code: def view_connectome(
      adjacency_matrix,
      node_coords,
      edge_threshold=None,
      edge_cmap=cm.bwr,
      symmetric_cmap=True,
      linewidth=6.0,
      node_color="auto",
      node_size=3.0,
      colorbar=True,
      colorbar_height=0.5,
      colorbar_fontsize=25,
      title=None,
      title_fontsize=25,
  ):
      """Insert a 3d plot of a connectome into an HTML page.
  
      Parameters
      ----------
      adjacency_matrix : ndarray, shape=(n_nodes, n_nodes)
          The weights of the edges.
  
      node_coords : ndarray, shape=(n_nodes, 3)
          The coordinates of the nodes in :term:`MNI` space.
  
      node_color : color or sequence of colors, default='auto'
          Color(s) of the nodes.
  
      edge_threshold : str, number or None, optional
          If None, no thresholding.
          If it is a number only connections of amplitude greater
          than threshold will be shown.
          If it is a string it must finish with a percent sign,
          e.g. "25.3%", and only connections of amplitude above the
          given percentile will be shown.
  
      edge_cmap : str or matplotlib colormap, default=cm.bwr
          Colormap to use.
  
      symmetric_cmap : bool, default=True
          Make colormap symmetric (ranging from -vmax to vmax).
  
      linewidth : float, default=6.0
          Width of the lines that show connections.
  
      node_size : float, default=3.0
          Size of the markers showing the seeds in pixels.
  
      colorbar : bool, default=True
          Add a colorbar.
  
      colorbar_height : float, default=0.5
          Height of the colorbar, relative to the figure height.
  
      colorbar_fontsize : int, default=25
          Fontsize of the colorbar tick labels.
  
      title : str, optional
          Title for the plot.
  
      title_fontsize : int, default=25
          Fontsize of the title.
  
      Returns
      -------
      ConnectomeView : plot of the connectome.
          It can be saved as an html page or rendered (transparently) by the
          Jupyter notebook. Useful methods are :
  
          - 'resize' to resize the plot displayed in a Jupyter notebook
          - 'save_as_html' to save the plot to a file
          - 'open_in_browser' to save the plot and open it in a web browser.
  
      See Also
      --------
      nilearn.plotting.plot_connectome:
          projected views of a connectome in a glass brain.
  
      nilearn.plotting.view_markers:
          interactive plot of colored markers
  
      nilearn.plotting.view_surf, nilearn.plotting.view_img_on_surf:
          interactive view of statistical maps or surface atlases on the cortical
          surface.
  
      """
      node_coords = np.asarray(node_coords)
  
      connectome_info = _get_connectome(
          adjacency_matrix,
          node_coords,
          threshold=edge_threshold,
          cmap=edge_cmap,
          symmetric_cmap=symmetric_cmap,
          marker_size=node_size,
          marker_color=node_color,
      )
      connectome_info["line_width"] = linewidth
      connectome_info["colorbar"] = colorbar
      connectome_info["cbar_height"] = colorbar_height
      connectome_info["cbar_fontsize"] = colorbar_fontsize
      connectome_info["title"] = title
      connectome_info["title_fontsize"] = title_fontsize
      return _make_connectome_html(connectome_info)
  
file_path: nilearn/nilearn/plotting/html_connectome.py
imports: import json
  import numpy
  from matplotlib import cm
  from scipy import sparse
  from nilearn.plotting.html_document import HTMLDocument
  from ..None import datasets
  from .None import cm
  from .js_plotting_utils import add_js_lib, colorscale, encode, get_html_template, mesh_to_plotly, to_color_strings
label_desc: Use image node_id 8 for calling a global function with example usage: view_connectome(adjacency_matrix, node_coords, edge_threshold, edge_cmap, symmetric_cmap, linewidth, node_color, node_size, colorbar, colorbar_height, colorbar_fontsize, title, title_fontsize) and returns: _make_connectome_html