Participant: MA3033

Time Zone: America/New_York

No message

Sep 08, 2026 11:30:00 EDT
Epoch Time: 1788881400
Created: 2026-09-08 11:30:10 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 11:15:00 EDT
Epoch Time: 1788880500
Created: 2026-09-08 11:15:11 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 11:00:00 EDT
Epoch Time: 1788879600
Created: 2026-09-08 11:00:14 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 10:45:00 EDT
Epoch Time: 1788878700
Created: 2026-09-08 10:45:18 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 10:30:00 EDT
Epoch Time: 1788877800
Created: 2026-09-08 10:30:17 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 10:15:00 EDT
Epoch Time: 1788876900
Created: 2026-09-08 10:15:18 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 10:00:00 EDT
Epoch Time: 1788876000
Created: 2026-09-08 10:00:17 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 09:45:00 EDT
Epoch Time: 1788875100
Created: 2026-09-08 09:45:10 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 09:30:00 EDT
Epoch Time: 1788874200
Created: 2026-09-08 09:30:11 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 09:15:00 EDT
Epoch Time: 1788873300
Created: 2026-09-08 09:15:08 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 09:00:00 EDT
Epoch Time: 1788872400
Created: 2026-09-08 09:00:09 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 08:45:00 EDT
Epoch Time: 1788871500
Created: 2026-09-08 08:45:06 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 08:30:00 EDT
Epoch Time: 1788870600
Created: 2026-09-08 08:30:06 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 08:15:00 EDT
Epoch Time: 1788869700
Created: 2026-09-08 08:15:05 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 08:00:00 EDT
Epoch Time: 1788868800
Created: 2026-09-08 08:00:05 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 07:45:00 EDT
Epoch Time: 1788867900
Created: 2026-09-08 07:45:04 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 07:30:00 EDT
Epoch Time: 1788867000
Created: 2026-09-08 07:30:04 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 07:15:00 EDT
Epoch Time: 1788866100
Created: 2026-09-08 07:15:04 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 07:00:00 EDT
Epoch Time: 1788865200
Created: 2026-09-08 07:00:05 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 06:45:00 EDT
Epoch Time: 1788864300
Created: 2026-09-08 06:45:02 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 06:30:00 EDT
Epoch Time: 1788863400
Created: 2026-09-08 06:30:01 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 06:15:00 EDT
Epoch Time: 1788862500
Created: 2026-09-08 06:15:01 EDT
Fitbit data rows: 0

No message

Sep 08, 2026 06:00:00 EDT
Epoch Time: 1788861600
Created: 2026-09-08 06:00:01 EDT
Fitbit data rows: 0

No message

Sep 07, 2026 17:45:00 EDT
Epoch Time: 1788817500
Created: 2026-09-07 17:45:16 EDT
Fitbit data rows: 33
Script Error 17:45:16
Category: script error
Description: Set parameter WLSAccessID Set parameter WLSSecret Set parameter LicenseID to value 2722107 Academic license 2722107 - for non-commercial use only - registered to am___@umich.edu Gurobi Optimizer version 12.0.3 build v12.0.3rc0 (linux64 - "Ubuntu 24.04.2 LTS") CPU model: Intel(R) Xeon(R) Platinum 8358 CPU @ 2.60GHz, instruction set [SSE2|AVX|AVX2|AVX512] Thread count: 4 physical cores, 4 logical processors, using up to 4 threads Academic license 2722107 - for non-commercial use only - registered to am___@umich.edu Optimize a model with 2266 rows, 2265 columns and 3477 nonzeros Model fingerprint: 0x74dd485f Variable types: 1053 continuous, 1212 integer (1212 binary) Coefficient statistics: Matrix range [1e+00, 2e+05] Objective range [1e-03, 1e-03] Bounds range [1e+00, 2e+05] RHS range [1e+00, 2e+05] Found heuristic solution: objective -0.0000000 Presolve removed 2266 rows and 2265 columns Presolve time: 0.00s Presolve: All rows and columns removed Explored 0 nodes (0 simplex iterations) in 0.00 seconds (0.00 work units) Thread count was 1 (of 4 available processors) Solution count 1: -0 No other solutions better than -0 Optimal solution found (tolerance 1.00e-04) Best objective -0.000000000000e+00, best bound -0.000000000000e+00, gap 0.0000% Gurobi Optimizer version 12.0.3 build v12.0.3rc0 (linux64 - "Ubuntu 24.04.2 LTS") CPU model: Intel(R) Xeon(R) Platinum 8358 CPU @ 2.60GHz, instruction set [SSE2|AVX|AVX2|AVX512] Thread count: 4 physical cores, 4 logical processors, using up to 4 threads Academic license 2722107 - for non-commercial use only - registered to am___@umich.edu Optimize a model with 2266 rows, 2265 columns and 3477 nonzeros Model fingerprint: 0x74dd485f Variable types: 1053 continuous, 1212 integer (1212 binary) Coefficient statistics: Matrix range [1e+00, 2e+05] Objective range [1e-03, 1e-03] Bounds range [1e+00, 2e+05] RHS range [1e+00, 2e+05] Presolve removed 2266 rows and 2265 columns Presolve time: 0.00s Presolve: All rows and columns removed Explored 0 nodes (0 simplex iterations) in 0.00 seconds (0.00 work units) Thread count was 1 (of 4 available processors) Solution count 1: -0 No other solutions better than -0 Optimal solution found (tolerance 1.00e-04) Best objective -0.000000000000e+00, best bound -0.000000000000e+00, gap 0.0000% Traceback (most recent call last): File "/home/deploy/matchaim-controller/controller_run.py", line 18, in <module> message_output = controller_fn(model_file_path, measurements_file_path, int(daily_iterations),int(group_numer)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/deploy/matchaim-controller/controller_func_2inp.py", line 368, in controller_fn message_output = [u1_sol[iteration],u2_sol[iteration],u3_sol[iteration],0] ~~~~~~^^^^^^^^^^^ KeyError: np.int64(53) Warning: environment still referenced so free is deferred (Continue to use WLS)
Command:
python3 /home/deploy/matchaim-controller/controller_run.py /home/deploy/matchaim-data/models/MAxxx.csv shared/measurement_files/MA3033_measurements_2026-09-07.csv 48 3 2>&1
Error created: 2026-09-07 17:45:16 EDT

No message

Sep 07, 2026 17:30:00 EDT
Epoch Time: 1788816600
Created: 2026-09-07 17:30:16 EDT
Fitbit data rows: 32
Version: 26.06.22.15.30 on SFR-MATCH-AIM