code: def _blurred_path_region(
      n_timestamps_1,
      n_timestamps_2,
      resolution_level,
      n_timestamps_reduced_1,
      n_timestamps_reduced_2,
      path,
      radius,
  ):
      path_length = path.shape[1]
      path_up = np.tile(path, radius)
      path_down = path_up.copy()
      path_left = path_up.copy()
      path_right = path_up.copy()
  
      for i in range(1, radius + 1):
          start = path_length * (i - 1)
          end = path_length * i
          path_up[0, start:end] += i
          path_down[0, start:end] -= i
          path_left[1, start:end] -= i
          path_right[1, start:end] += i
  
      path_radius = np.c_[
          path, path_up, path_down, path_left, path_right
      ]
      path_radius[0] = np.clip(
          path_radius[0], 0, n_timestamps_reduced_1 - 1
      )
      path_radius[1] = np.clip(
          path_radius[1], 0, n_timestamps_reduced_2 - 1
      )
  
      region_reduced = np.empty((2, n_timestamps_reduced_1))
      for i in range(n_timestamps_reduced_1):
          arr = path_radius[1, path_radius[0] == i]
          min_, max_ = np.min(arr), np.max(arr)
          region_reduced[0, i] = min_ * resolution_level
          region_reduced[1, i] = (max_ + 1) * resolution_level
  
      region = np.repeat(region_reduced, resolution_level, axis=1)
      region = _check_region(region, n_timestamps_1, n_timestamps_2)
  
      return region.astype("int64")
  
imports: import numpy
  from math import ceil, log2, sqrt
  from numba import njit, prange
  from sklearn.utils import check_array
label_desc: Use image node_id 23 for calling a global function with example usage: _blurred_path_region(n_timestamps_1, n_timestamps_2, resolution_level, n_timestamps_reduced_1, n_timestamps_reduced_2, path, radius) and returns: region