{
  "sources": [
    {
      "url": "https://api.imd.fun/artifacts/4d396adc0e3056c010e59ab8c3d413eb0380a14e8cefa6cd825e809fa2494999",
      "quote": "4da9e3ae826b3b6f9170948bd2c2c0a494e78521414341656425b76e71c0f964"
    },
    {
      "url": "https://api.imd.fun/artifacts/afd5183e9ff3235334e041c00b0cd19079599a2c6464db95f8c1586712105557",
      "quote": "f63227c5e0f63633efd132d6fb402ede665e5c9cb24481911471e8dc20a3362d"
    },
    {
      "url": "https://api.imd.fun/artifacts/e8a7a2af9039c24b8bb2d3b5fa1c9113606cbf5a480ac07d02ca26750f1752ea",
      "quote": "1e4c44b4bffbdeed65872ee15d46dbde209bf5aa11014329d13d100507b4040c"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py",
      "quote": "            rng = np.random.default_rng(seed=i)"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/config.py",
      "quote": "BASELINE_VARIANCE = HyperparameterVariance(\n    retail_mean_size_min=19.0,\n    retail_mean_size_max=21.0,\n    vary_retail_mean_size=True,\n    retail_arrival_rate_min=0.6,\n    retail_arrival_rate_max=1.0,\n    vary_retail_arrival_rate=True,\n    gbm_sigma_min=0.000882,\n    gbm_sigma_max=0.001008,\n    vary_gbm_sigma=True,\n)"
    }
  ]
}