from __future__ import annotations
import inspect
import itertools
import os
import warnings
from functools import lru_cache
from pathlib import Path
from typing import (
TYPE_CHECKING,
Any,
Dict,
List,
Optional,
Sequence,
Set,
Tuple,
Union,
)
import numpy as np
from pydantic import Extra, Field, validator
from .. import layers
from ..layers import Image, Layer
from ..layers._source import layer_source
from ..layers.image._image_utils import guess_labels
from ..layers.utils.stack_utils import split_channels
from ..settings import get_settings
from ..utils._register import create_func as create_add_method
from ..utils.colormaps import ensure_colormap
from ..utils.context import Context, create_context
from ..utils.events import Event, EventedModel, disconnect_events
from ..utils.key_bindings import KeymapProvider
from ..utils.misc import is_sequence
from ..utils.mouse_bindings import MousemapProvider
from ..utils.progress import progress
from ..utils.theme import available_themes
from ..utils.translations import trans
from ._viewer_mouse_bindings import dims_scroll
from .axes import Axes
from .camera import Camera
from .cursor import Cursor
from .dims import Dims
from .grid import GridCanvas
from .layerlist import LayerList
from .overlays import Overlays
from .scale_bar import ScaleBar
from .text_overlay import TextOverlay
from .tooltip import Tooltip
DEFAULT_THEME = 'dark'
EXCLUDE_DICT = {
'keymap',
'_mouse_wheel_gen',
'_mouse_drag_gen',
'_persisted_mouse_event',
'mouse_move_callbacks',
'mouse_drag_callbacks',
'mouse_wheel_callbacks',
}
EXCLUDE_JSON = EXCLUDE_DICT.union({'layers', 'active_layer'})
if TYPE_CHECKING:
from ..types import FullLayerData, LayerData
PathLike = Union[str, Path]
PathOrPaths = Union[PathLike, Sequence[PathLike]]
__all__ = ['ViewerModel', 'valid_add_kwargs']
def _current_theme() -> str:
return get_settings().appearance.theme
# KeymapProvider & MousemapProvider should eventually be moved off the ViewerModel
[docs]class ViewerModel(KeymapProvider, MousemapProvider, EventedModel):
"""Viewer containing the rendered scene, layers, and controlling elements
including dimension sliders, and control bars for color limits.
Parameters
----------
title : string
The title of the viewer window.
ndisplay : {2, 3}
Number of displayed dimensions.
order : tuple of int
Order in which dimensions are displayed where the last two or last
three dimensions correspond to row x column or plane x row x column if
ndisplay is 2 or 3.
axis_labels : list of str
Dimension names.
Attributes
----------
window : Window
Parent window.
layers : LayerList
List of contained layers.
dims : Dimensions
Contains axes, indices, dimensions and sliders.
"""
# Using allow_mutation=False means these attributes aren't settable and don't
# have an event emitter associated with them
axes: Axes = Field(default_factory=Axes, allow_mutation=False)
camera: Camera = Field(default_factory=Camera, allow_mutation=False)
cursor: Cursor = Field(default_factory=Cursor, allow_mutation=False)
dims: Dims = Field(default_factory=Dims, allow_mutation=False)
grid: GridCanvas = Field(default_factory=GridCanvas, allow_mutation=False)
layers: LayerList = Field(
default_factory=LayerList, allow_mutation=False
) # Need to create custom JSON encoder for layer!
scale_bar: ScaleBar = Field(default_factory=ScaleBar, allow_mutation=False)
text_overlay: TextOverlay = Field(
default_factory=TextOverlay, allow_mutation=False
)
overlays: Overlays = Field(default_factory=Overlays, allow_mutation=False)
help: str = ''
status: str = 'Ready'
tooltip: Tooltip = Field(default_factory=Tooltip, allow_mutation=False)
theme: str = Field(default_factory=_current_theme)
title: str = 'napari'
# 2-tuple indicating height and width
_canvas_size: Tuple[int, int] = (600, 800)
_ctx: Context
def __init__(self, title='napari', ndisplay=2, order=(), axis_labels=()):
# max_depth=0 means don't look for parent contexts.
self._ctx = create_context(self, max_depth=0)
# allow extra attributes during model initialization, useful for mixins
self.__config__.extra = Extra.allow
super().__init__(
title=title,
dims={
'axis_labels': axis_labels,
'ndisplay': ndisplay,
'order': order,
},
)
self.__config__.extra = Extra.ignore
settings = get_settings()
self.tooltip.visible = settings.appearance.layer_tooltip_visibility
settings.appearance.events.layer_tooltip_visibility.connect(
self._tooltip_visible_update
)
self._update_viewer_grid()
settings.application.events.grid_stride.connect(
self._update_viewer_grid
)
settings.application.events.grid_width.connect(
self._update_viewer_grid
)
settings.application.events.grid_height.connect(
self._update_viewer_grid
)
# Add extra events - ideally these will be removed too!
self.events.add(layers_change=Event, reset_view=Event)
# Connect events
self.grid.events.connect(self.reset_view)
self.grid.events.connect(self._on_grid_change)
self.dims.events.ndisplay.connect(self._update_layers)
self.dims.events.ndisplay.connect(self.reset_view)
self.dims.events.order.connect(self._update_layers)
self.dims.events.order.connect(self.reset_view)
self.dims.events.current_step.connect(self._update_layers)
self.cursor.events.position.connect(self._on_cursor_position_change)
self.layers.events.inserted.connect(self._on_add_layer)
self.layers.events.removed.connect(self._on_remove_layer)
self.layers.events.reordered.connect(self._on_grid_change)
self.layers.events.reordered.connect(self._on_layers_change)
self.layers.selection.events.active.connect(self._on_active_layer)
# Add mouse callback
self.mouse_wheel_callbacks.append(dims_scroll)
def _tooltip_visible_update(self, event):
self.tooltip.visible = event.value
def _update_viewer_grid(self):
"""Keep viewer grid settings up to date with settings values."""
settings = get_settings()
self.grid.stride = settings.application.grid_stride
self.grid.shape = (
settings.application.grid_height,
settings.application.grid_width,
)
@validator('theme')
def _valid_theme(cls, v):
themes = available_themes()
if v not in available_themes():
raise ValueError(
trans._(
"Theme '{theme_name}' not found; options are {themes}.",
deferred=True,
theme_name=v,
themes=themes,
)
)
return v
[docs] def json(self, **kwargs):
"""Serialize to json."""
# Manually exclude the layer list and active layer which cannot be serialized at this point
# and mouse and keybindings don't belong on model
# https://github.com/samuelcolvin/pydantic/pull/2231
# https://github.com/samuelcolvin/pydantic/issues/660#issuecomment-642211017
exclude = kwargs.pop('exclude', set())
exclude = exclude.union(EXCLUDE_JSON)
return super().json(exclude=exclude, **kwargs)
[docs] def dict(self, **kwargs):
"""Convert to a dictionary."""
# Manually exclude the layer list and active layer which cannot be serialized at this point
# and mouse and keybindings don't belong on model
# https://github.com/samuelcolvin/pydantic/pull/2231
# https://github.com/samuelcolvin/pydantic/issues/660#issuecomment-642211017
exclude = kwargs.pop('exclude', set())
exclude = exclude.union(EXCLUDE_DICT)
return super().dict(exclude=exclude, **kwargs)
def __hash__(self):
return id(self)
def __str__(self):
"""Simple string representation"""
return f'napari.Viewer: {self.title}'
@property
def _sliced_extent_world(self) -> np.ndarray:
"""Extent of layers in world coordinates after slicing.
D is either 2 or 3 depending on if the displayed data is 2D or 3D.
Returns
-------
sliced_extent_world : array, shape (2, D)
"""
if len(self.layers) == 0 and self.dims.ndim != 2:
# If no data is present and dims model has not been reset to 0
# than someone has passed more than two axis labels which are
# being saved and so default values are used.
return np.vstack(
[np.zeros(self.dims.ndim), np.repeat(512, self.dims.ndim)]
)
else:
return self.layers.extent.world[:, self.dims.displayed]
[docs] def reset_view(self):
"""Reset the camera view."""
extent = self._sliced_extent_world
scene_size = extent[1] - extent[0]
corner = extent[0]
grid_size = list(self.grid.actual_shape(len(self.layers)))
if len(scene_size) > len(grid_size):
grid_size = [1] * (len(scene_size) - len(grid_size)) + grid_size
size = np.multiply(scene_size, grid_size)
center = np.add(corner, np.divide(size, 2))[-self.dims.ndisplay :]
center = [0] * (self.dims.ndisplay - len(center)) + list(center)
self.camera.center = center
# zoom is definied as the number of canvas pixels per world pixel
# The default value used below will zoom such that the whole field
# of view will occupy 95% of the canvas on the most filled axis
if np.max(size) == 0:
self.camera.zoom = 0.95 * np.min(self._canvas_size)
else:
scale = np.array(size[-2:])
scale[np.isclose(scale, 0)] = 1
self.camera.zoom = 0.95 * np.min(
np.array(self._canvas_size) / scale
)
self.camera.angles = (0, 0, 90)
# Emit a reset view event, which is no longer used internally, but
# which maybe useful for building on napari.
self.events.reset_view(
center=self.camera.center,
zoom=self.camera.zoom,
angles=self.camera.angles,
)
def _new_labels(self):
"""Create new labels layer filling full world coordinates space."""
layers_extent = self.layers.extent
extent = layers_extent.world
scale = layers_extent.step
scene_size = extent[1] - extent[0]
corner = extent[0] + 0.5 * layers_extent.step
shape = [
np.round(s / sc).astype('int') if s > 0 else 1
for s, sc in zip(scene_size, scale)
]
empty_labels = np.zeros(shape, dtype=int)
self.add_labels(empty_labels, translate=np.array(corner), scale=scale)
def _update_layers(self, *, layers=None):
"""Updates the contained layers.
Parameters
----------
layers : list of napari.layers.Layer, optional
List of layers to update. If none provided updates all.
"""
layers = layers or self.layers
for layer in layers:
layer._slice_dims(
self.dims.point, self.dims.ndisplay, self.dims.order
)
def _on_active_layer(self, event):
"""Update viewer state for a new active layer."""
active_layer = event.value
if active_layer is None:
self.help = ''
self.cursor.style = 'standard'
self.camera.interactive = True
else:
self.help = active_layer.help
self.cursor.style = active_layer.cursor
self.cursor.size = active_layer.cursor_size
self.camera.interactive = active_layer.interactive
@staticmethod
def rounded_division(min_val, max_val, precision):
return int(((min_val + max_val) / 2) / precision) * precision
def _on_layers_change(self):
if len(self.layers) == 0:
self.dims.ndim = 2
self.dims.reset()
else:
ranges = self.layers._ranges
ndim = len(ranges)
self.dims.ndim = ndim
self.dims.set_range(range(ndim), ranges)
new_dim = self.dims.ndim
dim_diff = new_dim - len(self.cursor.position)
if dim_diff < 0:
self.cursor.position = self.cursor.position[:new_dim]
elif dim_diff > 0:
self.cursor.position = tuple(
list(self.cursor.position) + [0] * dim_diff
)
self.events.layers_change()
def _update_interactive(self, event):
"""Set the viewer interactivity with the `event.interactive` bool."""
self.camera.interactive = event.interactive
def _update_cursor(self, event):
"""Set the viewer cursor with the `event.cursor` string."""
self.cursor.style = event.cursor
def _update_cursor_size(self, event):
"""Set the viewer cursor_size with the `event.cursor_size` int."""
self.cursor.size = event.cursor_size
def _on_cursor_position_change(self):
"""Set the layer cursor position."""
with warnings.catch_warnings():
# Catch the deprecation warning on layer.position
warnings.filterwarnings(
'ignore',
message=str(
trans._('layer.position is deprecated', deferred=True)
),
)
for layer in self.layers:
layer.position = self.cursor.position
# Update status and help bar based on active layer
active = self.layers.selection.active
if active is not None:
self.status = active.get_status(
self.cursor.position,
view_direction=self.cursor._view_direction,
dims_displayed=list(self.dims.displayed),
world=True,
)
self.help = active.help
if self.tooltip.visible:
self.tooltip.text = active._get_tooltip_text(
self.cursor.position,
view_direction=self.cursor._view_direction,
dims_displayed=list(self.dims.displayed),
world=True,
)
def _on_grid_change(self):
"""Arrange the current layers is a 2D grid."""
extent = self._sliced_extent_world
n_layers = len(self.layers)
for i, layer in enumerate(self.layers):
i_row, i_column = self.grid.position(n_layers - 1 - i, n_layers)
self._subplot(layer, (i_row, i_column), extent)
def _subplot(self, layer, position, extent):
"""Shift a layer to a specified position in a 2D grid.
Parameters
----------
layer : napari.layers.Layer
Layer that is to be moved.
position : 2-tuple of int
New position of layer in grid.
extent : array, shape (2, D)
Extent of the world.
"""
scene_shift = extent[1] - extent[0]
translate_2d = np.multiply(scene_shift[-2:], position)
translate = [0] * layer.ndim
translate[-2:] = translate_2d
layer._translate_grid = translate
@property
def experimental(self):
"""Experimental commands for IPython console.
For example run "viewer.experimental.cmds.loader.help".
"""
from .experimental.commands import ExperimentalNamespace
return ExperimentalNamespace(self.layers)
def _on_add_layer(self, event):
"""Connect new layer events.
Parameters
----------
event : :class:`napari.layers.Layer`
Layer to add.
"""
layer = event.value
# Connect individual layer events to viewer events
# TODO: in a future PR, we should now be able to connect viewer *only*
# to viewer.layers.events... and avoid direct viewer->layer connections
layer.events.interactive.connect(self._update_interactive)
layer.events.cursor.connect(self._update_cursor)
layer.events.cursor_size.connect(self._update_cursor_size)
layer.events.data.connect(self._on_layers_change)
layer.events.scale.connect(self._on_layers_change)
layer.events.translate.connect(self._on_layers_change)
layer.events.rotate.connect(self._on_layers_change)
layer.events.shear.connect(self._on_layers_change)
layer.events.affine.connect(self._on_layers_change)
layer.events.name.connect(self.layers._update_name)
# Update dims and grid model
self._on_layers_change()
self._on_grid_change()
# Slice current layer based on dims
self._update_layers(layers=[layer])
if len(self.layers) == 1:
self.reset_view()
ranges = self.layers._ranges
midpoint = [self.rounded_division(*_range) for _range in ranges]
self.dims.set_point(range(len(ranges)), midpoint)
def _on_remove_layer(self, event):
"""Disconnect old layer events.
Parameters
----------
event : napari.utils.event.Event
Event which will remove a layer.
Returns
-------
layer : :class:`napari.layers.Layer` or list
The layer that was added (same as input).
"""
layer = event.value
# Disconnect all connections from layer
disconnect_events(layer.events, self)
disconnect_events(layer.events, self.layers)
self._on_layers_change()
self._on_grid_change()
[docs] def add_layer(self, layer: Layer) -> Layer:
"""Add a layer to the viewer.
Parameters
----------
layer : :class:`napari.layers.Layer`
Layer to add.
Returns
-------
layer : :class:`napari.layers.Layer` or list
The layer that was added (same as input).
"""
# Adding additional functionality inside `add_layer`
# should be avoided to keep full functionality
# from adding a layer through the `layers.append`
# method
self.layers.append(layer)
return layer
[docs] def add_image(
self,
data=None,
*,
channel_axis=None,
rgb=None,
colormap=None,
contrast_limits=None,
gamma=1,
interpolation='nearest',
rendering='mip',
depiction='volume',
iso_threshold=0.5,
attenuation=0.05,
name=None,
metadata=None,
scale=None,
translate=None,
rotate=None,
shear=None,
affine=None,
opacity=1,
blending=None,
visible=True,
multiscale=None,
cache=True,
plane=None,
experimental_clipping_planes=None,
) -> Union[Image, List[Image]]:
"""Add an image layer to the layer list.
Parameters
----------
data : array or list of array
Image data. Can be N >= 2 dimensional. If the last dimension has length
3 or 4 can be interpreted as RGB or RGBA if rgb is `True`. If a
list and arrays are decreasing in shape then the data is treated as
a multiscale image. Please note multiscale rendering is only
supported in 2D. In 3D, only the lowest resolution scale is
displayed.
channel_axis : int, optional
Axis to expand image along. If provided, each channel in the data
will be added as an individual image layer. In channel_axis mode,
all other parameters MAY be provided as lists, and the Nth value
will be applied to the Nth channel in the data. If a single value
is provided, it will be broadcast to all Layers.
rgb : bool or list
Whether the image is rgb RGB or RGBA. If not specified by user and
the last dimension of the data has length 3 or 4 it will be set as
`True`. If `False` the image is interpreted as a luminance image.
If a list then must be same length as the axis that is being
expanded as channels.
colormap : str, napari.utils.Colormap, tuple, dict, list
Colormaps to use for luminance images. If a string must be the name
of a supported colormap from vispy or matplotlib. If a tuple the
first value must be a string to assign as a name to a colormap and
the second item must be a Colormap. If a dict the key must be a
string to assign as a name to a colormap and the value must be a
Colormap. If a list then must be same length as the axis that is
being expanded as channels, and each colormap is applied to each
new image layer.
contrast_limits : list (2,)
Color limits to be used for determining the colormap bounds for
luminance images. If not passed is calculated as the min and max of
the image. If list of lists then must be same length as the axis
that is being expanded and then each colormap is applied to each
image.
gamma : list, float
Gamma correction for determining colormap linearity. Defaults to 1.
If a list then must be same length as the axis that is being
expanded as channels.
interpolation : str or list
Interpolation mode used by vispy. Must be one of our supported
modes. If a list then must be same length as the axis that is being
expanded as channels.
rendering : str or list
Rendering mode used by vispy. Must be one of our supported
modes. If a list then must be same length as the axis that is being
expanded as channels.
depiction : str
Selects a preset volume depiction mode in vispy
* volume: images are rendered as 3D volumes.
* plane: images are rendered as 2D planes embedded in 3D.
iso_threshold : float or list
Threshold for isosurface. If a list then must be same length as the
axis that is being expanded as channels.
attenuation : float or list
Attenuation rate for attenuated maximum intensity projection. If a
list then must be same length as the axis that is being expanded as
channels.
name : str or list of str
Name of the layer. If a list then must be same length as the axis
that is being expanded as channels.
metadata : dict or list of dict
Layer metadata. If a list then must be a list of dicts with the
same length as the axis that is being expanded as channels.
scale : tuple of float or list
Scale factors for the layer. If a list then must be a list of
tuples of float with the same length as the axis that is being
expanded as channels.
translate : tuple of float or list
Translation values for the layer. If a list then must be a list of
tuples of float with the same length as the axis that is being
expanded as channels.
rotate : float, 3-tuple of float, n-D array or list.
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. If a list then must have same length as
the axis that is being expanded as channels.
shear : 1-D array or list.
A vector of shear values for an upper triangular n-D shear matrix.
If a list then must have same length as the axis that is being
expanded as channels.
affine : n-D array or napari.utils.transforms.Affine
(N+1, N+1) affine transformation matrix in homogeneous coordinates.
The first (N, N) entries correspond to a linear transform and
the final column is a length N translation vector and a 1 or a
napari `Affine` transform object. Applied as an extra transform on
top of the provided scale, rotate, and shear values.
opacity : float or list
Opacity of the layer visual, between 0.0 and 1.0. If a list then
must be same length as the axis that is being expanded as channels.
blending : str or list
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'}. If a list then
must be same length as the axis that is being expanded as channels.
visible : bool or list of bool
Whether the layer visual is currently being displayed.
If a list then must be same length as the axis that is
being expanded as channels.
multiscale : bool
Whether the data is a multiscale image or not. Multiscale data is
represented by a list of array like image data. If not specified by
the user and if the data is a list of arrays that decrease in shape
then it will be taken to be multiscale. The first image in the list
should be the largest. Please note multiscale rendering is only
supported in 2D. In 3D, only the lowest resolution scale is
displayed.
cache : bool
Whether slices of out-of-core datasets should be cached upon
retrieval. Currently, this only applies to dask arrays.
plane : dict or SlicingPlane
Properties defining plane rendering in 3D. Properties are defined in
data coordinates. Valid dictionary keys are
{'position', 'normal', 'thickness', and 'enabled'}.
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.
Returns
-------
layer : :class:`napari.layers.Image` or list
The newly-created image layer or list of image layers.
"""
if colormap is not None:
# standardize colormap argument(s) to Colormaps, and make sure they
# are in AVAILABLE_COLORMAPS. This will raise one of many various
# errors if the colormap argument is invalid. See
# ensure_colormap for details
if isinstance(colormap, list):
colormap = [ensure_colormap(c) for c in colormap]
else:
colormap = ensure_colormap(colormap)
# doing this here for IDE/console autocompletion in add_image function.
kwargs = {
'rgb': rgb,
'colormap': colormap,
'contrast_limits': contrast_limits,
'gamma': gamma,
'interpolation': interpolation,
'rendering': rendering,
'depiction': depiction,
'iso_threshold': iso_threshold,
'attenuation': attenuation,
'name': name,
'metadata': metadata,
'scale': scale,
'translate': translate,
'rotate': rotate,
'shear': shear,
'affine': affine,
'opacity': opacity,
'blending': blending,
'visible': visible,
'multiscale': multiscale,
'cache': cache,
'plane': plane,
'experimental_clipping_planes': experimental_clipping_planes,
}
# these arguments are *already* iterables in the single-channel case.
iterable_kwargs = {
'scale',
'translate',
'rotate',
'shear',
'affine',
'contrast_limits',
'metadata',
'experimental_clipping_planes',
}
if channel_axis is None:
kwargs['colormap'] = kwargs['colormap'] or 'gray'
kwargs['blending'] = kwargs['blending'] or 'translucent'
# Helpful message if someone tries to add mulit-channel kwargs,
# but forget the channel_axis arg
for k, v in kwargs.items():
if k not in iterable_kwargs and is_sequence(v):
raise TypeError(
trans._(
"Received sequence for argument '{argument}', did you mean to specify a 'channel_axis'? ",
deferred=True,
argument=k,
)
)
layer = Image(data, **kwargs)
self.layers.append(layer)
return layer
else:
layerdata_list = split_channels(data, channel_axis, **kwargs)
layer_list = list()
for image, i_kwargs, _ in layerdata_list:
layer = Image(image, **i_kwargs)
self.layers.append(layer)
layer_list.append(layer)
return layer_list
[docs] def open_sample(
self,
plugin: str,
sample: str,
reader_plugin: Optional[str] = None,
**kwargs,
) -> List[Layer]:
"""Open `sample` from `plugin` and add it to the viewer.
To see all available samples registered by plugins, use
:func:`napari.plugins.available_samples`
Parameters
----------
plugin : str
name of a plugin providing a sample
sample : str
name of the sample
reader_plugin : str, optional
reader plugin to pass to viewer.open (only used if the sample data
is a string). by default None.
``**kwargs``
additional kwargs will be passed to the sample data loader provided
by `plugin`. Use of ``**kwargs`` may raise an error if the kwargs do
not match the sample data loader.
Returns
-------
layers : list
A list of any layers that were added to the viewer.
Raises
------
KeyError
If `plugin` does not provide a sample named `sample`.
"""
from ..plugins import _npe2, plugin_manager
# try with npe2
data, available = _npe2.get_sample_data(plugin, sample)
# then try with npe1
if data is None:
try:
data = plugin_manager._sample_data[plugin][sample]['data']
except KeyError:
available += list(plugin_manager.available_samples())
if data is None:
msg = trans._(
"Plugin {plugin!r} does not provide sample data named {sample!r}. ",
plugin=plugin,
sample=sample,
deferred=True,
)
if available:
msg = trans._(
"Plugin {plugin!r} does not provide sample data named {sample!r}. Available samples include: {samples}.",
deferred=True,
plugin=plugin,
sample=sample,
samples=available,
)
else:
msg = trans._(
"Plugin {plugin!r} does not provide sample data named {sample!r}. No plugin samples have been registered.",
deferred=True,
plugin=plugin,
sample=sample,
)
raise KeyError(msg)
with layer_source(sample=(plugin, sample)):
if callable(data):
added = []
for datum in data(**kwargs):
added.extend(self._add_layer_from_data(*datum))
return added
elif isinstance(data, (str, Path)):
return self.open(data, plugin=reader_plugin)
else:
raise TypeError(
trans._(
'Got unexpected type for sample ({plugin!r}, {sample!r}): {data_type}',
deferred=True,
plugin=plugin,
sample=sample,
data_type=type(data),
)
)
[docs] def open(
self,
path: PathOrPaths,
*,
stack: bool = False,
plugin: Optional[str] = None,
layer_type: Optional[str] = None,
**kwargs,
) -> List[Layer]:
"""Open a path or list of paths with plugins, and add layers to viewer.
A list of paths will be handed one-by-one to the napari_get_reader hook
if stack is False, otherwise the full list is passed to each plugin
hook.
Parameters
----------
path : str or list of str
A filepath, directory, or URL (or a list of any) to open.
stack : bool, optional
If a list of strings is passed and ``stack`` is ``True``, then the
entire list will be passed to plugins. It is then up to individual
plugins to know how to handle a list of paths. If ``stack`` is
``False``, then the ``path`` list is broken up and passed to plugin
readers one by one. by default False.
plugin : str, optional
Name of a plugin to use. If provided, will force ``path`` to be
read with the specified ``plugin``. If the requested plugin cannot
read ``path``, an exception will be raised.
layer_type : str, optional
If provided, will force data read from ``path`` to be passed to the
corresponding ``add_<layer_type>`` method (along with any
additional) ``kwargs`` provided to this function. This *may*
result in exceptions if the data returned from the path is not
compatible with the layer_type.
``**kwargs``
All other keyword arguments will be passed on to the respective
``add_layer`` method.
Returns
-------
layers : list
A list of any layers that were added to the viewer.
"""
paths = [path] if isinstance(path, (Path, str)) else path
paths = [os.fspath(path) for path in paths] # PathObjects -> str
if not isinstance(paths, (tuple, list)):
raise ValueError(
trans._(
"'path' argument must be a string, list, or tuple",
deferred=True,
)
)
if stack:
return self._add_layers_with_plugins(
paths,
kwargs=kwargs,
plugin=plugin,
layer_type=layer_type,
stack=stack,
)
added: List[Layer] = [] # for layers that get added
with progress(
paths,
desc=trans._('Opening Files'),
total=0
if len(paths) == 1
else None, # indeterminate bar for 1 file
) as pbr:
for _path in pbr:
added.extend(
self._add_layers_with_plugins(
[_path],
kwargs=kwargs,
plugin=plugin,
layer_type=layer_type,
stack=stack,
)
)
return added
def _add_layers_with_plugins(
self,
paths: List[str],
*,
stack: bool,
kwargs: Optional[dict] = None,
plugin: Optional[str] = None,
layer_type: Optional[str] = None,
) -> List[Layer]:
"""Load a path or a list of paths into the viewer using plugins.
This function is mostly called from self.open_path, where the ``stack``
argument determines whether a list of strings is handed to plugins one
at a time, or en-masse.
Parameters
----------
paths : list of str
A filepath, directory, or URL (or a list of any) to open. If a
list, the assumption is that the list is to be treated as a stack.
kwargs : dict, optional
keyword arguments that will be used to overwrite any of those that
are returned in the meta dict from plugins.
plugin : str, optional
Name of a plugin to use. If provided, will force ``path`` to be
read with the specified ``plugin``. If the requested plugin cannot
read ``path``, an exception will be raised.
layer_type : str, optional
If provided, will force data read from ``path`` to be passed to the
corresponding ``add_<layer_type>`` method (along with any
additional) ``kwargs`` provided to this function. This *may*
result in exceptions if the data returned from the path is not
compatible with the layer_type.
stack : bool
See `open` method
Stack=False => path is unique string, and list of len(1)
Stack=True => path is list of path
Returns
-------
List[Layer]
A list of any layers that were added to the viewer.
"""
from ..plugins.io import read_data_with_plugins
assert stack is not None
assert isinstance(paths, list)
assert not isinstance(paths, str)
if stack:
layer_data, hookimpl = read_data_with_plugins(
paths, plugin=plugin, stack=stack
)
else:
assert len(paths) == 1
layer_data, hookimpl = read_data_with_plugins(
paths, plugin=plugin, stack=stack
)
# glean layer names from filename. These will be used as *fallback*
# names, if the plugin does not return a name kwarg in their meta dict.
filenames = []
if len(paths) == len(layer_data):
filenames = iter(paths)
else:
# if a list of paths has been returned as a list of layer data
# without a 1:1 relationship between the two lists we iterate
# over the first name
filenames = itertools.repeat(paths[0])
# add each layer to the viewer
added: List[Layer] = [] # for layers that get added
plugin = hookimpl.plugin_name if hookimpl else None
for data, filename in zip(layer_data, filenames):
basename, _ext = os.path.splitext(os.path.basename(filename))
_data = _unify_data_and_user_kwargs(
data, kwargs, layer_type, fallback_name=basename
)
# actually add the layer
with layer_source(path=filename, reader_plugin=plugin):
added.extend(self._add_layer_from_data(*_data))
return added
def _add_layer_from_data(
self,
data,
meta: Dict[str, Any] = None,
layer_type: Optional[str] = None,
) -> List[Layer]:
"""Add arbitrary layer data to the viewer.
Primarily intended for usage by reader plugin hooks.
Parameters
----------
data : Any
Data in a format that is valid for the corresponding `add_*` method
of the specified ``layer_type``.
meta : dict, optional
Dict of keyword arguments that will be passed to the corresponding
`add_*` method. MUST NOT contain any keyword arguments that are
not valid for the corresponding method.
layer_type : str
Type of layer to add. MUST have a corresponding add_* method on
on the viewer instance. If not provided, the layer is assumed to
be "image", unless data.dtype is one of (np.int32, np.uint32,
np.int64, np.uint64), in which case it is assumed to be "labels".
Returns
-------
layers : list of layers
A list of layers added to the viewer.
Raises
------
ValueError
If ``layer_type`` is not one of the recognized layer types.
TypeError
If any keyword arguments in ``meta`` are unexpected for the
corresponding `add_*` method for this layer_type.
Examples
--------
A typical use case might be to upack a tuple of layer data with a
specified layer_type.
>>> viewer = napari.Viewer()
>>> data = (
... np.random.random((10, 2)) * 20,
... {'face_color': 'blue'},
... 'points',
... )
>>> viewer._add_layer_from_data(*data)
"""
layer_type = (layer_type or '').lower()
# assumes that big integer type arrays are likely labels.
if not layer_type:
layer_type = guess_labels(data)
if layer_type not in layers.NAMES:
raise ValueError(
trans._(
"Unrecognized layer_type: '{layer_type}'. Must be one of: {layer_names}.",
deferred=True,
layer_type=layer_type,
layer_names=layers.NAMES,
)
)
try:
add_method = getattr(self, 'add_' + layer_type)
layer = add_method(data, **(meta or {}))
except TypeError as exc:
if 'unexpected keyword argument' not in str(exc):
raise exc
bad_key = str(exc).split('keyword argument ')[-1]
raise TypeError(
trans._(
"_add_layer_from_data received an unexpected keyword argument ({bad_key}) for layer type {layer_type}",
deferred=True,
bad_key=bad_key,
layer_type=layer_type,
)
) from exc
return layer if isinstance(layer, list) else [layer]
def _normalize_layer_data(data: LayerData) -> FullLayerData:
"""Accepts any layerdata tuple, and returns a fully qualified tuple.
Parameters
----------
data : LayerData
1-, 2-, or 3-tuple with (data, meta, layer_type).
Returns
-------
FullLayerData
3-tuple with (data, meta, layer_type)
Raises
------
ValueError
If data has len < 1 or len > 3, or if the second item in ``data`` is
not a ``dict``, or the third item is not a valid layer_type ``str``
"""
if not isinstance(data, tuple) and 0 < len(data) < 4:
raise ValueError(
trans._(
"LayerData must be a 1-, 2-, or 3-tuple",
deferred=True,
)
)
_data = list(data)
if len(_data) > 1:
if not isinstance(_data[1], dict):
raise ValueError(
trans._(
"The second item in a LayerData tuple must be a dict",
deferred=True,
)
)
else:
_data.append(dict())
if len(_data) > 2:
if _data[2] not in layers.NAMES:
raise ValueError(
trans._(
"The third item in a LayerData tuple must be one of: {layers!r}.",
deferred=True,
layers=layers.NAMES,
)
)
else:
_data.append(guess_labels(_data[0]))
return tuple(_data) # type: ignore
def _unify_data_and_user_kwargs(
data: LayerData,
kwargs: Optional[dict] = None,
layer_type: Optional[str] = None,
fallback_name: str = None,
) -> FullLayerData:
"""Merge data returned from plugins with options specified by user.
If ``data == (_data, _meta, _type)``. Then:
- ``kwargs`` will be used to update ``_meta``
- ``layer_type`` will replace ``_type`` and, if provided, ``_meta`` keys
will be pruned to layer_type-appropriate kwargs
- ``fallback_name`` is used if ``not _meta.get('name')``
.. note:
If a user specified both layer_type and additional keyword arguments
to viewer.open(), it is their responsibility to make sure the kwargs
match the layer_type.
Parameters
----------
data : LayerData
1-, 2-, or 3-tuple with (data, meta, layer_type) returned from plugin.
kwargs : dict, optional
User-supplied keyword arguments, to override those in ``meta`` supplied
by plugins.
layer_type : str, optional
A user-supplied layer_type string, to override the ``layer_type``
declared by the plugin.
fallback_name : str, optional
A name for the layer, to override any name in ``meta`` supplied by the
plugin.
Returns
-------
FullLayerData
Fully qualified LayerData tuple with user-provided overrides.
"""
_data, _meta, _type = _normalize_layer_data(data)
if layer_type:
# the user has explicitly requested this be a certain layer type
# strip any kwargs from the plugin that are no longer relevant
_meta = prune_kwargs(_meta, layer_type)
_type = layer_type
if kwargs:
# if user provided kwargs, use to override any meta dict values that
# were returned by the plugin. We only prune kwargs if the user did
# *not* specify the layer_type. This means that if a user specified
# both layer_type and additional keyword arguments to viewer.open(),
# it is their responsibility to make sure the kwargs match the
# layer_type.
_meta.update(prune_kwargs(kwargs, _type) if not layer_type else kwargs)
if not _meta.get('name') and fallback_name:
_meta['name'] = fallback_name
return (_data, _meta, _type)
def prune_kwargs(kwargs: Dict[str, Any], layer_type: str) -> Dict[str, Any]:
"""Return copy of ``kwargs`` with only keys valid for ``add_<layer_type>``
Parameters
----------
kwargs : dict
A key: value mapping where some or all of the keys are parameter names
for the corresponding ``Viewer.add_<layer_type>`` method.
layer_type : str
The type of layer that is going to be added with these ``kwargs``.
Returns
-------
pruned_kwargs : dict
A key: value mapping where all of the keys are valid parameter names
for the corresponding ``Viewer.add_<layer_type>`` method.
Raises
------
ValueError
If ``ViewerModel`` does not provide an ``add_<layer_type>`` method
for the provided ``layer_type``.
Examples
--------
>>> test_kwargs = {
... 'scale': (0.75, 1),
... 'blending': 'additive',
... 'num_colors': 10,
... }
>>> prune_kwargs(test_kwargs, 'image')
{'scale': (0.75, 1), 'blending': 'additive'}
>>> # only labels has the ``num_colors`` argument
>>> prune_kwargs(test_kwargs, 'labels')
{'scale': (0.75, 1), 'blending': 'additive', 'num_colors': 10}
"""
add_method = getattr(ViewerModel, 'add_' + layer_type, None)
if not add_method or layer_type == 'layer':
raise ValueError(
trans._(
"Invalid layer_type: {layer_type}",
deferred=True,
layer_type=layer_type,
)
)
# get valid params for the corresponding add_<layer_type> method
valid = valid_add_kwargs()[layer_type]
return {k: v for k, v in kwargs.items() if k in valid}
@lru_cache(maxsize=1)
def valid_add_kwargs() -> Dict[str, Set[str]]:
"""Return a dict where keys are layer types & values are valid kwargs."""
valid = dict()
for meth in dir(ViewerModel):
if not meth.startswith('add_') or meth[4:] == 'layer':
continue
params = inspect.signature(getattr(ViewerModel, meth)).parameters
valid[meth[4:]] = set(params) - {'self', 'kwargs'}
return valid
for _layer in (
layers.Labels,
layers.Points,
layers.Shapes,
layers.Surface,
layers.Tracks,
layers.Vectors,
):
func = create_add_method(_layer, filename=__file__)
setattr(ViewerModel, func.__name__, func)