def testit():
for f, f2 in [(self.frame, self.frame2),
(self.mixed, self.mixed2)]:
for op, op_str in [('add', '+'), ('sub', '-'), ('mul', '*'),
('div', '/'), ('pow', '**')]:
op = getattr(operator, op, None)
if op is not None:
result = expr._can_use_numexpr(op, op_str, f, f,
'evaluate')
self.assert_(result == (not f._is_mixed_type))
result = expr.evaluate(op,
op_str,
f,
f,
use_numexpr=True)
expected = expr.evaluate(op,
op_str,
f,
f,
use_numexpr=False)
assert_array_equal(result, expected.values)
result = expr._can_use_numexpr(op, op_str, f2, f2,
'evaluate')
self.assert_(result == False)
def testit():
for f, f2 in [(self.frame, self.frame2),
(self.mixed, self.mixed2)]:
f11 = f
f12 = f + 1
f21 = f2
f22 = f2 + 1
for op, op_str in [('gt', '>'), ('lt', '<'), ('ge', '>='),
('le', '<='), ('eq', '=='), ('ne', '!=')]:
op = getattr(operator, op)
result = expr._can_use_numexpr(op, op_str, f11, f12,
'evaluate')
self.assert_(result == (not f11._is_mixed_type))
result = expr.evaluate(op,
op_str,
f11,
f12,
use_numexpr=True)
expected = expr.evaluate(op,
op_str,
f11,
f12,
use_numexpr=False)
assert_array_equal(result, expected.values)
result = expr._can_use_numexpr(op, op_str, f21, f22,
'evaluate')
self.assert_(result == False)
def testit():
for f, f2 in [(self.frame, self.frame2), (self.mixed, self.mixed2)]:
for op, op_str in [("add", "+"), ("sub", "-"), ("mul", "*"), ("div", "/"), ("pow", "**")]:
op = getattr(operator, op)
result = expr._can_use_numexpr(op, op_str, f, f, "evaluate")
self.assert_(result == (not f._is_mixed_type))
result = expr.evaluate(op, op_str, f, f, use_numexpr=True)
expected = expr.evaluate(op, op_str, f, f, use_numexpr=False)
assert_array_equal(result, expected.values)
result = expr._can_use_numexpr(op, op_str, f2, f2, "evaluate")
self.assert_(result == False)
def testit():
for f, f2 in [ (self.frame, self.frame2), (self.mixed, self.mixed2) ]:
for op, op_str in [('add','+'),('sub','-'),('mul','*'),('div','/'),('pow','**')]:
op = getattr(operator,op)
result = expr._can_use_numexpr(op, op_str, f, f)
self.assert_(result == (not f._is_mixed_type))
result = expr.evaluate(op, op_str, f, f, use_numexpr=True)
expected = expr.evaluate(op, op_str, f, f, use_numexpr=False)
assert_array_equal(result,expected.values)
result = expr._can_use_numexpr(op, op_str, f2, f2)
self.assert_(result == False)
def testit():
for f, f2 in [(self.frame, self.frame2), (self.mixed, self.mixed2)]:
f11 = f
f12 = f + 1
f21 = f2
f22 = f2 + 1
for op, op_str in [("gt", ">"), ("lt", "<"), ("ge", ">="), ("le", "<="), ("eq", "=="), ("ne", "!=")]:
op = getattr(operator, op)
result = expr._can_use_numexpr(op, op_str, f11, f12, "evaluate")
self.assert_(result == (not f11._is_mixed_type))
result = expr.evaluate(op, op_str, f11, f12, use_numexpr=True)
expected = expr.evaluate(op, op_str, f11, f12, use_numexpr=False)
assert_array_equal(result, expected.values)
result = expr._can_use_numexpr(op, op_str, f21, f22, "evaluate")
self.assert_(result == False)
def testit():
for f, f2 in [ (self.frame, self.frame2), (self.mixed, self.mixed2) ]:
f11 = f
f12 = f + 1
f21 = f2
f22 = f2 + 1
for op, op_str in [('gt','>'),('lt','<'),('ge','>='),('le','<='),('eq','=='),('ne','!=')]:
op = getattr(operator,op)
result = expr._can_use_numexpr(op, op_str, f11, f12, 'evaluate')
self.assert_(result == (not f11._is_mixed_type))
result = expr.evaluate(op, op_str, f11, f12, use_numexpr=True)
expected = expr.evaluate(op, op_str, f11, f12, use_numexpr=False)
assert_array_equal(result,expected.values)
result = expr._can_use_numexpr(op, op_str, f21, f22, 'evaluate')
self.assert_(result == False)
nr_runs=5,
nr_init=9,
max_iter=30,
delta=0.1,
labels=None,
entropy_cutoff=None)
classes = m4.classify(dat)
m4.shortInitEM(dat, 5, 5, 5, 0.1)
m4.EM(seq3, 20, 0.1)
print "####Finish\n", m4
dat.printClustering(2, pred)
evaluate(pred, true)
# ----------------------------- Example 4 -----------------------------
m5 = MixtureModel(1, [1.0], [NormalDistribution(3.0, 2.5)])
seq4 = m5.sample(1800)
#print "var = ", variance(seq4)
m6 = MixtureModel(1, [1.0], [NormalDistribution(-1.5, 2.5)])
#m6.EM(seq4,1,5)
#print m6
#seq5 = numarray.zeros(900,numarray.Float)
#for i in range(900):
dat = DataSet() dat.fromArray(seq3) print "vorher ------\n", m4 pred = m4.cluster(dat, nr_runs=5, nr_init=9, max_iter=30, delta=0.1, labels=None, entropy_cutoff=None) classes = m4.classify(dat) m4.shortInitEM(dat, 5, 5, 5, 0.1) m4.EM(seq3, 20, 0.1) print "####Finish\n", m4 dat.printClustering(2, pred) evaluate(pred, true) # ----------------------------- Example 4 ----------------------------- m5 = MixtureModel(1, [1.0], [NormalDistribution(3.0, 2.5)]) seq4 = m5.sample(1800) # print "var = ", variance(seq4) m6 = MixtureModel(1, [1.0], [NormalDistribution(-1.5, 2.5)]) # m6.EM(seq4,1,5) # print m6 # seq5 = numarray.zeros(900,numarray.Float)