import warnings
from contextlib import contextmanager
from copy import copy, deepcopy
from itertools import cycle
from typing import (
Any,
Callable,
ClassVar,
Optional,
Union,
)
import numpy as np
import numpy.typing as npt
import pandas as pd
from vispy.color import get_color_names
from napari.layers.base import Layer, no_op
from napari.layers.base._base_constants import ActionType
from napari.layers.base._base_mouse_bindings import (
highlight_box_handles,
transform_with_box,
)
from napari.layers.shapes._shape_list import ShapeList
from napari.layers.shapes._shapes_constants import (
Box,
ColorMode,
Mode,
ShapeType,
shape_classes,
)
from napari.layers.shapes._shapes_mouse_bindings import (
_set_highlight,
add_ellipse,
add_line,
add_path_polygon,
add_path_polygon_lasso,
add_rectangle,
finish_drawing_shape,
highlight,
polygon_creating,
select,
vertex_insert,
vertex_remove,
)
from napari.layers.shapes._shapes_utils import (
create_box,
extract_shape_type,
get_default_shape_type,
get_shape_ndim,
number_of_shapes,
rdp,
validate_num_vertices,
)
from napari.layers.utils.color_manager_utils import (
guess_continuous,
map_property,
)
from napari.layers.utils.color_transformations import (
normalize_and_broadcast_colors,
transform_color_cycle,
transform_color_with_defaults,
)
from napari.layers.utils.interactivity_utils import (
nd_line_segment_to_displayed_data_ray,
)
from napari.layers.utils.layer_utils import _FeatureTable, _unique_element
from napari.layers.utils.text_manager import TextManager
from napari.settings import get_settings
from napari.utils.colormaps import Colormap, ValidColormapArg, ensure_colormap
from napari.utils.colormaps.colormap_utils import ColorType
from napari.utils.colormaps.standardize_color import (
hex_to_name,
rgb_to_hex,
transform_color,
)
from napari.utils.events import Event
from napari.utils.events.custom_types import Array
from napari.utils.misc import ensure_iterable
from napari.utils.translations import trans
DEFAULT_COLOR_CYCLE = np.array([[1, 0, 1, 1], [0, 1, 0, 1]])
[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.
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.
axis_labels : tuple of str, optional
Dimension names of the layer data.
If not provided, axis_labels will be set to (..., 'axis -2', 'axis -1').
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'}.
cache : bool
Whether slices of out-of-core datasets should be cached upon retrieval.
Currently, this only applies to dask arrays.
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())
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.
experimental_clipping_planes : list of dicts, list of ClippingPlane, or ClippingPlaneList
Each dict defines a clipping plane in 3D in data coordinates.
Valid dictionary keys are {'position', 'normal', and 'enabled'}.
Values on the negative side of the normal are discarded if the plane is enabled.
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())
feature_defaults : dict[str, Any] or Dataframe-like
The default value of each feature in a table with one row.
features : dict[str, array-like] or Dataframe-like
Features table where each row corresponds to a shape and each column
is a feature.
metadata : dict
Layer metadata.
name : str
Name of the layer.
opacity : float
Opacity of the layer visual, between 0.0 and 1.0.
projection_mode : str
How data outside the viewed dimensions but inside the thick Dims slice will
be projected onto the viewed dimenions.
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.
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.
scale : tuple of float
Scale factors for the layer.
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.
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.
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.
translate : tuple of float
Translation values for the layer.
units : tuple of str or pint.Unit, optional
Units of the layer data in world coordinates.
If not provided, the default units are assumed to be pixels.
visible : bool
Whether the layer visual is currently being displayed.
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.
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.
axis_labels : tuple of str
Dimension names of the layer data.
features : Dataframe-like
Features table where each row corresponds to a shape and each column
is a feature.
feature_defaults : DataFrame-like
Stores the default value of each feature in a table with one row.
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.
units: tuple of pint.Unit
Units of the layer data in world coordinates.
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
"""
_modeclass = Mode
_colors = get_color_names()
_vertex_size = 10
_rotation_handle_length = 20
_highlight_color = (0, 0.6, 1)
_highlight_width = 1.5
_face_color_property: str
_edge_color_property: str
_face_color_cycle: npt.NDArray
_edge_color_cycle: npt.NDArray
_face_color_cycle_values: npt.NDArray
_edge_color_cycle_values: npt.NDArray
_face_color_mode: str
_edge_color_mode: str
# If more shapes are present then they are randomly subsampled
# in the thumbnail
_max_shapes_thumbnail = 100
_drag_modes: ClassVar[dict[Mode, Callable[['Shapes', Event], Any]]] = {
Mode.PAN_ZOOM: no_op,
Mode.TRANSFORM: transform_with_box,
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,
Mode.ADD_POLYGON_LASSO: add_path_polygon_lasso,
}
_move_modes: ClassVar[dict[Mode, Callable[['Shapes', Event], Any]]] = {
Mode.PAN_ZOOM: no_op,
Mode.TRANSFORM: highlight_box_handles,
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: polygon_creating,
Mode.ADD_POLYGON: polygon_creating,
Mode.ADD_POLYGON_LASSO: polygon_creating,
}
_double_click_modes: ClassVar[
dict[Mode, Callable[['Shapes', Event], Any]]
] = {
Mode.PAN_ZOOM: no_op,
Mode.TRANSFORM: 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,
Mode.ADD_POLYGON_LASSO: no_op,
}
_cursor_modes: ClassVar[dict[Mode, str]] = {
Mode.PAN_ZOOM: 'standard',
Mode.TRANSFORM: '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',
Mode.ADD_POLYGON_LASSO: 'cross',
}
_interactive_modes: ClassVar[set[Mode]] = {
Mode.PAN_ZOOM,
}
def __init__(
self,
data=None,
ndim=None,
*,
affine=None,
axis_labels=None,
blending='translucent',
cache=True,
edge_color='#777777',
edge_color_cycle=None,
edge_colormap='viridis',
edge_contrast_limits=None,
edge_width=1,
experimental_clipping_planes=None,
face_color='white',
face_color_cycle=None,
face_colormap='viridis',
face_contrast_limits=None,
feature_defaults=None,
features=None,
metadata=None,
name=None,
opacity=0.7,
projection_mode='none',
properties=None,
property_choices=None,
rotate=None,
scale=None,
shape_type='rectangle',
shear=None,
text=None,
translate=None,
units=None,
visible=True,
z_index=0,
) -> None:
if data is None or len(data) == 0:
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,
affine=affine,
axis_labels=axis_labels,
blending=blending,
cache=cache,
experimental_clipping_planes=experimental_clipping_planes,
metadata=metadata,
name=name,
opacity=opacity,
projection_mode=projection_mode,
rotate=rotate,
scale=scale,
shear=shear,
translate=translate,
units=units,
visible=visible,
)
self.events.add(
edge_width=Event,
edge_color=Event,
face_color=Event,
properties=Event,
current_edge_color=Event,
current_face_color=Event,
current_properties=Event,
highlight=Event,
features=Event,
feature_defaults=Event,
)
# Flag set to false to block thumbnail refresh
self._allow_thumbnail_update = True
self._display_order_stored = []
self._ndisplay_stored = self._slice_input.ndisplay
self._feature_table = _FeatureTable.from_layer(
features=features,
feature_defaults=feature_defaults,
properties=properties,
property_choices=property_choices,
num_data=number_of_shapes(data),
)
# 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._slice_input.ndisplay)
self._data_view.slice_key = np.array(self._data_slice.point)[
self._slice_input.not_displayed
]
self._value = (None, None)
self._value_stored = (None, None)
self._moving_value: tuple[Optional[int], Optional[int]] = (None, None)
self._selected_data = set()
self._selected_data_stored = set()
self._selected_data_history = set()
self._selected_box = None
self._last_cursor_position = 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: dict[str, Shapes] = {}
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._text = TextManager._from_layer(
text=text,
features=self.features,
)
# Trigger generation of view slice and thumbnail
self.mouse_wheel_callbacks.append(_set_highlight)
self.mouse_drag_callbacks.append(_set_highlight)
self.refresh()
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.feature_defaults[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.feature_defaults[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()
self.selected_data = set()
prior_data = len(self.data) > 0
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'),
)
)
data_not_empty = (
data is not None
and (isinstance(data, np.ndarray) and data.size > 0)
) or (isinstance(data, list) and len(data) > 0)
kwargs = {
'value': self.data,
'vertex_indices': ((),),
'data_indices': tuple(i for i in range(len(self.data))),
}
if prior_data and data_not_empty:
kwargs['action'] = ActionType.CHANGING
elif data_not_empty:
kwargs['action'] = ActionType.ADDING
kwargs['data_indices'] = tuple(i for i in range(len(data)))
else:
kwargs['action'] = ActionType.REMOVING
self.events.data(**kwargs)
self._data_view = ShapeList(ndisplay=self._slice_input.ndisplay)
self._data_view.slice_key = np.array(self._data_slice.point)[
self._slice_input.not_displayed
]
self._add_shapes(
data,
shape_type=shape_type,
edge_width=edge_widths,
edge_color=edge_color,
face_color=face_color,
z_index=z_indices,
n_new_shapes=n_new_shapes,
)
self._update_dims()
kwargs['data_indices'] = tuple(i for i in range(len(data)))
kwargs['value'] = self.data
if prior_data and data_not_empty:
kwargs['action'] = ActionType.CHANGED
elif data_not_empty:
kwargs['action'] = ActionType.ADDED
else:
kwargs['action'] = ActionType.REMOVED
self.events.data(**kwargs)
self._reset_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 features(self):
"""Dataframe-like features table.
It is an implementation detail that this is a `pandas.DataFrame`. In the future,
we will target the currently-in-development Data API dataframe protocol [1].
This will enable us to use alternate libraries such as xarray or cuDF for
additional features without breaking existing usage of this.
If you need to specifically rely on the pandas API, please coerce this to a
`pandas.DataFrame` using `features_to_pandas_dataframe`.
References
----------
.. [1]: https://data-apis.org/dataframe-protocol/latest/API.html
"""
return self._feature_table.values
@features.setter
def features(
self,
features: Union[dict[str, np.ndarray], pd.DataFrame],
) -> None:
self._feature_table.set_values(features, num_data=self.nshapes)
if self._face_color_property and (
self._face_color_property not in self.features
):
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.features
):
self._edge_color_property = ''
warnings.warn(
trans._(
'property used for edge_color dropped',
deferred=True,
),
RuntimeWarning,
)
self.text.refresh(self.features)
self.events.properties()
self.events.features()
@property
def feature_defaults(self):
"""Dataframe-like with one row of feature default values.
See `features` for more details on the type of this property.
"""
return self._feature_table.defaults
@feature_defaults.setter
def feature_defaults(
self, defaults: Union[dict[str, Any], pd.DataFrame]
) -> None:
self._feature_table.set_defaults(defaults)
self.events.current_properties()
self.events.feature_defaults()
@property
def properties(self) -> dict[str, np.ndarray]:
"""dict {str: np.ndarray (N,)}, DataFrame: Annotations for each shape"""
return self._feature_table.properties()
@properties.setter
def properties(self, properties: dict[str, Array]):
self.features = properties
@property
def property_choices(self) -> dict[str, np.ndarray]:
return self._feature_table.choices()
def _get_ndim(self):
"""Determine number of dimensions of the layer."""
ndim = self.ndim if self.nshapes == 0 else 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._feature_table.currents()
@current_properties.setter
def current_properties(self, current_properties):
update_indices = None
if (
self._update_properties
and len(self.selected_data) > 0
and self._mode in [Mode.SELECT, Mode.PAN_ZOOM]
):
update_indices = list(self.selected_data)
self._feature_table.set_currents(
current_properties, update_indices=update_indices
)
if update_indices is not None:
self.refresh_colors()
self.events.properties()
self.events.features()
self.events.current_properties()
self.events.feature_defaults()
@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(np.asarray(edge_color_cycle), 'edge')
@property
def edge_colormap(self) -> 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) -> Union[tuple[float, float], None]:
"""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) -> 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: Union[np.ndarray, cycle], 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')
)
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')
)
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
]
if (
unique_face_color := _unique_element(selected_face_colors)
) is not None:
with self.block_update_properties():
self.current_face_color = unique_face_color
selected_edge_colors = self._data_view._edge_color[
selected_data_indices
]
if (
unique_edge_color := _unique_element(selected_edge_colors)
) is not None:
with self.block_update_properties():
self.current_edge_color = unique_edge_color
unique_edge_width = _unique_element(
np.array(
[
self._data_view.shapes[i].edge_width
for i in selected_data
]
)
)
if unique_edge_width is not None:
with self.block_update_properties():
self.current_edge_width = unique_edge_width
unique_properties = {}
for k, v in self.properties.items():
unique_properties[k] = _unique_element(
v[selected_data_indices]
)
if all(p is not None for p in unique_properties.values()):
with self.block_update_properties():
self.current_properties = unique_properties
self._set_highlight()
@property
def _is_moving(self) -> bool:
return self._private_is_moving
@_is_moving.setter
def _is_moving(self, value):
assert value in (True, False)
if value:
assert self._moving_coordinates is not None
self._private_is_moving = value
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(update_color_mapping=True)
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.isin(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):
return color in self.properties
if isinstance(color, (list, np.ndarray)):
return False
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) -> dict[str, Any]:
"""Get dictionary of layer state.
Returns
-------
state : dict of str to Any
Dictionary of layer state.
"""
state = self._get_base_state()
face_color = self.face_color
edge_color = self.edge_color
if not face_color.size:
face_color = self._current_face_color
if not edge_color.size:
edge_color = self._current_edge_color
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': face_color,
'face_color_cycle': self.face_color_cycle,
'face_colormap': self.face_colormap.dict(),
'face_contrast_limits': self.face_contrast_limits,
'edge_color': edge_color,
'edge_color_cycle': self.edge_color_cycle,
'edge_colormap': self.edge_colormap.dict(),
'edge_contrast_limits': self.edge_contrast_limits,
'data': self.data,
'features': self.features,
'feature_defaults': self.feature_defaults,
}
)
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
"""
# This may be triggered when the string encoding instance changed,
# in which case it has no cached values, so generate them here.
self.text.string._apply(self.features)
return self.text.view_text(self._indices_view)
@property
def _view_text_coords(self) -> tuple[np.ndarray, str, str]:
"""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
anchor_x : str
The vispy text anchor for the x axis
anchor_y : str
The vispy text anchor for the y axis
"""
ndisplay = self._slice_input.ndisplay
order = self._slice_input.order
# 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._slice_input.displayed]
for position in in_view_shapes_coords
]
# TODO: fix types here with np.asarray(sliced_in_view_coords)
# but blocked by https://github.com/napari/napari/issues/6294
return self.text.compute_text_coords(
sliced_in_view_coords, ndisplay, order
)
@property
def _view_text_color(self) -> np.ndarray:
"""Get the colors of the text elements at the given indices."""
self.text.color._apply(self.features)
return self.text._view_color(self._indices_view)
@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, val: Union[str, Mode]):
mode = self._mode_setter_helper(val)
if mode == self._mode:
return
self._mode = mode
self.events.mode(mode=mode)
draw_modes = {
Mode.SELECT,
Mode.DIRECT,
Mode.VERTEX_INSERT,
Mode.VERTEX_REMOVE,
}
# don't update thumbnail on mode changes
if not (mode in draw_modes and self._mode in draw_modes):
# Shapes._finish_drawing() calls Shapes.refresh() via Shapes._update_dims()
# so we need to block thumbnail update from here
# TODO: this is not great... ideally we should no longer need this blocking system
# but maybe follow up PR
with self.block_thumbnail_update():
self._finish_drawing()
else:
self.refresh(data_displayed=False, extent=False, thumbnail=False)
def _reset_editable(self) -> None:
self.editable = self._slice_input.ndisplay == 2
def _on_editable_changed(self) -> None:
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 in 2D a (2, 2) array of 2 vertices that are
the 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 in 2D a (2, 2) array of
center position and radii magnitudes.
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,
gui=False,
):
"""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.
gui : bool
Whether the shape is drawn by drawing in the gui.
"""
data, shape_type = extract_shape_type(data, shape_type)
n_new_shapes = number_of_shapes(data)
if n_new_shapes > 0:
self.events.data(
value=self.data,
action=ActionType.ADDING,
data_indices=(-1,),
vertex_indices=((),),
)
self._add_shapes(
data,
shape_type=shape_type,
edge_width=edge_width,
edge_color=edge_color,
face_color=face_color,
z_index=z_index,
n_new_shapes=n_new_shapes,
)
# This should only emit when programmatically adding as with drawing this leads to premature emit.
if not gui:
self.events.data(
value=self.data,
action=ActionType.ADDED,
data_indices=(-1,),
vertex_indices=((),),
)
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,
n_new_shapes=n_shapes,
)
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,
n_new_shapes=0,
):
"""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.
n_new_shapes : int
The number of new shapes to be added to the Shapes layer.
"""
if n_new_shapes > 0:
total_shapes = n_new_shapes + self.nshapes
self._feature_table.resize(total_shapes)
if hasattr(self, 'text'):
self.text.apply(self.features)
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 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._slice_input.order)
self._ndisplay_stored = copy(self._slice_input.ndisplay)
self._update_dims()
def _add_shapes_to_view(self, shape_inputs, data_view):
"""Build new shapes and add them to the _data_view"""
shape_inputs = tuple(shape_inputs)
# build all shapes
sh_inp = tuple(
(
shape_classes[ShapeType(st)](
d,
edge_width=ew,
z_index=z,
dims_order=self._slice_input.order,
ndisplay=self._slice_input.ndisplay,
),
ec,
fc,
)
for d, st, ew, ec, fc, z in shape_inputs
)
shapes, edge_colors, face_colors = tuple(zip(*sh_inp))
# Add all shapes at once (faster than adding them one by one)
data_view.add(
shape=shapes,
edge_color=edge_colors,
face_color=face_colors,
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._update_from_layer(
text=text,
features=self.features,
)
[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(self.features)
@property
def _normalized_scale_factor(self):
"""Scale factor accounting for layer scale.
This is often needed when calculating screen-space sizes and distances
of vertices for interactivity (rescaling, adding vertices, etc).
"""
return self.scale_factor / self.scale[-1]
@property
def _normalized_vertex_radius(self):
"""Vertex radius normalized to screen space."""
return self._vertex_size * self._normalized_scale_factor / 2
def _set_view_slice(self):
"""Set the view given the slicing indices."""
with self._data_view.batched_updates():
ndisplay = self._slice_input.ndisplay
if ndisplay != self._ndisplay_stored:
self.selected_data = set()
self._data_view.ndisplay = min(self.ndim, ndisplay)
self._ndisplay_stored = ndisplay
self._clipboard = {}
if self._slice_input.order != self._display_order_stored:
self.selected_data = set()
self._data_view.update_dims_order(self._slice_input.order)
self._display_order_stored = copy(self._slice_input.order)
# Clear clipboard if dimensions swap
self._clipboard = {}
slice_key = np.array(self._data_slice.point)[
self._slice_input.not_displayed
]
if not np.array_equal(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 bounding 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[next(iter(index))]._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._normalized_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._highlight_visible
and 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._normalized_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 self._highlight_visible and len(self.selected_data) > 0:
if self._mode == Mode.SELECT:
# If in select mode just show the interaction bounding box
# including its vertices and the rotation handle
box = self._selected_box[Box.WITH_HANDLE]
if self._value[0] is None or 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_POLYGON_LASSO,
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 or 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._highlight_visible and 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) -> None:
"""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.array_equal(self._value, self._value_stored)
and np.array_equal(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) -> None:
"""Reset properties used in shape drawing."""
index = copy(self._moving_value[0])
self._is_moving = False
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)
self._last_cursor_position = None
if self._is_creating is True:
if self._mode == Mode.ADD_PATH:
vertices = self._data_view.shapes[index].data
if len(vertices) <= 2:
self._data_view.remove(index)
# Clear selected data to prevent issues.
# See https://github.com/napari/napari/pull/6912#discussion_r1601169680
self.selected_data.clear()
else:
self._data_view.edit(index, vertices[:-1])
if self._mode in {Mode.ADD_POLYGON, Mode.ADD_POLYGON_LASSO}:
vertices = self._data_view.shapes[index].data
if len(vertices) <= 3:
self._data_view.remove(index)
# Clear selected data to prevent issues.
# See https://github.com/napari/napari/pull/6912#discussion_r1601169680
self.selected_data.clear()
elif self._mode == Mode.ADD_POLYGON:
self._data_view.edit(index, vertices[:-1])
else:
vertices = rdp(
vertices,
epsilon=get_settings().experimental.rdp_epsilon,
)
self._data_view.edit(
index,
vertices[:-1],
new_type=shape_classes[ShapeType.POLYGON],
)
# handles the case that
if index is not None:
self.events.data(
value=self.data,
action=ActionType.ADDED,
data_indices=(-1,),
vertex_indices=((),),
)
self._is_creating = False
self._update_dims()
[docs]
@contextmanager
def block_thumbnail_update(self):
"""Use this context manager to block thumbnail updates"""
previous = self._allow_thumbnail_update
self._allow_thumbnail_update = False
try:
yield
finally:
self._allow_thumbnail_update = previous
def _update_thumbnail(self, event=None):
"""Update thumbnail with current shapes and colors."""
# Set the thumbnail to black, opacity 1
colormapped = np.zeros(self._thumbnail_shape)
colormapped[..., 3] = 1
# if the shapes layer is empty, don't update, just leave it black
if len(self.data) == 0:
self.thumbnail = colormapped
# don't update the thumbnail if dragging a shape
elif 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._slice_input.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._slice_input.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) -> None:
"""Remove any selected shapes."""
index = list(self.selected_data)
to_remove = sorted(index, reverse=True)
if len(index) > 0:
self.events.data(
value=self.data,
action=ActionType.REMOVING,
data_indices=tuple(
index,
),
vertex_indices=((),),
)
for ind in to_remove:
self._data_view.remove(ind)
self._feature_table.remove(index)
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.events.data(
value=self.data,
action=ActionType.REMOVED,
data_indices=tuple(
index,
),
vertex_indices=((),),
)
self.selected_data.clear()
self._finish_drawing()
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.array_equal(box[Box.TOP_CENTER], box[Box.HANDLE]):
r = self._rotation_handle_length * self._normalized_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.array_equal(box[Box.TOP_CENTER], box[Box.HANDLE]):
r = self._rotation_handle_length * self._normalized_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._slice_input.ndisplay == 3:
return (None, None)
if self._is_moving:
return self._moving_value
coord = [position[i] for i in self._slice_input.displayed]
# Check selected shapes
value = None
selected_index = list(self.selected_data)
if len(selected_index) > 0:
self.scale[self._slice_input.displayed]
# Get the vertex sizes. They need to be rescaled by a few parameters:
# - scale_factor, because vertex sizes are zoom-invariant
# - scale, because vertex sizes are not affected by scale (unlike in Points)
# - 2, because the radius is what we need
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)
# Check if any matching vertices
matches = np.all(
distances <= self._normalized_vertex_radius, 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)
# Check if any matching vertices
matches = np.all(
distances <= self._normalized_vertex_radius, 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], 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[None, float, int], Union[None, np.ndarray]]:
"""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 Union[None, float, int]
The data value along the supplied ray.
intersection_point : Union[None, 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:
# return None if in 2D mode
return None, None
if (start_point is None) or (end_point is None):
# return None if the ray doesn't intersect the data bounding box
return None, None
# Get the normal vector of the click plane
start_position, ray_direction = nd_line_segment_to_displayed_data_ray(
start_point=start_point,
end_point=end_point,
dims_displayed=dims_displayed,
)
value, intersection = self._data_view._inside_3d(
start_position, ray_direction
)
# add the full nD coords to intersection
intersection_point = start_point.copy()
intersection_point[dims_displayed] = intersection
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], Union[npt.NDArray, 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) -> None:
"""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(extent=False, highlight=False)
[docs]
def move_to_back(self) -> None:
"""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(extent=False, highlight=False)
def _copy_data(self) -> None:
"""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]),
'features': deepcopy(self.features.iloc[index]),
'indices': self._data_slice.point,
'text': self.text._copy(index),
}
else:
self._clipboard = {}
def _paste_data(self) -> None:
"""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._data_slice.point[i] - self._clipboard['indices'][i]
for i in self._slice_input.not_displayed
]
self._feature_table.append(self._clipboard['features'])
self.text._paste(**self._clipboard['text'])
# Add new shape data
for i, s in enumerate(self._clipboard['data']):
shape = deepcopy(s)
data = copy(shape.data)
not_disp = self._slice_input.not_displayed
data[:, not_disp] = data[:, not_disp] + 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
)
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
