def loglike_and_score(self, params):
        params = params.reshape(self.K, -1, order='F')
        cdf_dot_exog_params = self.cdf(np.dot(self.exog, params))
        loglike_value = np.sum(self.wendog * np.log(cdf_dot_exog_params))
        firstterm = self.wendog[:, 1:] - cdf_dot_exog_params[:, 1:]
        score_array = np.dot(firstterm.T, self.exog).flatten()
        return loglike_value, score_array
Return a dict mapping all job ids to job information
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/discrete/discrete_model.py/MNLogit.loglike_and_score--crossover with--dataset/ETHPy150Open saltstack/salt/salt/returners/local_cache.py/get_jids