code: def _eval_for(f, interval, dt):
      """Return x and y for function `f` over `interval` and delta `dt`"""
      real_f = lambdify_t(f)
      f_mn, f_mx = sorted(interval)
      time = np.arange(
          f_mn, f_mx, float(dt)
      )  # time values with support for g
      vals = real_f(time).astype(float)
      return vals
  
imports: import itertools
  import numpy
  import sympy
  from scipy.interpolate import interp1d
  from sympy import DiracDelta, Symbol
  from sympy.utilities.lambdify import implemented_function, lambdify
  from nipy.algorithms.statistics.formula.formulae import Formula, Term
label_desc: Use image node_id 9 for calling a global function with example usage: _eval_for(f, interval, dt) and returns: vals