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))
