RasterProcessing.__init__

RasterProcessing.__init__(name: str, algo: Callable | None = None, nodata: float | None = None, dtype: dtype | None = None, in_dtype: dtype | None = None, compress: str | None = None, nbits: int = False, per_band_algo: bool = False)[source]

Constructor

Parameters:

  • name (str) – Display name of the processing

  • algo (Callable[[List[np.ndarray], kwargs], np.ndarray], optional, default=None) – Lambda function used to compute the indice. The lambda function takes as input a multidimensional array of data to process and the list of the arguments values of the processing (see with_argument()). It returns the processed data.

  • nodata (float, optional, default=None) – Nodata value for the output data

  • dtype (rasterio or numpy data type, optional, default=None) – Type of generated data. When None, the generated data are supposed to be of the same type as input data.

  • in_dtype (rasterio or numpy data type, optional, default=None) – Type of processed data. When None, the processed data are supposed to be of the same type as dtype parameter.

  • compress (str, optional, default=None) – Set the compression to use.

  • nbits (int, optional, default=None) – Create a file with less than 8 bits per sample by passing a value from 1 to 7. The apparent pixel type should be Byte.

  • per_band_algo (bool, optional, default=False) – Whether the algo is applied on a dataset that contains only one band (per_band_algo=True) or on a dataset with all bands (per_band_algo=False)