NunoSempere/2024-election-modelling
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continue building print state function

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NunoSempere 2024-04-14 14:46:45 -04:00
parent 693538cdca
commit a4c01576cb
1 changed files with 53 additions and 36 deletions
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89
main.go
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@ -163,6 +163,7 @@ func readStates() ([]State, error) {
// 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)) {
@ -218,19 +219,52 @@ func getProbabilityAboveX(x float64, mean float64, std float64) float64 {
return 1 - getNormalCDF(x, mean, std)
}
func getChanceCandidateWinsFromPoll(candidate_p float64, poll_sample_size float64) float64 {
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)
}
/* Sample state by state */
func sampleFromState(state State) VotesForEachParty {
if dev {
func getChanceRepublicanWinFromPoll(poll Poll) float64 {
biden_percentage, biden_exists := poll.PollResults["Biden"]
trump_percentage, trump_exists := poll.PollResults["Trump"]
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)
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)
// fmt.Printf("\n\tPolls: %s", state.Polls)
for _, poll := range state.Polls {
p_republican_win_poll := getChanceRepublicanWinFromPoll(poll)
fmt.Printf("\n\tPoll: %+v", poll)
fmt.Printf("\n\t\tPoll says chance of R win: %f", p_republican_win_poll)
}
}
}
/* Sample state by state */
func sampleFromState(state State) VotesForEachParty {
switch state.Name {
case "Nebraska":
/*
@ -277,48 +311,31 @@ func sampleFromState(state State) VotesForEachParty {
/* Consider polls */
num_biden_votes := 0.0
num_trump_votes := 0.0
for _, recent_biden_trump_poll := range state.Polls {
biden_share := 0.0
trump_share := 0.0
for candidate_name, candidate_percentage := range recent_biden_trump_poll.PollResults {
if candidate_name == "Biden" {
biden_share = candidate_percentage / 100
} else if candidate_name == "Trump" {
trump_share = candidate_percentage / 100
}
}
sample_size := float64(recent_biden_trump_poll.SampleSize)
poll_biden_votes := biden_share * sample_size
poll_trump_votes := trump_share * sample_size
joint_trump_biden_sample_size := poll_biden_votes + poll_trump_votes
normalized_trump_share := trump_share / (trump_share + biden_share)
normalized_biden_share := biden_share / (trump_share + biden_share)
std_poll := math.Sqrt((normalized_trump_share * normalized_biden_share) / joint_trump_biden_sample_size)
for _, poll := range state.Polls {
// p_republican_win_poll = getChanceRepublicanWinFromPoll(poll)
p_trump_more_votes := getProbabilityAboveX(0.5, normalized_trump_share, std_poll)
if dev {
fmt.Printf("\n\tPoll: %+v", recent_biden_trump_poll)
fmt.Printf("\n\t\tPoll says chance of R win: %f", p_trump_more_votes)
biden_percentage, biden_exists := poll.PollResults["Biden"]
trump_percentage, trump_exists := poll.PollResults["Trump"]
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)
}
// Update general tally
num_biden_votes += poll_biden_votes
num_trump_votes += poll_trump_votes
}
total_sample_size := num_biden_votes + num_trump_votes
if total_sample_size != 0.0 {
aggregate_sample_size := num_biden_votes + num_trump_votes
if aggregate_sample_size != 0.0 {
aggregate_trump_share := num_trump_votes / (num_trump_votes + num_biden_votes)
aggregate_biden_share := num_biden_votes / (num_trump_votes + num_biden_votes)
std_all_polls := math.Sqrt((aggregate_trump_share * aggregate_biden_share) / total_sample_size)
p_republican_according_to_polls := getProbabilityAboveX(0.5, aggregate_trump_share, std_all_polls)
std_mean_aggregate_polls := math.Sqrt((aggregate_trump_share * aggregate_biden_share) / aggregate_sample_size)
p_republican_aggregate_polls := getProbabilityAboveX(0.5, aggregate_trump_share, std_mean_aggregate_polls)
if dev {
fmt.Printf("\n\tAggregating all polls naïvely says chance of R win: %f", p_republican_according_to_polls)
fmt.Printf("\n\tAggregating all polls naïvely says chance of R win: %f", p_republican_aggregate_polls)
}
weight_polls := 1.0
p_republican = weight_polls*p_republican_according_to_polls + (1.0-weight_polls)*p_baserate_republican
p_republican = weight_polls*p_republican_aggregate_polls + (1.0-weight_polls)*p_baserate_republican
}