code: def _one_mesh_info(
      surf_map,
      surf_mesh,
      threshold=None,
      cmap=cm.cold_hot,
      black_bg=False,
      bg_map=None,
      symmetric_cmap=True,
      bg_on_data=False,
      darkness=0.7,
      vmax=None,
      vmin=None,
  ):
      """Prepare info for plotting one surface map on a single mesh.
  
      This computes the dictionary that gets inserted in the web page,
      which contains the encoded mesh, colors, min and max values, and
      background color.
  
      """
      info = {}
      colors = colorscale(
          cmap,
          surf_map,
          threshold,
          symmetric_cmap=symmetric_cmap,
          vmax=vmax,
          vmin=vmin,
      )
      info["inflated_left"] = mesh_to_plotly(surf_mesh)
      info["vertexcolor_left"] = get_vertexcolor(
          surf_map,
          colors["cmap"],
          colors["norm"],
          absolute_threshold=colors["abs_threshold"],
          bg_map=bg_map,
          bg_on_data=bg_on_data,
          darkness=darkness,
      )
      info["cmin"], info["cmax"] = float(colors["vmin"]), float(
          colors["vmax"]
      )
      info["black_bg"] = black_bg
      info["full_brain_mesh"] = False
      info["colorscale"] = colors["colors"]
      return info
  
imports: import collections.abc
  import json
  from warnings import warn
  import matplotlib
  import matplotlib.pyplot
  import numpy
  from nilearn import datasets, surface
  from nilearn._utils import fill_doc
  from nilearn._utils.niimg_conversions import check_niimg_3d
  from nilearn.plotting import cm
  from nilearn.plotting.html_document import HTMLDocument
  from nilearn.plotting.js_plotting_utils import add_js_lib, colorscale, get_html_template, mesh_to_plotly, to_color_strings
label_desc: Use image node_id 2 for calling a global function with example usage: _one_mesh_info(surf_map, surf_mesh, threshold, cmap, black_bg, bg_map, symmetric_cmap, bg_on_data, darkness, vmax, vmin) and returns: info