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

  • 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. For resources for constructing custom color palettes, see also:


Mapping from cells to colors.

Return type