mirror of
https://github.com/Rucknium/misc-research.git
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284 lines
13 KiB
R
284 lines
13 KiB
R
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library(data.table)
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library(ggplot2)
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library(scales)
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library(Cairo)
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# NOTE: Also need lubridate package installed, but not loading it due to
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# it masking functions
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bch.data.dir <- ""
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spent.status.by.day <- readRDS(paste0(bch.data.dir, "spent_status_by_day.rds"))
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state.trans.by.day <- readRDS(paste0(bch.data.dir, "state_trans_by_day.rds"))
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sum.value.pre.fork <- sum(spent.status.by.day[1,
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.(value.btc.unspent.bch.unspent, value.btc.spent.bch.unspent,
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value.btc.unspent.bch.spent, value.btc.spent.bch.spent)])
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sum.outputs.pre.fork <- sum(spent.status.by.day[1,
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.(outputs.btc.unspent.bch.unspent, outputs.btc.spent.bch.unspent,
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outputs.btc.unspent.bch.spent, outputs.btc.spent.bch.spent)])
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current.status <- spent.status.by.day[block_time.date == "2022-03-31", ]
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current.status[,
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.(value.btc.unspent.bch.unspent, value.btc.spent.bch.unspent,
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value.btc.unspent.bch.spent, value.btc.spent.bch.spent)]
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100 * current.status[,
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.(value.btc.unspent.bch.unspent, value.btc.spent.bch.unspent,
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value.btc.unspent.bch.spent, value.btc.spent.bch.spent)] / sum.value.pre.fork
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current.status[,
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.(outputs.btc.unspent.bch.unspent, outputs.btc.spent.bch.unspent,
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outputs.btc.unspent.bch.spent, outputs.btc.spent.bch.spent)]
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100 * current.status[,
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.(outputs.btc.unspent.bch.unspent, outputs.btc.spent.bch.unspent,
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outputs.btc.unspent.bch.spent, outputs.btc.spent.bch.spent)] / sum.outputs.pre.fork
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spent.status.by.day.value.reshaped <- melt(spent.status.by.day[,
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.(block_time.date, value.btc.unspent.bch.unspent, value.btc.spent.bch.unspent,
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value.btc.unspent.bch.spent, value.btc.spent.bch.spent)], id.vars = c("block_time.date"),
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measure.vars = c("value.btc.unspent.bch.unspent", "value.btc.spent.bch.unspent",
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"value.btc.unspent.bch.spent", "value.btc.spent.bch.spent"))
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spent.status.by.day.value.reshaped[, block_time.date := as.POSIXct(block_time.date)]
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spent.status.by.day.value.reshaped[, variable :=
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factor(variable, levels = c("value.btc.unspent.bch.unspent", "value.btc.unspent.bch.spent",
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"value.btc.spent.bch.unspent", "value.btc.spent.bch.spent"))]
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spent.status.by.day.outputs.reshaped <- melt(spent.status.by.day[,
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.(block_time.date, outputs.btc.unspent.bch.unspent, outputs.btc.spent.bch.unspent,
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outputs.btc.unspent.bch.spent, outputs.btc.spent.bch.spent)], id.vars = c("block_time.date"),
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measure.vars = c("outputs.btc.unspent.bch.unspent", "outputs.btc.spent.bch.unspent",
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"outputs.btc.unspent.bch.spent", "outputs.btc.spent.bch.spent"))
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spent.status.by.day.outputs.reshaped[, block_time.date := as.POSIXct(block_time.date)]
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spent.status.by.day.outputs.reshaped[, variable :=
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factor(variable, levels = c("outputs.btc.unspent.bch.unspent", "outputs.btc.spent.bch.unspent",
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"outputs.btc.unspent.bch.spent", "outputs.btc.spent.bch.spent"))]
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state.trans.by.day.value.reshaped <- melt(state.trans.by.day[,
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.(block_time.date, value.ff.to.tf, value.ff.to.ft, value.ff.to.tt,
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value.tf.to.tt, value.ft.to.tt)], id.vars = c("block_time.date"),
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measure.vars = c("value.ff.to.tf", "value.ff.to.ft", "value.ff.to.tt",
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"value.tf.to.tt", "value.ft.to.tt"))
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state.trans.by.day.value.reshaped[, block_time.date := as.POSIXct(block_time.date)]
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state.trans.by.day.value.reshaped[, variable :=
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factor(variable, levels = c("value.ff.to.tf", "value.ff.to.ft", "value.ff.to.tt",
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"value.tf.to.tt", "value.ft.to.tt"))]
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state.trans.by.day.outputs.reshaped <- melt(state.trans.by.day[,
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.(block_time.date, outputs.ff.to.tf, outputs.ff.to.ft, outputs.ff.to.tt,
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outputs.tf.to.tt, outputs.ft.to.tt)], id.vars = c("block_time.date"),
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measure.vars = c("outputs.ff.to.tf", "outputs.ff.to.ft", "outputs.ff.to.tt",
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"outputs.tf.to.tt", "outputs.ft.to.tt"))
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state.trans.by.day.outputs.reshaped[, block_time.date := as.POSIXct(block_time.date)]
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state.trans.by.day.outputs.reshaped[, variable :=
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factor(variable, levels = c("outputs.ff.to.tf", "outputs.ff.to.ft", "outputs.ff.to.tt",
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"outputs.tf.to.tt", "outputs.ft.to.tt"))]
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date.breaks <- seq.POSIXt(min(spent.status.by.day.value.reshaped$block_time.date),
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max(spent.status.by.day.value.reshaped$block_time.date), by = "month")
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c_trans <- function(a, b, breaks = b$breaks, format = b$format) {
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a <- scales::as.trans(a)
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b <- scales::as.trans(b)
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name <- paste(a$name, b$name, sep = "-")
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trans <- function(x) a$trans(b$trans(x))
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inv <- function(x) b$inverse(a$inverse(x))
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trans_new(name, trans, inverse = inv, breaks = breaks, format=format)
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}
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# Thanks to https://stackoverflow.com/questions/59542697/reverse-datetime-posixct-data-axis-in-ggplot-version-3
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rev_date <- c_trans("reverse", "time")
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# #FF9900 BTC color
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# https://gist.github.com/paladini/ef383fce1b782d919898
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# #0AC18E BCH color
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# https://bitcoincashstandards.org/
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png(paste0(bch.data.dir, "preliminary-pre-fork-BTC-BCH-spent-status-by-value.png"), width = 800, height = 2000)
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print(
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ggplot(spent.status.by.day.value.reshaped, aes(x = block_time.date, y = value, fill = variable)) +
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ggtitle("Spent status of Pre-fork BTC and BCH by Bitcoin Value") +
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geom_area(alpha = 0.6 , size = 0, colour = "black") + coord_flip() +
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scale_x_continuous(trans = rev_date, breaks = date.breaks, labels = date_format("%b-%Y"), expand = c(0, 0)) +
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scale_y_continuous(breaks = sum.value.pre.fork * seq(0, 1, by = 0.1),
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labels = scales::percent_format(scale = 100 * 1/sum.value.pre.fork, accuracy = 1), expand = c(0, 0)) +
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scale_fill_manual(
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labels = c("BTC & BCH spent", "BTC spent & BCH unspent", "BTC unspent & BCH spent", "BTC & BCH unspent"),
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values = c("purple", "#FF9900", "#0AC18E", "darkgrey"),
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breaks = c("value.btc.spent.bch.spent", "value.btc.spent.bch.unspent",
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"value.btc.unspent.bch.spent", "value.btc.unspent.bch.unspent")) +
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ylab("Percentage of Pre-fork Bitcoin Value") +
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theme(legend.position = "top", axis.title.y = element_blank(),
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plot.title = element_text(size = 27),
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axis.text = element_text(size = 20), axis.title.x = element_text(size = 20),
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legend.title = element_blank(), legend.text = element_text(size = 14)) +
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geom_vline(xintercept = as.POSIXct("2017-11-12"), linetype = 3) +
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geom_text(aes(x = as.POSIXct("2017-11-12"), label = "Max BCH/BTC Exchange Rate",
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y = 0.75 * sum.value.pre.fork), colour = "black", size = 6, check_overlap = TRUE) +
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geom_vline(xintercept = as.POSIXct("2017-12-20"), linetype = 3) +
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geom_text(aes(x = as.POSIXct("2017-12-20"), label = "Max BCH/USD Exchange Rate",
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y = 0.75 * sum.value.pre.fork), colour = "black", size = 6, check_overlap = TRUE) +
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geom_vline(xintercept = as.POSIXct("2018-11-15"), linetype = 3) +
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geom_text(aes(x = as.POSIXct("2018-11-15"), label = "BSV Hard Fork",
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y = 0.25 * sum.value.pre.fork), colour = "black", size = 6, check_overlap = TRUE) +
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geom_vline(xintercept = as.POSIXct("2020-11-15"), linetype = 3) +
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geom_text(aes(x = as.POSIXct("2020-11-15"), label = "BCHABC Hard Fork",
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y = 0.25 * sum.value.pre.fork), colour = "black", size = 6, check_overlap = TRUE) +
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geom_text(aes(x = as.POSIXct("2022-03-15"), label = "github.com/Rucknium",
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y = 0.87 * sum.value.pre.fork), colour = "black", size = 6, check_overlap = TRUE)
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)
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# https://en.wikipedia.org/wiki/List_of_bitcoin_forks
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# expand = c(0, 0) due to:
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# https://stackoverflow.com/questions/48611719/remove-inner-padding-in-ggplot
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dev.off()
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png(paste0(bch.data.dir, "preliminary-pre-fork-BTC-BCH-spent-status-by-outputs.png"), width = 800, height = 2000)
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print(
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ggplot(spent.status.by.day.outputs.reshaped, aes(x = block_time.date, y = value, fill = variable)) +
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ggtitle("Spent status of Pre-fork BTC and BCH by Number of Outputs") +
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geom_area(alpha = 0.6 , size = 0, colour = "black") + coord_flip() +
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scale_x_continuous(trans = rev_date, breaks = date.breaks, labels = date_format("%b-%Y"), expand = c(0, 0)) +
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scale_y_continuous(breaks = sum.outputs.pre.fork * seq(0, 1, by = 0.1),
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labels = scales::percent_format(scale = 100 * 1/sum.outputs.pre.fork, accuracy = 1), expand = c(0, 0)) +
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scale_fill_manual(
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labels = c("BTC & BCH spent", "BTC spent & BCH unspent", "BTC unspent & BCH spent", "BTC & BCH unspent"),
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values = c("purple", "#FF9900", "#0AC18E", "darkgrey"),
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breaks = c("outputs.btc.spent.bch.spent", "outputs.btc.spent.bch.unspent",
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"outputs.btc.unspent.bch.spent", "outputs.btc.unspent.bch.unspent")) +
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ylab("Percentage of Pre-fork Outputs") +
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theme(legend.position = "top", axis.title.y = element_blank(),
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plot.title = element_text(size = 26),
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axis.text = element_text(size = 20), axis.title.x = element_text(size = 20),
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legend.title = element_blank(), legend.text = element_text(size = 14)) +
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geom_vline(xintercept = as.POSIXct("2017-11-12"), linetype = 3) +
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geom_text(aes(x = as.POSIXct("2017-11-12"), label = "Max BCH/BTC Exchange Rate",
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y = 0.75 * sum.outputs.pre.fork), colour = "black", size = 6, check_overlap = TRUE) +
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geom_vline(xintercept = as.POSIXct("2017-12-20"), linetype = 3) +
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geom_text(aes(x = as.POSIXct("2017-12-20"), label = "Max BCH/USD Exchange Rate",
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y = 0.75 * sum.outputs.pre.fork), colour = "black", size = 6, check_overlap = TRUE) +
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geom_vline(xintercept = as.POSIXct("2018-11-15"), linetype = 3) +
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geom_text(aes(x = as.POSIXct("2018-11-15"), label = "BSV Hard Fork",
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y = 0.10 * sum.outputs.pre.fork), colour = "black", size = 6, check_overlap = TRUE) +
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geom_vline(xintercept = as.POSIXct("2020-11-15"), linetype = 3) +
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geom_text(aes(x = as.POSIXct("2020-11-15"), label = "BCHABC Hard Fork",
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y = 0.15 * sum.outputs.pre.fork), colour = "black", size = 6, check_overlap = TRUE) +
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geom_text(aes(x = as.POSIXct("2022-03-15"), label = "github.com/Rucknium",
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y = 0.87 * sum.outputs.pre.fork), colour = "black", size = 6, check_overlap = TRUE)
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)
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dev.off()
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ann_text.value <- data.frame(
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block_time.date = as.POSIXct("2022-03-15"),
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value = 300000,
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variable = factor("value.ft.to.tt", levels = levels(state.trans.by.day.value.reshaped$variable)))
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# Due to
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# https://stackoverflow.com/questions/11889625/annotating-text-on-individual-facet-in-ggplot2
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png(paste0(bch.data.dir, "preliminary-pre-fork-BTC-BCH-trans-matrix-by-value.png"), width = 800, height = 2000)
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print(
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ggplot(state.trans.by.day.value.reshaped, aes(x = block_time.date, y = value, fill = variable)) +
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ggtitle("State Transition of Pre-fork BTC and BCH by Bitcoin Value\nKEY: {BTC Spent}{BCH Spent} to {BTC Spent}{BCH Spent}") +
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geom_line(aes(color = variable)) + coord_flip() +
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scale_x_continuous(trans = rev_date, labels = date_format("%b-%Y"), expand = c(0, 0),
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breaks = date.breaks) +
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scale_y_continuous(labels = scales::comma) +
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facet_grid(. ~ variable, labeller = labeller(variable =
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c(value.ff.to.tf = "FF to TF", value.ff.to.ft = "FF to FT", value.ff.to.tt = "FF to TT",
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value.tf.to.tt = "TF to TT", value.ft.to.tt = "FT to TT" ))) +
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ylab("Quantity of Bitcoin Value Transitioned per Day") +
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theme(legend.position = "none", axis.title.y = element_blank(),
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strip.text.x = element_text(size = 20), plot.title = element_text(size = 24),
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axis.text = element_text(size = 15), axis.title.x = element_text(size = 15),
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axis.text.x = element_text(angle = 270)) +
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geom_vline(xintercept = as.POSIXct("2017-11-12"), linetype = 3) +
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geom_vline(xintercept = as.POSIXct("2017-12-20"), linetype = 3) +
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geom_vline(xintercept = as.POSIXct("2018-11-15"), linetype = 3) +
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geom_vline(xintercept = as.POSIXct("2020-11-15"), linetype = 3) +
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geom_text(data = ann_text.value, label = "github.com/Rucknium",
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colour = "black", size = 4.5, check_overlap = TRUE)
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)
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dev.off()
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ann_text.output <- data.frame(
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block_time.date = as.POSIXct("2022-03-15"),
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value = 280000,
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variable = factor("outputs.ft.to.tt", levels = levels(state.trans.by.day.outputs.reshaped$variable)))
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png(paste0(bch.data.dir, "preliminary-pre-fork-BTC-BCH-trans-matrix-by-outputs.png"), width = 800, height = 2000)
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print(
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ggplot(state.trans.by.day.outputs.reshaped, aes(x = block_time.date, y = value, fill = variable)) +
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ggtitle("State Transition of Pre-fork BTC and BCH by Number of Outputs\nKEY: {BTC Spent}{BCH Spent} to {BTC Spent}{BCH Spent}") +
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geom_line(aes(color = variable)) + coord_flip() +
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scale_x_continuous(trans = rev_date, labels = date_format("%b-%Y"), expand = c(0, 0),
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breaks = date.breaks) +
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scale_y_continuous(labels = scales::comma) +
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facet_grid(. ~ variable, labeller = labeller(variable =
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c(outputs.ff.to.tf = "FF to TF", outputs.ff.to.ft = "FF to FT", outputs.ff.to.tt = "FF to TT",
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outputs.tf.to.tt = "TF to TT", outputs.ft.to.tt = "FT to TT" ))) +
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ylab("Number of Transitioned Outputs per Day") +
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theme(legend.position = "none", axis.title.y = element_blank(),
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strip.text.x = element_text(size = 20), plot.title = element_text(size = 24),
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axis.text = element_text(size = 15), axis.title.x = element_text(size = 15),
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axis.text.x = element_text(angle = 270)) +
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geom_vline(xintercept = as.POSIXct("2017-11-12"), linetype = 3) +
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geom_vline(xintercept = as.POSIXct("2017-12-20"), linetype = 3) +
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geom_vline(xintercept = as.POSIXct("2018-11-15"), linetype = 3) +
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geom_vline(xintercept = as.POSIXct("2020-11-15"), linetype = 3) +
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geom_text(data = ann_text.output, label = "github.com/Rucknium",
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colour = "black", size = 4.5, check_overlap = TRUE)
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)
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dev.off()
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