NAME <- "ses"
source(file.path('_helper', 'init.R'))

# Any tests added here should also be added to the valgrind test file

# - basic ----------------------------------------------------------------------

all.equal(ses(letters[1:10], letters[1:10]), character())
all.equal(ses(letters[1:10], LETTERS[1:10]), "1,10c1,10")
all.equal(ses(letters[1:5], LETTERS[1:10]), "1,5c1,10")
all.equal(ses(letters[1:10], LETTERS[1:5]), "1,10c1,5")
all.equal(ses(letters[2:10], letters[1:7]), c("0a1", "7,9d7"))
all.equal(
  ses(letters[c(1:5, 1:5, 1:5)], c("e", "d", "a", "b", "c")),
  c("1,4d0", "6,8d1", "10d2", "14,15d5")
)
all.equal(
  ses(c("e", "d", "a", "b", "c"), letters[c(1:5, 1:5, 1:5)]),
  c("0a1,4", "1a6,8", "2a10", "5a14,15")
)
# edit distance = 1

# - trigger edit distance 1 branches -------------------------------------------

all.equal(ses("a", c("a", "b")), "1a2")
all.equal(ses(c("a", "b"), "a"), "2d1")
all.equal(ses("c", c("b", "c")), "0a1")
all.equal(ses(c("b", "c"), "c"), "1d0")

all.equal(ses("a", character()), "1d0")
all.equal(ses(character(), "a"), "0a1")
all.equal(ses(character(), character()), character())

## this is from the atomic tests, haven't dug into why they actually trigger
## the desired branches, but it is fairly complex
set.seed(2)
w1 <- sample(
  c(
  "carrot", "cat", "cake", "eat", "rabbit", "holes", "the", "a", "pasta",
  "boom", "noon", "sky", "hat", "blah", "paris", "dog", "snake"
  ), 25, replace=TRUE
)
w4 <- w3 <- w2 <- w1
w2[sample(seq_along(w1), 5)] <- LETTERS[1:5]
w3 <- w1[8:15]
w4 <- c(w1[1:5], toupper(w1[1:5]), w1[6:15], toupper(w1[1:5]))

all.equal(ses(w1, w4), c("5a6,10", "15,21d19", "23,25c21,25"))

# - longer strings -------------------------------------------------------------

# A bigger string

string <- do.call(paste0, expand.grid(LETTERS, LETTERS, LETTERS))

all.equal(
  ses(string, c("hello", string[-c(5, 500, 1000)], "goodbye")),
  c("0a1", "5d5", "500d499", "1000d998", "17576a17575")
)
all.equal(
  ses(c(string[200:500], "hello", string[-(1:400)][-c(5, 500, 1000)]), string),
  c("0a1,199", "207,306d405", "800a900", "1299a1400")
)

# - max diffs ------------------------------------------------------------------

ses(letters[1:10], LETTERS[1:10], max.diffs=5) # "Exceeded `max.diffs`"
all.equal(
  ses(letters[1:10], LETTERS[1:10], max.diffs=5, warn=FALSE),
  "1,10c1,10"
)
all.equal(
  ses(
    letters[1:10],
    c(letters[1], LETTERS[2:5], letters[6:10]), max.diffs=5, warn=FALSE
  ),
  "2,5c2,5"
)
all.equal(
  ses(
    letters[1:10],
    c(letters[1], LETTERS[2:5], letters[6:8], LETTERS[9], letters[10]),
    max.diffs=5, warn=FALSE
  ),
  c("2,5c2,5", "9c9")
)
# - Issue 152 --------------------------------------------------------------

# h/t @hadley, used to error, now warns

all.equal(ses(letters[1:4], letters[1:3]), "4d3")
all.equal(ses(letters[1:3], letters[1:4]), "3a4")
ses(1, 2:9, max.diffs = 8)

# h/t @gadenbui, data is extracted from palmerpenguins@0.1.0::penguins
#
# comparison <- subset(penguins, year == 2007 | flipper_length_mm > 220)
# test <- subset(penguins, year == 2008)
# a <- test$bill_length_mm
# b <- comparison$bill_length_mm

a <- c(39.6, 40.1, 35, 42, 34.5, 41.4, 39, 40.6, 36.5, 37.6, 35.7, 
41.3, 37.6, 41.1, 36.4, 41.6, 35.5, 41.1, 35.9, 41.8, 33.5, 39.7, 
39.6, 45.8, 35.5, 42.8, 40.9, 37.2, 36.2, 42.1, 34.6, 42.9, 36.7, 
35.1, 37.3, 41.3, 36.3, 36.9, 38.3, 38.9, 35.7, 41.1, 34, 39.6, 
36.2, 40.8, 38.1, 40.3, 33.1, 43.2, 49.1, 48.4, 42.6, 44.4, 44, 
48.7, 42.7, 49.6, 45.3, 49.6, 50.5, 43.6, 45.5, 50.5, 44.9, 45.2, 
46.6, 48.5, 45.1, 50.1, 46.5, 45, 43.8, 45.5, 43.2, 50.4, 45.3, 
46.2, 45.7, 54.3, 45.8, 49.8, 46.2, 49.5, 43.5, 50.7, 47.7, 46.4, 
48.2, 46.5, 46.4, 48.6, 47.5, 51.1, 45.2, 45.2, 50.5, 49.5, 46.4, 
52.8, 40.9, 54.2, 42.5, 51, 49.7, 47.5, 47.6, 52, 46.9, 53.5, 
49, 46.2, 50.9, 45.5)
b <- c(39.1, 39.5, 40.3, NA, 36.7, 39.3, 38.9, 39.2, 34.1, 42, 37.8, 
37.8, 41.1, 38.6, 34.6, 36.6, 38.7, 42.5, 34.4, 46, 37.8, 37.7, 
35.9, 38.2, 38.8, 35.3, 40.6, 40.5, 37.9, 40.5, 39.5, 37.2, 39.5, 
40.9, 36.4, 39.2, 38.8, 42.2, 37.6, 39.8, 36.5, 40.8, 36, 44.1, 
37, 39.6, 41.1, 37.5, 36, 42.3, 46.1, 50, 48.7, 50, 47.6, 46.5, 
45.4, 46.7, 43.3, 46.8, 40.9, 49, 45.5, 48.4, 45.8, 49.3, 42, 
49.2, 46.2, 48.7, 50.2, 45.1, 46.5, 46.3, 42.9, 46.1, 44.5, 47.8, 
48.2, 50, 47.3, 42.8, 45.1, 59.6, 49.6, 50.5, 50.5, 50.1, 50.4, 
46.2, 54.3, 49.8, 49.5, 50.7, 46.4, 48.2, 48.6, 45.2, 52.5, 50, 
50.8, 52.1, 52.2, 49.5, 50.8, 46.9, 51.1, 55.9, 49.1, 49.8, 51.5, 
55.1, 48.8, 50.4, 46.5, 50, 51.3, 45.4, 52.7, 45.2, 46.1, 51.3, 
46, 51.3, 46.6, 51.7, 47, 52, 45.9, 50.5, 50.3, 58, 46.4, 49.2, 
42.4, 48.5, 43.2, 50.6, 46.7, 52)

# In <0.3.4: Exceeded buffer for finding fake snake
ses(a[-c(15:38, 50:90)], b[-c(40:85, 100:125)], max.diffs=80)

# In <0.3.4: Faux Snake Process Failed
ses(a[-(18:38)], b[-(50:80)], max.diffs=115)

# - issue 157 ------------------------------------------------------------------

# Arguably could match on 'A' instead of 'X' and be more compact
a <- c('a', 'b', 'c', 'A', 'X', 'Y', 'Z', 'W')
b <- c('X', 'C', 'A', 'U', 1, 2, 3)
ses(a, b, max.diffs=13)

# segfault (but may have beend debugging code)
ses(letters[1:2], LETTERS[1:2], max.diffs = 4)

# snake overrun
ses(c("G", "C", "T", "C", "A", "C", "G", "C"), c("T", "G"), max.diffs=2)

# effect of max.diffs on compactness (waldo logical comparison)
ses(c('A','A','A','A','A'), c('B','A','B','A','B'), max.diffs=0)
ses(c('A','A','A','A','A'), c('B','A','B','A','B'), max.diffs=1)
ses(c('A','A','A','A','A'), c('B','A','B','A','B'), max.diffs=2)

# back snake all matches before faux snake triggered
ses_dat(
  a=c("T", "A", "A", "C", "C", "A"),
  b=c("A", "G", "A", "A"), max.diffs = 0
)

# - errors ---------------------------------------------------------------------

try(ses('a', 'b', max.diffs='hello')) # "must be scalar integer"
try(ses('a', 'b', warn='hello'))      # "must be TRUE or FALSE"

a <- structure(1, class='diffobj_ogewlhgiadfl2')
try(ses(a, 1)) # "could not be coerced")
try(ses(1, a)) # "could not be coerced"

# We want to have a test file that fully covers the C code in order to run
# valgrind with just that one.  We were unable to isolate simple diffs that
# triggered all the code, but we were able to do it with the below in addition
# to the above.

# - Repeat tests for full coverage in SES file ---------------------------------
# From test.diffStr.R
# formula display changed
if(
  R.Version()$major >= 3 && R.Version()$minor >= "3.1" ||
  R.Version()$major >= 4) {
  rdsf1 <- function(x)
    readRDS(file.path("_helper", "objs", "diffStr", sprintf("%s.rds", x)))
  all.equal(
    as.character(
      diffStr(mdl1, mdl2, extra=list(strict.width="wrap"), line.limit=30)
    ),
    rdsf1(500)
  )
}
# from testthat.warnings.R

A3 <- c("a b c", "d e f A B C D", "g h i", "f")
B3 <- c("a b c", "xd e f E Q L S", "g h i", "q")

diffChr(A3, B3, max.diffs=2) # warn: "Exceeded diff"

# - ses_dat --------------------------------------------------------------------

a <- b <- do.call(paste0, expand.grid(LETTERS, LETTERS))
set.seed(2)
b <- b[-sample(length(b), 100)]
a <- a[-sample(length(b), 100)]

dat <- ses_dat(a, b)
all.equal(dat[['val']][dat[['op']] != 'Delete'], b)
all.equal(dat[['val']][dat[['op']] != 'Insert'], a)
all.equal(a[dat[['id.a']][!is.na(dat[['id.a']])]], a)

dat2 <- ses_dat(a, b, extra=FALSE)
all.equal(dat[1:2], dat2)
all.equal(length(dat2), 2L)

try(ses_dat(a, b, extra=NA)) # 'TRUE or FALSE'

# - encoding agnostic #144 -----------------------------------------------------

# h/t @hadley, these are different in string cache, but should compare equal
# as per ?identical
x <- c("fa\xE7ile", "fa\ue7ile")
Encoding(x) <- c("latin1", "UTF-8")
y <- rev(x)
all.equal(diffobj::ses(x, y), character())