mirror of
https://github.com/Rucknium/misc-research.git
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150 lines
5.3 KiB
R
150 lines
5.3 KiB
R
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# MUST install data.table and lubridate packages if not already installed
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library(data.table)
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# Must run misc-research/Monero-p2pool-Output-Stats/p2pool-output-stats.R
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# for blocks 2443120 to 2800470. Then get the file paths of the csv files below
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miner.payouts <- read.csv("miner-payouts-2443120-to-2800470.csv", stringsAsFactors = FALSE)
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blockchain.stats <- read.csv("blockchain-stats-2443120-to-2800470.csv", stringsAsFactors = FALSE)
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setDT(miner.payouts)
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setDT(blockchain.stats)
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miner.payouts[, date := as.Date(as.POSIXct(as.integer(timestamp), origin = "1970-01-01"))]
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p2pool.hashpower <- miner.payouts[, .(p2pool.hashpower.share = mean(is_p2pool)), by = "date"]
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miner.payouts[, week := paste0(lubridate::isoyear(as.Date(as.POSIXct(as.integer(timestamp),
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origin = "1970-01-01"))), "-",
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formatC(lubridate::isoweek(as.Date(as.POSIXct(as.integer(timestamp),
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origin = "1970-01-01"))), width = 2, flag = "0"))]
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blockchain.stats[, week := paste0(lubridate::isoyear(as.Date(Date)), "-",
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formatC(lubridate::isoweek(as.Date(Date)), width = 2, flag = "0"))]
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miner.payouts.week <- miner.payouts[, .(p2pool.outputs = sum(n_outputs[is_p2pool]),
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p2pool.share.mined.blocks = mean(is_p2pool)), by = "week"]
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blockchain.stats.week <- blockchain.stats[, .(OutTotal = sum(OutTotal)), by = "week"]
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data.week <- merge(miner.payouts.week, blockchain.stats.week, by = "week")
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data.week[, p2pool.output.share := p2pool.outputs / OutTotal]
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lubridate::isoweek(as.Date("2023-01-16"))
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data.week <- data.week[week != "2022-03"]
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# Trim week
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png("Monero-p2pool-Output-Stats/analysis/images/p2pool-mined-blocks.png")
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par(mar = c(6, 4, 4, 3) + 0.1)
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plot(data.week$p2pool.share.mined.blocks * 100, type = "l", xaxt = "n",
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main = "Share of Monero blocks mined by P2Pool, by week",
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sub = "ISO Week",
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ylab = "Percentage",
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xlab = NA, ylim = c(0, 10))
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axis(4)
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axis(1, at = seq(4, nrow(data.week), by = 4),
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labels = data.week$week[seq(4, nrow(data.week), by = 4)], las = 2, cex.axis = 0.8)
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legend("bottomright", legend = "Hard fork", lty = 1, col = "#FF6600")
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legend("topleft", legend = "github.com/Rucknium", bty = "n")
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lubridate::isoweek(as.Date("2022-08-15"))
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# Hard fork happened Saturday Aug 13. ISO week starts on Mondays
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abline(v = which(data.week$week == "2022-33"), col = "#FF6600")
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dev.off()
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png("Monero-p2pool-Output-Stats/analysis/images/outputs-total.png")
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par(mar = c(6, 4, 4, 3) + 0.1)
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plot(data.week$OutTotal, type = "l", xaxt = "n", xlab = NA,
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main = "Total number of Monero transaction outputs per week",
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sub = "ISO Week",
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ylab = "Transaction outputs",
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ylim = c(0, max(data.week$OutTotal)))
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axis(4)
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axis(1, at = seq(4, nrow(data.week), by = 4),
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labels = data.week$week[seq(4, nrow(data.week), by = 4)], las = 2, cex.axis = 0.8)
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abline(v = which(data.week$week == "2022-33"), col = "#FF6600")
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legend("bottomright", legend = "Hard fork", lty = 1, col = "#FF6600")
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legend("bottomleft", legend = "github.com/Rucknium", bty = "n")
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dev.off()
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png("Monero-p2pool-Output-Stats/analysis/images/p2pool-outputs-share.png")
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par(mar = c(6, 4, 4, 3) + 0.1)
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plot(data.week$p2pool.output.share * 100, type = "l", xaxt = "n", xlab = NA,
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main = "Share of Monero transaction outputs produced by P2Pool, by week",
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cex.main = 1.1,
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sub = "ISO Week",
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ylab = "Percentage")
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axis(4)
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axis(1, at = seq(4, nrow(data.week), by = 4),
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labels = data.week$week[seq(4, nrow(data.week), by = 4)], las = 2, cex.axis = 0.8)
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abline( v = which(data.week$week == "2022-33"), col = "#FF6600")
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legend("bottomright", legend = "Hard fork", lty = 1, col = "#FF6600")
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legend("topleft", legend = "github.com/Rucknium", bty = "n")
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dev.off()
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ring.size <- ifelse(1:nrow(data.week) < which(data.week$week == "2022-33"), 11, 16)
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png("Monero-p2pool-Output-Stats/analysis/images/median-effective-ring-size.png")
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par(mar = c(6, 4, 4, 3) + 0.1)
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# This is the median for the number of non-p2pool outputs chosen as decoys.
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# Then, one is added to represent the real spend. This gives us effective ring size.
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plot(1 + qbinom(0.5, ring.size - 1, 1 - data.week$p2pool.output.share), type = "l",
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ylim = c(0, 16), xaxt = "n", xlab = NA,
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main = "Median effective ring size due to P2Pool transaction outputs, by week",
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cex.main = 1.1,
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sub = "ISO Week",
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ylab = "Effective ring size")
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axis(4)
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axis(1, at = seq(4, nrow(data.week), by = 4),
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labels = data.week$week[seq(4, nrow(data.week), by = 4)], las = 2, cex.axis = 0.8)
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abline( v = which(data.week$week == "2022-33"), col = "#FF6600")
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legend("bottomright", legend = "Hard fork", lty = 1, col = "#FF6600")
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legend("bottomleft", legend = "github.com/Rucknium", bty = "n")
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dev.off()
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png("Monero-p2pool-Output-Stats/analysis/images/unlucky-5-percent-effective-ring-size.png")
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par(mar = c(6, 4, 4, 3) + 0.1)
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plot(1 + qbinom(0.05, ring.size - 1, 1 - data.week$p2pool.output.share), type = "l",
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ylim = c(0, 16), xaxt = "n", xlab = NA,
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main = "Effective ring size due to P2Pool transaction outputs\nfor the \"unluckiest\" 5 percent of rings, by week",
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cex.main = 1.1,
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sub = "ISO Week",
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ylab = "Effective ring size")
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axis(4)
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axis(1, at = seq(4, nrow(data.week), by = 4),
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labels = data.week$week[seq(4, nrow(data.week), by = 4)], las = 2, cex.axis = 0.8)
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abline( v = which(data.week$week == "2022-33"), col = "#FF6600")
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legend("bottomright", legend = "Hard fork", lty = 1, col = "#FF6600")
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legend("bottomleft", legend = "github.com/Rucknium", bty = "n")
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dev.off()
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