From 2fa525a86c140d8eb295f5812a9549834f092242 Mon Sep 17 00:00:00 2001
From: Rucknium <Rucknium@protonmail.com>
Date: Wed, 18 May 2022 13:23:48 +0000
Subject: [PATCH] Add BCH-Software-Performance

---
 ...N-Fulcrum-Conf-Intervals-and-Power-Calcs.R | 113 ++++++++++++++++++
 1 file changed, 113 insertions(+)
 create mode 100644 BCH-Software-Performance/BCHN-Fulcrum-Conf-Intervals-and-Power-Calcs.R

diff --git a/BCH-Software-Performance/BCHN-Fulcrum-Conf-Intervals-and-Power-Calcs.R b/BCH-Software-Performance/BCHN-Fulcrum-Conf-Intervals-and-Power-Calcs.R
new file mode 100644
index 0000000..b36a6ea
--- /dev/null
+++ b/BCH-Software-Performance/BCHN-Fulcrum-Conf-Intervals-and-Power-Calcs.R
@@ -0,0 +1,113 @@
+
+# Download ODS file from here:
+# https://docs.google.com/spreadsheets/d/1zR5XsKws_bKFFVGbf5FMaw0vcjLwFpUTveBCz4__bJg
+
+# MUST add filepath to downloaded .ods file here:
+P2P.Results.filepath <- ""
+
+# MUST Install these packages below once by un-commenting these lines:
+# install.packages("data.table")
+# install.packages("readODS")
+# install.packages("boot")
+# install.packages("presize")
+# install.packages("knitr")
+
+library(data.table)
+library(readODS)
+library(boot)
+library(presize)
+library(knitr)
+
+
+bchn.9Op <- read_ods(P2P.Results.filepath, sheet = "bchn-90p")
+bchn.9Op.start <- read_ods(P2P.Results.filepath, sheet = "bchn_start-90p")
+bchn.Op <- read_ods(P2P.Results.filepath, sheet = "bchn-0p")
+bchn.Op.start <- read_ods(P2P.Results.filepath, sheet = "bchn-start-0p")
+
+fulcrum.9Op <- read_ods(P2P.Results.filepath, sheet = "fulcrum-90p")
+fulcrum.Op <- read_ods(P2P.Results.filepath, sheet = "fulcrum-0p")
+
+for (i in c("bchn.9Op", "bchn.9Op.start", "bchn.Op", "bchn.Op.start", "fulcrum.9Op", "fulcrum.Op")) {
+  setDT(get(i))
+  setnames(get(i), colnames(get(i)), gsub("[^0-9a-zA-Z]", "", colnames(get(i))) )
+}
+
+block.phases <- data.table(BlockHeight = 0:max(bchn.9Op$BlockHeight), phase = "warmup", stringsAsFactors = FALSE)
+block.phases[BlockHeight %in% 145:244, phase := "empty"]
+block.phases[BlockHeight %in% 245:254, phase := "fan-out"]
+block.phases[BlockHeight %in% 255:259, phase := "steady state 1"]
+block.phases[BlockHeight %in% 260:261, phase := "fan-in"]
+block.phases[BlockHeight %in% 262:266, phase := "steady state 2"]
+
+bchn.9Op <- merge(bchn.9Op, bchn.9Op.start)
+bchn.9Op[, bchn.9Op.elasped.time := as.numeric(as.POSIXlt(CompletedTimestamp) - as.POSIXlt(StartTimestamp))]
+
+bchn.Op <- merge(bchn.Op, bchn.Op.start)
+bchn.Op[, bchn.Op.elasped.time := as.numeric(as.POSIXlt(CompletedTimestamp) - as.POSIXlt(StartTimestamp))]
+
+fulcrum.9Op[, fulcrum.9Op.elasped.time := ProcessingTimemsec]
+fulcrum.Op[, fulcrum.Op.elasped.time := ProcessingTimemsec]
+
+timing.data <- merge(block.phases, bchn.Op[, .(BlockHeight, bchn.Op.elasped.time)])
+timing.data <- merge(timing.data, bchn.9Op[, .(BlockHeight, bchn.9Op.elasped.time)], all.x = TRUE)
+timing.data <- merge(timing.data, fulcrum.Op[, .(BlockHeight, fulcrum.Op.elasped.time)], all.x = TRUE)
+timing.data <- merge(timing.data, fulcrum.9Op[, .(BlockHeight, fulcrum.9Op.elasped.time)], all.x = TRUE)
+
+
+timing.data <- timing.data[ ! phase %in% c("warmup", "empty", "fan-in"), ]
+
+mean.statistic <- function(x, w) {mean(x[w])}
+
+ci.table <- list()
+power.table <- list()
+
+set.seed(314)
+# bootstrapping involves some randomization
+
+for (i in setdiff(names(timing.data), c("BlockHeight", "phase"))) {
+  
+  by.output <- by(unlist(timing.data[, ..i]), timing.data$phase, FUN = function(x) {
+    
+    if ( any(is.na(x))) {
+      return(list(boot.ci = c(NA, NA), prec_mean.10 = NA, prec_mean.25 = NA, prec_mean.50 = NA))
+    }
+    
+    list(
+      boot.ci = round(boot.ci(boot(x, mean.statistic, R = 10000, stype = "i"), conf = 0.90, type = "perc")$percent[4:5]),
+      prec_mean.10 = ceiling(prec_mean(mean(x), sd(x), conf.width = 0.10 * mean(x), conf.level = 0.90)$n),
+      prec_mean.25 = ceiling(prec_mean(mean(x), sd(x), conf.width = 0.25 * mean(x), conf.level = 0.90)$n),
+      prec_mean.50 = ceiling(prec_mean(mean(x), sd(x), conf.width = 0.50 * mean(x), conf.level = 0.90)$n)
+    )
+  })
+  
+  ci.lower <- sapply(by.output, FUN = function(x) {x$boot.ci[1]})
+  ci.upper <- sapply(by.output, FUN = function(x) {x$boot.ci[2]})
+  
+  ci.table[[i]] <- data.table(processing.type = gsub(".elasped.time", "", i), 
+    block.type = names(by.output), ci.lower, ci.upper)
+  
+  prec_mean.10 <- sapply(by.output, FUN = function(x) {x$prec_mean.10})
+  prec_mean.25 <- sapply(by.output, FUN = function(x) {x$prec_mean.25})
+  prec_mean.50 <- sapply(by.output, FUN = function(x) {x$prec_mean.50})
+  
+  power.table[[i]] <- data.table(processing.type = gsub(".elasped.time", "", i), 
+    block.type = names(by.output), prec_mean.10, prec_mean.25, prec_mean.50)
+  
+}
+
+ci.table <- data.table::rbindlist(ci.table)
+power.table <- data.table::rbindlist(power.table)
+
+colnames(ci.table) <- c("Processing Type", "Block Type", 
+  "Lower 90% Confidence Interval", "Upper 90% Confidence Interval")
+colnames(power.table) <- c("Processing Type", "Block Type", 
+  "N for C.I. width < 10% of mean", "25%", "50%")
+
+
+knitr::kable(ci.table, format = "pipe")
+
+knitr::kable(power.table, format = "pipe")
+
+
+
+