Datasets¶

Datasets are any spatially reference information and usually consist of geometrical representations of a surface or volume in 3D space. In VTK, this superclass is represented by the vtk.vtkDataSet abstract class.

In VTK, datasets consist of geometry, topology, and attributes to which PyVista provides direct access:

Geometry is the collection of points and cells in 2D or 3D space.
Topology defines the structure of the dataset, or how the points are connected to each other to form a cells making a surface or volume.
Attributes are any data values that are associated to either the points or cells of the dataset

All of the following data types are listed subclasses of a dataset and share a set of common functionality which we wrap into the base class pyvista.DataSet.

The DataSet Model¶

The pyvista.DataSet class holds attributes that are common to all spatially referenced datasets in PyVista. This base class is analogous to VTK’s vtk.vtkDataSet class.

Attributes

`active_scalars`	Return the active scalars as an array.
`active_scalars_info`	[field, name].
`active_scalars_name`	Return the active scalar’s name.
`active_tensors`	Return the active tensors array.
`active_tensors_info`	[field, name].
`active_tensors_name`	Return the name of the active tensor array.
`active_vectors`	Return the active vectors array.
`active_vectors_info`	[field, name].
`active_vectors_name`	Return the name of the active vectors array.
`array_names`	Return a list of array names for the dataset.
`arrows`	Return a glyph representation of the active vector data as arrows.
`bounds`	Return the bounding box of this dataset.
`cell_arrays`	Return vtkCellData as DataSetAttributes.
`center`	Return the center of the bounding box.
`extent`	Return the range of the bounding box.
`length`	Return the length of the diagonal of the bounding box.
`n_arrays`	Return the number of arrays present in the dataset.
`n_cells`	Return the number of cells in the entire dataset.
`n_points`	Return the number of points in the entire dataset.
`number_of_cells`	Return the number of cells.
`number_of_points`	Return the number of points.
`point_arrays`	Return vtkPointData as DataSetAttributes.
`points`	Return a pointer to the points as a numpy object.
`t_coords`	Return the active texture coordinates on the points.
`textures`	Return a dictionary to hold compatible `vtk.vtkTexture` objects.
`vectors`	Return active vectors.
`volume`	Return the mesh volume.

Methods

`cast_to_unstructured_grid`()	Get a new representation of this object as an `pyvista.UnstructuredGrid`.
`cell_bounds`(ind)	Return the bounding box of a cell.
`cell_n_points`(ind)	Return the number of points in a cell.
`cell_points`(ind)	Return the points in a cell.
`cell_type`(ind)	Return the type of a cell.
`clear_arrays`()	Remove all arrays from point/cell/field data.
`clear_cell_arrays`()	Remove all cell arrays.
`clear_point_arrays`()	Remove all point arrays.
`clear_textures`()	Clear the textures from this mesh.
`copy_meta_from`(ido)	Copy pyvista meta data onto this object from another object.
`find_closest_cell`(point)	Find index of closest cell in this mesh to the given point.
`find_closest_point`(point[, n])	Find index of closest point in this mesh to the given point.
`get_array`(name[, preference, info])	Search both point, cell and field data for an array.
`get_data_range`([arr_var, preference])	Get the non-NaN min and max of a named array.
`overwrite`(mesh)	Overwrite this mesh inplace with the new mesh’s geometries and data.
`plot`([off_screen, full_screen, screenshot, …])	Plot a vtk or numpy object.
`points_to_double`()	Make points double precision.
`rename_array`(old_name, new_name[, preference])	Change array name by searching for the array then renaming it.
`rotate_x`(angle[, transform_all_input_vectors])	Rotate mesh about the x-axis.
`rotate_y`(angle[, transform_all_input_vectors])	Rotate mesh about the y-axis.
`rotate_z`(angle[, transform_all_input_vectors])	Rotate mesh about the z-axis.
`set_active_scalars`(name[, preference])	Find the scalars by name and appropriately sets it as active.
`set_active_tensors`(name[, preference])	Find the tensors by name and appropriately sets it as active.
`set_active_vectors`(name[, preference])	Find the vectors by name and appropriately sets it as active.
`translate`(xyz)	Translate the mesh.

class pyvista.DataSet(*args, **kwargs)¶

Bases: pyvista.core.filters.DataSetFilters, pyvista.core.dataobject.DataObject

Methods in common to spatially referenced objects.

property active_scalars¶: Return the active scalars as an array.

property active_scalars_info¶

[field, name].

Type: Return the active scalar’s field and name

property active_scalars_name¶: Return the active scalar’s name.

property active_tensors¶: Return the active tensors array.

property active_tensors_info¶

[field, name].

Type: Return the active tensor’s field and name

property active_tensors_name¶: Return the name of the active tensor array.

property active_vectors¶: Return the active vectors array.

property active_vectors_info¶

[field, name].

Type: Return the active scalar’s field and name

property active_vectors_name¶: Return the name of the active vectors array.

property array_names¶

Return a list of array names for the dataset.

This makes sure to put the active scalars’ name first in the list.

property arrows¶

Return a glyph representation of the active vector data as arrows.

Arrows will be located at the points of the mesh and their size will be dependent on the length of the vector. Their direction will be the “direction” of the vector

Returns: arrows – Active scalars represented as arrows.
Return type: pyvista.PolyData

property bounds¶

Return the bounding box of this dataset.

The form is: (xmin,xmax, ymin,ymax, zmin,zmax).

cast_to_unstructured_grid() → pyvista.core.pointset.UnstructuredGrid¶: Get a new representation of this object as an pyvista.UnstructuredGrid.

property cell_arrays¶: Return vtkCellData as DataSetAttributes.

cell_bounds(ind: int) → List[float]¶

Return the bounding box of a cell.

Parameters: ind (int) – Cell ID.
Returns: The limits of the cell in the X, Y and Z directions respectivelly.
Return type: list(float)

Examples

>>> from pyvista import examples
>>> mesh = examples.load_airplane()
>>> mesh.cell_bounds(0)
[896.9940185546875, 907.5390014648438, 48.760101318359375, 55.49020004272461, 80.74520111083984, 83.65809631347656]

cell_n_points(ind: int) → int¶

Return the number of points in a cell.

Parameters: ind (int) – Cell ID.
Returns: Number of points in the cell.
Return type: int

Examples

>>> from pyvista import examples
>>> mesh = examples.load_airplane()
>>> mesh.cell_n_points(0)
3

cell_points(ind: int) → numpy.ndarray¶

Return the points in a cell.

Parameters: ind (int) – Cell ID.
Returns: An array of floats with shape (number of points, 3) containing the coordinates of the cell corners.
Return type: numpy.ndarray

Examples

>>> from pyvista import examples
>>> mesh = examples.load_airplane()
>>> mesh.cell_points(0)  
[[896.99401855  48.76010132  82.26560211]
 [906.59301758  48.76010132  80.74520111]
 [907.53900146  55.49020004  83.65809631]]

cell_type(ind: int) → int¶

Return the type of a cell.

Parameters: ind (int) – Cell ID.
Returns: VTK cell type. See <https://vtk.org/doc/nightly/html/vtkCellType_8h_source.html>.
Return type: int

Examples

>>> from pyvista import examples
>>> mesh = examples.load_airplane()
>>> mesh.cell_type(0)
5

property center¶: Return the center of the bounding box.

clear_arrays()¶: Remove all arrays from point/cell/field data.

clear_cell_arrays()¶: Remove all cell arrays.

clear_point_arrays()¶: Remove all point arrays.

clear_textures()¶: Clear the textures from this mesh.

copy_meta_from(ido: pyvista.core.dataset.DataSet)¶: Copy pyvista meta data onto this object from another object.

property extent¶: Return the range of the bounding box.

find_closest_cell(point: Union[int, numpy.ndarray]) → Union[int, numpy.ndarray]¶

Find index of closest cell in this mesh to the given point.

Parameters: point (iterable(float) or np.ndarray) – Length 3 coordinate of the point to query or a numpy array of coordinates.
Returns: index – Index or indices of the cell in this mesh that is closest to the given point.
Return type: int or np.ndarray

Examples

Find nearest cell to a point on a sphere

>>> import pyvista
>>> mesh = pyvista.Sphere()
>>> index = mesh.find_closest_cell([0, 0, 0.5])
>>> index
59

Find the nearest cells to several random points. Note that -1 indicates that the locator was not able to find a reasonably close cell.

>>> import numpy as np
>>> points = np.random.random((1000, 3))
>>> indices = mesh.find_closest_cell(points)
>>> print(indices.shape)
(1000,)

find_closest_point(point: Iterable[float], n=1) → int¶

Find index of closest point in this mesh to the given point.

If wanting to query many points, use a KDTree with scipy or another library as those implementations will be easier to work with.

See: https://github.com/pyvista/pyvista-support/issues/107

Parameters

point (iterable(float)) – Length 3 coordinate of the point to query.
n (int, optional) – If greater than 1, returns the indices of the n closest points.

Returns

int

Return type

the index of the point in this mesh that is closes to the given point.

get_array(name: str, preference='cell', info=False) → Union[Tuple, numpy.ndarray]¶: Search both point, cell and field data for an array.

get_data_range(arr_var: Optional[Union[str, numpy.ndarray]] = None, preference='cell') → Tuple[Union[float, numpy.ndarray], Union[float, numpy.ndarray]]¶

Get the non-NaN min and max of a named array.

Parameters

arr_var (str, np.ndarray, optional) – The name of the array to get the range. If None, the active scalars is used.
preference (str, optional) – When scalars is specified, this is the preferred array type to search for in the dataset. Must be either 'point', 'cell', or 'field'.

property length¶: Return the length of the diagonal of the bounding box.

property n_arrays¶: Return the number of arrays present in the dataset.

property n_cells¶: Return the number of cells in the entire dataset.

property n_points¶: Return the number of points in the entire dataset.

property number_of_cells¶: Return the number of cells.

property number_of_points¶: Return the number of points.

overwrite(mesh: vtkmodules.vtkCommonDataModel.vtkDataSet)¶

Overwrite this mesh inplace with the new mesh’s geometries and data.

Parameters: mesh (vtk.vtkDataSet) – The overwriting mesh.

plot(off_screen=None, full_screen=False, screenshot=None, interactive=True, cpos=None, window_size=None, show_bounds=False, show_axes=True, notebook=None, background=None, text='', return_img=False, eye_dome_lighting=False, volume=False, parallel_projection=False, use_ipyvtk=None, jupyter_backend=None, return_viewer=False, jupyter_kwargs={}, **kwargs)¶

Plot a vtk or numpy object.

Parameters

item (vtk or numpy object) – VTK object or numpy array to be plotted.
off_screen (bool) – Plots off screen when True. Helpful for saving screenshots without a window popping up.
full_screen (bool, optional) – Opens window in full screen. When enabled, ignores window_size. Default False.
screenshot (str or bool, optional) –
Saves screenshot to file when enabled. See: help(pyvista.Plotter.screenshot). Default False.

When True, takes screenshot and returns numpy array of image.
window_size (list, optional) – Window size in pixels. Defaults to [1024, 768]
show_bounds (bool, optional) – Shows mesh bounds when True. Default False. Alias show_grid also accepted.
notebook (bool, optional) – When True, the resulting plot is placed inline a jupyter notebook. Assumes a jupyter console is active.
show_axes (bool, optional) – Shows a vtk axes widget. Enabled by default.
text (str, optional) – Adds text at the bottom of the plot.
volume (bool, optional) – Use the add_volume method for volume rendering.
use_ipyvtk (bool, optional) – Deprecated. Instead, set the backend either globally with pyvista.set_jupyter_backend('ipyvtklink') or with backend='ipyvtklink'.
jupyter_backend (str, optional) –
Jupyter notebook plotting backend to use. One of the following:
- 'none' : Do not display in the notebook.
- 'static' : Display a static figure.
- 'ipygany' : Show a ipygany widget
- 'panel' : Show a panel widget.
This can also be set globally with pyvista.set_jupyter_backend
jupyter_kwargs (dict, optional) – Keyword arguments for the Jupyter notebook plotting backend.
**kwargs (optional keyword arguments) – See help(Plotter.add_mesh) for additional options.

Returns

cpos (list) – List of camera position, focal point, and view up.
img (numpy.ndarray) – Array containing pixel RGB and alpha. Sized: [Window height x Window width x 3] for transparent_background=False [Window height x Window width x 4] for transparent_background=True Returned only when screenshot enabled

property point_arrays¶: Return vtkPointData as DataSetAttributes.

property points¶: Return a pointer to the points as a numpy object.

points_to_double()¶: Make points double precision.

rename_array(old_name: str, new_name: str, preference='cell')¶: Change array name by searching for the array then renaming it.

rotate_x(angle: float, transform_all_input_vectors=False)¶

Rotate mesh about the x-axis.

Parameters: angle (float) – Angle in degrees to rotate about the x-axis.

rotate_y(angle: float, transform_all_input_vectors=False)¶

Rotate mesh about the y-axis.

Parameters: angle (float) – Angle in degrees to rotate about the y-axis.

rotate_z(angle: float, transform_all_input_vectors=False)¶

Rotate mesh about the z-axis.

Parameters: angle (float) – Angle in degrees to rotate about the z-axis.

set_active_scalars(name: str, preference='cell')¶

Find the scalars by name and appropriately sets it as active.

To deactivate any active scalars, pass None as the name.

set_active_tensors(name: str, preference='point')¶

Find the tensors by name and appropriately sets it as active.

To deactivate any active tensors, pass None as the name.

set_active_vectors(name: str, preference='point')¶

Find the vectors by name and appropriately sets it as active.

To deactivate any active vectors, pass None as the name.

property t_coords¶: Return the active texture coordinates on the points.

property textures¶

Return a dictionary to hold compatible vtk.vtkTexture objects.

When casting back to a VTK dataset or filtering this dataset, these textures will not be passed.

translate(xyz: Union[list, tuple, numpy.ndarray])¶

Translate the mesh.

Parameters: xyz (list or tuple or np.ndarray) – Length 3 list, tuple or array.

property vectors¶: Return active vectors.

property volume¶

Return the mesh volume.

Returns: volume – Total volume of the mesh.
Return type: float