holoviews.core.data.image module#

class holoviews.core.data.image.ImageInterface(*, name)[source]#

Interface for 2 or 3D arrays representing images of raw luminance values, RGB values or HSV values.

Methods

`coords`(dataset, dim[, ordered, expanded, edges])	Returns the coordinates along a dimension.
`irregular`(dataset, dim)	ImageInterface does not support irregular data
`sample`(dataset[, samples])	Sample the Raster along one or both of its dimensions, returning a reduced dimensionality type, which is either a ItemTable, Curve or Scatter.
`select`(dataset[, selection_mask])	Slice the underlying numpy array in sheet coordinates.
`unpack_scalar`(dataset, data)	Given a dataset object and data in the appropriate format for the interface, return a simple scalar.
`values`(dataset, dim[, expanded, flat, ...])	The set of samples available along a particular dimension.

Parameter Definitions

classmethod coords(dataset, dim, ordered=False, expanded=False, edges=False)[source]#: Returns the coordinates along a dimension. Ordered ensures coordinates are in ascending order and expanded creates ND-array matching the dimensionality of the dataset.

classmethod irregular(dataset, dim)[source]#: ImageInterface does not support irregular data

classmethod sample(dataset, samples=None)[source]#: Sample the Raster along one or both of its dimensions, returning a reduced dimensionality type, which is either a ItemTable, Curve or Scatter. If two dimension samples and a new_xaxis is provided the sample will be the value of the sampled unit indexed by the value in the new_xaxis tuple.

classmethod select(dataset, selection_mask=None, **selection)[source]#: Slice the underlying numpy array in sheet coordinates.

classmethod unpack_scalar(dataset, data)[source]#: Given a dataset object and data in the appropriate format for the interface, return a simple scalar.

classmethod values(dataset, dim, expanded=True, flat=True, compute=True, keep_index=False)[source]#: The set of samples available along a particular dimension.