def test_db_get():
dbName = "/tmp/test2.dbdb"
if os.path.exists(dbName):
os.remove(dbName)
db = lab10.connect(dbName)
db.set("rahul", "aged")
db.set("pavlos", "aged")
db.set("kobe", "stillyoung")
db.commit()
db.close()
db = lab10.connect("/tmp/test2.dbdb")
assert db.get("rahul") == "aged"
db.commit()
db.close()
def test_db_get_error():
dbName = "/tmp/test2.dbdb"
if os.path.exists(dbName):
os.remove(dbName)
db = lab10.connect(dbName)
db.set(4.4, "ts484.dat")
with raises(KeyError):
db.get(3.9)
db.commit()
db.close()
def test_db_get_All_LTE():
dbName = "/tmp/test2.dbdb"
if os.path.exists(dbName):
os.remove(dbName)
db = lab10.connect(dbName)
db.set(4.4, "ts484.dat")
db.set(0.0, "ts3.dat") #vantagePT
db.set(1.3, "ts82.dat")
db.set(2.9, "ts84.dat")
db.set(2.3, "ts382.dat")
db.set(2.1, "ts52.dat")
db.set(1.8, "ts49.dat")
db.set(1.1, "ts77.dat")
db.set(5.3, "ts583.dat")
keys, vals = db.get_All_LTE(2.9)
assert keys == [0.0, 1.3, 2.9, 2.3, 2.1, 1.8, 1.1]
db.commit()
db.close()
'''
if __name__ == "__main__":
# Load in the TS to Evaluate
filename = sys.argv[1]
x = np.loadtxt(filename, delimiter=' ')
origTs = ts.TimeSeries(x[:,1],x[:,0])
time = np.arange(0.0, 1.0, 0.01)
testTs = origTs.interpolate(time)
# Find the Nearest vantagePt
minDist = float('inf')
for j in range(20):
dbName = "tsdb/db"+str(j)+".dbdb"
db = lab10.connect(dbName)
vantagePtFile = db.get(0)
x = np.loadtxt(vantagePtFile, delimiter=' ')
comparePt = ts.TimeSeries(x[:,1],x[:,0])
dist = 2*(1-ss.kernel_corr(comparePt,testTs))
if dist < minDist:
minDist = dist
minDbName = dbName
minVantagePtFile = vantagePtFile
#Connect to DB Referencing the Nearest vantagePT
db = lab10.connect(minDbName)
keys, filenames = db.get_All_LTE(float(2)*minDist)
nFiles = len(filenames)
#Dictionary Key File, Val = Distance to testTs
dbList = []
#Create TS Referencing
#The 20 randomally selected vantagePtFiles
for j in range(20):
fileName = 'tsdata/ts' + str(indexes[j]) + '.dat'
dbName = "tsdb/db" + str(j) + ".dbdb"
x = np.loadtxt(fileName, delimiter=' ')
vantagePt = ts.TimeSeries(x[:, 1], x[:, 0])
vantagePtList.append(vantagePt)
##Remove DB if it has previously been created
if os.path.exists(dbName):
os.remove(dbName)
# Connect to Databses
db = lab10.connect(dbName)
dbList.append(db)
#For all 20 Databases
#Loop through 1000 TimeSeries
#Add Key = Distance(vantagePt, comparePt)
#Value = comparePT's fileName
for i in range(1000):
fileName = 'tsdata/ts' + str(i) + '.dat'
x = np.loadtxt(fileName, delimiter=' ')
comparePt = ts.TimeSeries(x[:, 1], x[:, 0])
# Add Key,Value for ComparePt for all 20 Databases
for j in range(20):
dist = 2 * (1 - ss.kernel_corr(vantagePtList[j], comparePt))
dbList[j].set(dist, fileName)