Adjust vector subset values according to certain rules

Question

I am trying to code a function that converts Chinese numerals to Arabic. The idea is to get a set of scaled_digit vectors and a set of scale_factor vectors, multiply and add them up to generate the desired output.

digit=c('〇'=0,'一'=1,'二'=2,'三'=3,'四'=4,'五'=5,'六'=6,'七'=7,'八'=8,'九'=9)
scale=c('十'=10^1,'百'=10^2,'千'=10^3,'萬'=10^4,'億'=10^8,'兆'=10^12)

One of the problems I encounter is this:

When I have a number that is a few hundred 10^4s (萬) and a few thousand 10^12s (兆), I am left with a scale-factor vector that is as follows:

scale_factor=
structure(c(1000, 1e+12, 100, 10, 10000, 1000, 100, 10), .Names = c("千", 
"兆", "百", "十", "萬", "千", "百", "十"))

   [千]     兆    [百]    [十]    萬    千    百    十 
  [1e+03] 1e+12 [1e+02] [1e+01] 1e+04 1e+03 1e+02 1e+01

Scale factors to be adjusted have been marked by [ ].

The positions of the cardinal scale_factors can be found with the following code:

cardinal_scale_factor=which(diff(scale_factor)>=0, T)+1

兆 萬 
 2  5

How do I code so that scale_factor[1] and scale_factor[3:4] can be multiplied by scale_factor[2] and [5] respectively?

---

Expected result:

   [千]     兆    [百]    [十]    萬    千    百    十 
  [1e+15] 1e+12 [1e+06] [1e+05] 1e+04 1e+03 1e+02 1e+01 

Answer 1

A possible solution:

w1 <- which(rev(cummax(rev(scale_factor)) > rev(scale_factor)))

grp <- cumsum(c(1,diff(w1)) > 1) + 1

w2 <- aggregate(w1, list(grp), max)[[2]] + 1

scale_factor[w1] <- scale_factor[w1] * scale_factor[w2][grp]

which gives:

> scale_factor
   千    兆    百    十    萬    千    百    十 
1e+15 1e+12 1e+06 1e+05 1e+04 1e+03 1e+02 1e+01

What this does:

1. With cummax(rev(scale_factor)) you get the cummulative maximum of the reversed scale.
2. Comparing that with the reversed scale (cummax(rev(scale_factor)) > rev(scale_factor)) gives a logical vector.
3. Wrapping the logical vector from step 2 in rev and which subsequently, wou get an index vector of positions w1 that do not conform to the decreasing condition.
4. With cumsum(c(1,diff(w1)) > 1) + 1 you can group these positions for case the 3rd and 4th values in the example data.
5. With aggregate(w1, list(grp), function(x) max(x) + 1)[[2]] you determine the positions of the multipliers.
6. Finally, you multiply the values in scale_factor as determined in w1 with the multipliers from w2. You need to index w2 with the group numbers from grp.