{"sources":[{"url":"https://api.imd.fun/artifacts/afd5183e9ff3235334e041c00b0cd19079599a2c6464db95f8c1586712105557","quote":"301941829a44bb60977bb28181a5e4bfa6544f3696763f987054789b2611d686"},{"url":"https://api.imd.fun/artifacts/12606d82ec57ee9fe351945ec520b1ab8d79c8a472ff46b3bce6c5c0693b7b49","quote":"9253b6f3a49eafc1ed21ad19d9e2c0761c2ff151a6a7aa81e16de83834ad6a1b"},{"url":"https://api.imd.fun/artifacts/3d001532cce4c2885307bb007a5170f77dd4b2f8151d041696e04a1c60a0f475","quote":"cb6d945511e1e10af78baa64c2a6cb25806f0998403ce6440654bfc3c70092d9"},{"url":"https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py","quote":"            rng = np.random.default_rng(seed=i)\n\n            retail_mean_size = (\n                rng.uniform(self.variance.retail_mean_size_min, self.variance.retail_mean_size_max)\n                if self.variance.vary_retail_mean_size\n                else self.base_config.retail_mean_size\n            )\n            retail_arrival_rate = ("},{"url":"https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/config.py","quote":"    n_steps=10000,\n    initial_price=100.0,\n    initial_x=100.0,\n    initial_y=10000.0,"},{"url":"https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/contracts/src/VanillaStrategy.sol","quote":"    uint256 public constant FEE = 30 * BPS;"}]}