code: def _trajectories(X, dimension, time_delay):
      n_samples, n_timestamps = X.shape
      shape_new = (
          n_samples,
          n_timestamps - (dimension - 1) * time_delay,
          dimension,
      )
      s0, s1 = X.strides
      strides_new = (s0, s1, time_delay * s1)
      return as_strided(X, shape=shape_new, strides=strides_new)
  
file_path: pyts/pyts/image/recurrence.py
imports: import numpy
  from math import ceil
  from numpy.lib.stride_tricks import as_strided
  from sklearn.base import BaseEstimator
  from sklearn.utils.validation import check_array
  from ..base import UnivariateTransformerMixin
label_desc: Use image node_id 1 for calling a global function with example usage: _trajectories(X, dimension, time_delay) and returns: as_strided