mxcubecore.HardwareObjects.ESRF.ESRFEnergyScan#
Functions
|
Classes
|
|
|
|
|
|
|
- class mxcubecore.HardwareObjects.ESRF.ESRFEnergyScan.ESRFEnergyScan(name, tunable_bl)[source]#
Bases:
AbstractEnergyScan
,HardwareObject
- do_chooch(elt, edge, directory, archive_directory, prefix)[source]#
Use chooch to calculate edge and inflection point The brick expects the folowing parameters to be returned: pk, fppPeak, fpPeak, ip, fppInfl, fpInfl, rm, chooch_graph_x, chooch_graph_y1, chooch_graph_y2, title)
- escan_prepare()[source]#
Set the nesessary equipment in position for the scan. No need to know the c=scan paramets.
- execute_command(command_name, *args, **kwargs)[source]#
Execute command.
- Parameters:
- Raises:
AttributeError – If command not found.
- Returns:
Execution output.
- Return type:
Any
- get_static_parameters(config_file, element, edge)[source]#
Get any parameters, which are known before hand. Some of them are known from the theory, like the peak energy, others are equipment specific like the lower/upper ROI limits of the fluorescence detector. Usually these parameters are pre-defined in a file, but can also be calculated. The function should return a distionary with at least defined {‘edgeEnergy’: peak_energy} member, where ‘edgeEnergy’ is a compulsory key. It is convinient to put in the same dictionary the remote energy, the ROI min/max values. There are few more reserved key names: ‘eroi_min’, ‘eroi_max’ - min and max ROI limits if you want ot set one. ‘findattEnergy’ - energy to move to if you want to choose the attenuation for the scan.