def acq_rel_grid_scan(
dets: list,
exposure: float,
wait: float,
start0: float, stop0: float, num0: int,
start1: float, stop1: float, num1: int
):
"""Make a plan of two dimensional grid scan."""
area_det = xpd_configuration["area_det"]
x_controller = xpd_configuration["x_controller"]
y_controller = xpd_configuration["y_controller"]
def per_step(detectors, step: dict, pos_cache):
""" customized step to ensure shutter is open before
reading at each motor point and close shutter after reading
"""
yield from bps.checkpoint()
for motor, pos in step.items():
yield from bps.mv(motor, pos)
yield from bps.sleep(wait)
yield from open_shutter_stub()
yield from bps.sleep(glbl["shutter_sleep"])
yield from bps.trigger_and_read(list(detectors) + list(step.keys()))
yield from close_shutter_stub()
plan = bp.rel_grid_scan(
[area_det],
x_controller, start0, stop0, num0,
y_controller, start1, stop1, num1,
snake_axes=True,
per_step=per_step
)
yield from _configure_area_det(exposure)
yield from plan
def test_rmesh_pseudo(hw, RE):
p3x3 = hw.pseudo3x3
p3x3.set(1, -2, 100)
init_pos = p3x3.position
sig = hw.sig
d = DocCollector()
RE.subscribe(d.insert)
rs = RE(
bp.rel_grid_scan([sig], p3x3.pseudo1, 0, 3, 5, p3x3.pseudo2, 7, 10, 7))
if RE.call_returns_result:
uid = rs.run_start_uids[0]
else:
uid = rs[0]
df = pd.DataFrame(
[_['data'] for _ in d.event[d.descriptor[uid][0]['uid']]])
for k in p3x3.describe():
assert k in df
for k in sig.describe():
assert k in df
assert all(df[sig.name] == 0)
assert all(df[p3x3.pseudo3.name] == 100)
assert len(df) == 35
assert min(df[p3x3.pseudo1.name]) == 1
assert init_pos == p3x3.position
def test_rmesh_pseudo(hw, RE):
p3x3 = hw.pseudo3x3
p3x3.set(1, -2, 100)
init_pos = p3x3.position
sig = hw.sig
d = DocCollector()
RE.subscribe(d.insert)
rs, = RE(bp.rel_grid_scan(
[sig],
p3x3.pseudo1, 0, 3, 5,
p3x3.pseudo2, 7, 10, 7, False))
df = pd.DataFrame([_['data']
for _ in d.event[d.descriptor[rs][0]['uid']]])
for k in p3x3.describe():
assert k in df
for k in sig.describe():
assert k in df
assert all(df[sig.name] == 0)
assert all(df[p3x3.pseudo3.name] == 100)
assert len(df) == 35
assert min(df[p3x3.pseudo1.name]) == 1
assert init_pos == p3x3.position
def multi_sample_grid(samples, dx, dy, num_x, num_y):
uids = []
for index, sample_metadata in samples.items():
yield from mv(motor1, positions[index])
uid = yield from rel_grid_scan(
[det],
motor1, -dx, dx, num_x,
motor2, -dy, dy, num_y, False, # False -> Do not "snake" path.
md=sample_metadata)
uids.append(uid)
return tuple(uids) # tuple because immutable is safer
def user_plan(x_range, nx, y_range, ny, count_time=0.2, sample_name="no name"):
motor_args = []
motor_args += [neat_stage.y, -y_range, y_range, ny]
motor_args += [neat_stage.x, -x_range, x_range, nx, False]
yield from bps.mv(mca.preset_real_time, count_time, scaler.preset_time,
count_time)
_md = {"sample_name": sample_name}
yield from bp.rel_grid_scan(
[mca, scaler],
*motor_args,
# per_step=None, # use default
per_step=optimize_energy_per_step,
md=_md)
def test_outer_product_dscan(RE, hw):
scan = bp.rel_grid_scan([hw.det],
hw.motor1, 1, 3, 3,
hw.motor2, 10, 20, 2, False)
# Note: motor1 is the first motor specified, and so it is the "slow"
# axis, matching the numpy convention.
hw.motor1.set(5)
hw.motor2.set(8)
expected_data = [
{'motor2': 18.0, 'det': 1.0, 'motor1': 6.0},
{'motor2': 28.0, 'det': 1.0, 'motor1': 6.0},
{'motor2': 18.0, 'det': 1.0, 'motor1': 7.0},
{'motor2': 28.0, 'det': 1.0, 'motor1': 7.0},
{'motor2': 18.0, 'det': 1.0, 'motor1': 8.0},
{'motor2': 28.0, 'det': 1.0, 'motor1': 8.0}]
for d in expected_data:
d.update({'motor1_setpoint': d['motor1']})
d.update({'motor2_setpoint': d['motor2']})
multi_traj_checker(RE, scan, expected_data)
def test_outer_product_dscan_snaked(RE, hw):
scan = bp.rel_grid_scan([hw.det],
hw.motor1, 1, 3, 3,
hw.motor2, 10, 20, 2, True)
# Note: motor1 is the first motor specified, and so it is the "slow"
# axis, matching the numpy convention.
hw.motor1.set(5)
hw.motor2.set(8)
expected_data = [
{'motor2': 18.0, 'det': 1.0, 'motor1': 6.0},
{'motor2': 28.0, 'det': 1.0, 'motor1': 6.0},
{'motor2': 28.0, 'det': 1.0, 'motor1': 7.0},
{'motor2': 18.0, 'det': 1.0, 'motor1': 7.0},
{'motor2': 18.0, 'det': 1.0, 'motor1': 8.0},
{'motor2': 28.0, 'det': 1.0, 'motor1': 8.0}]
for d in expected_data:
d.update({'motor1_setpoint': d['motor1']})
d.update({'motor2_setpoint': d['motor2']})
multi_traj_checker(RE, scan, expected_data)
def relgridscan(self,
motor1,
start1,
stop1,
nstep1,
motor2,
start2,
nstop2,
nstep2,
nEvents,
record=True):
daq.configure(nEvents, record=record, controls=[motor1, motor2])
RE(
rel_grid_scan([daq],
motor1,
start1,
stop1,
nstep1,
motor2,
start2,
nstop2,
nstep2,
snake_axes=True))
def test_rmesh_pseudo(hw, RE):
p3x3 = hw.pseudo3x3
p3x3.set(1, -2, 100)
init_pos = p3x3.position
sig = hw.sig
d = DocCollector()
RE.subscribe(d.insert)
rs, = RE(
bp.rel_grid_scan([sig], p3x3.pseudo1, 0, 3, 5, p3x3.pseudo2, 7, 10, 7,
False))
df = pd.DataFrame([_['data'] for _ in d.event[d.descriptor[rs][0]['uid']]])
for k in p3x3.describe():
assert k in df
for k in sig.describe():
assert k in df
assert all(df[sig.name] == 0)
assert all(df[p3x3.pseudo3.name] == 100)
assert len(df) == 35
assert min(df[p3x3.pseudo1.name]) == 1
assert init_pos == p3x3.position
def _gen(self):
return rel_grid_scan(self.detectors, *self.args, md=self.md)
def test_simple_rel_grid_scan():
RE = RunEngine()
hardware = yaqc_bluesky.Device(39424)
sensor = yaqc_bluesky.Device(39425)
RE(rel_grid_scan([sensor], hardware, -1, 1, 15))
# Wilson's samples confgiure3 = configure_area_det(pe1c, 120, 0.2) plan10 = bp.count([pe1c], per_shot=my_take_reading) plan11 = bp.count([pe1c], per_shot=my_take_reading) plan12 = bp.count([pe1c], per_shot=my_take_reading) plan13 = bp.count([pe1c], per_shot=my_take_reading) plan14 = bp.count([pe1c], per_shot=my_take_reading) plan15 = bp.count([pe1c], per_shot=my_take_reading) plan16 = bp.count([pe1c], per_shot=my_take_reading) plan17 = bp.count([pe1c], per_shot=my_take_reading) plan18 = bp.count([pe1c], per_shot=my_take_reading) plan19 = bp.count([pe1c], per_shot=my_take_reading) # Yevgeny's samples configure4 = configure_area_det(pe1c, 120, 0.2) plan20 = bp.rel_grid_scan([pe1c], motor, -3, 3, 3, per_step=my_per_step) plan21 = bp.rel_grid_scan([pe1c], motor, -3, 3, 3, per_step=my_per_step) plan22 = bp.rel_grid_scan([pe1c], motor, -3, 3, 3, per_step=my_per_step) plan23 = bp.rel_grid_scan([pe1c], motor, -3, 3, 3, per_step=my_per_step) plan24 = bp.rel_grid_scan([pe1c], motor, -3, 3, 3, per_step=my_per_step) # Hunter's samples configure5 = configure_area_det(pe1c, 120, 0.2) plan25 = bp.rel_grid_scan([pe1c], motor, -3, 3, 3, per_step=my_per_step) plan26 = bp.rel_grid_scan([pe1c], motor, -3, 3, 3, per_step=my_per_step) plan27 = bp.rel_grid_scan([pe1c], motor, -3, 3, 3, per_step=my_per_step) plan28 = bp.rel_grid_scan([pe1c], motor, -3, 3, 3, per_step=my_per_step) # Wenhu's samples configure6 = configure_area_det(pe1c, 120, 0.2) plan29 = bp.count([pe1c], 3, 5, per_shot=my_take_reading)