Functions for evaluating if values
of vectors are within intervals
using a x %()% c(a, b) style notation for comparing
values of x with (a, b) interval to get a < x < b evaluated.
Interval endpoints can be open ((, )) or closed ([, ]).
Values of x are compared to interval endpoints a and b (a <= b).
Endpoints can be defined as a vector with two values (c(a, b)): these values will be compared as a single interval with each value in x.
If endpoints are stored in a matrix-like object or a list,
comparisons are made element-wise. If lengths do not match, shorter objects are recycled. Return values are logicals.
These value-to-interval operators work for numeric (integer, real) and ordered vectors, and object types which are measured at least on ordinal scale (e.g. dates).
The following special operators are used to indicate closed ([, ]) or open ((, )) interval endpoints:
| Operator | Expression | Condition |
|---|---|---|
%[]% |
x %[]% c(a, b) |
x >= a & x <= b |
%[)% |
x %[)% c(a, b) |
x >= a & x < b |
%(]% |
x %(]% c(a, b) |
x > a & x <= b |
%()% |
x %()% c(a, b) |
x > a & x < b |
| Eqal | Not equal | Less than | Greater than |
|---|---|---|---|
%[]% |
%)(% |
%[<]% |
%[>]% |
%[)% |
%)[% |
%[<)% |
%[>)% |
%(]% |
%](% |
%(<]% |
%(>]% |
%()% |
%][% |
%(<)% |
%(>)% |
The overlap of two closed intervals, [a1, b1] and [a2, b2],
is evaluated by the %[o]% operator (a1 <= b1, a2 <= b2).
| Operator | Expression | Condition |
|---|---|---|
%[o]% |
c(a1, b1) %[o]% c(a2, b2) |
`a1 %[]% c(a2, b2) |
%)o(% is used for the negation,
directional evaluation is done via the operators %[<o]% and %[o>]%.
| Eqal | Not equal | Less than | Greater than |
|---|---|---|---|
%[0]% |
%)0(% |
%[<0]% |
%[0>]% |
The previous operators will return NA for unordered factors.
Set overlap can be evaluated by the base %in% operator and its negation
%notin%.
Install development version from GitHub:
library(devtools)
install_github("psolymos/intrval")User visible changes are listed in the NEWS file.
Use the issue tracker to report a problem.
## Annette Dobson (1990) "An Introduction to Generalized Linear Models".
## Page 9: Plant Weight Data.
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2, 10, 20, labels = c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D9 <- lm(weight ~ group)
## compare 95% confidence intervals with 0
(CI.D9 <- confint(lm.D9))
# 2.5 % 97.5 %
# (Intercept) 4.56934 5.4946602
# groupTrt -1.02530 0.2833003
0 %[]% CI.D9
# (Intercept) groupTrt
# FALSE TRUE
lm.D90 <- lm(weight ~ group - 1) # omitting intercept
## compare 95% confidence of the 2 groups to each other
(CI.D90 <- confint(lm.D90))
# 2.5 % 97.5 %
# groupCtl 4.56934 5.49466
# groupTrt 4.19834 5.12366
CI.D90[1,] %[o]% CI.D90[2,]
# 2.5 %
# TRUE
DATE <- as.Date(c("2000-01-01","2000-02-01", "2000-03-31"))
DATE %[<]% as.Date(c("2000-01-151", "2000-03-15"))
# [1] TRUE FALSE FALSE
DATE %[]% as.Date(c("2000-01-151", "2000-03-15"))
# [1] FALSE TRUE FALSE
DATE %[>]% as.Date(c("2000-01-151", "2000-03-15"))
# [1] FALSE FALSE TRUE
## simple case with integers
1:5 %[]% c(2,4)
# [1] FALSE TRUE TRUE TRUE FALSE
1:5 %[)% c(2,4)
# [1] FALSE TRUE TRUE FALSE FALSE
1:5 %(]% c(2,4)
# [1] FALSE FALSE TRUE TRUE FALSE
1:5 %()% c(2,4)
# [1] FALSE FALSE TRUE FALSE FALSE
1:5 %][% c(2,4)
# [1] TRUE TRUE FALSE TRUE TRUE
1:5 %](% c(2,4)
# [1] TRUE TRUE FALSE FALSE TRUE
1:5 %)[% c(2,4)
# [1] TRUE FALSE FALSE TRUE TRUE
1:5 %)(% c(2,4)
# [1] TRUE FALSE FALSE FALSE TRUE
## interval formats
x <- rep(4, 5)
a <- 1:5
b <- 3:7
cbind(x=x, a=a, b=b)
# x a b
# [1,] 4 1 3
# [2,] 4 2 4
# [3,] 4 3 5
# [4,] 4 4 6
# [5,] 4 5 7
x %[]% cbind(a, b) # matrix
# [1] FALSE TRUE TRUE TRUE FALSE
x %[]% data.frame(a=a, b=b) # data.frame
# [1] FALSE TRUE TRUE TRUE FALSE
x %[]% list(a, b) # list
# [1] FALSE TRUE TRUE TRUE FALSE
## numeric
((1:5)+0.5) %[]% (c(2,4)+0.5)
# [1] FALSE TRUE TRUE TRUE FALSE
## character
c('a','b','c','d','e') %[]% c('b','d')
# [1] FALSE TRUE TRUE TRUE FALSE
## ordered
as.ordered(c('a','b','c','d','e')) %[]% c('b','d')
# [1] FALSE TRUE TRUE TRUE FALSE
## factor -- leads to NA with warnings
as.factor(c('a','b','c','d','e')) %[]% c('b','d')
# [1] NA NA NA NA NA
# Warning messages:
# 1: In Ops.factor(x, a) : ‘>=’ not meaningful for factors
# 2: In Ops.factor(x, b) : ‘<=’ not meaningful for factors
## dates
as.Date(1:5,origin='2000-01-01') %[]% as.Date(c(2,4),origin='2000-01-01')
# [1] FALSE TRUE TRUE TRUE FALSE
## testing overlap
cbind(rep(3,5),rep(4,5)) %[o]% cbind(1:5, 2:6)
# [1] FALSE TRUE TRUE TRUE FALSE
cbind(rep(3,5),rep(4,5)) %[<o]% cbind(1:5, 2:6)
# [1] FALSE FALSE FALSE FALSE TRUE
cbind(rep(3,5),rep(4,5)) %[o>]% cbind(1:5, 2:6)
# [1] TRUE FALSE FALSE FALSE FALSE
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