added script to analyse block data

Scripts/extrinsic_script.R

@@ -0,0 +1,99 @@
+library(jsonlite)
+library(doParallel)
+
+t1 <- proc.time()
+t <- system(command = "python3 get_chain_info.py", intern = TRUE)
+t2 <- (proc.time() - t1) #stopping recording time
+cat(paste(round(t2[3], 3), " seconds elapsed.")) #printing elapsed time
+
+
+
+
+
+compute_bytes <- function(x){
+
+  lapply(x$extrinsics_hex, function(x) sum(nchar(x)))
+
+}
+
+extrinsic_number <- function(x){
+
+  lapply(x$extrinsics_hex, function(x) length(x))
+
+}
+
+
+
+
+ncores = 12
+
+blocks <- seq(18987848 - (3600*24)/6, 18987848)
+
+groups <- cut(blocks,breaks = ncores, labels = FALSE)
+
+intervals <- list()
+
+for (i in 1:ncores){
+
+  intervals[[i]] <- blocks[groups == i]
+
+}
+
+
+start_time <- proc.time()
+cl <- doMC::registerDoMC(cores = ncores)
+
+t <- foreach(i = 1:ncores) %dopar% {
+
+  out <- system(paste("python3 test_script_1.py", intervals[[i]][1], intervals[[i]][length(intervals[[i]])]), intern = TRUE)
+
+}
+
+end_time <- (proc.time() - start_time) #stopping recording time
+cat(paste(round(end_time[3], 3), " seconds elapsed.")) #printing elapsed time
+
+t.sum <- lapply(t,FUN = function(x) fromJSON(x))
+
+#unlist(lapply(t.sum, function(x) compute_bytes(x)))
+#unlist(lapply(t.sum, function(x) extrinsic_number(x)))
+
+t.sum <- do.call(rbind,t.sum)
+
+block_limit <- 5240000
+
+block_mb <- block_limit / (1024*1024)
+
+block_avail_mb <- block_limit*0.75 / (1024*1024)
+
+t.sum$usage_mb <- t.sum$extrinsics_size_bytes / (1024*1024) / 2
+
+t.sum$usage_pct <- t.sum$usage_mb / block_avail_mb * 100
+
+p1 <- ggplot(data = t.sum, aes(x = block_number, y = usage_pct)) +
+  geom_line(colour = "black") +
+  ylab("Block Usage (%)") + xlab("Polkadot Relay Chain Block") + scale_y_continuous(breaks=c(1,3,5,10, 20, 30, 60))
+
+p2 <- ggplot(data = t.sum, aes(x = t.sum$block_number, y = t.sum$extrinsics_count)) +
+  geom_line(colour = "black") +
+  ylab("Number of Transactions") + xlab("Polkadot Relay Chain Block") + scale_y_continuous(breaks=c(250, 500, 750, 1000, 1250))
+
+grid.arrange(p1,p2, nrow = 1)
+
+
+block_avail_mb
+
+t.sum[t.sum$usage_mb == max(t.sum$usage_mb),]
+
+t.sum[t.sum$extrinsics_count == max(t.sum$extrinsics_count),]
+
+sum(t.sum$extrinsics_count)
+
+mean(t.sum$extrinsics_count)
+
+mean(t.sum$usage_pct)
+
+(max(t.sum$block_number) - min(t.sum$block_number)) / (3600*24/6)
+
+
+
+