"""An internal module for wrapping the use of mappers.""" from __future__ import annotations import sys from typing import TYPE_CHECKING from typing import Optional from typing import cast import numpy as np import pyvista from pyvista.core.utilities.arrays import FieldAssociation from pyvista.core.utilities.arrays import convert_array from pyvista.core.utilities.arrays import convert_string_array from pyvista.core.utilities.arrays import raise_not_matching from pyvista.core.utilities.helpers import wrap from pyvista.core.utilities.misc import abstract_class from pyvista.core.utilities.misc import no_new_attr from . import _vtk from .colors import Color from .colors import get_cmap_safe from .lookup_table import LookupTable from .tools import normalize from .utilities.algorithms import set_algorithm_input if TYPE_CHECKING: # pragma: no cover from pyvista.core._typing_core import BoundsLike @abstract_class class _BaseMapper(_vtk.vtkAbstractMapper): """Base Mapper with methods common to other mappers.""" _new_attr_exceptions = ('_theme',) def __init__(self, theme=None, **kwargs): self._theme = pyvista.themes.Theme() if theme is None: # copy global theme to ensure local property theme is fixed # after creation. self._theme.load_theme(pyvista.global_theme) else: self._theme.load_theme(theme) self.lookup_table = LookupTable() self.interpolate_before_map = kwargs.get( 'interpolate_before_map', self._theme.interpolate_before_map, ) @property def bounds(self) -> BoundsLike: # numpydoc ignore=RT01 """Return the bounds of this mapper. Examples -------- >>> import pyvista as pv >>> mapper = pv.DataSetMapper(dataset=pv.Cube()) >>> mapper.bounds (-0.5, 0.5, -0.5, 0.5, -0.5, 0.5) """ return self.GetBounds() def copy(self) -> _BaseMapper: """Create a copy of this mapper. Returns ------- pyvista.DataSetMapper A copy of this dataset mapper. Examples -------- >>> import pyvista as pv >>> mapper = pv.DataSetMapper(dataset=pv.Cube()) >>> mapper_copy = mapper.copy() """ new_mapper = type(self)(theme=self._theme) # even though this uses ShallowCopy, the new mapper no longer retains # any connection with the original new_mapper.ShallowCopy(self) if hasattr(self, 'dataset'): new_mapper.dataset = self.dataset return new_mapper @property def scalar_range(self) -> tuple[float, float]: # numpydoc ignore=RT01 """Return or set the scalar range. Examples -------- Return the scalar range of a mapper. >>> import pyvista as pv >>> mesh = pv.Sphere() >>> pl = pv.Plotter() >>> actor = pl.add_mesh(mesh, scalars=mesh.points[:, 2]) >>> actor.mapper.scalar_range (-0.5, 0.5) >>> pl.close() Return the scalar range of a composite dataset. In this example it's set to its default value of ``(0.0, 1.0)``. >>> import pyvista as pv >>> dataset = pv.MultiBlock( ... [pv.Cube(), pv.Sphere(center=(0, 0, 1))] ... ) >>> pl = pv.Plotter() >>> actor, mapper = pl.add_composite(dataset) >>> mapper.scalar_range (0.0, 1.0) >>> pl.close() """ return self.GetScalarRange() @scalar_range.setter def scalar_range(self, clim): # numpydoc ignore=GL08 self.SetScalarRange(*clim) @property def lookup_table(self) -> pyvista.LookupTable: # numpydoc ignore=RT01 """Return or set the lookup table. Examples -------- Return the lookup table of a dataset mapper. >>> import pyvista as pv >>> mesh = pv.Sphere() >>> pl = pv.Plotter() >>> actor = pl.add_mesh( ... mesh, scalars=mesh.points[:, 2], cmap='bwr' ... ) >>> actor.mapper.lookup_table LookupTable (...) Table Range: (-0.5, 0.5) N Values: 256 Above Range Color: None Below Range Color: None NAN Color: Color(name='darkgray', hex='#a9a9a9ff', opacity=255) Log Scale: False Color Map: "bwr" Return the lookup table of a composite dataset mapper. >>> import pyvista as pv >>> dataset = pv.MultiBlock( ... [pv.Cube(), pv.Sphere(center=(0, 0, 1))] ... ) >>> pl = pv.Plotter() >>> actor, mapper = pl.add_composite(dataset) >>> mapper.lookup_table # doctest:+SKIP """ return self.GetLookupTable() @lookup_table.setter def lookup_table(self, table): # numpydoc ignore=GL08 self.SetLookupTable(table) @property def color_mode(self) -> str: # numpydoc ignore=RT01 """Return or set the color mode. Either ``'direct'``, or ``'map'``. * ``'direct'`` - All integer types are treated as colors with values in the range 0-255 and floating types are treated as colors with values in the range 0.0-1.0 * ``'map'`` - All scalar data will be mapped through the lookup table. """ mode = self.GetColorModeAsString().lower() if mode == 'mapscalars': return 'map' return 'direct' @color_mode.setter def color_mode(self, value: str): # numpydoc ignore=GL08 if value == 'direct': self.SetColorModeToDirectScalars() elif value == 'map': self.SetColorModeToMapScalars() else: raise ValueError('Color mode must be either "default", "direct" or "map"') @property def interpolate_before_map(self) -> bool: # numpydoc ignore=RT01 """Return or set the interpolation of scalars before mapping. Enabling makes for a smoother scalars display. When ``False``, OpenGL will interpolate the mapped colors which can result in showing colors that are not present in the color map. Examples -------- Disable interpolation before mapping. >>> import pyvista as pv >>> dataset = pv.MultiBlock( ... [pv.Cube(), pv.Sphere(center=(0, 0, 1))] ... ) >>> dataset[0].point_data['data'] = dataset[0].points[:, 2] >>> dataset[1].point_data['data'] = dataset[1].points[:, 2] >>> pl = pv.Plotter() >>> actor, mapper = pl.add_composite( ... dataset, ... show_scalar_bar=False, ... n_colors=3, ... cmap='bwr', ... ) >>> mapper.interpolate_before_map = False >>> pl.show() Enable interpolation before mapping. >>> pl = pv.Plotter() >>> actor, mapper = pl.add_composite( ... dataset, ... show_scalar_bar=False, ... n_colors=3, ... cmap='bwr', ... ) >>> mapper.interpolate_before_map = True >>> pl.show() See :ref:`interpolate_before_mapping_example` for additional explanation regarding this attribute. """ return bool(self.GetInterpolateScalarsBeforeMapping()) @interpolate_before_map.setter def interpolate_before_map(self, value: bool): # numpydoc ignore=GL08 self.SetInterpolateScalarsBeforeMapping(value) @property def array_name(self) -> str: # numpydoc ignore=RT01 """Return or set the array name or number and component to color by. Examples -------- Show the name of the active scalars in the mapper. >>> import pyvista as pv >>> mesh = pv.Sphere() >>> mesh['my_scalars'] = mesh.points[:, 2] >>> pl = pv.Plotter() >>> actor = pl.add_mesh(mesh, scalars='my_scalars') >>> actor.mapper.array_name 'my_scalars' >>> pl.close() """ return self.GetArrayName() @array_name.setter def array_name(self, name: str): # numpydoc ignore=GL08 """Return or set the array name or number and component to color by.""" self.SetArrayName(name) @property def scalar_map_mode(self) -> str: # numpydoc ignore=RT01 """Return or set the scalar map mode. Examples -------- Show that the scalar map mode is set to ``'point'`` when setting the active scalars to point data. >>> import pyvista as pv >>> dataset = pv.MultiBlock( ... [pv.Cube(), pv.Sphere(center=(0, 0, 1))] ... ) >>> dataset[0].point_data['data'] = dataset[0].points[:, 2] >>> dataset[1].point_data['data'] = dataset[1].points[:, 2] >>> pl = pv.Plotter() >>> actor, mapper = pl.add_composite( ... dataset, scalars='data', show_scalar_bar=False ... ) >>> mapper.scalar_map_mode 'point' >>> pl.close() """ # map vtk strings to more sensible strings vtk_to_pv = { 'Default': 'default', 'UsePointData': 'point', 'UseCellData': 'cell', 'UsePointFieldData': 'point_field', 'UseCellFieldData': 'cell_field', 'UseFieldData': 'field', } return vtk_to_pv[self.GetScalarModeAsString()] @scalar_map_mode.setter def scalar_map_mode(self, scalar_mode: str | FieldAssociation): # numpydoc ignore=GL08 if isinstance(scalar_mode, FieldAssociation): scalar_mode = scalar_mode.name scalar_mode = scalar_mode.lower() if scalar_mode == 'default': self.SetScalarModeToDefault() elif scalar_mode == 'point': self.SetScalarModeToUsePointData() elif scalar_mode == 'cell': self.SetScalarModeToUseCellData() elif scalar_mode == 'point_field': self.SetScalarModeToUsePointFieldData() elif scalar_mode == 'cell_field': self.SetScalarModeToUseCellFieldData() elif scalar_mode == 'field': self.SetScalarModeToUseFieldData() else: raise ValueError( f'Invalid `scalar_map_mode` "{scalar_mode}". Should be either ' '"default", "point", "cell", "point_field", "cell_field" or "field".', ) @property def scalar_visibility(self) -> bool: # numpydoc ignore=RT01 """Return or set the scalar visibility. Examples -------- Show that scalar visibility is ``False``. >>> import pyvista as pv >>> mesh = pv.Sphere() >>> pl = pv.Plotter() >>> actor = pl.add_mesh(mesh) >>> actor.mapper.scalar_visibility False >>> pl.close() Show that scalar visibility is ``True``. >>> import pyvista as pv >>> dataset = pv.MultiBlock( ... [pv.Cube(), pv.Sphere(center=(0, 0, 1))] ... ) >>> dataset[0].point_data['data'] = dataset[0].points[:, 2] >>> dataset[1].point_data['data'] = dataset[1].points[:, 2] >>> pl = pv.Plotter() >>> actor, mapper = pl.add_composite(dataset, scalars='data') >>> mapper.scalar_visibility True >>> pl.close() """ return bool(self.GetScalarVisibility()) @scalar_visibility.setter def scalar_visibility(self, value: bool): # numpydoc ignore=GL08 self.SetScalarVisibility(value) def update(self): """Update this mapper.""" self.Update() @no_new_attr class _DataSetMapper(_BaseMapper): """Base wrapper for _vtk.vtkDataSetMapper. Parameters ---------- dataset : pyvista.DataSet, optional Dataset to assign to this mapper. theme : pyvista.plotting.themes.Theme, optional Plot-specific theme. """ _cmap = None def __init__( self, dataset: pyvista.DataSet | None = None, theme: pyvista.themes.Theme | None = None, ): """Initialize this class.""" super().__init__(theme=theme) if dataset is not None: self.dataset = dataset @property def dataset(self) -> pyvista.core.dataset.DataSet | None: # numpydoc ignore=RT01 """Return or set the dataset assigned to this mapper.""" return cast(Optional[pyvista.DataSet], wrap(self.GetInputAsDataSet())) @dataset.setter def dataset( self, obj: pyvista.core.dataset.DataSet | _vtk.vtkAlgorithm | _vtk.vtkAlgorithmOutput, ): # numpydoc ignore=GL08 set_algorithm_input(self, obj) def as_rgba(self): # numpydoc ignore=GL08 """Convert the active scalars to RGBA. This method is used to convert the active scalars to a fixed RGBA array and is used for certain mappers that do not support the "map" color mode. """ if self.color_mode == 'direct': return self.dataset.point_data.pop('__rgba__', None) self._configure_scalars_mode( self.lookup_table(self.dataset.active_scalars), '__rgba__', self.scalar_map_mode, True, ) def _configure_scalars_mode( self, scalars, scalars_name, preference, direct_scalars_color_mode, ): """Configure scalar mode. Parameters ---------- scalars : numpy.ndarray Array of scalars to assign to the mapper. scalars_name : str If the name of this array exists, scalars is ignored. Otherwise, the scalars will be added to the existing dataset and this parameter is the name to assign the scalars. preference : str Either ``'point'`` or ``'cell'``. direct_scalars_color_mode : bool When ``True``, scalars are treated as RGB colors. When ``False``, scalars are mapped to the color table. """ if scalars.shape[0] == self.dataset.n_points and scalars.shape[0] == self.dataset.n_cells: use_points = preference == 'point' use_cells = not use_points else: use_points = scalars.shape[0] == self.dataset.n_points use_cells = scalars.shape[0] == self.dataset.n_cells # Scalars interpolation approach if use_points: if ( scalars_name not in self.dataset.point_data or scalars_name == pyvista.DEFAULT_SCALARS_NAME ): self.dataset.point_data.set_array(scalars, scalars_name, False) self.dataset.active_scalars_name = scalars_name self.scalar_map_mode = 'point' elif use_cells: if ( scalars_name not in self.dataset.cell_data or scalars_name == pyvista.DEFAULT_SCALARS_NAME ): self.dataset.cell_data.set_array(scalars, scalars_name, False) self.dataset.active_scalars_name = scalars_name self.scalar_map_mode = 'cell' else: raise_not_matching(scalars, self.dataset) self.color_mode = 'direct' if direct_scalars_color_mode else 'map' def set_scalars( self, scalars, scalars_name, n_colors=256, scalar_bar_args=None, rgb=None, component=None, preference='point', custom_opac=False, annotations=None, log_scale=False, nan_color=None, above_color=None, below_color=None, cmap=None, flip_scalars=False, opacity=None, categories=False, clim=None, ): """Set the scalars on this mapper. Parameters ---------- scalars : numpy.ndarray Array of scalars to assign to the mapper. scalars_name : str If the name of this array exists, scalars is ignored. Otherwise, the scalars will be added to the existing dataset and this parameter is the name to assign the scalars. n_colors : int, default: 256 Number of colors to use when displaying scalars. scalar_bar_args : dict, optional Dictionary of keyword arguments to pass when adding the scalar bar to the scene. For options, see :func:`pyvista.Plotter.add_scalar_bar`. rgb : bool, default: False If an 2 dimensional array is passed as the scalars, plot those values as RGB(A) colors. ``rgba`` is also an accepted alias for this. Opacity (the A) is optional. If a scalars array ending with ``"_rgba"`` is passed, the default becomes ``True``. This can be overridden by setting this parameter to ``False``. component : int, optional Set component of vector valued scalars to plot. Must be nonnegative, if supplied. If ``None``, the magnitude of the vector is plotted. preference : str, default: 'Point' When ``dataset.n_points == dataset.n_cells`` and setting scalars, this parameter sets how the scalars will be mapped to the mesh. Can be either ``'point'`` or ``'cell'``. custom_opac : bool, default: False Use custom opacity. annotations : dict, optional Pass a dictionary of annotations. Keys are the float values in the scalars range to annotate on the scalar bar and the values are the string annotations. log_scale : bool, default: False Use log scale when mapping data to colors. Scalars less than zero are mapped to the smallest representable positive float. nan_color : pyvista.ColorLike, optional The color to use for all ``NaN`` values in the plotted scalar array. above_color : pyvista.ColorLike, optional Solid color for values below the scalars range (``clim``). This will automatically set the scalar bar ``above_label`` to ``'above'``. below_color : pyvista.ColorLike, optional Solid color for values below the scalars range (``clim``). This will automatically set the scalar bar ``below_label`` to ``'below'``. cmap : str, list, or pyvista.LookupTable Name of the Matplotlib colormap to use when mapping the ``scalars``. See available Matplotlib colormaps. Only applicable for when displaying ``scalars``. ``colormap`` is also an accepted alias for this. If ``colorcet`` or ``cmocean`` are installed, their colormaps can be specified by name. You can also specify a list of colors to override an existing colormap with a custom one. For example, to create a three color colormap you might specify ``['green', 'red', 'blue']``. This parameter also accepts a :class:`pyvista.LookupTable`. If this is set, all parameters controlling the color map like ``n_colors`` will be ignored. flip_scalars : bool, default: False Flip direction of cmap. Most colormaps allow ``*_r`` suffix to do this as well. opacity : str or numpy.ndarray, optional Opacity mapping for the scalars array. A string can also be specified to map the scalars range to a predefined opacity transfer function (options include: 'linear', 'linear_r', 'geom', 'geom_r'). Or you can pass a custom made transfer function that is an array either ``n_colors`` in length or shorter. categories : bool, default: False If set to ``True``, then the number of unique values in the scalar array will be used as the ``n_colors`` argument. clim : Sequence, optional Color bar range for scalars. Defaults to minimum and maximum of scalars array. Example: ``(-1, 2)``. """ if scalar_bar_args is None: scalar_bar_args = {'n_colors': n_colors} if not isinstance(scalars, np.ndarray): scalars = np.asarray(scalars) # Set the array title for when it is added back to the mesh if custom_opac: scalars_name = '__custom_rgba' if not np.issubdtype(scalars.dtype, np.number) and not isinstance( cmap, pyvista.LookupTable, ): # we can rapidly handle bools if scalars.dtype == np.bool_: cats = np.array([b'False', b'True'], dtype='|S5') values = np.array([0, 1]) clim = [-0.5, 1.5] else: # If str array, digitize and annotate cats, scalars = np.unique(scalars.astype('|S'), return_inverse=True) values = np.unique(scalars) clim = [np.min(values) - 0.5, np.max(values) + 0.5] scalars_name = f'{scalars_name}-digitized' n_colors = len(cats) scalar_bar_args.setdefault('n_labels', 0) self.lookup_table.SetAnnotations(convert_array(values), convert_string_array(cats)) # Use only the real component if an array is complex if np.issubdtype(scalars.dtype, np.complexfloating): scalars = scalars.astype(float) scalars_name = f'{scalars_name}-real' if scalars.ndim != 1: if rgb: pass elif scalars.ndim == 2 and ( scalars.shape[0] == self.dataset.n_points or scalars.shape[0] == self.dataset.n_cells ): if not isinstance(component, (int, type(None))): raise TypeError('component must be either None or an integer') if component is None: scalars = np.linalg.norm(scalars.copy(), axis=1) scalars_name = f'{scalars_name}-normed' elif component < scalars.shape[1] and component >= 0: scalars = np.array(scalars[:, component]).copy() scalars_name = f'{scalars_name}-{component}' else: raise ValueError( 'Component must be nonnegative and less than the ' f'dimensionality of the scalars array: {scalars.shape[1]}', ) else: scalars = scalars.ravel() if scalars.dtype == np.bool_: scalars = scalars.astype(np.float64) # Set scalars range if clim is None: clim = [np.nanmin(scalars), np.nanmax(scalars)] elif isinstance(clim, (int, float)): clim = [-clim, clim] if log_scale: if clim[0] <= 0: clim = [sys.float_info.min, clim[1]] if np.any(clim) and not rgb: self.scalar_range = clim[0], clim[1] if isinstance(cmap, pyvista.LookupTable): self.lookup_table = cmap self.scalar_range = self.lookup_table.scalar_range else: self.lookup_table.scalar_range = self.scalar_range # Set default map if cmap is None: cmap = pyvista.global_theme.cmap if self._theme is None else self._theme.cmap # have to add the attribute to pass it onward to some classes if isinstance(cmap, str): self._cmap = cmap if categories: if categories is True: n_colors = len(np.unique(scalars)) elif isinstance(categories, int): n_colors = categories self.lookup_table.apply_cmap(cmap, n_colors) # Set opactities if isinstance(opacity, np.ndarray) and not custom_opac: self.lookup_table.apply_opacity(opacity) if flip_scalars: self.lookup_table.values[:] = self.lookup_table.values[::-1] if custom_opac: # need to round the colors here since we're # directly displaying the colors hue = normalize(scalars, minimum=clim[0], maximum=clim[1]) scalars = np.round(hue * n_colors) / n_colors scalars = get_cmap_safe(cmap)(scalars) * 255 scalars[:, -1] *= opacity scalars = scalars.astype(np.uint8) # configure the lookup table if nan_color: self.lookup_table.nan_color = nan_color if above_color: self.lookup_table.above_range_color = above_color scalar_bar_args.setdefault('above_label', 'above') if below_color: self.lookup_table.below_range_color = below_color scalar_bar_args.setdefault('below_label', 'below') if isinstance(annotations, dict): self.lookup_table.annotations = annotations self.lookup_table.log_scale = log_scale self._configure_scalars_mode( scalars, scalars_name, preference, rgb or custom_opac, ) if isinstance(self, PointGaussianMapper): self.as_rgba() @property def cmap(self) -> str | None: # numpydoc ignore=RT01 """Colormap assigned to this mapper.""" return self._cmap @property def resolve(self) -> str: """Set or return the global flag to avoid z-buffer resolution. A global flag that controls whether the coincident topology (e.g., a line on top of a polygon) is shifted to avoid z-buffer resolution (and hence rendering problems). If not off, there are two methods to choose from. `polygon_offset` uses graphics systems calls to shift polygons, lines, and points from each other. `shift_zbuffer` is a legacy method that is used to remap the z-buffer to distinguish vertices, lines, and polygons, but does not always produce acceptable results. You should only use the polygon_offset method (or none) at this point. Returns ------- str Global flag to avoid z-buffer resolution. Must be either `off`, `polygon_offset` or `shift_zbuffer`. Examples -------- >>> import pyvista as pv >>> from pyvista import examples >>> mesh = examples.download_tri_quadratic_hexahedron() >>> surface_sep = mesh.separate_cells().extract_surface( ... nonlinear_subdivision=4 ... ) >>> edges = surface_sep.extract_feature_edges() >>> surface = mesh.extract_surface(nonlinear_subdivision=4) >>> plotter = pv.Plotter() >>> _ = plotter.add_mesh( ... surface, smooth_shading=True, split_sharp_edges=True ... ) >>> actor = plotter.add_mesh(edges, color='k', line_width=3) >>> actor.mapper.resolve = "polygon_offset" >>> plotter.show() """ vtk_to_pv = { _vtk.VTK_RESOLVE_OFF: 'off', _vtk.VTK_RESOLVE_POLYGON_OFFSET: 'polygon_offset', _vtk.VTK_RESOLVE_SHIFT_ZBUFFER: 'shift_zbuffer', } return vtk_to_pv[self.GetResolveCoincidentTopology()] @resolve.setter def resolve(self, resolve): # numpydoc ignore=GL08 if resolve == 'off': self.SetResolveCoincidentTopologyToOff() elif resolve == 'polygon_offset': self.SetResolveCoincidentTopologyToPolygonOffset() elif resolve == 'shift_zbuffer': self.SetResolveCoincidentTopologyToShiftZBuffer() else: raise ValueError('Resolve must be either "off", "polygon_offset" or "shift_zbuffer"') def set_custom_opacity(self, opacity, color, n_colors, preference='point'): """Set custom opacity. Parameters ---------- opacity : numpy.ndarray Opacity array to color the dataset. Array length must match either the number of points or cells. color : pyvista.ColorLike The color to use with the opacity array. n_colors : int Number of colors to use. preference : str, default: 'point' Either ``'point'`` or ``'cell'``. Used when the number of cells matches the number of points. """ # Create a custom RGBA array to supply our opacity to if opacity.size == self.dataset.n_points: rgba = np.empty((self.dataset.n_points, 4), np.uint8) elif opacity.size == self.dataset.n_cells: rgba = np.empty((self.dataset.n_cells, 4), np.uint8) else: # pragma: no cover raise ValueError( f"Opacity array size ({opacity.size}) does not equal " f"the number of points ({self.dataset.n_points}) or the " f"number of cells ({self.dataset.n_cells}).", ) default_color = self._theme.color if self._theme is not None else pyvista.global_theme.color rgba[:, :-1] = Color(color, default_color=default_color).int_rgb rgba[:, -1] = np.around(opacity * 255) self.color_mode = 'direct' self.lookup_table.n_values = n_colors self._configure_scalars_mode(rgba, '', preference, True) def __repr__(self): """Representation of the mapper.""" mapper_attr = [ f'{type(self).__name__} ({hex(id(self))})', f' Scalar visibility: {self.scalar_visibility}', f' Scalar range: {self.scalar_range}', f' Interpolate before mapping: {self.interpolate_before_map}', f' Scalar map mode: {self.scalar_map_mode}', f' Color mode: {self.color_mode}', '', ] mapper_attr.append('Attached dataset:') mapper_attr.append(str(self.dataset)) return '\n'.join(mapper_attr) class DataSetMapper(_DataSetMapper, _vtk.vtkDataSetMapper): """Wrap _vtk.vtkDataSetMapper. Parameters ---------- dataset : pyvista.DataSet, optional Dataset to assign to this mapper. theme : pyvista.plotting.themes.Theme, optional Plot-specific theme. Examples -------- Create a mapper outside :class:`pyvista.Plotter` and assign it to an actor. >>> import pyvista as pv >>> mesh = pv.Cube() >>> mapper = pv.DataSetMapper(dataset=mesh) >>> actor = pv.Actor(mapper=mapper) >>> actor.plot() """ def __init__( self, dataset: pyvista.DataSet | None = None, theme: pyvista.themes.Theme | None = None, ): """Initialize this class.""" super().__init__(dataset=dataset, theme=theme) @no_new_attr class PointGaussianMapper(_DataSetMapper, _vtk.vtkPointGaussianMapper): """Wrap vtkPointGaussianMapper. Parameters ---------- theme : pyvista.Theme, optional The theme to be used. emissive : bool, optional Whether or not the point should appear emissive. Default is set by the theme's ``lighting_params.emissive``. scale_factor : float, default: 1.0 Scale factor applied to the point size. """ def __init__(self, theme=None, emissive=None, scale_factor=1.0) -> None: super().__init__(theme=theme) if emissive is None: emissive = self._theme.lighting_params.emissive self.emissive = emissive self.scale_factor = scale_factor @property def emissive(self) -> bool: # numpydoc ignore=RT01 """Set or return emissive. This treats points as emissive light sources. Two points that overlap will have their brightness combined. """ return bool(self.GetEmissive()) @emissive.setter def emissive(self, value: bool): # numpydoc ignore=GL08 self.SetEmissive(value) @property def scale_factor(self) -> float: # numpydoc ignore=RT01 """Set or return the scale factor. Ranges from 0 to 1. A value of 0 will cause the splats to be rendered as simple points. Defaults to 1.0. """ return self.GetScaleFactor() @scale_factor.setter def scale_factor(self, value: float): # numpydoc ignore=GL08 self.SetScaleFactor(value) @property def scale_array(self) -> str: # numpydoc ignore=RT01 """Set or return the name of the array used to scale the splats. Scalars used to scale the gaussian points. Accepts a string name of an array that is present on the mesh. Notes ----- Setting this automatically sets ``scale_factor = 1.0``. Examples -------- Plot spheres using `style='points_gaussian'` style and scale them by radius. >>> import numpy as np >>> import pyvista as pv >>> n_spheres = 1_000 >>> pos = np.random.random((n_spheres, 3)) >>> rad = np.random.random(n_spheres) * 0.01 >>> pdata = pv.PolyData(pos) >>> pdata['radius'] = rad >>> pl = pv.Plotter() >>> actor = pl.add_mesh( ... pdata, ... style='points_gaussian', ... emissive=False, ... render_points_as_spheres=True, ... ) >>> actor.mapper.scale_array = 'radius' >>> pl.show() """ return self.GetScaleArray() @scale_array.setter def scale_array(self, name: str): # numpydoc ignore=GL08 if not self.dataset: # pragma: no cover raise RuntimeError('Missing dataset.') if name not in self.dataset.point_data: available_arrays = ", ".join(self.dataset.point_data.keys()) raise KeyError( f'Point array "{name}" does not exist. ' f'Available point arrays are: {available_arrays}', ) self.scale_factor = 1.0 self.SetScaleArray(name) def use_circular_splat(self, opacity: float = 1.0): """Set the fragment shader code to create a circular splat. Parameters ---------- opacity : float, default: 1.0 Desired opacity between 0 and 1. Notes ----- This very close to ParaView's PointGaussianMapper, but uses opacity to modify the scale as the opacity cannot be set from the actor's property. """ self.SetSplatShaderCode( "//VTK::Color::Impl\n" "float dist = dot(offsetVCVSOutput.xy,offsetVCVSOutput.xy);\n" "if (dist > 1.0) {\n" " discard;\n" "} else {\n" f" float scale = ({opacity} - dist);\n" " ambientColor *= scale;\n" " diffuseColor *= scale;\n" "}\n", ) # maintain consistency with the default style self.scale_factor *= 1.5 def use_default_splat(self): """Clear the fragment shader and use the default splat.""" self.SetSplatShaderCode(None) self.scale_factor /= 1.5 def __repr__(self): """Representation of the Gaussian mapper.""" mapper_attr = [ f'{type(self).__name__} ({hex(id(self))})', f' Scalar visibility: {self.scalar_visibility}', f' Scalar range: {self.scalar_range}', f' Emissive: {self.emissive}', f' Scale Factor: {self.scale_factor}', f' Using custom splat: {self.GetSplatShaderCode() is None}', '', ] mapper_attr.append('Attached dataset:') mapper_attr.append(str(self.dataset)) return '\n'.join(mapper_attr) @abstract_class class _BaseVolumeMapper(_BaseMapper): """Volume mapper class to override methods and attributes for to volume mappers.""" def __init__(self, theme=None): """Initialize this class.""" super().__init__(theme=theme) self._lut = LookupTable() self._scalar_range = (0.0, 256.0) @property def interpolate_before_map(self): # numpydoc ignore=RT01 """Interpolate before map is not supported with volume mappers.""" return @interpolate_before_map.setter def interpolate_before_map(self, *args): # numpydoc ignore=GL08 pass @property def dataset(self): # numpydoc ignore=RT01 """Return or set the dataset assigned to this mapper.""" # GetInputAsDataSet unavailable on volume mappers return wrap(self.GetDataSetInput()) @dataset.setter def dataset( self, obj: pyvista.core.dataset.DataSet | _vtk.vtkAlgorithm | _vtk.vtkAlgorithmOutput, ): set_algorithm_input(self, obj) @property def lookup_table(self): # numpydoc ignore=GL08 # numpydoc ignore=RT01 return self._lut @lookup_table.setter def lookup_table(self, lut): # numpydoc ignore=GL08 self._lut = lut @property def scalar_range(self) -> tuple[float, float]: # numpydoc ignore=RT01 """Return or set the scalar range.""" return self._scalar_range @scalar_range.setter def scalar_range(self, clim): # numpydoc ignore=GL08 if self.lookup_table is not None: self.lookup_table.SetRange(*clim) self._scalar_range = tuple(clim) @property def blend_mode(self) -> str: # numpydoc ignore=RT01 """Return or set the blend mode. One of the following: * ``"composite"`` * ``"maximum"`` * ``"minimum"`` * ``"average"`` * ``"additive"`` Also accepts integer values corresponding to ``vtk.vtkVolumeMapper.BlendModes``. For example ``vtk.vtkVolumeMapper.COMPOSITE_BLEND``. """ value = self.GetBlendMode() mode = {0: 'composite', 1: 'maximum', 2: 'minimum', 3: 'average', 4: 'additive'}.get(value) if mode is None: # pragma: no cover raise NotImplementedError(f'Unsupported blend mode return value {value}') return mode @blend_mode.setter def blend_mode(self, value: str | int): # numpydoc ignore=GL08 if isinstance(value, int): self.SetBlendMode(value) elif isinstance(value, str): value = value.lower() if value in ['additive', 'add', 'sum']: self.SetBlendModeToAdditive() elif value in ['average', 'avg', 'average_intensity']: self.SetBlendModeToAverageIntensity() elif value in ['composite', 'comp']: self.SetBlendModeToComposite() elif value in ['maximum', 'max', 'maximum_intensity']: self.SetBlendModeToMaximumIntensity() elif value in ['minimum', 'min', 'minimum_intensity']: self.SetBlendModeToMinimumIntensity() else: raise ValueError( f'Blending mode {value!r} invalid. ' 'Please choose either "additive", ' '"composite", "minimum" or "maximum".', ) else: raise TypeError(f'`blend_mode` should be either an int or str, not `{type(value)}`') def __del__(self): self._lut = None class FixedPointVolumeRayCastMapper(_BaseVolumeMapper, _vtk.vtkFixedPointVolumeRayCastMapper): """Wrap _vtk.vtkFixedPointVolumeRayCastMapper.""" class GPUVolumeRayCastMapper(_BaseVolumeMapper, _vtk.vtkGPUVolumeRayCastMapper): """Wrap _vtk.vtkGPUVolumeRayCastMapper.""" class OpenGLGPUVolumeRayCastMapper(_BaseVolumeMapper, _vtk.vtkOpenGLGPUVolumeRayCastMapper): """Wrap _vtk.vtkOpenGLGPUVolumeRayCastMapper.""" class SmartVolumeMapper(_BaseVolumeMapper, _vtk.vtkSmartVolumeMapper): """Wrap _vtk.vtkSmartVolumeMapper.""" class UnstructuredGridVolumeRayCastMapper( _BaseVolumeMapper, _vtk.vtkUnstructuredGridVolumeRayCastMapper ): """Wrap _vtk.vtkUnstructuredGridVolumeMapper."""