napari.components.Dims#
- class napari.components.Dims(*, ndim: int = 2, ndisplay: Literal[2, 3] = 2, last_used: int = 0, range: Tuple[Tuple[float, float, float], ...] = (), current_step: Tuple[int, ...] = (), order: Tuple[int, ...] = (), axis_labels: Tuple[str, ...] = ())[source]#
Bases:
EventedModel
Dimensions object modeling slicing and displaying.
- Parameters:
ndim (int) – Number of dimensions.
ndisplay (int) – Number of displayed dimensions.
last_used (int) – Dimension which was last used.
range (tuple of 3-tuple of float) – List of tuples (min, max, step), one for each dimension. In a world coordinates space. As with Python’s range and slice, max is not included.
current_step (tuple of int) – Tuple of the slider position for each dims slider, in slider coordinates.
order (tuple of int) – Tuple of ordering the dimensions, where the last dimensions are rendered.
axis_labels (tuple of str) – Tuple of labels for each dimension.
- range#
List of tuples (min, max, step), one for each dimension. In a world coordinates space. As with Python’s range and slice, max is not included.
- current_step#
Tuple the slider position for each dims slider, in slider coordinates.
- nsteps#
Number of steps available to each slider. These are calculated from the
range
.
- point#
List of floats setting the current value of the range slider when in POINT mode, one for each dimension. In a world coordinates space. These are calculated from the
current_step
andrange
.
- displayed#
List of dimensions that are displayed. These are calculated from the
order
andndisplay
.
- not_displayed#
List of dimensions that are not displayed. These are calculated from the
order
andndisplay
.
- displayed_order#
Order of only displayed dimensions. These are calculated from the
displayed
dimensions.
Methods
construct
([_fields_set])Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
copy
(*[, include, exclude, update, deep])Duplicate a model, optionally choose which fields to include, exclude and change.
dict
(*[, include, exclude, by_alias, ...])Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
enums_as_values
([as_values])Temporarily override how enums are retrieved.
from_orm
(obj)json
(*[, include, exclude, by_alias, ...])Generate a JSON representation of the model, include and exclude arguments as per dict().
parse_file
(path, *[, content_type, ...])parse_obj
(obj)parse_raw
(b, *[, content_type, encoding, ...])reset
()Reset dims values to initial states.
schema
([by_alias, ref_template])schema_json
(*[, by_alias, ref_template])set_axis_label
(axis, label)Sets new axis labels for the given axes.
set_current_step
(axis, value)Set the slider steps at which to slice this dimension.
set_point
(axis, value)Sets point to slice dimension in world coordinates.
set_range
(axis, _range)Sets ranges (min, max, step) for the given dimensions.
Transpose displayed dimensions.
update
(values[, recurse])Update a model in place.
update_forward_refs
(**localns)Try to update ForwardRefs on fields based on this Model, globalns and localns.
validate
(value)Attributes
Dimensions that are displayed.
events
Dimensions that are not displayed.
Number of slider steps for each dimension.
Value of each dimension.
Details
- classmethod construct(_fields_set: SetStr | None = None, **values: Any) Model #
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
- copy(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, update: DictStrAny | None = None, deep: bool = False) Model #
Duplicate a model, optionally choose which fields to include, exclude and change.
- Parameters:
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model
- Returns:
new model instance
- dict(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, by_alias: bool = False, skip_defaults: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny #
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- enums_as_values(as_values: bool = True)#
Temporarily override how enums are retrieved.
- Parameters:
as_values (bool, optional) – Whether enums should be shown as values (or as enum objects), by default True
- json(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, by_alias: bool = False, skip_defaults: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Callable[[Any], Any] | None = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode #
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
- set_axis_label(axis: int | Sequence[int], label: str | Sequence[str])[source]#
Sets new axis labels for the given axes.
- set_current_step(axis: int | Sequence[int], value: int | float | Sequence[int | float])[source]#
Set the slider steps at which to slice this dimension.
The position of the slider in world coordinates gets calculated from the current_step of the slider.
- set_point(axis: int | Sequence[int], value: float | Sequence[float])[source]#
Sets point to slice dimension in world coordinates.
The desired point gets transformed into an integer step of the slider and stored in the current_step.
- set_range(axis: int | Sequence[int], _range: Sequence[int | float] | Sequence[Sequence[int | float]])[source]#
Sets ranges (min, max, step) for the given dimensions.
- transpose()[source]#
Transpose displayed dimensions.
This swaps the order of the last two displayed dimensions. The order of the displayed is taken from Dims.order.
- update(values: EventedModel | dict, recurse: bool = True) None #
Update a model in place.
- Parameters:
values (dict, napari.utils.events.EventedModel) – Values to update the model with. If an EventedModel is passed it is first converted to a dictionary. The keys of this dictionary must be found as attributes on the current model.
recurse (bool) – If True, recursively update fields that are EventedModels. Otherwise, just update the immediate fields of this EventedModel, which is useful when the declared field type (e.g.
Union
) can have different realized types with different fields.