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

Scalar dimension

name : str

Name fo the dimension.

values : array_like

Scalar value for each sample of the dimension.

unit : str (optional)

Unit of the values.

tick_format : str (optional)

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

connectivity : ‘grid’ | ‘none’ | array of int, (n_edges, 2)

Connectivity 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 connectivity. 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.


connectivity(self) Retrieve the dimension’s connectivity graph
dimindex(self, arg) Convert a dimension index to an array index
index_into_dim(self, dim) Index into a subset dimension
intersect(self, dim[, check_dims]) Create a dimension object that is the intersection with dim