desis module

This Module has the functions related to working with a DESIS dataset.

desis_to_image(dataset, wavelengths=None, method='nearest', output=None, **kwargs)

Converts an DESIS dataset to an image.

Parameters:

Name	Type	Description	Default
dataset	xarray.Dataset or str	The dataset containing the DESIS data or the file path to the dataset.	required
wavelengths	array-like	The specific wavelengths to select. If None, all wavelengths are selected. Defaults to None.	None
method	str	The method to use for data interpolation. Defaults to "nearest".	'nearest'
output	str	The file path where the image will be saved. If None, the image will be returned as a PIL Image object. Defaults to None.	None
**kwargs		Additional keyword arguments to be passed to leafmap.array_to_image.	{}

Returns:

Type	Description
rasterio.Dataset or None	The image converted from the dataset. If output is provided, the image will be saved to the specified file and the function will return None.

Source code in hypercoast/desis.py

def desis_to_image(
    dataset: Union[xr.Dataset, str],
    wavelengths: Union[list, tuple] = None,
    method: Optional[str] = "nearest",
    output: Optional[str] = None,
    **kwargs,
):
    """
    Converts an DESIS dataset to an image.

    Args:
        dataset (xarray.Dataset or str): The dataset containing the DESIS data
            or the file path to the dataset.
        wavelengths (array-like, optional): The specific wavelengths to select.
            If None, all wavelengths are selected. Defaults to None.
        method (str, optional): The method to use for data interpolation.
            Defaults to "nearest".
        output (str, optional): The file path where the image will be saved. If
            None, the image will be returned as a PIL Image object. Defaults to None.
        **kwargs: Additional keyword arguments to be passed to
            `leafmap.array_to_image`.

    Returns:
        rasterio.Dataset or None: The image converted from the dataset. If
            `output` is provided, the image will be saved to the specified file
            and the function will return None.
    """
    from leafmap import array_to_image

    if isinstance(dataset, str):
        dataset = read_desis(dataset, method=method)

    if wavelengths is not None:
        dataset = dataset.sel(wavelength=wavelengths, method=method)

    return array_to_image(
        dataset["reflectance"], output=output, transpose=False, **kwargs
    )

extract_desis(ds, lat, lon)

Extracts DESIS data from a given xarray Dataset.

Parameters:

Name	Type	Description	Default
ds	xarray.Dataset	The dataset containing the DESIS data.	required
lat	float	The latitude of the point to extract.	required
lon	float	The longitude of the point to extract.	required

Returns:

Type	Description
xarray.DataArray	The extracted data.

Source code in hypercoast/desis.py

def extract_desis(ds: xr.Dataset, lat: float, lon: float) -> xr.DataArray:
    """
    Extracts DESIS data from a given xarray Dataset.

    Args:
        ds (xarray.Dataset): The dataset containing the DESIS data.
        lat (float): The latitude of the point to extract.
        lon (float): The longitude of the point to extract.

    Returns:
        xarray.DataArray: The extracted data.
    """

    crs = ds.attrs["crs"]

    x, y = convert_coords([[lat, lon]], "epsg:4326", crs)[0]

    values = ds.sel(x=x, y=y, method="nearest")["reflectance"].values / 10000

    da = xr.DataArray(
        values, dims=["wavelength"], coords={"wavelength": ds.coords["wavelength"]}
    )

    return da

filter_desis(dataset, lat, lon, return_plot=False, **kwargs)

Filters a DESIS dataset based on latitude and longitude.

Parameters:

Name	Type	Description	Default
dataset	xr.Dataset	The DESIS dataset to filter.	required
lat	float or tuple	The latitude to filter by. If a tuple or list, it represents a range.	required
lon	float or tuple	The longitude to filter by. If a tuple or list, it represents a range.	required

Returns:

Type	Description
xr.DataArray	The filtered DESIS data.

Source code in hypercoast/desis.py

def filter_desis(
    dataset: xr.Dataset,
    lat: Union[float, tuple],
    lon: Union[float, tuple],
    return_plot: Optional[bool] = False,
    **kwargs,
) -> xr.Dataset:
    """
    Filters a DESIS dataset based on latitude and longitude.

    Args:
        dataset (xr.Dataset): The DESIS dataset to filter.
        lat (float or tuple): The latitude to filter by. If a tuple or list,
            it represents a range.
        lon (float or tuple): The longitude to filter by. If a tuple or
            list, it represents a range.

    Returns:
        xr.DataArray: The filtered DESIS data.
    """

    if isinstance(lat, list) or isinstance(lat, tuple):
        min_lat = min(lat)
        max_lat = max(lat)
    else:
        min_lat = lat
        max_lat = lat

    if isinstance(lon, list) or isinstance(lon, tuple):
        min_lon = min(lon)
        max_lon = max(lon)
    else:
        min_lon = lon
        max_lon = lon

    if min_lat == max_lat and min_lon == max_lon:
        coords = [[min_lat, min_lon]]
    else:
        coords = [[min_lat, min_lon], [max_lat, max_lon]]
    coords = convert_coords(coords, "epsg:4326", dataset.rio.crs.to_string())

    if len(coords) == 1:
        x, y = coords[0]
        da = dataset.sel(x=x, y=y, method="nearest")["reflectance"]
    else:
        x_min, y_min = coords[0]
        x_max, y_max = coords[1]
        print(x_min, y_min, x_max, y_max)
        da = dataset.sel(x=slice(x_min, x_max), y=slice(y_min, y_max))["reflectance"]

    if return_plot:
        rrs_stack = da.stack(
            {"pixel": ["latitude", "longitude"]},
            create_index=False,
        )
        rrs_stack.plot.line(hue="pixel", **kwargs)
    else:
        return da

read_desis(filepath, wavelengths=None, method='nearest', **kwargs)

Reads DESIS data from a given file and returns an xarray Dataset.

Parameters:

Name	Type	Description	Default
filepath	str	Path to the file to read.	required
wavelengths	array-like	Specific wavelengths to select. If None, all wavelengths are selected.	None
method	str	Method to use for selection when wavelengths is not None. Defaults to "nearest".	'nearest'
**kwargs		Additional keyword arguments to pass to the sel method when bands is not None.	{}

Returns:

Type	Description
xr.Dataset	An xarray Dataset containing the DESIS data.

Source code in hypercoast/desis.py

def read_desis(
    filepath: str,
    wavelengths: Optional[Union[list, tuple]] = None,
    method: Optional[str] = "nearest",
    **kwargs,
) -> xr.Dataset:
    """
    Reads DESIS data from a given file and returns an xarray Dataset.

    Args:
        filepath (str): Path to the file to read.
        wavelengths (array-like, optional): Specific wavelengths to select. If
            None, all wavelengths are selected.
        method (str, optional): Method to use for selection when wavelengths is not
            None. Defaults to "nearest".
        **kwargs: Additional keyword arguments to pass to the `sel` method when
            bands is not None.

    Returns:
        xr.Dataset: An xarray Dataset containing the DESIS data.
    """

    url = "https://github.com/opengeos/datasets/releases/download/hypercoast/desis_wavelengths.csv"
    df = pd.read_csv(url)
    dataset = xr.open_dataset(filepath)
    dataset = dataset.rename(
        {"band": "wavelength", "band_data": "reflectance"}
    ).transpose("y", "x", "wavelength")
    dataset["wavelength"] = df["wavelength"].tolist()

    if wavelengths is not None:
        dataset = dataset.sel(wavelength=wavelengths, method=method, **kwargs)

    dataset.attrs["crs"] = dataset.rio.crs.to_string()

    return dataset