def test_merge(self):
e_si = si.Event()
# event test
events = [
db.Event(e_si, 3, "a"),
db.Event(e_si, 5, "b"),
db.Event.make_empty(e_si),
db.Event(e_si, 12, "c")
]
result = db.combine(*events)
self.assertEqual(result[0], "a")
self.assertEqual(result[1], "b")
self.assertEqual(result[2], "c")
self.assertTrue(np.array_equal(result.TS, np.asarray([3, 5, 12])))
self.assertEqual(result.SI, e_si)
# event empty test
empty_events = [db.Event.make_empty(e_si), db.Event.make_empty(e_si)]
empty_events_result = db.combine(*empty_events)
self.assertEqual(empty_events_result, db.Event.make_empty(e_si))
# event empty test 1
empty_event = [db.Event.make_empty(e_si)]
empty_event_result = db.combine(*empty_event)
self.assertEqual(empty_event_result, db.Event.make_empty(e_si))
def _split_data(self, signal, times, events):
result = db.make_empty(self._si)
while len(events) > 0 and len(signal) > 0:
gs = events.TS[0]
ts_index = np.array(times).searchsorted(gs)
if ts_index == 0 and times[0] > gs:
events = events[1:]
continue
if ts_index < len(times):
pos = ts_index + self._shift
if pos < 1:
events = events[1:]
continue
if len(times) >= (pos + self._window_size):
window_range = range(pos, pos + self._window_size)
wnd = db.Window(self._si, times[window_range], signal[window_range, ], events[0:1])
events = events[1:]
result = db.combine(result, wnd)
continue
break
else:
break
return result, events
def test_merge(self):
# window test
w_si = si.Window(3, 7, 250)
data_a = np.arange(1, 22).reshape((7, 3))
data_b = np.arange(22, 43).reshape((7, 3))
data_c = np.arange(43, 64).reshape((7, 3))
time_a = 3
time_b = 6
time_c = 35
A = db.Window(w_si, time_a, data_a, '1')
B = db.Window(w_si, time_b, data_b, '2')
C = db.Window(w_si, time_c, data_c, '3')
M = db.combine(A, B, C)
self.assertEqual(M[0], data_a)
self.assertEqual(M[1], data_b)
self.assertEqual(M[2], data_c)
self.assertTrue(np.array_equal(M.TS, [time_a, time_b, time_c]))
# self.assertNotEqual(db.SingleWindow(3, np.arange(1, 21)), np.arange(21, 41))
self.assertTrue(np.array_equal(M.metadata, ['1', '2', '3']))
self.assertEqual(M[0].metadata, '1')
def test_empty(self):
w_si = si.Window(5, 20, 250)
emptyWindows = [db.Window.make_empty(w_si), db.Window.make_empty(w_si)]
result2 = db.combine(*emptyWindows)
self.assertEqual(result2, db.Window.make_empty(w_si))
def test_merge_si_override(self):
si1 = si.Channels(1, 20, id=1)
si2 = si.Channels(1, 20, id=2)
si3 = si.Channels(1, 20, id=3)
A = db.Channels(si1, timeoption2ts(si1, 205), [1])
B = db.Channels(si2, timeoption2ts(si2, 206), [2])
merged = db.combine(A, B, si=si3)
expected = db.Channels(si3, timeoption2ts(si3, 206), [1, 2])
self.assertEqual(merged, expected)
def test_merge(self):
c_si = si.Channels(5, 20)
A = db.Channels(c_si, timeoption2ts(c_si, 205), np.arange(1, 26))
B = db.Channels(c_si, timeoption2ts(c_si, 215), np.arange(26, 76))
C = db.Channels(c_si, timeoption2ts(c_si, 224), np.arange(76, 121))
M = db.combine(A, B, C)
O = db.Channels(c_si, timeoption2ts(c_si, 224), np.arange(1, 121))
self.assertEqual(O, M)
def online(self, input_stream, events):
# combine signal
self._signal.extend(input_stream)
self._times.extend(input_stream.TS)
# combine events
if len(events) > 0:
self._events = db.combine(self._events, events)
(result, self._events) = self._split_data(self._signal, self._times, self._events)
return result
def check(self, i_si, blocks):
def code():
resonance.createOutput(resonance.input(0), 'out')
online = run.online([i_si], blocks, code)
offline = run.offline([i_si], blocks, code)
if len(blocks) > 0:
origin = db.combine(*blocks)
else:
origin = db.make_empty(i_si)
self.assertEqual(online['out'], origin)
self.assertEqual(online['out'], offline['out'])
def online(stream_info: Sequence[StreamInfo],
blocks: Sequence[db.Base],
code: code_type,
return_blocks: bool = False):
outputs = {}
id = 100
for i_si in stream_info:
i_si.online = True
if i_si.id is None:
i_si._id = id
id += 1
def process_queue():
queue = resonance.internal.pop_queue()
if len(queue) > 0:
for cmd, data in queue:
if cmd == 'createOutputStream':
outputs[data.name] = []
pass
if cmd == 'sendBlockToStream':
si, block = data
outputs[si.name].append(block)
pass
events.on_prepare(code, stream_info)
process_queue()
events.on_start()
process_queue()
for block in blocks:
events.on_data_block(block)
process_queue()
events.on_stop()
process_queue()
if return_blocks:
return outputs
else:
return {name: db.combine(*values) for name, values in outputs.items()}
def online(self, input):
return db.combine(
db.make_empty(self._si), *[
db.Event(self._si, block.TS[0:1], self._transform(block))
for block in input
])
def combine_blocks(si):
data = list(filter(lambda x: x.SI == si, blocks))
if len(data):
return db.combine(*data)
else:
return db.make_empty(si)
def offline(self, a, b):
result = db.combine(a, b, si=self._si)
order = np.argsort(result.TS)
result = result[order]
return result
