CODEWITHSUNDEEP
rexceldplyr
NColl
NColl

Reputation: 757

Change from acceleration (m/s^2) to velocity (m/s), replicating excel formula

I have a dataset which contains an acceleration and a time column. Within excel I can use these to create a velocity metric. However, I can't seem to replicate the formula in R as one step involves adding a cell to the previous cell in the data.

Within excel the formula is H5 = H4+(G5*(B5-B4)) which is calculating a difference in time between readings(B5-B4), multiplying the result by acceleration (G5*(B5-B4)) then adding the results to the starting velocity value which is always zero.

The first two steps are fine but I haven't found how to replicate the third

data %>%
  mutate(
    Time_diff = Time - lag(Time),
    Accel_Time = Accel*Time_diff
  )

Here is the dataset with expected velocity column also, I've skipped ahead slightly in the data here as the first 100 or so rows have a zero velocity reading. 

  > dput(head(data1, 20))
structure(list(Time = c(1.002, 1.004, 1.006, 1.008, 1.01, 1.012, 
          1.014, 1.016, 1.018, 1.02, 1.022, 1.024, 1.026, 1.028, 1.03, 
          1.032, 1.034, 1.036, 1.038, 1.04), Accel = c(-0.04, -0.04, -0.05, 
          -0.05, -0.04, -0.04, -0.05, -0.05, -0.05, -0.05, -0.05, -0.06, 
          -0.06, -0.06, -0.06, -0.06, -0.06, -0.06, -0.07, -0.06),          
          Velocity = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), 
          Time_diff = c(NA, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 
          0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002), 
          Accel_Time = c(NA, -0.0000800000000000001, -0.0001, -0.0001, 
          -0.0000800000000000001, -0.0000800000000000001, -0.0001, -0.0001, 
          -0.0001, -0.0001, -0.0001, -0.00012, -0.00012, -0.00012, -0.00012, -0.00012, -0.00012, -0.00012, -0.00014, -0.00012)), 
          row.names = c(NA, 20L), class = "data.frame")

Any advice on this would be appreciated, thanks

Upvotes: 0

Views: 1215

Answers (1)

Spätzle
Spätzle

Reputation: 747

constructing the example data frame:

data1 <- data.frame(Time = c(1.002, 1.004, 1.006, 1.008, 1.01, 1.012, 1.014, 1.016, 1.018, 1.02, 1.022, 1.024, 1.026, 1.028, 1.03, 1.032, 1.034, 1.036, 1.038, 1.04), Accel = c(-0.04, -0.04, -0.05, -0.05, -0.04, -0.04, -0.05, -0.05, -0.05, -0.05, -0.05, -0.06, -0.06, -0.06, -0.06, -0.06, -0.06, -0.06, -0.07, -0.06))

  1. computing the time lag - using 0 in the beginning and then simply subtracting 1st from 2nd, 2nd from 3rd and so on:

data1$Time_diff <- c(0,data1$Time[-1] - data1$Time[-length(data1$Time)])

  1. computing accel_time:

data1$accel_time <- data1$Time_diff * data1$Accel

  1. getting the cummulative sum of velocity:

data1$velocity <- cumsum(data1$accel_time)

one liner: cumsum(c(0,data1$Time[-1] - data1$Time[-length(data1$Time)]) * data1$Accel)

Upvotes: 3

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