eelbrain.Scalar

class eelbrain.Scalar(name, values, unit=None, tick_format=None, adjacency='grid')

Scalar dimension

Parameters:

  • name (str) – Name of the dimension.

  • values (ArrayLike) – Scalar value for each sample of the dimension.

  • unit (str) – Unit of the values.

  • tick_format (str) – Format string for formatting axis tick labels (‘%’-format, e.g. ‘%.0f’ to round to nearest integer).

  • adjacency (AdjacencyArg) – Adjacency between elements. Set to "none" for no connections or "grid" to use adjacency in the sequence of elements as connection. Set to numpy.ndarray to specify custom adjacency. The array should be of shape (n_edges, 2), and each row should specify one connection [i, j] with i < j, with rows sorted in ascending order. If the array’s dtype is uint32, property checks are disabled to improve efficiency.

Methods

adjacency()

Retrieve the dimension's adjacency graph

dimindex(arg)

Convert a dimension index to an array index

index_into_dim(dim)

Index into a subset dimension

intersect(dim[, check_dims])

Create a dimension object that is the intersection with dim