How to loop and use if else on this example with logical expressions using R

Question

I have two lengthy data sets with several columns and different lengths, for this example lets subset to few rows and just 3 columns:

Temp <- c(12.9423 ,12.9446 ,12.9412 ,12.9617 ,12.9742 ,12.9652 ,12.9463, 12.9847 ,12.9778,
        12.9589, 12.9305, 12.9275 ,12.8569 ,12.8531 ,12.9092, 12.9471, 12.9298, 12.9266,
        12.9374 ,12.9385, 12.9505, 12.9510, 12.9632 ,12.9621 ,12.9571, 12.9492 ,12.8988,
        12.8895 ,12.8777, 12.8956, 12.8748 ,12.7850 ,12.7323, 12.7546 ,12.7375 ,12.7020,
        12.7172, 12.7015, 12.6960, 12.6944, 12.6963, 12.6928, 12.6930 ,12.6883 ,12.6913)

Density <- c(26.38635 ,26.38531 ,26.38429, 26.38336, 26.38268 ,26.38242, 26.38265, 26.38343,
           26.38486, 26.38697 ,26.38945, 26.39188, 26.39365, 26.39424 ,26.39376 ,26.39250,
           26.39084 ,26.38912 ,26.38744 ,26.38587, 26.38456 ,26.38367, 26.38341 ,26.38398,
           26.38547 ,26.38793 ,26.39120 ,26.39509, 26.39955 ,26.40455, 26.41002, 26.41578,
           26.42126, 26.42593 ,26.42968, 26.43255 ,26.43463, 26.43603 ,26.43693 ,26.43750,
           26.43787, 26.43815, 26.43841 ,26.43871 ,26.43904)

po4 <-  c(0.4239840 ,0.4351156, 0.4456128, 0.4542392, 0.4608510, 0.4656445, 0.4690847,
        0.4717291, 0.4742391 ,0.4774904 ,0.4831152, 0.4922122, 0.5029904, 0.5128720,
        0.5190209, 0.5191368 ,0.5133212, 0.5027542 ,0.4905301 ,0.4796467 ,0.4708035,
        0.4638879, 0.4578364 ,0.4519745, 0.4481336, 0.4483697, 0.4531310, 0.4622930,
        0.4750474 ,0.4905152 ,0.5082183 ,0.5278212 ,0.5491580 ,0.5720519, 0.5961127,
        0.6207716 ,0.6449603, 0.6675704 ,0.6878331 ,0.7051851,0.7195461, 0.7305200,
        0.7359634 ,0.7343541, 0.7283988)

PP14 <- data.frame(Temp,Density,po4) ##df1

temp <- c(13.13875, 13.13477 ,13.12337 ,13.10662 ,13.09798 ,13.09542 ,13.08734 ,13.07616,
 13.06671 ,13.05899, 13.05890 ,13.05293 ,13.03322, 13.01515, 13.02552 ,13.01668,
12.99829, 12.97075 ,12.95572 ,12.95045 ,12.94541 ,12.94365 ,12.94609 ,12.94256,
12.93565 ,12.93258 ,12.93489 ,12.93209 ,12.92219 ,12.90730 ,12.90416 ,12.89974,
 12.89749 ,12.89626 ,12.89395, 12.89315 ,12.89274, 12.89276 ,12.89293 ,12.89302)

density <- c( 26.35897, 26.36274 ,26.36173 ,26.36401 ,26.36507 ,26.36662 ,26.36838,
26.36996,
  26.37286 ,26.37452 ,26.37402, 26.37571 ,26.37776, 26.38008 ,26.37959 ,26.38178,
26.38642 ,26.39158 ,26.39350, 26.39467, 26.39601, 26.39601, 26.39596 ,26.39517,
26.39728 ,26.39766, 26.39774, 26.39699 ,26.40081 ,26.40328 ,26.40416, 26.40486,
26.40513 ,26.40474 ,26.40552 ,26.40584, 26.40613, 26.40602 ,26.40595 ,26.40498)

krho <- c( -9.999999e+06, -1.786843e+00, -9.142976e-01, -9.650734e-01, -2.532397e+00,
  -3.760537e+00, -2.622484e+00, -1.776506e+00, -2.028391e+00, -2.225910e+00,
  -3.486826e+00, -2.062341e-01, -3.010643e+00, -3.878437e+00, -3.796426e+00,
-3.227138e+00, -3.335446e+00, -3.738037e+00, -4.577778e+00, -3.818099e+00,
-3.891467e+00, -4.585045e+00 ,-3.150283e+00 ,-4.371089e+00 ,-3.902601e+00,
-4.546019e+00, -3.932538e+00, -4.331247e+00, -4.508137e+00, -4.789201e+00,
   -4.383820e+00, -4.423486e+00, -4.334641e+00, -4.330544e+00, -4.838604e+00,
    -4.729123e+00, -4.381797e+00, -4.207365e+00, -4.276804e+00, -4.001305e+00)

MS14 <- data.frame(temp,density,krho) ##df2

So now I would like to loop through both data sets and check if MS14$density=PP14$Density if it is true then I would like to use the column krho in that row to multiply it by delta po4 that corresponds to the same density so diff(po4) in that row or range. something like

#MS14$krho[i] * diff(PP14$po4)[i]

BUT when I run

 PP14$Density == MS14$density 

of course it is always FALSE, because the large decimal numbers, none is exactly the same. I solved that by round the numbers to the 3rd decimal, but it should be a way to include that in the code so density +- 0.005 for example. Well or just rounding it to the 3rd decimal like:

PP14$Density_round2 <- round(PP14$Density ,digit=2) 

In any case I am not sure if I should use a nested loop to check both columns and make the operations accordingly or if it would be better to create a new data.frame with the intersect of each data.frame:

common <- intersect(PP14$Density, MS14$density) 

and then make calculations....(??)

So I would probably need a nested loop like:

{for i:PP14
  for j:MS14
 new-> PP14$Density[i] == MS14$density[j]
#if new is true then PP14$krho[i]* MS14$diff(po4)[j]#[for that particular row]
#and print it into a new data.frame df3
#}

So please, feel free to suggest the best way to proceed.. there might be several ways to do it..

Thank you so much in advance!!

Ps: suggestions using Matlab are also welcome

Answer 1

Something like this?

compareDec <- function(x, y, digits = NULL, tol = .Machine$double.eps^0.5){
  if(is.null(digits)){
    abs(x - y) < tol
  } else {
    round(x, digits = digits) == round(y, digits = digits)
  }
}

icomp <- outer(MS14$density, PP14$Density, compareDec, digits = 2)
m <- outer(MS14$krho, c(0, diff(PP14$po4)))

new <- which(icomp, arr.ind = TRUE)
df3 <- cbind.data.frame(new, Prod = m[new])

head(df3)
#  row col        Prod
#1  17   1  0.00000000
#2  18   1  0.00000000
#3  19   1  0.00000000
#4  20   1  0.00000000
#5  17   2 -0.03712885
#6  18   2 -0.04161033