code: def _lpi(point, space, model, n_points):
      """Local parameter importance for each hyperparameters"""
      grid = make_grid(point, space, model, n_points)
      variances = compute_variances(grid)
      ratios = variances / variances.sum()
      return ratios
  
file_path: orion/src/orion/analysis/lpi_utils.py
imports: import numpy
  import pandas
  from orion.analysis.base import flatten_numpy, to_numpy, train_regressor
  from orion.core.worker.transformer import build_required_space
label_desc: Use image node_id 3 for calling a global function with example usage: _lpi(point, space, model, n_points) and returns: ratios