def down(citynum, methodnum): cityname = [ 'tehachapi', 'cheyenne', 'palmsprings', 'lasvegas', 'lancaster' ] method = [ 'KMeans', 'SpectralClustering', 'AgglomerativeClustering', 'Birch' ] target_idx = NREL.park_id[cityname[citynum]] year_from, year_to = 2004, 2006 if sys.version_info < (3, ): mode = 'rU' else: mode = 'r' csvfile = 'cluster/' + method[methodnum] + '200.csv' pick = [] with open(csvfile, mode) as csv_arch: reader = csv.reader(csv_arch, delimiter=',') for row in reader: pick.append(int(row[0])) nrel = NREL() d = 0 turbines = nrel.fetch_nrel_meta_data_all() for row in turbines: turbine_index = np.int(row[0]) if (turbine_index != target_idx): if (pick[turbine_index - 1] == pick[target_idx - 1]): d = d + 1 for y in range(year_from, year_to + 1): measurement = nrel.fetch_nrel_data( row[0], y, ['date', 'corrected_score', 'speed'])
target_idx = NREL.park_id[cityname[citynum]] year_from, year_to = 2004, 2006 if sys.version_info < (3, ): mode = 'rU' else: mode = 'r' csvfile = 'cluster/' + method[methodnum] + '200.csv' pick = [] with open(csvfile, mode) as csv_arch: reader = csv.reader(csv_arch, delimiter=',') for row in reader: pick.append(int(row[0])) nrel = NREL() d = 0 turbines = nrel.fetch_nrel_meta_data_all() result = Windpark(target_idx, 0) for row in turbines: turbine_index = np.int(row[0]) if (turbine_index != target_idx): if (pick[turbine_index - 1] == pick[target_idx - 1]): d = d + 1 newturbine = Turbine(row[0], row[1], row[2], row[3], row[4], row[5], row[6]) for y in range(year_from, year_to + 1): measurement = nrel.fetch_nrel_data( row[0], y, ['date', 'corrected_score', 'speed']) if y == year_from: measurements = measurement else: measurements = np.concatenate((measurements, measurement))