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63 mixed orientations reconstruction #108

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merged 19 commits into from
May 14, 2024
Merged

63 mixed orientations reconstruction #108

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e53c1f0
Merge branch 'main' into 63-mixed-orientations-reconstruction
May 3, 2024
be05d4b
Merge branch 'main' into 63-mixed-orientations-reconstruction
May 3, 2024
d41d00b
Merge branch 'main' into 63-mixed-orientations-reconstruction
May 3, 2024
29530ab
Reverse RecoY calculation point to the top, but to 244mm this time
May 6, 2024
65bacfd
Merge branch 'main' into 63-mixed-orientations-reconstruction
May 6, 2024
38c28de
Preventing a potential logic problem with RecoY calculation by specif…
May 6, 2024
f534523
Updating the performance_reco script with exiting vs. stopping evalua…
May 7, 2024
33cab11
Taking out changes in config file
May 7, 2024
c293a1a
Hopefully y calculation this time correct, changed X anchor point to …
May 13, 2024
25d6d6b
Reinstating GetRecoX for Reco_Tree
May 13, 2024
dcdcbd7
Correcting above-below check
May 13, 2024
ad125a9
Changing direction again. Matches better this way. Why though?
May 13, 2024
ae2a58d
Implement direction calculation and add parameter in config file to a…
May 14, 2024
76069f5
Get actually z for z coordinate
May 14, 2024
33f54b0
Set DirectionDistance parameter to 10
May 14, 2024
1758549
Merging with 107-reco-track-direction-is-not-correct branch
May 14, 2024
a975342
Add multiple tracks per spill option in performance plots
May 14, 2024
37c10b7
Making CalculateRecoY explanation clearer
May 14, 2024
7c8a679
Restoring EvaluateTrackFinding
May 14, 2024
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4 changes: 3 additions & 1 deletion config/TMS_Default_Config.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -75,7 +75,9 @@
# Tilt angle of scintillator planes for calculation of y (tan(90-angle))
TiltAngle = 19.0811366877 #tan(90-3=87)
# Y difference for expectation of reconstruction from UV and from X hit [mm]
YDifference = 300.0
YDifference = 3000.0
# Distance from start to calculate track direction for [Number of planes]. Track matching done in plane pairs -> do not set to 1
DirectionDistance = 10

[Recon.AStar]
#CostMetric = "Manhattan"
Expand Down
118 changes: 64 additions & 54 deletions scripts/Reco/compare_2_data_sets_performance.py
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Original file line number Diff line number Diff line change
Expand Up @@ -61,15 +61,15 @@ def draw_comparison(out_dir, input_filename1, input_filename2):

n_events_2 = r2.GetEntries()

Reco_Start_1 = np.ones((n_events_1, 3), dtype = float) * -9999.
Reco_End_1 = np.ones((n_events_1, 3), dtype = float) * -9999.
Primary_True_Start_1 = np.ones((n_events_1, 3), dtype = float) * -9999.
Primary_True_End_1 = np.ones((n_events_1, 3), dtype = float) * -9999.
Reco_Start_1 = np.ones((n_events_1, 5, 3), dtype = float) * -9999.
Reco_End_1 = np.ones((n_events_1, 5, 3), dtype = float) * -9999.
Primary_True_Start_1 = np.ones((n_events_1, 5, 3), dtype = float) * -9999.
Primary_True_End_1 = np.ones((n_events_1, 5, 3), dtype = float) * -9999.

Reco_Start_2 = np.ones((n_events_2, 3), dtype = float) * -9999.
Reco_End_2 = np.ones((n_events_2, 3), dtype = float) * -9999.
Primary_True_Start_2 = np.ones((n_events_2, 3), dtype = float) * -9999.
Primary_True_End_2 = np.ones((n_events_2, 3), dtype = float) * -9999.
Reco_Start_2 = np.ones((n_events_2, 5, 3), dtype = float) * -9999.
Reco_End_2 = np.ones((n_events_2, 5, 3), dtype = float) * -9999.
Primary_True_Start_2 = np.ones((n_events_2, 5, 3), dtype = float) * -9999.
Primary_True_End_2 = np.ones((n_events_2, 5, 3), dtype = float) * -9999.

for current_spill_number in range(max_n_spills):
for i in range(n_events_1):
Expand All @@ -92,29 +92,34 @@ def draw_comparison(out_dir, input_filename1, input_filename2):
if true_event == None:
truth1.GetEntry(i)
true_event = truth1

nTracks = event.nTracks
if nTracks <= 0: continue

StartPos = np.frombuffer(event.StartPos, dtype = np.float32)
EndPos = np.frombuffer(event.EndPos, dtype = np.float32)
RecoTrackPrimaryParticleTruePositionTrackStart = np.frombuffer(true_event.RecoTrackPrimaryParticleTruePositionTrackStart, dtype = np.float32)
RecoTrackPrimaryParticleTruePositionTrackEnd = np.frombuffer(true_event.RecoTrackPrimaryParticleTruePositionTrackEnd, dtype = np.float32)
RecoTrackPrimaryParticleTruePositionTrackEnd = np.frombuffer(true_event.RecoTrackPrimaryParticleTruePositionTrackEnd, dtype = np.float32)

nTracks = event.nTracks
if nTracks <= 0: continue
if nTracks > 4: print("Too many tracks in event. Limit to first 5")
for j in range(nTracks):
if j > 4: break

if RecoTrackPrimaryParticleTruePositionTrackStart[0] > -8000. and not StartPos.size == 0:
Reco_Start_1[i, 0] = StartPos[0]
Reco_Start_1[i, 1] = StartPos[1]
Reco_Start_1[i, 2] = StartPos[2]
Primary_True_Start_1[i, 0] = RecoTrackPrimaryParticleTruePositionTrackStart[0]
Primary_True_Start_1[i, 1] = RecoTrackPrimaryParticleTruePositionTrackStart[1]
Primary_True_Start_1[i, 2] = RecoTrackPrimaryParticleTruePositionTrackStart[2]
if RecoTrackPrimaryParticleTruePositionTrackEnd[0] > -8000. and not EndPos.size == 0:
Reco_End_1[i, 0] = EndPos[0]
Reco_End_1[i, 1] = EndPos[1]
Reco_End_1[i, 2] = EndPos[2]
Primary_True_End_1[i, 0] = RecoTrackPrimaryParticleTruePositionTrackEnd[0]
Primary_True_End_1[i, 1] = RecoTrackPrimaryParticleTruePositionTrackEnd[1]
Primary_True_End_1[i, 2] = RecoTrackPrimaryParticleTruePositionTrackEnd[2]
if RecoTrackPrimaryParticleTruePositionTrackStart[j*4 + 0] > -8000. and not StartPos.size == 0:
if (EndPos[j*3 + 2] - StartPos[j*3 + 2]) > 890. and (RecoTrackPrimaryParticleTruePositionTrackEnd[j*4 + 2] - RecoTrackPrimaryParticleTruePositionTrackStart[j*4 + 2]) > 890.:
Reco_Start_1[i, j, 0] = StartPos[j*3 + 0]
Reco_Start_1[i, j, 1] = StartPos[j*3 + 1]
Reco_Start_1[i, j, 2] = StartPos[j*3 + 2]
Primary_True_Start_1[i, j, 0] = RecoTrackPrimaryParticleTruePositionTrackStart[j*4 + 0]
Primary_True_Start_1[i, j, 1] = RecoTrackPrimaryParticleTruePositionTrackStart[j*4 + 1]
Primary_True_Start_1[i, j, 2] = RecoTrackPrimaryParticleTruePositionTrackStart[j*4 + 2]
if RecoTrackPrimaryParticleTruePositionTrackEnd[j*4 + 0] > -8000. and not EndPos.size == 0:
if (EndPos[j*3 + 2] - StartPos[j*3 + 2]) > 890. and (RecoTrackPrimaryParticleTruePositionTrackEnd[j*4 + 2] - RecoTrackPrimaryParticleTruePositionTrackStart[j*4 + 2]) > 890.:
Reco_End_1[i, j, 0] = EndPos[j*3 + 0]
Reco_End_1[i, j, 1] = EndPos[j*3 + 1]
Reco_End_1[i, j, 2] = EndPos[j*3 + 2]
Primary_True_End_1[i, j, 0] = RecoTrackPrimaryParticleTruePositionTrackEnd[j*4 + 0]
Primary_True_End_1[i, j, 1] = RecoTrackPrimaryParticleTruePositionTrackEnd[j*4 + 1]
Primary_True_End_1[i, j, 2] = RecoTrackPrimaryParticleTruePositionTrackEnd[j*4 + 2]

for i in range(n_events_2):
try:
Expand All @@ -136,47 +141,52 @@ def draw_comparison(out_dir, input_filename1, input_filename2):
if true_event2 == None:
truth2.GetEntry(i)
true_event2 = truth2

nTracks = event2.nTracks
if nTracks <= 0: continue

StartPos = np.frombuffer(event2.StartPos, dtype = np.float32)
EndPos = np.frombuffer(event2.EndPos, dtype = np.float32)
RecoTrackPrimaryParticleTruePositionTrackStart = np.frombuffer(true_event2.RecoTrackPrimaryParticleTruePositionTrackStart, dtype = np.float32)
RecoTrackPrimaryParticleTruePositionTrackEnd = np.frombuffer(true_event2.RecoTrackPrimaryParticleTruePositionTrackEnd, dtype = np.float32)
RecoTrackPrimaryParticleTruePositionTrackEnd = np.frombuffer(true_event2.RecoTrackPrimaryParticleTruePositionTrackEnd, dtype = np.float32)

nTracks = event2.nTracks
if nTracks <= 0: continue
if nTracks > 4: print("Too many tracks in event. Limit to first 5")
for j in range(nTracks):
if j > 4: break

if RecoTrackPrimaryParticleTruePositionTrackStart[0] > -8000. and not StartPos.size == 0:
Reco_Start_2[i, 0] = StartPos[0]
Reco_Start_2[i, 1] = StartPos[1]
Reco_Start_2[i, 2] = StartPos[2]
Primary_True_Start_2[i, 0] = RecoTrackPrimaryParticleTruePositionTrackStart[0]
Primary_True_Start_2[i, 1] = RecoTrackPrimaryParticleTruePositionTrackStart[1]
Primary_True_Start_2[i, 2] = RecoTrackPrimaryParticleTruePositionTrackStart[2]
if RecoTrackPrimaryParticleTruePositionTrackEnd[0] > -8000. and not EndPos.size == 0:
Reco_End_2[i, 0] = EndPos[0]
Reco_End_2[i, 1] = EndPos[1]
Reco_End_2[i, 2] = EndPos[2]
Primary_True_End_2[i, 0] = RecoTrackPrimaryParticleTruePositionTrackEnd[0]
Primary_True_End_2[i, 1] = RecoTrackPrimaryParticleTruePositionTrackEnd[1]
Primary_True_End_2[i, 2] = RecoTrackPrimaryParticleTruePositionTrackEnd[2]
if RecoTrackPrimaryParticleTruePositionTrackStart[j*4 + 0] > -8000. and not StartPos.size == 0:
if (EndPos[j*3 + 2] - StartPos[j*3 + 2]) > 890. and (RecoTrackPrimaryParticleTruePositionTrackEnd[j*4 + 2] - RecoTrackPrimaryParticleTruePositionTrackStart[j*4 + 2]) > 890.:
Reco_Start_2[i, j, 0] = StartPos[j*3 + 0]
Reco_Start_2[i, j, 1] = StartPos[j*3 + 1]
Reco_Start_2[i, j, 2] = StartPos[j*3 + 2]
Primary_True_Start_2[i, j, 0] = RecoTrackPrimaryParticleTruePositionTrackStart[j*4 + 0]
Primary_True_Start_2[i, j, 1] = RecoTrackPrimaryParticleTruePositionTrackStart[j*4 + 1]
Primary_True_Start_2[i, j, 2] = RecoTrackPrimaryParticleTruePositionTrackStart[j*4 + 2]
if RecoTrackPrimaryParticleTruePositionTrackEnd[j*4 + 0] > -8000. and not EndPos.size == 0:
if (EndPos[j*3 + 2] - StartPos[j*3 + 2]) > 890. and (RecoTrackPrimaryParticleTruePositionTrackEnd[j*4 + 2] - RecoTrackPrimaryParticleTruePositionTrackStart[j*4 + 2]) > 890.:
Reco_End_2[i, j, 0] = EndPos[j*3 + 0]
Reco_End_2[i, j, 1] = EndPos[j*3 + 1]
Reco_End_2[i, j, 2] = EndPos[j*3 + 2]
Primary_True_End_2[i, j, 0] = RecoTrackPrimaryParticleTruePositionTrackEnd[j*4 + 0]
Primary_True_End_2[i, j, 1] = RecoTrackPrimaryParticleTruePositionTrackEnd[j*4 + 1]
Primary_True_End_2[i, j, 2] = RecoTrackPrimaryParticleTruePositionTrackEnd[j*4 + 2]

# filter out not filled indice
boolean_Reco_Start_1 = (Reco_Start_1[:, 0] != -9999.)
boolean_Reco_Start_1 = (Reco_Start_1[:, :, 0] != -9999.)
Reco_Start_1 = Reco_Start_1[boolean_Reco_Start_1]
boolean_Reco_End_1 = (Reco_End_1[:, 0] != -9999.)
boolean_Reco_End_1 = (Reco_End_1[:, :, 0] != -9999.)
Reco_End_1 = Reco_End_1[boolean_Reco_End_1]
boolean_Primary_Start_1 = (Primary_True_Start_1[:, 0] != -9999.)
boolean_Primary_Start_1 = (Primary_True_Start_1[:, :, 0] != -9999.)
Primary_True_Start_1 = Primary_True_Start_1[boolean_Primary_Start_1]
boolean_Primary_End_1 = (Primary_True_End_1[:, 0] != -9999.)
boolean_Primary_End_1 = (Primary_True_End_1[:, :, 0] != -9999.)
Primary_True_End_1 = Primary_True_End_1[boolean_Primary_End_1]

boolean_Reco_Start_2 = (Reco_Start_2[:, 0] != -9999.)
boolean_Reco_Start_2 = (Reco_Start_2[:, :, 0] != -9999.)
Reco_Start_2 = Reco_Start_2[boolean_Reco_Start_2]
boolean_Reco_End_2 = (Reco_End_2[:, 0] != -9999.)
boolean_Reco_End_2 = (Reco_End_2[:, :, 0] != -9999.)
Reco_End_2 = Reco_End_2[boolean_Reco_End_2]
boolean_Primary_Start_2 = (Primary_True_Start_2[:, 0] != -9999.)
boolean_Primary_Start_2 = (Primary_True_Start_2[:, :, 0] != -9999.)
Primary_True_Start_2 = Primary_True_Start_2[boolean_Primary_Start_2]
boolean_Primary_End_2 = (Primary_True_End_2[:, 0] != -9999.)
boolean_Primary_End_2 = (Primary_True_End_2[:, :, 0] != -9999.)
Primary_True_End_2 = Primary_True_End_2[boolean_Primary_End_2]

# subtract reconstruction from truth for all directions
Expand Down Expand Up @@ -299,7 +309,7 @@ def draw_comparison(out_dir, input_filename1, input_filename2):
# create histograms for all directions for truth and reconstruction


Reco_Start_x_1_hist, Reco_Start_x_1_bins = np.histogram(Reco_Start_1[:, 0], bins = 3, range = (-35.42, 35.42)) #int((max(Reco_Start_1[:, 0]) - min(Reco_Start_1[:, 0])) / 35.42)) #48
Reco_Start_x_1_hist, Reco_Start_x_1_bins = np.histogram(Reco_Start_1[:, 0], bins = int((max(Reco_Start_1[:, 0]) - min(Reco_Start_1[:, 0])) / 35.42))#3, range = (-35.42, 35.42)) # #48
Reco_Start_y_1_hist, Reco_Start_y_1_bins = np.histogram(Reco_Start_1[:, 1], bins = 40)#, range = (-4110., -910.))
Reco_Start_z_1_hist, Reco_Start_z_1_bins = np.histogram(Reco_Start_1[:, 2], bins = 100)#, range = (11360., 18320.))
Reco_End_x_1_hist, Reco_End_x_1_bins = np.histogram(Reco_End_1[:, 0], bins = int((max(Reco_End_1[:, 0]) - min(Reco_End_1[:, 0])) / 35.42))#48)#, range = (-3400., 3400.))
Expand All @@ -312,7 +322,7 @@ def draw_comparison(out_dir, input_filename1, input_filename2):
Primary_True_End_y_1_hist, Primary_True_End_y_1_bins = np.histogram(Primary_True_End_1[:, 1], bins = Reco_End_y_1_bins)#20)
Primary_True_End_z_1_hist, Primary_True_End_z_1_bins = np.histogram(Primary_True_End_1[:, 2], bins = 100)

Reco_Start_x_2_hist, Reco_Start_x_2_bins = np.histogram(Reco_Start_2[:, 0], bins = 3, range = (-35.42, 35.42))#10)#int((max(Reco_Start_2[:, 0]) - min(Reco_Start_2[:, 0])) / 35.42)) #48)#, range = (-3400., 3400.))
Reco_Start_x_2_hist, Reco_Start_x_2_bins = np.histogram(Reco_Start_2[:, 0], bins = int((max(Reco_Start_2[:, 0]) - min(Reco_Start_2[:, 0])) / 35.42))#3, range = (-35.42, 35.42))#10)# #48)#
Reco_Start_y_2_hist, Reco_Start_y_2_bins = np.histogram(Reco_Start_2[:, 1], bins = 40)#, range = (-4110., -910.))
Reco_Start_z_2_hist, Reco_Start_z_2_bins = np.histogram(Reco_Start_2[:, 2], bins = 100)#, range = (11360., 18320.))
Reco_End_x_2_hist, Reco_End_x_2_bins = np.histogram(Reco_End_2[:, 0], bins = int((max(Reco_End_2[:, 0]) - min(Reco_End_2[:, 0])) / 35.42)) #48)#, range = (-3400., 3400.))
Expand Down
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