129 lines
4.1 KiB
Python
129 lines
4.1 KiB
Python
from collections import OrderedDict
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#Debugging
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if get_exec_pars().args is None:
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PRE_ACTIONS = {z:0.1}
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POSITIONERS = ["x", "y"]
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START = [0.0,0.0]
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STOP = [1.0,1.0]
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STEPS = [3, 5]
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SENSORS = [scienta.dataMatrix, current]
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SETTLING_TIME = 0.1
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PASSES = 1
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ZIGZAG = True
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COMPRESSION = True
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DIAGS = []
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SNAPS = diag_channels
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MONITORS = []
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NAME=None
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import json
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def load_parameters(name):
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print "Scan Name: ", name
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filename = get_context().setup.expandPath("{script}/scans/" + name + ".json")
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with open(filename) as config_file:
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config = json.load(config_file, object_pairs_hook=OrderedDict) #Read ordered dictionaries
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for key in config.keys():
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globals()[key] = config[key]
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print str(key), " = ", config[key]
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with open(filename) as config_file:
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save_dataset("scripts/config.json", config_file.read(), type = 's')
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set_attribute("scripts", "config", filename)
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if NAME:
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load_parameters(NAME)
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reinit(None)
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#Enforece parameter types
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positioners = string_to_obj(POSITIONERS)
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sensors = string_to_obj(SENSORS)
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start = list(to_array(START, 'd'))
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end = list(to_array(STOP, 'd'))
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steps = list(to_array(STEPS, 'i'))
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latency = SETTLING_TIME
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passes = int(PASSES)
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zigzag = bool(ZIGZAG)
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#Setuop Scienta
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scienta.setGrabMode(Camera.GrabMode.Single)
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#Change photon parameters
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_id_mode=_grating=None
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if "id_mode" in PRE_ACTIONS.keys():
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_id_mode=PRE_ACTIONS.pop("id_mode")
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if "grating" in PRE_ACTIONS.keys():
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_grating=PRE_ACTIONS.pop("grating")
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if (_id_mode is not None) or (_grating is not None):
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print _id_mode, _grating
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change_photon_pars(_id_mode=_id_mode, _grating=_grating)
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#Execute pre-actions
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for key in PRE_ACTIONS.keys():
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if key=="eval":
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log("Eval " + str(PRE_ACTIONS[key]))
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eval(str(PRE_ACTIONS[key]))
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else:
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dev = string_to_obj(key)
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if isinstance(dev, Writable):
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log("Setting " + dev.name + " to: " + str(PRE_ACTIONS[key]))
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dev.write(PRE_ACTIONS[key])
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for key in PRE_ACTIONS.keys():
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dev = string_to_obj(key)
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if isinstance(dev, Device):
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log("Waiting " + dev.name)
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dev.waitReady(-1)
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#Run scan
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if COMPRESSION:
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set_exec_pars(compression=[scienta.dataMatrix])
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def before_read(pos, scan):
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if scienta.dataMatrix in sensors:
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trigger_scienta()
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data_3d = (scienta.dataMatrix in sensors) and ("thetay" in scienta.acquisitionMode.lower())
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if data_3d:
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print "3D dataset"
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def after_read(rec, scan):
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global data_3d
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#handle_diagnostics(rec)
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if data_3d:
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try:
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#path = get_exec_pars().scanPath + ("/3d_images/%04d" % rec.index)
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#data = scienta.takeStack()
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#save_dataset(path, data)
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path = get_exec_pars().scanPath + "/images"
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if rec.index==0:
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size=scienta.getImageSize()
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if len(size)<3:
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raise Exception("Data is not 3D")
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num_images = scan.getNumberOfRecords() * size[2]
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create_dataset(path, scienta.dataArray, None, (num_images, size[1], size[0]), {"layout":"contiguous", "compression":True})
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for img in scienta.takeStack():
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append_dataset(path, img)
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except:
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log(sys.exc_info()[1])
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try:
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if len(positioners)==0:
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ret= tscan (sensors, 1,0, passes=passes, \
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before_read=before_read, after_read=after_read, \
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snaps=SNAPS, diags=DIAGS, monitors=MONITORS, keep=True)
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#if (scienta.dataMatrix in sensors) and not data_3d:
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# save_dataset("/image", ret[scienta.dataMatrix][0], type = 'i', features={"compression":True})
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else:
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ret= ascan (positioners, sensors, start, end, steps, \
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latency= latency, relative=False, passes=passes, zigzag=zigzag, \
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before_read=before_read, after_read=after_read, \
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snaps=SNAPS, diags=DIAGS, monitors=MONITORS)
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set_device_channel_names(ret.scan, sensors, SNAPS, DIAGS, MONITORS )
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finally:
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scienta.stop()
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scienta.zeroSupplies()
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print ret
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