def db_with_dark_and_scan() -> Broker:
"""A database with a dark run and a motor scan inside. The last one is light and the first one is dark."""
db = databroker.v2.temp()
dark_data = [{"pe1_image": np.zeros_like(NI_FRAMES)}]
dark_uid = str(uuid.uuid4())
for name, doc in gen_stream(dark_data, {"dark_frame": True}, uid=dark_uid):
db.v1.insert(name, doc)
light_data = [{
"pe1_image": NI_FRAMES,
"temperature": 0
}, {
"pe1_image": NI_FRAMES,
"temperature": 1
}, {
"pe1_image": NI_FRAMES,
"temperature": 3
}]
start = dict(**START_DOC)
start.update({
"sc_dk_field_uid": dark_uid,
"hints": {
"dimensions": [(["temperature"], "primary")]
},
"sample_name": "Ni"
})
for name, doc in gen_stream(light_data, start):
db.v1.insert(name, doc)
return db
def runs():
x = np.arange(0, 26, 0.1)
comp0 = gen_stream([{
"q": x,
"iq": np.sin(x)
}], {
"lsq_type": "component",
"sample_name": "c0"
})
comp1 = gen_stream([{
"q": x,
"iq": np.cos(x)
}], {
"lsq_type": "component",
"sample_name": "c1"
})
target = gen_stream([{
"q": x,
"iq": np.cos(x) + np.sin(x) + np.exp(x / 26)
}], {
"lsq_type": "target",
"lsq_comps": ["c0", "c1"],
"sample_name": "c2"
})
return comp0, comp1, target
def db_with_dark_and_light() -> Broker:
"""A database with a dark run and a light run inside. The last one is light and the first one is dark."""
db = databroker.v2.temp()
dark_data = [{"pe1_image": np.zeros_like(NI_FRAMES)}]
dark_uid = str(uuid.uuid4())
for name, doc in gen_stream(dark_data, {"dark_frame": True}, uid=dark_uid):
db.v1.insert(name, doc)
light_data = [{"pe1_image": NI_FRAMES}]
for name, doc in gen_stream(light_data,
dict(**START_DOC, sc_dk_field_uid=dark_uid)):
db.v1.insert(name, doc)
return db
def db_with_dark_and_calib() -> Broker:
"""A database with a dark run and a light run inside. The last one is light and the first one is dark."""
db = databroker.v2.temp()
dark_data = [{"pe1_image": np.zeros_like(NI_FRAMES)}]
dark_uid = str(uuid.uuid4())
for name, doc in gen_stream(dark_data, {"dark_frame": True}, uid=dark_uid):
db.v1.insert(name, doc)
light_data = [{"pe1_image": NI_FRAMES}]
for name, doc in gen_stream(
light_data,
dict(sample_composition="Ni",
sc_dk_field_uid=dark_uid,
detector="perkin_elmer",
is_calibration=True,
bt_wavelength=0.1917)):
db.v1.insert(name, doc)
return db
def array_stream():
return gen_stream([
{
"x0": np.zeros(3),
"x1": np.zeros(5)
},
{
"x0": np.ones(3),
"x1": np.ones(5)
},
], {})
def db_with_fake_an():
"""A database that has a fake analysis run."""
db = databroker.v2.temp()
for name, doc in gen_stream([],
{"an_config": {
"SECTION": {
"key": "value"
}
}}):
db.v1.insert(name, doc)
return db
def db_with_img_and_bg_img() -> Broker:
"""A database with a dark image, a background image run and a data image run inside. The first one is dark
image, the second one is background image, the third one is the data image."""
db = databroker.v2.temp()
sample_name = "Kapton"
dk_uid = str(uuid.uuid4())
dk_meta = {"dark_frame": True}
dk_data = [{"pe1_image": np.ones_like(NI_IMG)}]
bg_meta = {"sample_name": sample_name, "sc_dk_field_uid": dk_uid}
bg_data = [{"pe1_image": 2 * np.ones_like(NI_IMG)}]
img_data = [{"pe1_image": 2 * np.ones_like(NI_IMG) + NI_IMG}]
img_meta = dict(**START_DOC,
bkgd_sample_name=sample_name,
sc_dk_field_uid=dk_uid)
for name, doc in gen_stream(dk_data, dk_meta, uid=dk_uid):
db.v1.insert(name, doc)
for name, doc in gen_stream(bg_data, bg_meta):
db.v1.insert(name, doc)
for name, doc in gen_stream(img_data, img_meta):
db.v1.insert(name, doc)
return db
def ymax_stream(request):
data = [{
"ymax": 0,
"x0": 0,
"x1": 0
}, {
"ymax": 1,
"x0": 1,
"x1": 1
}, {
"ymax": 2,
"x0": 2,
"x1": 2
}]
return gen_stream(data, request.param)
def simple_stream():
return gen_stream([{"x": 1}], {})
def test_gen_stream(gen_stream_args):
stream = mod.gen_stream(*gen_stream_args)
for name, doc in stream:
print(name, doc)
