package main

import (
	"encoding/csv"
	"fmt"
	"math"
	rand "math/rand/v2"
	"os"
	"strconv"
	"time"
	// "strings"
)

/* Structs */
type State struct {
	Name                         string
	Votes                        int
	PresidentialElectoralHistory map[string]string
	Polls                        []Poll
}

type VotesForEachParty struct {
	Democrats   int
	Republicans int
}

type Poll struct {
	PollId      string
	SampleSize  int
	PollResults map[string]float64
	Date        time.Time
	Partisan    string
}

/* Globals */
var r = rand.New(rand.NewPCG(uint64(100), uint64(2224)))
var dem_nominee_name = "Biden"
var rep_nominee_name = "Trump"

/* Sampling helper functions */
func getNormalCDF(x float64, mean float64, std float64) float64 {
	erf_term := (x - mean) / (std * math.Sqrt2)
	return (1 + math.Erf(erf_term)) / 2
}

func getProbabilityAboveX(x float64, mean float64, std float64) float64 {
	return 1 - getNormalCDF(x, mean, std)
}

func getChanceCandidateWinsFromPollShare(candidate_p float64, poll_sample_size float64) float64 {
	std := math.Sqrt(candidate_p * (1 - candidate_p) / poll_sample_size) // https://stats.stackexchange.com/questions/258879/how-to-interpret-margin-of-error-in-a-non-binary-poll
	return getProbabilityAboveX(0.5, candidate_p, std)
}

func getChanceRepublicanWinFromPoll(poll Poll, pretty_print bool) float64 {
	biden_percentage, biden_exists := poll.PollResults[dem_nominee_name]
	trump_percentage, trump_exists := poll.PollResults[rep_nominee_name]
	if !biden_exists || !trump_exists {
		panic("PollResults of poll filtered to have Biden/Trump doesn't have Biden/Trump")
	}
	biden_share := biden_percentage / 100.0 // will panic if the item is not found, but we've previously filtered for it
	trump_share := trump_percentage / 100.0

	normalized_trump_share := trump_share / (trump_share + biden_share)
	normalized_biden_share := biden_share / (trump_share + biden_share)

	joint_trump_biden_sample_size := (biden_share + trump_share) * float64(poll.SampleSize)
	std_error_poll_mean := math.Sqrt((normalized_trump_share * normalized_biden_share) / joint_trump_biden_sample_size)

	p_republican_win := getProbabilityAboveX(0.5, normalized_trump_share, std_error_poll_mean)

	if pretty_print {
		fmt.Printf("\n\t\tSample size: %f", joint_trump_biden_sample_size)
		fmt.Printf("\n\t\tMean R: %f", 100.0*normalized_trump_share)
		fmt.Printf("\n\t\tStd of mean R: %f", 100*std_error_poll_mean)
		fmt.Printf("\n\t\tPoll says chance of R win: %f", p_republican_win)
	}
	return p_republican_win
}

func getChanceRepublicanWinFromPollPlusUncertainty(poll Poll, state State, pretty_print bool) float64 {
	// Uncertainty from the state
	n_republican_win := 0
	for _, party := range state.PresidentialElectoralHistory {
		if party == "R" {
			n_republican_win++
		}
	}

	// Get the uncertainty from the poll
	biden_percentage, biden_exists := poll.PollResults[dem_nominee_name]
	trump_percentage, trump_exists := poll.PollResults[rep_nominee_name]
	if !biden_exists || !trump_exists {
		panic("PollResults of poll filtered to have Biden/Trump doesn't have Biden/Trump")
	}
	biden_share := biden_percentage / 100.0 // will panic if the item is not found, but we've previously filtered for it
	trump_share := trump_percentage / 100.0

	normalized_trump_share := trump_share / (trump_share + biden_share)
	normalized_biden_share := biden_share / (trump_share + biden_share)

	joint_trump_biden_sample_size := (biden_share + trump_share) * float64(poll.SampleSize)
	std_error_poll_mean := math.Sqrt((normalized_trump_share * normalized_biden_share) / joint_trump_biden_sample_size)

	/* Inject additional uncertainty */
	/*
		Possible factors:
			- National drift between now and the election (biggest one)
			- States more uncertain than the national average
			- Idiosyncratic factors
			- Polls not being as good as gallup
			- Increased polarization
		Also note that the polls already have some error already
	*/
	std_additional_uncertainty := 4.0 / 100.0

	if n_republican_win == 0 || n_republican_win == 6 {
		// if solid states for the last 6 elections
		std_additional_uncertainty = std_additional_uncertainty / 3.0

		if pretty_print {
			fmt.Printf("\n\t\tN republican wins: %d", n_republican_win)
			fmt.Printf("\n\t\t=> Reducing additional uncertainty")
		}
	}

	std_error := std_error_poll_mean + std_additional_uncertainty

	// std_error := std_error_poll_mean + 0.065
	p_republican_win := getProbabilityAboveX(0.5, normalized_trump_share, std_error)

	if pretty_print {
		fmt.Printf("\n\t\tStd with std_additional_uncertainty R: %f", 100*std_error)
		fmt.Printf("\n\t\tPoll plus uncertainty says chance of R win: %f", p_republican_win)
	}
	return p_republican_win
}

/* Print state by state data */
func printStates(states []State) {
	for _, state := range states {
		fmt.Printf("\n\nState: %s", state.Name)
		fmt.Printf("\n\tVotes: %d", state.Votes)
		fmt.Printf("\n\tHistory: %s", state.PresidentialElectoralHistory)

		p_baserate_republican_win := 0.0
		for _, party := range state.PresidentialElectoralHistory {
			if party == "R" {
				p_baserate_republican_win++
			}
		}
		fmt.Printf("\n\tHistorical base rate of R win: %f", p_baserate_republican_win/float64(len(state.PresidentialElectoralHistory)))

		// Individual poll
		for _, poll := range state.Polls {
			fmt.Printf("\n\tPoll: %+v", poll)
			_ = getChanceRepublicanWinFromPoll(poll, true)
			_ = getChanceRepublicanWinFromPollPlusUncertainty(poll, state, true)
		}

		// Aggregate poll
		num_biden_votes := 0.0
		num_trump_votes := 0.0
		for _, poll := range state.Polls {
			biden_percentage, biden_exists := poll.PollResults[dem_nominee_name]
			trump_percentage, trump_exists := poll.PollResults[rep_nominee_name]
			if !biden_exists || !trump_exists {
				panic("PollResults of poll filtered to have Biden/Trump doesn't have Biden/Trump")
			}
			num_biden_votes += (biden_percentage / 100.0) * float64(poll.SampleSize)
			num_trump_votes += (trump_percentage / 100.0) * float64(poll.SampleSize)
		}
		aggregate_sample_size := num_biden_votes + num_trump_votes
		if aggregate_sample_size != 0.0 {
			var aggregate_poll = Poll{SampleSize: int(aggregate_sample_size), PollResults: make(map[string]float64)}
			aggregate_poll.PollResults[dem_nominee_name] = 100.0 * num_biden_votes / aggregate_sample_size
			aggregate_poll.PollResults[rep_nominee_name] = 100.0 * num_trump_votes / aggregate_sample_size

			fmt.Printf("\n\tAggregate poll: %+v", aggregate_poll)
			_ = getChanceRepublicanWinFromPoll(aggregate_poll, true)
			_ = getChanceRepublicanWinFromPollPlusUncertainty(aggregate_poll, state, true)
		}
	}
}

/* Sample state by state */
func sampleFromState(state State) VotesForEachParty {
	switch state.Name {
	case "Nebraska":
		/*
			2000: R
			2004: R
			2008: Split, 1 D, 4 R
			2012: R
			2016: R
			2020: Split, 1 D, 4 R
		*/
		p_split := 2.0 / 6.0
		if r.Float64() < p_split {
			return VotesForEachParty{Democrats: 1, Republicans: 4}
		} else {
			return VotesForEachParty{Democrats: 0, Republicans: 5}
		}
	case "Maine":
		/*
			2000: D
			2004: D
			2008: D
			2012: D
			2016: Split: 3 D, 1 R
			2020: Split, 3 D, 1 R
		*/
		p_split := 2.0 / 6.0
		if r.Float64() < p_split {
			return VotesForEachParty{Democrats: 3, Republicans: 1}
		} else {
			return VotesForEachParty{Democrats: 1, Republicans: 0}
		}
	default:
		{
			/* Consider the base rate for the state */
			p_baserate_republican_win := 0.0
			for _, party := range state.PresidentialElectoralHistory {
				if party == "R" {
					p_baserate_republican_win++
				}
			}
			p_baserate_republican_win = p_baserate_republican_win / float64(len(state.PresidentialElectoralHistory))
			p_republican_win := p_baserate_republican_win // if no polls

			/* Consider polls */
			num_biden_votes := 0.0
			num_trump_votes := 0.0
			for _, poll := range state.Polls {
				biden_percentage, biden_exists := poll.PollResults[dem_nominee_name]
				trump_percentage, trump_exists := poll.PollResults[rep_nominee_name]
				if !biden_exists || !trump_exists {
					panic("PollResults of poll filtered to have Biden/Trump doesn't have Biden/Trump")
				}
				num_biden_votes += (biden_percentage / 100.0) * float64(poll.SampleSize)
				num_trump_votes += (trump_percentage / 100.0) * float64(poll.SampleSize)
			}

			aggregate_sample_size := num_biden_votes + num_trump_votes
			if aggregate_sample_size != 0.0 {
				var aggregate_poll = Poll{SampleSize: int(aggregate_sample_size), PollResults: make(map[string]float64)}
				aggregate_poll.PollResults[dem_nominee_name] = 100.0 * num_biden_votes / aggregate_sample_size
				aggregate_poll.PollResults[rep_nominee_name] = 100.0 * num_trump_votes / aggregate_sample_size

				p_republican_win_aggregate_polls := getChanceRepublicanWinFromPollPlusUncertainty(aggregate_poll, state, false)
				// p_republican_win_aggregate_polls = getChanceRepublicanWinFromPoll(aggregate_poll, false)

				weight_polls := 0.75
				p_republican_win = weight_polls*p_republican_win_aggregate_polls + (1.0-weight_polls)*p_baserate_republican_win
				// p_republican_win = p_republican_win_aggregate_polls
			}

			if r.Float64() < p_republican_win {
				return VotesForEachParty{Democrats: 0, Republicans: state.Votes}
			} else {
				return VotesForEachParty{Democrats: state.Votes, Republicans: 0}
			}
		}
	}
}

/* Simulate election */
func simulateElection(states []State) int {
	republican_seats := 0
	for _, state := range states {
		election_sample := sampleFromState(state)
		republican_seats += election_sample.Republicans
	}
	return republican_seats
}

/* Histogram */
func barString(n int) string {
	str := ""
	for i := 0; i < n; i++ {
		str += "█"
	}
	return str
}

func printElectoralCollegeHistogram(samples []int) {
	histogram := [538]int{}
	for _, sample := range samples {
		histogram[sample]++
	}

	max_count := 0
	for _, count := range histogram {
		if count > max_count {
			max_count = count
		}
	}

	cp := 0.0
	for i, count := range histogram {
		bar_length := (count * 100) / max_count // Assuming max_count bar length is 50 characters. 75.
		p := float64(count) / float64(len(samples)) * 100
		cp += p

		if i > 130 && i < 538 {
			fmt.Printf("[ %2d, %4d): %s %.2f%% (%.0f%%)\n", i, i+1, barString(bar_length), p, cp)
		} else if p >= 0.01 {
			fmt.Printf(">0.01 probability outside of domain, you might want to change histogram parameters\n")

		}
	}
}

/* Load data from csvs */
// Glue code
func readStates() ([]State, error) {
	var states map[string]State = make(map[string]State)

	/* Electoral college votes for the 2024 election*/
	votes_file, err := os.Open("data/num-electors/electoral-college-votes.csv")
	// votes_file, err := os.Open("data/electoral-college-votes-2010-census.csv")
	if err != nil {
		return nil, fmt.Errorf("error opening the votes file: %v", err)
	}
	defer votes_file.Close()

	votes_reader := csv.NewReader(votes_file)
	if _, err := votes_reader.Read(); err != nil { // Skip header
		return nil, fmt.Errorf("error reading votes header: %v", err)
	}
	for {
		csv_record, err := votes_reader.Read()
		if err != nil {
			break // EOF or an error
		}
		votes, err := strconv.Atoi(csv_record[1])
		if err != nil {
			continue // Error in converting votes, skip this record
		}
		state := csv_record[0]
		if _, exists := states[state]; !exists {
			states[state] = State{Name: state, Votes: votes, PresidentialElectoralHistory: make(map[string]string)}
		}
	}

	/* Election results */
	var years = []string{"2000", "2004", "2008", "2012", "2016", "2020"}
	for _, year := range years {
		electoral_history_filename := fmt.Sprintf("data/electoral-history/%s.csv", year)
		electoral_history_file, err := os.Open(electoral_history_filename)
		if err != nil {
			return nil, fmt.Errorf("error opening the electoral_history file for %s: %v", year, err)
		}
		electoral_history_reader := csv.NewReader(electoral_history_file)
		if _, err := electoral_history_reader.Read(); err != nil { // Skip header
			return nil, fmt.Errorf("error reading electoral_history header for %s: %v", year, err)
		}
		for {
			record, err := electoral_history_reader.Read()
			if err != nil {
				break // EOF or an error
			}
			state, party := record[0], record[1]
			data, exists := states[state]
			if !exists {
				continue // State not found in votes map, skip
			}
			// Update the party winning in the specific year
			data.PresidentialElectoralHistory[year] = party
			states[state] = data
		}

		electoral_history_file.Close()
	}

	/* Read polls */
	polls_file, err := os.Open("data/polls/president_polls_state.csv") // Make sure to update this path
	if err != nil {
		return nil, fmt.Errorf("error opening the polls file: %v", err)
	}
	defer polls_file.Close()

	// Using a temporary map to group poll results by state and poll ID
	state_polls_map := make(map[string]map[string]Poll)

	polls_reader := csv.NewReader(polls_file)
	_, err = polls_reader.Read() // Skip the header
	if err != nil {
		return nil, fmt.Errorf("error reading polls header: %v", err)
	}

	for {
		record, err := polls_reader.Read()
		if err != nil {
			break // EOF or an error
		}

		poll_id := record[0]
		state_name := record[12]
		end_date := record[14]
		partisan := record[32]
		candidate_name := record[44]

		date_layout := "1/2/06"
		parsed_date, err := time.Parse(date_layout, end_date)
		if err != nil {
			fmt.Println("Error parsing date: ", err)
		}

		sample_size, err := strconv.Atoi(record[22])
		if err != nil {
			continue // If error, skip this record
		}

		percentage, err := strconv.ParseFloat(record[47], 64) // percentage is in the 42nd column
		if err != nil {
			fmt.Printf("Error parsing percentage")
			continue // If error, skip this record
		}

		if _, exists := state_polls_map[state_name]; !exists {
			state_polls_map[state_name] = make(map[string]Poll)
		}

		poll, exists := state_polls_map[state_name][poll_id]
		if !exists {
			poll = Poll{
				PollId:      poll_id,
				SampleSize:  sample_size,
				PollResults: make(map[string]float64),
				Date:        parsed_date,
				Partisan:    partisan,
			}
		}
		poll.PollResults[candidate_name] = percentage
		state_polls_map[state_name][poll_id] = poll
	}

	// Add the aggregated poll data to the respective states
	for state_name, polls := range state_polls_map {

		// Filter polls by recency and by having both Biden and Trump
		var recent_polls []Poll
		for _, poll := range polls {
			if poll.Date.After(time.Now().AddDate(0, 0, -30)) {
				recent_polls = append(recent_polls, poll)
			}
		}
		var recent_biden_trump_polls []Poll
		for _, recent_poll := range recent_polls {
			has_biden := false
			has_trump := false
			for candidate_name, _ := range recent_poll.PollResults {
				if candidate_name == dem_nominee_name {
					has_biden = true
				} else if candidate_name == rep_nominee_name {
					has_trump = true
				}
			}
			if has_biden && has_trump {
				recent_biden_trump_polls = append(recent_biden_trump_polls, recent_poll)
			}
		}

		if state, exists := states[state_name]; exists {
			state.Polls = recent_biden_trump_polls
			states[state_name] = state // Not redundant
		} else {
			// fmt.Printf("Encountered new state: %s\n", state_name)
			/*
				states[state_name] = State{
					Name:  state_name,
					Polls: polls_slice,
				}
			*/
		}
	}

	// Convert statesData map to a slice for returning
	var states_slice []State
	for _, state := range states {
		states_slice = append(states_slice, state)
	}
	return states_slice, nil
}

func main() {
	states, err := readStates()
	if err != nil {
		fmt.Println("Error:", err)
		return
	}

	n_sims := 1_000_000

	printStates(states)
	fmt.Printf("\n\n")

	p_republicans := 0.0
	results := make([]int, n_sims)
	for i := 0; i < n_sims; i++ {
		republican_seats := simulateElection(states)
		results[i] = republican_seats
		if republican_seats >= 270 {
			p_republicans++
		}
	}
	printElectoralCollegeHistogram(results)

	p_republicans = p_republicans / float64(n_sims)
	fmt.Printf("\n%% republicans: %f\n", p_republicans)
}