class_docstr: Fit height of signal peak over background.
code: def nlnlike(self, params, endog):
      n_sig = params[0]
      n_bkg = params[1]
      if (n_sig < 0) or n_bkg < 0:
          return np.inf
      n_tot = n_bkg + n_sig
      alpha = endog
      sig = self.signal.pdf(alpha)
      bkg = self.background.pdf(alpha)
      sumlogl = np.sum(np.log((n_sig * sig) + (n_bkg * bkg)))
      sumlogl -= n_tot
      return -sumlogl
  
imports: import numpy
  from scipy import stats
  from statsmodels.base.model import GenericLikelihoodModel
  from numpy.testing import assert_array_less, assert_almost_equal, assert_allclose
label_desc: Use image node_id 4 for calling the TwoPeakLLHNoExog obj's underlying member method code with example usage: obj.nlnlike(params, endog) and returns: unknown, np