Add historical-p2pool-outputs.R

Monero-p2pool-Output-Stats/analysis/historical-p2pool-outputs.R

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