def _calcBatchUpdate(self, fitnesses):
        xdim = self.numParameters
        invSigma = inv(self.sigma)
        samples = self.allSamples[-self.batchSize:]
        phi = zeros((self.batchSize, self.numDistrParams / 1))
        phi[:, :xdim] = self._logDerivsX(samples, self.x, invSigma)
        phi[:, xdim:-1] = self._logDerivsFactorSigma(samples, self.x, invSigma, self.factorSigma)
        phi[:, -1] = 1

        update = dot(pinv2(phi), fitnesses)[:-1]
        return update
dataset/ETHPy150Open pybrain/pybrain/pybrain/optimization/distributionbased/nes.py/OriginalNES._calcBatchUpdate/operator `+` -> `/`