def test_array(self):
t = fromiter(self.gen(), self.ds, self.p)
shape, dtype = to_numpy(t.datashape)
shape_orig, dtype_orig = to_numpy(self.ds)
self.assertEqual(dtype, dtype_orig)
self.assertEqual(len(shape), 1)
self.assertEqual(shape[0], self.count)
def test_array(self):
t = fromiter(self.gen(), self.ds, self.p)
shape, dtype = to_numpy(t.datashape)
shape_orig, dtype_orig = to_numpy(self.ds)
self.assertEqual(dtype, dtype_orig)
self.assertEqual(len(shape), 1)
self.assertEqual(shape[0], self.count)
def build_array(array_name, rows):
if not os.path.exists(array_name):
ds = 'x, float'
p = params(clevel=5, storage=array_name)
t = fromiter((0.1*i for i in xrange(rows)),
dshape=ds, params=p)
t.commit()
else:
t = open(array_name)
return t
def build_array(array_name, rows):
if not os.path.exists(array_name):
ds = 'x, float'
p = params(clevel=5, storage=array_name)
t = fromiter((0.1*i for i in xrange(rows)),
dshape=ds, params=p)
t.commit()
else:
t = open(array_name)
return t
def test_dtw():
# note: ucr.dtw only supports float64 atm
count = 100
data = fromiter((sin(2*pi*i/count) for i in xrange(count)), 'x, float64')
query = data[50:60]
loc, dist = ucr.dtw(data, query, 0.1, verbose=False)
# these are stupid, mostly just to check for regressions
ok_ (isinstance(loc, (int, long)))
ok_ (isinstance(dist, float))
eq_ (loc, 50)
ok_ (dist < 1e-10 and dist >= 0.0)
def test_dtw():
# note: ucr.dtw only supports float64 atm
count = 100
data = fromiter((sin(2 * pi * i / count) for i in xrange(count)),
'x, float64')
query = data[50:60]
loc, dist = ucr.dtw(data, query, 0.1, verbose=False)
# these are stupid, mostly just to check for regressions
ok_(isinstance(loc, (int, long)))
ok_(isinstance(dist, float))
eq_(loc, 50)
ok_(dist < 1e-10 and dist >= 0.0)
def test_fromiter():
from blaze import fromiter, params
a = fromiter(xrange(10), 'x, float64', params=params(clevel=5))
