from ExtractResult import Result from Fit import Linear_fit from Transformation import EnelWindSpeedTransformation import numpy as np file_coord = np.load("ENEL_2014/Coord.npz") Coord = file_coord["Coord"] Coord_turb = file_coord["Coord_turb"] power_curve = file_coord["power_curve"] file = "ENEL_2014/Enel_dataset.npz" results = Result(file, "lasso") XTrain, YTrain, XTest, YTest = results.extract_train_test() enel_transf = EnelWindSpeedTransformation() XTrain, dict_ = enel_transf.transform(XTrain) XTest, dict_ = EnelWindSpeedTransformation().transform(XTest) for k in range(5,10): print(k, "vicini") turbine_dict = find_nearest_turbine(Coord,Coord_turb,k) XTrain_, output_dict = enel_transf.nearest_mean_turbine(turbine_dict,dict_,XTrain, power_curve) print(XTrain_.shape) XTest_, _ = enel_transf.nearest_mean_turbine(turbine_dict,dict_,XTest,power_curve) print(XTest_.shape) Linear_fit().fitting(XTrain_, YTrain, XTest_,YTest) #Power_fit().fitting(XTrain, YTrain, XTest,YTest)
from utility import generate_samples_dynamic_set, get_current_data, compute_mse, get_common_indexes, \ extract_chosen_indexes_from_start, center_test, find_nearest import sys file = "ENEL_2014/Enel_dataset.npz" results = Result(file, "lasso") sys.argv[1:] = [int(x) for x in sys.argv[1:]] k = sys.argv[1] XTrain, YTrain, XTest, YTest = results.extract_train_test() ##transformation of data transf = EnelWindSpeedTransformation() XTrain_transf, dict_ = transf.transform(XTrain) XTest_transf, dict_ = transf.transform(XTest) Coord = np.load("ENEL_2014/Coord.npz")["Coord"] neight_= find_nearest(Coord,k) XTrain_transf = transf.nearest_products_levels(neight_,dict_,XTrain) XTest_transf = transf.nearest_products_levels(neight_,dict_,XTest) ##center data XTrain_noCenter, XVal_noCenter, YTrain_noCenter, YVal_noCenter = train_test_split(XTrain_transf, YTrain, test_size=0.33,random_state=0) XTrain_, YTrain_, X_mean, y_mean, X_std = center_data(XTrain_noCenter, YTrain_noCenter, fit_intercept=True, normalize = True) XVal_, YVal_ = center_test(XVal_noCenter,YVal_noCenter,X_mean,y_mean,X_std)