package testutil

import (
	"encoding/csv"
	"encoding/hex"
	"fmt"
	"math/rand"
	"strings"

	cosmosMath "cosmossdk.io/math"
	"github.com/cometbft/cometbft/crypto/secp256k1"
	sdk "github.com/cosmos/cosmos-sdk/types"

	alloraMath "github.com/allora-network/allora-chain/math"
	"github.com/allora-network/allora-chain/utils"
	"github.com/allora-network/allora-chain/x/emissions/keeper"
	inferencesynthesis "github.com/allora-network/allora-chain/x/emissions/keeper/inference_synthesis"
	emissionstypes "github.com/allora-network/allora-chain/x/emissions/types"
)

var valueBundleBufferPool = utils.NewBytesPool(1024, 0)

func GenerateTestAccounts(count int) (
	privKeys []secp256k1.PrivKey,
	pubKeyHexStr []string,
	addrs []sdk.AccAddress,
	addrsStr []string,
) {
	privKeys = make([]secp256k1.PrivKey, count)
	pubKeyHexStr = make([]string, count)
	addrs = make([]sdk.AccAddress, count)
	addrsStr = make([]string, count)
	for i := 0; i < count; i++ {
		privKeys[i] = secp256k1.GenPrivKey()
		addrs[i] = sdk.AccAddress(privKeys[i].PubKey().Address())
		pubKeyHexStr[i] = hex.EncodeToString(privKeys[i].PubKey().Bytes())
		addrsStr[i] = addrs[i].String()
	}
	return privKeys, pubKeyHexStr, addrs, addrsStr
}

//nolint:gosec
func GenerateTestStakes(count int) []cosmosMath.Int {
	minStake := int64(200000)
	maxStake := int64(1200000)

	stakes := make([]cosmosMath.Int, count)
	cosmosOneE18 := inferencesynthesis.CosmosIntOneE18()

	for i := 0; i < count; i++ {
		randomValue := minStake + rand.Int63n(maxStake-minStake)

		stakes[i] = cosmosMath.NewInt(randomValue).Mul(cosmosOneE18)
	}

	return stakes
}

func GetSimulatedValuesGetterForEpoch(
	epoch string,
	headers string,
) func(header string) alloraMath.Dec {
	r := csv.NewReader(strings.NewReader(headers + "\n" + epoch + "\n"))
	headersRead, err := r.Read()
	if err != nil {
		panic(err)
	}
	valuesRead, err := r.Read()
	if err != nil {
		panic(err)
	}
	simulatedValuesDec := make(map[string]alloraMath.Dec)
	if len(headersRead) != len(valuesRead) {
		panic("Header and values length mismatch")
	}
	for i := 0; i < len(headersRead); i++ {
		simulatedValuesDec[headersRead[i]] = alloraMath.MustNewDecFromString(valuesRead[i])
	}

	return func(header string) alloraMath.Dec {
		value, exists := simulatedValuesDec[header]
		if !exists {
			panic(fmt.Sprintf("Header '%s' not found in simulated values map", header))
		}
		return value
	}
}

func GetSimulatedValuesGetterForEpochs() map[int]func(header string) alloraMath.Dec {
	const simulatorHeaders = "target,inference_0,inference_1,inference_2,inference_3,inference_4,forecasted_loss_0_for_0,forecasted_loss_0_for_1,forecasted_loss_0_for_2,forecasted_loss_0_for_3,forecasted_loss_0_for_4,forecasted_loss_1_for_0,forecasted_loss_1_for_1,forecasted_loss_1_for_2,forecasted_loss_1_for_3,forecasted_loss_1_for_4,forecasted_loss_2_for_0,forecasted_loss_2_for_1,forecasted_loss_2_for_2,forecasted_loss_2_for_3,forecasted_loss_2_for_4,forecast_implied_inference_0,forecast_implied_inference_1,forecast_implied_inference_2,forecast_implied_inference_0_oneout_0,forecast_implied_inference_0_oneout_1,forecast_implied_inference_0_oneout_2,forecast_implied_inference_0_oneout_3,forecast_implied_inference_0_oneout_4,forecast_implied_inference_1_oneout_0,forecast_implied_inference_1_oneout_1,forecast_implied_inference_1_oneout_2,forecast_implied_inference_1_oneout_3,forecast_implied_inference_1_oneout_4,forecast_implied_inference_2_oneout_0,forecast_implied_inference_2_oneout_1,forecast_implied_inference_2_oneout_2,forecast_implied_inference_2_oneout_3,forecast_implied_inference_2_oneout_4,network_inference,network_inference_errorbar_0,network_inference_errorbar_1,network_inference_errorbar_2,network_inference_errorbar_3,network_inference_errorbar_4,network_naive_inference,network_inference_oneout_0,network_inference_oneout_1,network_inference_oneout_2,network_inference_oneout_3,network_inference_oneout_4,network_inference_oneout_5,network_inference_oneout_6,network_inference_oneout_7,network_naive_inference_onein_0,network_naive_inference_onein_1,network_naive_inference_onein_2,network_loss,reputer_stake_0,reputer_stake_1,reputer_stake_2,reputer_stake_3,reputer_stake_4,reputer_0_loss_inference_0,reputer_0_loss_inference_1,reputer_0_loss_inference_2,reputer_0_loss_inference_3,reputer_0_loss_inference_4,reputer_1_loss_inference_0,reputer_1_loss_inference_1,reputer_1_loss_inference_2,reputer_1_loss_inference_3,reputer_1_loss_inference_4,reputer_2_loss_inference_0,reputer_2_loss_inference_1,reputer_2_loss_inference_2,reputer_2_loss_inference_3,reputer_2_loss_inference_4,reputer_3_loss_inference_0,reputer_3_loss_inference_1,reputer_3_loss_inference_2,reputer_3_loss_inference_3,reputer_3_loss_inference_4,reputer_4_loss_inference_0,reputer_4_loss_inference_1,reputer_4_loss_inference_2,reputer_4_loss_inference_3,reputer_4_loss_inference_4,reputer_0_loss_forecast_implied_inference_0,reputer_0_loss_forecast_implied_inference_1,reputer_0_loss_forecast_implied_inference_2,reputer_1_loss_forecast_implied_inference_0,reputer_1_loss_forecast_implied_inference_1,reputer_1_loss_forecast_implied_inference_2,reputer_2_loss_forecast_implied_inference_0,reputer_2_loss_forecast_implied_inference_1,reputer_2_loss_forecast_implied_inference_2,reputer_3_loss_forecast_implied_inference_0,reputer_3_loss_forecast_implied_inference_1,reputer_3_loss_forecast_implied_inference_2,reputer_4_loss_forecast_implied_inference_0,reputer_4_loss_forecast_implied_inference_1,reputer_4_loss_forecast_implied_inference_2,reputer_0_loss_forecast_implied_inference_0_oneout_0,reputer_0_loss_forecast_implied_inference_0_oneout_1,reputer_0_loss_forecast_implied_inference_0_oneout_2,reputer_0_loss_forecast_implied_inference_0_oneout_3,reputer_0_loss_forecast_implied_inference_0_oneout_4,reputer_0_loss_forecast_implied_inference_1_oneout_0,reputer_0_loss_forecast_implied_inference_1_oneout_1,reputer_0_loss_forecast_implied_inference_1_oneout_2,reputer_0_loss_forecast_implied_inference_1_oneout_3,reputer_0_loss_forecast_implied_inference_1_oneout_4,reputer_0_loss_forecast_implied_inference_2_oneout_0,reputer_0_loss_forecast_implied_inference_2_oneout_1,reputer_0_loss_forecast_implied_inference_2_oneout_2,reputer_0_loss_forecast_implied_inference_2_oneout_3,reputer_0_loss_forecast_implied_inference_2_oneout_4,reputer_1_loss_forecast_implied_inference_0_oneout_0,reputer_1_loss_forecast_implied_inference_0_oneout_1,reputer_1_loss_forecast_implied_inference_0_oneout_2,reputer_1_loss_forecast_implied_inference_0_oneout_3,reputer_1_loss_forecast_implied_inference_0_oneout_4,reputer_1_loss_forecast_implied_inference_1_oneout_0,reputer_1_loss_forecast_implied_inference_1_oneout_1,reputer_1_loss_forecast_implied_inference_1_oneout_2,reputer_1_loss_forecast_implied_inference_1_oneout_3,reputer_1_loss_forecast_implied_inference_1_oneout_4,reputer_1_loss_forecast_implied_inference_2_oneout_0,reputer_1_loss_forecast_implied_inference_2_oneout_1,reputer_1_loss_forecast_implied_inference_2_oneout_2,reputer_1_loss_forecast_implied_inference_2_oneout_3,reputer_1_loss_forecast_implied_inference_2_oneout_4,reputer_2_loss_forecast_implied_inference_0_oneout_0,reputer_2_loss_forecast_implied_inference_0_oneout_1,reputer_2_loss_forecast_implied_inference_0_oneout_2,reputer_2_loss_forecast_implied_inference_0_oneout_3,reputer_2_loss_forecast_implied_inference_0_oneout_4,reputer_2_loss_forecast_implied_inference_1_oneout_0,reputer_2_loss_forecast_implied_inference_1_oneout_1,reputer_2_loss_forecast_implied_inference_1_oneout_2,reputer_2_loss_forecast_implied_inference_1_oneout_3,reputer_2_loss_forecast_implied_inference_1_oneout_4,reputer_2_loss_forecast_implied_inference_2_oneout_0,reputer_2_loss_forecast_implied_inference_2_oneout_1,reputer_2_loss_forecast_implied_inference_2_oneout_2,reputer_2_loss_forecast_implied_inference_2_oneout_3,reputer_2_loss_forecast_implied_inference_2_oneout_4,reputer_3_loss_forecast_implied_inference_0_oneout_0,reputer_3_loss_forecast_implied_inference_0_oneout_1,reputer_3_loss_forecast_implied_inference_0_oneout_2,reputer_3_loss_forecast_implied_inference_0_oneout_3,reputer_3_loss_forecast_implied_inference_0_oneout_4,reputer_3_loss_forecast_implied_inference_1_oneout_0,reputer_3_loss_forecast_implied_inference_1_oneout_1,reputer_3_loss_forecast_implied_inference_1_oneout_2,reputer_3_loss_forecast_implied_inference_1_oneout_3,reputer_3_loss_forecast_implied_inference_1_oneout_4,reputer_3_loss_forecast_implied_inference_2_oneout_0,reputer_3_loss_forecast_implied_inference_2_oneout_1,reputer_3_loss_forecast_implied_inference_2_oneout_2,reputer_3_loss_forecast_implied_inference_2_oneout_3,reputer_3_loss_forecast_implied_inference_2_oneout_4,reputer_4_loss_forecast_implied_inference_0_oneout_0,reputer_4_loss_forecast_implied_inference_0_oneout_1,reputer_4_loss_forecast_implied_inference_0_oneout_2,reputer_4_loss_forecast_implied_inference_0_oneout_3,reputer_4_loss_forecast_implied_inference_0_oneout_4,reputer_4_loss_forecast_implied_inference_1_oneout_0,reputer_4_loss_forecast_implied_inference_1_oneout_1,reputer_4_loss_forecast_implied_inference_1_oneout_2,reputer_4_loss_forecast_implied_inference_1_oneout_3,reputer_4_loss_forecast_implied_inference_1_oneout_4,reputer_4_loss_forecast_implied_inference_2_oneout_0,reputer_4_loss_forecast_implied_inference_2_oneout_1,reputer_4_loss_forecast_implied_inference_2_oneout_2,reputer_4_loss_forecast_implied_inference_2_oneout_3,reputer_4_loss_forecast_implied_inference_2_oneout_4,reputer_0_loss_network_inference,reputer_1_loss_network_inference,reputer_2_loss_network_inference,reputer_3_loss_network_inference,reputer_4_loss_network_inference,reputer_0_loss_naive_network_inference,reputer_1_loss_naive_network_inference,reputer_2_loss_naive_network_inference,reputer_3_loss_naive_network_inference,reputer_4_loss_naive_network_inference,reputer_0_loss_network_inference_oneout_0,reputer_0_loss_network_inference_oneout_1,reputer_0_loss_network_inference_oneout_2,reputer_0_loss_network_inference_oneout_3,reputer_0_loss_network_inference_oneout_4,reputer_0_loss_network_inference_oneout_5,reputer_0_loss_network_inference_oneout_6,reputer_0_loss_network_inference_oneout_7,reputer_1_loss_network_inference_oneout_0,reputer_1_loss_network_inference_oneout_1,reputer_1_loss_network_inference_oneout_2,reputer_1_loss_network_inference_oneout_3,reputer_1_loss_network_inference_oneout_4,reputer_1_loss_network_inference_oneout_5,reputer_1_loss_network_inference_oneout_6,reputer_1_loss_network_inference_oneout_7,reputer_2_loss_network_inference_oneout_0,reputer_2_loss_network_inference_oneout_1,reputer_2_loss_network_inference_oneout_2,reputer_2_loss_network_inference_oneout_3,reputer_2_loss_network_inference_oneout_4,reputer_2_loss_network_inference_oneout_5,reputer_2_loss_network_inference_oneout_6,reputer_2_loss_network_inference_oneout_7,reputer_3_loss_network_inference_oneout_0,reputer_3_loss_network_inference_oneout_1,reputer_3_loss_network_inference_oneout_2,reputer_3_loss_network_inference_oneout_3,reputer_3_loss_network_inference_oneout_4,reputer_3_loss_network_inference_oneout_5,reputer_3_loss_network_inference_oneout_6,reputer_3_loss_network_inference_oneout_7,reputer_4_loss_network_inference_oneout_0,reputer_4_loss_network_inference_oneout_1,reputer_4_loss_network_inference_oneout_2,reputer_4_loss_network_inference_oneout_3,reputer_4_loss_network_inference_oneout_4,reputer_4_loss_network_inference_oneout_5,reputer_4_loss_network_inference_oneout_6,reputer_4_loss_network_inference_oneout_7,reputer_0_loss_naive_network_inference_onein_0,reputer_0_loss_naive_network_inference_onein_1,reputer_0_loss_naive_network_inference_onein_2,reputer_1_loss_naive_network_inference_onein_0,reputer_1_loss_naive_network_inference_onein_1,reputer_1_loss_naive_network_inference_onein_2,reputer_2_loss_naive_network_inference_onein_0,reputer_2_loss_naive_network_inference_onein_1,reputer_2_loss_naive_network_inference_onein_2,reputer_3_loss_naive_network_inference_onein_0,reputer_3_loss_naive_network_inference_onein_1,reputer_3_loss_naive_network_inference_onein_2,reputer_4_loss_naive_network_inference_onein_0,reputer_4_loss_naive_network_inference_onein_1,reputer_4_loss_naive_network_inference_onein_2,inference_loss_0,inference_loss_1,inference_loss_2,inference_loss_3,inference_loss_4,forecast_implied_inference_loss_0,forecast_implied_inference_loss_1,forecast_implied_inference_loss_2,forecast_implied_inference_loss_0_oneout_0,forecast_implied_inference_loss_0_oneout_1,forecast_implied_inference_loss_0_oneout_2,forecast_implied_inference_loss_0_oneout_3,forecast_implied_inference_loss_0_oneout_4,forecast_implied_inference_loss_1_oneout_0,forecast_implied_inference_loss_1_oneout_1,forecast_implied_inference_loss_1_oneout_2,forecast_implied_inference_loss_1_oneout_3,forecast_implied_inference_loss_1_oneout_4,forecast_implied_inference_loss_2_oneout_0,forecast_implied_inference_loss_2_oneout_1,forecast_implied_inference_loss_2_oneout_2,forecast_implied_inference_loss_2_oneout_3,forecast_implied_inference_loss_2_oneout_4,network_naive_loss,network_loss_oneout_0,network_loss_oneout_1,network_loss_oneout_2,network_loss_oneout_3,network_loss_oneout_4,network_loss_oneout_5,network_loss_oneout_6,network_loss_oneout_7,network_naive_loss_onein_0,network_naive_loss_onein_1,network_naive_loss_onein_2,forecasted_regret_0_inferer_0,forecasted_regret_0_inferer_1,forecasted_regret_0_inferer_2,forecasted_regret_0_inferer_3,forecasted_regret_0_inferer_4,forecasted_regret_1_inferer_0,forecasted_regret_1_inferer_1,forecasted_regret_1_inferer_2,forecasted_regret_1_inferer_3,forecasted_regret_1_inferer_4,forecasted_regret_2_inferer_0,forecasted_regret_2_inferer_1,forecasted_regret_2_inferer_2,forecasted_regret_2_inferer_3,forecasted_regret_2_inferer_4,inference_regret_worker_0,inference_regret_worker_1,inference_regret_worker_2,inference_regret_worker_3,inference_regret_worker_4,inference_regret_worker_5,inference_regret_worker_6,inference_regret_worker_7,naive_inference_regret_worker_0,naive_inference_regret_worker_1,naive_inference_regret_worker_2,naive_inference_regret_worker_3,naive_inference_regret_worker_4,inference_regret_worker_0_oneout_0,inference_regret_worker_1_oneout_0,inference_regret_worker_2_oneout_0,inference_regret_worker_3_oneout_0,inference_regret_worker_4_oneout_0,inference_regret_worker_5_oneout_0,inference_regret_worker_6_oneout_0,inference_regret_worker_7_oneout_0,inference_regret_worker_0_oneout_1,inference_regret_worker_1_oneout_1,inference_regret_worker_2_oneout_1,inference_regret_worker_3_oneout_1,inference_regret_worker_4_oneout_1,inference_regret_worker_5_oneout_1,inference_regret_worker_6_oneout_1,inference_regret_worker_7_oneout_1,inference_regret_worker_0_oneout_2,inference_regret_worker_1_oneout_2,inference_regret_worker_2_oneout_2,inference_regret_worker_3_oneout_2,inference_regret_worker_4_oneout_2,inference_regret_worker_5_oneout_2,inference_regret_worker_6_oneout_2,inference_regret_worker_7_oneout_2,inference_regret_worker_0_oneout_3,inference_regret_worker_1_oneout_3,inference_regret_worker_2_oneout_3,inference_regret_worker_3_oneout_3,inference_regret_worker_4_oneout_3,inference_regret_worker_5_oneout_3,inference_regret_worker_6_oneout_3,inference_regret_worker_7_oneout_3,inference_regret_worker_0_oneout_4,inference_regret_worker_1_oneout_4,inference_regret_worker_2_oneout_4,inference_regret_worker_3_oneout_4,inference_regret_worker_4_oneout_4,inference_regret_worker_5_oneout_4,inference_regret_worker_6_oneout_4,inference_regret_worker_7_oneout_4,inference_regret_worker_0_oneout_5,inference_regret_worker_1_oneout_5,inference_regret_worker_2_oneout_5,inference_regret_worker_3_oneout_5,inference_regret_worker_4_oneout_5,inference_regret_worker_5_oneout_5,inference_regret_worker_6_oneout_5,inference_regret_worker_7_oneout_5,inference_regret_worker_0_oneout_6,inference_regret_worker_1_oneout_6,inference_regret_worker_2_oneout_6,inference_regret_worker_3_oneout_6,inference_regret_worker_4_oneout_6,inference_regret_worker_5_oneout_6,inference_regret_worker_6_oneout_6,inference_regret_worker_7_oneout_6,inference_regret_worker_0_oneout_7,inference_regret_worker_1_oneout_7,inference_regret_worker_2_oneout_7,inference_regret_worker_3_oneout_7,inference_regret_worker_4_oneout_7,inference_regret_worker_5_oneout_7,inference_regret_worker_6_oneout_7,inference_regret_worker_7_oneout_7,inference_regret_worker_0_onein_0,inference_regret_worker_1_onein_0,inference_regret_worker_2_onein_0,inference_regret_worker_3_onein_0,inference_regret_worker_4_onein_0,inference_regret_worker_5_onein_0,inference_regret_worker_0_onein_1,inference_regret_worker_1_onein_1,inference_regret_worker_2_onein_1,inference_regret_worker_3_onein_1,inference_regret_worker_4_onein_1,inference_regret_worker_5_onein_1,inference_regret_worker_0_onein_2,inference_regret_worker_1_onein_2,inference_regret_worker_2_onein_2,inference_regret_worker_3_onein_2,inference_regret_worker_4_onein_2,inference_regret_worker_5_onein_2,inferer_score_0,inferer_score_1,inferer_score_2,inferer_score_3,inferer_score_4,forecaster_score_0,forecaster_score_1,forecaster_score_2,inferer_reward_fraction_0,inferer_reward_fraction_1,inferer_reward_fraction_2,inferer_reward_fraction_3,inferer_reward_fraction_4,forecaster_reward_fraction_0,forecaster_reward_fraction_1,forecaster_reward_fraction_2,reputer_listening_coefficient_0,reputer_listening_coefficient_1,reputer_listening_coefficient_2,reputer_listening_coefficient_3,reputer_listening_coefficient_4,reputer_adjusted_stake_0,reputer_adjusted_stake_1,reputer_adjusted_stake_2,reputer_adjusted_stake_3,reputer_adjusted_stake_4,reputer_score_0,reputer_score_1,reputer_score_2,reputer_score_3,reputer_score_4,reputer_reward_fraction_0,reputer_reward_fraction_1,reputer_reward_fraction_2,reputer_reward_fraction_3,reputer_reward_fraction_4,inferer_reward_fraction_smooth_0,inferer_reward_fraction_smooth_1,inferer_reward_fraction_smooth_2,inferer_reward_fraction_smooth_3,inferer_reward_fraction_smooth_4,forecaster_reward_fraction_smooth_0,forecaster_reward_fraction_smooth_1,forecaster_reward_fraction_smooth_2,reputer_reward_fraction_smooth_0,reputer_reward_fraction_smooth_1,reputer_reward_fraction_smooth_2,reputer_reward_fraction_smooth_3,reputer_reward_fraction_smooth_4,inferers_entropy,forecasters_entropy,reputers_entropy,forecaster_task_score,forecaster_score_ratio,forecasters_utility,inferers_reward_fraction,forecasters_reward_fraction,reputers_reward_fraction,topic_rewards,inferer_reward_0,inferer_reward_1,inferer_reward_2,inferer_reward_3,inferer_reward_4,forecaster_reward_0,forecaster_reward_1,forecaster_reward_2,reputer_reward_0,reputer_reward_1,reputer_reward_2,reputer_reward_3,reputer_reward_4"
	simulatorEpochs := map[int]string{
		300: 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	}

	gettersMap := map[int](func(header string) alloraMath.Dec){}
	for epochNumber, epoch := range simulatorEpochs {
		gettersMap[epochNumber] = GetSimulatedValuesGetterForEpoch(epoch, simulatorHeaders)
	}
	return gettersMap
}

func GetTokenomicsSimulatorValuesGetterForEpochs() map[int]func(header string) alloraMath.Dec {
	const simulatorHeaders = "epoch,time,network_tokens_total,network_tokens_emission,network_tokens_circulating,network_tokens_staked,investors_preseed_tokens_total,investors_preseed_tokens_emission,investors_preseed_tokens_circulating,investors_preseed_tokens_staked,investors_seed_tokens_total,investors_seed_tokens_emission,investors_seed_tokens_circulating,investors_seed_tokens_staked,team_tokens_total,team_tokens_emission,team_tokens_circulating,team_tokens_staked,ecosystem_tokens_total,ecosystem_tokens_emission,ecosystem_tokens_circulating,ecosystem_tokens_staked,foundation_tokens_total,foundation_tokens_emission,foundation_tokens_circulating,foundation_tokens_staked,participants_tokens_total,participants_tokens_emission,participants_tokens_circulating,participants_tokens_staked,ehat_target_i,ehat_max_i,ehat_i,e_i,validator_rewards,topics_rewards,n_active_topics,all_topic_weight_sum,topic_id_0,topic_months_live_0,topic_n_workers_0,topic_n_reputers_0,topic_total_stake_0,topic_total_fee_revenue_0,topic_weights_0,topic_rewards_0,topic_id_1,topic_months_live_1,topic_n_workers_1,topic_n_reputers_1,topic_total_stake_1,topic_total_fee_revenue_1,topic_weights_1,topic_rewards_1,topic_id_2,topic_months_live_2,topic_n_workers_2,topic_n_reputers_2,topic_total_stake_2,topic_total_fee_revenue_2,topic_weights_2,topic_rewards_2,n_active_validators,all_validator_stake_sum,validator_id_0,validator_months_live_0,validator_stake_0,validator_rewards_0,validator_id_1,validator_months_live_1,validator_stake_1,validator_rewards_1,validator_id_2,validator_months_live_2,validator_stake_2,validator_rewards_2"
	simulatorEpochs := map[int]string{
		0:  "0,2024-09-01 00:00:00,1000000000.0,155000000.0,155000000.0,47000000.0,50000000.0,0.0,0.0,0.0,260500000.0,0.0,0.0,0.0,175000000.0,0.0,0.0,0.0,359500000.0,0.0,0.0,0.0,100000000.0,100000000.0,100000000.0,25000000.0,55000000.0,55000000.0,55000000.0,22000000.0,0.0,0.01897758586916609,0.0,0.0,0.0,0.0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0",
		1:  "1,2024-10-01 00:00:00,1000000000.0,891946.5358508063,155891946.5358508,47321195.640835635,50000000.0,0.0,0.0,0.0,260500000.0,0.0,0.0,0.0,175000000.0,0.0,0.0,0.0,358608053.46414924,891946.5358508063,0.0,0.0,100237219.82336457,0.0,100237219.82336457,25059304.955841143,55654726.71248623,0.0,55654726.71248623,22261890.684994493,0.029639627659574466,0.01897758586916609,0.01897758586916609,0.01897758586916609,222986.63396270157,668959.9018881047,3,1040922.4433738946,1,1,5,7,1116348.8993855934,74337.26358999203,288073.46700455487,185133.48371979792,2,1,9,11,1254714.5661832283,68705.51709378888,293608.26465671515,188690.48041818666,3,1,16,11,1061630.2874523632,198658.64207814567,459240.7117126246,295135.9377501202,3,4000857.234830969,1,1,1220576.890643749,68028.50398354916,2,1,1199203.1614497465,66837.24529860828,3,1,1581077.1827374736,88120.88468054413",
		2:  "2,2024-11-01 00:00:00,1000000000.0,898042.0537055664,156789988.58955637,47644745.07894628,50000000.0,0.0,0.0,0.0,260500000.0,0.0,0.0,0.0,175000000.0,0.0,0.0,0.0,357710011.41044366,898042.0537055664,0.0,0.0,100475002.37917511,0.0,100475002.37917511,25118750.594793778,56314986.21038125,0.0,56314986.21038125,22525994.4841525,0.029534390847954634,0.01897758586916609,0.01897758586916609,0.01897758586916609,224510.5134263916,673531.5402791748,6,3018763.8682387685,1,2,5,7,1178060.0606255261,117255.20797804561,366439.0222759296,81758.04728837454,2,2,13,11,1317611.3929892904,72828.84212954807,308763.91550895997,68889.86508133536,3,2,17,10,1063497.0890552187,257078.24365257853,518901.17231771885,115774.64190590323,7,9131674.264555544,1,2,1288605.394627298,32474.531687282917,2,2,1266040.4067483547,31905.86464851901,3,2,1669198.0674180177,42065.961976199775",
		3:  "3,2024-12-01 00:00:00,1000000000.0,904182.2409502316,157694170.8305066,47970665.98185095,50000000.0,0.0,0.0,0.0,260500000.0,0.0,0.0,0.0,175000000.0,0.0,0.0,0.0,356805829.16949344,904182.2409502316,0.0,0.0,100713349.00234455,0.0,100713349.00234455,25178337.250586137,56980821.828162044,0.0,56980821.828162044,22792328.73126482,0.029428926796901407,0.01897758586916609,0.01897758586916609,0.01897758586916609,226045.5602375579,678136.6807126737,7,3414813.425347168,1,3,5,7,1205312.7430549844,157069.847923818,430815.45371665916,85554.23837055989,2,3,13,11,1340574.6813497355,128703.68926349623,408712.39019880164,81164.8629463206,3,3,17,9,1005576.7920433353,69994.63181035031,281151.6410350818,55832.98906266544,8,13848700.93929397,1,3,1321079.926314581,21927.723169595884,2,3,1297946.2713968738,21543.743085702266,3,3,1711264.0293942175,28404.12844007456",
		4:  "4,2025-01-01 00:00:00,1000000000.0,910367.4328716611,158604538.26337826,48298976.15070843,50000000.0,0.0,0.0,0.0,260500000.0,0.0,0.0,0.0,175000000.0,0.0,0.0,0.0,355895461.7366218,910367.4328716611,0.0,0.0,100952261.03095245,0.0,100952261.03095245,25238065.257738113,57652277.232425794,0.0,57652277.232425794,23060910.89297032,0.029323232347692546,0.01897758586916609,0.01897758586916609,0.01897758586916609,227591.8582179153,682775.5746537459,12,10163400.925300306,1,4,5,7,1233830.8225118376,101232.03575633248,358253.9126822921,24067.437947340186,2,4,16,11,1367629.6356651757,96122.53757752318,365457.8117297119,24551.39468072117,3,4,17,9,1024187.7883975571,139685.7921786202,372170.7196334454,25002.366711172075,9,17004927.05043693,1,4,1343007.649484177,18220.952729754186,2,4,1319490.014482576,17901.882532466505,3,4,1739668.1578342922,23602.55452121358",
		5:  "5,2025-02-01 00:00:00,1000000000.0,916597.9672928745,159521136.23067114,48629693.521330565,50000000.0,0.0,0.0,0.0,260500000.0,0.0,0.0,0.0,175000000.0,0.0,0.0,0.0,354978863.76932895,916597.9672928745,0.0,0.0,101191739.80625263,0.0,101191739.80625263,25297934.951563157,58329396.424418494,0.0,58329396.424418494,23331758.5697674,0.02921730431854131,0.01897758586916609,0.01897758586916609,0.01897758586916609,229149.49182321862,687448.4754696558,16,10938365.947389785,1,5,5,7,1241853.3018276177,155024.14135717688,433735.7455983521,27259.18830128681,2,5,16,11,1375813.433892083,164500.12416091637,468840.4001095446,29465.426540314365,3,5,17,9,1032521.9106346144,102134.21728211794,327704.05848956556,20595.366483202102,13,23240004.910929155,1,5,1361228.602213931,13542.579684064165,2,5,1337391.8970150424,13305.433271597905,4,5,1190566.924736879,11844.7022206535",
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		85: "85,2031-10-01 00:00:00,1000000000.0,1878701.0552812088,944548276.0505975,572450374.4437711,62225881.03833957,0.0,62225881.038339555,46669410.77875467,324196840.2097493,0.0,324196840.2097491,243147630.15731183,217790583.63418838,0.0,217790583.63418823,163342937.7256412,55451723.94940222,1878701.0552812088,0.0,0.0,112290617.9017662,0.0,112290617.9017662,28072654.47544155,228044353.26655453,0.0,228044353.26655453,91217741.30662182,0.002364339879700408,0.01897758586916609,0.002364339879700408,0.0032876299383283085,469675.2638203022,1409025.7914609066,154,164254691.32171264,2,85,194,10,1859767.2096619895,173599.01730846666,570071.101058042,4890.240138006446,4,85,2,21,2943562.8557979115,236161.7219807126,827386.530918446,7097.568734204856,5,85,31,18,3081975.5303828097,676134.2083104962,1397855.4463370822,11991.221442590753,88,222713236.04139948,5,85,3616468.3897437383,7643.04456783964,6,85,2193727.4154149876,4636.22368531099,8,85,9595246.834140075,20278.595383478918",
		86: "86,2031-11-01 00:00:00,1000000000.0,1824746.5659568368,946373022.6165545,573426348.4775708,62300262.89819642,0.0,62300262.89819641,46725197.17364731,324584369.6996035,0.0,324584369.6996033,243438277.2747025,218050920.14368737,0.0,218050920.14368722,163538190.1077654,53626977.38344539,1824746.5659568368,0.0,0.0,112335360.19047649,0.0,112335360.19047649,28083840.047619123,229102109.68459103,0.0,229102109.68459103,91640843.87383641,0.0022873961044804158,0.01897758586916609,0.0022873961044804158,0.003187606554943519,456186.6414892092,1368559.9244676277,154,168376116.80209213,2,86,196,10,1861397.2897079915,141481.74120751297,516735.7095514981,4200.024309057689,4,86,2,21,2945928.7120426465,572898.1141970728,1269638.1841981844,10319.610467735241,5,86,31,18,3085972.6041970067,221869.386268092,863105.6344478874,7015.316686962023,87,222099076.67459163,5,86,3624111.434311578,7459.34117057055,6,86,2198363.6391002988,4524.79033778417,8,86,9615525.429523554,19791.191858519054",
		87: "87,2031-12-01 00:00:00,1000000000.0,1771949.6401663898,948144972.2567209,574373967.4658343,62372455.862941034,0.0,62372455.86294102,46779341.89720576,324960495.04592294,0.0,324960495.04592276,243720371.28444207,218303595.5202935,0.0,218303595.52029335,163727696.64022002,51855027.743278995,1771949.6401663898,0.0,0.0,112378751.2470603,0.0,112378751.2470603,28094687.811765075,230129674.5805034,0.0,230129674.5805034,92051869.83220136,0.002212626120813226,0.01897758586916609,0.002212626120813226,0.0030901085115304897,442987.41004159744,1328962.2301247923,154,181971065.34214213,2,87,198,10,1862797.2978110109,127142.306027625,488542.0324454021,3567.89640005466,4,87,2,21,2949368.5821985584,693513.3504626909,1420149.9564336496,10371.57006068596,5,87,31,18,3088311.0430926606,504090.42304628406,1223675.148542997,8936.684803698716,86,214208630.54354024,5,87,3631570.7754821484,7525.52634927422,6,87,2202888.429438083,4564.937858892924,8,87,9635316.621382073,19966.794976805504",
		88: "88,2032-01-01 00:00:00,1000000000.0,1720305.306703497,949865277.5634242,575293858.2072634,62442510.17830714,0.0,62442510.17830712,46831882.633730344,325325478.0289803,0.0,325325478.02898014,243994108.5217351,218548785.62407485,0.0,218548785.6240747,163911589.21805602,50134722.436575495,1720305.306703497,0.0,0.0,112420824.39388657,0.0,112420824.39388657,28105206.09847164,231127679.3381758,0.0,231127679.3381758,92451071.73527032,0.0021399857334214625,0.01897758586916609,0.0021399857334214625,0.002995096233719587,430076.32667587424,1290228.9800276228,154,170533384.61310613,2,88,201,10,1863986.596611029,193135.74526424764,593035.783664481,4486.816209114873,4,88,2,22,3055893.1999229435,280504.9824241052,956741.2390214308,7238.554936170051,5,88,31,19,3211620.3728734273,302653.52104074956,1000765.4179874071,7571.635005229207,86,214877984.84843263,5,88,3639096.301831423,7298.600155742126,6,88,2207453.367296976,4427.285829792127,8,88,9655283.416358879,19364.712335561526",
		89: "89,2032-02-01 00:00:00,1000000000.0,1669807.501305684,951535085.06473,576186643.6252315,62510475.64309218,0.0,62510475.64309216,46882856.732319124,325679578.10051036,0.0,325679578.1005102,244259683.57538265,218786664.75082248,0.0,218786664.75082234,164089998.56311676,48464914.93526981,1669807.501305684,0.0,0.0,112461612.49139486,0.0,112461612.49139486,28115403.122848716,232096754.07891044,0.0,232096754.07891044,92838701.63156419,0.0020694307510591534,0.01897758586916609,0.0020694307510591534,0.002902529685453544,417451.875326421,1252355.6259792629,152,193912432.91773826,2,89,203,10,1865482.2020140672,109627.81723454742,461027.0124336789,2977.476812921334,4,89,2,22,3058306.0515683335,215812.15928551243,821436.2557134853,5305.128200121818,5,89,31,19,3214144.2512085037,438889.1732530747,1176025.2015333362,7595.190031257373,89,222604955.69449556,5,89,3646394.9019871647,6851.361663381618,6,89,2211880.6531267683,4155.993719317014,8,89,9674648.128694441,18178.095098674294",
		90: "90,2032-03-01 00:00:00,1000000000.0,1620449.1211246357,953155534.1858547,577052942.2411817,62576401.57597193,0.0,62576401.57597192,46932301.18197894,326023052.2108139,0.0,326023052.2108137,244517289.15811026,219017405.51590163,0.0,219017405.51590148,164263054.1369261,46844465.81414517,1620449.1211246357,0.0,0.0,112501147.92733784,0.0,112501147.92733784,28125286.98183446,233037526.95582965,0.0,233037526.95582965,93215010.78233187,0.0020009170407628406,0.01897758586916609,0.0020009170407628406,0.002812368420984474,405112.2802811589,1215336.8408434768,152,173689762.0214271,2,90,204,10,1866474.694285041,111586.99551685,456661.80942626705,3195.3404411569077,4,90,2,23,3163141.855339197,206999.14379501797,809943.3416018139,5667.311478745209,5,90,31,19,3216675.981218923,566039.1172216065,1338523.804055894,9365.878981481934,88,220736053.01466635,5,90,3653246.2636505463,6717.324559927365,6,90,2216036.6468460853,4074.6876392295158,8,90,9692826.223793115,17822.466636325735",
		91: "91,2032-04-01 00:00:00,1000000000.0,1572222.0793875805,954727756.2652421,577893367.6764939,62640336.78429805,0.0,62640336.78429803,46980252.588223524,326356154.64619297,0.0,326356154.6461928,244767115.9846446,219241178.74504304,0.0,219241178.7450429,164430884.05878216,45272243.734757595,1572222.0793875805,0.0,0.0,112539462.60693224,0.0,112539462.60693224,28134865.65173306,233950623.48277625,0.0,233950623.48277625,93580249.39311051,0.0019344005795776215,0.01897758586916609,0.0019344005795776215,0.002724571636843789,393055.5198468951,1179166.5595406853,153,174521060.07615346,2,91,209,9,1753474.847203315,125483.47270784187,468299.93257157283,3164.1087905528325,4,91,2,23,3165030.9591654455,453416.8714720797,1173697.327304274,7930.186985889076,5,91,31,19,3219797.9408794167,669965.4099771837,1460587.4641520178,9868.584881737832,86,217620761.55344346,5,91,3659963.588210474,6622.427665794776,6,91,2220111.334485315,4017.1237686626428,8,91,9710648.690429442,17570.685333445337",
		92: "92,2032-05-01 00:00:00,1000000000.0,1525117.3600273088,956252873.6252697,578708528.1827813,62702329.53487144,0.0,62702329.53487142,47026747.151153564,326679136.8766803,0.0,326679136.87668014,245009352.6575101,219458153.3720499,0.0,219458153.37204975,164593615.0290373,43747126.37473028,1525117.3600273088,0.0,0.0,112576587.94391267,0.0,112576587.94391267,28144146.985978168,234836665.89775553,0.0,234836665.89775553,93934666.35910222,0.0018698375037492405,0.01897758586916609,0.0018698375037492405,0.002639098223534334,381279.3400068272,1143838.0200204817,153,166062369.4017721,2,92,214,9,1754529.5501334993,261950.67769438215,664835.8094425278,4579.390735245884,4,92,2,22,3064606.9271232523,438255.1560391989,1159837.2006399792,7988.961568507968,5,92,32,19,3223087.4691733294,281455.7029252101,984206.3013891119,6779.215490710617,86,218025001.859974,5,92,3666586.0158762685,6423.617186725482,6,92,2224128.4582539774,3896.526558510613,8,92,9728219.375762887,17043.199561609603",
		93: "93,2032-06-01 00:00:00,1000000000.0,1479125.0720759218,957731998.6973454,579499026.2004791,62762427.52667732,0.0,62762427.5266773,47071820.645007975,326992247.41398895,0.0,326992247.41398877,245244185.56049156,219668496.3433705,0.0,219668496.34337035,164751372.25752777,42268001.302654356,1479125.0720759218,0.0,0.0,112612554.85247877,0.0,112612554.85247877,28153138.713119693,235696272.56083024,0.0,235696272.56083024,94278509.0243321,0.0018071841553832632,0.01897758586916609,0.0018071841553832632,0.002555906816719227,369781.26801898045,1109343.8040569413,157,185979661.3345189,2,93,216,9,1756056.0137119147,100723.92810401137,435834.08835194906,2599.692041810928,4,93,2,22,3067269.9143127548,336638.62046115415,1025130.7683536703,6114.76791634635,5,93,32,19,3225347.2076702327,271161.37737174105,938258.1578721394,5596.584414513877,88,221807598.59392232,5,93,3673009.633062994,6133.93372857417,6,93,2228024.984812488,3720.806359838067,8,93,9745262.575324496,16274.60877491505",
		94: "94,2032-07-01 00:00:00,1000000000.0,1434234.5036344954,959166233.2009798,580265457.9454826,62820677.86556107,0.0,62820677.86556105,47115508.399170786,327295731.6795733,0.0,327295731.6795731,245471798.75967985,219872372.52946362,0.0,219872372.52946347,164904279.3970976,40833766.79901986,1434234.5036344954,0.0,0.0,112647393.74012342,0.0,112647393.74012342,28161848.435030855,236530057.38625884,0.0,236530057.38625884,94612022.95450354,0.0017463971265815601,0.01897758586916609,0.0017463971265815601,0.0024749558477054606,358558.62590862386,1075675.8777258715,156,170297897.16307935,2,94,221,8,1642857.61716374,152849.02015092247,497028.3331584742,3139.44797576032,4,94,2,22,3069308.17028487,190022.6450997964,780039.6483706684,4927.071017316176,5,94,33,19,3227212.735808404,347872.30701605405,1051974.452419235,6644.729977890657,92,227630134.04620105,5,94,3679143.5667915684,5804.76246059828,6,94,2231745.791172326,3521.133099324157,8,94,9761537.184099412,15401.24857193555",
		95: "95,2032-08-01 00:00:00,1000000000.0,1390434.1752473512,960556667.3762271,581008413.0235122,62877127.040818125,0.0,62877127.04081811,47157845.28061359,327589831.88266253,0.0,327589831.88266236,245692373.91199678,220069944.6428633,0.0,220069944.64286315,165052458.48214737,39443332.62377251,1390434.1752473512,0.0,0.0,112681134.50132678,0.0,112681134.50132678,28170283.625331696,237338629.30855682,0.0,237338629.30855682,94935451.72342274,0.001687433301074716,0.01897758586916609,0.001687433301074716,0.002396203593042386,347608.5438118378,1042825.6314355134,158,171886325.35367435,2,95,224,8,1643904.0998223268,162000.80839951528,514866.7689753072,3123.6706140356127,4,95,2,22,3070950.5272906423,354832.3896073904,1027384.2569665861,6233.088259310926,5,95,34,19,3229427.6458010343,293105.07465562946,977855.2685541837,5932.598394807451,91,226673318.59202543,5,95,3684948.3292521667,5659.757698254716,6,95,2235266.92427165,3433.174105013314,8,95,9776938.432671348,15016.52061723859",
	}
	// until shown necessary, skip time and epoch columns
	filteredSimulatorEpochs := map[int]string{}
	for epochNumber, epoch := range simulatorEpochs {
		filteredSimulatorEpochs[epochNumber] = strings.Join(strings.Split(epoch, ",")[2:], ",")
	}
	filteredSimulatorHeaders := strings.Join(strings.Split(simulatorHeaders, ",")[2:], ",")
	gettersMap := map[int](func(header string) alloraMath.Dec){}
	for epochNumber, epoch := range filteredSimulatorEpochs {
		gettersMap[epochNumber] = GetSimulatedValuesGetterForEpoch(epoch, filteredSimulatorHeaders)
	}
	return gettersMap
}

func GetInferencesFromCsv(
	topicId uint64,
	blockHeight int64,
	inferers []string,
	epochGet func(header string) alloraMath.Dec,
) (emissionstypes.Inferences, error) {
	if len(inferers) != 5 {
		return emissionstypes.Inferences{}, fmt.Errorf("expected 5 inferers, got %d", len(inferers))
	}
	return emissionstypes.Inferences{
		Inferences: []*emissionstypes.Inference{
			{
				Inferer:     inferers[0],
				Value:       epochGet("inference_0"),
				TopicId:     topicId,
				BlockHeight: blockHeight,
			},
			{
				Inferer:     inferers[1],
				Value:       epochGet("inference_1"),
				TopicId:     topicId,
				BlockHeight: blockHeight,
			},
			{
				Inferer:     inferers[2],
				Value:       epochGet("inference_2"),
				TopicId:     topicId,
				BlockHeight: blockHeight,
			},
			{
				Inferer:     inferers[3],
				Value:       epochGet("inference_3"),
				TopicId:     topicId,
				BlockHeight: blockHeight,
			},
			{
				Inferer:     inferers[4],
				Value:       epochGet("inference_4"),
				TopicId:     topicId,
				BlockHeight: blockHeight,
			},
		},
	}, nil
}

func GetForecastsFromCsv(
	topicId uint64,
	blockHeight int64,
	inferers []string,
	forecasters []string,
	epochGet func(header string) alloraMath.Dec,
) (emissionstypes.Forecasts, error) {
	if len(inferers) != 5 {
		return emissionstypes.Forecasts{}, fmt.Errorf("expected 5 inferers, got %d", len(inferers))
	}
	if len(forecasters) != 3 {
		return emissionstypes.Forecasts{}, fmt.Errorf("expected 3 forecasters, got %d", len(forecasters))
	}
	return emissionstypes.Forecasts{
		Forecasts: []*emissionstypes.Forecast{
			{
				Forecaster: forecasters[0],
				ForecastElements: []*emissionstypes.ForecastElement{
					{
						Inferer: inferers[0],
						Value:   epochGet("forecasted_loss_0_for_0"),
					},
					{
						Inferer: inferers[1],
						Value:   epochGet("forecasted_loss_0_for_1"),
					},
					{
						Inferer: inferers[2],
						Value:   epochGet("forecasted_loss_0_for_2"),
					},
					{
						Inferer: inferers[3],
						Value:   epochGet("forecasted_loss_0_for_3"),
					},
					{
						Inferer: inferers[4],
						Value:   epochGet("forecasted_loss_0_for_4"),
					},
				},
				TopicId:     topicId,
				BlockHeight: blockHeight,
				ExtraData:   nil,
			},
			{
				Forecaster: forecasters[1],
				ForecastElements: []*emissionstypes.ForecastElement{
					{
						Inferer: inferers[0],
						Value:   epochGet("forecasted_loss_1_for_0"),
					},
					{
						Inferer: inferers[1],
						Value:   epochGet("forecasted_loss_1_for_1"),
					},
					{
						Inferer: inferers[2],
						Value:   epochGet("forecasted_loss_1_for_2"),
					},
					{
						Inferer: inferers[3],
						Value:   epochGet("forecasted_loss_1_for_3"),
					},
					{
						Inferer: inferers[4],
						Value:   epochGet("forecasted_loss_1_for_4"),
					},
				},
				TopicId:     topicId,
				BlockHeight: blockHeight,
				ExtraData:   nil,
			},
			{
				Forecaster: forecasters[2],
				ForecastElements: []*emissionstypes.ForecastElement{
					{
						Inferer: inferers[0],
						Value:   epochGet("forecasted_loss_2_for_0"),
					},
					{
						Inferer: inferers[1],
						Value:   epochGet("forecasted_loss_2_for_1"),
					},
					{
						Inferer: inferers[2],
						Value:   epochGet("forecasted_loss_2_for_2"),
					},
					{
						Inferer: inferers[3],
						Value:   epochGet("forecasted_loss_2_for_3"),
					},
					{
						Inferer: inferers[4],
						Value:   epochGet("forecasted_loss_2_for_4"),
					},
				},
				TopicId:     topicId,
				BlockHeight: blockHeight,
				ExtraData:   nil,
			},
		},
	}, nil
}

func GetNetworkLossFromCsv(
	topicId uint64,
	blockHeight int64,
	inferers []string,
	forecasters []string,
	reputer string,
	epochGet func(header string) alloraMath.Dec,
) (emissionstypes.ValueBundle, error) {
	if len(inferers) != 5 {
		return emissionstypes.ValueBundle{}, fmt.Errorf("expected 5 inferers, got %d", len(inferers))
	}
	if len(forecasters) != 3 {
		return emissionstypes.ValueBundle{}, fmt.Errorf("expected 3 forecasters, got %d", len(forecasters))
	}
	return emissionstypes.ValueBundle{
		TopicId: topicId,
		ReputerRequestNonce: &emissionstypes.ReputerRequestNonce{
			ReputerNonce: &emissionstypes.Nonce{BlockHeight: blockHeight}},
		Reputer:       reputer,
		ExtraData:     nil,
		CombinedValue: epochGet("network_loss"),
		InfererValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: inferers[0],
				Value:  epochGet("inference_loss_0"),
			},
			{
				Worker: inferers[1],
				Value:  epochGet("inference_loss_1"),
			},
			{
				Worker: inferers[2],
				Value:  epochGet("inference_loss_2"),
			},
			{
				Worker: inferers[3],
				Value:  epochGet("inference_loss_3"),
			},
			{
				Worker: inferers[4],
				Value:  epochGet("inference_loss_4"),
			},
		},
		NaiveValue: epochGet("network_naive_loss"),
		ForecasterValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("forecast_implied_inference_loss_0"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("forecast_implied_inference_loss_1"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("forecast_implied_inference_loss_2"),
			},
		},
		OneOutInfererForecasterValues: []*emissionstypes.OneOutInfererForecasterValues{
			{
				Forecaster: forecasters[0],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("forecast_implied_inference_loss_0_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("forecast_implied_inference_loss_0_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("forecast_implied_inference_loss_0_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("forecast_implied_inference_loss_0_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("forecast_implied_inference_loss_0_oneout_4"),
					},
				},
			},
			{
				Forecaster: forecasters[1],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("forecast_implied_inference_loss_1_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("forecast_implied_inference_loss_1_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("forecast_implied_inference_loss_1_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("forecast_implied_inference_loss_1_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("forecast_implied_inference_loss_1_oneout_4"),
					},
				},
			},
			{
				Forecaster: forecasters[2],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("forecast_implied_inference_loss_2_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("forecast_implied_inference_loss_2_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("forecast_implied_inference_loss_2_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("forecast_implied_inference_loss_2_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("forecast_implied_inference_loss_2_oneout_4"),
					},
				},
			},
		},
		OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
			{
				Worker: inferers[0],
				Value:  epochGet("network_loss_oneout_0"),
			},
			{
				Worker: inferers[1],
				Value:  epochGet("network_loss_oneout_1"),
			},
			{
				Worker: inferers[2],
				Value:  epochGet("network_loss_oneout_2"),
			},
			{
				Worker: inferers[3],
				Value:  epochGet("network_loss_oneout_3"),
			},
			{
				Worker: inferers[4],
				Value:  epochGet("network_loss_oneout_4"),
			},
		},
		OneOutForecasterValues: []*emissionstypes.WithheldWorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("network_loss_oneout_5"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("network_loss_oneout_6"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("network_loss_oneout_7"),
			},
		},
		OneInForecasterValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("network_naive_loss_onein_0"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("network_naive_loss_onein_1"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("network_naive_loss_onein_2"),
			},
		},
	}, nil
}

func signValueBundle(valueBundle *emissionstypes.ValueBundle, privateKey secp256k1.PrivKey) []byte {
	buf := valueBundleBufferPool.Get()
	defer valueBundleBufferPool.Put(buf)
	marshaled, err := valueBundle.XXX_Marshal(buf, true)
	if err != nil {
		panic(err)
	}

	valueBundleSignature, err := privateKey.Sign(marshaled)
	if err != nil {
		panic(err)
	}

	return valueBundleSignature
}

// helper struct for GetReputersDataFromCsv
type ReputerKey struct {
	Address    string
	PrivateKey secp256k1.PrivKey
	PubKeyHex  string
}

func GetReputersDataFromCsv(
	topicId uint64,
	blockHeight int64,
	inferers []string,
	forecasters []string,
	reputers []ReputerKey,
	epochGet func(header string) alloraMath.Dec,
) (emissionstypes.ReputerValueBundles, error) {
	if len(inferers) != 5 {
		return emissionstypes.ReputerValueBundles{}, fmt.Errorf("expected 5 inferers, got %d", len(inferers))
	}
	if len(forecasters) != 3 {
		return emissionstypes.ReputerValueBundles{}, fmt.Errorf("expected 3 forecasters, got %d", len(forecasters))
	}
	if len(reputers) != 5 {
		return emissionstypes.ReputerValueBundles{}, fmt.Errorf("expected 5 reputers, got %d", len(reputers))
	}
	valueBundle1 := &emissionstypes.ValueBundle{
		TopicId: topicId,
		ReputerRequestNonce: &emissionstypes.ReputerRequestNonce{
			ReputerNonce: &emissionstypes.Nonce{BlockHeight: blockHeight},
		},
		Reputer:       reputers[0].Address,
		ExtraData:     nil,
		CombinedValue: epochGet("reputer_0_loss_network_inference"),
		InfererValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: inferers[0],
				Value:  epochGet("reputer_0_loss_inference_0"),
			},
			{
				Worker: inferers[1],
				Value:  epochGet("reputer_0_loss_inference_1"),
			},
			{
				Worker: inferers[2],
				Value:  epochGet("reputer_0_loss_inference_2"),
			},
			{
				Worker: inferers[3],
				Value:  epochGet("reputer_0_loss_inference_3"),
			},
			{
				Worker: inferers[4],
				Value:  epochGet("reputer_0_loss_inference_4"),
			},
		},
		ForecasterValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_0_loss_forecast_implied_inference_0"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_0_loss_forecast_implied_inference_1"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_0_loss_forecast_implied_inference_2"),
			},
		},
		NaiveValue: epochGet("reputer_0_loss_naive_network_inference"),
		OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
			{
				Worker: inferers[0],
				Value:  epochGet("reputer_0_loss_network_inference_oneout_0"),
			},
			{
				Worker: inferers[1],
				Value:  epochGet("reputer_0_loss_network_inference_oneout_1"),
			},
			{
				Worker: inferers[2],
				Value:  epochGet("reputer_0_loss_network_inference_oneout_2"),
			},
			{
				Worker: inferers[3],
				Value:  epochGet("reputer_0_loss_network_inference_oneout_3"),
			},
			{
				Worker: inferers[4],
				Value:  epochGet("reputer_0_loss_network_inference_oneout_4"),
			},
		},
		OneOutForecasterValues: []*emissionstypes.WithheldWorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_0_loss_network_inference_oneout_5"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_0_loss_network_inference_oneout_6"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_0_loss_network_inference_oneout_7"),
			},
		},
		OneInForecasterValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_0_loss_naive_network_inference_onein_0"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_0_loss_naive_network_inference_onein_1"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_0_loss_naive_network_inference_onein_2"),
			},
		},
		OneOutInfererForecasterValues: []*emissionstypes.OneOutInfererForecasterValues{
			{
				Forecaster: forecasters[0],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_0_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_0_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_0_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_0_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_0_oneout_4"),
					},
				},
			},
			{
				Forecaster: forecasters[1],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_1_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_1_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_1_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_1_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_1_oneout_4"),
					},
				},
			},
			{
				Forecaster: forecasters[2],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_2_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_2_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_2_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_2_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_0_loss_forecast_implied_inference_2_oneout_4"),
					},
				},
			},
		},
	}
	signature1 := signValueBundle(valueBundle1, reputers[0].PrivateKey)
	reputerValueBundle1 := &emissionstypes.ReputerValueBundle{
		ValueBundle: valueBundle1,
		Signature:   signature1,
		Pubkey:      reputers[0].PubKeyHex,
	}

	valueBundle2 := &emissionstypes.ValueBundle{
		TopicId: topicId,
		ReputerRequestNonce: &emissionstypes.ReputerRequestNonce{
			ReputerNonce: &emissionstypes.Nonce{BlockHeight: blockHeight},
		},
		Reputer:       reputers[1].Address,
		ExtraData:     nil,
		CombinedValue: epochGet("reputer_1_loss_network_inference"),
		InfererValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: inferers[0],
				Value:  epochGet("reputer_1_loss_inference_0"),
			},
			{
				Worker: inferers[1],
				Value:  epochGet("reputer_1_loss_inference_1"),
			},
			{
				Worker: inferers[2],
				Value:  epochGet("reputer_1_loss_inference_2"),
			},
			{
				Worker: inferers[3],
				Value:  epochGet("reputer_1_loss_inference_3"),
			},
			{
				Worker: inferers[4],
				Value:  epochGet("reputer_1_loss_inference_4"),
			},
		},
		ForecasterValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_1_loss_forecast_implied_inference_0"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_1_loss_forecast_implied_inference_1"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_1_loss_forecast_implied_inference_2"),
			},
		},
		NaiveValue: epochGet("reputer_1_loss_naive_network_inference"),
		OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
			{
				Worker: inferers[0],
				Value:  epochGet("reputer_1_loss_network_inference_oneout_0"),
			},
			{
				Worker: inferers[1],
				Value:  epochGet("reputer_1_loss_network_inference_oneout_1"),
			},
			{
				Worker: inferers[2],
				Value:  epochGet("reputer_1_loss_network_inference_oneout_2"),
			},
			{
				Worker: inferers[3],
				Value:  epochGet("reputer_1_loss_network_inference_oneout_3"),
			},
			{
				Worker: inferers[4],
				Value:  epochGet("reputer_1_loss_network_inference_oneout_4"),
			},
		},
		OneOutForecasterValues: []*emissionstypes.WithheldWorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_1_loss_network_inference_oneout_5"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_1_loss_network_inference_oneout_6"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_1_loss_network_inference_oneout_7"),
			},
		},
		OneInForecasterValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_1_loss_naive_network_inference_onein_0"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_1_loss_naive_network_inference_onein_1"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_1_loss_naive_network_inference_onein_2"),
			},
		},
		OneOutInfererForecasterValues: []*emissionstypes.OneOutInfererForecasterValues{
			{
				Forecaster: forecasters[0],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_0_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_0_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_0_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_0_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_0_oneout_4"),
					},
				},
			},
			{
				Forecaster: forecasters[1],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_1_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_1_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_1_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_1_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_1_oneout_4"),
					},
				},
			},
			{
				Forecaster: forecasters[2],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_2_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_2_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_2_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_2_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_1_loss_forecast_implied_inference_2_oneout_4"),
					},
				},
			},
		},
	}
	signature2 := signValueBundle(valueBundle2, reputers[1].PrivateKey)
	reputerValueBundle2 := &emissionstypes.ReputerValueBundle{
		ValueBundle: valueBundle2,
		Signature:   signature2,
		Pubkey:      reputers[1].PubKeyHex,
	}

	valueBundle3 := &emissionstypes.ValueBundle{
		TopicId: topicId,
		ReputerRequestNonce: &emissionstypes.ReputerRequestNonce{
			ReputerNonce: &emissionstypes.Nonce{BlockHeight: blockHeight},
		},
		Reputer:       reputers[2].Address,
		ExtraData:     nil,
		CombinedValue: epochGet("reputer_2_loss_network_inference"),
		InfererValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: inferers[0],
				Value:  epochGet("reputer_2_loss_inference_0"),
			},
			{
				Worker: inferers[1],
				Value:  epochGet("reputer_2_loss_inference_1"),
			},
			{
				Worker: inferers[2],
				Value:  epochGet("reputer_2_loss_inference_2"),
			},
			{
				Worker: inferers[3],
				Value:  epochGet("reputer_2_loss_inference_3"),
			},
			{
				Worker: inferers[4],
				Value:  epochGet("reputer_2_loss_inference_4"),
			},
		},
		ForecasterValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_2_loss_forecast_implied_inference_0"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_2_loss_forecast_implied_inference_1"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_2_loss_forecast_implied_inference_2"),
			},
		},
		NaiveValue: epochGet("reputer_2_loss_naive_network_inference"),
		OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
			{
				Worker: inferers[0],
				Value:  epochGet("reputer_2_loss_network_inference_oneout_0"),
			},
			{
				Worker: inferers[1],
				Value:  epochGet("reputer_2_loss_network_inference_oneout_1"),
			},
			{
				Worker: inferers[2],
				Value:  epochGet("reputer_2_loss_network_inference_oneout_2"),
			},
			{
				Worker: inferers[3],
				Value:  epochGet("reputer_2_loss_network_inference_oneout_3"),
			},
			{
				Worker: inferers[4],
				Value:  epochGet("reputer_2_loss_network_inference_oneout_4"),
			},
		},
		OneOutForecasterValues: []*emissionstypes.WithheldWorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_2_loss_network_inference_oneout_5"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_2_loss_network_inference_oneout_6"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_2_loss_network_inference_oneout_7"),
			},
		},
		OneInForecasterValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_2_loss_naive_network_inference_onein_0"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_2_loss_naive_network_inference_onein_1"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_2_loss_naive_network_inference_onein_2"),
			},
		},
		OneOutInfererForecasterValues: []*emissionstypes.OneOutInfererForecasterValues{
			{
				Forecaster: forecasters[0],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_0_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_0_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_0_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_0_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_0_oneout_4"),
					},
				},
			},
			{
				Forecaster: forecasters[1],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_1_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_1_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_1_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_1_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_1_oneout_4"),
					},
				},
			},
			{
				Forecaster: forecasters[2],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_2_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_2_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_2_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_2_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_2_loss_forecast_implied_inference_2_oneout_4"),
					},
				},
			},
		},
	}
	signature3 := signValueBundle(valueBundle3, reputers[2].PrivateKey)
	reputerValueBundle3 := &emissionstypes.ReputerValueBundle{
		ValueBundle: valueBundle3,
		Signature:   signature3,
		Pubkey:      reputers[2].PubKeyHex,
	}

	valueBundle4 := &emissionstypes.ValueBundle{
		TopicId: topicId,
		ReputerRequestNonce: &emissionstypes.ReputerRequestNonce{
			ReputerNonce: &emissionstypes.Nonce{BlockHeight: blockHeight},
		},
		Reputer:       reputers[3].Address,
		ExtraData:     nil,
		CombinedValue: epochGet("reputer_3_loss_network_inference"),
		InfererValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: inferers[0],
				Value:  epochGet("reputer_3_loss_inference_0"),
			},
			{
				Worker: inferers[1],
				Value:  epochGet("reputer_3_loss_inference_1"),
			},
			{
				Worker: inferers[2],
				Value:  epochGet("reputer_3_loss_inference_2"),
			},
			{
				Worker: inferers[3],
				Value:  epochGet("reputer_3_loss_inference_3"),
			},
			{
				Worker: inferers[4],
				Value:  epochGet("reputer_3_loss_inference_4"),
			},
		},
		ForecasterValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_3_loss_forecast_implied_inference_0"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_3_loss_forecast_implied_inference_1"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_3_loss_forecast_implied_inference_2"),
			},
		},
		NaiveValue: epochGet("reputer_3_loss_naive_network_inference"),
		OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
			{
				Worker: inferers[0],
				Value:  epochGet("reputer_3_loss_network_inference_oneout_0"),
			},
			{
				Worker: inferers[1],
				Value:  epochGet("reputer_3_loss_network_inference_oneout_1"),
			},
			{
				Worker: inferers[2],
				Value:  epochGet("reputer_3_loss_network_inference_oneout_2"),
			},
			{
				Worker: inferers[3],
				Value:  epochGet("reputer_3_loss_network_inference_oneout_3"),
			},
			{
				Worker: inferers[4],
				Value:  epochGet("reputer_3_loss_network_inference_oneout_4"),
			},
		},
		OneOutForecasterValues: []*emissionstypes.WithheldWorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_3_loss_network_inference_oneout_5"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_3_loss_network_inference_oneout_6"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_3_loss_network_inference_oneout_7"),
			},
		},
		OneInForecasterValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_3_loss_naive_network_inference_onein_0"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_3_loss_naive_network_inference_onein_1"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_3_loss_naive_network_inference_onein_2"),
			},
		},
		OneOutInfererForecasterValues: []*emissionstypes.OneOutInfererForecasterValues{
			{
				Forecaster: forecasters[0],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_0_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_0_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_0_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_0_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_0_oneout_4"),
					},
				},
			},
			{
				Forecaster: forecasters[1],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_1_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_1_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_1_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_1_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_1_oneout_4"),
					},
				},
			},
			{
				Forecaster: forecasters[2],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_2_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_2_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_2_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_2_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_3_loss_forecast_implied_inference_2_oneout_4"),
					},
				},
			},
		},
	}
	signature4 := signValueBundle(valueBundle4, reputers[3].PrivateKey)
	reputerValueBundle4 := &emissionstypes.ReputerValueBundle{
		ValueBundle: valueBundle4,
		Signature:   signature4,
		Pubkey:      reputers[3].PubKeyHex,
	}

	valueBundle5 := &emissionstypes.ValueBundle{
		TopicId: topicId,
		ReputerRequestNonce: &emissionstypes.ReputerRequestNonce{
			ReputerNonce: &emissionstypes.Nonce{BlockHeight: blockHeight},
		},
		Reputer:       reputers[4].Address,
		ExtraData:     nil,
		CombinedValue: epochGet("reputer_4_loss_network_inference"),
		InfererValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: inferers[0],
				Value:  epochGet("reputer_4_loss_inference_0"),
			},
			{
				Worker: inferers[1],
				Value:  epochGet("reputer_4_loss_inference_1"),
			},
			{
				Worker: inferers[2],
				Value:  epochGet("reputer_4_loss_inference_2"),
			},
			{
				Worker: inferers[3],
				Value:  epochGet("reputer_4_loss_inference_3"),
			},
			{
				Worker: inferers[4],
				Value:  epochGet("reputer_4_loss_inference_4"),
			},
		},
		ForecasterValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_4_loss_forecast_implied_inference_0"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_4_loss_forecast_implied_inference_1"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_4_loss_forecast_implied_inference_2"),
			},
		},
		NaiveValue: epochGet("reputer_4_loss_naive_network_inference"),
		OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
			{
				Worker: inferers[0],
				Value:  epochGet("reputer_4_loss_network_inference_oneout_0"),
			},
			{
				Worker: inferers[1],
				Value:  epochGet("reputer_4_loss_network_inference_oneout_1"),
			},
			{
				Worker: inferers[2],
				Value:  epochGet("reputer_4_loss_network_inference_oneout_2"),
			},
			{
				Worker: inferers[3],
				Value:  epochGet("reputer_4_loss_network_inference_oneout_3"),
			},
			{
				Worker: inferers[4],
				Value:  epochGet("reputer_4_loss_network_inference_oneout_4"),
			},
		},
		OneOutForecasterValues: []*emissionstypes.WithheldWorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_4_loss_network_inference_oneout_5"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_4_loss_network_inference_oneout_6"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_4_loss_network_inference_oneout_7"),
			},
		},
		OneInForecasterValues: []*emissionstypes.WorkerAttributedValue{
			{
				Worker: forecasters[0],
				Value:  epochGet("reputer_4_loss_naive_network_inference_onein_0"),
			},
			{
				Worker: forecasters[1],
				Value:  epochGet("reputer_4_loss_naive_network_inference_onein_1"),
			},
			{
				Worker: forecasters[2],
				Value:  epochGet("reputer_4_loss_naive_network_inference_onein_2"),
			},
		},
		OneOutInfererForecasterValues: []*emissionstypes.OneOutInfererForecasterValues{
			{
				Forecaster: forecasters[0],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_0_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_0_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_0_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_0_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_0_oneout_4"),
					},
				},
			},
			{
				Forecaster: forecasters[1],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_1_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_1_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_1_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_1_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_1_oneout_4"),
					},
				},
			},
			{
				Forecaster: forecasters[2],
				OneOutInfererValues: []*emissionstypes.WithheldWorkerAttributedValue{
					{
						Worker: inferers[0],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_2_oneout_0"),
					},
					{
						Worker: inferers[1],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_2_oneout_1"),
					},
					{
						Worker: inferers[2],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_2_oneout_2"),
					},
					{
						Worker: inferers[3],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_2_oneout_3"),
					},
					{
						Worker: inferers[4],
						Value:  epochGet("reputer_4_loss_forecast_implied_inference_2_oneout_4"),
					},
				},
			},
		},
	}
	signature5 := signValueBundle(valueBundle5, reputers[4].PrivateKey)
	reputerValueBundle5 := &emissionstypes.ReputerValueBundle{
		ValueBundle: valueBundle5,
		Signature:   signature5,
		Pubkey:      reputers[4].PubKeyHex,
	}
	return emissionstypes.ReputerValueBundles{
		ReputerValueBundles: []*emissionstypes.ReputerValueBundle{
			reputerValueBundle1,
			reputerValueBundle2,
			reputerValueBundle3,
			reputerValueBundle4,
			reputerValueBundle5,
		},
	}, nil
}

func GetTotalInfererRewardForTopicInEpoch(
	epochGet func(header string) alloraMath.Dec,
) (alloraMath.Dec, error) {
	infererRewards := []alloraMath.Dec{
		epochGet("inferer_reward_0"),
		epochGet("inferer_reward_1"),
		epochGet("inferer_reward_2"),
		epochGet("inferer_reward_3"),
		epochGet("inferer_reward_4"),
	}
	totalInferersReward := alloraMath.ZeroDec()
	var err error
	for _, reward := range infererRewards {
		totalInferersReward, err = totalInferersReward.Add(reward)
		if err != nil {
			return alloraMath.ZeroDec(), err
		}
	}
	return totalInferersReward, nil
}

func GetTotalForecasterRewardForTopicInEpoch(
	epochGet func(header string) alloraMath.Dec,
) (alloraMath.Dec, error) {
	forecasterRewards := []alloraMath.Dec{
		epochGet("forecaster_reward_0"),
		epochGet("forecaster_reward_1"),
		epochGet("forecaster_reward_2"),
	}
	totalForecastersReward := alloraMath.ZeroDec()
	var err error
	for _, reward := range forecasterRewards {
		totalForecastersReward, err = totalForecastersReward.Add(reward)
		if err != nil {
			return alloraMath.ZeroDec(), err
		}
	}
	return totalForecastersReward, nil
}

func GetTotalReputerRewardForTopicInEpoch(
	epochGet func(header string) alloraMath.Dec,
) (alloraMath.Dec, error) {
	reputerRewards := []alloraMath.Dec{
		epochGet("reputer_reward_0"),
		epochGet("reputer_reward_1"),
		epochGet("reputer_reward_2"),
		epochGet("reputer_reward_3"),
		epochGet("reputer_reward_4"),
	}
	// Reputer rewards
	totalReputersReward := alloraMath.ZeroDec()
	for _, reward := range reputerRewards {
		totalReputersReward, _ = totalReputersReward.Add(reward)
	}
	return totalReputersReward, nil
}

func GetTotalRewardForTopicInEpoch(
	epochGet func(header string) alloraMath.Dec,
) (alloraMath.Dec, error) {
	totalRewardForTopic := alloraMath.ZeroDec()
	totalInferersReward, err := GetTotalInfererRewardForTopicInEpoch(epochGet)
	if err != nil {
		return alloraMath.ZeroDec(), err
	}
	totalForecastersReward, err := GetTotalForecasterRewardForTopicInEpoch(epochGet)
	if err != nil {
		return alloraMath.ZeroDec(), err
	}
	totalReputersReward, err := GetTotalReputerRewardForTopicInEpoch(epochGet)
	if err != nil {
		return alloraMath.ZeroDec(), err
	}
	totalRewardForTopic, err = totalRewardForTopic.Add(totalInferersReward)
	if err != nil {
		return alloraMath.ZeroDec(), err
	}
	totalRewardForTopic, err = totalRewardForTopic.Add(totalForecastersReward)
	if err != nil {
		return alloraMath.ZeroDec(), err
	}
	totalRewardForTopic, err = totalRewardForTopic.Add(totalReputersReward)
	if err != nil {
		return alloraMath.ZeroDec(), err
	}

	return totalRewardForTopic, nil
}

func SetRegretsFromPreviousEpoch(
	ctx sdk.Context,
	k keeper.Keeper,
	topicId uint64,
	blockHeight int64,
	inferers []string,
	forecasters []string,
	epochPrevGet func(header string) alloraMath.Dec,
) error {
	// Set inferer network regrets
	infererNetworkRegrets := map[string]inferencesynthesis.Regret{}
	for i, inferer := range inferers {
		infererNetworkRegrets[inferer] = epochPrevGet(fmt.Sprintf("inference_regret_worker_%v", i))
	}

	for inferer, regret := range infererNetworkRegrets {
		err := k.SetInfererNetworkRegret(
			ctx,
			topicId,
			inferer,
			emissionstypes.TimestampedValue{BlockHeight: blockHeight, Value: regret},
		)
		if err != nil {
			return fmt.Errorf("error setting inferer network regret: %v", err)
		}
	}

	// Set forecaster network regrets
	forecasterNetworkRegrets := map[string]inferencesynthesis.Regret{}
	for i, forecaster := range forecasters {
		forecasterNetworkRegrets[forecaster] = epochPrevGet(fmt.Sprintf("inference_regret_worker_%v", i+5))
	}

	for forecaster, regret := range forecasterNetworkRegrets {
		err := k.SetForecasterNetworkRegret(
			ctx,
			topicId,
			forecaster,
			emissionstypes.TimestampedValue{BlockHeight: blockHeight, Value: regret},
		)
		if err != nil {
			return fmt.Errorf("error setting forecaster network regret: %v", err)
		}
	}

	// Set naive inferer network regrets
	infererNaiveNetworkRegrets := map[string]inferencesynthesis.Regret{}
	for i, inferer := range inferers {
		infererNaiveNetworkRegrets[inferer] = epochPrevGet(fmt.Sprintf("naive_inference_regret_worker_%v", i))
	}

	for inferer, regret := range infererNaiveNetworkRegrets {
		err := k.SetNaiveInfererNetworkRegret(
			ctx,
			topicId,
			inferer,
			emissionstypes.TimestampedValue{BlockHeight: blockHeight, Value: regret},
		)
		if err != nil {
			return fmt.Errorf("error setting naive inferer network regret: %v", err)
		}
	}

	// Set one-out inferer-inferer network regrets
	for i := range inferers {
		for j := range inferers {
			headerName := fmt.Sprintf("inference_regret_worker_%v_oneout_%v", i, j)
			err := k.SetOneOutInfererInfererNetworkRegret(
				ctx,
				topicId,
				inferers[j],
				inferers[i],
				emissionstypes.TimestampedValue{
					BlockHeight: blockHeight,
					Value:       epochPrevGet(headerName),
				},
			)
			if err != nil {
				return fmt.Errorf("error setting one-out inferer-inferer network regret: %v", err)
			}
		}
	}

	// Set one-out inferer-forecaster network regrets
	for i := range inferers {
		for j := range forecasters {
			headerName := fmt.Sprintf("inference_regret_worker_%v_oneout_%v", j+5, i)
			err := k.SetOneOutInfererForecasterNetworkRegret(
				ctx,
				topicId,
				inferers[i],
				forecasters[j],
				emissionstypes.TimestampedValue{
					BlockHeight: blockHeight,
					Value:       epochPrevGet(headerName),
				},
			)
			if err != nil {
				return fmt.Errorf("error setting one-out inferer-forecaster network regret: %v", err)
			}
		}
	}

	// Set one-out forecaster-inferer network regrets
	for i := range inferers {
		for j := range forecasters {
			headerName := fmt.Sprintf("inference_regret_worker_%v_oneout_%v", i, j+5)
			err := k.SetOneOutForecasterInfererNetworkRegret(
				ctx,
				topicId,
				forecasters[j],
				inferers[i],
				emissionstypes.TimestampedValue{
					BlockHeight: blockHeight,
					Value:       epochPrevGet(headerName),
				},
			)
			if err != nil {
				return fmt.Errorf("error setting one-out forecaster-inferer network regret: %v", err)
			}
		}
	}

	// Set one-out forecaster-forecaster network regrets
	for i := range forecasters {
		for j := range forecasters {
			headerName := fmt.Sprintf("inference_regret_worker_%v_oneout_%v", i+5, j+5)
			err := k.SetOneOutForecasterForecasterNetworkRegret(
				ctx,
				topicId,
				forecasters[j],
				forecasters[i],
				emissionstypes.TimestampedValue{
					BlockHeight: blockHeight,
					Value:       epochPrevGet(headerName),
				},
			)
			if err != nil {
				return fmt.Errorf("error setting one-out forecaster-forecaster network regret: %v", err)
			}
		}
	}

	// Set one-in forecaster network regrets
	for i := range forecasters {
		headerName := fmt.Sprintf("inference_regret_worker_5_onein_%v", i)
		err := k.SetOneInForecasterNetworkRegret(
			ctx,
			topicId,
			forecasters[i],
			forecasters[i],
			emissionstypes.TimestampedValue{
				BlockHeight: blockHeight,
				Value:       epochPrevGet(headerName),
			},
		)
		if err != nil {
			return fmt.Errorf("error setting one-in forecaster network regret: %v", err)
		}
		for j := range inferers {
			headerName := fmt.Sprintf("inference_regret_worker_%v_onein_%v", j, i)
			err := k.SetOneInForecasterNetworkRegret(
				ctx,
				topicId,
				forecasters[i],
				inferers[j],
				emissionstypes.TimestampedValue{
					BlockHeight: blockHeight,
					Value:       epochPrevGet(headerName),
				},
			)
			if err != nil {
				return fmt.Errorf("error setting one-in forecaster network regret: %v", err)
			}
		}
	}

	return nil
}

func GetSortitionSimulatorValuesGetterForEpochs() map[int]func(header string) alloraMath.Dec {
	const simulatorHeaders = "epoch,n_participants,n_participants_max,n_participants_drawn,quality_cutoff,percentile,alpha_quality,quality_percentile,0_prev_participated,0_prev_quality_ema,0_sort_position_previous_quality_ema,0_sort_position_quality_metrics,0_active,0_quality_metric,0_quality_ema,1_prev_participated,1_prev_quality_ema,1_sort_position_previous_quality_ema,1_sort_position_quality_metrics,1_active,1_quality_metric,1_quality_ema,2_prev_participated,2_prev_quality_ema,2_sort_position_previous_quality_ema,2_sort_position_quality_metrics,2_active,2_quality_metric,2_quality_ema,3_prev_participated,3_prev_quality_ema,3_sort_position_previous_quality_ema,3_sort_position_quality_metrics,3_active,3_quality_metric,3_quality_ema,4_prev_participated,4_prev_quality_ema,4_sort_position_previous_quality_ema,4_sort_position_quality_metrics,4_active,4_quality_metric,4_quality_ema,5_prev_participated,5_prev_quality_ema,5_sort_position_previous_quality_ema,5_sort_position_quality_metrics,5_active,5_quality_metric,5_quality_ema,6_prev_participated,6_prev_quality_ema,6_sort_position_previous_quality_ema,6_sort_position_quality_metrics,6_active,6_quality_metric,6_quality_ema,7_prev_participated,7_prev_quality_ema,7_sort_position_previous_quality_ema,7_sort_position_quality_metrics,7_active,7_quality_metric,7_quality_ema"
	simulatorEpochs := map[int]string{
		300: "300,8,5,5,0.15051785184201963,20,0.1,0.1255336081888135,true,0.11406254395706042,7,,,,0.11520965038023573,true,0.11747935227513646,5,,,,0.11828477786650417,true,0.35614532609011657,1,4,true,0.09166028668778334,0.3296968221498833,true,0.1172213184572862,6,,,,0.11805254743043893,true,0.4770759602298508,0,1,true,0.4591089530674562,0.4752792595136114,true,0.15051785184201963,4,2,true,0.43381630437630625,0.1788476970954483,true,0.1792792070820537,3,3,true,0.13400193856407105,0.17475148023025544,true,0.2215930893092064,2,0,true,0.48414844671682644,0.2478486250499684",
		301: "301,8,5,5,0.17475148023025544,20,0.1,0.010460649655629104,true,0.11520965038023573,7,,,,0.10473475030777507,true,0.11828477786650417,5,,,,0.10750236504541666,true,0.3296968221498833,1,3,true,0.02075826620396365,0.2988029665552913,true,0.11805254743043893,6,,,,0.10729335765295794,true,0.4752792595136114,0,0,true,0.6875270309955097,0.4965040366618012,true,0.1788476970954483,3,1,true,0.3595578447635491,0.19691871186225837,true,0.17475148023025544,4,2,true,0.05789280428041588,0.16306561263527147,true,0.2478486250499684,2,4,true,-0.030729816537709093,0.21999078089120067",
		302: "302,8,5,5,0.16306561263527147,20,0.1,0.1565910640663154,true,0.10473475030777507,7,,,,0.10992038168362911,true,0.10750236504541666,5,,,,0.11241123494750653,true,0.2988029665552913,1,4,true,-0.05947253078680703,0.2629754168210815,true,0.10729335765295794,6,,,,0.11222312829429369,true,0.4965040366618012,0,0,true,0.5153355119581934,0.49838718419144046,true,0.19691871186225837,3,1,true,0.47883682207567724,0.22511052288360026,true,0.16306561263527147,4,2,true,0.2820599766834697,0.1749650490400913,true,0.21999078089120067,2,3,true,0.210606962779596,0.2190523990800402",
		303: "303,8,5,5,0.1749650490400913,20,0.1,0.18795584642520996,true,0.10992038168362911,7,,,,0.1177239281577872,true,0.11241123494750653,5,,,,0.11996569609527688,true,0.2629754168210815,1,3,true,0.2512156876803045,0.26179944390700377,true,0.11222312829429369,6,,,,0.11979640010738532,true,0.49838718419144046,0,0,true,0.555229733452909,0.5040714391175873,true,0.22511052288360026,2,1,true,0.48873694862691053,0.2514731654579313,true,0.1749650490400913,4,4,true,-0.06508351859516817,0.15096019227656537,true,0.2190523990800402,3,2,true,0.30171740692373467,0.22731889986440965",
		304: "304,8,5,5,0.15096019227656537,20,0.1,0.01408285006346982,true,0.1177239281577872,7,,,,0.10735982034835548,true,0.11996569609527688,5,,,,0.10937741149209618,true,0.26179944390700377,1,4,true,-0.13637884964629166,0.22198161455167423,true,0.11979640010738532,6,,,,0.10922504510299377,true,0.5040714391175873,0,1,true,0.1934773927554307,0.4730120344813717,true,0.2514731654579313,2,0,true,0.24949941658457403,0.25127579057059557,true,0.15096019227656537,4,3,true,0.051698274990910176,0.14103400054799986,true,0.22731889986440965,3,2,true,0.10932939132483192,0.21551994901045188",
		305: "305,8,5,5,0.14103400054799986,20,0.1,0.06121677931568584,true,0.10735982034835548,7,,,,0.10274551624508851,true,0.10937741149209618,5,,,,0.10456134827445514,true,0.22198161455167423,2,1,true,0.3579613129177525,0.23557958438828205,true,0.10922504510299377,6,,,,0.10442421852426298,true,0.4730120344813717,0,0,true,0.6198100803338487,0.4876918390666194,true,0.25127579057059557,1,4,true,0.03193548076732808,0.2293417595902688,true,0.14103400054799986,4,2,true,0.15089314615315577,0.14201991510851544,true,0.21551994901045188,3,3,true,0.06853710395277528,0.20082166450468422",
		306: "306,8,5,5,0.14201991510851544,20,0.1,0.1309176581536055,true,0.10274551624508851,7,,,,0.10556273043594021,true,0.10456134827445514,5,,,,0.10719697926237018,true,0.23557958438828205,1,3,true,0.1439993324438856,0.2264215591938424,true,0.10442421852426298,6,,,,0.10707356248719724,true,0.4876918390666194,0,4,true,0.07859096099248519,0.446781751259206,true,0.2293417595902688,2,0,true,0.554175540675531,0.261825137698795,true,0.14201991510851544,4,1,true,0.46245461286023215,0.1740633848836871,true,0.20082166450468422,3,2,true,0.42567056985384594,0.2233065550396004",
		307: "307,8,5,5,0.1740633848836871,20,0.1,0.14261635986161547,true,0.10556273043594021,7,,,,0.10926809337850774,true,0.10719697926237018,5,,,,0.11073891732229471,true,0.2264215591938424,2,3,true,0.14482679072658144,0.21826208234711633,true,0.10707356248719724,6,,,,0.11062784222463906,true,0.446781751259206,0,1,true,0.31097762812975904,0.4332013389462613,true,0.261825137698795,1,2,true,0.22457920041535723,0.25810054397045123,true,0.1740633848836871,4,4,true,0.13377463640175158,0.17003451003549358,true,0.2233065550396004,3,0,true,0.42651218237060573,0.24362711777270094",
		308: "308,8,5,5,0.17003451003549358,20,0.1,0.06252053239505342,true,0.10926809337850774,7,,,,0.1045933372801623,true,0.11073891732229471,5,,,,0.10591707882957058,true,0.21826208234711633,3,4,true,0.004786140489145108,0.1969144881613192,true,0.11062784222463906,6,,,,0.1058171112416805,true,0.4332013389462613,0,0,true,0.6969287637406706,0.4595740814257022,true,0.25810054397045123,1,2,true,0.10762636487230662,0.24305312606063678,true,0.17003451003549358,4,3,true,0.0769541303715305,0.16072647206909726,true,0.24362711777270094,2,1,true,0.39896060379874576,0.25916046637530543",
		309: "309,8,5,5,0.16072647206909726,20,0.1,-0.010277757353331252,true,0.1045933372801623,7,,,,0.09310622781681295,true,0.10591707882957058,5,,,,0.0942975952112804,true,0.1969144881613192,3,3,true,0.011231534534002219,0.17834619279858752,true,0.1058171112416805,6,,,,0.09420762438217933,true,0.4595740814257022,0,0,true,0.906123243224335,0.5042289976055655,true,0.24305312606063678,2,4,true,-0.09631492490266516,0.2091163209643066,true,0.16072647206909726,4,2,true,0.18007488295055368,0.1626613131572429,true,0.25916046637530543,1,1,true,0.4404613912790495,0.2772905588656799",
		310: "310,8,5,5,0.1626613131572429,20,0.1,0.03598644427061674,true,0.09310622781681295,7,,,,0.08739424946219333,true,0.0942975952112804,5,,,,0.08846648011721403,true,0.17834619279858752,3,2,true,0.2304013504028307,0.18355170855901184,true,0.09420762438217933,6,,,,0.08838550637102308,true,0.5042289976055655,0,0,true,0.3519728252685276,0.48900338037186175,true,0.2091163209643066,2,1,true,0.28717046062525703,0.21692173493040165,true,0.1626613131572429,4,4,true,-0.11612843112314528,0.13478233872920406,true,0.2772905588656799,1,3,true,0.07401516311905723,0.2569630192910176",
		311: "311,8,5,5,0.13478233872920406,20,0.1,0.3882498634713742,true,0.08739424946219333,7,,,,0.11747981086311142,true,0.08846648011721403,5,,,,0.11844481845263005,true,0.18355170855901184,3,2,true,0.44291752660848804,0.20948829036395947,true,0.08838550637102308,6,,,,0.1183719420810582,true,0.48900338037186175,0,0,true,0.6774038903373872,0.5078434313684143,true,0.21692173493040165,2,3,true,0.42315646269242724,0.2375452077066042,true,0.13478233872920406,4,1,true,0.6435931091640481,0.18566341577268847,true,0.2569630192910176,1,4,true,0.248623466587162,0.25612906402063207",
		312: "312,8,5,5,0.18566341577268847,20,0.1,0.2047637518756514,true,0.11747981086311142,7,,,,0.1262082049643654,true,0.11844481845263005,5,,,,0.12707671179493218,true,0.20948829036395947,3,0,true,0.5204664207769446,0.240586103405258,true,0.1183719420810582,6,,,,0.1270111230605175,true,0.5078434313684143,0,1,true,0.49628634168234953,0.5066877223998077,true,0.2375452077066042,2,3,true,0.23767166486962246,0.23755785342290603,true,0.18566341577268847,4,4,true,0.0731320998997671,0.17441028418539634,true,0.25612906402063207,1,2,true,0.3770674034638276,0.26822289796495163",
		313: "313,8,5,5,0.17441028418539634,20,0.1,0.302444539832311,true,0.1262082049643654,7,,,,0.14383183845116,true,0.12707671179493218,5,,,,0.14461349459867007,true,0.240586103405258,2,2,true,0.42796796183333885,0.2593242892480661,true,0.1270111230605175,6,,,,0.14455446473769687,true,0.5066877223998077,0,3,true,0.41914369710241073,0.49793331987006806,true,0.23755785342290603,3,1,true,0.49628347999243383,0.26343041607985884,true,0.17441028418539634,4,4,true,-0.1643520892480879,0.14053404684204793,true,0.26822289796495163,1,0,true,0.503123302978025,0.291712938466259",
		314: "314,8,5,5,0.14461349459867007,20,0.1,-0.023411686574991413,true,0.14383183845116,6,,,,0.12710748594854485,true,0.14461349459867007,4,4,true,-0.024598176273040145,0.12769232751149906,true,0.2593242892480661,3,0,true,0.4891701455709334,0.28230887488035283,true,0.14455446473769687,5,,,,0.12775784960642805,true,0.49793331987006806,0,2,true,0.24550977530231838,0.4726909654132931,true,0.26343041607985884,2,3,true,-0.02311506415047923,0.23477586805682504,true,0.14053404684204793,7,,,,0.12413947350034399,true,0.291712938466259,1,1,true,0.35190856340058146,0.2977325009596913",
		315: "315,8,5,5,0.12775784960642805,20,0.1,0.1490394203154356,true,0.12710748594854485,6,,,,0.12930067938523393,true,0.12769232751149906,5,,,,0.12982703679189272,true,0.28230887488035283,2,2,true,0.2873264516650472,0.2828106325588223,true,0.12775784960642805,4,4,true,-0.2058985696135995,0.0943922076844253,true,0.4726909654132931,0,1,true,0.5703057123860868,0.4824524401105724,true,0.23477586805682504,3,3,true,0.23777391779769436,0.23507567303091198,true,0.12413947350034399,7,,,,0.12662946818185314,true,0.2977325009596913,1,0,true,0.6734363919622122,0.3353028900599434",
		316: "316,8,5,5,0.12982703679189272,20,0.1,-0.08069447105736081,true,0.12930067938523393,5,,,,0.10830116434097446,true,0.12982703679189272,4,3,true,-0.07131881970234927,0.10971245114246853,true,0.2828106325588223,2,1,true,0.285394410146682,0.2830690103176083,true,0.0943922076844253,7,,,,0.07688353981024669,true,0.4824524401105724,0,2,true,0.07140369856352868,0.44134756595586805,true,0.23507567303091198,3,0,true,0.4126816813015799,0.2528362738579788,true,0.12662946818185314,6,,,,0.10589707425793175,true,0.3353028900599434,1,4,true,-0.11819707647740699,0.2899528934062084",
		317: "317,8,5,5,0.10971245114246853,20,0.1,0.07037817416378767,true,0.10830116434097446,5,,,,0.10450886532325579,true,0.10971245114246853,4,3,true,0.11923793320680443,0.11066499934890212,true,0.2830690103176083,2,2,true,0.28207389099595326,0.2829694983854428,true,0.07688353981024669,7,,,,0.07623300324560078,true,0.44134756595586805,0,0,true,0.4676613475700888,0.4439789441172901,true,0.2528362738579788,3,1,true,0.4152082410321782,0.26907347057539877,true,0.10589707425793175,6,,,,0.10234518424851735,true,0.2899528934062084,1,4,true,-0.12506086200827946,0.2484515178647596",
		318: "318,8,5,5,0.11066499934890212,20,0.1,0.10070911263801881,true,0.10450886532325579,5,,,,0.1041288900547321,true,0.11066499934890212,4,4,true,0.05919964866172753,0.10551846428018466,true,0.2829694983854428,1,2,true,0.3396441324700214,0.28863696179390064,true,0.07623300324560078,7,,,,0.0786806141848426,true,0.4439789441172901,0,0,true,0.8169172129020008,0.4812727709957612,true,0.26907347057539877,2,3,true,0.11108647863209162,0.2532747713810681,true,0.10234518424851735,6,,,,0.1021815770874675,true,0.2484515178647596,3,1,true,0.3875699988267758,0.2623633659609612",
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		391: "391,8,5,5,0.13655395968531905,20,0.1,0.126426253073959,true,0.13655395968531905,4,4,true,-0.1376822882190953,0.10913033489487761,true,0.10402708834361844,6,,,,0.10626700481665251,true,0.3649250030642178,1,3,true,0.19245338839722254,0.3476778415975183,true,0.10052224364422287,7,,,,0.10311264458719649,true,0.5307126233172126,0,1,true,0.32070066866863467,0.5097114278523548,true,0.18476160279991827,3,2,true,0.30351522977984235,0.19663696549791068,true,0.19741447869439685,2,0,true,0.6133437223150044,0.23900740305645762,true,0.1046058318848771,5,,,,0.1067878740037853",
		392: "392,8,5,5,0.10913033489487761,20,0.1,0.011349402067768764,true,0.10913033489487761,4,3,true,0.036782310526963916,0.10189553245808625,true,0.10626700481665251,6,,,,0.09677524454176413,true,0.3476778415975183,1,1,true,0.28245674421377215,0.34115573185914366,true,0.10311264458719649,7,,,,0.09393632033525372,true,0.5097114278523548,0,0,true,0.47782121871228767,0.506522406938348,true,0.19663696549791068,3,2,true,0.2691898234896351,0.20389225129708313,true,0.23900740305645762,2,4,true,-0.09038223176901186,0.2060684395739107,true,0.1067878740037853,5,,,,0.09724402681018364",
		393: "393,8,5,5,0.10189553245808625,20,0.1,-0.08471812831896004,true,0.10189553245808625,4,4,true,-0.20582379396690367,0.07112359981558725,true,0.09677524454176413,6,,,,0.07862590725569171,true,0.34115573185914366,1,0,true,0.8087858602948734,0.38791874470271664,true,0.09393632033525372,7,,,,0.07607087546983234,true,0.506522406938348,0,1,true,0.7254621145755304,0.5284163777020663,true,0.20389225129708313,3,3,true,-0.05444171190697414,0.1780588549766774,true,0.2060684395739107,2,2,true,0.009782507922990041,0.1864398464088186,true,0.09724402681018364,5,,,,0.07904781129726927",
		394: "394,8,5,5,0.07904781129726927,20,0.1,0.04117889221158516,true,0.07112359981558725,7,,,,0.06812912905518705,true,0.07862590725569171,5,,,,0.07488120575128107,true,0.38791874470271664,1,4,true,-0.0238557520285666,0.34674129502958834,true,0.07607087546983234,6,,,,0.07258167714400762,true,0.5284163777020663,0,0,true,0.7378198226704431,0.549356722198904,true,0.1780588549766774,3,1,true,0.5350536630181723,0.2137583357808269,true,0.1864398464088186,2,3,true,0.0574375532716231,0.17353961709509907,true,0.07904781129726927,4,2,true,0.3407090744835244,0.10521393761589479",
		395: "395,8,5,5,0.10521393761589479,20,0.1,-0.015863097236965946,true,0.06812912905518705,7,,,,0.05972990642597174,true,0.07488120575128107,5,,,,0.06580677545245638,true,0.34674129502958834,1,2,true,0.05116641890338741,0.3171838074169682,true,0.07258167714400762,6,,,,0.06373719970591027,true,0.549356722198904,0,0,true,0.8065191259463069,0.5750729625736443,true,0.2137583357808269,2,3,true,-0.014907027620294333,0.1908917994407148,true,0.17353961709509907,3,4,true,-0.019687375703652393,0.15421691781522395,true,0.10521393761589479,4,1,true,0.2693499667126922,0.12162754052557453",
		396: "396,8,5,5,0.12162754052557453,20,0.1,0.25342996186643657,true,0.05972990642597174,7,,,,0.07909991197001823,true,0.06580677545245638,5,,,,0.08456909409385441,true,0.3171838074169682,1,0,true,0.6689331960673114,0.3523587462820026,true,0.06373719970591027,6,,,,0.0827064759219629,true,0.5750729625736443,0,3,true,0.28986819330126873,0.5465524856464068,true,0.1908917994407148,2,2,true,0.43028523175754296,0.2148311426723976,true,0.15421691781522395,3,4,true,0.10767703612710798,0.14956292964641235,true,0.12162754052557453,4,1,true,0.44591367098283663,0.15405615357130076",
		397: "397,8,5,5,0.14956292964641235,20,0.1,0.03409475232310376,true,0.07909991197001823,7,,,,0.07459939600532678,true,0.08456909409385441,5,,,,0.07952165991677934,true,0.3523587462820026,1,0,true,0.4391500402026953,0.36103787567407186,true,0.0827064759219629,6,,,,0.07784530356207699,true,0.5465524856464068,0,2,true,0.14691860933238288,0.5065890980150044,true,0.2148311426723976,2,4,true,-0.1635787777223531,0.17699015063292256,true,0.14956292964641235,4,3,true,0.08351313483446796,0.1429579501652179,true,0.15405615357130076,3,1,true,0.18614239863499968,0.15726477807767067",
		398: "398,8,5,5,0.1429579501652179,20,0.1,0.2512012736036656,true,0.07459939600532678,7,,,,0.09225958376516066,true,0.07952165991677934,5,,,,0.09668962128546797,true,0.36103787567407186,1,3,true,0.26266732074771715,0.3512008201814364,true,0.07784530356207699,6,,,,0.09518090056623585,true,0.5065890980150044,0,0,true,0.6305809366259272,0.5189882818760967,true,0.17699015063292256,2,2,true,0.320799516630486,0.19137108723267893,true,0.1429579501652179,4,4,true,0.20533708502745948,0.14919586365144205,true,0.15726477807767067,3,1,true,0.39288962475253114,0.18082726274515673",
		399: "399,8,5,5,0.14919586365144205,20,0.1,0.2204127355889608,true,0.09225958376516066,7,,,,0.10507489894754068,true,0.09668962128546797,5,,,,0.10906193271581725,true,0.3512008201814364,1,1,true,0.4246860676467026,0.358549344927963,true,0.09518090056623585,6,,,,0.10770408406850834,true,0.5189882818760967,0,0,true,0.6071424328304225,0.5278036969715293,true,0.19137108723267893,2,2,true,0.3153506021558414,0.2037690387249952,true,0.14919586365144205,4,3,true,0.24153305474064352,0.1584295827603622,true,0.18082726274515673,3,4,true,0.13593145898222994,0.17633768236886405",
		400: "400,8,5,5,0.1584295827603622,20,0.1,0.12289460679596906,true,0.10507489894754068,7,,,,0.10685686973238352,true,0.10906193271581725,5,,,,0.11044520012383244,true,0.358549344927963,1,1,true,0.4232790444194137,0.365022314877108,true,0.10770408406850834,6,,,,0.10922313634125443,true,0.5278036969715293,0,0,true,0.5351434581777635,0.5285376730921527,true,0.2037690387249952,2,2,true,0.2365383104204157,0.20704596589453725,true,0.1584295827603622,4,3,true,0.18535548931591248,0.16112217341591722,true,0.17633768236886405,3,4,true,-0.12694892328380467,0.14600902180359718",
	}
	// skip epoch column, change true values to be alloraMath.OneDec()
	// and empty values to be alloraMath.ZeroDec()
	filteredSimulatorEpochs := map[int]string{}
	for epochNumber, epoch := range simulatorEpochs {
		outputted := ""
		splitted := strings.Split(epoch, ",")[1:] // remove epoch header
		stop := len(splitted) - 1
		for i, value := range splitted {
			if value == "" { // empty string represent as alloraMath.ZeroDec()
				outputted += "0"
			} else if value == "true" { // true string represent as alloraMath.OneDec()
				outputted += "1"
			} else { // you have a real value, just use that
				outputted += value
			}
			if i != stop { // add comma if not last value
				outputted += ","
			}
		}
		filteredSimulatorEpochs[epochNumber] = outputted
	}
	filteredSimulatorHeaders := strings.Join(strings.Split(simulatorHeaders, ",")[1:], ",")
	gettersMap := map[int](func(header string) alloraMath.Dec){}
	for epochNumber, epoch := range filteredSimulatorEpochs {
		gettersMap[epochNumber] = GetSimulatedValuesGetterForEpoch(epoch, filteredSimulatorHeaders)
	}
	return gettersMap
}
