def testgendata():
fname = 'test2.dat'
querys = 1000
d = 2
k=3
bnds = ((-10,10),)*d
clsses = (0,1)
data = getflatcsv(fname)
kdt = kdtknn(k,method='mode')
kdt.addEvidence(data)
kdt.rebuildKDT()
stime = time.time()
for x in xrange(querys):
pnt = numpy.array(gendata.gensingle(d,bnds,clsses))
reslt = kdt.query(numpy.array([pnt[:-1]]))
print pnt,"->",reslt
etime = time.time()
print etime-stime,'/',querys,'=',(etime-stime)/float(querys),'avg wallclock time per query'
def testgendata():
fname = "test2.dat"
querys = 1000
d = 2
k = 3
bnds = ((-10, 10),) * d
clsses = (0, 1)
data = getflatcsv(fname)
kdt = KDTKNN(k)
kdt.addEvidence(data)
kdt.rebuildKDT()
stime = time.time()
for x in xrange(querys):
pnt = numpy.array(gendata.gensingle(d, bnds, clsses))
reslt = kdt.query(numpy.array([pnt[:-1]]))
print pnt, "->", reslt
etime = time.time()
print etime - stime, "/", querys, "=", (etime - stime) / float(querys), "avg wallclock time per query"
def testgendata():
fname = 'test2.dat'
querys = 1000
d = 2
k=3
bnds = ((-10,10),)*d
clsses = (0,1)
data = getflatcsv(fname)
kdt = kdtknn(k,method='mode')
kdt.addEvidence(data)
kdt.rebuildKDT()
stime = time.time()
for x in range(querys):
pnt = numpy.array(gendata.gensingle(d,bnds,clsses))
reslt = kdt.query(numpy.array([pnt[:-1]]))
print(pnt,"->",reslt)
etime = time.time()
print(etime-stime,'/',querys,'=',(etime-stime)/float(querys),'avg wallclock time per query')
def testgendata():
anchors = 200
fname = 'test2.dat'
querys = 1000
d = 2
k = 3
bnds = ((-10,10),)*d
clsses = (0,1)
foo = FastKNN(anchors,k)
data = getflatcsv(fname)
foo.addEvidence(data[:,:-1],data[:,-1])
foo.num_checks = 0
for x in range(querys):
pnt = numpy.array(gendata.gensingle(d,bnds,clsses))
foo.query(pnt[:-1])
if x % 50 == 0:
print(float(foo.num_checks)/float(x+1), end=' ')
print(x,"/",querys)
print("Average # queries:", float(foo.num_checks)/float(querys))
def testgendata():
anchors = 200
fname = 'test2.dat'
querys = 1000
d = 2
k = 3
bnds = ((-10, 10), ) * d
clsses = (0, 1)
foo = FastKNN(anchors, k)
data = getflatcsv(fname)
foo.addEvidence(data[:, :-1], data[:, -1])
foo.num_checks = 0
for x in range(querys):
pnt = numpy.array(gendata.gensingle(d, bnds, clsses))
foo.query(pnt[:-1])
if x % 50 == 0:
print(float(foo.num_checks) / float(x + 1), end=' ')
print(x, "/", querys)
print("Average # queries:", float(foo.num_checks) / float(querys))
