|
4 | 4 | # here only define the workflows as a combination of the steps defined above: |
5 | 5 | workflows = Matrix() |
6 | 6 |
|
7 | | -## Here we define higher (>50k events) stats data workflows |
8 | | -## not to be run as default. 150k, 250k, 500k or 1M events each |
| 7 | +## Here we define fixed high stats data workflows |
| 8 | +## not to be run as default. 10k, 50k, 150k, 250k, 500k or 1M events each |
9 | 9 |
|
10 | 10 | offset_era = 0.1 # less than 10 eras per year |
11 | 11 | offset_pd = 0.001 # less than 100 pds per year |
12 | | -offset_events = 0.0001 # less than 10 event setups (50k,150k,250k,500k) |
| 12 | +offset_events = 0.0001 # less than 10 event setups (10k,50k,150k,250k,500k,1M) |
13 | 13 |
|
14 | 14 | ## 2024 |
15 | 15 | base_wf = 2024.0 |
16 | 16 | for e_n,era in enumerate(eras_2024): |
17 | 17 | for p_n,pd in enumerate(pds_2024): |
18 | | - for e_key,evs in event_steps_dict.items(): |
19 | | - if "10k" == e_key: # already defined in relval_standard |
20 | | - continue |
| 18 | + for e_key,evs in event_steps_dict.items(): |
21 | 19 | wf_number = base_wf |
22 | 20 | wf_number = wf_number + offset_era * e_n |
23 | 21 | wf_number = wf_number + offset_pd * p_n |
24 | 22 | wf_number = wf_number + offset_events * evs |
25 | 23 | wf_number = round(wf_number,6) |
26 | | - |
27 | | - step_name = "Run" + pd.replace("ParkingDouble","Park2") + era.split("Run")[1] + "_" + e_key |
| 24 | + step_name = 'Run' + pd.replace('ParkingDouble','Park2') + era.split('Run')[1] + '_' + e_key |
28 | 25 | y = str(int(base_wf)) |
29 | | - suff = "ZB_" if "ZeroBias" in step_name else "" |
| 26 | + suff = 'ZB_' if 'ZeroBias' in step_name else '' |
| 27 | + # Running C,D,E with the offline GT. |
| 28 | + # Could be removed once 2025 wfs are in and we'll test the online GT with them |
| 29 | + recosetup = 'RECONANORUN3_' + suff + 'reHLT_2024' |
| 30 | + recosetup = recosetup if era[-1] > 'E' else recosetup + '_Offline' |
30 | 31 | workflows[wf_number] = ['',[step_name,'HLTDR3_' + y,'RECONANORUN3_' + suff + 'reHLT_'+y,'HARVESTRUN3_' + suff + y]] |
31 | 32 |
|
32 | 33 | ## 2023 |
33 | 34 | base_wf = 2023.0 |
34 | 35 | for e_n,era in enumerate(eras_2023): |
35 | 36 | for p_n,pd in enumerate(pds_2023): |
36 | | - for e_key,evs in event_steps_dict.items(): |
37 | | - if "10k" == e_key: # already defined in relval_standard |
38 | | - continue |
| 37 | + for e_key,evs in event_steps_dict.items(): |
39 | 38 | wf_number = base_wf |
40 | 39 | wf_number = wf_number + offset_era * e_n |
41 | 40 | wf_number = wf_number + offset_pd * p_n |
42 | 41 | wf_number = wf_number + offset_events * evs |
43 | 42 | wf_number = round(wf_number,6) |
44 | | - |
45 | | - step_name = "Run" + pd.replace("ParkingDouble","Park2") + era.split("Run")[1] + "_" + e_key |
46 | | - y = str(int(base_wf)) + "B" if "2023B" in era else str(int(base_wf)) |
47 | | - suff = "ZB_" if "ZeroBias" in step_name else "" |
| 43 | + step_name = 'Run' + pd.replace('ParkingDouble','Park2') + era.split('Run')[1] + '_' + e_key |
| 44 | + y = str(int(base_wf)) + 'B' if '2023B' in era else str(int(base_wf)) |
| 45 | + suff = 'ZB_' if 'ZeroBias' in step_name else '' |
48 | 46 | workflows[wf_number] = ['',[step_name,'HLTDR3_' + y,'RECONANORUN3_' + suff + 'reHLT_'+y,'HARVESTRUN3_' + suff + y]] |
49 | 47 |
|
50 | 48 | ## 2022 |
51 | 49 | base_wf = 2022.0 |
52 | 50 | for e_n,era in enumerate(eras_2022_1): |
53 | 51 | for p_n,pd in enumerate(pds_2022_1): |
54 | | - for e_key,evs in event_steps_dict.items(): |
55 | | - if "10k" == e_key: # already defined in relval_standard |
56 | | - continue |
| 52 | + for e_key,evs in event_steps_dict.items(): |
57 | 53 | wf_number = base_wf |
58 | 54 | wf_number = wf_number + offset_era * e_n |
59 | 55 | wf_number = wf_number + offset_pd * p_n |
60 | 56 | wf_number = wf_number + offset_events * evs |
61 | 57 | wf_number = round(wf_number,6) |
62 | | - step_name = "Run" + pd + era.split("Run")[1] + "_" + e_key |
| 58 | + step_name = 'Run' + pd + era.split('Run')[1] + '_' + e_key |
63 | 59 | y = str(int(base_wf)) |
64 | | - suff = "ZB_" if "ZeroBias" in step_name else "" |
| 60 | + suff = 'ZB_' if 'ZeroBias' in step_name else '' |
65 | 61 | workflows[wf_number] = ['',[step_name,'HLTDR3_' + y,'RECONANORUN3_' + suff + 'reHLT_'+y,'HARVESTRUN3_' + suff + y]] |
66 | 62 |
|
67 | 63 | # PD names changed during 2022 |
68 | 64 | for e_n,era in enumerate(eras_2022_2): |
69 | 65 | for p_n,pd in enumerate(pds_2022_2): |
70 | | - for e_key,evs in event_steps_dict.items(): |
71 | | - if "10k" == e_key: # already defined in relval_standard |
72 | | - continue |
| 66 | + for e_key,evs in event_steps_dict.items(): |
73 | 67 | wf_number = base_wf |
74 | 68 | wf_number = wf_number + offset_era * (e_n + len(eras_2022_1)) |
75 | 69 | wf_number = wf_number + offset_pd * (p_n + len(pds_2022_1)) |
76 | 70 | wf_number = wf_number + offset_events * evs |
77 | 71 | wf_number = round(wf_number,6) |
78 | | - step_name = "Run" + pd + era.split("Run")[1] + "_" + e_key |
| 72 | + step_name = 'Run' + pd + era.split('Run')[1] + '_' + e_key |
79 | 73 | y = str(int(base_wf)) |
80 | | - suff = "ZB_" if "ZeroBias" in step_name else "" |
| 74 | + suff = 'ZB_' if 'ZeroBias' in step_name else '' |
81 | 75 | workflows[wf_number] = ['',[step_name,'HLTDR3_' + y,'RECONANORUN3_' + suff + 'reHLT_'+y,'HARVESTRUN3_' + suff + y]] |
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