napari.utils.CyclicLabelColormap#

class napari.utils.CyclicLabelColormap(colors, display_name: str | None = None, *, name: str = 'custom', interpolation: Literal[ColormapInterpolationMode.ZERO] = ColormapInterpolationMode.ZERO, controls: Array = None, use_selection: bool = False, selection: int = 0, background_value: int = 0, seed: float = 0.5)[source]#

Bases: LabelColormapBase

Color cycle with a background value.

colors#

Colors to be used for mapping. For values above the number of colors, the colors will be cycled.

Type:

ColorArray

use_selection#

Whether map only selected label. If True only selected label will be mapped to not transparent color.

Type:

bool

selection#

The selected label.

Type:

int

background_value#

Which value should be treated as a background and mapped to transparent color.

Type:

int

interpolation#

required by implementation, please do not set value

Type:

Literal[‘zero’]

seed#

seed used for random color generation. Used for reproducibility. It will be removed in the future release.

Type:

float

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().

map(values)

Map values to colors.

parse_file(path, *[, content_type, ...])

parse_obj(obj)

parse_raw(b, *[, content_type, encoding, ...])

reset()

Reset the state of the model to default values.

schema([by_alias, ref_template])

schema_json(*[, by_alias, ref_template])

shuffle(seed)

Shuffle the colormap colors.

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

colorbar

events

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().

map(values: ndarray | integer | int) → ndarray[source]#

Map values to colors.

Parameters:

values (np.ndarray or int) – Values to be mapped.

Returns:

but with the last dimension of size 4 Mapped colors.

Return type:

np.ndarray of the same shape as values,

reset()#

Reset the state of the model to default values.

shuffle(seed: int)[source]#

Shuffle the colormap colors.

Parameters:

seed (int) – Seed for the random number generator.

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.

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