code: def validate_first_step(first_step, t0, t_bound):
      """Assert that first_step is valid and return it."""
      if first_step <= 0:
          raise ValueError("`first_step` must be positive.")
      if first_step > np.abs(t_bound - t0):
          raise ValueError("`first_step` exceeds bounds.")
      return first_step
  
file_path: scipy/scipy/integrate/_ivp/common.py
imports: from itertools import groupby
  from warnings import warn
  import numpy
  from scipy.sparse import find, coo_matrix
label_desc: Use image node_id 1 for calling a global function with example usage: validate_first_step(first_step, t0, t_bound) and returns: first_step