Source code for napari.layers.shapes.shapes

import warnings
from contextlib import contextmanager
from copy import copy, deepcopy
from itertools import cycle
from typing import Dict, List, Tuple, Union

import numpy as np
from vispy.color import get_color_names

from ...utils.colormaps import Colormap, ValidColormapArg, ensure_colormap
from ...utils.colormaps.standardize_color import (
    hex_to_name,
    rgb_to_hex,
    transform_color,
)
from ...utils.events import Event
from ...utils.events.custom_types import Array
from ...utils.misc import ensure_iterable
from ...utils.translations import trans
from ..base import Layer, no_op
from ..utils.color_manager_utils import guess_continuous, map_property
from ..utils.color_transformations import (
    ColorType,
    normalize_and_broadcast_colors,
    transform_color_cycle,
    transform_color_with_defaults,
)
from ..utils.layer_utils import (
    coerce_current_properties,
    get_current_properties,
    prepare_properties,
)
from ..utils.text_manager import TextManager
from ._shape_list import ShapeList
from ._shapes_constants import (
    BACKSPACE,
    Box,
    ColorMode,
    Mode,
    ShapeType,
    shape_classes,
)
from ._shapes_mouse_bindings import (
    add_ellipse,
    add_line,
    add_path_polygon,
    add_path_polygon_creating,
    add_rectangle,
    finish_drawing_shape,
    highlight,
    select,
    vertex_insert,
    vertex_remove,
)
from ._shapes_utils import (
    create_box,
    extract_shape_type,
    get_default_shape_type,
    get_shape_ndim,
    number_of_shapes,
    validate_num_vertices,
)

DEFAULT_COLOR_CYCLE = np.array([[1, 0, 1, 1], [0, 1, 0, 1]])


_REV_SHAPE_HELP = {
    trans._('hold <space> to pan/zoom'): {
        Mode.VERTEX_INSERT,
        Mode.VERTEX_REMOVE,
        Mode.ADD_RECTANGLE,
        Mode.ADD_ELLIPSE,
        Mode.ADD_LINE,
    },
    trans._(
        'hold <space> to pan/zoom, press <esc>, or double click to finish drawing'
    ): {
        Mode.ADD_PATH,
        Mode.ADD_POLYGON,
    },
    trans._(
        'hold <space> to pan/zoom, press <{BACKSPACE}> to remove selected',
        BACKSPACE=BACKSPACE,
    ): {Mode.SELECT, Mode.DIRECT},
    trans._('enter a selection mode to edit shape properties'): {
        Mode.PAN_ZOOM
    },
}


# This avoid duplicating the trans._ help messages above
# as some modes have the same help.
# while most tooling will recognise identical messages,
# this can lead to human error.
_FWD_SHAPE_HELP = {}
for t, modes in _REV_SHAPE_HELP.items():
    for m in modes:
        _FWD_SHAPE_HELP[m] = t


[docs]class Shapes(Layer): """Shapes layer. Parameters ---------- data : list or array List of shape data, where each element is an (N, D) array of the N vertices of a shape in D dimensions. Can be an 3-dimensional array if each shape has the same number of vertices. ndim : int Number of dimensions for shapes. When data is not None, ndim must be D. An empty shapes layer can be instantiated with arbitrary ndim. properties : dict {str: array (N,)}, DataFrame Properties for each shape. Each property should be an array of length N, where N is the number of shapes. property_choices : dict {str: array (N,)} possible values for each property. text : str, dict Text to be displayed with the shapes. If text is set to a key in properties, the value of that property will be displayed. Multiple properties can be composed using f-string-like syntax (e.g., '{property_1}, {float_property:.2f}). A dictionary can be provided with keyword arguments to set the text values and display properties. See TextManager.__init__() for the valid keyword arguments. For example usage, see /napari/examples/add_shapes_with_text.py. shape_type : string or list String of shape shape_type, must be one of "{'line', 'rectangle', 'ellipse', 'path', 'polygon'}". If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. edge_width : float or list Thickness of lines and edges. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. edge_color : str, array-like If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. edge_color_cycle : np.ndarray, list Cycle of colors (provided as string name, RGB, or RGBA) to map to edge_color if a categorical attribute is used color the vectors. edge_colormap : str, napari.utils.Colormap Colormap to set edge_color if a continuous attribute is used to set face_color. edge_contrast_limits : None, (float, float) clims for mapping the property to a color map. These are the min and max value of the specified property that are mapped to 0 and 1, respectively. The default value is None. If set the none, the clims will be set to (property.min(), property.max()) face_color : str, array-like If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. face_color_cycle : np.ndarray, list Cycle of colors (provided as string name, RGB, or RGBA) to map to face_color if a categorical attribute is used color the vectors. face_colormap : str, napari.utils.Colormap Colormap to set face_color if a continuous attribute is used to set face_color. face_contrast_limits : None, (float, float) clims for mapping the property to a color map. These are the min and max value of the specified property that are mapped to 0 and 1, respectively. The default value is None. If set the none, the clims will be set to (property.min(), property.max()) z_index : int or list Specifier of z order priority. Shapes with higher z order are displayed ontop of others. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. name : str Name of the layer. metadata : dict Layer metadata. scale : tuple of float Scale factors for the layer. translate : tuple of float Translation values for the layer. rotate : float, 3-tuple of float, or n-D array. If a float convert into a 2D rotation matrix using that value as an angle. If 3-tuple convert into a 3D rotation matrix, using a yaw, pitch, roll convention. Otherwise assume an nD rotation. Angles are assumed to be in degrees. They can be converted from radians with np.degrees if needed. shear : 1-D array or n-D array Either a vector of upper triangular values, or an nD shear matrix with ones along the main diagonal. affine : n-D array or napari.utils.transforms.Affine (N+1, N+1) affine transformation matrix in homogeneous coordinates. The first (N, N) entries correspond to a linear transform and the final column is a length N translation vector and a 1 or a napari `Affine` transform object. Applied as an extra transform on top of the provided scale, rotate, and shear values. opacity : float Opacity of the layer visual, between 0.0 and 1.0. blending : str One of a list of preset blending modes that determines how RGB and alpha values of the layer visual get mixed. Allowed values are {'opaque', 'translucent', and 'additive'}. visible : bool Whether the layer visual is currently being displayed. cache : bool Whether slices of out-of-core datasets should be cached upon retrieval. Currently, this only applies to dask arrays. Attributes ---------- data : (N, ) list of array List of shape data, where each element is an (N, D) array of the N vertices of a shape in D dimensions. properties : dict {str: array (N,)}, DataFrame Properties for each shape. Each property should be an array of length N, where N is the number of shapes. text : str, dict Text to be displayed with the shapes. If text is set to a key in properties, the value of that property will be displayed. Multiple properties can be composed using f-string-like syntax (e.g., '{property_1}, {float_property:.2f}). For example usage, see /napari/examples/add_shapes_with_text.py. shape_type : (N, ) list of str Name of shape type for each shape. edge_color : str, array-like Color of the shape border. Numeric color values should be RGB(A). face_color : str, array-like Color of the shape face. Numeric color values should be RGB(A). edge_width : (N, ) list of float Edge width for each shape. z_index : (N, ) list of int z-index for each shape. current_edge_width : float Thickness of lines and edges of the next shape to be added or the currently selected shape. current_edge_color : str Color of the edge of the next shape to be added or the currently selected shape. current_face_color : str Color of the face of the next shape to be added or the currently selected shape. selected_data : set List of currently selected shapes. nshapes : int Total number of shapes. mode : Mode Interactive mode. The normal, default mode is PAN_ZOOM, which allows for normal interactivity with the canvas. The SELECT mode allows for entire shapes to be selected, moved and resized. The DIRECT mode allows for shapes to be selected and their individual vertices to be moved. The VERTEX_INSERT and VERTEX_REMOVE modes allow for individual vertices either to be added to or removed from shapes that are already selected. Note that shapes cannot be selected in this mode. The ADD_RECTANGLE, ADD_ELLIPSE, ADD_LINE, ADD_PATH, and ADD_POLYGON modes all allow for their corresponding shape type to be added. Notes ----- _data_dict : Dict of ShapeList Dictionary containing all the shape data indexed by slice tuple _data_view : ShapeList Object containing the currently viewed shape data. _selected_data_history : set Set of currently selected captured on press of <space>. _selected_data_stored : set Set of selected previously displayed. Used to prevent rerendering the same highlighted shapes when no data has changed. _selected_box : None | np.ndarray `None` if no shapes are selected, otherwise a 10x2 array of vertices of the interaction box. The first 8 points are the corners and midpoints of the box. The 9th point is the center of the box, and the last point is the location of the rotation handle that can be used to rotate the box. _drag_start : None | np.ndarray If a drag has been started and is in progress then a length 2 array of the initial coordinates of the drag. `None` otherwise. _drag_box : None | np.ndarray If a drag box is being created to select shapes then this is a 2x2 array of the two extreme corners of the drag. `None` otherwise. _drag_box_stored : None | np.ndarray If a drag box is being created to select shapes then this is a 2x2 array of the two extreme corners of the drag that have previously been rendered. `None` otherwise. Used to prevent rerendering the same drag box when no data has changed. _is_moving : bool Bool indicating if any shapes are currently being moved. _is_selecting : bool Bool indicating if a drag box is currently being created in order to select shapes. _is_creating : bool Bool indicating if any shapes are currently being created. _fixed_aspect : bool Bool indicating if aspect ratio of shapes should be preserved on resizing. _aspect_ratio : float Value of aspect ratio to be preserved if `_fixed_aspect` is `True`. _fixed_vertex : None | np.ndarray If a scaling or rotation is in progress then a length 2 array of the coordinates that are remaining fixed during the move. `None` otherwise. _fixed_index : int If a scaling or rotation is in progress then the index of the vertex of the bounding box that is remaining fixed during the move. `None` otherwise. _update_properties : bool Bool indicating if properties are to allowed to update the selected shapes when they are changed. Blocking this prevents circular loops when shapes are selected and the properties are changed based on that selection _allow_thumbnail_update : bool Flag set to true to allow the thumbnail to be updated. Blocking the thumbnail can be advantageous where responsiveness is critical. _clipboard : dict Dict of shape objects that are to be used during a copy and paste. _colors : list List of supported vispy color names. _vertex_size : float Size of the vertices of the shapes and bounding box in Canvas coordinates. _rotation_handle_length : float Length of the rotation handle of the bounding box in Canvas coordinates. _input_ndim : int Dimensions of shape data. _thumbnail_update_thresh : int If there are more than this number of shapes, the thumbnail won't update during interactive events _property_choices : dict {str: array (N,)} Possible values for the properties in Shapes.properties. """ _colors = get_color_names() _vertex_size = 10 _rotation_handle_length = 20 _highlight_color = (0, 0.6, 1) _highlight_width = 1.5 # If more shapes are present then they are randomly subsampled # in the thumbnail _max_shapes_thumbnail = 100 _drag_modes = { Mode.PAN_ZOOM: no_op, Mode.SELECT: select, Mode.DIRECT: select, Mode.VERTEX_INSERT: vertex_insert, Mode.VERTEX_REMOVE: vertex_remove, Mode.ADD_RECTANGLE: add_rectangle, Mode.ADD_ELLIPSE: add_ellipse, Mode.ADD_LINE: add_line, Mode.ADD_PATH: add_path_polygon, Mode.ADD_POLYGON: add_path_polygon, } _move_modes = { Mode.PAN_ZOOM: no_op, Mode.SELECT: highlight, Mode.DIRECT: highlight, Mode.VERTEX_INSERT: highlight, Mode.VERTEX_REMOVE: highlight, Mode.ADD_RECTANGLE: no_op, Mode.ADD_ELLIPSE: no_op, Mode.ADD_LINE: no_op, Mode.ADD_PATH: add_path_polygon_creating, Mode.ADD_POLYGON: add_path_polygon_creating, } _double_click_modes = { Mode.PAN_ZOOM: no_op, Mode.SELECT: no_op, Mode.DIRECT: no_op, Mode.VERTEX_INSERT: no_op, Mode.VERTEX_REMOVE: no_op, Mode.ADD_RECTANGLE: no_op, Mode.ADD_ELLIPSE: no_op, Mode.ADD_LINE: no_op, Mode.ADD_PATH: finish_drawing_shape, Mode.ADD_POLYGON: finish_drawing_shape, } _cursor_modes = { Mode.PAN_ZOOM: 'standard', Mode.SELECT: 'pointing', Mode.DIRECT: 'pointing', Mode.VERTEX_INSERT: 'cross', Mode.VERTEX_REMOVE: 'cross', Mode.ADD_RECTANGLE: 'cross', Mode.ADD_ELLIPSE: 'cross', Mode.ADD_LINE: 'cross', Mode.ADD_PATH: 'cross', Mode.ADD_POLYGON: 'cross', } _interactive_modes = { Mode.PAN_ZOOM, } def __init__( self, data=None, *, ndim=None, properties=None, property_choices=None, text=None, shape_type='rectangle', edge_width=1, edge_color='#777777', edge_color_cycle=None, edge_colormap='viridis', edge_contrast_limits=None, face_color='white', face_color_cycle=None, face_colormap='viridis', face_contrast_limits=None, z_index=0, name=None, metadata=None, scale=None, translate=None, rotate=None, shear=None, affine=None, opacity=0.7, blending='translucent', visible=True, cache=True, experimental_clipping_planes=None, ): if data is None: if ndim is None: ndim = 2 data = np.empty((0, 0, ndim)) else: data, shape_type = extract_shape_type(data, shape_type) data_ndim = get_shape_ndim(data) if ndim is not None and ndim != data_ndim: raise ValueError( trans._( "Shape dimensions must be equal to ndim", deferred=True, ) ) ndim = data_ndim super().__init__( data, ndim=ndim, name=name, metadata=metadata, scale=scale, translate=translate, rotate=rotate, shear=shear, affine=affine, opacity=opacity, blending=blending, visible=visible, cache=cache, experimental_clipping_planes=experimental_clipping_planes, ) self.events.add( mode=Event, edge_width=Event, edge_color=Event, face_color=Event, properties=Event, current_edge_color=Event, current_face_color=Event, current_properties=Event, highlight=Event, ) # Flag set to false to block thumbnail refresh self._allow_thumbnail_update = True self._display_order_stored = [] self._ndisplay_stored = self._ndisplay self._properties, self._property_choices = prepare_properties( properties, property_choices, num_data=len(data) ) # make the text if text is None or isinstance(text, (list, np.ndarray, str)): self._text = TextManager(text, len(data), self.properties) elif isinstance(text, dict): copied_text = deepcopy(text) copied_text['properties'] = self.properties copied_text['n_text'] = len(data) self._text = TextManager(**copied_text) else: raise TypeError( trans._( 'text should be a string, array, or dict', deferred=True, ) ) # The following shape properties are for the new shapes that will # be drawn. Each shape has a corresponding property with the # value for itself if np.isscalar(edge_width): self._current_edge_width = edge_width else: self._current_edge_width = 1 self._data_view = ShapeList(ndisplay=self._ndisplay) self._data_view.slice_key = np.array(self._slice_indices)[ list(self._dims_not_displayed) ] self._value = (None, None) self._value_stored = (None, None) self._moving_value = (None, None) self._selected_data = set() self._selected_data_stored = set() self._selected_data_history = set() self._selected_box = None self._drag_start = None self._fixed_vertex = None self._fixed_aspect = False self._aspect_ratio = 1 self._is_moving = False # _moving_coordinates are needed for fixing aspect ratio during # a resize, it stores the last pointer coordinate value that happened # during a mouse move to that pressing/releasing shift # can trigger a redraw of the shape with a fixed aspect ratio. self._moving_coordinates = None self._fixed_index = 0 self._is_selecting = False self._drag_box = None self._drag_box_stored = None self._is_creating = False self._clipboard = {} # change mode once to trigger the # Mode setting logic self._mode = Mode.SELECT self.mode = Mode.PAN_ZOOM self._status = self.mode self._init_shapes( data, shape_type=shape_type, edge_width=edge_width, edge_color=edge_color, edge_color_cycle=edge_color_cycle, edge_colormap=edge_colormap, edge_contrast_limits=edge_contrast_limits, face_color=face_color, face_color_cycle=face_color_cycle, face_colormap=face_colormap, face_contrast_limits=face_contrast_limits, z_index=z_index, ) # set the current_* properties if len(data) > 0: self._current_edge_color = self.edge_color[-1] self._current_face_color = self.face_color[-1] elif len(data) == 0 and len(self.properties) > 0: self._initialize_current_color_for_empty_layer(edge_color, 'edge') self._initialize_current_color_for_empty_layer(face_color, 'face') elif len(data) == 0 and len(self.properties) == 0: self._current_edge_color = transform_color_with_defaults( num_entries=1, colors=edge_color, elem_name="edge_color", default="black", ) self._current_face_color = transform_color_with_defaults( num_entries=1, colors=face_color, elem_name="face_color", default="black", ) self.current_properties = get_current_properties( self._properties, self._property_choices, len(data) ) # Trigger generation of view slice and thumbnail self._update_dims() def _initialize_current_color_for_empty_layer( self, color: ColorType, attribute: str ): """Initialize current_{edge,face}_color when starting with empty layer. Parameters ---------- color : (N, 4) array or str The value for setting edge or face_color attribute : str in {'edge', 'face'} The name of the attribute to set the color of. Should be 'edge' for edge_color or 'face' for face_color. """ color_mode = getattr(self, f'_{attribute}_color_mode') if color_mode == ColorMode.DIRECT: curr_color = transform_color_with_defaults( num_entries=1, colors=color, elem_name=f'{attribute}_color', default="white", ) elif color_mode == ColorMode.CYCLE: color_cycle = getattr(self, f'_{attribute}_color_cycle') curr_color = transform_color(next(color_cycle)) # add the new color cycle mapping color_property = getattr(self, f'_{attribute}_color_property') prop_value = self._property_choices[color_property][0] color_cycle_map = getattr(self, f'{attribute}_color_cycle_map') color_cycle_map[prop_value] = np.squeeze(curr_color) setattr(self, f'{attribute}_color_cycle_map', color_cycle_map) elif color_mode == ColorMode.COLORMAP: color_property = getattr(self, f'_{attribute}_color_property') prop_value = self._property_choices[color_property][0] colormap = getattr(self, f'{attribute}_colormap') contrast_limits = getattr(self, f'_{attribute}_contrast_limits') curr_color, _ = map_property( prop=prop_value, colormap=colormap, contrast_limits=contrast_limits, ) setattr(self, f'_current_{attribute}_color', curr_color) @property def data(self): """list: Each element is an (N, D) array of the vertices of a shape.""" return self._data_view.data @data.setter def data(self, data): self._finish_drawing() data, shape_type = extract_shape_type(data) n_new_shapes = number_of_shapes(data) # not given a shape_type through data if shape_type is None: shape_type = self.shape_type edge_widths = self._data_view.edge_widths edge_color = self._data_view.edge_color face_color = self._data_view.face_color z_indices = self._data_view.z_indices # fewer shapes, trim attributes if self.nshapes > n_new_shapes: shape_type = shape_type[:n_new_shapes] edge_widths = edge_widths[:n_new_shapes] z_indices = z_indices[:n_new_shapes] edge_color = edge_color[:n_new_shapes] face_color = face_color[:n_new_shapes] # more shapes, add attributes elif self.nshapes < n_new_shapes: n_shapes_difference = n_new_shapes - self.nshapes shape_type = ( shape_type + [get_default_shape_type(shape_type)] * n_shapes_difference ) edge_widths = edge_widths + [1] * n_shapes_difference z_indices = z_indices + [0] * n_shapes_difference edge_color = np.concatenate( ( edge_color, self._get_new_shape_color(n_shapes_difference, 'edge'), ) ) face_color = np.concatenate( ( face_color, self._get_new_shape_color(n_shapes_difference, 'face'), ) ) self._data_view = ShapeList() self.add( data, shape_type=shape_type, edge_width=edge_widths, edge_color=edge_color, face_color=face_color, z_index=z_indices, ) self._update_dims() self.events.data(value=self.data) self._set_editable() def _on_selection(self, selected: bool): # this method is slated for removal. don't add anything new. if not selected: self._finish_drawing() @property def properties(self) -> Dict[str, np.ndarray]: """dict {str: np.ndarray (N,)}, DataFrame: Annotations for each shape""" return self._properties @properties.setter def properties(self, properties: Dict[str, Array]): self._properties, self._property_choices = prepare_properties( properties, self._property_choices, num_data=len(self.data) ) if self._face_color_property and ( self._face_color_property not in self._properties ): self._face_color_property = '' warnings.warn( trans._( 'property used for face_color dropped', deferred=True, ), RuntimeWarning, ) if self._edge_color_property and ( self._edge_color_property not in self._properties ): self._edge_color_property = '' warnings.warn( trans._( 'property used for edge_color dropped', deferred=True, ), RuntimeWarning, ) if self.text.values is not None: self.refresh_text() self.events.properties() @property def property_choices(self) -> Dict[str, np.ndarray]: return self._property_choices def _get_ndim(self): """Determine number of dimensions of the layer.""" if self.nshapes == 0: ndim = self.ndim else: ndim = self.data[0].shape[1] return ndim @property def _extent_data(self) -> np.ndarray: """Extent of layer in data coordinates. Returns ------- extent_data : array, shape (2, D) """ if len(self.data) == 0: extrema = np.full((2, self.ndim), np.nan) else: maxs = np.max([np.max(d, axis=0) for d in self.data], axis=0) mins = np.min([np.min(d, axis=0) for d in self.data], axis=0) extrema = np.vstack([mins, maxs]) return extrema @property def nshapes(self): """int: Total number of shapes.""" return len(self._data_view.shapes) @property def current_edge_width(self): """float: Width of shape edges including lines and paths.""" return self._current_edge_width @current_edge_width.setter def current_edge_width(self, edge_width): self._current_edge_width = edge_width if self._update_properties: for i in self.selected_data: self._data_view.update_edge_width(i, edge_width) self.events.edge_width() @property def current_edge_color(self): """str: color of shape edges including lines and paths.""" hex_ = rgb_to_hex(self._current_edge_color)[0] return hex_to_name.get(hex_, hex_) @current_edge_color.setter def current_edge_color(self, edge_color): self._current_edge_color = transform_color(edge_color) if self._update_properties: for i in self.selected_data: self._data_view.update_edge_color(i, self._current_edge_color) self.events.edge_color() self._update_thumbnail() self.events.current_edge_color() @property def current_face_color(self): """str: color of shape faces.""" hex_ = rgb_to_hex(self._current_face_color)[0] return hex_to_name.get(hex_, hex_) @current_face_color.setter def current_face_color(self, face_color): self._current_face_color = transform_color(face_color) if self._update_properties: for i in self.selected_data: self._data_view.update_face_color(i, self._current_face_color) self.events.face_color() self._update_thumbnail() self.events.current_face_color() @property def current_properties(self) -> Dict[str, np.ndarray]: """dict{str: np.ndarray(1,)}: properties for the next added shape.""" return self._current_properties @current_properties.setter def current_properties(self, current_properties): self._current_properties = coerce_current_properties( current_properties ) if ( self._update_properties and len(self.selected_data) > 0 and self._mode in [Mode.SELECT, Mode.PAN_ZOOM] ): props = self.properties for k in props: props[k][list(self.selected_data)] = current_properties[k] self.properties = props self.refresh_colors() self.events.current_properties() @property def shape_type(self): """list of str: name of shape type for each shape.""" return self._data_view.shape_types @shape_type.setter def shape_type(self, shape_type): self._finish_drawing() new_data_view = ShapeList() shape_inputs = zip( self._data_view.data, ensure_iterable(shape_type), self._data_view.edge_widths, self._data_view.edge_color, self._data_view.face_color, self._data_view.z_indices, ) self._add_shapes_to_view(shape_inputs, new_data_view) self._data_view = new_data_view self._update_dims() @property def edge_color(self): """(N x 4) np.ndarray: Array of RGBA face colors for each shape""" return self._data_view.edge_color @edge_color.setter def edge_color(self, edge_color): self._set_color(edge_color, 'edge') self.events.edge_color() self._update_thumbnail() @property def edge_color_cycle(self) -> np.ndarray: """Union[list, np.ndarray] : Color cycle for edge_color. Can be a list of colors defined by name, RGB or RGBA """ return self._edge_color_cycle_values @edge_color_cycle.setter def edge_color_cycle(self, edge_color_cycle: Union[list, np.ndarray]): self._set_color_cycle(edge_color_cycle, 'edge') @property def edge_colormap(self) -> Tuple[str, Colormap]: """Return the colormap to be applied to a property to get the edge color. Returns ------- colormap : napari.utils.Colormap The Colormap object. """ return self._edge_colormap @edge_colormap.setter def edge_colormap(self, colormap: ValidColormapArg): self._edge_colormap = ensure_colormap(colormap) @property def edge_contrast_limits(self) -> Tuple[float, float]: """None, (float, float): contrast limits for mapping the edge_color colormap property to 0 and 1 """ return self._edge_contrast_limits @edge_contrast_limits.setter def edge_contrast_limits( self, contrast_limits: Union[None, Tuple[float, float]] ): self._edge_contrast_limits = contrast_limits @property def edge_color_mode(self) -> str: """str: Edge color setting mode DIRECT (default mode) allows each shape color to be set arbitrarily CYCLE allows the color to be set via a color cycle over an attribute COLORMAP allows color to be set via a color map over an attribute """ return str(self._edge_color_mode) @edge_color_mode.setter def edge_color_mode(self, edge_color_mode: Union[str, ColorMode]): self._set_color_mode(edge_color_mode, 'edge') @property def face_color(self): """(N x 4) np.ndarray: Array of RGBA face colors for each shape""" return self._data_view.face_color @face_color.setter def face_color(self, face_color): self._set_color(face_color, 'face') self.events.face_color() self._update_thumbnail() @property def face_color_cycle(self) -> np.ndarray: """Union[np.ndarray, cycle]: Color cycle for face_color Can be a list of colors defined by name, RGB or RGBA """ return self._face_color_cycle_values @face_color_cycle.setter def face_color_cycle(self, face_color_cycle: Union[np.ndarray, cycle]): self._set_color_cycle(face_color_cycle, 'face') @property def face_colormap(self) -> Tuple[str, Colormap]: """Return the colormap to be applied to a property to get the face color. Returns ------- colormap : napari.utils.Colormap The Colormap object. """ return self._face_colormap @face_colormap.setter def face_colormap(self, colormap: ValidColormapArg): self._face_colormap = ensure_colormap(colormap) @property def face_contrast_limits(self) -> Union[None, Tuple[float, float]]: """None, (float, float) : clims for mapping the face_color colormap property to 0 and 1 """ return self._face_contrast_limits @face_contrast_limits.setter def face_contrast_limits( self, contrast_limits: Union[None, Tuple[float, float]] ): self._face_contrast_limits = contrast_limits @property def face_color_mode(self) -> str: """str: Face color setting mode DIRECT (default mode) allows each shape color to be set arbitrarily CYCLE allows the color to be set via a color cycle over an attribute COLORMAP allows color to be set via a color map over an attribute """ return str(self._face_color_mode) @face_color_mode.setter def face_color_mode(self, face_color_mode): self._set_color_mode(face_color_mode, 'face') def _set_color_mode( self, color_mode: Union[ColorMode, str], attribute: str ): """Set the face_color_mode or edge_color_mode property Parameters ---------- color_mode : str, ColorMode The value for setting edge or face_color_mode. If color_mode is a string, it should be one of: 'direct', 'cycle', or 'colormap' attribute : str in {'edge', 'face'} The name of the attribute to set the color of. Should be 'edge' for edge_colo_moder or 'face' for face_color_mode. """ color_mode = ColorMode(color_mode) if color_mode == ColorMode.DIRECT: setattr(self, f'_{attribute}_color_mode', color_mode) elif color_mode in (ColorMode.CYCLE, ColorMode.COLORMAP): color_property = getattr(self, f'_{attribute}_color_property') if color_property == '': if self.properties: new_color_property = next(iter(self.properties)) setattr( self, f'_{attribute}_color_property', new_color_property, ) warnings.warn( trans._( '_{attribute}_color_property was not set, setting to: {new_color_property}', deferred=True, attribute=attribute, new_color_property=new_color_property, ) ) else: raise ValueError( trans._( 'There must be a valid Shapes.properties to use {color_mode}', deferred=True, color_mode=color_mode, ) ) # ColorMode.COLORMAP can only be applied to numeric properties color_property = getattr(self, f'_{attribute}_color_property') if (color_mode == ColorMode.COLORMAP) and not issubclass( self.properties[color_property].dtype.type, np.number ): raise TypeError( trans._( 'selected property must be numeric to use ColorMode.COLORMAP', deferred=True, ) ) setattr(self, f'_{attribute}_color_mode', color_mode) self.refresh_colors() def _set_color_cycle(self, color_cycle: np.ndarray, attribute: str): """Set the face_color_cycle or edge_color_cycle property Parameters ---------- color_cycle : (N, 4) or (N, 1) array The value for setting edge or face_color_cycle attribute : str in {'edge', 'face'} The name of the attribute to set the color of. Should be 'edge' for edge_color or 'face' for face_color. """ transformed_color_cycle, transformed_colors = transform_color_cycle( color_cycle=color_cycle, elem_name=f'{attribute}_color_cycle', default="white", ) setattr(self, f'_{attribute}_color_cycle_values', transformed_colors) setattr(self, f'_{attribute}_color_cycle', transformed_color_cycle) if self._update_properties is True: color_mode = getattr(self, f'_{attribute}_color_mode') if color_mode == ColorMode.CYCLE: self.refresh_colors(update_color_mapping=True) @property def edge_width(self): """list of float: edge width for each shape.""" return self._data_view.edge_widths @edge_width.setter def edge_width(self, width): """Set edge width of shapes using float or list of float. If list of float, must be of equal length to n shapes Parameters ---------- width : float or list of float width of all shapes, or each shape if list """ if isinstance(width, list): if not len(width) == self.nshapes: raise ValueError( trans._('Length of list does not match number of shapes') ) else: widths = width else: widths = [width for _ in range(self.nshapes)] for i, width in enumerate(widths): self._data_view.update_edge_width(i, width) @property def z_index(self): """list of int: z_index for each shape.""" return self._data_view.z_indices @z_index.setter def z_index(self, z_index): """Set z_index of shape using either int or list of int. When list of int is provided, must be of equal length to n shapes. Parameters ---------- z_index : int or list of int z-index of shapes """ if isinstance(z_index, list): if not len(z_index) == self.nshapes: raise ValueError( trans._('Length of list does not match number of shapes') ) else: z_indices = z_index else: z_indices = [z_index for _ in range(self.nshapes)] for i, z_idx in enumerate(z_indices): self._data_view.update_z_index(i, z_idx) @property def selected_data(self): """set: set of currently selected shapes.""" return self._selected_data @selected_data.setter def selected_data(self, selected_data): self._selected_data = set(selected_data) self._selected_box = self.interaction_box(self._selected_data) # Update properties based on selected shapes if len(selected_data) > 0: selected_data_indices = list(selected_data) selected_face_colors = self._data_view._face_color[ selected_data_indices ] face_colors = np.unique(selected_face_colors, axis=0) if len(face_colors) == 1: face_color = face_colors[0] with self.block_update_properties(): self.current_face_color = face_color selected_edge_colors = self._data_view._edge_color[ selected_data_indices ] edge_colors = np.unique(selected_edge_colors, axis=0) if len(edge_colors) == 1: edge_color = edge_colors[0] with self.block_update_properties(): self.current_edge_color = edge_color edge_width = list( {self._data_view.shapes[i].edge_width for i in selected_data} ) if len(edge_width) == 1: edge_width = edge_width[0] with self.block_update_properties(): self.current_edge_width = edge_width properties = {} for k, v in self.properties.items(): # pandas uses `object` as dtype for strings by default, which # combined with the axis argument breaks np.unique axis = 0 if v.ndim > 1 else None properties[k] = np.unique(v[selected_data_indices], axis=axis) n_unique_properties = np.array( [len(v) for v in properties.values()] ) if np.all(n_unique_properties == 1): with self.block_update_properties(): self.current_properties = properties def _set_color(self, color, attribute: str): """Set the face_color or edge_color property Parameters ---------- color : (N, 4) array or str The value for setting edge or face_color attribute : str in {'edge', 'face'} The name of the attribute to set the color of. Should be 'edge' for edge_color or 'face' for face_color. """ if self._is_color_mapped(color): if guess_continuous(self.properties[color]): setattr(self, f'_{attribute}_color_mode', ColorMode.COLORMAP) else: setattr(self, f'_{attribute}_color_mode', ColorMode.CYCLE) setattr(self, f'_{attribute}_color_property', color) self.refresh_colors() else: if len(self.data) > 0: transformed_color = transform_color_with_defaults( num_entries=len(self.data), colors=color, elem_name="face_color", default="white", ) colors = normalize_and_broadcast_colors( len(self.data), transformed_color ) else: colors = np.empty((0, 4)) setattr(self._data_view, f'{attribute}_color', colors) setattr(self, f'_{attribute}_color_mode', ColorMode.DIRECT) color_event = getattr(self.events, f'{attribute}_color') color_event()
[docs] def refresh_colors(self, update_color_mapping: bool = False): """Calculate and update face and edge colors if using a cycle or color map Parameters ---------- update_color_mapping : bool If set to True, the function will recalculate the color cycle map or colormap (whichever is being used). If set to False, the function will use the current color cycle map or color map. For example, if you are adding/modifying shapes and want them to be colored with the same mapping as the other shapes (i.e., the new shapes shouldn't affect the color cycle map or colormap), set update_color_mapping=False. Default value is False. """ self._refresh_color('face', update_color_mapping) self._refresh_color('edge', update_color_mapping)
def _refresh_color( self, attribute: str, update_color_mapping: bool = False ): """Calculate and update face or edge colors if using a cycle or color map Parameters ---------- attribute : str in {'edge', 'face'} The name of the attribute to set the color of. Should be 'edge' for edge_color or 'face' for face_color. update_color_mapping : bool If set to True, the function will recalculate the color cycle map or colormap (whichever is being used). If set to False, the function will use the current color cycle map or color map. For example, if you are adding/modifying shapes and want them to be colored with the same mapping as the other shapes (i.e., the new shapes shouldn't affect the color cycle map or colormap), set update_color_mapping=False. Default value is False. """ if self._update_properties: color_mode = getattr(self, f'_{attribute}_color_mode') if color_mode in [ColorMode.CYCLE, ColorMode.COLORMAP]: colors = self._map_color(attribute, update_color_mapping) setattr(self._data_view, f'{attribute}_color', colors) color_event = getattr(self.events, f'{attribute}_color') color_event() def _initialize_color(self, color, attribute: str, n_shapes: int): """Get the face/edge colors the Shapes layer will be initialized with Parameters ---------- color : (N, 4) array or str The value for setting edge or face_color attribute : str in {'edge', 'face'} The name of the attribute to set the color of. Should be 'edge' for edge_color or 'face' for face_color. Returns ------- init_colors : (N, 4) array or str The calculated values for setting edge or face_color """ if self._is_color_mapped(color): if guess_continuous(self.properties[color]): setattr(self, f'_{attribute}_color_mode', ColorMode.COLORMAP) else: setattr(self, f'_{attribute}_color_mode', ColorMode.CYCLE) setattr(self, f'_{attribute}_color_property', color) init_colors = self._map_color( attribute, update_color_mapping=False ) else: if n_shapes > 0: transformed_color = transform_color_with_defaults( num_entries=n_shapes, colors=color, elem_name="face_color", default="white", ) init_colors = normalize_and_broadcast_colors( n_shapes, transformed_color ) else: init_colors = np.empty((0, 4)) setattr(self, f'_{attribute}_color_mode', ColorMode.DIRECT) return init_colors def _map_color(self, attribute: str, update_color_mapping: bool = False): """Calculate the mapping for face or edge colors if using a cycle or color map Parameters ---------- attribute : str in {'edge', 'face'} The name of the attribute to set the color of. Should be 'edge' for edge_color or 'face' for face_color. update_color_mapping : bool If set to True, the function will recalculate the color cycle map or colormap (whichever is being used). If set to False, the function will use the current color cycle map or color map. For example, if you are adding/modifying shapes and want them to be colored with the same mapping as the other shapes (i.e., the new shapes shouldn't affect the color cycle map or colormap), set update_color_mapping=False. Default value is False. Returns ------- colors : (N, 4) array or str The calculated values for setting edge or face_color """ color_mode = getattr(self, f'_{attribute}_color_mode') if color_mode == ColorMode.CYCLE: color_property = getattr(self, f'_{attribute}_color_property') color_properties = self.properties[color_property] if update_color_mapping: color_cycle = getattr(self, f'_{attribute}_color_cycle') color_cycle_map = { k: np.squeeze(transform_color(c)) for k, c in zip(np.unique(color_properties), color_cycle) } setattr(self, f'{attribute}_color_cycle_map', color_cycle_map) else: # add properties if they are not in the colormap # and update_color_mapping==False color_cycle_map = getattr(self, f'{attribute}_color_cycle_map') color_cycle_keys = [*color_cycle_map] props_in_map = np.in1d(color_properties, color_cycle_keys) if not np.all(props_in_map): props_to_add = np.unique( color_properties[np.logical_not(props_in_map)] ) color_cycle = getattr(self, f'_{attribute}_color_cycle') for prop in props_to_add: color_cycle_map[prop] = np.squeeze( transform_color(next(color_cycle)) ) setattr( self, f'{attribute}_color_cycle_map', color_cycle_map, ) colors = np.array([color_cycle_map[x] for x in color_properties]) if len(colors) == 0: colors = np.empty((0, 4)) elif color_mode == ColorMode.COLORMAP: color_property = getattr(self, f'_{attribute}_color_property') color_properties = self.properties[color_property] if len(color_properties) > 0: contrast_limits = getattr(self, f'{attribute}_contrast_limits') colormap = getattr(self, f'{attribute}_colormap') if update_color_mapping or contrast_limits is None: colors, contrast_limits = map_property( prop=color_properties, colormap=colormap ) setattr( self, f'{attribute}_contrast_limits', contrast_limits, ) else: colors, _ = map_property( prop=color_properties, colormap=colormap, contrast_limits=contrast_limits, ) else: colors = np.empty((0, 4)) return colors def _get_new_shape_color(self, adding: int, attribute: str): """Get the color for the shape(s) to be added. Parameters ---------- adding : int the number of shapes that were added (and thus the number of color entries to add) attribute : str in {'edge', 'face'} The name of the attribute to set the color of. Should be 'edge' for edge_color_mode or 'face' for face_color_mode. Returns ------- new_colors : (N, 4) array (Nx4) RGBA array of colors for the N new shapes """ color_mode = getattr(self, f'_{attribute}_color_mode') if color_mode == ColorMode.DIRECT: current_face_color = getattr(self, f'_current_{attribute}_color') new_colors = np.tile(current_face_color, (adding, 1)) elif color_mode == ColorMode.CYCLE: property_name = getattr(self, f'_{attribute}_color_property') color_property_value = self.current_properties[property_name][0] # check if the new color property is in the cycle map # and add it if it is not color_cycle_map = getattr(self, f'{attribute}_color_cycle_map') color_cycle_keys = [*color_cycle_map] if color_property_value not in color_cycle_keys: color_cycle = getattr(self, f'_{attribute}_color_cycle') color_cycle_map[color_property_value] = np.squeeze( transform_color(next(color_cycle)) ) setattr(self, f'{attribute}_color_cycle_map', color_cycle_map) new_colors = np.tile( color_cycle_map[color_property_value], (adding, 1) ) elif color_mode == ColorMode.COLORMAP: property_name = getattr(self, f'_{attribute}_color_property') color_property_value = self.current_properties[property_name][0] colormap = getattr(self, f'{attribute}_colormap') contrast_limits = getattr(self, f'_{attribute}_contrast_limits') fc, _ = map_property( prop=color_property_value, colormap=colormap, contrast_limits=contrast_limits, ) new_colors = np.tile(fc, (adding, 1)) return new_colors def _is_color_mapped(self, color): """determines if the new color argument is for directly setting or cycle/colormap""" if isinstance(color, str): if color in self.properties: return True else: return False elif isinstance(color, (list, np.ndarray)): return False else: raise ValueError( trans._( 'face_color should be the name of a color, an array of colors, or the name of an property', deferred=True, ) ) def _get_state(self): """Get dictionary of layer state. Returns ------- state : dict Dictionary of layer state. """ state = self._get_base_state() state.update( { 'ndim': self.ndim, 'properties': self.properties, 'property_choices': self._property_choices, 'text': self.text.dict(), 'shape_type': self.shape_type, 'opacity': self.opacity, 'z_index': self.z_index, 'edge_width': self.edge_width, 'face_color': self.face_color, 'face_color_cycle': self.face_color_cycle, 'face_colormap': self.face_colormap.name, 'face_contrast_limits': self.face_contrast_limits, 'edge_color': self.edge_color, 'edge_color_cycle': self.edge_color_cycle, 'edge_colormap': self.edge_colormap.name, 'edge_contrast_limits': self.edge_contrast_limits, 'data': self.data, } ) return state @property def _indices_view(self): return np.where(self._data_view._displayed)[0] @property def _view_text(self) -> np.ndarray: """Get the values of the text elements in view Returns ------- text : (N x 1) np.ndarray Array of text strings for the N text elements in view """ return self.text.view_text(self._indices_view) @property def _view_text_coords(self) -> np.ndarray: """Get the coordinates of the text elements in view Returns ------- text_coords : (N x D) np.ndarray Array of coordinates for the N text elements in view """ # get the coordinates of the vertices for the shapes in view in_view_shapes_coords = [ self._data_view.data[i] for i in self._indices_view ] # get the coordinates for the dimensions being displayed sliced_in_view_coords = [ position[:, self._dims_displayed] for position in in_view_shapes_coords ] return self.text.compute_text_coords( sliced_in_view_coords, self._ndisplay ) @property def mode(self): """MODE: Interactive mode. The normal, default mode is PAN_ZOOM, which allows for normal interactivity with the canvas. The SELECT mode allows for entire shapes to be selected, moved and resized. The DIRECT mode allows for shapes to be selected and their individual vertices to be moved. The VERTEX_INSERT and VERTEX_REMOVE modes allow for individual vertices either to be added to or removed from shapes that are already selected. Note that shapes cannot be selected in this mode. The ADD_RECTANGLE, ADD_ELLIPSE, ADD_LINE, ADD_PATH, and ADD_POLYGON modes all allow for their corresponding shape type to be added. """ return str(self._mode) @mode.setter def mode(self, mode: Union[str, Mode]): old_mode = self._mode mode, changed = self._mode_setter_helper(mode, Mode) if not changed: return if mode.value not in Mode.keys(): raise ValueError( trans._( "Mode not recognized: {mode}", deferred=True, mode=mode ) ) old_mode = self._mode self._mode = mode self.help = _FWD_SHAPE_HELP[mode] draw_modes = { Mode.SELECT, Mode.DIRECT, Mode.VERTEX_INSERT, Mode.VERTEX_REMOVE, } self.events.mode(mode=mode) # don't update thumbnail on mode changes with self.block_thumbnail_update(): if not (mode in draw_modes and old_mode in draw_modes): # Shapes._finish_drawing() calls Shapes.refresh() self._finish_drawing() else: self.refresh() def _set_editable(self, editable=None): """Set editable mode based on layer properties.""" if editable is None: if self._ndisplay == 3: self.editable = False else: self.editable = True if not self.editable: self.mode = Mode.PAN_ZOOM
[docs] def add_rectangles( self, data, *, edge_width=None, edge_color=None, face_color=None, z_index=None, ): """Add rectangles to the current layer. Parameters ---------- data : Array | List[Array] List of rectangle data where each element is a (4, D) array of 4 vertices in D dimensions, or a (2, D) array of 2 vertices in D dimensions, where the vertices are top-left and bottom-right corners. Can be a 3-dimensional array for multiple shapes, or list of 2 or 4 vertices for a single shape. edge_width : float | list thickness of lines and edges. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. edge_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. face_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. z_index : int | list Specifier of z order priority. Shapes with higher z order are displayed ontop of others. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. """ # rectangles can have either 4 vertices or (top left, bottom right) valid_vertices_per_shape = (2, 4) validate_num_vertices( data, 'rectangle', valid_vertices=valid_vertices_per_shape ) self.add( data, shape_type='rectangle', edge_width=edge_width, edge_color=edge_color, face_color=face_color, z_index=z_index, )
[docs] def add_ellipses( self, data, *, edge_width=None, edge_color=None, face_color=None, z_index=None, ): """Add ellipses to the current layer. Parameters ---------- data : Array | List[Array] List of ellipse data where each element is a (4, D) array of 4 vertices in D dimensions representing a bounding box, or a (2, D) array of center position and radii magnitudes in D dimensions. Can be a 3-dimensional array for multiple shapes, or list of 2 or 4 vertices for a single shape. edge_width : float | list thickness of lines and edges. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. edge_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. face_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. z_index : int | list Specifier of z order priority. Shapes with higher z order are displayed ontop of others. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. """ valid_elem_per_shape = (2, 4) validate_num_vertices( data, 'ellipse', valid_vertices=valid_elem_per_shape ) self.add( data, shape_type='ellipse', edge_width=edge_width, edge_color=edge_color, face_color=face_color, z_index=z_index, )
[docs] def add_polygons( self, data, *, edge_width=None, edge_color=None, face_color=None, z_index=None, ): """Add polygons to the current layer. Parameters ---------- data : Array | List[Array] List of polygon data where each element is a (V, D) array of V vertices in D dimensions representing a polygon. Can be a 3-dimensional array if polygons have same number of vertices, or a list of V vertices for a single polygon. edge_width : float | list thickness of lines and edges. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. edge_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. face_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. z_index : int | list Specifier of z order priority. Shapes with higher z order are displayed ontop of others. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. """ min_vertices = 3 validate_num_vertices(data, 'polygon', min_vertices=min_vertices) self.add( data, shape_type='polygon', edge_width=edge_width, edge_color=edge_color, face_color=face_color, z_index=z_index, )
[docs] def add_lines( self, data, *, edge_width=None, edge_color=None, face_color=None, z_index=None, ): """Add lines to the current layer. Parameters ---------- data : Array | List[Array] List of line data where each element is a (2, D) array of 2 vertices in D dimensions representing a line. Can be a 3-dimensional array for multiple shapes, or list of 2 vertices for a single shape. edge_width : float | list thickness of lines and edges. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. edge_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. face_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. z_index : int | list Specifier of z order priority. Shapes with higher z order are displayed ontop of others. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. """ valid_vertices_per_line = (2,) validate_num_vertices( data, 'line', valid_vertices=valid_vertices_per_line ) self.add( data, shape_type='line', edge_width=edge_width, edge_color=edge_color, face_color=face_color, z_index=z_index, )
[docs] def add_paths( self, data, *, edge_width=None, edge_color=None, face_color=None, z_index=None, ): """Add paths to the current layer. Parameters ---------- data : Array | List[Array] List of path data where each element is a (V, D) array of V vertices in D dimensions representing a path. Can be a 3-dimensional array if all paths have same number of vertices, or a list of V vertices for a single path. edge_width : float | list thickness of lines and edges. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. edge_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. face_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. z_index : int | list Specifier of z order priority. Shapes with higher z order are displayed ontop of others. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. """ min_vertices_per_path = 2 validate_num_vertices(data, 'path', min_vertices=min_vertices_per_path) self.add( data, shape_type='path', edge_width=edge_width, edge_color=edge_color, face_color=face_color, z_index=z_index, )
[docs] def add( self, data, *, shape_type='rectangle', edge_width=None, edge_color=None, face_color=None, z_index=None, ): """Add shapes to the current layer. Parameters ---------- data : Array | Tuple(Array,str) | List[Array | Tuple(Array, str)] | Tuple(List[Array], str) List of shape data, where each element is either an (N, D) array of the N vertices of a shape in D dimensions or a tuple containing an array of the N vertices and the shape_type string. When a shape_type is present, it overrides keyword arg shape_type. Can be an 3-dimensional array if each shape has the same number of vertices. shape_type : string | list String of shape shape_type, must be one of "{'line', 'rectangle', 'ellipse', 'path', 'polygon'}". If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. Overridden by data shape_type, if present. edge_width : float | list thickness of lines and edges. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. edge_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. face_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. z_index : int | list Specifier of z order priority. Shapes with higher z order are displayed ontop of others. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. """ data, shape_type = extract_shape_type(data, shape_type) if edge_width is None: edge_width = self.current_edge_width n_new_shapes = number_of_shapes(data) if edge_color is None: edge_color = self._get_new_shape_color( n_new_shapes, attribute='edge' ) if face_color is None: face_color = self._get_new_shape_color( n_new_shapes, attribute='face' ) if self._data_view is not None: z_index = z_index or max(self._data_view._z_index, default=-1) + 1 else: z_index = z_index or 0 if n_new_shapes > 0: if len(self.properties) > 0: first_prop_key = next(iter(self.properties)) n_prop_values = len(self.properties[first_prop_key]) else: n_prop_values = 0 total_shapes = n_new_shapes + self.nshapes if total_shapes > n_prop_values: n_props_to_add = total_shapes - n_prop_values for k in self.properties: new_property = np.repeat( self.current_properties[k], n_props_to_add, axis=0 ) self.properties[k] = np.concatenate( (self.properties[k], new_property), axis=0 ) self.text.add(self.current_properties, n_props_to_add) if total_shapes < n_prop_values: for k in self.properties: self.properties[k] = self.properties[k][:total_shapes] n_props_to_remove = n_prop_values - total_shapes indices_to_remove = np.arange(n_prop_values)[ -n_props_to_remove: ] self.text.remove(indices_to_remove) self._add_shapes( data, shape_type=shape_type, edge_width=edge_width, edge_color=edge_color, face_color=face_color, z_index=z_index, ) self.events.data(value=self.data)
def _init_shapes( self, data, *, shape_type='rectangle', edge_width=None, edge_color=None, edge_color_cycle, edge_colormap, edge_contrast_limits, face_color=None, face_color_cycle, face_colormap, face_contrast_limits, z_index=None, ): """Add shapes to the data view. Parameters ---------- data : Array | Tuple(Array,str) | List[Array | Tuple(Array, str)] | Tuple(List[Array], str) List of shape data, where each element is either an (N, D) array of the N vertices of a shape in D dimensions or a tuple containing an array of the N vertices and the shape_type string. When a shape_type is present, it overrides keyword arg shape_type. Can be an 3-dimensional array if each shape has the same number of vertices. shape_type : string | list String of shape shape_type, must be one of "{'line', 'rectangle', 'ellipse', 'path', 'polygon'}". If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. Overriden by data shape_type, if present. edge_width : float | list thickness of lines and edges. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. edge_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. face_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. z_index : int | list Specifier of z order priority. Shapes with higher z order are displayed ontop of others. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. """ n_shapes = number_of_shapes(data) with self.block_update_properties(): self._edge_color_property = '' self.edge_color_cycle_map = {} self.edge_colormap = edge_colormap self._edge_contrast_limits = edge_contrast_limits if edge_color_cycle is None: edge_color_cycle = deepcopy(DEFAULT_COLOR_CYCLE) self.edge_color_cycle = edge_color_cycle edge_color = self._initialize_color( edge_color, attribute='edge', n_shapes=n_shapes ) self._face_color_property = '' self.face_color_cycle_map = {} self.face_colormap = face_colormap self._face_contrast_limits = face_contrast_limits if face_color_cycle is None: face_color_cycle = deepcopy(DEFAULT_COLOR_CYCLE) self.face_color_cycle = face_color_cycle face_color = self._initialize_color( face_color, attribute='face', n_shapes=n_shapes ) with self.block_thumbnail_update(): self._add_shapes( data, shape_type=shape_type, edge_width=edge_width, edge_color=edge_color, face_color=face_color, z_index=z_index, z_refresh=False, ) self._data_view._update_z_order() self.refresh_colors() def _add_shapes( self, data, *, shape_type='rectangle', edge_width=None, edge_color=None, face_color=None, z_index=None, z_refresh=True, ): """Add shapes to the data view. Parameters ---------- data : Array | Tuple(Array,str) | List[Array | Tuple(Array, str)] | Tuple(List[Array], str) List of shape data, where each element is either an (N, D) array of the N vertices of a shape in D dimensions or a tuple containing an array of the N vertices and the shape_type string. When a shape_type is present, it overrides keyword arg shape_type. Can be an 3-dimensional array if each shape has the same number of vertices. shape_type : string | list String of shape shape_type, must be one of "{'line', 'rectangle', 'ellipse', 'path', 'polygon'}". If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. Overridden by data shape_type, if present. edge_width : float | list thickness of lines and edges. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. edge_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. face_color : str | tuple | list If string can be any color name recognized by vispy or hex value if starting with `#`. If array-like must be 1-dimensional array with 3 or 4 elements. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. z_index : int | list Specifier of z order priority. Shapes with higher z order are displayed on top of others. If a list is supplied it must be the same length as the length of `data` and each element will be applied to each shape otherwise the same value will be used for all shapes. z_refresh : bool If set to true, the mesh elements are reindexed with the new z order. When shape_index is provided, z_refresh will be overwritten to false, as the z indices will not change. When adding a batch of shapes, set to false and then call ShapesList._update_z_order() once at the end. """ if edge_width is None: edge_width = self.current_edge_width if edge_color is None: edge_color = self._current_edge_color if face_color is None: face_color = self._current_face_color if self._data_view is not None: z_index = z_index or max(self._data_view._z_index, default=-1) + 1 else: z_index = z_index or 0 if len(data) > 0: if np.array(data[0]).ndim == 1: # If a single array for a shape has been passed turn into list data = [data] # transform the colors transformed_ec = transform_color_with_defaults( num_entries=len(data), colors=edge_color, elem_name="edge_color", default="white", ) transformed_edge_color = normalize_and_broadcast_colors( len(data), transformed_ec ) transformed_fc = transform_color_with_defaults( num_entries=len(data), colors=face_color, elem_name="face_color", default="white", ) transformed_face_color = normalize_and_broadcast_colors( len(data), transformed_fc ) # Turn input arguments into iterables shape_inputs = zip( data, ensure_iterable(shape_type), ensure_iterable(edge_width), transformed_edge_color, transformed_face_color, ensure_iterable(z_index), ) self._add_shapes_to_view(shape_inputs, self._data_view) self._display_order_stored = copy(self._dims_order) self._ndisplay_stored = copy(self._ndisplay) self._update_dims() def _add_shapes_to_view(self, shape_inputs, data_view): """Build new shapes and add them to the _data_view""" for d, st, ew, ec, fc, z in shape_inputs: shape_cls = shape_classes[ShapeType(st)] shape = shape_cls( d, edge_width=ew, z_index=z, dims_order=self._dims_order, ndisplay=self._ndisplay, ) # Add shape data_view.add(shape, edge_color=ec, face_color=fc, z_refresh=False) data_view._update_z_order() @property def text(self) -> TextManager: """TextManager: The TextManager object containing the text properties""" return self._text @text.setter def text(self, text): self._text._set_text( text, n_text=len(self.data), properties=self.properties )
[docs] def refresh_text(self): """Refresh the text values. This is generally used if the properties were updated without changing the data """ self.text.refresh_text(self.properties)
def _set_view_slice(self): """Set the view given the slicing indices.""" if not self._ndisplay == self._ndisplay_stored: self.selected_data = set() self._data_view.ndisplay = min(self.ndim, self._ndisplay) self._ndisplay_stored = copy(self._ndisplay) self._clipboard = {} if not self._dims_order == self._display_order_stored: self.selected_data = set() self._data_view.update_dims_order(self._dims_order) self._display_order_stored = copy(self._dims_order) # Clear clipboard if dimensions swap self._clipboard = {} slice_key = np.array(self._slice_indices)[ list(self._dims_not_displayed) ] if not np.all(slice_key == self._data_view.slice_key): self.selected_data = set() self._data_view.slice_key = slice_key
[docs] def interaction_box(self, index): """Create the interaction box around a shape or list of shapes. If a single index is passed then the boudning box will be inherited from that shapes interaction box. If list of indices is passed it will be computed directly. Parameters ---------- index : int | list Index of a single shape, or a list of shapes around which to construct the interaction box Returns ------- box : np.ndarray 10x2 array of vertices of the interaction box. The first 8 points are the corners and midpoints of the box in clockwise order starting in the upper-left corner. The 9th point is the center of the box, and the last point is the location of the rotation handle that can be used to rotate the box """ if isinstance(index, (list, np.ndarray, set)): if len(index) == 0: box = None elif len(index) == 1: box = copy(self._data_view.shapes[list(index)[0]]._box) else: indices = np.isin(self._data_view.displayed_index, list(index)) box = create_box(self._data_view.displayed_vertices[indices]) else: box = copy(self._data_view.shapes[index]._box) if box is not None: rot = box[Box.TOP_CENTER] length_box = np.linalg.norm( box[Box.BOTTOM_LEFT] - box[Box.TOP_LEFT] ) if length_box > 0: r = self._rotation_handle_length * self.scale_factor rot = ( rot - r * (box[Box.BOTTOM_LEFT] - box[Box.TOP_LEFT]) / length_box ) box = np.append(box, [rot], axis=0) return box
def _outline_shapes(self): """Find outlines of any selected or hovered shapes. Returns ------- vertices : None | np.ndarray Nx2 array of any vertices of outline or None triangles : None | np.ndarray Mx3 array of any indices of vertices for triangles of outline or None """ if self._value is not None and ( self._value[0] is not None or len(self.selected_data) > 0 ): if len(self.selected_data) > 0: index = list(self.selected_data) if self._value[0] is not None: if self._value[0] in index: pass else: index.append(self._value[0]) index.sort() else: index = self._value[0] centers, offsets, triangles = self._data_view.outline(index) vertices = centers + ( self.scale_factor * self._highlight_width * offsets ) vertices = vertices[:, ::-1] else: vertices = None triangles = None return vertices, triangles def _compute_vertices_and_box(self): """Compute location of highlight vertices and box for rendering. Returns ------- vertices : np.ndarray Nx2 array of any vertices to be rendered as Markers face_color : str String of the face color of the Markers edge_color : str String of the edge color of the Markers and Line for the box pos : np.ndarray Nx2 array of vertices of the box that will be rendered using a Vispy Line width : float Width of the box edge """ if len(self.selected_data) > 0: if self._mode == Mode.SELECT: # If in select mode just show the interaction boudning box # including its vertices and the rotation handle box = self._selected_box[Box.WITH_HANDLE] if self._value[0] is None: face_color = 'white' elif self._value[1] is None: face_color = 'white' else: face_color = self._highlight_color edge_color = self._highlight_color vertices = box[:, ::-1] # Use a subset of the vertices of the interaction_box to plot # the line around the edge pos = box[Box.LINE_HANDLE][:, ::-1] width = 1.5 elif self._mode in ( [ Mode.DIRECT, Mode.ADD_PATH, Mode.ADD_POLYGON, Mode.ADD_RECTANGLE, Mode.ADD_ELLIPSE, Mode.ADD_LINE, Mode.VERTEX_INSERT, Mode.VERTEX_REMOVE, ] ): # If in one of these mode show the vertices of the shape itself inds = np.isin( self._data_view.displayed_index, list(self.selected_data) ) vertices = self._data_view.displayed_vertices[inds][:, ::-1] # If currently adding path don't show box over last vertex if self._mode == Mode.ADD_PATH: vertices = vertices[:-1] if self._value[0] is None: face_color = 'white' elif self._value[1] is None: face_color = 'white' else: face_color = self._highlight_color edge_color = self._highlight_color pos = None width = 0 else: # Otherwise show nothing vertices = np.empty((0, 2)) face_color = 'white' edge_color = 'white' pos = None width = 0 elif self._is_selecting: # If currently dragging a selection box just show an outline of # that box vertices = np.empty((0, 2)) edge_color = self._highlight_color face_color = 'white' box = create_box(self._drag_box) width = 1.5 # Use a subset of the vertices of the interaction_box to plot # the line around the edge pos = box[Box.LINE][:, ::-1] else: # Otherwise show nothing vertices = np.empty((0, 2)) face_color = 'white' edge_color = 'white' pos = None width = 0 return vertices, face_color, edge_color, pos, width def _set_highlight(self, force=False): """Render highlights of shapes. Includes boundaries, vertices, interaction boxes, and the drag selection box when appropriate. Parameters ---------- force : bool Bool that forces a redraw to occur when `True` """ # Check if any shape or vertex ids have changed since last call if ( self.selected_data == self._selected_data_stored and np.all(self._value == self._value_stored) and np.all(self._drag_box == self._drag_box_stored) ) and not force: return self._selected_data_stored = copy(self.selected_data) self._value_stored = copy(self._value) self._drag_box_stored = copy(self._drag_box) self.events.highlight() def _finish_drawing(self, event=None): """Reset properties used in shape drawing.""" index = copy(self._moving_value[0]) self._is_moving = False self.selected_data = set() self._drag_start = None self._drag_box = None self._is_selecting = False self._fixed_vertex = None self._value = (None, None) self._moving_value = (None, None) if self._is_creating is True and self._mode == Mode.ADD_PATH: vertices = self._data_view.shapes[index].data if len(vertices) <= 2: self._data_view.remove(index) else: self._data_view.edit(index, vertices[:-1]) if self._is_creating is True and self._mode == Mode.ADD_POLYGON: vertices = self._data_view.shapes[index].data if len(vertices) <= 3: self._data_view.remove(index) else: self._data_view.edit(index, vertices[:-1]) self._is_creating = False self._update_dims()
[docs] @contextmanager def block_thumbnail_update(self): """Use this context manager to block thumbnail updates""" self._allow_thumbnail_update = False yield self._allow_thumbnail_update = True
def _update_thumbnail(self, event=None): """Update thumbnail with current shapes and colors.""" # don't update the thumbnail if dragging a shape if self._is_moving is False and self._allow_thumbnail_update is True: # calculate min vals for the vertices and pad with 0.5 # the offset is needed to ensure that the top left corner of the shapes # corresponds to the top left corner of the thumbnail de = self._extent_data offset = np.array([de[0, d] for d in self._dims_displayed]) + 0.5 # calculate range of values for the vertices and pad with 1 # padding ensures the entire shape can be represented in the thumbnail # without getting clipped shape = np.ceil( [de[1, d] - de[0, d] + 1 for d in self._dims_displayed] ).astype(int) zoom_factor = np.divide( self._thumbnail_shape[:2], shape[-2:] ).min() colormapped = self._data_view.to_colors( colors_shape=self._thumbnail_shape[:2], zoom_factor=zoom_factor, offset=offset[-2:], max_shapes=self._max_shapes_thumbnail, ) self.thumbnail = colormapped
[docs] def remove_selected(self): """Remove any selected shapes.""" index = list(self.selected_data) to_remove = sorted(index, reverse=True) for ind in to_remove: self._data_view.remove(ind) if len(index) > 0: for k in self.properties: self.properties[k] = np.delete( self.properties[k], index, axis=0 ) self.text.remove(index) self._data_view._edge_color = np.delete( self._data_view._edge_color, index, axis=0 ) self._data_view._face_color = np.delete( self._data_view._face_color, index, axis=0 ) self.selected_data = set() self._finish_drawing() self.events.data(value=self.data)
def _rotate_box(self, angle, center=[0, 0]): """Perform a rotation on the selected box. Parameters ---------- angle : float angle specifying rotation of shapes in degrees. center : list coordinates of center of rotation. """ theta = np.radians(angle) transform = np.array( [[np.cos(theta), np.sin(theta)], [-np.sin(theta), np.cos(theta)]] ) box = self._selected_box - center self._selected_box = box @ transform.T + center def _scale_box(self, scale, center=[0, 0]): """Perform a scaling on the selected box. Parameters ---------- scale : float, list scalar or list specifying rescaling of shape. center : list coordinates of center of rotation. """ if not isinstance(scale, (list, np.ndarray)): scale = [scale, scale] box = self._selected_box - center box = np.array(box * scale) if not np.all(box[Box.TOP_CENTER] == box[Box.HANDLE]): r = self._rotation_handle_length * self.scale_factor handle_vec = box[Box.HANDLE] - box[Box.TOP_CENTER] cur_len = np.linalg.norm(handle_vec) box[Box.HANDLE] = box[Box.TOP_CENTER] + r * handle_vec / cur_len self._selected_box = box + center def _transform_box(self, transform, center=[0, 0]): """Perform a linear transformation on the selected box. Parameters ---------- transform : np.ndarray 2x2 array specifying linear transform. center : list coordinates of center of rotation. """ box = self._selected_box - center box = box @ transform.T if not np.all(box[Box.TOP_CENTER] == box[Box.HANDLE]): r = self._rotation_handle_length * self.scale_factor handle_vec = box[Box.HANDLE] - box[Box.TOP_CENTER] cur_len = np.linalg.norm(handle_vec) box[Box.HANDLE] = box[Box.TOP_CENTER] + r * handle_vec / cur_len self._selected_box = box + center def _get_value(self, position): """Value of the data at a position in data coordinates. Parameters ---------- position : tuple Position in data coordinates. Returns ------- shape : int | None Index of shape if any that is at the coordinates. Returns `None` if no shape is found. vertex : int | None Index of vertex if any that is at the coordinates. Returns `None` if no vertex is found. """ if self._ndisplay == 3: return (None, None) if self._is_moving: return self._moving_value coord = [position[i] for i in self._dims_displayed] # Check selected shapes value = None selected_index = list(self.selected_data) if len(selected_index) > 0: if self._mode == Mode.SELECT: # Check if inside vertex of interaction box or rotation handle box = self._selected_box[Box.WITH_HANDLE] distances = abs(box - coord) # Get the vertex sizes sizes = self._vertex_size * self.scale_factor / 2 # Check if any matching vertices matches = np.all(distances <= sizes, axis=1).nonzero() if len(matches[0]) > 0: value = (selected_index[0], matches[0][-1]) elif self._mode in ( [Mode.DIRECT, Mode.VERTEX_INSERT, Mode.VERTEX_REMOVE] ): # Check if inside vertex of shape inds = np.isin(self._data_view.displayed_index, selected_index) vertices = self._data_view.displayed_vertices[inds] distances = abs(vertices - coord) # Get the vertex sizes sizes = self._vertex_size * self.scale_factor / 2 # Check if any matching vertices matches = np.all(distances <= sizes, axis=1).nonzero()[0] if len(matches) > 0: index = inds.nonzero()[0][matches[-1]] shape = self._data_view.displayed_index[index] vals, idx = np.unique( self._data_view.displayed_index, return_index=True ) shape_in_list = list(vals).index(shape) value = (shape, index - idx[shape_in_list]) if value is None: # Check if mouse inside shape shape = self._data_view.inside(coord) value = (shape, None) return value def _get_value_3d( self, start_point: np.ndarray, end_point: np.ndarray, dims_displayed: List[int], ) -> Tuple[Union[float, int], None]: """Get the layer data value along a ray Parameters ---------- start_point : np.ndarray The start position of the ray used to interrogate the data. end_point : np.ndarray The end position of the ray used to interrogate the data. dims_displayed : List[int] The indices of the dimensions currently displayed in the Viewer. Returns ------- value The data value along the supplied ray. vertex : None Index of vertex if any that is at the coordinates. Always returns `None`. """ value, _ = self._get_index_and_intersection( start_point=start_point, end_point=end_point, dims_displayed=dims_displayed, ) return (value, None) def _get_index_and_intersection( self, start_point: np.ndarray, end_point: np.ndarray, dims_displayed: List[int], ) -> Tuple[Union[float, int], None]: """Get the shape index and intersection point of the first shape (i.e., closest to start_point) along the specified 3D line segment. Note: this method is meant to be used for 3D intersection and returns (None, None) when used in 2D (i.e., len(dims_displayed) is 2). Parameters ---------- start_point : np.ndarray The start position of the ray used to interrogate the data in layer coordinates. end_point : np.ndarray The end position of the ray used to interrogate the data in layer coordinates. dims_displayed : List[int] The indices of the dimensions currently displayed in the Viewer. Returns ------- value The data value along the supplied ray. intersection_point : np.ndarray (n,) array containing the point where the ray intersects the first shape (i.e., the shape most in the foreground). The coordinate is in layer coordinates. """ if len(dims_displayed) == 3: if (start_point is not None) and (end_point is not None): # Get the normal vector of the click plane start_position_view = start_point[dims_displayed] end_position_view = end_point[dims_displayed] ray_direction = end_position_view - start_position_view ray_direction_normed = ray_direction / np.linalg.norm( ray_direction ) # step the start position back a little bit to be able to detect shapes # that contain the start_position start_position_view = ( start_position_view - 0.1 * ray_direction_normed ) value, intersection = self._data_view._inside_3d( start_position_view, ray_direction_normed ) # add the full nD coords to intersection intersection_point = start_point.copy() intersection_point[dims_displayed] = intersection else: value = None intersection_point = None else: value = None intersection_point = None return value, intersection_point
[docs] def get_index_and_intersection( self, position: np.ndarray, view_direction: np.ndarray, dims_displayed: List[int], ) -> Tuple[Union[float, int], None]: """Get the shape index and intersection point of the first shape (i.e., closest to start_point) "under" a mouse click. See examples/add_points_on_nD_shapes.py for example usage. Parameters ---------- position : tuple Position in either data or world coordinates. view_direction : Optional[np.ndarray] A unit vector giving the direction of the ray in nD world coordinates. The default value is None. dims_displayed : Optional[List[int]] A list of the dimensions currently being displayed in the viewer. The default value is None. Returns ------- value The data value along the supplied ray. intersection_point : np.ndarray (n,) array containing the point where the ray intersects the first shape (i.e., the shape most in the foreground). The coordinate is in layer coordinates. """ start_point, end_point = self.get_ray_intersections( position, view_direction, dims_displayed ) if (start_point is not None) and (end_point is not None): shape_index, intersection_point = self._get_index_and_intersection( start_point=start_point, end_point=end_point, dims_displayed=dims_displayed, ) else: shape_index = (None,) intersection_point = None return shape_index, intersection_point
[docs] def move_to_front(self): """Moves selected objects to be displayed in front of all others.""" if len(self.selected_data) == 0: return new_z_index = max(self._data_view._z_index) + 1 for index in self.selected_data: self._data_view.update_z_index(index, new_z_index) self.refresh()
[docs] def move_to_back(self): """Moves selected objects to be displayed behind all others.""" if len(self.selected_data) == 0: return new_z_index = min(self._data_view._z_index) - 1 for index in self.selected_data: self._data_view.update_z_index(index, new_z_index) self.refresh()
def _copy_data(self): """Copy selected shapes to clipboard.""" if len(self.selected_data) > 0: index = list(self.selected_data) self._clipboard = { 'data': [ deepcopy(self._data_view.shapes[i]) for i in self._selected_data ], 'edge_color': deepcopy(self._data_view._edge_color[index]), 'face_color': deepcopy(self._data_view._face_color[index]), 'properties': { k: deepcopy(v[index]) for k, v in self.properties.items() }, 'indices': self._slice_indices, } if len(self.text.values) == 0: self._clipboard['text'] = np.empty(0) else: self._clipboard['text'] = deepcopy(self.text.values[index]) else: self._clipboard = {} def _paste_data(self): """Paste any shapes from clipboard and then selects them.""" cur_shapes = self.nshapes if len(self._clipboard.keys()) > 0: # Calculate offset based on dimension shifts offset = [ self._slice_indices[i] - self._clipboard['indices'][i] for i in self._dims_not_displayed ] for k in self.properties: self.properties[k] = np.concatenate( (self.properties[k], self._clipboard['properties'][k]), axis=0, ) # Add new shape data for i, s in enumerate(self._clipboard['data']): shape = deepcopy(s) data = copy(shape.data) data[:, self._dims_not_displayed] = data[ :, self._dims_not_displayed ] + np.array(offset) shape.data = data face_color = self._clipboard['face_color'][i] edge_color = self._clipboard['edge_color'][i] self._data_view.add( shape, face_color=face_color, edge_color=edge_color ) if len(self._clipboard['text']) > 0: self.text.values = np.concatenate( (self.text.values, self._clipboard['text']), axis=0 ) self.selected_data = set( range(cur_shapes, cur_shapes + len(self._clipboard['data'])) ) self.move_to_front()
[docs] def to_masks(self, mask_shape=None): """Return an array of binary masks, one for each shape. Parameters ---------- mask_shape : np.ndarray | tuple | None tuple defining shape of mask to be generated. If non specified, takes the max of all the vertices Returns ------- masks : np.ndarray Array where there is one binary mask for each shape """ if mask_shape is None: # See https://github.com/napari/napari/issues/2778 # Point coordinates land on pixel centers. We want to find the # smallest shape that will hold the largest point in the data, # using rounding. mask_shape = np.round(self._extent_data[1]) + 1 mask_shape = np.ceil(mask_shape).astype('int') masks = self._data_view.to_masks(mask_shape=mask_shape) return masks
[docs] def to_labels(self, labels_shape=None): """Return an integer labels image. Parameters ---------- labels_shape : np.ndarray | tuple | None Tuple defining shape of labels image to be generated. If non specified, takes the max of all the vertiecs Returns ------- labels : np.ndarray Integer array where each value is either 0 for background or an integer up to N for points inside the shape at the index value - 1. For overlapping shapes z-ordering will be respected. """ if labels_shape is None: # See https://github.com/napari/napari/issues/2778 # Point coordinates land on pixel centers. We want to find the # smallest shape that will hold the largest point in the data, # using rounding. labels_shape = np.round(self._extent_data[1]) + 1 labels_shape = np.ceil(labels_shape).astype('int') labels = self._data_view.to_labels(labels_shape=labels_shape) return labels