napari.components.Dims#

class napari.components.Dims(*, ndim: int = 2, ndisplay: Literal[2, 3] = 2, order: tuple[int, ...] = (), axis_labels: tuple[str, ...] = (), rollable: tuple[bool, ...] = (), range: tuple[RangeTuple, ...] = (), margin_left: tuple[float, ...] = (), margin_right: tuple[float, ...] = (), point: tuple[float, ...] = (), last_used: int = 0)[source]#

Bases: EventedModel

Dimensions object modeling slicing and displaying.

Parameters:

ndim (int) – Number of dimensions.
ndisplay (int) – Number of displayed dimensions.
range (tuple of 3-tuple of float) – List of tuples (min, max, step), one for each dimension in world coordinates space. Lower and upper bounds are inclusive.
point (tuple of floats) – Dims position in world coordinates for each dimension.
margin_left (tuple of floats) – Left margin in world pixels of the slice for each dimension.
margin_right (tuple of floats) – Right margin in world pixels of the slice for each dimension.
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.
last_used (int) – Dimension which was last interacted with.

ndim#

Number of dimensions.

Type:: int

ndisplay#

Number of displayed dimensions.

Type:: int

range#

List of tuples (min, max, step), one for each dimension in world coordinates space. Lower and upper bounds are inclusive.

Type:: tuple of 3-tuple of float

point#

Dims position in world coordinates for each dimension.

Type:: tuple of floats

margin_left#

Left margin (=thickness) in world pixels of the slice for each dimension.

Type:: tuple of floats

margin_right#

Right margin (=thickness) in world pixels of the slice for each dimension.

Type:: tuple of floats

order#

Tuple of ordering the dimensions, where the last dimensions are rendered.

Type:: tuple of int

axis_labels#

Tuple of labels for each dimension.

Type:: tuple of str

last_used#

Dimension which was last used. Tuple the slider position for each dims slider, in world coordinates.

Type:: int

current_step#

Current step for each dimension (same as point, but in slider coordinates).

Type:: tuple of int

nsteps#

Number of steps available to each slider. These are calculated from the range.

Type:: tuple of int

thickness#

Thickness of the slice (sum of both margins) for each dimension in world coordinates.

Type:: tuple of floats

displayed#

List of dimensions that are displayed. These are calculated from the order and ndisplay.

Type:: tuple of int

not_displayed#

List of dimensions that are not displayed. These are calculated from the order and ndisplay.

Type:: tuple of int

displayed_order#

Order of only displayed dimensions. These are calculated from the displayed dimensions.

Type:: tuple of int

rollable#

Tuple of axis roll state. If True the axis is rollable.

Type:: tuple of bool

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.
`roll`()	Roll order of dimensions for display.
`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_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`()	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

`current_step`
`displayed`	Dimensions that are displayed.
`displayed_order`
`events`
`not_displayed`	Dimensions that are not displayed.
`nsteps`
`thickness`

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

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.

property displayed: tuple[int, ...]#

Dimensions that are displayed.

Type:: Tuple

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().

property not_displayed: tuple[int, ...]#

Dimensions that are not displayed.

Type:: Tuple

reset()[source]#: Reset dims values to initial states.

roll()[source]#: Roll order of dimensions for display.

set_axis_label(axis: int | Sequence[int], label: str | Sequence[str])[source]#

Sets new axis labels for the given axes.

Parameters:

axis (int or sequence of int) – Dimension index or a sequence of axes whos labels will be set.
label (str or sequence of str) – Given labels for the specified axes.

set_point(axis: int | Sequence[int], value: float | Sequence[float])[source]#

Sets point to slice dimension in world coordinates.

Parameters:

axis (int or sequence of int) – Dimension index or a sequence of axes whos point will be set.
value (scalar or sequence of scalars) – Value of the point for each axis.

set_range(axis: int | Sequence[int], _range: Sequence[int | float] | Sequence[Sequence[int | float]])[source]#

Sets ranges (min, max, step) for the given dimensions.

Parameters:

axis (int or sequence of int) – Dimension index or a sequence of axes whos range will be set.
_range (tuple or sequence of tuple) – Range specified as (min, max, step) or a sequence of these range tuples.

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.

classmethod update_forward_refs(**localns: Any) → None#: Try to update ForwardRefs on fields based on this Model, globalns and localns.