LavueController server allows for communication with LaVue GUI via tango interface, e.g. with user scripts or macros
Attributes
The user can pass to and read back from the LaVue GUI the following attributes:
- BeamCenterX: x-coordinate of the beam center in pixels, e.g. used in
Angle/Q Tool
- BeamCenterY: y-coordinate of the beam center in pixels, e.g. used in
Angle/Q Tool
- PixelSizeX: x-size of the detector pixel in micrometers, e.g. used in
Angle/Q Tool
- PixelSizeY: y-size of the detector pixel in micrometers, e.g. used in
Angle/Q Tool
- DetectorDistance: detector distance from the sample in mm, e.g. used in
Angle/Q Tool
- Energy: beam energy in eV, e.g. used in
Angle/Q Tool
- DetectorROIs: JSON dictionary with Regions Of Interests ranges, e.g.
{"pilatusrois": [[67, 131, 124, 153], [67, 69, 117, 119], [134, 129, 184, 179], [125, 72, 175, 122]]}
Moreover the user can read from the LaVue GUI:
- DetectorROIsValues: JSON dictionary with Regions Of Interests sums, e.g.
{"pilatusrois": [8167.0, 2262.0, 478.0, 1069.0]}
Finally, the user can change state of lavue by writing to
- LavueState: JSON dictionary with lavue configuration with parameters corresponding to command-line parameters of lavue (to display them:
lavue -h
). The currently supported commands are:source, configuration, start, stop, imagefile, offset, rangewindow, dsfactor, dsreduction, filters, mbuffer, maskfile, maskhighvalue, transformation, scaling, levels, autofactor, gradient, viewrange, tool, tangodevice, doordevice, analysisdevice, log
.
e.g.
import tango import json lc = tango.DeviceProxy("p09/lavuecontroller/1") # start the Test source lc.LavueState = json.dumps({"source": "test", "start": True}) # stop an image source lc.LavueState = json.dumps({"stop":True}) # set the hidra source with a server configured lc.LavueState = json.dumps({"source": "hidra", "configuration": "haspilatus1m.desy.de"}) # start Tango Attribute image source with a tango attribute from TangoTest server # lc.LavueState = json.dumps({"source": "tangoattr", "configuration": "sys/tg_test/1/double_image_ro", "start": True}) # set ROI tool in the tool combobox lc.LavueState = json.dumps({"tool": "roi"}) # set display intensity levels lc.LavueState = json.dumps({"levels": "m20,20"}) # set level auto factor lc.LavueState = json.dumps({"autofactor": 1})
# set auto levels
lc.LavueState = json.dumps({"autofactor": ""})
# set mask values above lc.LavueState = json.dumps({"maskhighvalue": 30000}) # set flip-up-down transformation lc.LavueState = json.dumps({"transformation": "flip-up-down"}) # set log intensity scaling lc.LavueState = json.dumps({"scaling": "log"}) # set eiger image source with configuration defined by alias "eiger" # (otherwise you have to set as configuration the whole URL string) lc.LavueState = json.dumps({"source":"http", "configuration":"eiger", "start":True})
You can read the current LaVue state via LavueState
. To update the viewrange
parameter write to LavueState
an empty JSON dictionary or {"__update__": true}
.
Properties
The DynamicROIsValues device property can be set to true
or false.
When it is true dynamic attributes with ROIs sums are added.
They names are defined by ROIs aliases from Lavue GUI.
The DynamicROIs device property can be set to true
or false.
When it is true dynamic attributes with ROIs bounds are added.
They names are defined by ROIs aliases from Lavue GUI.
The ROIAttributesNames device property contains names of dynamic attributes which will be created event if the corresponding ROIs aliases in Lavue GUI are missing.