- GPCCA.plot_macrostates(states=None, color=None, discrete=False, mode=PlotMode.EMBEDDING, time_key='latent_time', same_plot=True, title=None, cmap='viridis', **kwargs)
Plot continuous or categorical observations in an embedding or along pseudotime.
bool) – Whether to plot the data as continuous or discrete observations. If the data cannot be plotted as continuous observations, it will be plotted as discrete.
Literal[‘embedding’, ‘time’]) –
Valid options are:
’embedding’ - plot the embedding while coloring in continuous or categorical observations.
’time’ - plot the pseudotime on x-axis and the probabilities/memberships on y-axis.
bool) – Whether to plot the data on the same plot or not. Only use when
mode = 'embedding'. If True and
discrete = False,
str) – Colormap for continuous data.
- Return type
Nothing, just plots the figure. Optionally saves it based on