Module pyaurorax.tools.grid_files

Prepare grid data for plotting.

Classes

class GridFilesManager (aurorax_obj)

Expand source code

class GridFilesManager:
    """
    The GridFilesManager object is initialized within every PyAuroraX object. It acts as a way to access 
    the submodules and carry over configuration information in the super class.
    """

    def __init__(self, aurorax_obj):
        self.__aurorax_obj = aurorax_obj

    def prep_grid_image(
        self,
        grid: np.ndarray,
        fill_val: Union[int, float] = -999.0,
        scale: Optional[Union[list, np.ndarray]] = None,
        cmap: Optional[str] = "Greys_r",
    ) -> np.ndarray:
        """
        Takes a grid image, and converts it to RGBA format, masking all empty cells with max
        transparency, so that it can be plotted overtop of a map.

        NOTE: the grid data passed in must be for a single grid image. Multiple images in a single
        call to this function is presently not supported.

        Args:
            grid (numpy.ndarray): 
                The grid array to prepare. Usually a result of reading a grid file and obtaining grid data from 
                said file. 
                
                Please note that the data must be a single frame; multiple frames are currently not supported.

            fill_val (int or float): 
                The fill value that was used to fill grid cells containing no data. Usually obtained from the 
                grid file's metadata.

            scale (list or numpy.ndarray): 
                A two-element vector specifying the minimum and maximum values to scale data between. This parameter
                is optional. Defaults to data min/max.

            cmap (str): 
                A string giving the name of a matplotlib colormap to prep single-channel image data using. This parameter
                is optional. Defaults to "Greys_r".

        Returns:
            The prepared RGBA grid array.

        Raises:
            ValueError: issues encountered with supplied parameters
        """
        return func_prep_grid_image(self.__aurorax_obj, grid, fill_val, scale, cmap)

The GridFilesManager object is initialized within every PyAuroraX object. It acts as a way to access the submodules and carry over configuration information in the super class.

Methods

def prep_grid_image(self,
grid: numpy.ndarray,
fill_val: float | int = -999.0,
scale: numpy.ndarray | list | None = None,
cmap: str | None = 'Greys_r') ‑> numpy.ndarray

Expand source code

def prep_grid_image(
    self,
    grid: np.ndarray,
    fill_val: Union[int, float] = -999.0,
    scale: Optional[Union[list, np.ndarray]] = None,
    cmap: Optional[str] = "Greys_r",
) -> np.ndarray:
    """
    Takes a grid image, and converts it to RGBA format, masking all empty cells with max
    transparency, so that it can be plotted overtop of a map.

    NOTE: the grid data passed in must be for a single grid image. Multiple images in a single
    call to this function is presently not supported.

    Args:
        grid (numpy.ndarray): 
            The grid array to prepare. Usually a result of reading a grid file and obtaining grid data from 
            said file. 
            
            Please note that the data must be a single frame; multiple frames are currently not supported.

        fill_val (int or float): 
            The fill value that was used to fill grid cells containing no data. Usually obtained from the 
            grid file's metadata.

        scale (list or numpy.ndarray): 
            A two-element vector specifying the minimum and maximum values to scale data between. This parameter
            is optional. Defaults to data min/max.

        cmap (str): 
            A string giving the name of a matplotlib colormap to prep single-channel image data using. This parameter
            is optional. Defaults to "Greys_r".

    Returns:
        The prepared RGBA grid array.

    Raises:
        ValueError: issues encountered with supplied parameters
    """
    return func_prep_grid_image(self.__aurorax_obj, grid, fill_val, scale, cmap)

Takes a grid image, and converts it to RGBA format, masking all empty cells with max transparency, so that it can be plotted overtop of a map.

NOTE: the grid data passed in must be for a single grid image. Multiple images in a single call to this function is presently not supported.

Args

grid : numpy.ndarray

The grid array to prepare. Usually a result of reading a grid file and obtaining grid data from said file.

Please note that the data must be a single frame; multiple frames are currently not supported.

fill_val : int or float

The fill value that was used to fill grid cells containing no data. Usually obtained from the grid file's metadata.

scale : list or numpy.ndarray

A two-element vector specifying the minimum and maximum values to scale data between. This parameter is optional. Defaults to data min/max.

cmap : str

A string giving the name of a matplotlib colormap to prep single-channel image data using. This parameter is optional. Defaults to "Greys_r".

Returns

The prepared RGBA grid array.

Raises

ValueError

issues encountered with supplied parameters