code: def cf_photosic_realistic(eps_and_d: np.ndarray) -> float:
      """eps_and_d is a vector composed in a first part with the epsilon values
      (the material used in each one of the layers), and in a second part with the
      thicknesses of each one of the layers, like in Bragg.
      Any number of layers can work. Basically I used between 4 and 50 layers,
      and the best results are generally obtained when the structure has between 10 and 20 layers.
      The epsilon values are generally comprised between 1.00 and 9.00.
      """
      dimension = int(eps_and_d.size / 2)
      eps = eps_and_d[0:dimension]
      d = eps_and_d[dimension : dimension * 2]
      epsd = np.array([eps, d])
      lam_min = 375
      lam_max = 750
      n_lam = 100
      theta = 0 * 180 / np.pi
      vlam = np.linspace(lam_min, lam_max, n_lam)
      scc = np.zeros(n_lam)
      Ab = np.zeros(n_lam)
      # spectrum=np.zeros(n_lam)
      for k in range(n_lam):
          # absorb=absorption(epsd,theta*pi/180,lam[k])
          lam = vlam[k]
          epsilon = np.append(1, np.append(epsd[0], epscSi(lam)))
          mu = np.ones(epsilon.size)
          type_ = np.arange(0, epsd[0].size + 2)
          hauteur = np.append(0, np.append(epsd[1], 30000))
          pol = 0
          absorb = absorption(
              lam, epsilon, mu, type_, hauteur, pol, theta
          )
          scc[k] = solar(lam)
          Ab[k] = absorb[len(absorb) - 1]
      max_scc = np.trapz(scc, vlam)
      j_sc = np.trapz(scc * Ab, vlam)
      CE = j_sc / max_scc
      cost = 1 - CE
      return cost
  
file_path: nevergrad/nevergrad/functions/photonics/photonics.py
imports: import typing
  from pathlib import Path
  import numpy
  from scipy.linalg import toeplitz
label_desc: Use image node_id 15 for calling a global function with example usage: cf_photosic_realistic(eps_and_d) and returns: cost