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Add script to calc rewards from delegation.
This commit is contained in:
FiveMovesAhead
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151
tig-benchmarker/calc_rewards.py
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151
tig-benchmarker/calc_rewards.py
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import numpy as np
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import json
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import requests
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from typing import List, Dict
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from common.structs import *
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from copy import deepcopy
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def calc_influence(fractions, opow_config) -> Dict[str, float]:
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benchmarkers = list(fractions)
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factors = list(next(iter(fractions.values())))
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num_challenges = len(factors) - 1
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avg_qualifier_fractions = {
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benchmarker: sum(
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fractions[benchmarker][f]
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for f in factors
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if f != "weighted_deposit"
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) / num_challenges
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for benchmarker in benchmarkers
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}
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deposit_fraction_cap = {
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benchmarker: avg_qualifier_fractions[benchmarker] * opow_config["max_deposit_to_qualifier_ratio"]
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for benchmarker in benchmarkers
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}
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capped_fractions = {
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benchmarker: {
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**fractions[benchmarker],
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"weighted_deposit": min(
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fractions[benchmarker]["weighted_deposit"],
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deposit_fraction_cap[benchmarker]
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)
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}
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for benchmarker in benchmarkers
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}
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avg_fraction = {
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benchmarker: np.mean(list(capped_fractions[benchmarker].values()))
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for benchmarker in benchmarkers
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}
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var_fraction = {
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benchmarker: np.var(list(capped_fractions[benchmarker].values()))
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for benchmarker in benchmarkers
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}
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imbalance = {
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benchmarker: (var_fraction[benchmarker] / np.square(avg_fraction[benchmarker]) / num_challenges) if avg_fraction[benchmarker] > 0 else 0
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for benchmarker in benchmarkers
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}
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imbalance_penalty = {
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benchmarker: 1.0 - np.exp(-opow_config["imbalance_multiplier"] * imbalance[benchmarker])
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for benchmarker in benchmarkers
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}
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weighted_avg_fraction = {
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benchmarker: ((avg_qualifier_fractions[benchmarker] * num_challenges) + capped_fractions[benchmarker]["weighted_deposit"] * opow_config["deposit_multiplier"]) / (num_challenges + opow_config["deposit_multiplier"])
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for benchmarker in benchmarkers
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}
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unormalised_influence = {
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benchmarker: weighted_avg_fraction[benchmarker] * (1.0 - imbalance_penalty[benchmarker])
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for benchmarker in benchmarkers
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}
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total = sum(unormalised_influence.values())
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influence = {
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benchmarker: unormalised_influence[benchmarker] / total
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for benchmarker in benchmarkers
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}
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return influence
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API_URL = "https://mainnet-api.tig.foundation"
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player_id = input("Enter player_id: ").lower()
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print("Fetching data...")
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block = Block.from_dict(requests.get(f"{API_URL}/get-block?include_data").json()["block"])
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opow_data = {
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x["player_id"]: OPoW.from_dict(x)
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for x in requests.get(f"{API_URL}/get-opow?block_id={block.id}").json()["opow"]
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}
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player_data = Player.from_dict(requests.get(f"{API_URL}/get-player-data?player_id={player_id}&block_id={block.id}").json()["player"])
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factors = {
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benchmarker: {
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**{
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f: opow_data[benchmarker].block_data.num_qualifiers_by_challenge.get(f, 0)
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for f in block.data.active_ids["challenge"]
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},
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"weighted_deposit": opow_data[benchmarker].block_data.delegated_weighted_deposit.to_float()
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}
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for benchmarker in opow_data
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}
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total_factors = {
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f: sum(factors[benchmarker][f] for benchmarker in opow_data)
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for f in list(block.data.active_ids["challenge"]) + ["weighted_deposit"]
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}
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fractions = {
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benchmarker: {
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f: factors[benchmarker][f] / total_factors[f]
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for f in total_factors
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}
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for benchmarker in opow_data
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}
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sum_other_deposit_fractions = sum(
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fractions[benchmarker]["weighted_deposit"] for benchmarker in opow_data if benchmarker != player_id
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)
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def simulate_deposit_fraction(deposit_fraction):
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delta = fractions[player_id]["weighted_deposit"] - deposit_fraction
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fractions2 = deepcopy(fractions)
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for benchmarker in opow_data:
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if benchmarker != player_id:
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fractions2[benchmarker]["weighted_deposit"] += delta * fractions[benchmarker]["weighted_deposit"] / sum_other_deposit_fractions
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else:
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fractions2[benchmarker]["weighted_deposit"] = deposit_fraction
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influence = calc_influence(fractions2, block.config["opow"])
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return influence[player_id]
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print("Calculating rewards...")
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average_fraction_of_qualifiers = sum(fractions[player_id][f] for f in block.data.active_ids["challenge"]) / len(block.data.active_ids["challenge"])
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self_only_deposit_fraction = player_data.block_data.weighted_deposit.to_float() / total_factors["weighted_deposit"]
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influence = {
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"current": opow_data[player_id].block_data.influence.to_float(),
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"only_self_deposit": simulate_deposit_fraction(self_only_deposit_fraction),
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"at_parity": simulate_deposit_fraction(average_fraction_of_qualifiers)
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}
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current_reward = opow_data[player_id].block_data.reward.to_float()
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reward = {
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"current": current_reward,
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"only_self_deposit": influence["only_self_deposit"] / influence["current"] * current_reward,
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"at_parity": influence["at_parity"] / influence["current"] * current_reward
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}
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print("-----Current State-----")
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for f in sorted(block.data.active_ids["challenge"]):
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print(f"%qualifiers for {f}: {fractions[player_id][f] * 100:.2f}%")
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print(f"average %qualifiers: {average_fraction_of_qualifiers * 100:.2f}%")
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print(f"%weighted_deposit (self only): {self_only_deposit_fraction * 100:.2f}%")
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print(f"%weighted_deposit (current self + delegated): {fractions[player_id]['weighted_deposit'] * 100:.2f}%")
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print("----------------------")
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print(f"Scenario 1 (only self-deposit)")
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print(f"%weighted_deposit = {self_only_deposit_fraction * 100:.2f}%")
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print(f"reward = {reward['only_self_deposit']:.4f} TIG per block")
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print("")
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print("Scenario 2 (current self + delegated deposit)")
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print(f"%weighted_deposit = {fractions[player_id]['weighted_deposit'] * 100:.2f}%")
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print(f"reward = {reward['current']:.4f} TIG per block ({reward['current'] / reward['only_self_deposit'] * 100 - 100:.2f}% difference*)")
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print("")
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print(f"Scenario 3 (self + delegated deposit at parity)")
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print(f"%weighted_deposit = average %qualifiers = {average_fraction_of_qualifiers * 100:.2f}%")
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print(f"reward = {reward['at_parity']:.4f} TIG per block ({reward['at_parity'] / reward['only_self_deposit'] * 100 - 100:.2f}% difference*)")
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print("")
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print("*These are percentage differences in reward compared with relying only on self-deposit (Scenario 1).")
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print("")
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print("Note: the imbalance penalty is such that your reward increases at a high rate when moving up to parity")
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