code: def sample_in_log_scale_new(lstM: List, num_points: int) -> List:
      lst = np.array(lstM)
      # Create an evenly spaced array in the log scale domain
      evenly_spaced_log_x = np.linspace(
          np.log10(lst.min()), np.log10(lst.max()), num_points
      )
      # Convert the new array back to the original scale
      evenly_spaced_x = 10**evenly_spaced_log_x
      # Find the indices of the sampled points in the original x-array
      indices = [
          np.abs(lst - point).argmin() for point in evenly_spaced_x
      ]
      return indices
  
file_path: singa/examples/model_selection/TRAILS-Database-Native-Model-Selection/internal/ml/model_selection/src/tools/compute.py
imports: from typing import List
  import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: sample_in_log_scale_new(lstM, num_points) and returns: indices