code: def explicit_step():
      """Creates a stepper function with explicit time marching scheme.
  
      Explicit time marching scheme is the simplest scheme for 1D PDEs.
      Given a space-discretized equation
  
      ```
      du/dt = A(t) u(t) + b(t)
      ```
      (here `u` is a value vector, `A` and `b` are the matrix and the vector defined
      by the PDE), it approximates the right-hand side with its value before the
      time step:
  
      ```
      (u(t2) - u(t1)) / (t2 - t1) = A(t1) u(t1) + b(t1)
      ```
      This scheme avoids any matrix inversions and thus is much faster than other
      schemes. It is, however, stable only with small time steps and is only first
      order accurate. Usually, Crank-Nicolson or Extrapolation schemes are
      preferable.
  
      More details can be found in `weighted_implicit_explicit.py` describing the
      weighted implicit-explicit scheme - explicit scheme is a special case
      with `theta = 1`.
  
      Returns:
        Callable to be used in finite-difference PDE solvers (see fd_solvers.py).
      """
  
      def step_fn(
          time,
          next_time,
          coord_grid,
          value_grid,
          boundary_conditions,
          second_order_coeff_fn,
          first_order_coeff_fn,
          zeroth_order_coeff_fn,
          inner_second_order_coeff_fn,
          inner_first_order_coeff_fn,
          num_steps_performed,
          dtype=None,
          name=None,
      ):
          """Performs the step."""
          del num_steps_performed
          name = name or "explicit_step"
          return parabolic_equation_step(
              time,
              next_time,
              coord_grid,
              value_grid,
              boundary_conditions,
              second_order_coeff_fn,
              first_order_coeff_fn,
              zeroth_order_coeff_fn,
              inner_second_order_coeff_fn,
              inner_first_order_coeff_fn,
              time_marching_scheme=explicit_scheme,
              dtype=dtype,
              name=name,
          )
  
      return step_fn
  
label_desc: Use image node_id 1 for calling a global function with example usage: explicit_step() and returns: step_fn, parabolic_equation_step