def test_plugins():
class EchoPlugin:
def get_events(self, header, a):
yield a
b = Broker(metadatastore.commands, filestore.api, {'a': EchoPlugin()})
hdr = b[-1]
assert 'echo-plugin-test' in list(b.get_events(hdr, a='echo-plugin-test'))
assert 'echo-plugin-test' not in list(b.get_events(hdr))
def main(args=None):
parser = create_parser()
ns = parser.parse_args(args)
nd = ns.__dict__
if ns.cmd in FACILITY_PARSER_MAP:
db = Broker.named(nd['db_name'])
db_path = db.get_config()['metadatastore']['config']['directory']
writer = NpyWriter(db.fs, db_path)
for n, d in FACILITY_PARSER_MAP[ns.cmd]['cmd'](nd['input_data']):
if n == 'descriptor':
for k in ['tof', 'intensity', 'error']:
d['data_keys'][k]['external'] = True
if n == 'event':
for k in ['tof', 'intensity', 'error']:
d['data'][k] = writer.write(d['data'][k])
d['filled'][k] = False
print(n)
pprint(d)
db.insert(n, d)
else:
db_config_path = os.path.expanduser('~/.config/databroker/'
'{}.yaml'.format(nd['name']))
path = os.path.expanduser(nd['path'])
config = {'description': 'lightweight personal database',
'metadatastore': {'module': 'databroker.headersource.sqlite',
'class': 'MDS',
'config': {'directory': path,
'timezone': 'US/Eastern'}},
'assets': {'module': 'databroker.assets.sqlite',
'class': 'Registry',
'config': {'dbpath': os.path.join(
path, 'database.sql')}}}
os.makedirs(path, exist_ok=True)
os.makedirs(os.path.split(db_config_path)[0], exist_ok=True)
with open(db_config_path, 'w', encoding='utf8') as f:
yaml.dump(config, f)
from databroker import Broker
db = Broker.named('hxn')
db_analysis = Broker.named('hxn_analysis')
from hxntools.handlers.xspress3 import Xspress3HDF5Handler
from hxntools.handlers.timepix import TimepixHDF5Handler
db.reg.register_handler(Xspress3HDF5Handler.HANDLER_NAME,
Xspress3HDF5Handler)
db.reg.register_handler(TimepixHDF5Handler._handler_name,
TimepixHDF5Handler, overwrite=True)
from databroker import Broker
db = Broker.named('hxn')
#db_analysis = Broker.named('hxn_analysis')
from hxntools.handlers.xspress3 import Xspress3HDF5Handler
from hxntools.handlers.timepix import TimepixHDF5Handler
db.reg.register_handler(Xspress3HDF5Handler.HANDLER_NAME,
Xspress3HDF5Handler)
db.reg.register_handler(TimepixHDF5Handler._handler_name,
TimepixHDF5Handler, overwrite=True)
# Set up a RunEngine and use metadata backed by a sqlite file.
from bluesky import RunEngine
from bluesky.utils import get_history
RE = RunEngine(get_history())
# Set up a Broker.
from databroker import Broker
db = Broker.named('csx')
# Subscribe metadatastore to documents.
# If this is removed, data is not saved to metadatastore.
RE.subscribe(db.insert)
# Set up SupplementalData.
from bluesky import SupplementalData
sd = SupplementalData()
RE.preprocessors.append(sd)
# Add a progress bar.
from bluesky.utils import ProgressBarManager
pbar_manager = ProgressBarManager()
RE.waiting_hook = pbar_manager
# Register bluesky IPython magics.
from bluesky.magics import BlueskyMagics
get_ipython().register_magics(BlueskyMagics)
# Set up the BestEffortCallback.
from bluesky.callbacks.best_effort import BestEffortCallback
bec = BestEffortCallback()
RE.subscribe(bec)
import time
import sys
from bluesky.simulators import summarize_plan
# Set up a RunEngine and use metadata backed by a sqlite file.
from bluesky import RunEngine
from bluesky.utils import get_history
RE = RunEngine({})
# Set up a Broker.
from databroker import Broker
db = Broker.named('iss')
db_analysis = Broker.named('iss-analysis')
# Subscribe metadatastore to documents.
# If this is removed, data is not saved to metadatastore.
RE.subscribe(db.insert)
# Set up SupplementalData.
from bluesky import SupplementalData
sd = SupplementalData()
RE.preprocessors.append(sd)
# Add a progress bar.
from timeit import default_timer as timer
from bluesky.utils import ProgressBarManager
pbar_manager = ProgressBarManager()
#RE.waiting_hook = pbar_manager
def configure_base(user_ns,
broker_name,
*,
bec=True,
epics_context=False,
magics=True,
mpl=True,
ophyd_logging=True,
pbar=True):
"""
Perform base setup and instantiation of important objects.
This factory function instantiates essential objects to data collection
environments at NSLS-II and adds them to the current namespace. In some
cases (documented below), it will check whether certain variables already
exist in the user name space, and will avoid creating them if so. The
following are added:
* ``RE`` -- a RunEngine
This is created only if an ``RE`` instance does not currently exist in
the namespace.
* ``db`` -- a Broker (from "databroker"), subscribe to ``RE``
* ``bec`` -- a BestEffortCallback, subscribed to ``RE``
* ``peaks`` -- an alias for ``bec.peaks``
* ``sd`` -- a SupplementalData preprocessor, added to ``RE.preprocessors``
* ``pbar_maanger`` -- a ProgressBarManager, set as the ``RE.waiting_hook``
And it performs some low-level configuration:
* creates a context in ophyd's control layer (``ophyd.setup_ophyd()``)
* turns out interactive plotting (``matplotlib.pyplot.ion()``)
* bridges the RunEngine and Qt event loops
(``bluesky.utils.install_kicker()``)
* logs ERROR-level log message from ophyd to the standard out
Parameters
----------
user_ns: dict
a namespace --- for example, ``get_ipython().user_ns``
broker_name : Union[str, Broker]
Name of databroker configuration or a Broker instance.
bec : boolean, optional
True by default. Set False to skip BestEffortCallback.
epics_context : boolean, optional
True by default. Set False to skip ``setup_ophyd()``.
magics : boolean, optional
True by default. Set False to skip registration of custom IPython
magics.
mpl : boolean, optional
True by default. Set False to skip matplotlib ``ion()`` at event-loop
bridging.
ophyd_logging : boolean, optional
True by default. Set False to skip ERROR-level log configuration for
ophyd.
pbar : boolean, optional
True by default. Set false to skip ProgressBarManager.
Returns
-------
names : list
list of names added to the namespace
Examples
--------
Configure IPython for CHX.
>>>> configure_base(get_ipython().user_ns, 'chx');
"""
ns = {} # We will update user_ns with this at the end.
# Set up a RunEngine and use metadata backed by a sqlite file.
from bluesky import RunEngine
from bluesky.utils import get_history
# if RunEngine already defined grab it
# useful when users make their own custom RunEngine
if 'RE' in user_ns:
RE = user_ns['RE']
else:
RE = RunEngine(get_history())
ns['RE'] = RE
# Set up SupplementalData.
# (This is a no-op until devices are added to it,
# so there is no need to provide a 'skip_sd' switch.)
from bluesky import SupplementalData
sd = SupplementalData()
RE.preprocessors.append(sd)
ns['sd'] = sd
if isinstance(broker_name, str):
# Set up a Broker.
from databroker import Broker
db = Broker.named(broker_name)
ns['db'] = db
else:
db = broker_name
RE.subscribe(db.insert)
if pbar:
# Add a progress bar.
from bluesky.utils import ProgressBarManager
pbar_manager = ProgressBarManager()
RE.waiting_hook = pbar_manager
ns['pbar_manager'] = pbar_manager
if magics:
# Register bluesky IPython magics.
from bluesky.magics import BlueskyMagics
get_ipython().register_magics(BlueskyMagics)
if bec:
# Set up the BestEffortCallback.
from bluesky.callbacks.best_effort import BestEffortCallback
_bec = BestEffortCallback()
RE.subscribe(_bec)
ns['bec'] = _bec
ns['peaks'] = _bec.peaks # just as alias for less typing
if mpl:
# Import matplotlib and put it in interactive mode.
import matplotlib.pyplot as plt
ns['plt'] = plt
plt.ion()
# Make plots update live while scans run.
from bluesky.utils import install_kicker
install_kicker()
if epics_context:
# Create a context in the underlying EPICS client.
from ophyd import setup_ophyd
setup_ophyd()
if not ophyd_logging:
# Turn on error-level logging, particularly useful for knowing when
# pyepics callbacks fail.
import logging
import ophyd.ophydobj
ch = logging.StreamHandler()
ch.setLevel(logging.ERROR)
ophyd.ophydobj.logger.addHandler(ch)
# convenience imports
# some of the * imports are for 'back-compatibility' of a sort -- we have
# taught BL staff to expect LiveTable and LivePlot etc. to be in their
# namespace
import numpy as np
ns['np'] = np
import bluesky.callbacks
ns['bc'] = bluesky.callbacks
import_star(bluesky.callbacks, ns)
import bluesky.plans
ns['bp'] = bluesky.plans
import_star(bluesky.plans, ns)
import bluesky.plan_stubs
ns['bps'] = bluesky.plan_stubs
import_star(bluesky.plan_stubs, ns)
# special-case the commonly-used mv / mvr and its aliases mov / movr4
ns['mv'] = bluesky.plan_stubs.mv
ns['mvr'] = bluesky.plan_stubs.mvr
ns['mov'] = bluesky.plan_stubs.mov
ns['movr'] = bluesky.plan_stubs.movr
import bluesky.preprocessors
ns['bpp'] = bluesky.preprocessors
import bluesky.callbacks.broker
import_star(bluesky.callbacks.broker, ns)
import bluesky.simulators
import_star(bluesky.simulators, ns)
user_ns.update(ns)
return list(ns)
from bluesky.utils import install_qt_kicker
install_qt_kicker()
print("Installing Qt Kicker...")
# Make ophyd listen to pyepics.
from ophyd import setup_ophyd
setup_ophyd()
# Set up a RunEngine and use metadata backed by a sqlite file.
from bluesky import RunEngine
from bluesky.utils import get_history
RE = RunEngine(get_history())
# Set up a Broker.
from databroker import Broker
db = Broker.named('fmx')
# Subscribe metadatastore to documents.
# If this is removed, data is not saved to metadatastore.
RE.subscribe(db.insert)
# Set up SupplementalData.
from bluesky import SupplementalData
sd = SupplementalData()
RE.preprocessors.append(sd)
# Add a progress bar.
# from bluesky.utils import ProgressBarManager
# pbar_manager = ProgressBarManager()
# RE.waiting_hook = pbar_manager
import networkx as nx
from databroker import Broker
from shed_streaming.translation import FromEventStream
from shed_streaming.replay import replay
db_path = '/home/christopher/ldrd_demo'
config = {'description': 'lightweight personal database',
'metadatastore': {'module': 'databroker.headersource.sqlite',
'class': 'MDS',
'config': {'directory': db_path,
'timezone': 'US/Eastern'}},
'assets': {'module': 'databroker.assets.sqlite',
'class': 'Registry',
'config': {'dbpath': db_path + '/database.sql'}}}
db = Broker.from_config(config)
def y():
suid = str(uuid.uuid4())
yield ('start', {'uid': suid,
'time': time.time()})
duid = str(uuid.uuid4())
yield ('descriptor', {'uid': duid,
'run_start': suid,
'name': 'primary',
'data_keys': {'det_image': {'dtype': 'int',
'units': 'arb'}},
'time': time.time()})
for i in range(5):
yield ('event', {'uid': str(uuid.uuid4()),
from seisidd.utility import print_dict
list_predefined_vars = lambda : print_dict(keywords_vars)
list_predefined_func = lambda : print_dict(keywords_func)
# --- get system info
HOSTNAME = socket.gethostname() or 'localhost'
USERNAME = getpass.getuser() or '6-BM-A user'
keywords_vars['HOSTNAME'] = 'host name'
keywords_vars['USERNAME'] = '******'
# --- setup metadata handler
from databroker import Broker
metadata_db = Broker.named("mongodb_config")
keywords_vars['metadata_db'] = 'Default metadata handler'
# --- setup RunEngine
from bluesky import RunEngine
from bluesky.callbacks.best_effort import BestEffortCallback
keywords_func['get_runengine'] = 'Get a bluesky RunEngine'
def get_runengine(db=None):
"""
Return an instance of RunEngine. It is recommended to have only
one RunEngine per session.
"""
RE = RunEngine({})
db = metadata_db if db is None else db
RE.subscribe(db.insert)
from databroker import Broker
db = Broker.named('csx2')
import nslsii
nslsii.configure_base(get_ipython().user_ns, db)
# make sure Best Effort Callback does not plot the baseline readings
bec.noplot_streams.append('pgm_energy_monitor')
### comment this out to:
### disable the zmq servce and re-enable best effort callback plotting locally
bec.disable_plots()
from bluesky.callbacks.zmq import Publisher
pub = Publisher('xf23id-ca:5577')
RE.subscribe(pub)
#####
# TODO not need this
from epics import caget, caput
from amostra.client.commands import SampleReference, ContainerReference
# Optional: set any metadata that rarely changes.
# convenience imports
def ensure_proposal_id(md):
if 'proposal_id' not in md:
raise ValueError("Please run user_checkin() first")
print(f"creating {omnia_xy_index_fp}")
t0 = time.time()
grid_x = list()
grid_y = list()
uids = list()
for h in self.dbr(sample_name="omnia"):
grid_x.append(h.start["Grid_X"])
grid_y.append(h.start["Grid_Y"])
uids.append(h.start["uid"])
df = pd.DataFrame(zip(grid_x, grid_y, uids),
columns=("Grid_X", "Grid_Y", "uid"))
df.to_csv(omnia_xy_index_fp, sep="\t")
print(f"finished {omnia_xy_index_fp} in {time.time()-t0:.3}s")
from databroker import Broker
from ophyd.sim import hw
dbr = Broker.named("pdf")
sim = hw()
omnia_det = OmniaDetector(
dbr=dbr,
name="omnia_det",
motor1=sim.motor1,
motor_field1="motor1",
motor2=sim.motor2,
motor_field2="motor2",
)
uids = ('79b54d30-7fff-4a24-80c1-1d5cb3e71373',
'b0b7a12b-ec80-47a1-ac24-c86eb9ebf464',
'c1e766fa-dff6-4747-877a-5a26de278ca4',
'5de9a73c-367e-43a9-8377-80e945ad165f')
from databroker import Broker
db = Broker.named('xpd')
peak1_c = db[uids[0]].table()
peak1_f = db[uids[1]].table()
peak2_c = db[uids[2]].table()
peak2_f = db[uids[3]].table()
peaks_x = list(peak1_f.th_cal)
peaks_y = list(peak1_f.sc_chan1)
peaks_x.extend(list(peak2_f.th_cal))
peaks_y.extend(list(peak2_f.sc_chan1))
xdata = peaks_x
ydata = peaks_y
import matplotlib.pyplot as plt
theta_offset = -35.26
wguess = .1878
max_step = .004
D = 'Si'
detector_name = 'sc_chan1'
theta_offset = -35.26
guessed_sigma = .0012
nsigmas = 15
import h5py
from databroker import Broker
from databroker._core import register_builtin_handlers
db = Broker.named('xfm')
register_builtin_handlers(db.reg)
# srx detector, to be moved to filestore
from databroker.assets.handlers import Xspress3HDF5Handler, HandlerBase
class BulkXSPRESS(HandlerBase):
HANDLER_NAME = 'XPS3_FLY'
def __init__(self, resource_fn):
self._handle = h5py.File(resource_fn, 'r')
def __call__(self):
return self._handle['entry/instrument/detector/data'][:]
db.reg.register_handler(BulkXSPRESS.HANDLER_NAME, BulkXSPRESS, overwrite=True)
class ZebraHDF5Handler(HandlerBase):
HANDLER_NAME = 'ZEBRA_HDF51'
def __init__(self, resource_fn):
self._handle = h5py.File(resource_fn, 'r')
def __call__(self, column):
from databroker import Broker
db = Broker.named("iss")
import sys
sys.path.insert(0, '/home/xf08id/Repos/workflows')
import interpolation
data = dict()
data['requester'] = "xf08id-ws02"
#data['uid'] = "55f14401-8c60-4474-a24e-62b7722c933c"
data['uid'] = db[-1].start['uid']
store =data.copy()
signal = None
context = None
interpolation.create_req_func(data, store, signal, context)
interpolation.process_run_func(data, store, signal, context)
def interpolate_and_save(db_name,
db_analysis_name,
uid,
mono_name='mono1_enc',
pulses_per_degree=None):
''' Interpolate measured data and save to an analysis store.
Parameters
----------
# TODO : change to config (don't rely on Broker.named which explores
local directory)
db_config: str
the name the database (in /etc/databroker/name.yml)
db_analysis_config : str
the name of the analysis database (in /etc/databroker/name.yml)
uid : str
The uid of the data set
mono_name : str
the monochromator encoder name. Defaults to 'mono1_enc'
pulses_per_degree : float
pulses per degree of the encoder from the monochromator
defaults to the current setup at QAS
Returns
-------
interp_df : the interpolated data
bin_df : the binned data if e0 is set
'''
# the pulses per degree, hard coded for now
# TODO : Make a signal to pb1.enc1
# and have it passed at configuration_attrs
# (which results in data in descriptor)
if pulses_per_degree is None:
ppd = 23600 * 400 / 360
else:
ppd = pulses_per_degree
db = Broker.named(db_name)
hdr = db[uid]
start = hdr.start
if 'e0' not in start:
e0 = 8979
print("Warning, e0 not in start, setting to Cu: {}".format(e0))
else:
e0 = float(hdr.start['e0'])
db_analysis = Broker.named(db_analysis_name)
# the important part of Bruno's code that does the interpolation
gen_parser = xasdata.XASdataGeneric(ppd, db=db, mono_name='mono1_enc')
gen_parser.load(uid)
# data saves in gen_parser.interp_df
gen_parser.interpolate()
# useful command for debugging, looking at energy
# this is automatically run by gen_parser
#energy = encoder2energy(res[:,3], ppd)
PREFIX = "/nsls2/xf07bm/data/interpolated_data"
write_path_template = PREFIX + '/%Y/%m/%d/'
DIRECTORY = datetime.now().strftime(write_path_template)
scan_id = hdr.start['scan_id']
md = hdr.start
filename = 'xas_' + md.get("name", str(uuid4())[:6]) + "_" + str(scan_id)
os.makedirs(DIRECTORY, exist_ok=True)
filepath = DIRECTORY
# file is exported
fileout = gen_parser.export_trace(filename, filepath)
call(['chmod', '774', fileout])
bin_df, bin_df_filename = bin_data(gen_parser,
fileout,
e0,
scan_id=scan_id)
result = dict(bin_df=bin_df,
bin_df_filename=bin_df_filename,
interp_df=gen_parser.interp_df,
interp_df_filename=fileout,
scan_id=scan_id)
return result
from matplotlib import rcParams
from databroker import Broker
from scipy.interpolate import splev, splrep
from plot_configs import params, dpi, figure_dir
from metadata_parsing import print_meta
rcParams.update(params)
SAVE_FIGS = False
SHOW_FIT = False
try:
db
except NameError:
db = Broker.named('local_file')
uid = '3de221b4-b9d5-470f-a2b8-a9c3e09a6e94'
print('UID = {}'.format(uid[0:6]))
header = db[uid] # db is a DataBroker instance
df = header.table()
plt.figure(dpi=dpi)
for fs in df['srs_lockin_filt_slope'].unique():
idx = (df['srs_lockin_filt_slope'] == fs)
plt.semilogy(df.loc[idx]['fg_freq'],
df.loc[idx]['amp'],
marker='*',
label='Filter = {}'.format(fs.replace('-', ' ')))
plt.grid(True)
'''
Mock file resource
In this example, we're going to save a file resource to databroker and try
to retrieve it with a file handler
You can run this from your laptop at home as well, so long as you install
databroker.
You'll create a resource as in the previous example, and try to retrieve it
using the datum info
'''
from databroker.tests.utils import temp_config
from databroker import Broker
# this will create a temporary databroker object with nothing in it
db = Broker.from_config(temp_config)
from databroker.assets.handlers_base import HandlerBase
class MyHandler(HandlerBase):
def __init__(self, *args, **kwargs):
print("In init, received args : {}, kwargs {}".format(args, kwargs))
def __call__(self, *args, **kwargs):
print("In call, received args : {}, kwargs {}".format(args, kwargs))
# registering a handler according to a certain spec
db.reg.register_handler("ISSFILE", MyHandler)
import h5py
from databroker import Broker
from databroker._core import register_builtin_handlers
db = Broker.named('srx')
register_builtin_handlers(db.fs)
# srx detector, to be moved to filestore
from databroker.assets.handlers import Xspress3HDF5Handler, HandlerBase
class BulkXSPRESS(HandlerBase):
HANDLER_NAME = 'XPS3_FLY'
def __init__(self, resource_fn):
self._handle = h5py.File(resource_fn, 'r')
def __call__(self):
return self._handle['entry/instrument/detector/data'][:]
db.reg.register_handler(BulkXSPRESS.HANDLER_NAME, BulkXSPRESS, overwrite=True)
class ZebraHDF5Handler(HandlerBase):
HANDLER_NAME = 'ZEBRA_HDF51'
def __init__(self, resource_fn):
self._handle = h5py.File(resource_fn, 'r')
def __call__(self, column):
def run_server(
folder,
outbound_proxy_address=glbl_dict["outbound_proxy_address"],
prefix=None,
handlers=None,
):
"""Start up the portable databroker server
Parameters
----------
folder : str
The location where to save the portable databrokers
outbound_proxy_address : str, optional
The address and port of the zmq proxy. Defaults to
``glbl_dict["outbound_proxy_address"]``
prefix : bytes or list of bytes, optional
The Publisher channels to listen to. Defaults to
``[b"an", b"raw"]``
handlers : dict
The map between handler specs and handler classes, defaults to
the map used by the experimental databroker if possible
"""
# TODO: convert to bytestrings if needed
# TODO: maybe separate this into different processes?
# TODO: support multiple locations for folders
if prefix is None:
prefix = [b"an", b"raw"]
d = RemoteDispatcher(outbound_proxy_address, prefix=prefix)
portable_folder = folder
portable_configs = {}
for folder_name in ["an", "raw"]:
fn = os.path.join(portable_folder, folder_name)
os.makedirs(fn, exist_ok=True)
# if the path doesn't exist then make the databrokers
with open(
os.path.join(portable_folder, f"{folder_name}.yml"), "w"
) as f:
f.write(portable_template.format(folder_name))
print(portable_template.format(folder_name))
print(fn)
portable_configs[folder_name] = yaml.load(
io.StringIO(portable_template.format(fn))
)
os.makedirs(os.path.join(fn, "data"), exist_ok=True)
# TODO: add more files here, eg. a databroker readme/tutorial
with open(os.path.join(portable_folder, "db_load.py"), "w") as f:
f.write(load_script)
an_broker = Broker.from_config(portable_configs["an"])
an_source = Stream()
zed = an_source.Store(
os.path.join(
portable_configs["an"]["metadatastore"]["config"]["directory"],
"data",
),
NpyWriter,
)
zed.starsink(an_broker.insert)
raw_broker = Broker.from_config(portable_configs["raw"])
if handlers is None:
handlers = raw_broker.reg.handler_reg
raw_source = Stream()
raw_source.starmap(
ExportCallback(
os.path.join(
portable_configs["raw"]["metadatastore"]["config"][
"directory"
],
"data",
),
handler_reg=handlers,
)
).starsink(raw_broker.insert)
rr = RunRouter(
[
lambda x: (lambda *nd: raw_source.emit(nd))
if x.get("analysis_stage", "") == "raw"
else None
]
+ [
lambda x: (lambda *nd: an_source.emit(nd))
if x.get("analysis_stage", None) == "pdf"
else None,
lambda x: (lambda *nd: an_source.emit(nd))
if x.get("analysis_stage", None) == "integration"
else None,
]
)
d.subscribe(rr)
print("Starting Portable DB Server")
d.start()
import scipy.interpolate as inter
from databroker import Broker
from plot_configs import params, dpi, figure_dir
from metadata_parsing import print_meta
rcParams.update(params)
plt.figure(dpi=dpi)
SAVE_FIGS = False
PLOT_FIT = False
try:
db
except NameError:
db = Broker.named(
'local_file') # a broker poses queries for saved data sets
'''
| 0 | f31271f1-4231-4798-afe6-83e8647c0927 | 2018-07-06 15:29:07 | phase_dependence_offset | count | ADA2200 | 10 |
| 1 | 63bfefd6-3cc6-45ef-9497-2e97a5cf8f6f | 2018-07-06 15:28:36 | phase_dependence_offset | count | ADA2200 | 10 |
| 2 | b270dad3-96fd-475a-ad1e-b2789db96ed0 | 2018-07-06 15:27:07 | phase_dependence | scan | ADA2200 | 60 |
'''
# get data into a pandas data-frame
uid = 'b270dad3-96fd-475a-ad1e-b2789db96ed0'
print('UID = {}'.format(uid[0:6]))
header = db[uid]
df = header.table()
print_meta(header, os.path.basename(__file__))
# view the baseline data (i.e. configuration values)
print('open meta table')
from bluesky.utils import install_qt_kicker
install_qt_kicker()
print("Insalling Qt Kicker...")
# Make ophyd listen to pyepics.
from ophyd import setup_ophyd
setup_ophyd()
# Set up a RunEngine and use metadata backed by a sqlite file.
from bluesky import RunEngine
from bluesky.utils import get_history
RE = RunEngine(get_history())
# Set up a Broker.
from databroker import Broker
db = Broker.named('amx')
# Subscribe metadatastore to documents.
# If this is removed, data is not saved to metadatastore.
from bluesky import RunEngine
RE = RunEngine()
abort = RE.abort
resume = RE.resume
stop = RE.stop
RE.subscribe(db.insert)
# Set up SupplementalData.
from bluesky import SupplementalData
from bluesky import RunEngine
from bluesky.run_engine import get_bluesky_event_loop
from bluesky.callbacks.best_effort import BestEffortCallback
from databroker import Broker
# The following plans/devices must be imported (otherwise plan parsing wouldn't work)
from ophyd.sim import det1, det2, motor # noqa: F401
from bluesky.plans import count, scan # noqa: F401
import logging
logger = logging.getLogger(__name__)
DB = [Broker.named('temp')]
class RunEngineWorker(Process):
"""
The class implementing Run Engine Worker thread.
Parameters
----------
conn: multiprocessing.Connection
One end of bidirectional (input/output) pipe. The other end is used by RE Manager.
args, kwargs
`args` and `kwargs` of the `multiprocessing.Process`
"""
def __init__(self, *args, conn, **kwargs):
from ophyd.sim import det4, motor1, motor2, motor3
from bluesky import RunEngine
from bluesky.callbacks.best_effort import BestEffortCallback
from databroker.tests.utils import temp_config
from databroker import Broker
# db setup
config = temp_config()
tempdir = config['metadatastore']['config']['directory']
def cleanup():
shutil.rmtree(tempdir)
db = Broker.from_config(config)
RE = RunEngine({})
# subscribe BEC
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))
def test_auto_register():
db_auto = Broker.from_config(temp_config())
db_manual = Broker.from_config(temp_config(), auto_register=False)
assert db_auto.reg.handler_reg
assert not db_manual.reg.handler_reg
import os
import shutil
import tempfile
import yaml
from databroker import Broker
try:
db = Broker.named('xpd')
except NameError:
from xpdsim import db
import logging
from pkg_resources import resource_filename as rs_fn
logger = logging.getLogger(__name__)
pytest_dir = rs_fn('xpdan', 'tests')
def load_configuration(name):
"""
Load configuration data from a cascading series of locations.
The precedence order is (highest priority last):
1. The conda environment
- CONDA_ENV/etc/{name}.yaml (if CONDA_ETC_ is defined for the env)
2. The shipped version
3. At the system level
- /etc/{name}.yml
4. In the user's home directory
- ~/.config/{name}.yml
logger.info(__file__)
"""set up the databroker (db)"""
import os
callback_db = {}
# load config from ~/.config/databroker/mongodb_config.yml
from databroker import Broker
db = Broker.named("mongodb_config")
# Subscribe metadatastore to documents.
# If this is removed, data is not saved to metadatastore.
callback_db['Broker'] = RE.subscribe(db.insert)
# Set up SupplementalData.
from bluesky import SupplementalData
sd = SupplementalData()
RE.preprocessors.append(sd)
# Add a progress bar.
from bluesky.utils import ProgressBarManager
pbar_manager = ProgressBarManager()
RE.waiting_hook = pbar_manager
# Register bluesky IPython magics.
from bluesky.magics import BlueskyMagics
get_ipython().register_magics(BlueskyMagics)
# Set up the BestEffortCallback.
from bluesky.callbacks.best_effort import BestEffortCallback
bec = BestEffortCallback()
simmotor2.read()
simmotor2.set(1)
# RE(scan([detector],simmotor1,0,14,10))
#Flyer
from ophyd.sim import hw
from bluesky.run_engine import RunEngine
from databroker import temp_config, Broker
from bluesky.plans import fly
import bluesky.plans as bp
hw = hw()
flying_zebra = hw.flyer1
db = Broker.named('temp')
RE = RunEngine()
RE.subscribe(db.insert)
RE(fly([flying_zebra]))
RE(fly([flying_zebra]))
hdr = db[-1]
hdr.stream_names
hdr.table('stream_name')
hw.direct_img
hw.det.exposure_time = 1
RE(bp.count([hw.det], num=3))
db[-1].table()
RE = CustomRunEngine()
gs.RE = RE
mds = MDS(
{
'host': 'xf16idc-ca',
'database': 'metadatastore_production_v1',
'port': 27017,
'timezone': 'US/Eastern'
},
auth=False)
db = Broker(
mds,
FileStore({
'host': 'xf16idc-ca',
'database': 'filestore',
'port': 27017
}))
register_builtin_handlers(db.fs)
RE.subscribe('all', mds.insert)
if is_ipython():
# FIXME: Remove this once we migrate to PYTHON 3.5
from IPython import get_ipython
from IPython.core.pylabtools import backend2gui
from matplotlib import get_backend
ip = get_ipython()
ipython_gui_name = backend2gui.get(get_backend())
if ipython_gui_name:
import h5py
from databroker import Broker
from databroker._core import register_builtin_handlers
db = Broker.named('xfm')
register_builtin_handlers(db.reg)
# srx detector, to be moved to filestore
from databroker.assets.handlers import Xspress3HDF5Handler, HandlerBase
class BulkXSPRESS(HandlerBase):
HANDLER_NAME = 'XPS3_FLY'
def __init__(self, resource_fn):
self._handle = h5py.File(resource_fn, 'r')
def __call__(self):
return self._handle['entry/instrument/detector/data'][:]
db.reg.register_handler(BulkXSPRESS.HANDLER_NAME, BulkXSPRESS,
overwrite=True)
class ZebraHDF5Handler(HandlerBase):
HANDLER_NAME = 'ZEBRA_HDF51'
def __init__(self, resource_fn):
self._handle = h5py.File(resource_fn, 'r')
def __call__(self, column):
return self._handle[column][:]
class SISHDF5Handler(HandlerBase):
This module is for the necessary packages for the XPCS analysis
"""
from IPython.core.magics.display import Javascript
from skbeam.core.utils import multi_tau_lags
from skimage.draw import line_aa, line, polygon, ellipse, circle
from modest_image import imshow
# edit handlers here to switch to PIMS or dask
# this does the databroker import
#from chxtools.handlers import EigerHandler
from eiger_io.fs_handler import EigerHandler
#from databroker import DataBroker as db, get_images, get_table, get_events, get_fields
from databroker import get_images, get_table, get_events, get_fields
from databroker.assets.path_only_handlers import RawHandler
## Import all the required packages for Data Analysis
from databroker import Broker
db = Broker.named('chx')
#* scikit-beam - data analysis tools for X-ray science
# - https://github.com/scikit-beam/scikit-beam
#* xray-vision - plotting helper functions for X-ray science
# - https://github.com/Nikea/xray-vision
import xray_vision
import matplotlib.cm as mcm
import copy
import xray_vision.mpl_plotting as mpl_plot
from xray_vision.mpl_plotting import speckle
from xray_vision.mask.manual_mask import ManualMask
import skbeam.core.roi as roi
import skbeam.core.correlation as corr
import skbeam.core.utils as utils
import numpy as np
from datetime import datetime
# import nslsii # Register bluesky IPython magics. #from bluesky.magics import BlueskyMagics #get_ipython().register_magics(BlueskyMagics) #nslsii.configure_base(get_ipython().user_ns, 'amx') import bluesky.plans as bp from bluesky.run_engine import RunEngine from bluesky.utils import get_history RE = RunEngine(get_history()) beamline = os.environ["BEAMLINE_ID"] from databroker import Broker db = Broker.named(beamline) RE.subscribe(db.insert) # from bluesky.callbacks.best_effort import BestEffortCallback # bec = BestEffortCallback() # RE.subscribe(bec) # convenience imports # from ophyd.commands import * from bluesky.callbacks import * # from bluesky.spec_api import * # from bluesky.global_state import gs, abort, stop, resume # from databroker import (DataBroker as db, get_events, get_images, # get_table, get_fields, restream, process)
def run(self):
"""
Overrides the `run()` function of the `multiprocessing.Process` class. Called
by the `start` method.
"""
logging.basicConfig(level=max(logging.WARNING, self._log_level))
logging.getLogger(__name__).setLevel(self._log_level)
success = True
from .profile_tools import set_re_worker_active, clear_re_worker_active
# Set the environment variable indicating that RE Worker is active. Status may be
# checked using 'is_re_worker_active()' in startup scripts or modules.
set_re_worker_active()
from .plan_monitoring import RunList, CallbackRegisterRun
self._active_run_list = RunList(
) # Initialization should be done before communication is enabled.
self._comm_to_manager.add_method(self._request_state_handler,
"request_state")
self._comm_to_manager.add_method(self._request_plan_report_handler,
"request_plan_report")
self._comm_to_manager.add_method(self._request_run_list_handler,
"request_run_list")
self._comm_to_manager.add_method(self._command_close_env_handler,
"command_close_env")
self._comm_to_manager.add_method(self._command_confirm_exit_handler,
"command_confirm_exit")
self._comm_to_manager.add_method(self._command_run_plan_handler,
"command_run_plan")
self._comm_to_manager.add_method(self._command_pause_plan_handler,
"command_pause_plan")
self._comm_to_manager.add_method(self._command_continue_plan_handler,
"command_continue_plan")
self._comm_to_manager.add_method(self._command_reset_worker_handler,
"command_reset_worker")
self._comm_to_manager.start()
self._exit_event = threading.Event()
self._exit_confirmed_event = threading.Event()
self._re_report_lock = threading.Lock()
from bluesky import RunEngine
from bluesky.run_engine import get_bluesky_event_loop
from bluesky.callbacks.best_effort import BestEffortCallback
from bluesky_kafka import Publisher as kafkaPublisher
from bluesky.utils import PersistentDict
from .profile_tools import global_user_namespace
# TODO: TC - Do you think that the following code may be included in RE.__init__()
# (for Python 3.8 and above)
# Setting the default event loop is needed to make the code work with Python 3.8.
loop = get_bluesky_event_loop()
asyncio.set_event_loop(loop)
try:
keep_re = self._config_dict["keep_re"]
startup_dir = self._config_dict.get("startup_dir", None)
startup_module_name = self._config_dict.get(
"startup_module_name", None)
startup_script_path = self._config_dict.get(
"startup_script_path", None)
self._re_namespace = load_worker_startup_code(
startup_dir=startup_dir,
startup_module_name=startup_module_name,
startup_script_path=startup_script_path,
keep_re=keep_re,
)
if keep_re and ("RE" not in self._re_namespace):
raise RuntimeError(
"Run Engine is not created in the startup code and 'keep_re' option is activated."
)
self._existing_plans = plans_from_nspace(self._re_namespace)
self._existing_devices = devices_from_nspace(self._re_namespace)
logger.info("Startup code loading was completed")
except Exception as ex:
logger.exception(
"Failed to start RE Worker environment. Error while loading startup code: %s.",
str(ex),
)
success = False
# Load lists of allowed plans and devices
logger.info("Loading the lists of allowed plans and devices ...")
path_pd = self._config_dict["existing_plans_and_devices_path"]
path_ug = self._config_dict["user_group_permissions_path"]
try:
self._allowed_plans, self._allowed_devices = load_allowed_plans_and_devices(
path_existing_plans_and_devices=path_pd,
path_user_group_permissions=path_ug)
except Exception as ex:
logger.exception(
"Error occurred while loading lists of allowed plans and devices from '%s': %s",
path_pd, str(ex))
if success:
logger.info("Instantiating and configuring Run Engine ...")
try:
# Make RE namespace available to the plan code.
global_user_namespace.set_user_namespace(
user_ns=self._re_namespace, use_ipython=False)
if self._config_dict["keep_re"]:
# Copy references from the namespace
self._RE = self._re_namespace["RE"]
self._db = self._re_namespace.get("RE", None)
else:
# Instantiate a new Run Engine and Data Broker (if needed)
md = {}
if self._config_dict["use_persistent_metadata"]:
# This code is temporarily copied from 'nslsii' before better solution for keeping
# continuous sequence Run ID is found. TODO: continuous sequence of Run IDs.
directory = os.path.expanduser("~/.config/bluesky/md")
os.makedirs(directory, exist_ok=True)
md = PersistentDict(directory)
self._RE = RunEngine(md)
self._re_namespace["RE"] = self._RE
def factory(name, doc):
# Documents from each run are routed to an independent
# instance of BestEffortCallback
bec = BestEffortCallback()
return [bec], []
# Subscribe to Best Effort Callback in the way that works with multi-run plans.
rr = RunRouter([factory])
self._RE.subscribe(rr)
# Subscribe RE to databroker if config file name is provided
self._db = None
if "databroker" in self._config_dict:
config_name = self._config_dict["databroker"].get(
"config", None)
if config_name:
logger.info(
"Subscribing RE to Data Broker using configuration '%s'.",
config_name)
from databroker import Broker
self._db = Broker.named(config_name)
self._re_namespace["db"] = self._db
self._RE.subscribe(self._db.insert)
# Subscribe Run Engine to 'CallbackRegisterRun'. This callback is used internally
# by the worker process to keep track of the runs that are open and closed.
run_reg_cb = CallbackRegisterRun(
run_list=self._active_run_list)
self._RE.subscribe(run_reg_cb)
if "kafka" in self._config_dict:
logger.info(
"Subscribing to Kafka: topic '%s', servers '%s'",
self._config_dict["kafka"]["topic"],
self._config_dict["kafka"]["bootstrap"],
)
kafka_publisher = kafkaPublisher(
topic=self._config_dict["kafka"]["topic"],
bootstrap_servers=self._config_dict["kafka"]
["bootstrap"],
key="kafka-unit-test-key",
# work with a single broker
producer_config={
"acks": 1,
"enable.idempotence": False,
"request.timeout.ms": 5000
},
serializer=partial(msgpack.dumps, default=mpn.encode),
)
self._RE.subscribe(kafka_publisher)
if "zmq_data_proxy_addr" in self._config_dict:
from bluesky.callbacks.zmq import Publisher
publisher = Publisher(
self._config_dict["zmq_data_proxy_addr"])
self._RE.subscribe(publisher)
self._execution_queue = queue.Queue()
self._state["environment_state"] = "ready"
except BaseException as ex:
success = False
logger.exception(
"Error occurred while initializing the environment: %s.",
str(ex))
if success:
logger.info("RE Environment is ready")
self._execute_in_main_thread()
else:
self._exit_event.set()
logger.info("Environment is waiting to be closed ...")
self._state["environment_state"] = "closing"
# Wait until confirmation is received from RE Manager
while not self._exit_confirmed_event.is_set():
ttime.sleep(0.02)
# Clear the environment variable indicating that RE Worker is active. It is an optional step
# since the process is about to close, but we still do it for consistency.
clear_re_worker_active()
self._RE = None
self._comm_to_manager.stop()
logger.info("Run Engine environment was closed successfully")