remove logging

NAMESPACE

@@ -24,7 +24,5 @@ importFrom(stats,quantile)
 importFrom(stats,time)
 importFrom(utils,head)
 importFrom(utils,read.csv)
-importFrom(utils,setTxtProgressBar)
 importFrom(utils,tail)
 importFrom(utils,timestamp)
-importFrom(utils,txtProgressBar)

R/auxiliary.R

@@ -26,10 +26,3 @@ intervalPriceLevelGaps <-
   function(volume, breaks) intervalSumBreaks(ifelse(volume == 0, 1, 0), 
       breaks)
 
-# logs to console in form of:
-#     calling function => msg
-logger <- function(msg) {
-  caller <- head(sys.call(-1), 1)
-  cat(paste0("    ", caller, " => ", msg, "\n"))
-}
-

R/data.R

@@ -75,17 +75,14 @@ processData <- function(csv.file) {
   zombie.ids <- getZombieIds(events, trades)
   zombies <- events[events$id %in% zombie.ids, ]
   events <- events[!events$id %in% zombie.ids, ]
-  logger(paste("removed", length(zombie.ids), "zombies"))
   created.ids <- events[events$action == "created", ]$id
   duplicate.update.event.ids <- events[events$type != "pacman" & events$action
       == "changed" & events$fill == 0 & events$id %in% created.ids, ]$event.id
   events <- events[!events$event.id %in% duplicate.update.event.ids, ]
-  logger(paste("removed", length(duplicate.update.event.ids), 
+  warning(paste("removed", length(duplicate.update.event.ids),
       "duplicated updates"))
   depth <- priceLevelVolume(events)
-  logger("calculating depth metrics (may take some time...)")
   depth.summary <- depthMetrics(depth)
-  logger("calculating order aggressiveness...")
   events <- orderAggressiveness(events, depth.summary)
   # depth summary data starts 1 minute later to allow for order book population.
   offset <- min(events$timestamp) + 60
@@ -114,7 +111,6 @@ processData <- function(csv.file) {
 ##' }
 ##' @export loadData
 loadData <- function(bin.file, ...) {
-  logger(paste("loading binary from", bin.file))
   readRDS(file=bin.file, ...)
 }
 
@@ -135,6 +131,5 @@ loadData <- function(bin.file, ...) {
 ##' }
 ##' @export saveData
 saveData <- function(lob.data, bin.file, ...) {
-  logger(paste("saving binary to", bin.file))
   saveRDS(lob.data, file=bin.file, ...)
 }

R/depth.R

@@ -60,10 +60,8 @@ priceLevelVolume <- function(events) {
         side=volume.deltas$direction)
   }
 
-  logger("calculating priceLevelVolume from bid event deltas...")
   bids <- events[events$direction == "bid", ]
   depth.bid <- directionalPriceLevelVolume(bids)
-  logger("calculating priceLevelVolume from ask event deltas...")
   asks <- events[events$direction == "ask", ]
   depth.ask <- directionalPriceLevelVolume(asks)
   depth.data <- rbind(depth.bid, depth.ask)
@@ -137,31 +135,24 @@ priceLevelVolume <- function(events) {
 filterDepth <- function(d, from, to) {
 
   # 1. get all active price levels before start of range.  
-  logger(paste("filterDepth between", from, "and", to))
   pre <- d[d$timestamp <= from, ]
-  logger(paste("got", nrow(pre), "previous deltas"))
   pre <- pre[order(pre$price, pre$timestamp), ]
-  logger(paste("ordered", nrow(pre), "previous deltas"))
 
   # last update for each price level <= from. this becomes the starting point 
   # for all updates within the range.
   pre <- pre[!duplicated(pre$price, fromLast=T) & pre$volume > 0, ] 
-  logger(paste("extracted", nrow(pre), "previously updated deltas"))
 
   # clamp range (reset timestamp to from if price level active before start of
   # range.
   if(nrow(pre) > 0) {
     pre$timestamp <- as.POSIXct(sapply(pre$timestamp, function(r) {
       max(from, r)
     }), origin="1970-01-01", tz="UTC") 
-    logger("clamped range.")
   }
 
   # 2. add all volume change within the range.
   mid <- d[d$timestamp > from & d$timestamp < to, ]
-  logger(paste("got", nrow(mid), "in range deltas"))
   range <- rbind(pre, mid)
-  logger(paste("appended range now contains", nrow(range), "deltas"))
 
   # 3. at the end of the range, set all price level volume to 0.
   open.ends <- data.frame(timestamp=to,
@@ -171,8 +162,6 @@ filterDepth <- function(d, from, to) {
   # combine pre, mid and open.ends. ensure it is in order.  
   range <- rbind(range, open.ends)
   range <- range[order(range$price, range$timestamp), ]
-  logger(paste("closed range. depth filtering resulted in", 
-      length(unique(range$price)), "price levels."))
 
   range
 }
@@ -204,7 +193,6 @@ filterDepth <- function(d, from, to) {
 ##' @author phil
 ##' @keywords internal
 depthMetrics <- function(depth, bps=25, bins=20) {
-  pb <- txtProgressBar(1, nrow(depth), 0, style=3)
   pctNames <- function(name) paste0(name, seq(bps, bps*bins, bps), "bps")
   ordered.depth <- depth[order(depth$timestamp), ]
   ordered.depth$price <- as.integer(round(100*ordered.depth$price))
@@ -299,7 +287,6 @@ depthMetrics <- function(depth, bps=25, bins=20) {
         if(i > 1) metrics[i, ] <- metrics[i - 1, ]
       }
     }
-    setTxtProgressBar(pb, i)
   }
 
   # back into $  

R/event-processing.R

@@ -26,14 +26,12 @@ loadEventData <- function(file) {
         deletes[which(duplicated(deletes$id)), ]$id, ]
     duplicate.event.ids <- duplicate.deletes[duplicated(duplicate.deletes$id), 
         ]$event.id
-    logger(paste("removed", length(duplicate.event.ids), 
+    warning(paste("removed", length(duplicate.event.ids), 
         "duplicate order cancellations: ", 
     paste(events[duplicate.event.ids, ]$id, collapse=" ")))
     events[!events$event.id %in% duplicate.event.ids, ]
   }
 
-  logger(paste("loading data from", file))
-
   events <- read.csv(file, header=T, sep=",")
   events$timestamp <- as.POSIXct(events$timestamp/1000, origin="1970-01-01", 
       tz="UTC")
@@ -64,7 +62,6 @@ loadEventData <- function(file) {
   ### fix timestamps: most of the time the event stream is out of order.
   ### the events have been ordered by id, volume, then action. now re-assign 
   ### the timestamps to match this order for each order id.
-  logger("realigning event timestamps...")
   ts.ordered <- unlist(tapply(events$timestamp, events$id, sort), use.names=F)
   events$timestamp <- as.POSIXct(ts.ordered, origin="1970-01-01", tz="UTC")
 

R/matching-engine.R

@@ -32,8 +32,6 @@
 ##' @keywords internal
 eventMatch <- function(events, cut.off.ms=5000) {
   matcher <- function() {
-    logger(paste("matching", nrow(events), "events..."))
-
     res <- integer()
     cols <- c("event.id", "fill", "timestamp")
 

R/ob-analytics.R

@@ -111,7 +111,6 @@
 ##' @importFrom grDevices colorRampPalette
 ##' @importFrom stats aggregate quantile time
 ##' @importFrom utils head read.csv setTxtProgressBar tail timestamp 
-##'             txtProgressBar
 ##' @author Philip Stubbings \email{phil@@parasec.net}
 ##' @references \url{http://parasec.net/transmission/order-book-visualisation}
 NULL

R/order-types.R

@@ -33,15 +33,12 @@ setOrderTypes <- function(events, trades) {
     })
   }
 
-  logger("identifying order types...")
-
   events$type <- "unknown"
   events$type <- factor(events$type, c("unknown", "flashed-limit", 
       "resting-limit", "market-limit", "pacman", "market"))
 
   # pacman orders (this needs to be determined first)
   pac.men <- which(isPacman(events))
-  logger(paste("found", length(pac.men), "pacman orders"))
   if(length(pac.men) > 0)
     events[which(events$id %in% names(pac.men)), ]$type <- "pacman"
 
@@ -67,8 +64,6 @@ setOrderTypes <- function(events, trades) {
   pacman.ids <- unique(events[events$type=="pacman", ]$id)
   maker.ids <- maker.ids[!maker.ids %in% taker.ids]
   maker.ids <- maker.ids[!maker.ids %in% pacman.ids]
-  logger(paste("found", length(flashed.ids), "flashed-limit and", 
-      length(forever.ids)+length(maker.ids), "resting orders"))
   events[events$id %in% flashed.ids, ]$type <- "flashed-limit"
   events[events$id %in% forever.ids | 
          events$id %in% maker.ids, ]$type <- "resting-limit"
@@ -79,17 +74,15 @@ setOrderTypes <- function(events, trades) {
   ml.ids <- taker.ids[taker.ids %in% unique(events[events$event.id %in% 
       trades$maker.event.id, ]$id)]
   ml.ids <- ml.ids[!ml.ids %in% pacman.ids]
-  logger(paste("found", length(ml.ids), "market-limit orders"))
   events[events$id %in% ml.ids, ]$type <- "market-limit"
 
   # market orders: at least 1 taking event, no identified making events.
   mo.ids <- taker.ids[!taker.ids %in% unique(events[events$event.id %in% 
       trades$maker.event.id, ]$id)]
   mo.ids <- mo.ids[!mo.ids %in% pacman.ids]
-  logger(paste("found", length(mo.ids), "market orders"))
   events[events$id %in% mo.ids, ]$type <- "market"  
 
-  logger(paste("could not identify", length(which(events$type=="unknown")), 
+  warning(paste("could not identify", length(which(events$type=="unknown")), 
       "orders"))
 
   events

R/trades.R

@@ -42,8 +42,6 @@
 ##' @keywords internal
 matchTrades <- function(events) {
 
-  logger(paste("inferring trades from", nrow(events), "events..."))
-
   # trades with matching maker/taker.
   # align them by event id.
   matching.bids <- events[events$direction == "bid" & 

R/visualisation.R

@@ -48,7 +48,6 @@ plotTimeSeries <- function(timestamp, series, start.time=min(timestamp),
     end.time=max(timestamp), title="time series", y.label="series") {
 
   stopifnot(length(timestamp) == length(series))
-  logger(paste("plotTimeSeries between", start.time, "and", end.time))
 
   df <- data.frame(ts=timestamp, val=series)
   df <- df[df$ts >= start.time & df$ts <= end.time, ]
@@ -221,7 +220,6 @@ plotPriceLevels <- function(depth, spread=NULL, trades=NULL,
     unchanged.prices <- unchanged.prices[unchanged]
     depth.filtered <- depth.filtered[!depth.filtered$price 
         %in% unchanged.prices, ]
-    logger(paste("removed", length(unchanged.prices), "unchanged depths"))
   }
 
   depth.filtered[depth.filtered$volume==0, ]$volume <- NA
@@ -485,14 +483,12 @@ plotVolumeMap <- function(events,
     events <- events[events$volume >= volume.from | events$volume == 0, ]
   else {
     lim <- quantile(events$volume, 0.0001)
-    logger(paste("lower volume limit =", lim))
     events <- events[events$volume >= lim, ]
   }
   if(!is.null(volume.to))
     events <- events[events$volume <= volume.to, ]
   else {
     lim <- quantile(events$volume, 0.9999)
-    logger(paste("uppper volume limit =", lim))
     events <- events[events$volume <= lim, ]
   }
 
@@ -568,9 +564,6 @@ plotCurrentDepth <- function(order.book,
     bid.quantiles <- with(bids, price[volume >= quantile(volume, 0.99)])
     ask.quantiles <- with(asks, price[volume >= quantile(volume, 0.99)])
 
-    logger(paste("bid quantiles =", paste(bid.quantiles, collapse=", "),
-                 "ask quantiles =", paste(ask.quantiles, collapse=", ")))
-
     p <- p + geom_vline(xintercept=bid.quantiles, colour="#222222")
     p <- p + geom_vline(xintercept=ask.quantiles, colour="#222222")
   }
@@ -630,21 +623,17 @@ plotVolumePercentiles <- function(depth.summary,
   # see: http://stackoverflow.com/questions/9439256
   liquidity <- NULL; percentile <- NULL 
 
-  logger(paste("plot depth percentiles between", start.time, "and", end.time))
-
   bid.names <- paste0("bid.vol", seq(from=25, to=500, by=25), "bps")
   ask.names <- paste0("ask.vol", seq(from=25, to=500, by=25), "bps")
 
   td <- difftime(end.time, start.time, units="secs")
-  logger(paste("time range =", td, "secs"))
   td <- round(as.numeric(td))
 
   # resolution: if(td > 15 minutes, minute ticks, else seconds. 
   frequency <- ifelse(td > 900, "mins", "secs")
   ob.percentiles <- depth.summary[depth.summary$timestamp 
       >= start.time-ifelse(frequency == "mins", 60, 1) & depth.summary$timestamp
       <= end.time, c("timestamp", bid.names, ask.names)]
-  logger(paste("aggregating to", frequency, "intervals"))
 
   # remove duplicates (take last entry) (for zoo to work)
   ob.percentiles <- ob.percentiles[!duplicated(ob.percentiles$timestamp, 
@@ -655,8 +644,6 @@ plotVolumePercentiles <- function(depth.summary,
 
   # intervals truncated to frequency
   intervals <- as.POSIXct(trunc(time(zoo.obj), frequency))
-  logger(paste("aggregation:", min(intervals), ":", max(intervals), "by =", 
-      frequency))
 
   # use zoo to aggregate by intervals. take mean of each interval.
   aggregated <- aggregate(zoo.obj, intervals, mean)
@@ -764,7 +751,6 @@ plotEventsHistogram <- function(events,
     bw=NULL) {
 
   stopifnot(val == "volume" || val == "price")
-  logger(paste("from =", start.time, "to =", end.time))
 
   events <- events[events$timestamp >= start.time
                  & events$timestamp <= end.time, ]