id.\n return scheduler._scheduled || (scheduler._scheduled = animationFrameProvider.requestAnimationFrame(() => scheduler.flush(undefined)));\n }\n\n protected recycleAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle | undefined {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n if (delay != null ? delay > 0 : this.delay > 0) {\n return super.recycleAsyncId(scheduler, id, delay);\n }\n // If the scheduler queue has no remaining actions with the same async id,\n // cancel the requested animation frame and set the scheduled flag to\n // undefined so the next AnimationFrameAction will request its own.\n const { actions } = scheduler;\n if (id != null && actions[actions.length - 1]?.id !== id) {\n animationFrameProvider.cancelAnimationFrame(id as number);\n scheduler._scheduled = undefined;\n }\n // Return undefined so the action knows to request a new async id if it's rescheduled.\n return undefined;\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\nexport class AnimationFrameScheduler extends AsyncScheduler {\n public flush(action?: AsyncAction): void {\n this._active = true;\n // The async id that effects a call to flush is stored in _scheduled.\n // Before executing an action, it's necessary to check the action's async\n // id to determine whether it's supposed to be executed in the current\n // flush.\n // Previous implementations of this method used a count to determine this,\n // but that was unsound, as actions that are unsubscribed - i.e. cancelled -\n // are removed from the actions array and that can shift actions that are\n // scheduled to be executed in a subsequent flush into positions at which\n // they are executed within the current flush.\n const flushId = this._scheduled;\n this._scheduled = undefined;\n\n const { actions } = this;\n let error: any;\n action = action || actions.shift()!;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions[0]) && action.id === flushId && actions.shift());\n\n this._active = false;\n\n if (error) {\n while ((action = actions[0]) && action.id === flushId && actions.shift()) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AnimationFrameAction } from './AnimationFrameAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\n\n/**\n *\n * Animation Frame Scheduler\n *\n * Perform task when `window.requestAnimationFrame` would fire\n *\n * When `animationFrame` scheduler is used with delay, it will fall back to {@link asyncScheduler} scheduler\n * behaviour.\n *\n * Without delay, `animationFrame` scheduler can be used to create smooth browser animations.\n * It makes sure scheduled task will happen just before next browser content repaint,\n * thus performing animations as efficiently as possible.\n *\n * ## Example\n * Schedule div height animation\n * ```ts\n * // html:
\n * import { animationFrameScheduler } from 'rxjs';\n *\n * const div = document.querySelector('div');\n *\n * animationFrameScheduler.schedule(function(height) {\n * div.style.height = height + \"px\";\n *\n * this.schedule(height + 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * }, 0, 0);\n *\n * // You will see a div element growing in height\n * ```\n */\n\nexport const animationFrameScheduler = new AnimationFrameScheduler(AnimationFrameAction);\n\n/**\n * @deprecated Renamed to {@link animationFrameScheduler}. Will be removed in v8.\n */\nexport const animationFrame = animationFrameScheduler;\n", "import { Observable } from '../Observable';\nimport { SchedulerLike } from '../types';\n\n/**\n * A simple Observable that emits no items to the Observer and immediately\n * emits a complete notification.\n *\n * Just emits 'complete', and nothing else.\n *\n * ![](empty.png)\n *\n * A simple Observable that only emits the complete notification. It can be used\n * for composing with other Observables, such as in a {@link mergeMap}.\n *\n * ## Examples\n *\n * Log complete notification\n *\n * ```ts\n * import { EMPTY } from 'rxjs';\n *\n * EMPTY.subscribe({\n * next: () => console.log('Next'),\n * complete: () => console.log('Complete!')\n * });\n *\n * // Outputs\n * // Complete!\n * ```\n *\n * Emit the number 7, then complete\n *\n * ```ts\n * import { EMPTY, startWith } from 'rxjs';\n *\n * const result = EMPTY.pipe(startWith(7));\n * result.subscribe(x => console.log(x));\n *\n * // Outputs\n * // 7\n * ```\n *\n * Map and flatten only odd numbers to the sequence `'a'`, `'b'`, `'c'`\n *\n * ```ts\n * import { interval, mergeMap, of, EMPTY } from 'rxjs';\n *\n * const interval$ = interval(1000);\n * const result = interval$.pipe(\n * mergeMap(x => x % 2 === 1 ? of('a', 'b', 'c') : EMPTY),\n * );\n * result.subscribe(x => console.log(x));\n *\n * // Results in the following to the console:\n * // x is equal to the count on the interval, e.g. (0, 1, 2, 3, ...)\n * // x will occur every 1000ms\n * // if x % 2 is equal to 1, print a, b, c (each on its own)\n * // if x % 2 is not equal to 1, nothing will be output\n * ```\n *\n * @see {@link Observable}\n * @see {@link NEVER}\n * @see {@link of}\n * @see {@link throwError}\n */\nexport const EMPTY = new Observable((subscriber) => subscriber.complete());\n\n/**\n * @param scheduler A {@link SchedulerLike} to use for scheduling\n * the emission of the complete notification.\n * @deprecated Replaced with the {@link EMPTY} constant or {@link scheduled} (e.g. `scheduled([], scheduler)`). Will be removed in v8.\n */\nexport function empty(scheduler?: SchedulerLike) {\n return scheduler ? emptyScheduled(scheduler) : EMPTY;\n}\n\nfunction emptyScheduled(scheduler: SchedulerLike) {\n return new Observable((subscriber) => scheduler.schedule(() => subscriber.complete()));\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport function isScheduler(value: any): value is SchedulerLike {\n return value && isFunction(value.schedule);\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\nimport { isScheduler } from './isScheduler';\n\nfunction last(arr: T[]): T | undefined {\n return arr[arr.length - 1];\n}\n\nexport function popResultSelector(args: any[]): ((...args: unknown[]) => unknown) | undefined {\n return isFunction(last(args)) ? args.pop() : undefined;\n}\n\nexport function popScheduler(args: any[]): SchedulerLike | undefined {\n return isScheduler(last(args)) ? args.pop() : undefined;\n}\n\nexport function popNumber(args: any[], defaultValue: number): number {\n return typeof last(args) === 'number' ? args.pop()! : defaultValue;\n}\n", "export const isArrayLike = ((x: any): x is ArrayLike => x && typeof x.length === 'number' && typeof x !== 'function');", "import { isFunction } from \"./isFunction\";\n\n/**\n * Tests to see if the object is \"thennable\".\n * @param value the object to test\n */\nexport function isPromise(value: any): value is PromiseLike {\n return isFunction(value?.then);\n}\n", "import { InteropObservable } from '../types';\nimport { observable as Symbol_observable } from '../symbol/observable';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being Observable (but not necessary an Rx Observable) */\nexport function isInteropObservable(input: any): input is InteropObservable {\n return isFunction(input[Symbol_observable]);\n}\n", "import { isFunction } from './isFunction';\n\nexport function isAsyncIterable(obj: any): obj is AsyncIterable {\n return Symbol.asyncIterator && isFunction(obj?.[Symbol.asyncIterator]);\n}\n", "/**\n * Creates the TypeError to throw if an invalid object is passed to `from` or `scheduled`.\n * @param input The object that was passed.\n */\nexport function createInvalidObservableTypeError(input: any) {\n // TODO: We should create error codes that can be looked up, so this can be less verbose.\n return new TypeError(\n `You provided ${\n input !== null && typeof input === 'object' ? 'an invalid object' : `'${input}'`\n } where a stream was expected. You can provide an Observable, Promise, ReadableStream, Array, AsyncIterable, or Iterable.`\n );\n}\n", "export function getSymbolIterator(): symbol {\n if (typeof Symbol !== 'function' || !Symbol.iterator) {\n return '@@iterator' as any;\n }\n\n return Symbol.iterator;\n}\n\nexport const iterator = getSymbolIterator();\n", "import { iterator as Symbol_iterator } from '../symbol/iterator';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being an Iterable */\nexport function isIterable(input: any): input is Iterable {\n return isFunction(input?.[Symbol_iterator]);\n}\n", "import { ReadableStreamLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport async function* readableStreamLikeToAsyncGenerator(readableStream: ReadableStreamLike): AsyncGenerator {\n const reader = readableStream.getReader();\n try {\n while (true) {\n const { value, done } = await reader.read();\n if (done) {\n return;\n }\n yield value!;\n }\n } finally {\n reader.releaseLock();\n }\n}\n\nexport function isReadableStreamLike(obj: any): obj is ReadableStreamLike {\n // We don't want to use instanceof checks because they would return\n // false for instances from another Realm, like an + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/objects.inv b/objects.inv new file mode 100644 index 0000000..34d202d --- /dev/null +++ b/objects.inv @@ -0,0 +1,7 @@ +# Sphinx inventory version 2 +# Project: eo-tides +# Version: 0.0.0 +# The remainder of this file is compressed using zlib. +xڕ + } +2`TW $Ⱥ~3H+w{!qreo-tides: Tide modelling tools for large-scale satellite earth observation analysis","text":"

Warning

Note: This package is a work in progress, and not currently ready for operational use.

The eo-tides package provides tools for analysing coastal and ocean satellite earth observation data using information about ocean tides.

eo-tides combines advanced tide modelling functionality from the pyTMD package and integrates it with pandas, xarray and odc-geo to provide a powerful set of parallelised tools for integrating satellite imagery with tide data \u2013 from local, regional to continental scale.

Some key functionality includes the ability to:

  • Model tides from multiple global ocean tide models in parallel, and return tide heights in standardised pandas.DataFrame format for further analysis
  • \"Tag\" satellite data with tide height and stage based on the exact moment of image acquisition
  • Model tides for every individual satellite pixel, producing three-dimensional \"tide height\" xarray-format datacubes that can be combined with satellite data
  • Combine multiple tide models into a single locally-optimised \"ensemble\" model informed by satellite altimetry and satellite-observed patterns of tidal inundation
  • Calculate statistics describing local tide dynamics, as well as biases caused by interactions between tidal processes and satellite orbits
  • Validate modelled tides using measured sea levels from coastal tide gauges (e.g. GESLA)

These tools can be applied directly to petabytes of freely available satellite data (e.g. from Digital Earth Australia or Microsoft Planetary Computer) loaded via Open Data Cube's odc-stac or datacube packages, supporting coastal and ocean earth observation analysis for any time period or location globally.

"},{"location":"#supported-tide-models","title":"Supported tide models","text":"

eo-tides supports all ocean tide models supported by pyTMD. These include:

  • Finite Element Solution tide models (FES2022, FES2014, FES2012)
  • TOPEX/POSEIDON global tide models (TPXO10, TPXO9, TPXO8)
  • Global Ocean Tide models (GOT5.6, GOT5.5, GOT4.10)
  • Empirical Ocean Tide models (EOT20)
  • Hamburg direct data Assimilation Methods for Tides models (HAMTIDE11)

For instructions on how to set up these models for use in eo-tides, refer to Setting up tide models.

"},{"location":"#citing-eo-tides","title":"Citing eo-tides","text":"

To cite eo-tides in your work, please use the following citation:

Bishop-Taylor, R., Sagar, S., Phillips, C., & Newey, V. (2024). eo-tides: Tide modelling tools for large-scale satellite earth observation analysis [Computer software]. https://github.com/GeoscienceAustralia/eo-tides\n
"},{"location":"api/","title":"API reference","text":""},{"location":"api/#eo_tides.model","title":"eo_tides.model","text":""},{"location":"api/#eo_tides.model.model_tides","title":"model_tides","text":"
model_tides(\n    x,\n    y,\n    time,\n    model=\"FES2014\",\n    directory=None,\n    crs=\"EPSG:4326\",\n    crop=True,\n    method=\"spline\",\n    extrapolate=True,\n    cutoff=None,\n    mode=\"one-to-many\",\n    parallel=True,\n    parallel_splits=5,\n    output_units=\"m\",\n    output_format=\"long\",\n    ensemble_models=None,\n    **ensemble_kwargs\n)\n

Compute tides at multiple points and times using tidal harmonics.

This function supports all tidal models supported by pyTMD, including FES Finite Element Solution models, TPXO TOPEX/POSEIDON models, EOT Empirical Ocean Tide models, GOT Global Ocean Tide models, and HAMTIDE Hamburg direct data Assimilation Methods for Tides models.

This function requires access to tide model data files. These should be placed in a folder with subfolders matching the formats specified by pyTMD: https://pytmd.readthedocs.io/en/latest/getting_started/Getting-Started.html#directories

For FES2014 (https://www.aviso.altimetry.fr/es/data/products/auxiliary-products/global-tide-fes/description-fes2014.html):

  • {directory}/fes2014/ocean_tide/

For FES2022 (https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/global-tide-fes.html):

  • {directory}/fes2022b/ocean_tide/

For TPXO8-atlas (https://www.tpxo.net/tpxo-products-and-registration):

  • {directory}/tpxo8_atlas/

For TPXO9-atlas-v5 (https://www.tpxo.net/tpxo-products-and-registration):

  • {directory}/TPXO9_atlas_v5/

For EOT20 (https://www.seanoe.org/data/00683/79489/):

  • {directory}/EOT20/ocean_tides/

For GOT4.10c (https://earth.gsfc.nasa.gov/geo/data/ocean-tide-models):

  • {directory}/GOT4.10c/grids_oceantide_netcdf/

For HAMTIDE (https://www.cen.uni-hamburg.de/en/icdc/data/ocean/hamtide.html):

  • {directory}/hamtide/

This function is a modification of the pyTMD package's compute_tide_corrections function. For more info: https://pytmd.readthedocs.io/en/stable/user_guide/compute_tide_corrections.html

Parameters:

Name Type Description Default x float or list of floats

One or more x and y coordinates used to define the location at which to model tides. By default these coordinates should be lat/lon; use \"crs\" if they are in a custom coordinate reference system.

required y float or list of floats

One or more x and y coordinates used to define the location at which to model tides. By default these coordinates should be lat/lon; use \"crs\" if they are in a custom coordinate reference system.

required time A datetime array or pandas.DatetimeIndex

An array containing datetime64[ns] values or a pandas.DatetimeIndex providing the times at which to model tides in UTC time.

required model string

The tide model used to model tides. Options include:

  • \"FES2014\" (pre-configured on DEA Sandbox)
  • \"FES2022\"
  • \"TPXO9-atlas-v5\"
  • \"TPXO8-atlas\"
  • \"EOT20\"
  • \"HAMTIDE11\"
  • \"GOT4.10\"
  • \"ensemble\" (advanced ensemble tide model functionality; combining multiple models based on external model rankings)
'FES2014' directory string

The directory containing tide model data files. If no path is provided, this will default to the environment variable DEA_TOOLS_TIDE_MODELS if set, otherwise \"/var/share/tide_models\". Tide modelling files should be stored in sub-folders for each model that match the structure provided by pyTMD.

For example:

  • {directory}/fes2014/ocean_tide/
  • {directory}/tpxo8_atlas/
  • {directory}/TPXO9_atlas_v5/
None crs str

Input coordinate reference system for x and y coordinates. Defaults to \"EPSG:4326\" (WGS84; degrees latitude, longitude).

'EPSG:4326' crop bool optional

Whether to crop tide model constituent files on-the-fly to improve performance. Cropping will be performed based on a 1 degree buffer around all input points. Defaults to True.

True method string

Method used to interpolate tidal constituents from model files. Options include:

  • \"spline\": scipy bivariate spline interpolation (default)
  • \"bilinear\": quick bilinear interpolation
  • \"linear\", \"nearest\": scipy regular grid interpolations
'spline' extrapolate bool

Whether to extrapolate tides for x and y coordinates outside of the valid tide modelling domain using nearest-neighbor.

True cutoff int or float

Extrapolation cutoff in kilometers. The default is None, which will extrapolate for all points regardless of distance from the valid tide modelling domain.

None mode string

The analysis mode to use for tide modelling. Supports two options:

  • \"one-to-many\": Models tides for every timestep in \"time\" at every input x and y coordinate point. This is useful if you want to model tides for a specific list of timesteps across multiple spatial points (e.g. for the same set of satellite acquisition times at various locations across your study area).
  • \"one-to-one\": Model tides using a different timestep for each x and y coordinate point. In this mode, the number of x and y points must equal the number of timesteps provided in \"time\".
'one-to-many' parallel boolean

Whether to parallelise tide modelling using concurrent.futures. If multiple tide models are requested, these will be run in parallel. Optionally, tide modelling can also be run in parallel across input x and y coordinates (see \"parallel_splits\" below). Default is True.

True parallel_splits int

Whether to split the input x and y coordinates into smaller, evenly-sized chunks that are processed in parallel. This can provide a large performance boost when processing large numbers of coordinates. The default is 5 chunks, which will split coordinates into 5 parallelised chunks.

5 output_units str

Whether to return modelled tides in floating point metre units, or integer centimetre units (i.e. scaled by 100) or integer millimetre units (i.e. scaled by 1000. Returning outputs in integer units can be useful for reducing memory usage. Defaults to \"m\" for metres; set to \"cm\" for centimetres or \"mm\" for millimetres.

'm' output_format str

Whether to return the output dataframe in long format (with results stacked vertically along \"tide_model\" and \"tide_m\" columns), or wide format (with a column for each tide model). Defaults to \"long\".

'long' ensemble_models list

An optional list of models used to generate the ensemble tide model if \"ensemble\" tide modelling is requested. Defaults to [\"FES2014\", \"TPXO9-atlas-v5\", \"EOT20\", \"HAMTIDE11\", \"GOT4.10\", \"FES2012\", \"TPXO8-atlas-v1\"].

None **ensemble_kwargs

Keyword arguments used to customise the generation of optional ensemble tide models if \"ensemble\" modelling are requested. These are passed to the underlying _ensemble_model function. Useful parameters include ranking_points (path to model rankings data), k (for controlling how model rankings are interpolated), and ensemble_top_n (how many top models to use in the ensemble calculation).

{}

Returns:

Type Description DataFrame

A dataframe containing modelled tide heights.

Source code in eo_tides/model.py 
def model_tides(\n    x,\n    y,\n    time,\n    model=\"FES2014\",\n    directory=None,\n    crs=\"EPSG:4326\",\n    crop=True,\n    method=\"spline\",\n    extrapolate=True,\n    cutoff=None,\n    mode=\"one-to-many\",\n    parallel=True,\n    parallel_splits=5,\n    output_units=\"m\",\n    output_format=\"long\",\n    ensemble_models=None,\n    **ensemble_kwargs,\n):\n    \"\"\"Compute tides at multiple points and times using tidal harmonics.\n\n    This function supports all tidal models supported by `pyTMD`,\n    including FES Finite Element Solution models, TPXO TOPEX/POSEIDON\n    models, EOT Empirical Ocean Tide models, GOT Global Ocean Tide\n    models, and HAMTIDE Hamburg direct data Assimilation Methods for\n    Tides models.\n\n    This function requires access to tide model data files.\n    These should be placed in a folder with subfolders matching\n    the formats specified by `pyTMD`:\n    <https://pytmd.readthedocs.io/en/latest/getting_started/Getting-Started.html#directories>\n\n    For FES2014 (<https://www.aviso.altimetry.fr/es/data/products/auxiliary-products/global-tide-fes/description-fes2014.html>):\n\n    - `{directory}/fes2014/ocean_tide/`\n\n    For FES2022 (<https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/global-tide-fes.html>):\n\n    - `{directory}/fes2022b/ocean_tide/`\n\n    For TPXO8-atlas (<https://www.tpxo.net/tpxo-products-and-registration>):\n\n    - `{directory}/tpxo8_atlas/`\n\n    For TPXO9-atlas-v5 (<https://www.tpxo.net/tpxo-products-and-registration>):\n\n    - `{directory}/TPXO9_atlas_v5/`\n\n    For EOT20 (<https://www.seanoe.org/data/00683/79489/>):\n\n    - `{directory}/EOT20/ocean_tides/`\n\n    For GOT4.10c (<https://earth.gsfc.nasa.gov/geo/data/ocean-tide-models>):\n\n    - `{directory}/GOT4.10c/grids_oceantide_netcdf/`\n\n    For HAMTIDE (<https://www.cen.uni-hamburg.de/en/icdc/data/ocean/hamtide.html>):\n\n    - `{directory}/hamtide/`\n\n    This function is a modification of the `pyTMD` package's\n    `compute_tide_corrections` function. For more info:\n    <https://pytmd.readthedocs.io/en/stable/user_guide/compute_tide_corrections.html>\n\n    Parameters\n    ----------\n    x, y : float or list of floats\n        One or more x and y coordinates used to define\n        the location at which to model tides. By default these\n        coordinates should be lat/lon; use \"crs\" if they\n        are in a custom coordinate reference system.\n    time : A datetime array or pandas.DatetimeIndex\n        An array containing `datetime64[ns]` values or a\n        `pandas.DatetimeIndex` providing the times at which to\n        model tides in UTC time.\n    model : string, optional\n        The tide model used to model tides. Options include:\n\n        - \"FES2014\" (pre-configured on DEA Sandbox)\n        - \"FES2022\"\n        - \"TPXO9-atlas-v5\"\n        - \"TPXO8-atlas\"\n        - \"EOT20\"\n        - \"HAMTIDE11\"\n        - \"GOT4.10\"\n        - \"ensemble\" (advanced ensemble tide model functionality;\n          combining multiple models based on external model rankings)\n    directory : string, optional\n        The directory containing tide model data files. If no path is\n        provided, this will default to the environment variable\n        `DEA_TOOLS_TIDE_MODELS` if set, otherwise \"/var/share/tide_models\".\n        Tide modelling files should be stored in sub-folders for each\n        model that match the structure provided by `pyTMD`.\n\n        For example:\n\n        - `{directory}/fes2014/ocean_tide/`\n        - `{directory}/tpxo8_atlas/`\n        - `{directory}/TPXO9_atlas_v5/`\n    crs : str, optional\n        Input coordinate reference system for x and y coordinates.\n        Defaults to \"EPSG:4326\" (WGS84; degrees latitude, longitude).\n    crop : bool optional\n        Whether to crop tide model constituent files on-the-fly to\n        improve performance. Cropping will be performed based on a\n        1 degree buffer around all input points. Defaults to True.\n    method : string, optional\n        Method used to interpolate tidal constituents\n        from model files. Options include:\n\n        - \"spline\": scipy bivariate spline interpolation (default)\n        - \"bilinear\": quick bilinear interpolation\n        - \"linear\", \"nearest\": scipy regular grid interpolations\n    extrapolate : bool, optional\n        Whether to extrapolate tides for x and y coordinates outside of\n        the valid tide modelling domain using nearest-neighbor.\n    cutoff : int or float, optional\n        Extrapolation cutoff in kilometers. The default is None, which\n        will extrapolate for all points regardless of distance from the\n        valid tide modelling domain.\n    mode : string, optional\n        The analysis mode to use for tide modelling. Supports two options:\n\n        - \"one-to-many\": Models tides for every timestep in \"time\" at\n        every input x and y coordinate point. This is useful if you\n        want to model tides for a specific list of timesteps across\n        multiple spatial points (e.g. for the same set of satellite\n        acquisition times at various locations across your study area).\n        - \"one-to-one\": Model tides using a different timestep for each\n        x and y coordinate point. In this mode, the number of x and\n        y points must equal the number of timesteps provided in \"time\".\n    parallel : boolean, optional\n        Whether to parallelise tide modelling using `concurrent.futures`.\n        If multiple tide models are requested, these will be run in\n        parallel. Optionally, tide modelling can also be run in parallel\n        across input x and y coordinates (see \"parallel_splits\" below).\n        Default is True.\n    parallel_splits : int, optional\n        Whether to split the input x and y coordinates into smaller,\n        evenly-sized chunks that are processed in parallel. This can\n        provide a large performance boost when processing large numbers\n        of coordinates. The default is 5 chunks, which will split\n        coordinates into 5 parallelised chunks.\n    output_units : str, optional\n        Whether to return modelled tides in floating point metre units,\n        or integer centimetre units (i.e. scaled by 100) or integer\n        millimetre units (i.e. scaled by 1000. Returning outputs in\n        integer units can be useful for reducing memory usage.\n        Defaults to \"m\" for metres; set to \"cm\" for centimetres or \"mm\"\n        for millimetres.\n    output_format : str, optional\n        Whether to return the output dataframe in long format (with\n        results stacked vertically along \"tide_model\" and \"tide_m\"\n        columns), or wide format (with a column for each tide model).\n        Defaults to \"long\".\n    ensemble_models : list, optional\n        An optional list of models used to generate the ensemble tide\n        model if \"ensemble\" tide modelling is requested. Defaults to\n        [\"FES2014\", \"TPXO9-atlas-v5\", \"EOT20\", \"HAMTIDE11\", \"GOT4.10\",\n        \"FES2012\", \"TPXO8-atlas-v1\"].\n    **ensemble_kwargs :\n        Keyword arguments used to customise the generation of optional\n        ensemble tide models if \"ensemble\" modelling are requested.\n        These are passed to the underlying `_ensemble_model` function.\n        Useful parameters include `ranking_points` (path to model\n        rankings data), `k` (for controlling how model rankings are\n        interpolated), and `ensemble_top_n` (how many top models to use\n        in the ensemble calculation).\n\n    Returns\n    -------\n    pandas.DataFrame\n        A dataframe containing modelled tide heights.\n\n    \"\"\"\n    # Set tide modelling files directory. If no custom path is provided,\n    # first try global environmental var, then \"/var/share/tide_models\"\n    if directory is None:\n        if \"DEA_TOOLS_TIDE_MODELS\" in os.environ:\n            directory = os.environ[\"DEA_TOOLS_TIDE_MODELS\"]\n        else:\n            directory = \"/var/share/tide_models\"\n\n    # Verify path exists\n    directory = pathlib.Path(directory).expanduser()\n    if not directory.exists():\n        raise FileNotFoundError(\"Invalid tide directory\")\n\n    # If time passed as a single Timestamp, convert to datetime64\n    if isinstance(time, pd.Timestamp):\n        time = time.to_datetime64()\n\n    # Turn inputs into arrays for consistent handling\n    models_requested = np.atleast_1d(model)\n    x = np.atleast_1d(x)\n    y = np.atleast_1d(y)\n    time = np.atleast_1d(time)\n\n    # Validate input arguments\n    assert method in (\"bilinear\", \"spline\", \"linear\", \"nearest\")\n    assert output_units in (\n        \"m\",\n        \"cm\",\n        \"mm\",\n    ), \"Output units must be either 'm', 'cm', or 'mm'.\"\n    assert output_format in (\n        \"long\",\n        \"wide\",\n    ), \"Output format must be either 'long' or 'wide'.\"\n    assert len(x) == len(y), \"x and y must be the same length.\"\n    if mode == \"one-to-one\":\n        assert len(x) == len(time), (\n            \"The number of supplied x and y points and times must be \"\n            \"identical in 'one-to-one' mode. Use 'one-to-many' mode if \"\n            \"you intended to model multiple timesteps at each point.\"\n        )\n\n    # Verify that all provided models are supported\n    valid_models = [\n        # Standard built-in pyTMD models\n        \"EOT20\",\n        \"FES2014\",\n        \"FES2022\",\n        \"GOT4.10\",\n        \"HAMTIDE11\",\n        \"TPXO8-atlas\",  # binary version, not suitable for clipping\n        \"TPXO9-atlas-v5\",\n        # Non-standard models, defined internally\n        \"FES2012\",\n        \"FES2014_extrapolated\",\n        \"FES2022_extrapolated\",\n        \"GOT5.6\",\n        \"GOT5.6_extrapolated\",\n        \"TPXO8-atlas-v1\",  # netCDF version\n        # Advanced ensemble model functionality\n        \"ensemble\",\n    ]\n    if not all(m in valid_models for m in models_requested):\n        raise ValueError(\n            f\"One or more of the models requested {models_requested} is \"\n            f\"not valid. The following models are currently supported: \"\n            f\"{valid_models}\",\n        )\n\n    # If ensemble modelling is requested, use a custom list of models\n    # for subsequent processing\n    if \"ensemble\" in models_requested:\n        print(\"Running ensemble tide modelling\")\n        models_to_process = (\n            ensemble_models\n            if ensemble_models is not None\n            else [\n                \"FES2014\",\n                \"TPXO9-atlas-v5\",\n                \"EOT20\",\n                \"HAMTIDE11\",\n                \"GOT4.10\",\n                \"FES2012\",\n                \"TPXO8-atlas-v1\",\n            ]\n        )\n\n    # Otherwise, models to process are the same as those requested\n    else:\n        models_to_process = models_requested\n\n    # Update tide modelling func to add default keyword arguments that\n    # are used for every iteration during parallel processing\n    iter_func = partial(\n        _model_tides,\n        directory=directory,\n        crs=crs,\n        crop=crop,\n        method=method,\n        extrapolate=extrapolate,\n        cutoff=np.inf if cutoff is None else cutoff,\n        output_units=output_units,\n        mode=mode,\n    )\n\n    # Ensure requested parallel splits is not smaller than number of points\n    parallel_splits = min(parallel_splits, len(x))\n\n    # Parallelise if either multiple models or multiple splits requested\n    if parallel & ((len(models_to_process) > 1) | (parallel_splits > 1)):\n        with ProcessPoolExecutor() as executor:\n            print(f\"Modelling tides using {', '.join(models_to_process)} in parallel\")\n\n            # Optionally split lon/lat points into `splits_n` chunks\n            # that will be applied in parallel\n            x_split = np.array_split(x, parallel_splits)\n            y_split = np.array_split(y, parallel_splits)\n\n            # Get every combination of models and lat/lon points, and\n            # extract as iterables that can be passed to `executor.map()`\n            # In \"one-to-many\" mode, pass entire set of timesteps to each\n            # parallel iteration by repeating timesteps by number of total\n            # parallel iterations. In \"one-to-one\" mode, split up\n            # timesteps into smaller parallel chunks too.\n            if mode == \"one-to-many\":\n                model_iters, x_iters, y_iters = zip(\n                    *[(m, x_split[i], y_split[i]) for m in models_to_process for i in range(parallel_splits)],\n                )\n                time_iters = [time] * len(model_iters)\n            elif mode == \"one-to-one\":\n                time_split = np.array_split(time, parallel_splits)\n                model_iters, x_iters, y_iters, time_iters = zip(\n                    *[\n                        (m, x_split[i], y_split[i], time_split[i])\n                        for m in models_to_process\n                        for i in range(parallel_splits)\n                    ],\n                )\n\n            # Apply func in parallel, iterating through each input param\n            model_outputs = list(\n                tqdm(\n                    executor.map(iter_func, model_iters, x_iters, y_iters, time_iters),\n                    total=len(model_iters),\n                ),\n            )\n\n    # Model tides in series if parallelisation is off\n    else:\n        model_outputs = []\n\n        for model_i in models_to_process:\n            print(f\"Modelling tides using {model_i}\")\n            tide_df = iter_func(model_i, x, y, time)\n            model_outputs.append(tide_df)\n\n    # Combine outputs into a single dataframe\n    tide_df = pd.concat(model_outputs, axis=0)\n\n    # Optionally compute ensemble model and add to dataframe\n    if \"ensemble\" in models_requested:\n        ensemble_df = _ensemble_model(x, y, crs, tide_df, models_to_process, **ensemble_kwargs)\n\n        # Update requested models with any custom ensemble models, then\n        # filter the dataframe to keep only models originally requested\n        models_requested = np.union1d(models_requested, ensemble_df.tide_model.unique())\n        tide_df = pd.concat([tide_df, ensemble_df]).query(\"tide_model in @models_requested\")\n\n    # Optionally convert to a wide format dataframe with a tide model in\n    # each dataframe column\n    if output_format == \"wide\":\n        # Pivot into wide format with each time model as a column\n        print(\"Converting to a wide format dataframe\")\n        tide_df = tide_df.pivot(columns=\"tide_model\", values=\"tide_m\")\n\n        # If in 'one-to-one' mode, reindex using our input time/x/y\n        # values to ensure the output is sorted the same as our inputs\n        if mode == \"one-to-one\":\n            output_indices = pd.MultiIndex.from_arrays([time, x, y], names=[\"time\", \"x\", \"y\"])\n            tide_df = tide_df.reindex(output_indices)\n\n    return tide_df\n
"},{"location":"api/#eo_tides.model.pixel_tides","title":"pixel_tides","text":"
pixel_tides(\n    ds,\n    times=None,\n    resample=True,\n    calculate_quantiles=None,\n    resolution=None,\n    buffer=None,\n    resample_method=\"bilinear\",\n    model=\"FES2014\",\n    dask_chunks=\"auto\",\n    dask_compute=True,\n    **model_tides_kwargs\n)\n

Obtain tide heights for each pixel in a dataset by modelling tides into a low-resolution grid surrounding the dataset, then (optionally) spatially resample this low-res data back into the original higher resolution dataset extent and resolution.

Parameters:

Name Type Description Default ds Dataset

A dataset whose geobox (ds.odc.geobox) will be used to define the spatial extent of the low resolution tide modelling grid.

required times pandas.DatetimeIndex or list of pandas.Timestamps

By default, the function will model tides using the times contained in the time dimension of ds. Alternatively, this param can be used to model tides for a custom set of times instead. For example: times=pd.date_range(start=\"2000\", end=\"2001\", freq=\"5h\")

None resample bool

Whether to resample low resolution tides back into ds's original higher resolution grid. Set this to False if you do not want low resolution tides to be re-projected back to higher resolution.

True calculate_quantiles list or array

Rather than returning all individual tides, low-resolution tides can be first aggregated using a quantile calculation by passing in a list or array of quantiles to compute. For example, this could be used to calculate the min/max tide across all times: calculate_quantiles=[0.0, 1.0].

None resolution int

The desired resolution of the low-resolution grid used for tide modelling. The default None will create a 5000 m resolution grid if ds has a projected CRS (i.e. metre units), or a 0.05 degree resolution grid if ds has a geographic CRS (e.g. degree units). Note: higher resolutions do not necessarily provide better tide modelling performance, as results will be limited by the resolution of the underlying global tide model (e.g. 1/16th degree / ~5 km resolution grid for FES2014).

None buffer int

The amount by which to buffer the higher resolution grid extent when creating the new low resolution grid. This buffering is important as it ensures that ensure pixel-based tides are seamless across dataset boundaries. This buffer will eventually be clipped away when the low-resolution data is re-projected back to the resolution and extent of the higher resolution dataset. To ensure that at least two pixels occur outside of the dataset bounds, the default None applies a 12000 m buffer if ds has a projected CRS (i.e. metre units), or a 0.12 degree buffer if ds has a geographic CRS (e.g. degree units).

None resample_method string

If resampling is requested (see resample above), use this resampling method when converting from low resolution to high resolution pixels. Defaults to \"bilinear\"; valid options include \"nearest\", \"cubic\", \"min\", \"max\", \"average\" etc.

'bilinear' model string or list of strings

The tide model or a list of models used to model tides, as supported by the pyTMD Python package. Options include: - \"FES2014\" (default; pre-configured on DEA Sandbox) - \"FES2022\" - \"TPXO8-atlas\" - \"TPXO9-atlas-v5\" - \"EOT20\" - \"HAMTIDE11\" - \"GOT4.10\"

'FES2014' dask_chunks str or tuple

Can be used to configure custom Dask chunking for the final resampling step. The default of \"auto\" will automatically set x/y chunks to match those in ds if they exist, otherwise will set x/y chunks that cover the entire extent of the dataset. For custom chunks, provide a tuple in the form (y, x), e.g. (2048, 2048).

'auto' dask_compute bool

Whether to compute results of the resampling step using Dask. If False, this will return tides_highres as a Dask array.

True **model_tides_kwargs

Optional parameters passed to the dea_tools.coastal.model_tides function. Important parameters include \"directory\" (used to specify the location of input tide modelling files) and \"cutoff\" (used to extrapolate modelled tides away from the coast; if not specified here, cutoff defaults to np.inf).

{}

Returns:

Type Description If `resample` is False:

tides_lowres : xr.DataArray A low resolution data array giving either tide heights every timestep in ds (if times is None), tide heights at every time in times (if times is not None), or tide height quantiles for every quantile provided by calculate_quantiles.

If `resample` is True:

tides_highres, tides_lowres : tuple of xr.DataArrays In addition to tides_lowres (see above), a high resolution array of tide heights will be generated that matches the exact spatial resolution and extent of ds. This will contain either tide heights every timestep in ds (if times is None), tide heights at every time in times (if times is not None), or tide height quantiles for every quantile provided by calculate_quantiles.

Source code in eo_tides/model.py 
def pixel_tides(\n    ds,\n    times=None,\n    resample=True,\n    calculate_quantiles=None,\n    resolution=None,\n    buffer=None,\n    resample_method=\"bilinear\",\n    model=\"FES2014\",\n    dask_chunks=\"auto\",\n    dask_compute=True,\n    **model_tides_kwargs,\n):\n    \"\"\"Obtain tide heights for each pixel in a dataset by modelling\n    tides into a low-resolution grid surrounding the dataset,\n    then (optionally) spatially resample this low-res data back\n    into the original higher resolution dataset extent and resolution.\n\n    Parameters\n    ----------\n    ds : xarray.Dataset\n        A dataset whose geobox (`ds.odc.geobox`) will be used to define\n        the spatial extent of the low resolution tide modelling grid.\n    times : pandas.DatetimeIndex or list of pandas.Timestamps, optional\n        By default, the function will model tides using the times\n        contained in the `time` dimension of `ds`. Alternatively, this\n        param can be used to model tides for a custom set of times\n        instead. For example:\n        `times=pd.date_range(start=\"2000\", end=\"2001\", freq=\"5h\")`\n    resample : bool, optional\n        Whether to resample low resolution tides back into `ds`'s original\n        higher resolution grid. Set this to `False` if you do not want\n        low resolution tides to be re-projected back to higher resolution.\n    calculate_quantiles : list or np.array, optional\n        Rather than returning all individual tides, low-resolution tides\n        can be first aggregated using a quantile calculation by passing in\n        a list or array of quantiles to compute. For example, this could\n        be used to calculate the min/max tide across all times:\n        `calculate_quantiles=[0.0, 1.0]`.\n    resolution : int, optional\n        The desired resolution of the low-resolution grid used for tide\n        modelling. The default None will create a 5000 m resolution grid\n        if `ds` has a projected CRS (i.e. metre units), or a 0.05 degree\n        resolution grid if `ds` has a geographic CRS (e.g. degree units).\n        Note: higher resolutions do not necessarily provide better\n        tide modelling performance, as results will be limited by the\n        resolution of the underlying global tide model (e.g. 1/16th\n        degree / ~5 km resolution grid for FES2014).\n    buffer : int, optional\n        The amount by which to buffer the higher resolution grid extent\n        when creating the new low resolution grid. This buffering is\n        important as it ensures that ensure pixel-based tides are seamless\n        across dataset boundaries. This buffer will eventually be clipped\n        away when the low-resolution data is re-projected back to the\n        resolution and extent of the higher resolution dataset. To\n        ensure that at least two pixels occur outside of the dataset\n        bounds, the default None applies a 12000 m buffer if `ds` has a\n        projected CRS (i.e. metre units), or a 0.12 degree buffer if\n        `ds` has a geographic CRS (e.g. degree units).\n    resample_method : string, optional\n        If resampling is requested (see `resample` above), use this\n        resampling method when converting from low resolution to high\n        resolution pixels. Defaults to \"bilinear\"; valid options include\n        \"nearest\", \"cubic\", \"min\", \"max\", \"average\" etc.\n    model : string or list of strings\n        The tide model or a list of models used to model tides, as\n        supported by the `pyTMD` Python package. Options include:\n        - \"FES2014\" (default; pre-configured on DEA Sandbox)\n        - \"FES2022\"\n        - \"TPXO8-atlas\"\n        - \"TPXO9-atlas-v5\"\n        - \"EOT20\"\n        - \"HAMTIDE11\"\n        - \"GOT4.10\"\n    dask_chunks : str or tuple, optional\n        Can be used to configure custom Dask chunking for the final\n        resampling step. The default of \"auto\" will automatically set\n        x/y chunks to match those in `ds` if they exist, otherwise will\n        set x/y chunks that cover the entire extent of the dataset.\n        For custom chunks, provide a tuple in the form `(y, x)`, e.g.\n        `(2048, 2048)`.\n    dask_compute : bool, optional\n        Whether to compute results of the resampling step using Dask.\n        If False, this will return `tides_highres` as a Dask array.\n    **model_tides_kwargs :\n        Optional parameters passed to the `dea_tools.coastal.model_tides`\n        function. Important parameters include \"directory\" (used to\n        specify the location of input tide modelling files) and \"cutoff\"\n        (used to extrapolate modelled tides away from the coast; if not\n        specified here, cutoff defaults to `np.inf`).\n\n    Returns\n    -------\n    If `resample` is False:\n\n        tides_lowres : xr.DataArray\n            A low resolution data array giving either tide heights every\n            timestep in `ds` (if `times` is None), tide heights at every\n            time in `times` (if `times` is not None), or tide height quantiles\n            for every quantile provided by `calculate_quantiles`.\n\n    If `resample` is True:\n\n        tides_highres, tides_lowres : tuple of xr.DataArrays\n            In addition to `tides_lowres` (see above), a high resolution\n            array of tide heights will be generated that matches the\n            exact spatial resolution and extent of `ds`. This will contain\n            either tide heights every timestep in `ds` (if `times` is None),\n            tide heights at every time in `times` (if `times` is not None),\n            or tide height quantiles for every quantile provided by\n            `calculate_quantiles`.\n\n    \"\"\"\n    from odc.geo.geobox import GeoBox\n\n    # First test if no time dimension and nothing passed to `times`\n    if (\"time\" not in ds.dims) & (times is None):\n        raise ValueError(\n            \"`ds` does not contain a 'time' dimension. Times are required \"\n            \"for modelling tides: please pass in a set of custom tides \"\n            \"using the `times` parameter. For example: \"\n            \"`times=pd.date_range(start='2000', end='2001', freq='5h')`\",\n        )\n\n    # If custom times are provided, convert them to a consistent\n    # pandas.DatatimeIndex format\n    if times is not None:\n        if isinstance(times, list):\n            time_coords = pd.DatetimeIndex(times)\n        elif isinstance(times, pd.Timestamp):\n            time_coords = pd.DatetimeIndex([times])\n        else:\n            time_coords = times\n\n    # Otherwise, use times from `ds` directly\n    else:\n        time_coords = ds.coords[\"time\"]\n\n    # Set defaults passed to `model_tides`\n    model_tides_kwargs.setdefault(\"cutoff\", np.inf)\n\n    # Standardise model into a list for easy handling\n    model = [model] if isinstance(model, str) else model\n\n    # Test if no time dimension and nothing passed to `times`\n    if (\"time\" not in ds.dims) & (times is None):\n        raise ValueError(\n            \"`ds` does not contain a 'time' dimension. Times are required \"\n            \"for modelling tides: please pass in a set of custom tides \"\n            \"using the `times` parameter. For example: \"\n            \"`times=pd.date_range(start='2000', end='2001', freq='5h')`\",\n        )\n\n    # If custom times are provided, convert them to a consistent\n    # pandas.DatatimeIndex format\n    if times is not None:\n        if isinstance(times, list):\n            time_coords = pd.DatetimeIndex(times)\n        elif isinstance(times, pd.Timestamp):\n            time_coords = pd.DatetimeIndex([times])\n        else:\n            time_coords = times\n\n    # Otherwise, use times from `ds` directly\n    else:\n        time_coords = ds.coords[\"time\"]\n\n    # Determine spatial dimensions\n    y_dim, x_dim = ds.odc.spatial_dims\n\n    # Determine resolution and buffer, using different defaults for\n    # geographic (i.e. degrees) and projected (i.e. metres) CRSs:\n    crs_units = ds.odc.geobox.crs.units[0][0:6]\n    if ds.odc.geobox.crs.geographic:\n        if resolution is None:\n            resolution = 0.05\n        elif resolution > 360:\n            raise ValueError(\n                f\"A resolution of greater than 360 was \"\n                f\"provided, but `ds` has a geographic CRS \"\n                f\"in {crs_units} units. Did you accidently \"\n                f\"provide a resolution in projected \"\n                f\"(i.e. metre) units?\",\n            )\n        if buffer is None:\n            buffer = 0.12\n    else:\n        if resolution is None:\n            resolution = 5000\n        elif resolution < 1:\n            raise ValueError(\n                f\"A resolution of less than 1 was provided, \"\n                f\"but `ds` has a projected CRS in \"\n                f\"{crs_units} units. Did you accidently \"\n                f\"provide a resolution in geographic \"\n                f\"(degree) units?\",\n            )\n        if buffer is None:\n            buffer = 12000\n\n    # Raise error if resolution is less than dataset resolution\n    dataset_res = ds.odc.geobox.resolution.x\n    if resolution < dataset_res:\n        raise ValueError(\n            f\"The resolution of the low-resolution tide \"\n            f\"modelling grid ({resolution:.2f}) is less \"\n            f\"than `ds`'s pixel resolution ({dataset_res:.2f}). \"\n            f\"This can cause extremely slow tide modelling \"\n            f\"performance. Please select provide a resolution \"\n            f\"greater than {dataset_res:.2f} using \"\n            f\"`pixel_tides`'s 'resolution' parameter.\",\n        )\n\n    # Create a new reduced resolution tide modelling grid after\n    # first buffering the grid\n    print(f\"Creating reduced resolution {resolution} x {resolution} {crs_units} tide modelling array\")\n    buffered_geobox = ds.odc.geobox.buffered(buffer)\n    rescaled_geobox = GeoBox.from_bbox(bbox=buffered_geobox.boundingbox, resolution=resolution)\n    rescaled_ds = odc.geo.xr.xr_zeros(rescaled_geobox)\n\n    # Flatten grid to 1D, then add time dimension\n    flattened_ds = rescaled_ds.stack(z=(x_dim, y_dim))\n    flattened_ds = flattened_ds.expand_dims(dim={\"time\": time_coords.values})\n\n    # Model tides in parallel, returning a pandas.DataFrame\n    tide_df = model_tides(\n        x=flattened_ds[x_dim],\n        y=flattened_ds[y_dim],\n        time=flattened_ds.time,\n        crs=f\"EPSG:{ds.odc.geobox.crs.epsg}\",\n        model=model,\n        **model_tides_kwargs,\n    )\n\n    # Convert our pandas.DataFrame tide modelling outputs to xarray\n    tides_lowres = (\n        # Rename x and y dataframe indexes to match x and y xarray dims\n        tide_df.rename_axis([\"time\", x_dim, y_dim])\n        # Add tide model column to dataframe indexes so we can convert\n        # our dataframe to a multidimensional xarray\n        .set_index(\"tide_model\", append=True)\n        # Convert to xarray and select our tide modelling xr.DataArray\n        .to_xarray()\n        .tide_m\n        # Re-index and transpose into our input coordinates and dim order\n        .reindex_like(rescaled_ds)\n        .transpose(\"tide_model\", \"time\", y_dim, x_dim)\n    )\n\n    # Optionally calculate and return quantiles rather than raw data.\n    # Set dtype to dtype of the input data as quantile always returns\n    # float64 (memory intensive)\n    if calculate_quantiles is not None:\n        print(\"Computing tide quantiles\")\n        tides_lowres = tides_lowres.quantile(q=calculate_quantiles, dim=\"time\").astype(tides_lowres.dtype)\n\n    # If only one tidal model exists, squeeze out \"tide_model\" dim\n    if len(tides_lowres.tide_model) == 1:\n        tides_lowres = tides_lowres.squeeze(\"tide_model\")\n\n    # Ensure CRS is present before we apply any resampling\n    tides_lowres = tides_lowres.odc.assign_crs(ds.odc.geobox.crs)\n\n    # Reproject into original high resolution grid\n    if resample:\n        print(\"Reprojecting tides into original array\")\n        tides_highres, tides_lowres = _pixel_tides_resample(\n            tides_lowres,\n            ds,\n            resample_method,\n            dask_chunks,\n            dask_compute,\n        )\n        return tides_highres, tides_lowres\n\n    print(\"Returning low resolution tide array\")\n    return tides_lowres\n
"},{"location":"api/#eo_tides.stats","title":"eo_tides.stats","text":""},{"location":"api/#eo_tides.stats.tide_stats","title":"tide_stats","text":"
tide_stats(a)\n

Test function.

Parameters:

Name Type Description Default a int

Test

required

Returns:

Type Description Test Source code in eo_tides/stats.py 
def tide_stats(a):\n    \"\"\"\n    Test function.\n\n    Parameters\n    ----------\n    a : int\n        Test\n\n    Returns\n    -------\n    Test\n\n    \"\"\"\n    return a\n
"},{"location":"api/#eo_tides.validation","title":"eo_tides.validation","text":""},{"location":"api/#eo_tides.validation.eval_metrics","title":"eval_metrics","text":"
eval_metrics(x, y, round=3, all_regress=False)\n

Calculate a set of common statistical metrics based on two input actual and predicted vectors.

These include:

  • Pearson correlation
  • Root Mean Squared Error
  • Mean Absolute Error
  • R-squared
  • Bias
  • Linear regression parameters (slope, p-value, intercept, standard error)

Parameters:

Name Type Description Default x array

An array providing \"actual\" variable values.

required y array

An array providing \"predicted\" variable values.

required round int

Number of decimal places to round each metric to. Defaults to 3.

3 all_regress bool

Whether to return linear regression p-value, intercept and standard error (in addition to only regression slope). Defaults to False.

False

Returns:

Type Description Series

A pd.Series containing all calculated metrics.

Source code in eo_tides/validation.py 
def eval_metrics(x, y, round=3, all_regress=False):\n    \"\"\"\n    Calculate a set of common statistical metrics\n    based on two input actual and predicted vectors.\n\n    These include:\n\n    * Pearson correlation\n    * Root Mean Squared Error\n    * Mean Absolute Error\n    * R-squared\n    * Bias\n    * Linear regression parameters (slope, p-value, intercept, standard error)\n\n    Parameters\n    ----------\n    x : numpy.array\n        An array providing \"actual\" variable values.\n    y : numpy.array\n        An array providing \"predicted\" variable values.\n    round : int\n        Number of decimal places to round each metric\n        to. Defaults to 3.\n    all_regress : bool\n        Whether to return linear regression p-value,\n        intercept and standard error (in addition to\n        only regression slope). Defaults to False.\n\n    Returns\n    -------\n    pandas.Series\n        A `pd.Series` containing all calculated metrics.\n    \"\"\"\n\n    # Create dataframe to drop na\n    xy_df = pd.DataFrame({\"x\": x, \"y\": y}).dropna()\n\n    # Compute linear regression\n    lin_reg = stats.linregress(x=xy_df.x, y=xy_df.y)\n\n    # Calculate statistics\n    stats_dict = {\n        \"Correlation\": xy_df.corr().iloc[0, 1],\n        \"RMSE\": sqrt(mean_squared_error(xy_df.x, xy_df.y)),\n        \"MAE\": mean_absolute_error(xy_df.x, xy_df.y),\n        \"R-squared\": lin_reg.rvalue**2,\n        \"Bias\": (xy_df.y - xy_df.x).mean(),\n        \"Regression slope\": lin_reg.slope,\n    }\n\n    # Additional regression params\n    if all_regress:\n        stats_dict.update({\n            \"Regression p-value\": lin_reg.pvalue,\n            \"Regression intercept\": lin_reg.intercept,\n            \"Regression standard error\": lin_reg.stderr,\n        })\n\n    # Return as\n    return pd.Series(stats_dict).round(round)\n
"},{"location":"api/#eo_tides.validation.load_gauge_gesla","title":"load_gauge_gesla","text":"
load_gauge_gesla(\n    x=None,\n    y=None,\n    site_code=None,\n    time=(\"2018\", \"2020\"),\n    max_distance=None,\n    correct_mean=False,\n    filter_use_flag=True,\n    site_metadata=True,\n    data_path=\"/gdata1/data/sea_level/gesla/\",\n    metadata_path=\"/gdata1/data/sea_level/GESLA3_ALL 2.csv\",\n)\n

Load and process all available Global Extreme Sea Level Analysis (GESLA) tide gauge data with an x, y, time spatiotemporal query, or from a list of specific tide gauges.

Can optionally filter by gauge quality and append detailed gauge metadata.

Modified from original code in https://github.com/philiprt/GeslaDataset.

Parameters:

Name Type Description Default x numeric or list / tuple

Coordinates (in degrees longitude, latitude) used to load GESLA tide gauge observations. If provided as singular values (e.g. x=150, y=-32), then the nearest tide gauge will be returned. If provided as a list or tuple (e.g. x=(150, 152), y=(-32, -30)), then all gauges within the provided bounding box will be loaded. Leave as None to return all available gauges, or if providing a list of site codes using site_code.

None y numeric or list / tuple

Coordinates (in degrees longitude, latitude) used to load GESLA tide gauge observations. If provided as singular values (e.g. x=150, y=-32), then the nearest tide gauge will be returned. If provided as a list or tuple (e.g. x=(150, 152), y=(-32, -30)), then all gauges within the provided bounding box will be loaded. Leave as None to return all available gauges, or if providing a list of site codes using site_code.

None site_code str or list of str

GESLA site code(s) for which to load data (e.g. site_code=\"62650\"). If site_code is provided, x and y will be ignored.

None time tuple or list of str

Time range to consider, given as a tuple of start and end dates, e.g. time=(\"2020\", \"2021\"). The default of None will return all tide observations from the year 1800 onward.

('2018', '2020') max_distance numeric

Optional max distance within which to return the nearest tide gauge when x and y are provided as singular coordinates. Defaults to None, which will always return a tide gauge no matter how far away it is located from x and y.

None correct_mean bool

Whether to correct sea level measurements to a standardised mean sea level by subtracting the mean of all observed sea level observations. This can be useful when GESLA tide heights come from different or unknown tide datums. Note: the observed mean sea level calculated here may differ from true long-term/ astronomical Mean Sea Level (MSL) datum.

False filter_use_flag bool

Whether to filter out low quality observations with a \"use_flag\" value of 0 (do not use). Defaults to True.

True site_metadata bool

Whether to add tide gauge station metadata as additional columns in the output DataFrame. Defaults to True.

True data_path str

Path to the raw GESLA data files. Default is /gdata1/data/sea_level/gesla/.

'/gdata1/data/sea_level/gesla/' metadata_path str

Path to the GESLA station metadata file. Default is /gdata1/data/sea_level/GESLA3_ALL 2.csv.

'/gdata1/data/sea_level/GESLA3_ALL 2.csv'

Returns:

Type Description DataFrame

Processed GESLA data as a DataFrame with columns including:

  • \"time\": Timestamps,
  • \"sea_level\": Observed sea level (m),
  • \"qc_flag\": Observed sea level QC flag,
  • \"use_flag\": Use-in-analysis flag (1 = use, 0 = do not use),

...and additional columns from station metadata.

Source code in eo_tides/validation.py 
def load_gauge_gesla(\n    x=None,\n    y=None,\n    site_code=None,\n    time=(\"2018\", \"2020\"),\n    max_distance=None,\n    correct_mean=False,\n    filter_use_flag=True,\n    site_metadata=True,\n    data_path=\"/gdata1/data/sea_level/gesla/\",\n    metadata_path=\"/gdata1/data/sea_level/GESLA3_ALL 2.csv\",\n):\n    \"\"\"\n    Load and process all available Global Extreme Sea Level Analysis\n    (GESLA) tide gauge data with an `x, y, time` spatiotemporal query,\n    or from a list of specific tide gauges.\n\n    Can optionally filter by gauge quality and append detailed gauge metadata.\n\n    Modified from original code in <https://github.com/philiprt/GeslaDataset>.\n\n    Parameters\n    ----------\n    x, y : numeric or list/tuple, optional\n        Coordinates (in degrees longitude, latitude) used to load GESLA\n        tide gauge observations. If provided as singular values\n        (e.g. `x=150, y=-32`), then the nearest tide gauge will be returned.\n        If provided as a list or tuple (e.g. `x=(150, 152), y=(-32, -30)`),\n        then all gauges within the provided bounding box will be loaded.\n        Leave as `None` to return all available gauges, or if providing a\n        list of site codes using `site_code`.\n    site_code : str or list of str, optional\n        GESLA site code(s) for which to load data (e.g. `site_code=\"62650\"`).\n        If `site_code` is provided, `x` and `y` will be ignored.\n    time : tuple or list of str, optional\n        Time range to consider, given as a tuple of start and end dates,\n        e.g. `time=(\"2020\", \"2021\")`. The default of None will return all\n        tide observations from the year 1800 onward.\n    max_distance : numeric, optional\n        Optional max distance within which to return the nearest tide gauge\n        when `x` and `y` are provided as singular coordinates. Defaults to\n        None, which will always return a tide gauge no matter how far away\n        it is located from `x` and `y`.\n    correct_mean : bool, optional\n        Whether to correct sea level measurements to a standardised mean\n        sea level by subtracting the mean of all observed sea level\n        observations. This can be useful when GESLA tide heights come\n        from different or unknown tide datums. Note: the observed mean\n        sea level calculated here may differ from true long-term/\n        astronomical Mean Sea Level (MSL) datum.\n    filter_use_flag : bool, optional\n        Whether to filter out low quality observations with a \"use_flag\"\n        value of 0 (do not use). Defaults to True.\n    site_metadata : bool, optional\n        Whether to add tide gauge station metadata as additional columns\n        in the output DataFrame. Defaults to True.\n    data_path : str, optional\n        Path to the raw GESLA data files. Default is\n        `/gdata1/data/sea_level/gesla/`.\n    metadata_path : str, optional\n        Path to the GESLA station metadata file.\n        Default is `/gdata1/data/sea_level/GESLA3_ALL 2.csv`.\n\n    Returns\n    -------\n    pd.DataFrame\n        Processed GESLA data as a DataFrame with columns including:\n\n        - \"time\": Timestamps,\n        - \"sea_level\": Observed sea level (m),\n        - \"qc_flag\": Observed sea level QC flag,\n        - \"use_flag\": Use-in-analysis flag (1 = use, 0 = do not use),\n\n        ...and additional columns from station metadata.\n    \"\"\"\n    # Load tide gauge metadata\n    metadata_df, metadata_gdf = _load_gauge_metadata(metadata_path)\n\n    # Use supplied site codes if available\n    if site_code is not None:\n        site_code = [site_code] if not isinstance(site_code, list) else site_code\n\n    # If x and y are tuples, use xy bounds to identify sites\n    elif isinstance(x, (tuple, list)) & isinstance(y, (tuple, list)):\n        bbox = BoundingBox.from_xy(x, y)\n        site_code = metadata_gdf.cx[bbox.left : bbox.right, bbox.top : bbox.bottom].index\n\n    # If x and y are single numbers, select nearest row\n    elif isinstance(x, Number) & isinstance(y, Number):\n        site_code = _nearest_row(metadata_gdf, x, y, max_distance).site_code\n\n        # Raise exception if no valid tide gauges are found\n        if site_code.isnull().all():\n            raise Exception(f\"No tide gauge found within {max_distance} degrees of {x}, {y}.\")\n\n    # Otherwise if all are None, return all available site codes\n    elif (site_code is None) & (x is None) & (y is None):\n        site_code = metadata_df.index.to_list()\n\n    else:\n        raise TypeError(\n            \"`x` and `y` must be provided as either singular coordinates (e.g. `x=150`), or as a tuple bounding box (e.g. `x=(150, 152)`).\"\n        )\n\n    # Prepare times\n    if time is None:\n        time = [\"1800\", str(datetime.datetime.now().year)]\n    time = [time] if not isinstance(time, (list, tuple)) else time\n    start_time = round_date_strings(time[0], round_type=\"start\")\n    end_time = round_date_strings(time[-1], round_type=\"end\")\n\n    # Identify paths to load and nodata values for each site\n    metadata_df[\"file_name\"] = data_path + metadata_df[\"file_name\"]\n    paths_na = metadata_df.loc[site_code, [\"file_name\", \"null_value\"]]\n\n    # Load and combine into a single dataframe\n    data_df = (\n        pd.concat([_load_gesla_dataset(s, p, na_value=na) for s, p, na in paths_na.itertuples()])\n        .sort_index()\n        .loc[slice(start_time, end_time)]\n        .reset_index()\n        .set_index(\"site_code\")\n    )\n\n    # Optionally filter by use flag column\n    if filter_use_flag:\n        data_df = data_df.loc[data_df.use_flag == 1]\n\n    # Optionally insert metadata into dataframe\n    if site_metadata:\n        data_df[metadata_df.columns] = metadata_df.loc[site_code]\n\n    # Add time to index and remove duplicates\n    data_df = data_df.set_index(\"time\", append=True)\n    duplicates = data_df.index.duplicated()\n    if duplicates.sum() > 0:\n        warnings.warn(\"Duplicate timestamps were removed.\")\n        data_df = data_df.loc[~duplicates]\n\n    # Remove observed mean sea level if requested\n    if correct_mean:\n        data_df[\"sea_level\"] = data_df[\"sea_level\"].sub(data_df.groupby(\"site_code\")[\"sea_level\"].transform(\"mean\"))\n\n    # Return data\n    return data_df\n
"},{"location":"api/#eo_tides.validation.round_date_strings","title":"round_date_strings","text":"
round_date_strings(date, round_type='end')\n

Round a date string up or down to the start or end of a given time period.

Parameters:

Name Type Description Default date str

Date string of variable precision (e.g. \"2020\", \"2020-01\", \"2020-01-01\").

required round_type str

Type of rounding to perform. Valid options are \"start\" or \"end\". If \"start\", date is rounded down to the start of the time period. If \"end\", date is rounded up to the end of the time period. Default is \"end\".

'end'

Returns:

Name Type Description date_rounded str

The rounded date string.

Examples:

>>> round_date_strings('2020')\n'2020-12-31 00:00:00'\n
>>> round_date_strings('2020-01', round_type='start')\n'2020-01-01 00:00:00'\n
>>> round_date_strings('2020-01', round_type='end')\n'2020-01-31 00:00:00'\n
Source code in eo_tides/validation.py 
def round_date_strings(date, round_type=\"end\"):\n    \"\"\"\n    Round a date string up or down to the start or end of a given time\n    period.\n\n    Parameters\n    ----------\n    date : str\n        Date string of variable precision (e.g. \"2020\", \"2020-01\",\n        \"2020-01-01\").\n    round_type : str, optional\n        Type of rounding to perform. Valid options are \"start\" or \"end\".\n        If \"start\", date is rounded down to the start of the time period.\n        If \"end\", date is rounded up to the end of the time period.\n        Default is \"end\".\n\n    Returns\n    -------\n    date_rounded : str\n        The rounded date string.\n\n    Examples\n    --------\n    >>> round_date_strings('2020')\n    '2020-12-31 00:00:00'\n\n    >>> round_date_strings('2020-01', round_type='start')\n    '2020-01-01 00:00:00'\n\n    >>> round_date_strings('2020-01', round_type='end')\n    '2020-01-31 00:00:00'\n    \"\"\"\n\n    # Determine precision of input date string\n    date_segments = len(date.split(\"-\"))\n\n    # If provided date has no \"-\", treat it as having year precision\n    if date_segments == 1 and round_type == \"start\":\n        date_rounded = str(pd.to_datetime(date) + YearBegin(0))\n    elif date_segments == 1 and round_type == \"end\":\n        date_rounded = str(pd.to_datetime(date) + YearEnd(0))\n\n    # If provided date has one \"-\", treat it as having month precision\n    elif date_segments == 2 and round_type == \"start\":\n        date_rounded = str(pd.to_datetime(date) + MonthBegin(0))\n    elif date_segments == 2 and round_type == \"end\":\n        date_rounded = str(pd.to_datetime(date) + MonthEnd(0))\n\n    # If more than one \"-\", then return date as-is\n    elif date_segments > 2:\n        date_rounded = date\n\n    return date_rounded\n
"},{"location":"api/#eo_tides.utils","title":"eo_tides.utils","text":""},{"location":"api/#eo_tides.utils.idw","title":"idw","text":"
idw(\n    input_z,\n    input_x,\n    input_y,\n    output_x,\n    output_y,\n    p=1,\n    k=10,\n    max_dist=None,\n    k_min=1,\n    epsilon=1e-12,\n)\n

Perform Inverse Distance Weighting (IDW) interpolation.

This function performs fast IDW interpolation by creating a KDTree from the input coordinates then uses it to find the k nearest neighbors for each output point. Weights are calculated based on the inverse distance to each neighbor, with weights descreasing with increasing distance.

Code inspired by: https://github.com/DahnJ/REM-xarray

Parameters:

Name Type Description Default input_z array - like

Array of values at the input points. This can be either a 1-dimensional array, or a 2-dimensional array where each column (axis=1) represents a different set of values to be interpolated.

required input_x array - like

Array of x-coordinates of the input points.

required input_y array - like

Array of y-coordinates of the input points.

required output_x array - like

Array of x-coordinates where the interpolation is to be computed.

required output_y array - like

Array of y-coordinates where the interpolation is to be computed.

required p int or float

Power function parameter defining how rapidly weightings should decrease as distance increases. Higher values of p will cause weights for distant points to decrease rapidly, resulting in nearby points having more influence on predictions. Defaults to 1.

1 k int

Number of nearest neighbors to use for interpolation. k=1 is equivalent to \"nearest\" neighbour interpolation. Defaults to 10.

10 max_dist int or float

Restrict neighbouring points to less than this distance. By default, no distance limit is applied.

None k_min int

If max_dist is provided, some points may end up with less than k nearest neighbours, potentially producing less reliable interpolations. Set k_min to set any points with less than k_min neighbours to NaN. Defaults to 1.

1 epsilon float

Small value added to distances to prevent division by zero errors in the case that output coordinates are identical to input coordinates. Defaults to 1e-12.

1e-12

Returns:

Name Type Description interp_values ndarray

Interpolated values at the output coordinates. If input_z is 1-dimensional, interp_values will also be 1-dimensional. If input_z is 2-dimensional, interp_values will have the same number of rows as input_z, with each column (axis=1) representing interpolated values for one set of input data.

Examples:

>>> input_z = [1, 2, 3, 4, 5]\n>>> input_x = [0, 1, 2, 3, 4]\n>>> input_y = [0, 1, 2, 3, 4]\n>>> output_x = [0.5, 1.5, 2.5]\n>>> output_y = [0.5, 1.5, 2.5]\n>>> idw(input_z, input_x, input_y, output_x, output_y, k=2)\narray([1.5, 2.5, 3.5])\n
Source code in eo_tides/utils.py 
def idw(\n    input_z,\n    input_x,\n    input_y,\n    output_x,\n    output_y,\n    p=1,\n    k=10,\n    max_dist=None,\n    k_min=1,\n    epsilon=1e-12,\n):\n    \"\"\"Perform Inverse Distance Weighting (IDW) interpolation.\n\n    This function performs fast IDW interpolation by creating a KDTree\n    from the input coordinates then uses it to find the `k` nearest\n    neighbors for each output point. Weights are calculated based on the\n    inverse distance to each neighbor, with weights descreasing with\n    increasing distance.\n\n    Code inspired by: https://github.com/DahnJ/REM-xarray\n\n    Parameters\n    ----------\n    input_z : array-like\n        Array of values at the input points. This can be either a\n        1-dimensional array, or a 2-dimensional array where each column\n        (axis=1) represents a different set of values to be interpolated.\n    input_x : array-like\n        Array of x-coordinates of the input points.\n    input_y : array-like\n        Array of y-coordinates of the input points.\n    output_x : array-like\n        Array of x-coordinates where the interpolation is to be computed.\n    output_y : array-like\n        Array of y-coordinates where the interpolation is to be computed.\n    p : int or float, optional\n        Power function parameter defining how rapidly weightings should\n        decrease as distance increases. Higher values of `p` will cause\n        weights for distant points to decrease rapidly, resulting in\n        nearby points having more influence on predictions. Defaults to 1.\n    k : int, optional\n        Number of nearest neighbors to use for interpolation. `k=1` is\n        equivalent to \"nearest\" neighbour interpolation. Defaults to 10.\n    max_dist : int or float, optional\n        Restrict neighbouring points to less than this distance.\n        By default, no distance limit is applied.\n    k_min : int, optional\n        If `max_dist` is provided, some points may end up with less than\n        `k` nearest neighbours, potentially producing less reliable\n        interpolations. Set `k_min` to set any points with less than\n        `k_min` neighbours to NaN. Defaults to 1.\n    epsilon : float, optional\n        Small value added to distances to prevent division by zero\n        errors in the case that output coordinates are identical to\n        input coordinates. Defaults to 1e-12.\n\n    Returns\n    -------\n    interp_values : numpy.ndarray\n        Interpolated values at the output coordinates. If `input_z` is\n        1-dimensional, `interp_values` will also be 1-dimensional. If\n        `input_z` is 2-dimensional, `interp_values` will have the same\n        number of rows as `input_z`, with each column (axis=1)\n        representing interpolated values for one set of input data.\n\n    Examples\n    --------\n    >>> input_z = [1, 2, 3, 4, 5]\n    >>> input_x = [0, 1, 2, 3, 4]\n    >>> input_y = [0, 1, 2, 3, 4]\n    >>> output_x = [0.5, 1.5, 2.5]\n    >>> output_y = [0.5, 1.5, 2.5]\n    >>> idw(input_z, input_x, input_y, output_x, output_y, k=2)\n    array([1.5, 2.5, 3.5])\n\n    \"\"\"\n    # Convert to numpy arrays\n    input_x = np.atleast_1d(input_x)\n    input_y = np.atleast_1d(input_y)\n    input_z = np.atleast_1d(input_z)\n    output_x = np.atleast_1d(output_x)\n    output_y = np.atleast_1d(output_y)\n\n    # Verify input and outputs have matching lengths\n    if not (input_z.shape[0] == len(input_x) == len(input_y)):\n        raise ValueError(\"All of `input_z`, `input_x` and `input_y` must be the same length.\")\n    if not (len(output_x) == len(output_y)):\n        raise ValueError(\"Both `output_x` and `output_y` must be the same length.\")\n\n    # Verify k is smaller than total number of points, and non-zero\n    if k > input_z.shape[0]:\n        raise ValueError(\n            f\"The requested number of nearest neighbours (`k={k}`) \"\n            f\"is smaller than the total number of points ({input_z.shape[0]}).\",\n        )\n    if k == 0:\n        raise ValueError(\"Interpolation based on `k=0` nearest neighbours is not valid.\")\n\n    # Create KDTree to efficiently find nearest neighbours\n    points_xy = np.column_stack((input_y, input_x))\n    tree = KDTree(points_xy)\n\n    # Determine nearest neighbours and distances to each\n    grid_stacked = np.column_stack((output_y, output_x))\n    distances, indices = tree.query(grid_stacked, k=k, workers=-1)\n\n    # If k == 1, add an additional axis for consistency\n    if k == 1:\n        distances = distances[..., np.newaxis]\n        indices = indices[..., np.newaxis]\n\n    # Add small epsilon to distances to prevent division by zero errors\n    # if output coordinates are the same as input coordinates\n    distances = np.maximum(distances, epsilon)\n\n    # Set distances above max to NaN if specified\n    if max_dist is not None:\n        distances[distances > max_dist] = np.nan\n\n    # Calculate weights based on distance to k nearest neighbours.\n    weights = 1 / np.power(distances, p)\n    weights = weights / np.nansum(weights, axis=1).reshape(-1, 1)\n\n    # 1D case: Compute weighted sum of input_z values for each output point\n    if input_z.ndim == 1:\n        interp_values = np.nansum(weights * input_z[indices], axis=1)\n\n    # 2D case: Compute weighted sum for each set of input_z values\n    # weights[..., np.newaxis] adds a dimension for broadcasting\n    else:\n        interp_values = np.nansum(\n            weights[..., np.newaxis] * input_z[indices],\n            axis=1,\n        )\n\n    # Set any points with less than `k_min` valid weights to NaN\n    interp_values[np.isfinite(weights).sum(axis=1) < k_min] = np.nan\n\n    return interp_values\n
"},{"location":"credits/","title":"Citations and credits","text":""},{"location":"credits/#citing-eo-tides","title":"Citing eo-tides","text":"

To cite eo-tides in your work, please use the following citation:

Bishop-Taylor, R., Sagar, S., Phillips, C., & Newey, V. (2024). eo-tides: Tide modelling tools for large-scale satellite earth observation analysis [Computer software]. https://github.com/GeoscienceAustralia/eo-tides\n
"},{"location":"credits/#references","title":"References","text":"

Placeholder

"},{"location":"credits/#credits","title":"Credits","text":"

Placeholder

"},{"location":"install/","title":"Installing eo-tides","text":"

eo-tides can be installed into your Python environment from PyPI using pip:

pip install eo-tides\n

By default, only essential package dependencies are installed. To install all packages required for running the included Jupyter Notebook examples (including odc-stac and pystac-client for loading freely available satellite data):

pip install eo-tides[notebooks]\n

Once you have installed eo-tides, you will need to download and set up at least one tide model before you can model tides.

"},{"location":"setup/","title":"Setting up tide models","text":""},{"location":"setup/#fes2014-finite-element-solution-tide-model","title":"FES2014 Finite Element Solution tide model","text":"
  1. Register with AVISO+, and select FES2014 / FES2012 (Oceanic Tides Heights) from the PRODUCT SELECTION section:
  1. Once your registration is complete, login to MY AVISO+.
  2. Once logged in, select My products in the left-hand menu:
  1. FES2014 / FES2012 (Oceanic Tides Heights) should appear under Your current subscriptions. Right click on Ftp, and copy the FTP address.
  1. Using an FTP client like FileZilla, log in to the FTP using your AVISO+ username and password:

  1. Navigate to /auxiliary/tide_model/fes2014_elevations_and_load/, and download one of the following files:

  2. fes2014b_elevations/ocean_tide.tar.xz, or

  3. fes2014b_elevations_extrapolated/ocean_tide_extrapolated.tar.xz (this extrapolated version includes additional coverage of the coastal zone, which can be useful for coastal applications)

  4. Create a new folder (i.e. tide_models/fes2014/) to store the model files in an accessible location. Extract ocean_tide.tar.xz into this folder (e.g. tar -xf ocean_tide.tar.xz). You should end up with the following directory structure containing the extracted NetCDF files:

tide_models/fes2014/ocean_tide/\n    |- 2n2.nc\n    |- ...\n    |- t2.nc\n
"},{"location":"setup/#modelling-tides","title":"Modelling tides","text":"

Tides can now be modelled using the model_tides function from the eo_tides.model module:

import pandas as pd\nfrom eo_tides.model import model_tides\n\nlons=[155, 160]\nlats=[-35, -36]\nexample_times = pd.date_range(\"2022-01-01\", \"2022-01-04\", freq=\"1D\")\n\nmodel_tides(\n        x=lons,\n        y=lats,\n        time=example_times,\n        directory='tide_models/'\n)\n

Depending on where you created the tide_models directory, you may need to update the directory parameter of the model_tides function to point to the location of the FES2014 model files.

"},{"location":"notebooks/Model_tides/","title":"Modelling tides","text":"In\u00a0[1]: Copied! 
from eo_tides.model import model_tides, pixel_tides\nfrom eo_tides.validation import eval_metrics, load_gauge_gesla\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\n%load_ext autoreload\n%autoreload 2\n
from eo_tides.model import model_tides, pixel_tides from eo_tides.validation import eval_metrics, load_gauge_gesla import pandas as pd import matplotlib.pyplot as plt %load_ext autoreload %autoreload 2 In\u00a0[2]: Copied! 
modelled_df = model_tides(\n    x=122.2186, \n    y=-18.0008, \n    time=pd.date_range(\"2018-01-01\", \"2018-01-20\", freq=\"1h\"), \n    directory=\"../../tests/data/tide_models_tests\"\n)\n\n# Plot\nmodelled_df.reset_index([\"x\", \"y\"]).tide_m.plot()\n
modelled_df = model_tides( x=122.2186, y=-18.0008, time=pd.date_range(\"2018-01-01\", \"2018-01-20\", freq=\"1h\"), directory=\"../../tests/data/tide_models_tests\" ) # Plot modelled_df.reset_index([\"x\", \"y\"]).tide_m.plot() 
Modelling tides using FES2014\n
Out[2]: 
<Axes: xlabel='time'>
In\u00a0[3]: Copied! 
# Load gauge data, subtracting to observed mean sea level\ngauge_df = load_gauge_gesla(\n    x=122.3186,\n    y=-18.0008,\n    time=(\"2018-01-01\", \"2018-01-20\"),\n    correct_mean=True,\n    data_path=\"../../tests/data/\",\n    metadata_path=\"../../tests/data/GESLA3_ALL 2.csv\"\n)\ngauge_df.head()\n
# Load gauge data, subtracting to observed mean sea level gauge_df = load_gauge_gesla( x=122.3186, y=-18.0008, time=(\"2018-01-01\", \"2018-01-20\"), correct_mean=True, data_path=\"../../tests/data/\", metadata_path=\"../../tests/data/GESLA3_ALL 2.csv\" ) gauge_df.head() 
/workspaces/eo-tides/.venv/lib/python3.10/site-packages/geopandas/array.py:403: UserWarning: Geometry is in a geographic CRS. Results from 'sjoin_nearest' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n\n  warnings.warn(\n/workspaces/eo-tides/eo_tides/validation.py:157: FutureWarning: Support for nested sequences for 'parse_dates' in pd.read_csv is deprecated. Combine the desired columns with pd.to_datetime after parsing instead.\n  pd.read_csv(\n
Out[3]: sea_level qc_flag use_flag file_name site_name country contributor_abbreviated contributor_full contributor_website contributor_contact ... start_date_time end_date_time number_of_years time_zone_hours datum_information instrument precision null_value gauge_type overall_record_quality site_code time 62650 2018-01-01 00:00:00 1.204227 1 1 ../../tests/data/broome-62650-aus-bom Broome AUS BOM Bureau of Meteorology http://www.bom.gov.au/oceanography/projects/nt... tides@bom.gov.au ... 2/07/1966 0:00 31/12/2019 23:00 51 0 Chart Datum / Lowest Astronomical Tide Unspecified Unspecified -99.9999 Coastal No obvious issues 2018-01-01 01:00:00 2.307227 1 1 ../../tests/data/broome-62650-aus-bom Broome AUS BOM Bureau of Meteorology http://www.bom.gov.au/oceanography/projects/nt... tides@bom.gov.au ... 2/07/1966 0:00 31/12/2019 23:00 51 0 Chart Datum / Lowest Astronomical Tide Unspecified Unspecified -99.9999 Coastal No obvious issues 2018-01-01 02:00:00 2.708227 1 1 ../../tests/data/broome-62650-aus-bom Broome AUS BOM Bureau of Meteorology http://www.bom.gov.au/oceanography/projects/nt... tides@bom.gov.au ... 2/07/1966 0:00 31/12/2019 23:00 51 0 Chart Datum / Lowest Astronomical Tide Unspecified Unspecified -99.9999 Coastal No obvious issues 2018-01-01 03:00:00 2.133227 1 1 ../../tests/data/broome-62650-aus-bom Broome AUS BOM Bureau of Meteorology http://www.bom.gov.au/oceanography/projects/nt... tides@bom.gov.au ... 2/07/1966 0:00 31/12/2019 23:00 51 0 Chart Datum / Lowest Astronomical Tide Unspecified Unspecified -99.9999 Coastal No obvious issues 2018-01-01 04:00:00 1.045227 1 1 ../../tests/data/broome-62650-aus-bom Broome AUS BOM Bureau of Meteorology http://www.bom.gov.au/oceanography/projects/nt... tides@bom.gov.au ... 2/07/1966 0:00 31/12/2019 23:00 51 0 Chart Datum / Lowest Astronomical Tide Unspecified Unspecified -99.9999 Coastal No obvious issues

5 rows \u00d7 26 columns

In\u00a0[4]: Copied! 
# Combine modelled and observed gauge data and compare\njoined_df = gauge_df.join(modelled_df)\njoined_df.plot.scatter(x=\"sea_level\", y=\"tide_m\")\neval_metrics(x=joined_df.sea_level, y=joined_df.tide_m)\n
# Combine modelled and observed gauge data and compare joined_df = gauge_df.join(modelled_df) joined_df.plot.scatter(x=\"sea_level\", y=\"tide_m\") eval_metrics(x=joined_df.sea_level, y=joined_df.tide_m) Out[4]: 
Correlation         0.998\nRMSE                0.144\nMAE                 0.113\nR-squared           0.995\nBias                0.004\nRegression slope    0.986\ndtype: float64
In\u00a0[5]: Copied! 
import odc.stac\nimport pystac_client\n\n# Connect to stac catalogue\ncatalog = pystac_client.Client.open(\"https://explorer.dea.ga.gov.au/stac\")\n\n# Set cloud defaults\nodc.stac.configure_rio(\n    cloud_defaults=True,\n    aws={\"aws_unsigned\": True},\n)\n\n# Build a query with the parameters above\nbbox = [122.2186 - 0.03, -18.0008 - 0.03, 122.2186 + 0.03, -18.0008 + 0.03]\nquery = catalog.search(\n    bbox=bbox,\n    collections=[\"ga_ls8c_ard_3\"],\n    datetime=\"2018-01-01/2018-01-31\",\n)\n\n# Search the STAC catalog for all items matching the query\nds = odc.stac.load(\n    list(query.items()),\n    bands=[\"nbart_red\", \"nbart_green\", \"nbart_blue\"],\n    crs=\"utm\",\n    resolution=30,\n    groupby=\"solar_day\",\n    bbox=bbox,\n    fail_on_error=False,\n    chunks={},\n)\n
import odc.stac import pystac_client # Connect to stac catalogue catalog = pystac_client.Client.open(\"https://explorer.dea.ga.gov.au/stac\") # Set cloud defaults odc.stac.configure_rio( cloud_defaults=True, aws={\"aws_unsigned\": True}, ) # Build a query with the parameters above bbox = [122.2186 - 0.03, -18.0008 - 0.03, 122.2186 + 0.03, -18.0008 + 0.03] query = catalog.search( bbox=bbox, collections=[\"ga_ls8c_ard_3\"], datetime=\"2018-01-01/2018-01-31\", ) # Search the STAC catalog for all items matching the query ds = odc.stac.load( list(query.items()), bands=[\"nbart_red\", \"nbart_green\", \"nbart_blue\"], crs=\"utm\", resolution=30, groupby=\"solar_day\", bbox=bbox, fail_on_error=False, chunks={}, ) In\u00a0[6]: Copied! 
ds.isel(time=0).odc.explore(vmin=0, vmax=2000)\n
ds.isel(time=0).odc.explore(vmin=0, vmax=2000) 
/workspaces/eo-tides/.venv/lib/python3.10/site-packages/rasterio/warp.py:344: NotGeoreferencedWarning: Dataset has no geotransform, gcps, or rpcs. The identity matrix will be returned.\n  _reproject(\n
Out[6]: Make this Notebook Trusted to load map: File -> Trust Notebook"},{"location":"notebooks/Model_tides/#modelling-tides","title":"Modelling tides\u00b6","text":""},{"location":"notebooks/Model_tides/#using-model_tides","title":"Using model_tides\u00b6","text":""},{"location":"notebooks/Model_tides/#validation-against-gesla-tide-gauges","title":"Validation against GESLA tide gauges\u00b6","text":""},{"location":"notebooks/Model_tides/#combining-satellite-data-with-tides-using-pixel_tides","title":"Combining satellite data with tides using pixel_tides\u00b6","text":""},{"location":"notebooks/Model_tides/#load-satellite-data-using-stac","title":"Load satellite data using STAC\u00b6","text":""}]} \ No newline at end of file diff --git a/setup/index.html b/setup/index.html new file mode 100644 index 0000000..ebdf645 --- /dev/null +++ b/setup/index.html @@ -0,0 +1,862 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Setting up tide models - eo-tides + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Setting up tide models

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FES2014 Finite Element Solution tide model

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  1. Register with AVISO+, and select FES2014 / FES2012 (Oceanic Tides Heights) from the PRODUCT SELECTION section:
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  1. Once your registration is complete, login to MY AVISO+.
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  2. Once logged in, select My products in the left-hand menu:
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  1. FES2014 / FES2012 (Oceanic Tides Heights) should appear under Your current subscriptions. Right click on Ftp, and copy the FTP address.
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  1. Using an FTP client like FileZilla, log in to the FTP using your AVISO+ username and password:
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    Navigate to /auxiliary/tide_model/fes2014_elevations_and_load/, and download one of the following files:

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    fes2014b_elevations/ocean_tide.tar.xz, or

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    fes2014b_elevations_extrapolated/ocean_tide_extrapolated.tar.xz (this extrapolated version includes additional coverage of the coastal zone, which can be useful for coastal applications)

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    Create a new folder (i.e. tide_models/fes2014/) to store the model files in an accessible location. Extract ocean_tide.tar.xz into this folder (e.g. tar -xf ocean_tide.tar.xz). You should end up with the following directory structure containing the extracted NetCDF files:

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tide_models/fes2014/ocean_tide/
+    |- 2n2.nc
+    |- ...
+    |- t2.nc
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Modelling tides

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Tides can now be modelled using the model_tides function from the eo_tides.model module:

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import pandas as pd
+from eo_tides.model import model_tides
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+lons=[155, 160]
+lats=[-35, -36]
+example_times = pd.date_range("2022-01-01", "2022-01-04", freq="1D")
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+model_tides(
+        x=lons,
+        y=lats,
+        time=example_times,
+        directory='tide_models/'
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Depending on where you created the tide_models directory, you may need to update the directory parameter of the model_tides function to point to the location of the FES2014 model files.

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+ + + + + + + + + + \ No newline at end of file diff --git a/sitemap.xml b/sitemap.xml new file mode 100644 index 0000000..5e7a5ab --- /dev/null +++ b/sitemap.xml @@ -0,0 +1,31 @@ + + + + https://GeoscienceAustralia.github.io/eo-tides/ + 2024-09-28 + + + https://GeoscienceAustralia.github.io/eo-tides/api/ + 2024-09-28 + + + https://GeoscienceAustralia.github.io/eo-tides/changelog/ + 2024-09-28 + + + https://GeoscienceAustralia.github.io/eo-tides/credits/ + 2024-09-28 + + + https://GeoscienceAustralia.github.io/eo-tides/install/ + 2024-09-28 + + + https://GeoscienceAustralia.github.io/eo-tides/setup/ + 2024-09-28 + + + https://GeoscienceAustralia.github.io/eo-tides/notebooks/Model_tides/ + 2024-09-28 + + \ No newline at end of file diff --git a/sitemap.xml.gz b/sitemap.xml.gz new file mode 100644 index 0000000..c72268b Binary files /dev/null and b/sitemap.xml.gz differ diff --git a/stylesheets/extra.css b/stylesheets/extra.css new file mode 100644 index 0000000..ac7a477 --- /dev/null +++ b/stylesheets/extra.css @@ -0,0 +1,25 @@ +[data-md-color-scheme="eotides"] { + --md-primary-fg-color: #215f9a; + --md-primary-fg-color--light: #4a7dbe; + --md-primary-fg-color--dark: #184878; + --md-primary-bg-color: #ffffff; + --md-primary-bg-color--light: #ffffff; + --md-default-fg-color--lighter: #ffffff; + --md-footer-bg-color: #113457; + --md-footer-bg-color--dark: #113457; +} + +/* Target the search input placeholder icon */ +.md-search__icon.md-icon svg { + color: #ffffff !important; +} + +/* Increase content width */ +.md-grid { + max-width: 1200px; +} + +/* Add wrapping to code blocks */ +code { + white-space: pre-wrap !important; +}