Reorganise R files and connect with python test code

analysis.R

@@ -1,34 +1,10 @@
-library(XML)
+# Calculate distances (in metres) using the function pointDistance from the 'raster' package.
 library(raster)
 
-shift.vec <- function (vec, shift) {
-  if(length(vec) <= abs(shift)) {
-    rep(NA ,length(vec))
-  }else{
-    if (shift >= 0) {
-      c(rep(NA, shift), vec[1:(length(vec)-shift)]) }
-    else {
-      c(vec[(abs(shift)+1):length(vec)], rep(NA, abs(shift))) } } }
-
-pfile <- htmlTreeParse("Rik_Veenboer_2015-11-10_17-21-59.gpx", useInternalNodes = T)
-
-# Get all elevations, times and coordinates via the respective xpath
-elevations <- as.numeric(xpathSApply(pfile, path = "//trkpt/ele", xmlValue))
-times = xpathSApply(pfile, path = "//trkpt/time", xmlValue)
-coords <- xpathSApply(pfile, path = "//trkpt", xmlAttrs)
-
-# Extract latitude and longitude from the coordinates
-lats <- as.numeric(coords["lat",])
-lons <- as.numeric(coords["lon",])
-# Put everything in a dataframe and get rid of old variables
-geodf <- data.frame(lat = lats, lon = lons, ele = elevations, time = times)
-rm(list=c("elevations", "lats", "lons", "pfile", "times", "coords"))
-head(geodf)
-
 # Shift vectors for lat and lon so that each row also contains the next position.
 geodf$lat.p1 <- shift.vec(geodf$lat, -1)
 geodf$lon.p1 <- shift.vec(geodf$lon, -1)
-# Calculate distances (in metres) using the function pointDistance from the 'raster' package.
+
 # Parameter 'lonlat' has to be TRUE!
 geodf$dist.to.prev <- apply(geodf, 1, FUN = function (row) {
   pointDistance(c(as.numeric(row["lat.p1"]),
@@ -36,12 +12,16 @@ geodf$dist.to.prev <- apply(geodf, 1, FUN = function (row) {
                 c(as.numeric(row["lat"]), as.numeric(row["lon"])),
                 lonlat = T)
 })
+
 # Transform the column 'time' so that R knows how to interpret it.
 geodf$time <- strptime(geodf$time, format = "%Y-%m-%dT%H:%M:%OS")
+
 # Shift the time vector, too.
 geodf$time.p1 <- shift.vec(geodf$time, -1)
+
 # Calculate the number of seconds between two positions.
 geodf$time.diff.to.prev <- as.numeric(difftime(geodf$time.p1, geodf$time))
+
 # Calculate metres per seconds, kilometres per hour and two LOWESS smoothers to get rid of some noise.
 geodf$speed.m.per.sec <- geodf$dist.to.prev / geodf$time.diff.to.prev
 geodf$speed.km.per.h <- geodf$speed.m.per.sec * 3.6
@@ -50,7 +30,6 @@ geodf$speed.km.per.h <- ifelse(geodf$speed.km.per.h > 40, 0, geodf$speed.km.per.
 geodf$lowess.speed <- lowess(geodf$speed.km.per.h, f = 0.01)$y
 geodf$lowess.ele <- lowess(geodf$ele, f = 0.02)$y
 
-
 # Plot elevations and smoother
 plot(geodf$ele, type = "l", bty = "n", xaxt = "n", ylab = "Elevatio", xlab = "", col = "grey40")
 lines(geodf$lowess.ele, col = "red", lwd = 3)

flow.py

@@ -114,8 +114,8 @@ class Flow:
                 for item in contents:
                     self.downloadTraining(item['listItemId'])
 
-    def processTraining(self):
-        proc = subprocess.Popen(['RScript','test.R', 'Rik_Veenboer_2015-04-25_10-14-43'], stdout = subprocess.PIPE, universal_newlines = True)
+    def processTraining(self, session):
+        proc = subprocess.Popen(['RScript','test.R', session], stdout = subprocess.PIPE, universal_newlines = True)
         while True:
           line = proc.stdout.readline()
           if line != '':

stash.R

@@ -0,0 +1,2 @@
+cat("\014")
+setwd(dirname(parent.frame(2)$ofile))

test.R

@@ -1,2 +1,34 @@
-args <- commandArgs(trailingOnly = TRUE)
-print(args)
+library(XML)
+
+args = commandArgs(trailingOnly = TRUE)
+datadir = 'data'
+session = args[1]
+filename = paste(datadir, '/', session, '.gpx', sep = '')
+print(filename)
+
+shift.vec <- function (vec, shift) {
+  if(length(vec) <= abs(shift)) {
+    rep(NA ,length(vec))
+  }else{
+    if (shift >= 0) {
+      c(rep(NA, shift), vec[1:(length(vec)-shift)]) }
+    else {
+      c(vec[(abs(shift)+1):length(vec)], rep(NA, abs(shift))) } } }
+
+pfile <- htmlTreeParse("data/Rik_Veenboer_2015-11-10_17-21-59.gpx", useInternalNodes = T)
+
+# Get all elevations, times and coordinates via the respective xpath
+elevations <- as.numeric(xpathSApply(pfile, path = "//trkpt/ele", xmlValue))
+times = xpathSApply(pfile, path = "//trkpt/time", xmlValue)
+coords <- xpathSApply(pfile, path = "//trkpt", xmlAttrs)
+
+# Extract latitude and longitude from the coordinates
+lats <- as.numeric(coords["lat",])
+lons <- as.numeric(coords["lon",])
+
+# Put everything in a dataframe and get rid of old variables
+geodf <- data.frame(lat = lats, lon = lons, ele = elevations, time = times)
+rm(list=c("elevations", "lats", "lons", "pfile", "times", "coords"))
+
+# Output head of frame
+print(head(geodf))

test.py

@@ -21,7 +21,7 @@ with Flow() as flow:
         # print(start <= test <= end)
         # flow.getEventsInRange(start, end)
         # flow.parseCalenderEvents()
-        flow.processTraining()
+        flow.processTraining('Rik_Veenboer_2015-11-10_17-21-59')
 
 sys.exit()
 

xtest.R

@@ -2,12 +2,15 @@
 #install.packages("plotKML")
 #install.packages("maptools")
 #install.packages("gpsbabel")
-cat("\014")
+
 library(XML)
 
+cat("\014")
+setwd(dirname(parent.frame(2)$ofile))
 
-file = "Rik_Veenboer_2015-11-10_17-21-59.gpx"
-file = "test.gpx"
+
+file = "data/Rik_Veenboer_2015-11-10_17-21-59.gpx"
+#file = "test.gpx"
 
 data = xmlParse(file)
 
@@ -28,3 +31,4 @@ colnames(xx) = c("lat", "lon")
 
 
 xxx=merge(result, xx)
+