Merge branch 'mwaterla_docs' into 'master'

Update documentation

See merge request !2519

Hlt/RecoConf/options/VP_tracking_monitors.py

@@ -9,11 +9,17 @@
 # or submit itself to any jurisdiction.                                       #
 ###############################################################################
 """
-This test includes algorithms intended to run as part of the VELO monitoring, online and offline, which rely on tracks. This includes the Hit Efficiency monitors.
-Pay attention on this specific configuration as it is just an integration test. 
-If the pseudo hit efficiencies are the desired output, the loop over sensor_under_study should be extended to a 'range(208)' and masking in the PR removed. 
+Pay attention on this specific configuration as it is just an integration test.
+
+Options file to test the tracking in the VELO. At the moment only the VPHitEfficiencyMonitor is included, but this can be extended to include other algorithms.
+
+In the VPHitEfficiencyMonitor, the hit efficiency of sensors is determined and stored in an output ROOT file. Note: This is done independantly fromt the tracking efficiency.
+The VPHitEfficiencyMonitor will produce the hit efficiency per sensor. To cover the entire VELO, a loop over sensor_under_study is needed (but tracking is ran only once). At the moment this loop is
+kept short for integration tests, but all 208 sensors should be used when the pseudo hit efficiencies are the desired output.
 The tracks are fitted using the TrackMasterFitter and all extrapolators used are LinearExtrapolators. This includes the extrapolator used in the TrackInterpolator.
-For the unbiassed hit efficiencies an example options file can be found under /examples/VP_hit_efficiency.py 
+As input for the VPHitEfficiencyMonitor, data is intended. To have 1 entry in all sensors requires on O(10^3) events at avg_mu=2.2. A more detailed map of the hit efficiencies,
+for instance to use in Boole, needs an order of events of ~O(10^10). (assuming 16x16 pixel bins)
+For the unbiassed hit efficiencies, an example options file can be found under ./examples/VP_hit_efficiency.py
 """
 
 from Moore import options, run_reconstruction

Hlt/RecoConf/options/examples/VP_hit_efficiency.py

@@ -15,8 +15,8 @@ from RecoConf.hlt1_tracking import (
     make_VeloClusterTrackingSIMD,
     make_reco_pvs,
     make_PatPV3DFuture_pvs,
-    get_global_measurement_provider,
     make_RetinaClusters,
+    get_global_measurement_provider,
     _rawevent_to_rawbank,
 )
 
@@ -42,9 +42,14 @@ from PyConf.Tools import (
 
 make_reco_pvs.global_bind(make_pvs_from_velo_tracks=make_PatPV3DFuture_pvs)
 """
-This file is an example of how to calculate the VELO hit efficiencies. 
-The algorithm uses tracks fitted by the TrackMasterFitter and only uses the LinearExtrapolator. Both in the interpolator and efficiency algorithm. 
-Due to the masking of the sensor_under_study, the track-fit has to be performed for each sensor separately. 
+Options file to determine the hit efficiencies in the VELO
+
+In the VPHitEfficiencyMonitor, the hit efficiency of sensors is determined and stored in an output ROOT file. Note: This is done independantly fromt the tracking efficiency.
+The VPHitEfficiencyMonitor will produce the hit efficiency per sensor. To cover the entire VELO, a loop over sensor_under_study is needed. To make sure the hit efficiencies 
+are not biassed, the sensor_under_study needs to be masked in tracking. Therefore, contrary to the options in VP_tracking_monitor.py, the tracking needs to be repeated for each sensor. 
+The tracks are fitted using the TrackMasterFitter and all extrapolators used are LinearExtrapolators. This includes the extrapolator used in the TrackInterpolator.
+As input for the VPHitEfficiencyMonitor, data is intended. To have 1 entry in all sensors requires on O(10^3) events at avg_mu=2.2. A more detailed map of the hit efficiencies,
+for instance to use in Boole, needs an order of events of ~O(10^10). (assuming 16x16 pixel bins)
 """
 
 
@@ -64,6 +69,7 @@ def make_my_sequence():
             my_SensorMask = [
                 sensor in [sensor_under_study] for sensor in range(208)
             ]
+
             vpClustering = VeloRetinaClusterTrackingSIMDFull(
                 RawBanks=_rawevent_to_rawbank(
                     default_raw_banks("VPRetinaCluster"), "VPRetinaCluster"),