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513 lines
16 KiB
513 lines
16 KiB
package main
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import (
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"encoding/csv"
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"fmt"
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"math"
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rand "math/rand/v2"
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"os"
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"strconv"
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"time"
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// "strings"
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)
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/* Structs */
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type State struct {
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Name string
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Votes int
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PresidentialElectoralHistory map[string]string
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Polls []Poll
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}
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type VotesForEachParty struct {
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Democrats int
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Republicans int
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}
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type Poll struct {
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PollId string
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SampleSize int
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PollResults map[string]float64
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Date time.Time
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Partisan string
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}
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/* Globals */
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var r = rand.New(rand.NewPCG(uint64(100), uint64(2224)))
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var dem_nominee_name = "Biden"
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var rep_nominee_name = "Trump"
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/* Sampling helper functions */
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func getNormalCDF(x float64, mean float64, std float64) float64 {
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erf_term := (x - mean) / (std * math.Sqrt2)
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return (1 + math.Erf(erf_term)) / 2
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}
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func getProbabilityAboveX(x float64, mean float64, std float64) float64 {
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return 1 - getNormalCDF(x, mean, std)
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}
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func getChanceCandidateWinsFromPollShare(candidate_p float64, poll_sample_size float64) float64 {
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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
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return getProbabilityAboveX(0.5, candidate_p, std)
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}
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func getChanceRepublicanWinFromPoll(poll Poll, pretty_print bool) float64 {
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biden_percentage, biden_exists := poll.PollResults[dem_nominee_name]
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trump_percentage, trump_exists := poll.PollResults[rep_nominee_name]
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if !biden_exists || !trump_exists {
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panic("PollResults of poll filtered to have Biden/Trump doesn't have Biden/Trump")
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}
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biden_share := biden_percentage / 100.0 // will panic if the item is not found, but we've previously filtered for it
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trump_share := trump_percentage / 100.0
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normalized_trump_share := trump_share / (trump_share + biden_share)
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normalized_biden_share := biden_share / (trump_share + biden_share)
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joint_trump_biden_sample_size := (biden_share + trump_share) * float64(poll.SampleSize)
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std_error_poll_mean := math.Sqrt((normalized_trump_share * normalized_biden_share) / joint_trump_biden_sample_size)
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p_republican_win := getProbabilityAboveX(0.5, normalized_trump_share, std_error_poll_mean)
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if pretty_print {
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fmt.Printf("\n\t\tSample size: %f", joint_trump_biden_sample_size)
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fmt.Printf("\n\t\tMean R: %f", 100.0*normalized_trump_share)
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fmt.Printf("\n\t\tStd of mean R: %f", 100*std_error_poll_mean)
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fmt.Printf("\n\t\tPoll says chance of R win: %f", p_republican_win)
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}
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return p_republican_win
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}
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func getChanceRepublicanWinFromPollPlusUncertainty(poll Poll, state State, pretty_print bool) float64 {
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// Uncertainty from the state
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n_republican_win := 0
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for _, party := range state.PresidentialElectoralHistory {
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if party == "R" {
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n_republican_win++
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}
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}
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// Get the uncertainty from the poll
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biden_percentage, biden_exists := poll.PollResults[dem_nominee_name]
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trump_percentage, trump_exists := poll.PollResults[rep_nominee_name]
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if !biden_exists || !trump_exists {
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panic("PollResults of poll filtered to have Biden/Trump doesn't have Biden/Trump")
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}
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biden_share := biden_percentage / 100.0 // will panic if the item is not found, but we've previously filtered for it
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trump_share := trump_percentage / 100.0
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normalized_trump_share := trump_share / (trump_share + biden_share)
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normalized_biden_share := biden_share / (trump_share + biden_share)
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joint_trump_biden_sample_size := (biden_share + trump_share) * float64(poll.SampleSize)
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std_error_poll_mean := math.Sqrt((normalized_trump_share * normalized_biden_share) / joint_trump_biden_sample_size)
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/* Inject additional uncertainty */
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/*
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Possible factors:
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- National drift between now and the election (biggest one)
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- States more uncertain than the national average
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- Idiosyncratic factors
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- Polls not being as good as gallup
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- Increased polarization
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Also note that the polls already have some error already
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*/
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std_additional_uncertainty := 5.0 / 100.0
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if n_republican_win == 0 || n_republican_win == 6 {
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// if solid states for the last 6 elections
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std_additional_uncertainty = std_additional_uncertainty / 3.0
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if pretty_print {
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fmt.Printf("\n\t\tN republican wins: %d", n_republican_win)
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fmt.Printf("\n\t\t=> Reducing additional uncertainty")
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}
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}
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std_error := std_error_poll_mean + std_additional_uncertainty
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// std_error := std_error_poll_mean + 0.065
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p_republican_win := getProbabilityAboveX(0.5, normalized_trump_share, std_error)
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if pretty_print {
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fmt.Printf("\n\t\tStd with std_additional_uncertainty R: %f", 100*std_error)
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fmt.Printf("\n\t\tPoll plus uncertainty says chance of R win: %f", p_republican_win)
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}
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return p_republican_win
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}
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/* Print state by state data */
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func printStates(states []State) {
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for _, state := range states {
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fmt.Printf("\n\nState: %s", state.Name)
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fmt.Printf("\n\tVotes: %d", state.Votes)
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fmt.Printf("\n\tHistory: %s", state.PresidentialElectoralHistory)
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p_baserate_republican_win := 0.0
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for _, party := range state.PresidentialElectoralHistory {
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if party == "R" {
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p_baserate_republican_win++
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}
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}
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fmt.Printf("\n\tHistorical base rate of R win: %f", p_baserate_republican_win/float64(len(state.PresidentialElectoralHistory)))
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// Individual poll
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for _, poll := range state.Polls {
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fmt.Printf("\n\tPoll: %+v", poll)
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_ = getChanceRepublicanWinFromPoll(poll, true)
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_ = getChanceRepublicanWinFromPollPlusUncertainty(poll, state, true)
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}
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// Aggregate poll
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num_biden_votes := 0.0
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num_trump_votes := 0.0
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for _, poll := range state.Polls {
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biden_percentage, biden_exists := poll.PollResults[dem_nominee_name]
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trump_percentage, trump_exists := poll.PollResults[rep_nominee_name]
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if !biden_exists || !trump_exists {
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panic("PollResults of poll filtered to have Biden/Trump doesn't have Biden/Trump")
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}
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num_biden_votes += (biden_percentage / 100.0) * float64(poll.SampleSize)
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num_trump_votes += (trump_percentage / 100.0) * float64(poll.SampleSize)
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}
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aggregate_sample_size := num_biden_votes + num_trump_votes
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if aggregate_sample_size != 0.0 {
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var aggregate_poll = Poll{SampleSize: int(aggregate_sample_size), PollResults: make(map[string]float64)}
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aggregate_poll.PollResults[dem_nominee_name] = 100.0 * num_biden_votes / aggregate_sample_size
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aggregate_poll.PollResults[rep_nominee_name] = 100.0 * num_trump_votes / aggregate_sample_size
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fmt.Printf("\n\tAggregate poll: %+v", aggregate_poll)
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_ = getChanceRepublicanWinFromPoll(aggregate_poll, true)
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_ = getChanceRepublicanWinFromPollPlusUncertainty(aggregate_poll, state, true)
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}
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}
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}
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/* Sample state by state */
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func sampleFromState(state State) VotesForEachParty {
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switch state.Name {
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case "Nebraska":
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/*
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2000: R
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2004: R
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2008: Split, 1 D, 4 R
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2012: R
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2016: R
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2020: Split, 1 D, 4 R
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*/
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p_split := 2.0 / 6.0
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if r.Float64() < p_split {
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return VotesForEachParty{Democrats: 1, Republicans: 4}
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} else {
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return VotesForEachParty{Democrats: 0, Republicans: 5}
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}
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case "Maine":
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/*
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2000: D
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2004: D
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2008: D
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2012: D
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2016: Split: 3 D, 1 R
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2020: Split, 3 D, 1 R
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*/
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p_split := 2.0 / 6.0
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if r.Float64() < p_split {
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return VotesForEachParty{Democrats: 3, Republicans: 1}
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} else {
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return VotesForEachParty{Democrats: 1, Republicans: 0}
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}
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default:
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{
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/* Consider the base rate for the state */
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p_baserate_republican_win := 0.0
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for _, party := range state.PresidentialElectoralHistory {
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if party == "R" {
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p_baserate_republican_win++
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}
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}
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p_baserate_republican_win = p_baserate_republican_win / float64(len(state.PresidentialElectoralHistory))
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p_republican_win := p_baserate_republican_win // if no polls
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/* Consider polls */
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num_biden_votes := 0.0
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num_trump_votes := 0.0
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for _, poll := range state.Polls {
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biden_percentage, biden_exists := poll.PollResults[dem_nominee_name]
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trump_percentage, trump_exists := poll.PollResults[rep_nominee_name]
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if !biden_exists || !trump_exists {
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panic("PollResults of poll filtered to have Biden/Trump doesn't have Biden/Trump")
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}
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num_biden_votes += (biden_percentage / 100.0) * float64(poll.SampleSize)
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num_trump_votes += (trump_percentage / 100.0) * float64(poll.SampleSize)
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}
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aggregate_sample_size := num_biden_votes + num_trump_votes
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if aggregate_sample_size != 0.0 {
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var aggregate_poll = Poll{SampleSize: int(aggregate_sample_size), PollResults: make(map[string]float64)}
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aggregate_poll.PollResults[dem_nominee_name] = 100.0 * num_biden_votes / aggregate_sample_size
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aggregate_poll.PollResults[rep_nominee_name] = 100.0 * num_trump_votes / aggregate_sample_size
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p_republican_win_aggregate_polls := getChanceRepublicanWinFromPollPlusUncertainty(aggregate_poll, state, false)
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// p_republican_win_aggregate_polls = getChanceRepublicanWinFromPoll(aggregate_poll, false)
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// weight_polls := 0.75
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// p_republican = weight_polls*p_republican_win_aggregate_polls + (1.0-weight_polls)*p_baserate_republican_win
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p_republican_win = p_republican_win_aggregate_polls
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}
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if r.Float64() < p_republican_win {
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return VotesForEachParty{Democrats: 0, Republicans: state.Votes}
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} else {
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return VotesForEachParty{Democrats: state.Votes, Republicans: 0}
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}
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}
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}
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}
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/* Simulate election */
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func simulateElection(states []State) int {
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republican_seats := 0
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for _, state := range states {
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election_sample := sampleFromState(state)
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republican_seats += election_sample.Republicans
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}
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return republican_seats
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}
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/* Histogram */
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func barString(n int) string {
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str := ""
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for i := 0; i < n; i++ {
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str += "█"
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}
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return str
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}
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func printElectoralCollegeHistogram(samples []int) {
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histogram := [538]int{}
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for _, sample := range samples {
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histogram[sample]++
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}
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max_count := 0
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for _, count := range histogram {
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if count > max_count {
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max_count = count
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}
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}
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cp := 0.0
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for i, count := range histogram {
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bar_length := (count * 75) / max_count // Assuming max_count bar length is 50 characters
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p := float64(count) / float64(len(samples)) * 100
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cp += p
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if i > 130 && i < 400 {
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fmt.Printf("[ %2d, %4d): %s %.2f%% (%.0f%%)\n", i, i+1, barString(bar_length), p, cp)
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} else if p >= 0.01 {
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fmt.Printf(">0.01 probability outside of domain, you might want to change histogram parameters\n")
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}
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}
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}
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/* Load data from csvs */
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// Glue code
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func readStates() ([]State, error) {
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var states map[string]State = make(map[string]State)
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/* Electoral college votes for the 2024 election*/
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votes_file, err := os.Open("data/num-electors/electoral-college-votes.csv")
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// votes_file, err := os.Open("data/electoral-college-votes-2010-census.csv")
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if err != nil {
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return nil, fmt.Errorf("error opening the votes file: %v", err)
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}
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defer votes_file.Close()
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votes_reader := csv.NewReader(votes_file)
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if _, err := votes_reader.Read(); err != nil { // Skip header
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return nil, fmt.Errorf("error reading votes header: %v", err)
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}
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for {
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csv_record, err := votes_reader.Read()
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if err != nil {
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break // EOF or an error
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}
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votes, err := strconv.Atoi(csv_record[1])
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if err != nil {
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continue // Error in converting votes, skip this record
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}
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state := csv_record[0]
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if _, exists := states[state]; !exists {
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states[state] = State{Name: state, Votes: votes, PresidentialElectoralHistory: make(map[string]string)}
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}
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}
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/* Election results */
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var years = []string{"2000", "2004", "2008", "2012", "2016", "2020"}
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for _, year := range years {
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electoral_history_filename := fmt.Sprintf("data/electoral-history/%s.csv", year)
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electoral_history_file, err := os.Open(electoral_history_filename)
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if err != nil {
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return nil, fmt.Errorf("error opening the electoral_history file for %s: %v", year, err)
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}
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electoral_history_reader := csv.NewReader(electoral_history_file)
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if _, err := electoral_history_reader.Read(); err != nil { // Skip header
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return nil, fmt.Errorf("error reading electoral_history header for %s: %v", year, err)
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}
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for {
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record, err := electoral_history_reader.Read()
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if err != nil {
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break // EOF or an error
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}
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state, party := record[0], record[1]
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data, exists := states[state]
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if !exists {
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continue // State not found in votes map, skip
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}
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// Update the party winning in the specific year
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data.PresidentialElectoralHistory[year] = party
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states[state] = data
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}
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electoral_history_file.Close()
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}
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/* Read polls */
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polls_file, err := os.Open("data/polls/president_polls_state.csv") // Make sure to update this path
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if err != nil {
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return nil, fmt.Errorf("error opening the polls file: %v", err)
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}
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defer polls_file.Close()
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// Using a temporary map to group poll results by state and poll ID
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state_polls_map := make(map[string]map[string]Poll)
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polls_reader := csv.NewReader(polls_file)
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_, err = polls_reader.Read() // Skip the header
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if err != nil {
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return nil, fmt.Errorf("error reading polls header: %v", err)
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}
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for {
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record, err := polls_reader.Read()
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if err != nil {
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break // EOF or an error
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}
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poll_id := record[0]
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state_name := record[12]
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end_date := record[14]
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partisan := record[32]
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candidate_name := record[44]
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date_layout := "1/2/06"
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parsed_date, err := time.Parse(date_layout, end_date)
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if err != nil {
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fmt.Println("Error parsing date: ", err)
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}
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sample_size, err := strconv.Atoi(record[22])
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if err != nil {
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continue // If error, skip this record
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}
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percentage, err := strconv.ParseFloat(record[47], 64) // percentage is in the 42nd column
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if err != nil {
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fmt.Printf("Error parsing percentage")
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continue // If error, skip this record
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}
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if _, exists := state_polls_map[state_name]; !exists {
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state_polls_map[state_name] = make(map[string]Poll)
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}
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poll, exists := state_polls_map[state_name][poll_id]
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if !exists {
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poll = Poll{
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PollId: poll_id,
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SampleSize: sample_size,
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PollResults: make(map[string]float64),
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Date: parsed_date,
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Partisan: partisan,
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}
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}
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poll.PollResults[candidate_name] = percentage
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state_polls_map[state_name][poll_id] = poll
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}
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// Add the aggregated poll data to the respective states
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for state_name, polls := range state_polls_map {
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// Filter polls by recency and by having both Biden and Trump
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var recent_polls []Poll
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for _, poll := range polls {
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if poll.Date.After(time.Now().AddDate(0, 0, -30)) {
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recent_polls = append(recent_polls, poll)
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}
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}
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var recent_biden_trump_polls []Poll
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for _, recent_poll := range recent_polls {
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has_biden := false
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has_trump := false
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for candidate_name, _ := range recent_poll.PollResults {
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if candidate_name == dem_nominee_name {
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has_biden = true
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} else if candidate_name == rep_nominee_name {
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has_trump = true
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}
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}
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if has_biden && has_trump {
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recent_biden_trump_polls = append(recent_biden_trump_polls, recent_poll)
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}
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}
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if state, exists := states[state_name]; exists {
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state.Polls = recent_biden_trump_polls
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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 := 100_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)
|
|
}
|