def test_tune_centroid(RE, hw):
det = hw.det
motor = hw.motor
scan1 = bp.tune_centroid([det], 'det', motor, 0, 5, 0.1, 10, snake=True)
scan2 = bp.tune_centroid([det], 'det', motor, 0, 5, 0.01, 10, snake=True)
scan3 = bp.tune_centroid([det], 'det', motor, 0, 5, 0.1, 10, snake=False)
scan4 = bp.tune_centroid([det], 'det', motor, 5, 0, 0.1, 10, snake=False)
actual_traj = []
col = collector('motor', actual_traj)
counter1 = CallbackCounter()
counter2 = CallbackCounter()
RE(scan1, {'event': [col, counter1]})
RE(scan2, {'event': counter2})
#assert counter1.value > counter2.value
assert actual_traj[0] == 0
actual_traj = []
col = collector('motor', actual_traj)
RE(scan3, {'event': col})
monotonic_increasing = np.all(np.diff(actual_traj) > 0)
assert not monotonic_increasing
actual_traj = []
col = collector('motor', actual_traj)
RE(scan4, {'event': col})
monotonic_decreasing = np.all(np.diff(actual_traj) < 0)
assert not monotonic_decreasing
with pytest.raises(ValueError): # min step < 0
scan5 = bp.tune_centroid([det], 'det', motor, 5, 0, -0.1, 10, snake=False)
RE(scan5)
def test_adaptive_ascan(RE, hw):
scan1 = bp.adaptive_scan([hw.det], 'det', hw.motor, 0, 5, 0.1, 1, 0.1, True)
scan2 = bp.adaptive_scan([hw.det], 'det', hw.motor, 0, 5, 0.1, 1, 0.2, True)
scan3 = bp.adaptive_scan([hw.det], 'det', hw.motor, 0, 5, 0.1, 1, 0.1, False)
scan4 = bp.adaptive_scan([hw.det], 'det', hw.motor, 5, 0, 0.1, 1, 0.1, False)
actual_traj = []
col = collector('motor', actual_traj)
counter1 = CallbackCounter()
counter2 = CallbackCounter()
RE(scan1, {'event': [col, counter1]})
RE(scan2, {'event': counter2})
assert counter1.value > counter2.value
assert actual_traj[0] == 0
actual_traj = []
col = collector('motor', actual_traj)
RE(scan3, {'event': col})
monotonic_increasing = np.all(np.diff(actual_traj) > 0)
assert monotonic_increasing
actual_traj = []
col = collector('motor', actual_traj)
RE(scan4, {'event': col})
monotonic_decreasing = np.all(np.diff(actual_traj) < 0)
assert monotonic_decreasing
with pytest.raises(ValueError): # min step < 0
scan5 = bp.adaptive_scan([hw.det], 'det', hw.motor,
5, 0, -0.1, 1.0, 0.1, False)
RE(scan5)
def test_all():
c = CallbackCounter()
RE(stepscan(det, motor), subs={'all': c})
assert c.value == 10 + 1 + 2 # events, descriptor, start and stop
c = CallbackCounter()
token = RE.subscribe('all', c)
RE(stepscan(det, motor))
RE.unsubscribe(token)
assert c.value == 10 + 1 + 2
def test_all(RE, hw):
c = CallbackCounter()
RE(stepscan(hw.det, hw.motor), {'all': c})
assert c.value == 10 + 1 + 2 # events, descriptor, start and stop
c = CallbackCounter()
token = RE.subscribe(c)
RE(stepscan(hw.det, hw.motor))
RE.unsubscribe(token)
assert c.value == 10 + 1 + 2
def test_average_stream(RE, hw):
# Create callback chain
avg = AverageStream(10)
c = CallbackCounter()
d = DocCollector()
avg.subscribe(c)
avg.subscribe(d.insert)
# Run a basic plan
RE(stepscan(hw.det, hw.motor), {'all': avg})
assert c.value == 1 + 1 + 2 # events, descriptor, start and stop
# See that we made sensible descriptor
start_uid = d.start[0]['uid']
assert start_uid in d.descriptor
desc_uid = d.descriptor[start_uid][0]['uid']
assert desc_uid in d.event
evt = d.event[desc_uid][0]
assert evt['seq_num'] == 1
assert all([
key in d.descriptor[start_uid][0]['data_keys']
for key in evt['data'].keys()
])
# See that we returned the correct average
assert evt['data']['motor'] == -0.5 # mean of range(-5, 5)
assert evt['data']['motor_setpoint'] == -0.5 # mean of range(-5, 5)
assert start_uid in d.stop
assert d.stop[start_uid]['num_events'] == {'primary': 1}
def test_adaptive_ascan():
scan1 = AdaptiveAbsScan([det], 'det', motor, 0, 5, 0.1, 1, 0.1, True)
scan2 = AdaptiveAbsScan([det], 'det', motor, 0, 5, 0.1, 1, 0.2, True)
scan3 = AdaptiveAbsScan([det], 'det', motor, 0, 5, 0.1, 1, 0.1, False)
actual_traj = []
col = collector('motor', actual_traj)
counter1 = CallbackCounter()
counter2 = CallbackCounter()
RE(scan1, subs={'event': [col, counter1]})
RE(scan2, subs={'event': counter2})
assert_greater(counter1.value, counter2.value)
assert_equal(actual_traj[0], 0)
actual_traj = []
col = collector('motor', actual_traj)
RE(scan3, {'event': col})
monotonic_increasing = np.all(np.diff(actual_traj) > 0)
assert_true(monotonic_increasing)
def test_adaptive_dscan():
scan1 = AdaptiveDeltaScanPlan([det], 'det', motor, 0, 5, 0.1, 1, 0.1, True)
scan2 = AdaptiveDeltaScanPlan([det], 'det', motor, 0, 5, 0.1, 1, 0.2, True)
scan3 = AdaptiveDeltaScanPlan([det], 'det', motor, 0, 5, 0.1, 1, 0.1,
False)
actual_traj = []
col = collector('motor', actual_traj)
counter1 = CallbackCounter()
counter2 = CallbackCounter()
motor.set(1)
RE(scan1, subs={'event': [col, counter1]})
RE(scan2, subs={'event': counter2})
assert counter1.value > counter2.value
assert actual_traj[0] == 1
actual_traj = []
col = collector('motor', actual_traj)
RE(scan3, {'event': col})
monotonic_increasing = np.all(np.diff(actual_traj) > 0)
assert monotonic_increasing
def test_subscribe_msg():
assert RE.state == 'idle'
c = CallbackCounter()
def counting_stepscan(det, motor):
yield Msg('subscribe', None, 'start', c)
yield from stepscan(det, motor)
RE(counting_stepscan(det, motor)) # should advance c
assert c.value == 1
RE(counting_stepscan(det, motor)) # should advance c
assert c.value == 2
RE(stepscan(det, motor)) # should not
assert c.value == 2
def test_measure_average(RE, hw):
logger.debug("test_measure_average")
# Pseudo-plan to measure average and check values
def measure_plan(detectors):
yield from open_run()
ret = yield from measure_average(detectors, num=250)
assert ret['motor'] == 0.0
assert ret['motor_setpoint'] == 0.0
assert np.isclose(ret['noisy_det'], 1.0, atol=0.01)
yield from close_run()
# Execute plan
cnt = CallbackCounter()
RE(measure_plan([hw.motor, hw.noisy_det]), {'event': [cnt]})
# Check that we saw the right number of events
assert cnt.value == 250
def test_straight_through_stream(RE, hw):
# Just a stream that sinks the events it receives
ss = NegativeStream()
# Create callback chain
c = CallbackCounter()
d = DocCollector()
ss.subscribe(c)
ss.subscribe(d.insert)
# Run a basic plan
RE(stepscan(hw.det, hw.motor), {'all': ss})
# Check that our metadata is there
assert c.value == 10 + 1 + 2 # events, descriptor, start and stop
assert d.start[0]['stream_level'] == 'boring'
desc = d.descriptor[d.start[0]['uid']][0]
events = d.event[desc['uid']]
print(desc)
print([evt['data'] for evt in events])
assert all([
evt['data'][key] <= 0 for evt in events for key in evt['data'].keys()
])
assert all([key in desc['data_keys'] for key in events[0]['data'].keys()])
