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albanpuech
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Jan 16, 2026
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| # Optional strict coverage check (comment out if you allow missing => 0) | ||
| expected = n_buses * n_scenarios | ||
| actual = df[["load_scenario", "load"]].drop_duplicates().shape[0] |
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I'll modify it to ensure strict checks
| out = np.zeros((n_buses, n_scenarios, 2), dtype=float) | ||
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| # If duplicates exist, keep last | ||
| df = df.sort_index().drop_duplicates(subset=["load_scenario", "load"], keep="last") |
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shouldnt we enforce no duplicate from the start?
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Yes, will update with checks to ensure right bus numbers, right load_scenario numbers, no duplicates, etc
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@hithuv can you please check the following? maybe in the init of the class
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To generate data with precomputed load scenarios loaded from a csv with columns: load_scenario, load, p_mw, q_mvar
Add this argument to config yaml file
scenario_file: "/path/to/load-scenarios/load-scenarios-precomputed-temp.csv" # precomputed scenarios (cols: load_scenario, load, p_mw, q_mvar)