aa50234c0e3854567214a3109188ee9bedc33551,cde/BaseConditionalDensity.py,ConditionalDensity,_conditional_value_at_risk_mc_pdf,#ConditionalDensity#Any#Any#Any#Any#,221

Before Change

      p = self.pdf(x_cond_tiled, y_samples).flatten()
      q = exp_f.flatten()
      importance_weights = p / q
      cvar = np.mean(y_samples * importance_weights, axis=0) / alpha
      CVaRs[i] = cvar

    return CVaRs

After Change

    CVaRs = np.zeros(x_cond.shape[0])

    for i in range(x_cond.shape[0]):
      upper = float(VaRs[i])
      func_to_integrate = lambda y: y * np.squeeze(self._tiled_pdf(y, x_cond[i], n_samples_int))
      integral = numeric_integation(func_to_integrate, n_samples_int, lower, upper)
      CVaRs[i] = integral / alpha

    return CVaRs

Instances