code: def best_fit_line(points, label=None):
      x = points[:, 0]
      y = points[:, 1]
  
      model = skl.LinearRegression()
      model.fit(x[:, np.newaxis], y)
  
      xline = np.array([x.min(), x.max()])
      yline = model.predict(xline[:, np.newaxis])
  
      if label is None:
          r2_score = skm.r2_score(x, y, sample_weight=None)
          label = "r^2: %0.3f" % r2_score
  
      return xline, yline, label
  
imports: import itertools
  import warnings
  import numpy
  import sklearn.linear_model
  import sklearn.metrics
  import eta.core.serial
  import eta.core.utils
  import fiftyone.core.expressions
  import fiftyone.core.labels
label_desc: Use image node_id 4 for calling a global function with example usage: best_fit_line(points, label) and returns: xline,  yline,  label