pegasus.wordcloud

pegasus.wordcloud(data, factor, max_words=20, features='highly_variable_features', random_state=0, colormap='hsv', width=800, height=400, panel_size=(6, 4), return_fig=False, dpi=300.0, **kwargs)[source]

Generate one word cloud image for factor (starts from 0) in data.uns[‘W’].

Parameters

  • data (AnnData or UnimodalData or MultimodalData object) – The main data object.

  • factor (int) – Which factor to plot. factor starts from 0.

  • max_words (int, optional, default: 20) – Maximum number of genes to show in the image.

  • features (str, optional, default: highly_variable_features) – Features selected for NMF computation.

  • random_state (int, optional, default: 0) – Random seed passing to WordCloud function.

  • colormap (str, optional, default: hsv) – Color map for plotting words.

  • width (int, optional, default: 800) – Canvas width.

  • height (int, optional, default: 400) – Canvas height.

  • panel_size (tuple, optional, default: (6, 4)) – The plot size (width, height) in inches.

  • return_fig (bool, optional, default: False) – Return a Figure object if True; return None otherwise.

  • dpi (float, optional, default: 300.0) – The resolution in dots per inch.

Return type

Optional[Figure]

Returns

  • Figure object – A matplotlib.figure.Figure object containing the dot plot if return_fig == True

Examples

>>> fig = pg.wordcloud(data, factor=0)