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• Print the central keys using: "facetdata.print_keys()"
  
• Print the key entries of "data_struct" using: "facetdata.print_data_entries()"
  
  

params

• Print all entries using: "facetdata.print_params_entries()"
  
  

• Get information about the scan:

  print("number of steps:          ", facetdata.nSteps)
  print("number of shots per step: ", facetdata.n_shot)

  

  facetdata.print_scanPVs()
  facetdata.print_scanVals()

  
  
  
  

scalars

List all entries

• using: "facetdata.print_scalars_entries()"
  
  
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Common index concept

• We explain the "common index" concept using "steps" as an example
  print all steps: "facetdata.print_steps()"
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• The list contains much more than just 20 x 50 = 1000 entries (number of shots per step x number of steps)
• To get the number of successful shots:
  

  shotidx_list        = facetdata.get_shotidx_list()
  print("number of shots: ", facetdata.get_scan_length())
  print("shot idx:        ", shotidx_list)

  
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  Note that the function "get_shotidx_list()" returns a "LinData" object that represents a list of all successful shots
  
  
• To access scalar variables properly, we need to use the scalar common index:
  use the function "facetdata.get_scalar_cidx" to convert a shot index to a common index.
  
  
• This is how it is done internally:
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• We can get a  "LinData" object with all scan values using "facetdata.get_scan_value_list()"
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• We can plot the scanned values:
  
  

  plot            = facet.FacetPlot(facetdata)
  plot.set_output_folder(output_folder)
  plot.scatter(shotidx_list, scan_value_list, colorylabel=False) 
  plot.save("scan_values", png=True)

  
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Access scalar variables through lists

• The lists are loaded during initialization; access them, e.g., using:
  print(facetdata.BSA_List_S20.dtype)
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• Access them using a "FacetScalar" object:
  

  bpm_3218_x            = facet.FacetScalar(facetdata, "BSA_List_S20", "BPMS_LI20_3218_X").get_data()
  bpm_3218_y            = facet.FacetScalar(facetdata, "BSA_List_S20", "BPMS_LI20_3218_Y").get_data()

  plot            = facet.FacetPlot(facetdata)
  plot.set_output_folder(output_folder)
  plot.scatter(bpm_3218_x, bpm_3218_y, colorylabel=False)  
  plot.save("bpm_3218", png=True)

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