don't resample more temperature than will be used

GGIRread::resample is very expensive, and we were resampling *all* of the temperature every time we needed to read a block of it.

This edit makes g.readaccfile for movisens got 2x faster.

R/g.readaccfile.R

@@ -247,6 +247,7 @@ g.readaccfile = function(filename, blocksize, blocknumber, filequality,
     # there may or may not be a temp.bin file containing temperature
     try(expr = {P$data$temperature = g.readtemp_movisens(filename,
                                                          from = startpage, to = endpage,
+                                                         acc_sf = sf, acc_length = nrow(P$data),
                                                          interpolationType = params_rawdata[["interpolationType"]])
     }, silent = TRUE)
   } else if (mon == MONITOR$ACTIGRAPH && dformat == FORMAT$GT3X) {

R/g.readtemp_movisens.R

@@ -1,22 +1,33 @@
-g.readtemp_movisens = function(datafile, from = c(), to = c(), interpolationType=1) {
+g.readtemp_movisens = function(datafile, from = c(), to = c(), acc_sf, acc_length, interpolationType=1) {
     # Acceleration data and temperature were sampled at different rates,
     # so we need to resample temperature to get the same sampling rate
     # as what we have for acceleration.
 
-    temperature = unisensR::readUnisensSignalEntry(dirname(datafile), "temp.bin")
+    temp_sf = 1 # temperature is most likely sampled at 1Hz, but we'll double-check later
+
+    temp_from = ceiling(from / acc_sf * temp_sf)
+    temp_to = ceiling(to / acc_sf * temp_sf)
+
+    temperature = unisensR::readUnisensSignalEntry(dirname(datafile), "temp.bin", 
+                                                   startIndex = temp_from, endIndex = temp_to)
+    new_temp_sf = attr(temperature, "sampleRate")
+
+    # We had guessed that temperature was sampled at 1Hz. Let's check, and if we were wrong, then re-do.
+    if (temp_sf != new_temp_sf) {
+        temp_from = ceiling(from / acc_sf * new_temp_sf)
+        temp_to = ceiling(to / acc_sf * new_temp_sf)
+
+        temperature = unisensR::readUnisensSignalEntry(dirname(datafile), "temp.bin", 
+                                                       startIndex = temp_from, endIndex = temp_to)
+    }
+
     temperature = temperature$temp
 
     # we don't care about the exact timestamp values because we'll throw the timestamps away anyway.
     rawTime = seq_len(length(temperature))
-
-    acc_length = unisensR::getUnisensSignalSampleCount(dirname(datafile), "acc.bin")
     timeRes = seq(from = 1, to = rawTime[length(rawTime)], length.out = acc_length)
 
     temperature = GGIRread::resample(as.matrix(temperature), rawTime, timeRes, length(temperature), type=interpolationType)
 
-    if(length(from) > 0 && length(to) > 0) {
-       temperature = temperature[from:to]
-    }
-
     invisible(temperature)
 }

man/g.readtemp_movisens.Rd

@@ -8,7 +8,8 @@ Reads the temperature from movisens files.
   it to the matrix where accelerations are stored
 }
 \usage{
-g.readtemp_movisens(datafile, from = c(), to = c(), interpolationType=1)
+g.readtemp_movisens(datafile, from = c(), to = c(), acc_sf, acc_length,
+                    interpolationType=1)
 }
 \arguments{
   \item{datafile}{
@@ -24,6 +25,12 @@ g.readtemp_movisens(datafile, from = c(), to = c(), interpolationType=1)
     End point to derive the temperature from movisens files (automatically 
     calculated by GGIR)
   }
+  \item{acc_sf}{
+    Sample frequency of acceleration data
+  }
+  \item{acc_length}{
+    number of acceleration data samples
+  }
   \item{interpolationType}{
     Integer to indicate type of interpolation to be used when resampling time series (mainly relevant for Axivity sensors), 1=linear, 2=nearest neighbour.
   }
@@ -34,6 +41,6 @@ g.readtemp_movisens(datafile, from = c(), to = c(), interpolationType=1)
 \keyword{internal}
 \examples{
 \dontrun{
-  P = g.readtemp_movisens(datafile, from = c(), to = c())
+  P = g.readtemp_movisens(datafile, from = c(), to = c(), acc_sf = 64, acc_length = 3000)
 }
 }