def test_relative_pseudo(hw, RE, db):
RE.subscribe(db.insert)
p = hw.pseudo3x3
p.set(1, 1, 1)
base_pos = p.position
# this triggers the merging code path
rs, = RE(
bp.relative_inner_product_scan([p], 5, p.pseudo1, -1, 1, p.pseudo2, -2,
-1))
tb1 = db[rs].table().drop('time', 1)
assert p.position == base_pos
# this triggers this does not
rs, = RE(
bp.relative_inner_product_scan([p], 5, p.real1, 1, -1, p.real2, 2, 1))
tb2 = db[rs].table().drop('time', 1)
assert p.position == base_pos
# same columns
assert set(tb1) == set(tb2)
# same number of points
assert len(tb1) == len(tb2)
def get_hint(c):
h = c.hints['fields']
return h[0] if h else c.name
for c in list(p.pseudo_positioners) + list(p.real_positioners):
col = get_hint(c)
print(col)
assert (tb1[col] == tb2[col]).all()
assert (tb1[get_hint(p.pseudo1)] == np.linspace(0, 2, 5)).all()
def test_reset_wrapper(hw, RE):
p = hw.pseudo3x3
m_col = MsgCollector()
RE.msg_hook = m_col
RE(bp.relative_inner_product_scan([], 1, p.pseudo1, 0, 1, p.pseudo2, 0, 1))
expecte_objs = [
p, None, None, p, None, p, None, None, p, None, None, p, p, None
]
assert len(m_col.msgs) == 14
assert [m.obj for m in m_col.msgs] == expecte_objs
def test_relative_pseudo(hw, RE, db):
RE.subscribe(db.insert)
p = hw.pseudo3x3
p.set(1, 1, 1)
base_pos = p.position
# this triggers the merging code path
rs, = RE(bp.relative_inner_product_scan([p],
5,
p.pseudo1, -1, 1,
p.pseudo2, -2, -1))
tb1 = db[rs].table().drop('time', 1)
assert p.position == base_pos
# this triggers this does not
rs, = RE(bp.relative_inner_product_scan([p],
5,
p.real1, 1, -1,
p.real2, 2, 1))
tb2 = db[rs].table().drop('time', 1)
assert p.position == base_pos
# same columns
assert set(tb1) == set(tb2)
# same number of points
assert len(tb1) == len(tb2)
def get_hint(c):
h = c.hints['fields']
return h[0] if h else c.name
for c in list(p.pseudo_positioners) + list(p.real_positioners):
col = get_hint(c)
print(col)
assert (tb1[col] == tb2[col]).all()
assert (tb1[get_hint(p.pseudo1)] == np.linspace(0, 2, 5)).all()
def test_reset_wrapper(hw, RE):
p = hw.pseudo3x3
m_col = MsgCollector()
RE.msg_hook = m_col
RE(bp.relative_inner_product_scan([], 1,
p.pseudo1, 0, 1,
p.pseudo2, 0, 1))
expecte_objs = [p, None, None,
p, None, p,
None, None, p,
None, None, p,
p, None]
assert len(m_col.msgs) == 14
assert [m.obj for m in m_col.msgs] == expecte_objs
def test_inner_product_dscan(RE, hw):
scan = bp.relative_inner_product_scan([hw.det], 3,
hw.motor1, 1, 3,
hw.motor2, 10, 30)
# 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': 7.0},
{'motor2': 38.0, '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_inner_product_dscan(RE, hw):
scan = bp.relative_inner_product_scan([hw.det], 3,
hw.motor1, 1, 3,
hw.motor2, 10, 30)
# 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': 7.0},
{'motor2': 38.0, '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 _gen(self):
return relative_inner_product_scan(self.detectors,
self.num,
*self.args,
md=self.md)
bec = BestEffortCallback()
RE.subscribe(bec)
RE.subscribe(db.insert)
# move motor to a reproducible location
RE(mov(motor1, 0))
RE(mov(motor2, 0))
RE(
relative_outer_product_scan([det4], motor1, -1, 0, 10, motor2, -2, 0, 20,
True))
RE(outer_product_scan([det4], motor1, -1, 0, 10, motor2, -2, 0, 20, True))
# move motor to a reproducible location
RE(mov(motor1, 0))
RE(mov(motor2, 0))
RE(relative_inner_product_scan([det4], 10, motor1, -1, 0, motor2, -2, 0))
RE(inner_product_scan([det4], 10, motor1, -1, 0, motor2, -2, 0))
# do it manually
from cycler import cycler
mot1_cycl = cycler(motor1, np.linspace(-1, 0, 10))
mot2_cycl = cycler(motor2, np.linspace(-2, 0, 10))
# inner product
inner_hints = {
'fields': [det4.name],
'dimensions': [([motor1.name, motor2.name], 'primary')]
}
RE(scan_nd([det4], mot1_cycl + mot2_cycl), hints=inner_hints)
from bluesky.plans import relative_inner_product_scan
from bluesky.callbacks import LiveTable
assert slt_mb2.connected
uids = RE(relative_inner_product_scan([em], 5, slt_mb2.o, 0, 1, slt_mb2.i, 0, 1,
md={'note': 'demo'}),
LiveTable([slt_mb2.o, slt_mb2.i, em]))
headers = db[uids]
columns = ['time', 'em_chan22']
name_template = '{scan_id}_{note}.csv'
for h in headers:
db.get_table(headers)[columns].to_csv(name_template.format(**h.start))
# or, in one line:
# db.get_table(db[uids])[['time', 'em_chan22']].to_csv('your_filename_here.csv')
RE.subscribe(db.insert)
# move motor to a reproducible location
RE(mov(motor1, 0))
RE(mov(motor2, 0))
RE(relative_outer_product_scan([det4], motor1, -1, 0, 10, motor2, -2,
0, 20, True))
RE(outer_product_scan([det4], motor1, -1, 0, 10, motor2, -2, 0, 20,
True))
# move motor to a reproducible location
RE(mov(motor1, 0))
RE(mov(motor2, 0))
RE(relative_inner_product_scan([det4], 10, motor1, -1, 0, motor2, -2,
0))
RE(inner_product_scan([det4], 10, motor1, -1, 0, motor2, -2, 0))
# do it manually
from cycler import cycler
mot1_cycl = cycler(motor1, np.linspace(-1, 0, 10))
mot2_cycl = cycler(motor2, np.linspace(-2, 0, 10))
# inner product
inner_hints = {'fields' : [det4.name],
'dimensions' : [ ([motor1.name, motor2.name],'primary')]}
RE(scan_nd([det4], mot1_cycl+mot2_cycl), hints=inner_hints)
from bluesky.plans import relative_inner_product_scan from bluesky.callbacks import LiveTable assert slt_mb2.connected RE(relative_inner_product_scan([em], 5, slt_mb2.o, 0, 1, slt_mb2.i, 0, 1), LiveTable([slt_mb2.o, slt_mb2.i, em]))
def d2scan(dets, *args, time=None, md=None):
args, time = _get_a2_args(*args, time=time)
total_points = int(args[-1])
yield from _pre_scan(dets, total_points=total_points, count_time=time)
return (yield from plans.relative_inner_product_scan(dets, *args, md=md,
per_step=one_nd_step))
from bluesky.plans import relative_inner_product_scan
from bluesky.callbacks import LiveTable
assert slt_mb2.connected
uids = RE(
relative_inner_product_scan([em],
5,
slt_mb2.o,
0,
1,
slt_mb2.i,
0,
1,
md={'note': 'demo'}),
LiveTable([slt_mb2.o, slt_mb2.i, em]))
headers = db[uids]
columns = ['time', 'em_chan22']
name_template = '{scan_id}_{note}.csv'
for h in headers:
db.get_table(headers)[columns].to_csv(name_template.format(**h.start))
# or, in one line:
# db.get_table(db[uids])[['time', 'em_chan22']].to_csv('your_filename_here.csv')
