code: def annotate_heatmap(
      im,
      data=None,
      valfmt="{x:.2f}",
      textcolors=("black", "white"),
      threshold=None,
      **textkw,
  ):
      """
      A function to annotate a heatmap.
  
      Parameters
      ----------
      im
          The AxesImage to be labeled.
      data
          Data used to annotate.  If None, the image's data is used.  Optional.
      valfmt
          The format of the annotations inside the heatmap.  This should either
          use the string format method, e.g. "$ {x:.2f}", or be a
          `matplotlib.ticker.Formatter`.  Optional.
      textcolors
          A pair of colors.  The first is used for values below a threshold,
          the second for those above.  Optional.
      threshold
          Value in data units according to which the colors from textcolors are
          applied.  If None (the default) uses the middle of the colormap as
          separation.  Optional.
      **kwargs
          All other arguments are forwarded to each call to `text` used to create
          the text labels.
      """
  
      if not isinstance(data, (list, np.ndarray)):
          data = im.get_array()
  
      # Normalize the threshold to the images color range.
      if threshold is not None:
          threshold = im.norm(threshold)
      else:
          threshold = im.norm(data.max()) / 2.0
  
      # Set default alignment to center, but allow it to be
      # overwritten by textkw.
      kw = dict(
          horizontalalignment="center", verticalalignment="center"
      )
      kw.update(textkw)
  
      # Get the formatter in case a string is supplied
      if isinstance(valfmt, str):
          valfmt = matplotlib.ticker.StrMethodFormatter(valfmt)
  
      # Loop over the data and create a `Text` for each "pixel".
      # Change the text's color depending on the data.
      texts = []
      for i in range(data.shape[0]):
          for j in range(data.shape[1]):
              kw.update(
                  color=textcolors[int(im.norm(data[i, j]) > threshold)]
              )
              text = im.axes.text(j, i, valfmt(data[i, j], None), **kw)
              texts.append(text)
  
      return texts
  
imports: import matplotlib.pyplot
  import numpy
  import matplotlib
  import matplotlib
label_desc: Use image node_id 2 for calling a global function with example usage: annotate_heatmap(im, data, valfmt, textcolors, threshold) and returns: texts