d1<-data.frame(ID=c(1:6),
Locx1=c(100,121,146,194,162,182),
Locx2=c(148,170,184,236,196,190),
Locy1=c(119,173,104,164,188,142),
Locy2=c(168,180,120,210,190,213))
In the above data, Locx1
is the starting point of x and Locx2
is the endpoint of x, Locy1
is the starting point of y and Locy2
is the endpoint of y. I want to find the y values in which the 50% (and more) of the Locy1
and Locy2
is between the Locx1
and Locx2
in R. How can I do that?
For instance, the 1st row fits this example. the starting point of y is (119) between Locx1
and Locx2
and (148-119)/(168-119) is greater than %50.
Thanks
Dividing lengths
of the intersect
s of x
and y
by the full y
lengths.
## helper FUNs
intl <- function(i) length(i[[1]]:i[[2]]) ## interval length
seq1 <- function(i) i[[1]]:i[[2]] ## seq from `:`
res <- lengths(Map(intersect, apply(y, 1, seq1), apply(x, 1, seq1))) / apply(y, 1, intl)
# [1] 0.6000000 0.0000000 0.0000000 0.3617021 1.0000000 0.1250000
res > .5
# [1] TRUE FALSE FALSE FALSE TRUE FALSE
Data:
d1 <- structure(list(ID = 1:6, Locx1 = c(100, 121, 146, 194, 162, 182
), Locy1 = c(119, 173, 104, 164, 188, 142), Locx2 = c(148, 170,
184, 236, 196, 190), Locy2 = c(168, 180, 120, 210, 190, 213)), class = "data.frame", row.names = c(NA,
-6L))
if I get you right
df %>%
filter((pmin(Locy2, Locx2) - pmax(Locy1, Locx1)) / (Locx2 - Locx1) >= 0.5)
ID Locx1 Locx2 Locy1 Locy2
1 1 100 148 119 168
2 6 182 190 142 213
A somewhat more long winded but hopefully also more transparent solution which yields the same result as @jay.sf
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
d1<-data.frame(ID=c(1:6),
Locx1=c(100,121,146,194,162,182),
Locx2=c(148,170,184,236,196,190),
Locy1=c(119,173,104,164,188,142),
Locy2=c(168,180,120,210,190,213))
d2 <- d1 %>% mutate(seqx = purrr::map2(Locx1, Locx2, .f = ~seq(.x, .y, 1)),
seqy = purrr::map2(Locy1, Locy2, .f = ~seq(.x, .y, 1)),
intersection = purrr::map2(seqx, seqy, .f = ~intersect(.x, .y)),
overlap = purrr::map2_dbl(intersection, seqy, .f = ~length(.x)/length(.y)),
my_condition = overlap >= 0.5
)
d2 %>% select(-contains('seq'), -intersection)
#> ID Locx1 Locx2 Locy1 Locy2 overlap my_condition
#> 1 1 100 148 119 168 0.6000000 TRUE
#> 2 2 121 170 173 180 0.0000000 FALSE
#> 3 3 146 184 104 120 0.0000000 FALSE
#> 4 4 194 236 164 210 0.3617021 FALSE
#> 5 5 162 196 188 190 1.0000000 TRUE
#> 6 6 182 190 142 213 0.1250000 FALSE
Created on 2020-09-03 by the reprex package (v0.3.0)
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