moscot.plotting.pull¶
- moscot.plotting.pull(obj, key='pull', basis='umap', time_points=None, fill_value=nan, scale=True, dot_scale_factor=2.0, cmap=None, na_color='#e8ebe9', title=None, suptitle=None, suptitle_fontsize=None, ax=None, return_fig=False, figsize=None, dpi=None, save=None, **kwargs)[source]¶
Plot the pull-back distribution.
See also
See Pull/push distributions on how to
compute
and plot the pull-back distribution.
- Parameters:
obj (
Union
[AnnData
,CompoundProblem
]) –Object containing the
pull-back
distribution. Valid options are:AnnData
- annotated data object.CompoundProblem
- one of themoscot.problems
.
key (
str
) – Key inuns['moscot_results']
where the pull-back distribution is stored.time_points (
Optional
[Sequence
[float
]]) – Time points inobs
to highlight.fill_value (
float
) – Fill value for observations not present in selected batchesscale (
bool
) – Whether to linearly scale the distribution.dot_scale_factor (
float
) – Scale factor for thetime_points
.cmap (
Union
[str
,Colormap
,None
]) – Colormap for continuous observations.na_color (
str
) – Color for NaN values.suptitle_fontsize (
Optional
[float
]) – Font size of the suptitle.ax (
Optional
[Axes
]) – Ax used for plotting. IfNone
, create a new one.return_fig (
bool
) – Whether to return the figure.figsize (
Optional
[Tuple
[float
,float
]]) – Size of the figure.save (
Union
[str
,Path
,None
]) – Path where to save the figure.kwargs (
Any
) – Keyword arguments forembedding()
.
- Return type:
- Returns:
: If
return_fig = True
, returns and plots the figure. Otherwise, just plots the figure.