Merge pull request #6 from jhmigueles/issue4_nonIntegerSF

Issue4 non integer sf

.github/workflows/r.yml

@@ -110,4 +110,4 @@ jobs:
         uses: actions/upload-artifact@main
         with:
           name: ${{ runner.os }}-r${{ matrix.config.r }}-results
-          path: check
+          path: check

DESCRIPTION

@@ -8,10 +8,11 @@ Description: A tool to obtain activity counts, originally a translation of the
   'python' package 'agcounts' <https://github.com/actigraph/agcounts>. This tool
   allows the processing of data from any accelerometer brand, with a more flexible 
   approach to handle different sampling frequencies.
+URL: https://github.com/jhmigueles/actilifecounts
 Encoding: UTF-8
 LazyData: true
 Depends: R (>= 2.10)
-Imports: gsignal, pracma
+Imports: gsignal, pracma, GGIRread
 RoxygenNote: 7.2.1
 License: LGPL (>= 3)
 Suggests: 

NAMESPACE

@@ -6,6 +6,7 @@ export(resample_10hz)
 export(resample_30hz)
 export(sum_counts)
 export(trim_data)
+importFrom(GGIRread,resample)
 importFrom(gsignal,filter)
 importFrom(gsignal,filter_zi)
 importFrom(pracma,Lcm)

R/resample_30hz.R

@@ -7,6 +7,7 @@
 #'
 #' @return resampled_data
 #' @importFrom pracma Lcm
+#' @importFrom GGIRread resample
 #' @author Jairo Hidalgo Migueles
 #' @references Ali Neishabouri et al. DOI: https://doi.org/10.21203/rs.3.rs-1370418/v1
 #' @export
@@ -17,44 +18,52 @@ resample_30hz = function(raw = c(), sf = 30, verbose = FALSE) {
 
   # make sure it is a matrix
   raw = as.matrix(raw)
-
-  # define factors using the least common multiple so that any sf can be converted.
-  upsample_factor = pracma::Lcm(sf, 30) / sf
-  downsample_factor = pracma::Lcm(sf, 30) / 30
-
-  # upsample by factor
-  n = nrow(raw); m = ncol(raw)
-  upsample_data = matrix(rep(0, upsample_factor*n*m), ncol = m)
-  fill_i = seq(1, nrow(upsample_data), by = upsample_factor)
-  upsample_data[fill_i, ] = raw
-
-  # other variables
-  a_fp = pi / (pi + 2 * upsample_factor)
-  b_fp = (pi - 2 * upsample_factor) / (pi + 2 * upsample_factor)
-  up_factor_fp = upsample_factor
-
-  # Allocate memory and then LPF.  LPF is only done at non
-  # integer multiples of 30 Hz. This LPF is garbage and does a
-  # poor job of attenuating higher frequencies that need to be
-  # rejected. This is the reason why there is aliasing which
-  # causes the "tail" on the epochs.
-  if (sf %% 30 != 0) {
-    upsample_data_roll = upsample_data[c(nrow(upsample_data), 1:(nrow(upsample_data) - 1)),]
-    upsample_data = (a_fp * up_factor_fp) * (upsample_data + upsample_data_roll)
-    for (i in 2:nrow(upsample_data)) upsample_data[i,] = upsample_data[i,] - b_fp * upsample_data[i - 1,]
+
+  if (sf %% 1 == 0) { # sf is integer
+    # define factors using the least common multiple so that any sf can be converted.
+    upsample_factor = pracma::Lcm(sf, 30) / sf
+    downsample_factor = pracma::Lcm(sf, 30) / 30
+
+    # upsample by factor
+    n = nrow(raw); m = ncol(raw)
+    upsample_data = matrix(rep(0, upsample_factor*n*m), ncol = m)
+    fill_i = seq(1, nrow(upsample_data), by = upsample_factor)
+    upsample_data[fill_i, ] = raw
+
+    # other variables
+    a_fp = pi / (pi + 2 * upsample_factor)
+    b_fp = (pi - 2 * upsample_factor) / (pi + 2 * upsample_factor)
+    up_factor_fp = upsample_factor
+
+    # Allocate memory and then LPF.  LPF is only done at non
+    # integer multiples of 30 Hz. This LPF is garbage and does a
+    # poor job of attenuating higher frequencies that need to be
+    # rejected. This is the reason why there is aliasing which
+    # causes the "tail" on the epochs.
+    if (sf %% 30 != 0) {
+      upsample_data_roll = upsample_data[c(nrow(upsample_data), 1:(nrow(upsample_data) - 1)),]
+      upsample_data = (a_fp * up_factor_fp) * (upsample_data + upsample_data_roll)
+      for (i in 2:nrow(upsample_data)) upsample_data[i,] = upsample_data[i,] - b_fp * upsample_data[i - 1,]
+    }
+    if (sf == 30) downsample_data = raw
+    if (sf != 30) downsample_data = upsample_data[seq(1, nrow(upsample_data), by = downsample_factor),]
+
+    if (verbose) cat(" Done!\n")
+    downsample_data = matrix(round(downsample_data, 3), ncol = m)
+    colnames(downsample_data) = colnames(raw)
+  } else { # sf is not integer
+    downsample_data = GGIRread::resample(raw = raw, 
+                                         rawTime = 1:nrow(raw), 
+                                         time = 1:(nrow(raw)/sf*30), 
+                                         stop = nrow(raw), 
+                                         type = 1)
+    colnames(downsample_data) = colnames(raw)
   }
-  if (sf == 30) downsample_data = raw
-  if (sf != 30) downsample_data = upsample_data[seq(1, nrow(upsample_data), by = downsample_factor),]
-
-  if (verbose) cat(" Done!\n")
-  downsample_data = matrix(round(downsample_data, 3), ncol = m)
-  colnames(downsample_data) = colnames(raw)
-
+
   # free memory
-  rm(raw, upsample_data)
-  if (exists("upsample_data_roll")) rm(upsample_data_roll)
+  rm(list = setdiff(ls(), c("downsample_data")))
   gc()
-
+  
   # return
   return(downsample_data)
 }