I'm trying to understand some results available in picketfence.result_data['mlc_positions_by_leaf'] dictionnary.
For example, using an integrated image with 10 pickets
- 'offsets_from_cax_mm': [65.26953901931351, 50.28011012703084, 35.27186791603355, 20.266991623371677, 5.260303567943333, -9.751371576478455, -24.757808639163564, -39.76862481744024, -54.783193605823556, -69.75075800609807],
- 'mlc_positions_by_leaf': {
[...]
'15': [131.43360342737398, 146.42161475299872, 161.43251387842128, 176.44624194002458, 191.46825779373773, 206.49736620570349, 221.5258751568509, 236.53135100021882, 251.5530831470596, 266.5205398505989],
'16': [131.47908671525886, 146.4807264723526, 161.4737616589679, 176.49306290128303, 191.49040290413393, 206.48751214912562, 221.4841243604419, 236.5021192599006, 251.53165394985348, 266.4991951454547],
[...]
I understand that maybe my origin is not the same but i'm struggling to understand the kind of distances I got in mlc_positions_by_leaf' {} ?
For example for leaf15 my first picket position (picket[0]) is at 131.43360342737398mm but from cax my 'mean" corresponding picket position is
65.26953901931351mm.
My corresponding last picket position is 266.5205398505989?
Could youi give me some detail to understand it?
My theoretical position from my RTPlan for picket[0] is 65mm. What is thus my corresponding absolute position error for leaf 15, picket[0] ?
Thanks in advance for your help.
François