# eelbrain.plot.colors_for_oneway¶

`eelbrain.plot.``colors_for_oneway`(cells, hue_start=0.2, light_range=0.5, cmap=None, light_cycle=None, always_cycle_hue=False, locations=None, unambiguous=None)

Define colors for a single factor design

Parameters
• cells (sequence of str) – Cells for which to assign colors.

• hue_start (`Union`[`float`, `Sequence`[`float`]]) – First hue value (`0 <= hue < 1`) or list of hue values.

• light_range (scalar | tuple of 2 scalar) – Scalar that specifies the amount of lightness variation (default 0.5). If positive, the first color is lightest; if negative, the first color is darkest. A tuple can be used to specify exact end-points (e.g., `(1.0, 0.4)`). `0.2` is equivalent to `(0.4, 0.6)`. The `light_cycle` parameter can be used to cycle between light and dark more than once.

• cmap (`Optional`[`str`]) – Use a matplotlib colormap instead of the default color generation algorithm. Name of a matplotlib colormap to use (e.g., ‘jet’). If specified, `hue_start` and `light_range` are ignored.

• light_cycle (`Optional`[`int`]) – Cycle from light to dark in `light_cycle` cells to make nearby colors more distinct (default cycles once).

• always_cycle_hue (`bool`) – Cycle hue even when cycling lightness. With `False` (default), hue is constant within a lightness cycle.

• locations (`Optional`[`Sequence`[`float`]]) – Locations of the cells on the color-map (all in range [0, 1]; default is evenly spaced; example: `numpy.linspace(0, 1, len(cells)) ** 0.5`).

• unambiguous (`Union`[`bool`, `Sequence`[`int`], `None`]) – Use unambiguos colors. If `True`, choose the `n` first colors; use a list of `int` to pick specific colors. Other parameters are ignored.

Returns

dict – Mapping from cells to colors.

Return type

{str: tuple}