def qrnn_test(data, loc, season): model = QRNNCV(tol=1e-2, hidden_nodes=[3], n_jobs=1, ntrails=3) #model = QRNN(tol=1e-2, ntrails=3) dmodel = DownscaleModel(data, model, season=season) dmodel.train(location={'lat': loc[0], 'lon': loc[1]}) return pandas.DataFrame(dmodel.get_results())
def mssl_test(data, loc, season): model = pMSSL(gamma=0.1, lambd=0.1) dmodel = DownscaleModel(data, model, season=season) dmodel.train() return pandas.DataFrame(dmodel.get_results())
def bma_test(data, loc, season): model = BMA() dmodel = DownscaleModel(data, model, season=season) dmodel.train(location={'lat': loc[0], 'lon': loc[1]}) return pandas.DataFrame(dmodel.get_results())
def lasso_test(data, loc, season): model = LassoCV(max_iter=2000, normalize=True) dmodel = DownscaleModel(data, model, season=season) dmodel.train(location={'lat': loc[0], 'lon': loc[1]}) return pandas.DataFrame(dmodel.get_results())
def mtlasso_test(data, loc, season): model = MultiTaskLassoCV(max_iter=2000, normalize=True) dmodel = DownscaleModel(data, model, season=season) dmodel.train() return pandas.DataFrame(dmodel.get_results())
def stepwiseregression_test(data, loc, season): model = BackwardStepwiseRegression() dmodel = DownscaleModel(data, model, season=season) dmodel.train(location={'lat': loc[0], 'lon': loc[1]}) return pandas.DataFrame(dmodel.get_results())