class_docstr: Interactive visualisation of embeddings.
  
  Displays a scatterplot that can be embedded inside a Jupyter notebook.
docstr: Visualise embeddings
  
  Parameters
  ----------
  embeddings : n-dimensional array shape (n_samples, )
      Data to be visualised.
  classes : array, shape (n_samples)
      Optional array of class labels to be overlayed on the scatterplot.
  
  Returns
  -------
  An instance of panel.Row
docstr_tok: ["Visualise","embeddings","Parameters","--","--","--","--","--","embeddings",":","n-dimensional","array","shape","(","n_samples",",",")","Data","to","be","visualised",".","classes",":","array",",","shape","(","n_samples",")","Optional","array","of","class","labels","to","be","overlayed","on","the","scatterplot",".","Returns","--","--","--","-","An","instance","of","panel.Row"]
code: def view(self, embeddings, classes=None):
      """Visualise embeddings
  
      Parameters
      ----------
      embeddings : n-dimensional array shape (n_samples, )
          Data to be visualised.
      classes : array, shape (n_samples)
          Optional array of class labels to be overlayed on the scatterplot.
  
      Returns
      -------
      An instance of panel.Row
      """
      self.embeddings = embeddings
      self.classes = classes
      return pn.Row(self._get_points, self.param)
  
file_path: ivis/ivis/utils/vis_utils.py
imports: import pandas
  import numpy
label_desc: Use image node_id 3 for calling the EmbeddingsExplorer obj's underlying member method code with example usage: obj.view(embeddings, classes) and returns: pn