def test_filter_so(self):
so = TestIndexObj().particles
so.make_persistent('test.particle')
raw_data = [((i, i * 0.1), (i * 0.2, i * 0.3, i * 0.4))
for i in range(10)]
la = lambda (
(pid, time),
(x, y, z)): x > 0 and x < 3 and y > 0 and y < 3 and z > 0 and z < 3
filtered = hecuba_filter(
lambda ((pid, time), (x, y, z)): x > 0 and x < 3 and y > 0 and y <
3 and z > 0 and z < 3, so.iteritems())
c1 = len(python_filter(la, raw_data))
c2 = len(python_filter(la, filtered))
self.assertEqual(c1, c2)
def test_filter_so_local_var(self):
so = TestIndexObj().particles
so.make_persistent('test.particle')
raw_data = [((i, i * 0.1), (i * 0.2, i * 0.3, i * 0.4))
for i in range(10)]
fx, tx, fy, ty, fz, tz = 0, 3, 0, 3, 0, 3
la = lambda (
(pid, time), (x, y, z)
): x > fx and x < tx and y > fy and y < ty and z > fz and z < tz
filtered = hecuba_filter(
lambda ((pid, time), (x, y, z)): x > fx and x < tx and y > fy and y
< ty and z > fz and z < tz, so.iteritems())
c1 = len(python_filter(la, raw_data))
c2 = len(python_filter(la, filtered))
self.assertEqual(c1, c2)
def test_filter_sampled2(self):
so = TestIndexObj().particles
so.make_persistent('test.particle')
import random
raw_data = [((i, i * 0.1), (i * 0.2, i * 0.3, i * 0.4))
for i in range(10)]
la = lambda \
((pid, time), (x, y, z)): x > 0 and x < 3 and y > 0 and y < 3 and z > 0 and z < 3 and random.random() < 1
filtered = hecuba_filter(
lambda ((pid, time), (x, y, z)): x > 0 and x < 3 and y > 0 and y <
3 and z > 0 and z < 3 and random.random() < 1, so.iteritems())
c1 = len(python_filter(la, raw_data))
f = [a for a in filtered]
c2 = len(python_filter(la, f))
self.assertEqual(filtered._qbeast_meta.precision, 1)
self.assertEqual(filtered._qbeast_meta.from_point, [0, 0, 0])
self.assertEqual(filtered._qbeast_meta.to_point, [3, 3, 3])
self.assertEqual(c1, c2)