code: def disconnected_vertices(model):
      """
      Returns a boolean vector indicating which vertices are disconnected from the umap graph.
      These vertices will often be scattered across the space and make it difficult to focus on the main
      manifold.  They can either be filtered and have UMAP re-run or simply filtered from the interactive plotting tool
      via the subset_points parameter.
      Use ~disconnected_vertices(model) to only plot the connected points.
      Parameters
      ----------
      model: a trained UMAP model
  
      Returns
      -------
      A boolean vector indicating which points are disconnected
      """
      check_is_fitted(model, "graph_")
      if model.unique:
          vertices_disconnected = (
              np.array(
                  model.graph_[model._unique_inverse_].sum(axis=1)
              ).flatten()
              == 0
          )
      else:
          vertices_disconnected = (
              np.array(model.graph_.sum(axis=1)).flatten() == 0
          )
      return vertices_disconnected
  
file_path: umap/umap/utils.py
imports: import time
  from warnings import warn
  import numpy
  import numba
  from sklearn.utils.validation import check_is_fitted
  import scipy.sparse
label_desc: Use image node_id 8 for calling a global function with example usage: disconnected_vertices(model) and returns: vertices_disconnected