def main():
config = read_config()
dbc = DBScanner(config)
data = get_data(config)
dbc.dbscan(data)
def main():
config = {'eps': 2.5, 'min_pts': 2, 'dim': 2}
dbc = DBScanner(config)
data = get_data(config)
dbc.dbscan(data)
def post(self):
args = parser.parse_args()
data = {'points': args['points']}
def jsonTransformLib(s):
return json.loads(str(s).replace("'", '"'))
def libTransformDbScan(s):
return dict(id = int(s['nro_oc']), value = [float(s['lat']), float(s['lng'])])
map_iterator = map(jsonTransformLib, data['points'])
output_list = list(map_iterator)
lib_iterator = map(libTransformDbScan, output_list)
lib_list = list(lib_iterator)
config = read_config()
dbc = DBScanner(config)
dbc.dbscan(lib_list)
msg = dbc.getData()
return msg, 201
def main():
config = read_config()
dbc = DBScanner(config)
data = get_data(config)
print('data')
print(data)
dbc.dbscan(data)
dbc.export()
config = {}
try:
with open(CONFIG, 'rb') as file_obj:
for line in file_obj:
if line[0] != '#' and line.strip() != '':
key, value = line.split('=')
if '.' in value.strip():
config[key.strip()] = float(value.strip())
else:
config[key.strip()] = int(value.strip())
except:
print("Error reading the configuration file.\
expected lines: param = value \n param = {eps, min_pts, dim}, \
value = {float, int, int}")
sys.exit()
return config
if __name__ == "__main__":
CONFIG = 'config.txt'
DATA = 'data/abc.csv'
# DATA = 'data/jain.csv'
# DATA = 'data/dummy.csv'
config = read_config()
dbc = DBScanner(config)
data = get_data(config)
dbc.dbscan(data)
dbc.export()
if __name__ == "__main__":
# 参数初始化
min_pts = 4 # 最少有6个点
l = 4
slope = 0.1
filepath = 'abc.csv'
data = readData(filepath)
distanceMatrix = calDistanceMatrix(data)
distanceList = getKdistance(min_pts, distanceMatrix)
x = range(len(distanceList))
plt.figure()
plt.plot(x, distanceList)
#plt.show()
epsCandidate = calEpsCandidate(distanceList, l, slope)
while len(epsCandidate) == 0:
l = input("请输入向前找的点数")
slope = input("请输入期望的斜率阈值")
epsCandidate = calEpsCandidate(distanceList, l, slope)
# 现在参数确定了，min_pts还有eps已知，data已知，可以来DBSCAN聚类了
eps = epsCandidate[int(len(epsCandidate) / 2)]
config = {'eps': eps, 'min_pts': min_pts, 'dim': 2}
dbc = DBScanner(config)
dbc.dbscan(data)