tensormesh.visualization¶

Draw Graph¶

参数:

sparse_matrix (Union[SparseMatrix, ScipySparseMatrix]) -- the sparse matrix
points (Union[Tensor, np.ndarray]) -- 2D tensor of shape [n_points, 2] the points of the mesh
color (str, optional) -- the color of the edge, default is "blue"
linewidth (int, optional) -- the width of the edge, default is 3
ax (Axes, optional) -- the axis, default is None

返回:

ax -- the axis

返回类型:

Axes

Draw Mesh¶

draw_mesh(mesh, draw_basis: bool = True, edgecolor='blue', linewidth=3, alpha=0.3, ax=None)[源代码]¶

参数:

mesh (Mesh) -- the mesh
draw_basis (bool) -- whether to draw basis
edgecolor (str, optional) -- the color of the edge, default is "blue"
linewidth (float, optional) -- the width of the edge, default is 3
alpha (float, optional) -- the transparency of the edge, default is 0.3
ax (Axes, optional) -- the axis, default is None

返回:

ax -- the axis

返回类型:

Axes

Draw Facet¶

draw_facet_2d(points: Tensor | ndarray, elements: Dict[str, Tensor | ndarray], draw_basis: bool = False, point_color: str = 'orange', color: str = 'blue', alpha: float = 0.5, linewidth: int = 1, ax: Axes | None = None)[源代码]¶

参数:

points (Tensor|np.ndarray) -- 2D tensor of shape [n_points, 2] the points of the mesh
elements (Dict[str,Tensor|np.ndarray]) -- the elements of the mesh [n_element, n_basis]
color (str, optional) -- the color of the facet, default is "blue"
alpha (float, optional) -- the transparency of the facet, default is 0.5
linewidth (int, optional) -- the linewidth of the facet, default is 3
ax (Axes, optional) -- the axis, default is None

返回:

ax -- the axis

返回类型:

Axes

draw_face(mesh, color='blue', linewidth=3, ax=None)[源代码]¶

参数:

mesh (Mesh) -- the mesh
ax (Axes, optional) -- the axis, default is None

返回:

ax -- the axis

返回类型:

Axes

Draw Element Value¶

Parameters:¶

points: torch.Tensor or np.ndarray: [n_points, 2]
elements: torch.Tensor or np.ndarray: [n_elements, 3]
values: torch.Tensor or np.ndarray: [n_elements]
alpha: float or torch.Tensor or np.ndarray: [n_elements] should be greater or equal 0
cmap: str: colormap, default is 'viridis'
color: str: color, if alpha is torch.Tensor or np.ndarray, the color will be used default is None
ax: Axes: default is None

Returns:¶

Axes

参数:

points (Tensor or np.ndarray) -- [n_points, 2]
elements (Dict[str, Tensor or np.ndarray]) -- keys are 'tri' or 'quad' values are torch.Tensor or np.ndarray [n_elements, 3] or [n_elements, 4]
values (Dict[str, Tensor or np.ndarray]) -- [n_elements]
alpha (float or Tensor or np.ndarray) -- [n_elements] should be greater or equal 0 and less or equal than 1
cmap (str) -- colormap, default is 'viridis'
color (str) -- color, if alpha is torch.Tensor or np.ndarray, the color will be used default is None
ax (plt.Axes) -- default is None

返回:

collections (Dict[str, matplotlib.collections.PolyCollection]) -- Dictionary mapping element types to their polygon collections
ax (matplotlib.axes.Axes) -- The matplotlib axes object

update_element_value_2d_tri(img: PolyCollection, values: Tensor | ndarray, alpha: float | Tensor | ndarray | None = None) → PolyCollection[源代码]¶

Update face colors of a triangle PolyCollection.

参数:

img (PolyCollection) -- Collection returned by a draw helper.
values (Tensor or np.ndarray) -- Per-element values, shape (n_elements,).
alpha (float or Tensor or np.ndarray, optional) -- Per-element opacity, shape (n_elements,); must be non-negative when provided as an array.

返回:

The same collection with updated array data.

返回类型:

PolyCollection

update_element_value_2d(collections: Dict[str, PolyCollection], values: Dict[str, Tensor | ndarray], alpha: float | Dict[str, Tensor | ndarray] = 1.0) → Dict[str, PolyCollection][源代码]¶

参数:

collections (Dict[str,PolyCollection])
values (Dict[str, Tensor or np.ndarray]) -- [n_elements]
alpha (float or Tensor or np.ndarray) -- [n_elements] should be greater or equal 0 and less or equal than 1

参数:

points (Tensor or np.ndarray) -- [n_points, 3]
elements (Dict[str,Tensor|np.ndarray]) -- dictionary of elements for each element type
values (Dict[str,Tensor|np.ndarray]) -- dictionary of values for each element type [n_elements]
alpha (float or Dict[str,Tensor|np.ndarray]) -- transparency value(s), default is 1.0
cmap (str) -- colormap, default is 'viridis'
color (Optional[str]) -- if specified, use this color instead of colormap
ax (Optional[plt.Axes]) -- matplotlib 3D axes, default is None

返回:

collections (Dict[str,Path3DCollection]) -- dictionary of scatter collections for each element type
ax (Axes3D) -- the matplotlib 3D axes

update_element_value_3d(collections: Dict[str, Path3DCollection], points: Tensor | ndarray, elements: Dict[str, Tensor | ndarray], values: Dict[str, Tensor | ndarray], density: int = 25)[源代码]¶

Update the element values for a 3D visualization

参数:

collections (Dict[str, Path3DCollection]) -- Dictionary mapping element types to their scatter plot collections
points (Union[Tensor, np.ndarray]) -- Points tensor of shape [n_points, 3]
elements (Dict[str, Union[Tensor, np.ndarray]]) -- Dictionary mapping element types to their element arrays
values (Dict[str, Union[Tensor, np.ndarray]]) -- Dictionary mapping element types to their value arrays
density (int) -- Grid density for interpolation, default 25

Draw element values for 2D or 3D mesh

参数:

mesh (Mesh) -- The mesh object containing points and elements
values (Dict[str, Union[Tensor, np.ndarray]]) -- Dictionary mapping element types to their value arrays
alpha (Optional[Union[float, Dict[str, Union[Tensor, np.ndarray]]]]) -- Transparency value(s). If None, defaults to 1.0 for 2D and 0.2 for 3D. For float values, should be between 0 and 1. For tensor/array values, should be shape [n_elements] with values between 0 and 1.
cmap (str) -- Colormap name, default 'viridis'
color (Optional[str]) -- If specified, use this color instead of colormap
density (int) -- Grid density for 3D interpolation, default 25
ax (Optional[Union[Axes, Axes3D]]) -- Matplotlib axes, default None

返回:

collections (Dict[str, Union[PolyCollection, Path3DCollection]]) -- Dictionary mapping element types to their collections
ax (Union[Axes, Axes3D]) -- The matplotlib axes

update_element_value(mesh, collections: Dict[str, PolyCollection | Path3DCollection], values: Dict[str, Tensor | ndarray], alpha: float | Dict[str, Tensor | ndarray] = 1.0, density: int = 25)[源代码]¶

Update element values for 2D or 3D visualization

参数:

mesh (Mesh) -- The mesh object containing points and elements
collections (Dict[str, Union[PolyCollection, Path3DCollection]]) -- Dictionary mapping element types to their collections
values (Dict[str, Union[Tensor, np.ndarray]]) -- Dictionary mapping element types to their value arrays
alpha (float or Dict[str, Union[Tensor, np.ndarray]]) -- Transparency value(s), default 1.0
density (int) -- Grid density for 3D interpolation, default 25

Draw Point Value¶

draw_point_value_2d_tri_gouraud(points: Tensor | ndarray, point_values: Tensor | ndarray, elements: Tensor | ndarray, cmap: str = 'jet', ax: Axes | None = None) → Tuple[TriMesh, Axes][源代码]¶

参数:

points (Union[Tensor,np.ndarray]) -- 2D tensor of shape [n_points, 2] the points of the mesh
point_values (Union[Tensor,np.ndarray]) -- 1D tensor of shape [n_points] the value of the points
elements (Union[Tensor,np.ndarray]) -- 2D tensor of shape [n_elements, 3] the elements of the mesh
cmap (str, optional) -- the colormap, default is 'jet'
ax (Axes, optional) -- the axis, default is None

返回:

img (matplotlib.collections.PathCollection)
ax (matplotlib.axes.Axes)

update_point_value_2d_tri_gouraud(img: TriMesh, point_values: Tensor | ndarray)[源代码]¶

参数:

img (PolyCollection) -- the image
point_values (Union[Tensor,np.ndarray]) -- the point values, 1D tensor of shape [n_points]

draw_point_value_2d_interpolation(points: Tensor | ndarray, point_values: Tensor | ndarray, density: int = 100, cmap: str = 'jet', use_scatter: bool = False, ax: Axes | None = None) → Tuple[PathCollection | AxesImage, Axes][源代码]¶

Parameters:¶

points: Union[torch.Tensor,np.ndarray]: 2D tensor of shape [n_points, 2] the points of the mesh
point_values: Union[torch.Tensor,np.ndarray]: 1D tensor of shape [n_points] the value of the points
density: int: the density of the interpolation default is 100
cmap: str: the colormap default is 'jet'
ax: Optional[matplotlib.axes.Axes]: the axis default is None

returns:

img (matplotlib.collections.PathCollection)
ax (matplotlib.axes.Axes)

update_point_value_2d_interpolation(img: PathCollection | AxesImage, points: Tensor | ndarray, point_values: Tensor | ndarray)[源代码]¶

参数:

img (Union[PathCollection,AxesImage]) -- the image
points (Union[Tensor,np.ndarray]) -- the points, 2D tensor of shape [n_points, 2]
point_values (Union[Tensor,np.ndarray]) -- the point values, 1D tensor of shape [n_points]

draw_point_value_2d(points: Tensor | ndarray, point_values: Tensor | ndarray, elements: Dict[str, Tensor | ndarray], density: int = 100, cmap: str = 'jet', use_scatter: bool = False, ax: Axes | None = None)[源代码]¶

Draw nodal values on a 2D mesh.

For first-order triangles uses Gouraud shading; otherwise uses 2D interpolation.

参数:

points (Union[Tensor,np.ndarray]) -- 2D tensor of shape [n_points, 2] the points of the mesh
point_values (Union[Tensor,np.ndarray]) -- 1D tensor of shape [n_points] the value of the points
elements (Dict[str,Union[Tensor,np.ndarray]]) -- 2D tensor of shape [n_elements, n_basis] the elements of the mesh
density (int) -- the density of the interpolation default is 100
cmap (str) -- the colormap default is 'jet'
use_scatter (bool)
ax (Optional[Axes]) -- the axis default is None

返回:

img (matplotlib.collections.PathCollection)
ax (matplotlib.axes.Axes) -- the axis

update_point_value_2d(img: PathCollection | PolyCollection | AxesImage, points: Tensor | ndarray, point_values: Tensor | ndarray)[源代码]¶

参数:

img (PathCollection) -- the image
points (Union[Tensor,np.ndarray]) -- the points, 2D tensor of shape [n_points, 2]
point_values (Union[Tensor,np.ndarray]) -- the point values, 1D tensor of shape [n_points]

draw_point_value_3d_interpolation(points: Tensor | ndarray, point_values: Tensor | ndarray, density: int = 25, cmap: str = 'jet', ax: Axes3D | None = None) → tuple[Path3DCollection, Axes3D][源代码]¶

参数:

points (Union[Tensor, np.ndarray]) -- 3D tensor of shape [n_points, 3] the points of the mesh
point_values (Union[Tensor, np.ndarray]) -- 1D tensor of shape [n_points] the value of the points
density (int) -- the density of the interpolation default is 50
cmap (str) -- the colormap default is 'jet'
ax (Optional[Axes]) -- the axis, should be a 3D axis default is None

返回:

img (list[matplotlib.collections.PathCollection]) -- list of scatter plots for each slice
ax (matplotlib.axes.Axes) -- the 3D axis

update_point_value_3d_interpolation(img: Path3DCollection, points: Tensor | ndarray, point_values: Tensor | ndarray)[源代码]¶

参数:

scatter_plots (list[PathCollection]) -- list of scatter plots returned by draw_point_value_3d_interpolation
points (Union[Tensor, np.ndarray]) -- the points, 3D tensor of shape [n_points, 3]
point_values (Union[Tensor, np.ndarray]) -- the point values, 1D tensor of shape [n_points]

参数:

points (Union[Tensor, np.ndarray]) -- tensor of shape [n_points, dim] the points of the mesh
point_values (Union[Tensor, np.ndarray]) -- 1D tensor of shape [n_points] the value of the points
elements (Dict[str,Union[Tensor, np.ndarray]]) -- the elements of the mesh
density (int) -- the density of the interpolation default is 100
cmap (str) -- the colormap default is 'jet'
use_scatter (bool) -- whether to use scatter plot (2D only)
ax (Optional[Axes]) -- the axis default is None

返回:

img (Union[matplotlib.collections.PathCollection, list[matplotlib.collections.PathCollection]])
ax (matplotlib.axes.Axes)

update_point_value(mesh, img: TriMesh | AxesImage | PathCollection | Path3DCollection, point_values: Tensor | ndarray)[源代码]¶

参数:

img (Union[PathCollection, PolyCollection, AxesImage, list]) -- the visualization object(s) to update
points (Union[Tensor, np.ndarray]) -- the points
point_values (Union[Tensor, np.ndarray]) -- the point values

Stream Plotter¶

class StreamPlotter(nrows: int = 1, ncols: int = 1, width: int = 5, height: int = 5, filename: str = 'stream_plotter.mp4')[源代码]¶

基类：object

__init__(nrows: int = 1, ncols: int = 1, width: int = 5, height: int = 5, filename: str = 'stream_plotter.mp4')[源代码]¶

grab_frame(**savefig_kwargs)[源代码]¶

update()[源代码]¶

draw_mesh_2d(points: Tensor | ndarray, elements: Dict[str, Tensor | ndarray], point_values: Tensor | ndarray, ax: Axes | None = None, cmap: str = 'jet', density: int = 100, use_scatter: bool = False, show_colorbar: bool = True, title: str = '', update: bool = True, show_mesh: bool = True, show_basis: bool = True, umin: float | None = None, umax: float | None = None, linewidth: int = 1, basiscolor: str = 'orange', linecolor: str = 'blue')[源代码]¶

参数:

mesh (Mesh) -- the mesh
point_values (Tensor [n_point]) -- the value of the points
ax (Axes, optional) -- the axis, default is None
cmap (str)
density (int)
use_scatter (bool)
show_colorbar (bool, optional) -- whether to show the colorbar, default is True
title (str, optional) -- the title of the plot, default is ""
update (bool, optional) -- whether to update the plot, default is True
show_mesh (bool, optional) -- whether to show the mesh, default is True

draw_mesh_2d_static(points: Tensor | ndarray, elements: Dict[str, Tensor | ndarray], point_values: Dict[str, Tensor | ndarray] | ndarray | Tensor, show_colorbar: bool = True, show_mesh: bool = False, filename: str = 'mesh_2d_stream.jpq', umin: float | None = None, umax: float | None = None, **kwargs)[源代码]¶

参数:

mesh (Mesh)
point_values (Dict[str,np.ndarray|Tensor]|Tensor|np.ndarray) -- if more than one value is supposed to be drawn, then one could use {value_name:value} format each tensor or ndarray should be of shape [time_seq, n_points]

Animation¶

animate_deformation(mesh, displacement: Tensor, file_name: str, frames: int = 30, fps: int = 10, scale_factor: float = 1.0, scalars: str = 'displacement')[源代码]¶

Static Plot¶

plot_deformation(mesh, displacement: Tensor, file_name: str, scale_factor: float = 1.0, camera_position='isometric', fixed_nodes=None, force_vectors=None, linearize: bool = True)[源代码]¶

PyVista¶

plot_value(kwargs, mesh, save_path=None, dt=None, show_mesh=False)[源代码]¶

Utilities¶

as_sparse_matrix(x: SparseMatrix | coo_matrix | csr_matrix | csc_matrix | dia_matrix | dok_matrix | lil_matrix) → SparseMatrix[源代码]¶

as_tensor(x: Tensor | ndarray) → Tensor[源代码]¶

as_ndarray(x: Tensor | ndarray) → ndarray[源代码]¶

dim(x: Tensor | ndarray) → int[源代码]¶

grid(dim: int, min_vals: Sequence[float], max_vals: Sequence[float], density: int = 100) → ndarray[源代码]¶

Create a grid of points in 2D or 3D space.

参数:

dim (int) -- Dimension of the grid (2 or 3)
min_vals (Sequence[float]) -- Minimum values for each dimension
max_vals (Sequence[float]) -- Maximum values for each dimension
density (int, optional) -- Number of points along each dimension, by default 100

返回:

Grid points with shape (density^dim, dim)

返回类型:

np.ndarray

setup_headless()[源代码]¶: Start xvfb for headless rendering if needed.

mesh_to_pyvista(mesh, point_data=None, cell_data=None, linearize=False)[源代码]¶

Convert TensorMesh to PyVista mesh via intermediate VTU file.

参数:

mesh (Mesh)
point_data (dict, optional) -- Dict of {name: tensor/array} to add as point data.
cell_data (dict, optional) -- Dict of {name: tensor/array} to add as cell data.
linearize (bool, optional) -- If True, convert high-order elements to linear (e.g. tet10 -> tet4).

返回类型:

pyvista.DataSet