R - difference between sums of consecutive pairs

Question

I have used the diff(x,) function on a data set to find the difference between force for time intervals of 0.0003s. The problem is due to this high sampling frequencies and the measuring inaccuracies of the system this does not yield any meaningful data.

I am wondering if it was possible to find the difference between 100 consecutive numbers. For example "difference = (Fz101+Fz102...Fz200)-(Fz1+Fz2...Fz100)

currently i am dividing by 0.000333 (sampling frequency) since i am trying to find the peak value for (delta Fz)/(delta t.)

(max(diff(lift_S8_Intns40_chainno$Fz)))/0.00033333
[1] 40472.2

Seen a similiar question asked if this helps anyone in helping me. [link to similiar question][1] How to find the difference between sums of consecutive pairs and triplets in R?

Any help is appreciated but my skills are not good in r so please make it as simple as possible.

Data structure

structure(list(Time = c(18.31266667, 18.313, 18.31333333, 18.31366667, 
18.314, 18.31433333, 18.31466667, 18.315, 18.31533333, 18.31566667, 
18.316, 18.31633333, 18.31666667, 18.317, 18.31733333, 18.31766667, 
18.318, 18.31833333, 18.31866667, 18.319, 18.31933333, 18.31966667, 
18.32, 18.32033333, 18.32066667, 18.321, 18.32133333, 18.32166667, 
18.322, 18.32233333, 18.32266667, 18.323, 18.32333333, 18.32366667, 
18.324, 18.32433333, 18.32466667, 18.325, 18.32533333, 18.32566667, 
18.326, 18.32633333, 18.32666667, 18.327, 18.32733333, 18.32766667, 
18.328, 18.32833333, 18.32866667, 18.329, 18.32933333, 18.32966667, 
18.33, 18.33033333, 18.33066667, 18.331, 18.33133333, 18.33166667, 
18.332, 18.33233333, 18.33266667, 18.333, 18.33333333, 18.33366667, 
18.334, 18.33433333, 18.33466667, 18.335, 18.33533333, 18.33566667, 
18.336, 18.33633333, 18.33666667, 18.337, 18.33733333, 18.33766667, 
18.338, 18.33833333, 18.33866667, 18.339, 18.33933333, 18.33966667, 
18.34, 18.34033333, 18.34066667, 18.341, 18.34133333, 18.34166667, 
18.342, 18.34233333, 18.34266667, 18.343, 18.34333333, 18.34366667, 
18.344, 18.34433333, 18.34466667, 18.345, 18.34533333, 18.34566667, 
18.346, 18.34633333, 18.34666667, 18.347, 18.34733333, 18.34766667, 
18.348, 18.34833333, 18.34866667, 18.349, 18.34933333, 18.34966667, 
18.35, 18.35033333, 18.35066667, 18.351, 18.35133333, 18.35166667, 
18.352, 18.35233333, 18.35266667, 18.353, 18.35333333, 18.35366667, 
18.354, 18.35433333, 18.35466667, 18.355, 18.35533333, 18.35566667, 
18.356, 18.35633333, 18.35666667, 18.357, 18.35733333, 18.35766667, 
18.358, 18.35833333, 18.35866667, 18.359, 18.35933333, 18.35966667, 
18.36, 18.36033333, 18.36066667, 18.361, 18.36133333, 18.36166667, 
18.362, 18.36233333, 18.36266667, 18.363, 18.36333333, 18.36366667, 
18.364, 18.36433333, 18.36466667, 18.365, 18.36533333, 18.36566667, 
18.366, 18.36633333, 18.36666667, 18.367, 18.36733333, 18.36766667, 
18.368, 18.36833333, 18.36866667, 18.369, 18.36933333, 18.36966667, 
18.37, 18.37033333, 18.37066667, 18.371, 18.37133333, 18.37166667, 
18.372, 18.37233333, 18.37266667, 18.373, 18.37333333, 18.37366667, 
18.374, 18.37433333, 18.37466667, 18.375, 18.37533333, 18.37566667, 
18.376, 18.37633333, 18.37666667, 18.377, 18.37733333, 18.37766667, 
18.378, 18.37833333, 18.37866667, 18.379), Fz = c(2751.996392, 
2751.614101, 2752.364284, 2751.993635, 2751.615723, 2751.995127, 
2751.989063, 2751.241442, 2749.366648, 2750.486962, 2748.242022, 
2747.498762, 2748.245589, 2747.4998, 2748.254604, 2748.631317, 
2749.006798, 2750.129349, 2749.38176, 2749.385262, 2748.640657, 
2750.13658, 2748.640073, 2749.393888, 2750.145076, 2751.274421, 
2750.157172, 2750.15688, 2750.165279, 2752.407479, 2752.042472, 
2753.550297, 2752.424309, 2750.927558, 2751.688556, 2751.317583, 
2752.819117, 2752.45398, 2752.836757, 2752.472626, 2754.353062, 
2754.725527, 2755.111158, 2754.376021, 2752.882448, 2752.510924, 
2754.006329, 2755.508722, 2756.638796, 2756.636202, 2757.76947, 
2756.284199, 2757.408096, 2758.165381, 2757.418894, 2758.172774, 
2758.178838, 2758.936415, 2758.56421, 2757.448825, 2757.824079, 
2758.569203, 2759.69824, 2760.082914, 2759.711827, 2760.840004, 
2761.215128, 2760.84743, 2760.099193, 2760.851808, 2759.359468, 
2758.25031, 2758.624201, 2759.755281, 2760.511577, 2761.635327, 
2763.137948, 2763.143331, 2761.64191, 2763.1528, 2762.406524, 
2763.525491, 2763.157339, 2762.781356, 2763.909695, 2764.666851, 
2763.919813, 2763.543975, 2763.928017, 2765.045866, 2765.426243, 
2766.182961, 2765.058383, 2763.936351, 2765.06542, 2763.947052, 
2764.699019, 2764.70424, 2763.584867, 2763.22145, 2763.975492, 
2764.349189, 2764.354994, 2763.613307, 2760.9942, 2759.878475, 
2762.486297, 2762.115389, 2763.994527, 2762.121615, 2762.876597, 
2761.391148, 2761.391991, 2761.768055, 2761.769126, 2759.525662, 
2758.406516, 2758.786634, 2758.783261, 2757.669758, 2756.920758, 
2756.540737, 2756.545277, 2756.176055, 2756.171515, 2755.423667, 
2754.67611, 2753.178257, 2752.423923, 2753.16895, 2748.678277, 
2747.927494, 2746.429754, 2746.424955, 2746.797971, 2746.424663, 
2745.674982, 2746.424792, 2743.432215, 2743.432994, 2741.179315, 
2742.67553, 2739.672447, 2738.921647, 2738.173637, 2737.424005, 
2736.294822, 2735.180735, 2734.431882, 2734.425007, 2733.301013, 
2732.930623, 2730.676264, 2729.172881, 2728.424855, 2727.298218, 
2726.930066, 2726.177678, 2724.680797, 2723.5587, 2723.931652, 
2722.428675, 2721.683421, 2720.557108, 2718.311893, 2716.438883, 
2717.549484, 2717.545139, 2718.671354, 2714.548217, 2716.42254, 
2713.060416, 2714.557005, 2714.554119, 2712.681174, 2711.561898, 
2710.437904, 2710.438585, 2709.688272, 2707.067122, 2708.192203, 
2705.564778, 2707.439879, 2705.949079, 2705.573079, 2705.577036, 
2704.828393, 2702.954102, 2702.20199, 2701.079406, 2699.206235, 
2697.708138, 2695.836101, 2696.588814, 2696.968721, 2696.966354, 
2696.970764, 2696.22504, 2694.349549, 2695.852121)), .Names = c("Time", 
"Fz"), row.names = 1299:1498, class = "data.frame")

Could you post some example data to show what your data looks like? See also http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example — TARehman, May 06 '15 at 20:02
@TARehman I have edited my post so it shows some of the data. Yes i that is what i want to do and then find the maximum difference in my data set for these 100 intervals. — Markus Esbjørn Sloth, May 06 '15 at 20:39
You only have 200 observations here, so there is only one interval. You should just provide a mock data of 30 observation and set and interval for, lets say 3. — David Arenburg, May 06 '15 at 20:47
After looking through the data again i think intervals of 20 would actually be alright considering the relative accuracy of the Fz measurements. I don't really have a strong reason for choosing an interval of 100 or 20, just wanting to test if this would create some slightly more realistic values. So the exact interval you chose to work with is not of great importance. — Markus Esbjørn Sloth, May 06 '15 at 21:01
Can you show how would the process be after lets say `(r4+r5+r6) - (r1+r2+r3)` (if the interval is 3)? What will be the next comparison? — David Arenburg, May 06 '15 at 21:13

David Arenburg · Answer 1 · 2015-05-06T22:11:20.717

Here's a possible approach using the zoo package

Function

library(zoo)
IntrvalsDif <- function(x, n) {
  temp <- rollsum(x, n)
  sapply(seq_len(length(x) - n + 1), function(x) temp[x + n] - temp[x])
}

Test

IntrvalsDif(df$Fz, 20)
#   [1]   22.712120   31.780260   37.846728   48.042024   55.623904   59.831923   61.789132   67.470180   73.906584   79.581470
#  [11]   81.889676   83.816224   80.498591   81.303658   85.113723   87.410109   91.579034   93.126436   97.284240   99.556696
#  [21]  101.445531   99.204143   98.458872   96.574869   97.299629  101.391636  108.484213  111.843855  111.830721  108.817601
#  [31]  108.804484  104.667484  103.899693  100.132011   94.484088   91.846433   88.453795   88.053184   85.777665   83.127912
#  [41]   83.855688   84.967116   86.079728   84.951745   81.943294   79.311783   74.809550   70.305436   67.663273   68.031700
#  [51]   68.010152   72.486929   78.453469   83.671546   86.262716   87.723876   86.573048   83.175009   80.529002   79.394259
#  [61]   73.758934   70.745457   66.612867   64.351423   62.484932   55.371569   46.756346   42.618145   38.493014   34.730700
#  [71]   27.612391   18.995970    6.271506   -3.829068  -10.178434  -18.028571  -24.761686  -32.615260  -40.093775  -46.838338
#  [81]  -52.458680  -61.082382  -69.714532  -78.721904  -86.991107  -88.898297  -88.564729  -94.941400 -102.449946 -114.087060
#  [91] -120.115474 -131.764148 -140.435989 -151.731834 -164.906638 -176.581499 -185.261108 -191.700139 -198.144375 -208.693815
# [101] -217.378887 -226.065596 -232.122351 -241.185464 -251.002620 -264.177813 -277.722667 -288.293768 -297.354158 -303.775595
# [111] -313.566873 -314.745817 -316.279034 -317.070287 -318.979261 -322.381222 -328.406668 -334.420050 -342.305322 -345.705694
# [121] -351.343224 -352.849444 -359.231092 -360.347288 -361.457419 -363.321285 -366.306745 -366.670795 -366.308869 -364.077356
# [131] -365.210203 -366.711412 -371.584748 -371.950517 -369.317205 -366.687770 -363.297645 -361.044891 -356.536870 -352.777977
# [141] -349.395261 -347.887047 -344.504089 -340.758605 -337.002095 -329.879165 -319.755890 -313.731643 -310.687084 -311.395920
# [151] -304.987941 -305.325773 -300.807844 -303.409489 -306.756032 -306.724804 -305.584028 -302.559006 -301.033458 -301.379656
# [161] -296.103079          NA          NA          NA          NA          NA          NA          NA          NA          NA
# [171]          NA          NA          NA          NA          NA          NA          NA          NA          NA          NA
# [181]          NA

R - difference between sums of consecutive pairs

1 Answers1