code: def double_frame(i):
      plt.figure(figsize=(10, 3))
      wts_small = mod_small._calc_wts(xs_orig[i])
      wts_big = mod_big._calc_wts(xs_orig[i])
  
      plt.scatter(xs_sparse, ys_sparse, color="gray")
  
      plt.plot(xs_orig, wts_big, color="green", alpha=0.5)
      plt.plot(xs_orig, wts_small, color="red", alpha=0.5)
  
      plt.plot(
          xs_orig[:i],
          preds_big[:i],
          color="green",
          label="$\sigma$=0.1",
      )
      plt.plot(
          xs_orig[:i],
          preds_small[:i],
          color="red",
          label="$\sigma$=0.01",
      )
  
      plt.legend()
  
imports: from pathlib import Path
  import gif
  import matplotlib.pylab
  import seaborn
  import numpy
  from sklego.linear_model import LowessRegression
  from sklearn.datasets import make_regression
  import pandas
  from sklearn.pipeline import Pipeline, FeatureUnion
  from sklearn.linear_model import LinearRegression
  from sklearn.decomposition import PCA
  from sklearn.model_selection import GridSearchCV
  from sklego.meta import EstimatorTransformer
  from sklego.linear_model import ProbWeightRegression
  from sklego.preprocessing import ColumnSelector
  from sklearn import set_config
  from sklearn.utils import estimator_html_repr
  import numpy
  import numpy
  from sklearn.linear_model import LinearRegression
  import numpy
  from sklearn.linear_model import LinearRegression
  from sklego.linear_model import LADRegression
  import numpy
  from sklego.linear_model import QuantileRegression
label_desc: Use image node_id 4 for calling a global function with example usage: double_frame(i) without return types