How to use the pysal.model.spreg.user_output function in pysal

def __init__(self, y, x, w,
                 max_iter=1, epsilon=0.00001, step1c=False,
                 vm=False, name_y=None, name_x=None,
                 name_w=None, name_ds=None):

        n = USER.check_arrays(y, x)
        USER.check_y(y, n)
        USER.check_weights(w, y, w_required=True)
        x_constant = USER.check_constant(x)
        BaseGM_Error_Het.__init__(
            self, y, x_constant, w.sparse, max_iter=max_iter,
            step1c=step1c, epsilon=epsilon)
        self.title = "SPATIALLY WEIGHTED LEAST SQUARES (HET)"
        self.name_ds = USER.set_name_ds(name_ds)
        self.name_y = USER.set_name_y(name_y)
        self.name_x = USER.set_name_x(name_x, x)
        self.name_x.append('lambda')
        self.name_w = USER.set_name_w(name_w, w)
        SUMMARY.GM_Error_Het(reg=self, w=w, vm=vm)

cols2regi='all', method='full', epsilon=0.0000001,
                 regime_lag_sep=False, regime_err_sep=False, cores=False, spat_diag=False,
                 vm=False, name_y=None, name_x=None,
                 name_w=None, name_ds=None, name_regimes=None):

        n = USER.check_arrays(y, x)
        USER.check_y(y, n)
        USER.check_weights(w, y, w_required=True)
        USER.check_spat_diag(spat_diag, w)
        name_y = USER.set_name_y(name_y)
        self.name_y = name_y
        self.name_x_r = USER.set_name_x(
            name_x, x) + [USER.set_name_yend_sp(name_y)]
        self.method = method
        self.epsilon = epsilon
        self.name_regimes = USER.set_name_ds(name_regimes)
        self.constant_regi = constant_regi
        self.n = n
        cols2regi = REGI.check_cols2regi(
            constant_regi, cols2regi, x, add_cons=False)
        self.cols2regi = cols2regi
        self.regimes_set = REGI._get_regimes_set(regimes)
        self.regimes = regimes
        self.regime_lag_sep = regime_lag_sep
        self._cache = {}
        self.name_ds = USER.set_name_ds(name_ds)
        self.name_w = USER.set_name_w(name_w, w)
        USER.check_regimes(self.regimes_set, self.n, x.shape[1])

        # regime_err_sep is ignored, always False

        if regime_lag_sep == True:

def GM_Lag_Regimes_Multi(self, y, x, w_i, w, regi_ids, cores=False,
                             yend=None, q=None, w_lags=1, lag_q=True,
                             robust=None, gwk=None, sig2n_k=False, cols2regi='all',
                             spat_diag=False, vm=False, name_y=None, name_x=None,
                             name_yend=None, name_q=None, name_regimes=None,
                             name_w=None, name_gwk=None, name_ds=None):
        #        pool = mp.Pool(cores)
        self.name_ds = USER.set_name_ds(name_ds)
        name_x = USER.set_name_x(name_x, x)
        name_yend.append(USER.set_name_yend_sp(name_y))
        self.name_w = USER.set_name_w(name_w, w_i)
        self.name_gwk = USER.set_name_w(name_gwk, gwk)
        results_p = {}
        """
        for r in self.regimes_set:
            w_r = w_i[r].sparse
            if system() == 'Windows':
                is_win = True
                results_p[r] = _work(*(y,x,regi_ids,r,yend,q,w_r,w_lags,lag_q,robust,sig2n_k,self.name_ds,name_y,name_x,name_yend,name_q,self.name_w,name_regimes))
            else:                
                results_p[r] = pool.apply_async(_work,args=(y,x,regi_ids,r,yend,q,w_r,w_lags,lag_q,robust,sig2n_k,self.name_ds,name_y,name_x,name_yend,name_q,self.name_w,name_regimes, ))
                is_win = False
        """
        for r in self.regimes_set:
            w_r = w_i[r].sparse
            if cores:

def __init__(self,bigy,bigX,w,regimes=None,nonspat_diag=True,spat_diag=False,\
        vm=False, epsilon=0.0000001,\
        name_bigy=None,name_bigX=None,name_ds=None,name_w=None,name_regimes=None):
        
        #need checks on match between bigy, bigX dimensions
        # check on variable names for listing results
        self.name_ds = USER.set_name_ds(name_ds)
        self.name_w = USER.set_name_w(name_w, w)
        self.n_eq = len(bigy.keys())        
        #initialize names - should be generated by sur_stack
        if name_bigy:
            self.name_bigy = name_bigy
        else: # need to construct y names
            self.name_bigy = {}
            for r in range(self.n_eq):
                yn = 'dep_var_' + str(r)
                self.name_bigy[r] = yn               
        if name_bigX is None:
            name_bigX = {}
            for r in range(self.n_eq):
                k = bigX[r].shape[1] - 1
                name_x = ['var_' + str(i + 1) + "_" + str(r+1) for i in range(k)]
                ct = 'Constant_' + str(r+1)  # NOTE: constant always included in X
                name_x.insert(0, ct)

def __init__(self, y, x, regimes, yend=None, q=None,
                 w=None, w_lags=1, lag_q=True,
                 robust=None, gwk=None, sig2n_k=False,
                 spat_diag=False, constant_regi='many',
                 cols2regi='all', regime_lag_sep=False, regime_err_sep=True,
                 cores=False, vm=False, name_y=None, name_x=None,
                 name_yend=None, name_q=None, name_regimes=None,
                 name_w=None, name_gwk=None, name_ds=None):

        n = USER.check_arrays(y, x)
        USER.check_y(y, n)
        USER.check_weights(w, y, w_required=True)
        USER.check_robust(robust, gwk)
        USER.check_spat_diag(spat_diag, w)
        name_x = USER.set_name_x(name_x, x, constant=True)
        name_y = USER.set_name_y(name_y)
        name_yend = USER.set_name_yend(name_yend, yend)
        name_q = USER.set_name_q(name_q, q)
        name_q.extend(
            USER.set_name_q_sp(name_x, w_lags, name_q, lag_q, force_all=True))
        self.name_regimes = USER.set_name_ds(name_regimes)
        self.constant_regi = constant_regi
        self.n = n
        cols2regi = REGI.check_cols2regi(
            constant_regi, cols2regi, x, yend=yend, add_cons=False)
        self.cols2regi = cols2regi

def __init__(self, flows, cost, cost_func='pow', o_vars=None, d_vars=None,
            origins=None, destinations=None, constant=True, framework='GLM',
            SF=None, CD=None, Lag=None, Quasi=False):
        n = User.check_arrays(flows, cost)
        #User.check_y(flows, n)
        self.n = n
        self.f = flows
        self.c = cost
        self.ov = o_vars
        self.dv = d_vars
        if type(cost_func) == str:
            if cost_func.lower() == 'pow':
                self.cf = np.log
                if (self.c==0).any():
                    raise ValueError("Zero values detected: cost function 'pow'"
                            "requires the logarithm of the cost variable which"
                            "is undefined at 0")
            elif cost_func.lower() == 'exp':
                self.cf = lambda x: x*1.0
        elif (type(cost_func) == FunctionType) | (type(cost_func) == np.ufunc):

def __init__(self, y, x, w, method='full', epsilon=0.0000001,
                 spat_diag=False, vm=False, name_y=None, name_x=None,
                 name_w=None, name_ds=None):
        n = USER.check_arrays(y, x)
        USER.check_y(y, n)
        USER.check_weights(w, y, w_required=True)
        x_constant = USER.check_constant(x)
        method = method.upper()
        BaseML_Lag.__init__(
            self, y=y, x=x_constant, w=w, method=method, epsilon=epsilon)
        # increase by 1 to have correct aic and sc, include rho in count
        self.k += 1
        self.title = "MAXIMUM LIKELIHOOD SPATIAL LAG" + \
            " (METHOD = " + method + ")"
        self.name_ds = USER.set_name_ds(name_ds)
        self.name_y = USER.set_name_y(name_y)
        self.name_x = USER.set_name_x(name_x, x)
        name_ylag = USER.set_name_yend_sp(self.name_y)
        self.name_x.append(name_ylag)  # rho changed to last position
        self.name_w = USER.set_name_w(name_w, w)

max_iter=1, epsilon=0.00001, step1c=False,
                 cores=False, inv_method='power_exp',
                 constant_regi='many', cols2regi='all',
                 regime_err_sep=False, regime_lag_sep=False,
                 vm=False, name_y=None, name_x=None,
                 name_yend=None, name_q=None,
                 name_w=None, name_ds=None, name_regimes=None):

        n = USER.check_arrays(y, x)
        self.step1c = step1c
        USER.check_y(y, n)
        USER.check_weights(w, y, w_required=True)
        name_x = USER.set_name_x(name_x, x, constant=True)
        self.name_y = USER.set_name_y(name_y)
        name_yend = USER.set_name_yend(name_yend, yend)
        name_q = USER.set_name_q(name_q, q)
        name_q.extend(
            USER.set_name_q_sp(name_x, w_lags, name_q, lag_q, force_all=True))

        cols2regi = REGI.check_cols2regi(
            constant_regi, cols2regi, x, yend=yend, add_cons=False)
        self.regimes_set = REGI._get_regimes_set(regimes)
        self.regimes = regimes
        USER.check_regimes(self.regimes_set, n, x.shape[1])
        self.regime_err_sep = regime_err_sep
        self.regime_lag_sep = regime_lag_sep

        if regime_lag_sep == True:
            if regime_err_sep == False:
                raise Exception("For spatial combo models, if spatial lag is set by regimes (regime_lag_sep=True), spatial error must also be set by regimes (regime_err_sep=True).")
            add_lag = [w_lags, lag_q]
        else:

self.name_w = USER.set_name_w(name_w, w)
        self.n = n
        self.y = y

        name_x = USER.set_name_x(name_x, x)
        if summ:
            name_yend = USER.set_name_yend(name_yend, yend)
            self.name_y = USER.set_name_y(name_y)
            name_q = USER.set_name_q(name_q, q)
        self.name_x_r = name_x + name_yend

        cols2regi = REGI.check_cols2regi(
            constant_regi, cols2regi, x, yend=yend)
        self.regimes_set = REGI._get_regimes_set(regimes)
        self.regimes = regimes
        USER.check_regimes(self.regimes_set, self.n, x.shape[1])
        self.regime_err_sep = regime_err_sep

        if regime_err_sep == True:
            if set(cols2regi) == set([True]):
                self._endog_error_regimes_multi(y, x, regimes, w, yend, q, cores,
                                                max_iter, epsilon, A1, cols2regi, vm,
                                                name_x, name_yend, name_q, add_lag)
            else:
                raise Exception("All coefficients must vary accross regimes if regime_err_sep = True.")
        else:
            x_constant = USER.check_constant(x)
            q, name_q = REGI.Regimes_Frame.__init__(self, q,
                                                    regimes, constant_regi=None, cols2regi='all', names=name_q)
            x, name_x = REGI.Regimes_Frame.__init__(self, x_constant,
                                                    regimes, constant_regi=None, cols2regi=cols2regi,
                                                    names=name_x)

def _work(y, x, w, regi_ids, r, robust, sig2n_k, name_ds, name_y, name_x, name_w, name_regimes):
    y_r = y[regi_ids[r]]
    x_r = x[regi_ids[r]]
    x_constant = USER.check_constant(x_r)
    if robust == 'hac':
        robust = None
    model = BaseOLS(y_r, x_constant, robust=robust, sig2n_k=sig2n_k)
    model.title = "ORDINARY LEAST SQUARES ESTIMATION - REGIME %s" % r
    model.robust = USER.set_robust(robust)
    model.name_ds = name_ds
    model.name_y = '%s_%s' % (str(r), name_y)
    model.name_x = ['%s_%s' % (str(r), i) for i in name_x]
    model.name_w = name_w
    model.name_regimes = name_regimes
    if w:
        w_r, warn = REGI.w_regime(w, regi_ids[r], r, transform=True)
        set_warn(model, warn)
        model.w = w_r
    return model