Module i2pp.core.visualizers.discretization_visualizer

Functions for visualizations.

Classes

class DiscretizationVisualizer (pixel_type: PixelValueType,
pixel_range: numpy.ndarray,
title: str | None = None)
Expand source code 
class DiscretizationVisualizer(Visualizer):
    """A visualizer for finite element discretization grids.

    This class extends `Visualizer` to handle unstructured grids based on
    finite element discretization data. It generates PyVista `UnstructuredGrid`
    representations from element and node data, allowing visualization with RGB
    or scalar values.
    """

    def compute_grid(
        self,
        elements_with_values: list[Element],
        dis: Discretization,
    ) -> None:
        """Generates an unstructured grid from discretization data.

        This function constructs a pyvista unstructured grid using the nodes
        and elements from a discretization file. It assigns pixel values (RGB
        or scalar) to the grid cells based on the provided
        `elements_with_values` list.

        If no value can be assigned to an element (e.g., due to filtering or
        if the element is outside the grid), the element value is set to white
        (255 for RGB, the upper bound of `pixel_range` for scalar values).

        All necessary information for plotting (such as the grid, extracted
        grid, value presence mask, and metadata) is stored in the class
        instance attributes (`self.grid`, `self.extracted_grid`,
        `self.grid_visible`, `self.ele_has_value`, and `self.nan_exist`) for
        later use.

        Arguments:
            elements_with_values (list[Element]): List of elements with
                assigned values.
            dis (Discretization): The discretization object containing nodes
                and elements.
        Returns:
            None
        """

        unstructured_grid, ele_has_value = initialize_unstructured_grid(
            elements_with_values, self.pixel_type, dis
        )

        self.nan_exist = not np.all(ele_has_value)
        self.ele_has_value = ele_has_value
        self.grid = unstructured_grid
        self.extracted_grid = (
            unstructured_grid.extract_cells(ele_has_value)
            if self.nan_exist
            else unstructured_grid
        )
        self.grid_visible = unstructured_grid

        return None

A visualizer for finite element discretization grids.

This class extends Visualizer to handle unstructured grids based on finite element discretization data. It generates PyVista UnstructuredGrid representations from element and node data, allowing visualization with RGB or scalar values.

Initialize the Visualizer.

Arguments

pixel_type (PixelValueType): Specifies whether the pixel data is RGB or scalar. title (str | None, optional): The title of the plot window. Defaults to None.

Ancestors

Methods

def compute_grid(self,
elements_with_values: list[Element],
dis: Discretization) ‑> None
Expand source code 
def compute_grid(
    self,
    elements_with_values: list[Element],
    dis: Discretization,
) -> None:
    """Generates an unstructured grid from discretization data.

    This function constructs a pyvista unstructured grid using the nodes
    and elements from a discretization file. It assigns pixel values (RGB
    or scalar) to the grid cells based on the provided
    `elements_with_values` list.

    If no value can be assigned to an element (e.g., due to filtering or
    if the element is outside the grid), the element value is set to white
    (255 for RGB, the upper bound of `pixel_range` for scalar values).

    All necessary information for plotting (such as the grid, extracted
    grid, value presence mask, and metadata) is stored in the class
    instance attributes (`self.grid`, `self.extracted_grid`,
    `self.grid_visible`, `self.ele_has_value`, and `self.nan_exist`) for
    later use.

    Arguments:
        elements_with_values (list[Element]): List of elements with
            assigned values.
        dis (Discretization): The discretization object containing nodes
            and elements.
    Returns:
        None
    """

    unstructured_grid, ele_has_value = initialize_unstructured_grid(
        elements_with_values, self.pixel_type, dis
    )

    self.nan_exist = not np.all(ele_has_value)
    self.ele_has_value = ele_has_value
    self.grid = unstructured_grid
    self.extracted_grid = (
        unstructured_grid.extract_cells(ele_has_value)
        if self.nan_exist
        else unstructured_grid
    )
    self.grid_visible = unstructured_grid

    return None

Generates an unstructured grid from discretization data.

This function constructs a pyvista unstructured grid using the nodes and elements from a discretization file. It assigns pixel values (RGB or scalar) to the grid cells based on the provided elements_with_values list.

If no value can be assigned to an element (e.g., due to filtering or if the element is outside the grid), the element value is set to white (255 for RGB, the upper bound of pixel_range for scalar values).

All necessary information for plotting (such as the grid, extracted grid, value presence mask, and metadata) is stored in the class instance attributes (self.grid, self.extracted_grid, self.grid_visible, self.ele_has_value, and self.nan_exist) for later use.

Arguments

elements_with_values (list[Element]): List of elements with assigned values. dis (Discretization): The discretization object containing nodes and elements.

Returns

None

Inherited members