tests/testthat/test-tf_parse.R
In gpilgrim2670/JumpeR: Importing and Working with Track and Field Data
test_that("tf_parse heat sheet - no results", {
skip_on_cran()
file <- "http://tfresultsdata.deltatiming.com/2018-hurricane-invitational/180316F028.htm"
expect_message(out <- file %>%
read_results() %>%
tf_parse(), "No results found in file")
expect_equivalent(out, data.frame())
})
test_that("long jump with prelims/finals on the same page, missing wind and X instead of FOUL", {
skip_on_cran()
file <- "http://tfresultsdata.deltatiming.com/2019-sun-belt-outdoor-championships/190510F029.htm"
df_test <- file %>%
read_results() %>%
tf_parse(
relay_athletes = TRUE,
rounds = TRUE,
round_attempts = TRUE,
split_attempts = TRUE,
splits = TRUE
)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", "15", "1", "2", "3", "4",
"5", "6", "7", "8", "9", "10", "11", "12", "13", "14", NA), Bib_Number = c("73",
"163", "76", "231", "309", "299", "214", "377", "288", "164",
"107", "171", "352", "380", "276", "241", "248", "207", "92",
"87", "351", "200", "186", "194", "262", "360", "333", "190",
"110", "128"), Name = c("Erewele, Osereme", "Lodge, Detrich",
"Givens, Johnaya", "Vaikla, Hanna-Mai", "Cowans, Kaprecia", "Trawick, Brittany",
"Griffin, Elysa", "Matthews, Chante", "Middlebrooks, JaM", "Lynch, Meagan",
"Allen, Bria", "Seymour, Jakeeyah", "Simpson, Payton", "Obikudu, Chineme",
"Gordon, Amber", "Ferdinand, Naomi", "Hilton, Live", "Berge, Emilie",
"Nwofor, Emma", "Mack, Arabriaun", "Scott-Kilgo, Jasm", "Shaw, Alexus",
"Harrison, Ra'Bree", "Moore, Na'ilah", "Smith, Kylah", "Billingsley, Imun",
"Dendy, Micaiah", "Hunt, Jaeda", "Edison, Nicole", "Briggs, Kelsey"
), Age = c("FR", "SR", "FR", "SO", "FR", "FR", "JR", "SO", "JR",
"FR", "FR", "FR", "SR", "SR", "FR", "JR", "FR", "JR", "JR", "JR",
"FR", "SR", "JR", "FR", "SR", "SO", "JR", "FR", "JR", "JR"),
Team = c("Arkansas State", "Georgia Southern", "Arkansas State",
"South Alabama", "UL-Lafayette", "Troy", "South Alabama",
"UT-Arlington", "Troy", "Georgia Southern", "Arkansas-Lit",
"Georgia Southern", "UL-Monroe", "UT-Arlington", "Troy",
"Texas State", "Texas State", "South Alabama", "Arkansas State",
"Arkansas State", "UL-Monroe", "Georgia State", "Georgia State",
"Georgia State", "Texas State", "UT-Arlington", "UL-Monroe",
"Georgia State", "Arkansas-Lit", "Coastal Carolina"), Finals_Result = c("5.85m",
"5.64m", "5.62m", "5.47m", "5.43m", "5.42m", "5.32m", "5.31m",
"5.24m", "5.18m", "5.03m", "4.96m", "4.95m", "4.92m", "4.61m",
"6.11m", "6.06m", "5.92m", "5.88m", "5.88m", "5.86m", "5.71m",
"5.61m", "5.56m", "5.56m", "5.53m", "5.50m", "5.49m", "5.32m",
"FOUL"), Wind_Speed = c("0.6", "+0.0", "1.8", "0.2", "0.3",
"1.6", "1.2", "1.4", "1.2", "1.3", "1.1", "+0.0", "+0.0",
"+0.0", "0.1", "0.6", "+0.0", "1.8", "+0.0", "+0.0", "+0.0",
"+0.0", "+0.0", "+0.0", "+0.0", "0.1", "+0.0", "0.2", "0.2",
NA), DQ = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1), Event = c("Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump"), Round_1 = c("X", "5.41m",
"5.62m", "X", "5.41m", "X", "5.12m", "5.27m", "5.00m", "5.18m",
"5.03m", "X", "4.82m", "4.92m", "X", "5.78m", "5.77m", "5.59m",
"5.70m", "5.59m", "5.53m", "5.53m", "5.30m", "X", "5.24m",
"5.53m", "X", "5.37m", "5.30m", "X"), Round_1_Wind = c(NA,
"0.3", "1.8", NA, "1.9", NA, "+0.0", "0.9", "+0.0", "1.3",
"1.1", NA, "+0.0", "+0.0", NA, "0.1", "+0.0", "+0.0", "+0.0",
"0.8", "+0.0", "-0.6", "+0.0", NA, "+0.0", "0.1", NA, "0.3",
"+0.0", NA), Round_2 = c("5.79m", "5.64m", "5.36m", "X",
"5.42m", "X", "5.32m", "5.31m", "X", "5.13m", "5.00m", "X",
"4.95m", "4.71m", "4.61m", "X", "5.80m", "5.47m", "5.77m",
"5.13m", "5.51m", "5.63m", "5.29m", "5.50m", "5.35m", "5.31m",
"5.50m", "5.32m", "5.15m", "X"), Round_2_Wind = c("0.8",
"+0.0", "0.1", NA, "1.1", NA, "1.2", "1.4", NA, "1.4", "0.7",
NA, "1.2", "+0.0", "0.1", NA, "0.1", "0.9", "0.3", "+0.0",
"+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0",
"+0.0", NA), Round_3 = c("X", "X", "5.56m", "5.47m", "5.43m",
"5.42m", "X", "5.16m", "5.24m", "X", "5.03m", "4.96m", "4.95m",
"4.89m", "X", "5.77m", "6.06m", "X", "X", "5.88m", "5.77m",
"5.71m", "5.61m", "5.56m", "5.56m", "X", "5.47m", "5.49m",
"5.32m", "X"), Round_3_Wind = c(NA, NA, "1.9", "0.2", "0.3",
"1.6", NA, "+0.0", "1.2", NA, "0.8", "+0.0", "+0.0", "+0.0",
NA, "0.3", "+0.0", NA, NA, "+0.0", "+0.0", "+0.0", "+0.0",
"+0.0", "+0.0", NA, "+0.0", "0.2", "0.2", NA), Round_4 = c("5.85m",
"X", "5.38m", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "5.81m", "5.76m", "5.80m", "5.86m", "X", "5.70m", "5.60m",
NA, NA, NA, NA, NA, NA, NA, NA), Round_4_Wind = c("0.6",
NA, "+0.0", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
"0.3", "0.9", "0.9", "0.7", NA, "+0.0", "1.0", NA, NA, NA,
NA, NA, NA, NA, NA), Round_5 = c("X", "5.47m", "X", NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "X", "X", "5.83m",
"5.88m", "5.55m", "X", "5.58m", NA, NA, NA, NA, NA, NA, NA,
NA), Round_5_Wind = c(NA, "+0.0", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, "1.1", "+0.0", "+0.0",
NA, "0.3", NA, NA, NA, NA, NA, NA, NA, NA), Round_6 = c("X",
"X", "5.56m", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "6.11m", "5.72m", "5.92m", "5.87m", "X", "5.86m", "X",
NA, NA, NA, NA, NA, NA, NA, NA), Round_6_Wind = c(NA, NA,
"0.3", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "0.6",
"+0.0", "1.8", "1.4", NA, "+0.0", NA, NA, NA, NA, NA, NA,
NA, NA, NA)), row.names = c(NA, -30L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("triple jump with attempts_split and split_attempts", {
skip_on_cran()
file <- "http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F031.htm"
df_test <- file %>%
read_results() %>%
tf_parse(
relay_athletes = TRUE,
rounds = TRUE,
round_attempts = TRUE,
split_attempts = TRUE,
splits = TRUE
)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19",
"20", NA, NA), Name = c("Raqib, Nisa", "Britt, Kaylah", "Austin, Nikeela",
"Taub, Shannon", "Lewis, Aaliyah", "Phoennik, Courtney", "Seto, Maris",
"McQueeney, Hope", "Holmberg, Gabby", "DeLuca, Maria", "Horrell, Rachel",
"Billone, Caroline", "Streeter, Quintasia", "Adams, Katlyn",
"Ketterman, Stefanie", "Latoza, Kayla", "Hershberger, Faith",
"Collins, Abbey", "Lodge, Emily", "Douglas, Jill", "Wagner, Alexis",
"Swartzbaugh, Lydia"), Age = c("SO", "FR", "SR", "SR", "SO",
"JR", "SR", "FR", "JR", "JR", "SO", "JR", "FR", "SR", "SO", "SO",
"FR", "SO", "FR", "SO", "JR", "SR"), Team = c("Buffalo", "Buffalo",
"Indiana (Pa.)", "Unattached", "California (Pa.)", "John Carroll",
"Duquesne", "Clarion", "Duquesne", "John Carroll", "Indiana (Pa.)",
"Duquesne", "California (Pa.)", "Grove City", "Indiana (Pa.)",
"California (Pa.)", "Indiana (Pa.)", "Grove City", "Clarion",
"Westminster (Pa.)", "California (Pa.)", "Geneva"), Finals_Result = c("12.77m",
"12.02m", "11.79m", "11.39m", "11.17m", "11.15m", "11.12m", "11.09m",
"11.06m", "11.01m", "10.93m", "10.90m", "10.82m", "10.53m", "10.17m",
"10.13m", "10.02m", "9.75m", "9.13m", "8.97m", "FOUL", "FOUL"
), DQ = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 1), Event = c("Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump"), Round_1 = c("12.33m",
"11.02m", "11.46m", "11.39m", "11.04m", "10.89m", "X", "11.09m",
"X", "10.75m", "X", "10.79m", "X", "10.35m", "10.17m", "X", "10.02m",
"9.75m", "9.13m", "8.97m", "X", "X"), Round_2 = c("12.36m", "X",
"11.44m", "-", "11.07m", "11.04m", "X", "10.66m", "11.06m", "ND",
"10.93m", "10.90m", "10.47m", "10.53m", "ND", "10.13m", "ND",
"ND", "ND", "ND", "X", "X"), Round_3 = c("12.38m", "X", "11.26m",
"-", "X", "10.86m", "11.06m", "ND", "X", "11.01m", "10.65m",
"10.81m", "10.82m", "10.43m", "X", "X", "ND", "X", "ND", "ND",
"X", "X"), Round_4 = c("12.13m", "X", "11.72m", "-", "X", "11.13m",
"X", "10.82m", "-", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA), Round_5 = c("12.77m", "12.02m", "11.79m", "-", "11.13m",
"10.76m", "X", "10.71m", "-", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), Round_6 = c("12.27m", "X", "11.77m", "-",
"11.17m", "11.15m", "11.12m", "10.87m", "-", NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA)), row.names = c(NA, -22L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("tf_parse_round_attempts", {
file <-
system.file("extdata",
"Results-IVP-Track-Field-Championship-2019-20-v2.pdf",
package = "JumpeR")
raw_results <- read_results(file)
df <-
tf_parse(
raw_results,
rounds = TRUE,
round_attempts = TRUE,
relay_athletes = TRUE
)
total_O_round_1 <-
sum(df$Round_1_Attempts == "O", na.rm = TRUE) # should be 17
expect_equal(total_O_round_1, 17)
})
test_that("tf_parse mapping hytek", {
skip_on_cran()
links <-
c(
"http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F022.htm",
"http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F036.htm",
"http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F035.htm"
)
df_test <- links %>%
map(read_results) %>%
map(tf_parse) %>%
map(head, 3) %>%
bind_rows()
df_standard <-
structure(list(Place = c("1", "2", "3", "1", "2", "3", "1", "2",
"3"), Team = c("Pittsburgh", "Pittsburgh", "Kent State", "Buffalo",
"Youngstown St.", "Walsh", "Buffalo", "Pittsburgh", "Pittsburgh"
), Finals_Result = c("3:16.26", "3:21.54", "3:21.77", "18.91m",
"17.95m", "17.57m", "17.41m", "16.47m", "16.27m"), DQ = c(0,
0, 0, 0, 0, 0, 0, 0, 0), Event = c("Men 4x400 Meter Relay", "Men 4x400 Meter Relay",
"Men 4x400 Meter Relay", "Men Weight Throw", "Men Weight Throw",
"Men Weight Throw", "Women Weight Throw", "Women Weight Throw",
"Women Weight Throw"), Name = c(NA, NA, NA, "Wray, Samuel", "Gutzky, Ben",
"Ott, Jacob", "Hoyte, Asia", "Mallett, Shannah", "Gyles, Antoinette"
), Age = c(NA, NA, NA, "SR", "SR", "SO", "JR", "FR", "JR")), row.names = c(NA,
-9L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("tf_parse safely mapping hytek", {
skip_on_cran()
links <-
c(
"http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F022.htm",
"http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F036.htm",
"http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F035.htm"
)
df_test <- links %>%
map(read_results) %>%
map(
purrr::safely(tf_parse, otherwise = NA),
relay_athletes = TRUE,
rounds = TRUE,
round_attempts = TRUE,
split_attempts = TRUE,
splits = TRUE
) %>%
SwimmeR::discard_errors() %>%
map(head, 3) %>%
bind_rows()
df_standard <-
structure(list(Place = c("1", "2", "3", "1", "2", "3", "1", "2",
"3"), Team = c("Pittsburgh", "Pittsburgh", "Kent State", "Buffalo",
"Youngstown St.", "Walsh", "Buffalo", "Pittsburgh", "Pittsburgh"
), Finals_Result = c("3:16.26", "3:21.54", "3:21.77", "18.91m",
"17.95m", "17.57m", "17.41m", "16.47m", "16.27m"), DQ = c(0,
0, 0, 0, 0, 0, 0, 0, 0), Event = c("Men 4x400 Meter Relay", "Men 4x400 Meter Relay",
"Men 4x400 Meter Relay", "Men Weight Throw", "Men Weight Throw",
"Men Weight Throw", "Women Weight Throw", "Women Weight Throw",
"Women Weight Throw"), Name = c(NA, NA, NA, "Wray, Samuel", "Gutzky, Ben",
"Ott, Jacob", "Hoyte, Asia", "Mallett, Shannah", "Gyles, Antoinette"
), Age = c(NA, NA, NA, "SR", "SR", "SO", "JR", "FR", "JR"), Round_1 = c(NA,
NA, NA, "17.01m", "ND", "17.57m", "ND", "16.47m", "15.36m"),
Round_2 = c(NA, NA, NA, "18.06m", "17.43m", "ND", "ND", "16.12m",
"16.27m"), Round_3 = c(NA, NA, NA, "ND", "17.59m", "15.98m",
"14.71m", "16.42m", "ND"), Round_4 = c(NA, NA, NA, "18.91m",
"17.39m", "ND", "17.41m", "16.31m", "ND"), Round_5 = c(NA,
NA, NA, "18.33m", "17.68m", "17.29m", "15.01m", "15.17m",
"ND"), Round_6 = c(NA, NA, NA, "18.86m", "17.95m", "ND",
"ND", "15.37m", "15.68m")), row.names = c(NA, -9L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("tf_parse_rounds", {
file <-
system.file("extdata", "underdistance-2020-result.pdf", package = "JumpeR")
raw_results <- read_results(file)
df <-
tf_parse(
raw_results,
rounds = TRUE,
round_attempts = TRUE,
relay_athletes = TRUE
)
total_FOUL_round_1 <-
sum(df$Round_1 == "FOUL", na.rm = TRUE) # should be 8
total_FOUL_round_2 <-
sum(df$Round_2 == "FOUL", na.rm = TRUE) # should be 9
total_FOUL_round_3 <-
sum(df$Round_3 == "FOUL", na.rm = TRUE) # should be 6
total_FOUL_round_4 <-
sum(df$Round_4 == "FOUL", na.rm = TRUE) # should be 10
total_FOUL_round_5 <-
sum(df$Round_5 == "FOUL", na.rm = TRUE) # should be 11
total_FOUL_round_6 <-
sum(df$Round_6 == "FOUL", na.rm = TRUE) # should be 9
FOUL_list <-
c(
total_FOUL_round_1,
total_FOUL_round_2,
total_FOUL_round_3,
total_FOUL_round_4,
total_FOUL_round_5,
total_FOUL_round_6
)
expect_equal(FOUL_list, c(8, 9, 6, 10, 11, 9))
})
test_that("tf_parse_standard", {
skip_on_cran() # due to time, risk of external resources failing
# import standard
df_standard <- readRDS(system.file("extdata", "df_standard.rds", package = "JumpeR"))
# import test files
file_1 <-
system.file("extdata", "Results-IVP-Track-Field-Championship-2019-20-v2.pdf", package = "JumpeR") # good
file_2 <- system.file("extdata", "underdistance-2020-result.pdf", package = "JumpeR") # good
file_3 <-
system.file("extdata", "SMTFA-2019-Full-Results.pdf", package = "JumpeR") # good
file_4 <-
system.file("extdata", "sa-performance-trial-1-day-1-results.pdf", package = "JumpeR") # good
url_1 <- "http://results.yentiming.com/2019/Indoor/12-21-18-west.htm" # good
# url_2 <- "http://leonetiming.com/2019/Indoor/GregPageRelays/Results.htm"
# test external links
# if(sum(sapply(c(url_1, url_2), is_link_broken)) > 0.9){
raw_data <- try(read_results(url_1), silent = TRUE)
if(any(grep("error", class(raw_data)))){
skip("Link to external data is broken")
suppressWarnings(closeAllConnections())
} else {
# list of sources
sources <- c(file_1,
file_2,
file_3,
file_4)
# url_2)
# helper function to apply read_results across list of links
Read_Map <- function(links) {
scrape_test_all <-
purrr::map(links, read_results, node = "pre")
names(scrape_test_all) <- links
return(scrape_test_all)
}
# helper function to apply swim_parse across all files
Parse_Map <- function(links) {
all_results <-
purrr::map(links, tf_parse)
return(all_results)
}
# get test data to compare with standard
suppressWarnings(df_test <- Read_Map(sources))
suppressWarnings(df_test$url_1 <- raw_data)
df_test <- Parse_Map(df_test)
df_test <- dplyr::bind_rows(df_test, .id = "source") %>%
dplyr::select(-source)
# to regenerate df_standard if df_test is more correct
# windows
# readr::write_rds(df_test, "~/JumpeR/inst/extdata/df_standard.rds")
# mac
# readr::write_rds(df_test, "inst/extdata/df_standard.rds")
# to compare results
# df <- dplyr::anti_join(df_standard, df_test)
# compare standard to test
expect_equivalent(df_standard,
df_test)
}
})
test_that("tf_parse_attempts_splits_works", {
skip_on_cran() # due to risk of external resources failing
url_2 <- "http://leonetiming.com/2019/Indoor/GregPageRelays/Results.htm"
raw_data <- try(read_results(url_2), silent = TRUE)
if(any(grep("error", class(raw_data)))){
skip("Link to external data is broken")
suppressWarnings(closeAllConnections())
} else {
df_standard_polevault_hytek <- readRDS(system.file("extdata", "df_standard_polevault_hytek.rds", package = "JumpeR"))
df <-
tf_parse(
raw_data,
rounds = TRUE,
round_attempts = TRUE,
split_attempts = TRUE
)
df_test <- df %>%
dplyr::filter(Event == "Men Pole Vault")
expect_equivalent(df_test, df_standard_polevault_hytek)
# to regenerate df_standard if df_test is more correct
# windows
# readr::write_rds(df_test, "~/JumpeR/inst/extdata/df_standard_polevault_hytek.rds")
# mac
# readr::write_rds(df_test, "inst/extdata/df_standard_polevault_hytek.rds")
# to compare results
# df <- dplyr::anti_join(df_standard_polevault, df_test)
}
})
test_that("tf_parse high jump with team scores", {
skip_on_cran()
file <-
"http://tfresultsdata.deltatiming.com/2019-horizon-outdoor-championships/190503F026.htm"
raw_results <- read_results(file)
df_test <-
tf_parse(
raw_results,
rounds = TRUE,
round_attempts = TRUE,
relay_athletes = TRUE
)
df_standard <-
structure(
list(
Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10"),
Bib_Number = c(
"410",
"370",
"413",
"422",
"463",
"464",
"314",
"290",
"355",
"414"
),
Name = c(
"Alex Hugh-Plott",
"Brady Irwin",
"Salvatore Narusch",
"Chase VanSickle",
"Terron Taylor",
"Daiquain Watson",
"Bryan Keubeng",
"Joseph Lietzow",
"Trevor Coenen",
"Marcus Nellum"
),
Age = c("FR", "JR", "FR", "FR", "FR", "SO",
"FR", "SO", "JR", "FR"),
Team = c(
"OAKLAND",
"MILWAUKEE",
"OAKLAND",
"OAKLAND",
"YOUNGSTOWN ST.",
"YOUNGSTOWN ST.",
"ILLINOIS-CHICAGO",
"DETROIT MERCY",
"MILWAUKEE",
"OAKLAND"
),
Prelims_Result = c(
"2.03m",
"2.01m",
"1.95m",
"2.00m",
"2.03m",
"1.87m",
"1.90m",
"1.80m",
"1.96m",
"1.80m"
),
Finals_Result = c(
"2.03m",
"2.00m",
"1.97m",
"1.97m",
"1.94m",
"1.94m",
"1.91m",
"1.88m",
"1.88m",
"1.85m"
),
DQ = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
Event = c(
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump"
),
Round_1 = c(
"1.75",
"1.75",
"1.75",
"1.75",
"1.75",
"1.75",
"1.75",
"1.75",
"1.75",
"1.75"
),
Round_1_Attempts = c("-",
"-", "-", "-", "-", "O", "-", "O", "-", "O"),
Round_10 = c("2.06",
NA, NA, NA, NA, NA, NA, NA, NA, NA),
Round_10_Attempts = c("XXX",
NA, NA, NA, NA, NA, NA, NA, NA, NA),
Round_2 = c(
"1.80",
"1.80",
"1.80",
"1.80",
"1.80",
"1.80",
"1.80",
"1.80",
"1.80",
"1.80"
),
Round_2_Attempts = c("O", "-", "O", "O", "-", "O", "-", "O",
"O", "XO"),
Round_3 = c(
"1.85",
"1.85",
"1.85",
"1.85",
"1.85",
"1.85",
"1.85",
"1.85",
"1.85",
"1.85"
),
Round_3_Attempts = c("-",
"-", "-", "-", "O", "O", "O", "XXO", "O", "XXO"),
Round_4 = c(
"1.88",
"1.88",
"1.88",
"1.88",
"1.88",
"1.88",
"1.88",
"1.88",
"1.88",
"1.88"
),
Round_4_Attempts = c("O", "-", "O", "O", "-", "XO",
"-", "O", "XO", "XXX"),
Round_5 = c(
"1.91",
"1.91",
"1.91",
"1.91",
"1.91",
"1.91",
"1.91",
"1.91",
"1.91",
NA
),
Round_5_Attempts = c("-",
"O", "XO", "XO", "O", "XO", "O", "XXX", "XXX", NA),
Round_6 = c(
"1.94",
"1.94",
"1.94",
"1.94",
"1.94",
"1.94",
"1.94",
NA,
NA,
NA
),
Round_6_Attempts = c("XO", "XXO", "O", "XXO", "O", "O",
"XXX", NA, NA, NA),
Round_7 = c("1.97", "1.97", "1.97",
"1.97", "1.97", "1.97", NA, NA, NA, NA),
Round_7_Attempts = c("O",
"XXO", "XO", "XO", "XXX", "XXX", NA, NA, NA, NA),
Round_8 = c("2.00",
"2.00", "2.00", "2.00", NA, NA, NA, NA, NA, NA),
Round_8_Attempts = c("O",
"XXO", "XXX", "XXX", NA, NA, NA, NA, NA, NA),
Round_9 = c("2.03",
"2.03", NA, NA, NA, NA, NA, NA, NA, NA),
Round_9_Attempts = c("XO",
"XXX", NA, NA, NA, NA, NA, NA, NA, NA)
),
row.names = c(NA,-10L),
class = "data.frame"
)
expect_equivalent(df_test, df_standard)
})
test_that("tf_parse pass through", {
skip_on_cran()
#### Hept Shot Put ####
file <- "https://www.flashresults.com/2021_Meets/Indoor/03-11_NCAA/033-3_compiledSeries.htm"
df_test <- file %>%
read_results() %>%
tf_parse()
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", "15", NA), Name = c("Karel TILGA",
"Max VOLLMER", "Kyle GARLAND", "Leo NEUGEBAUER", "Daniel SPEJCHER",
"Felix WOLTER", "Ayden OWENS", "Jacob SPOTSWOOD", "Alex SPYRIDONIDIS",
"Peyton HAACK", "Isaiah MARTIN", "Kristo SIMULASK", "Austin WEST",
"Etamar BHASTEKAR", "Denim ROGERS", "Markus BALLENGEE"), Event = c("Hept Shot Put",
"Hept Shot Put", "Hept Shot Put", "Hept Shot Put", "Hept Shot Put",
"Hept Shot Put", "Hept Shot Put", "Hept Shot Put", "Hept Shot Put",
"Hept Shot Put", "Hept Shot Put", "Hept Shot Put", "Hept Shot Put",
"Hept Shot Put", "Hept Shot Put", "Hept Shot Put"), Gender = c("Men",
"Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men"), Finals_Result = c("16.04m",
"15.82m", "15.41m", "14.95m", "14.86m", "14.13m", "14.07m", "13.58m",
"13.47m", "13.44m", "13.33m", "13.03m", "12.92m", "12.32m", "12.22m",
"DNS"), Event_Date = structure(c(18698, 18698, 18698, 18698,
18698, 18698, 18698, 18698, 18698, 18698, 18698, 18698, 18698,
18698, 18698, 18698), class = "Date"), Team = c("Georgia", "Oregon",
"Georgia", "Texas", "Arkansas", "Pittsburgh", "Michigan", "Alabama",
"Auburn", "Iowa", "Purdue", "Oklahoma", "Iowa", "Arkansas", "Houston Baptist",
"Arkansas"), Round_1 = c("15.52", "15.45", "14.95", "14.95",
"14.86", "12.97", "12.26", "13.01", "13.47", "X", "13.24", "13.03",
"12.92", "10.73", "12.22", "DNS"), Round_2 = c("14.86", "15.70",
"15.41", "13.47", "14.73", "X", "12.93", "13.58", "13.19", "12.22",
"13.11", "12.54", "X", "11.22", "12.19", NA), Round_3 = c("16.04",
"15.82", "13.94", "14.71", "X", "14.13", "14.07", "12.27", "13.11",
"13.44", "13.33", "X", "12.60", "12.32", "X", NA), Age = c("SO",
"SO", "SO", "SO", "SO", "SR", "SO", "JR", "JR", "JR", "JR", "JR",
"SO", "SR", "SR", "SR")), row.names = c(NA, -16L), class = "data.frame")
expect_equivalent(df_test, df_standard)
#### Long Jump ####
file <-
"https://www.flashresults.com/2019_Meets/Outdoor/06-05_NCAAOTF-Austin/015-1_compiled.htm"
df_test <- file %>%
read_results() %>%
tf_parse()
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19",
"20", "21", NA, NA, NA), Name = c("JuVaughn HARRISON", "Trumaine JEFFERSON",
"Yann RANDRIANASOLO", "Justin HALL", "Jacob FINCHAM-DUKES", "Jamie BROWN",
"Kemonie BRIGGS", "Jordan LATIMER", "Odaine LEWIS", "Steffin MCCARTER",
"Chris MCBRIDE", "Grant HOLLOWAY", "Charles BROWN", "Carter SHELL",
"Samory FRAGA", "R'Lazon BRUMFIELD", "Allen GORDON", "Kenan JONES",
"Jullane WALKER", "DaJuan SEWARD", "Rayvon GREY", "Keshun MCGEE",
"Jalen SEALS", "Derrick MONROE"), Event = c("Long Jump", "Long Jump",
"Long Jump", "Long Jump", "Long Jump", "Long Jump", "Long Jump",
"Long Jump", "Long Jump", "Long Jump", "Long Jump", "Long Jump",
"Long Jump", "Long Jump", "Long Jump", "Long Jump", "Long Jump",
"Long Jump", "Long Jump", "Long Jump", "Long Jump", "Long Jump",
"Long Jump", "Long Jump"), Gender = c("Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men",
"Men", "Men"), Wind = c("+0.7", "+1.6", "+2.3", "+0.7", "+2.0",
"+1.8", "+2.1", "+3.2", "+2.1", "+1.3", "+1.0", "+1.3", "+3.1",
"+2.8", "+2.7", "+1.6", "+1.4", "+1.7", "+2.0", "+2.6", "+1.6",
NA, NA, NA), Finals_Result = c("8.20m", "8.18m", "8.12m", "8.05m",
"8.00m", "7.88m", "7.87m", "7.83m", "7.78m", "7.76m", "7.73m",
"7.72m", "7.70m", "7.67m", "7.65m", "7.62m", "7.61m", "7.54m",
"7.44m", "7.38m", "7.38m", "FOUL", "DNS", "DNS"), Event_Date = structure(c(18053,
18053, 18053, 18053, 18053, 18053, 18053, 18053, 18053, 18053,
18053, 18053, 18053, 18053, 18053, 18053, 18053, 18053, 18053,
18053, 18053, 18053, 18053, 18053), class = "Date"), Team = c(NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_)), row.names = c(NA,
-24L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("tf_parse 1600m with team scores at bottom", {
skip_on_cran()
file <- "http://results.deltatiming.com/tf/2019-hurricane-invitational/190315F076"
df_test <- file %>%
read_results() %>%
tf_parse()
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13"), Name = c("Robert Pedroza", "Sukeil Foucha",
"Will Noonan", "Alec Collado", "Humberto Ramirez", "Zachary Vincennie",
"Kevin Kergean", "James Cusack", "George Stark", "Pedro Garcia",
"Tomas Esber", "Lucas Nolasco", "Lucas Batista"), Age = c("JR",
"SR", "SR", "SR", "SO", "JR", "JR", "SR", "FR", "JR", "JR", "JR",
"SR"), Team = c("Key West HS", "Piper", "Spanish River", "Miami Coral Park",
"Piper", "Spanish River", "Miami Columbus", "Ransom Everglades",
"Palmer Trinity", "Braddock", "Ransom Everglades", "Cypress Bay",
"Miami Coral Park"), Finals_Result = c("4:19.69", "4:25.06",
"4:25.56", "4:27.56", "4:28.72", "4:29.69", "4:32.37", "4:33.01",
"4:34.06", "4:38.01", "4:42.45", "4:42.76", "5:23.53"), DQ = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Event = c("Boys 1600m Run Invitational High School",
"Boys 1600m Run Invitational High School", "Boys 1600m Run Invitational High School",
"Boys 1600m Run Invitational High School", "Boys 1600m Run Invitational High School",
"Boys 1600m Run Invitational High School", "Boys 1600m Run Invitational High School",
"Boys 1600m Run Invitational High School", "Boys 1600m Run Invitational High School",
"Boys 1600m Run Invitational High School", "Boys 1600m Run Invitational High School",
"Boys 1600m Run Invitational High School", "Boys 1600m Run Invitational High School"
)), row.names = c(NA, -13L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("hytek_parse long jump with wind speeds by round/attempt", {
skip_on_cran()
file <- "http://results.deltatiming.com/ncaa/tf/2019-florida-relays/print/190328F005"
df_test <- file %>%
read_results() %>%
tf_parse(rounds = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", "15", "16", "17"), Name = c("Alyssa Jones",
"Caroline Johnston", "Eddiyah Frye", "Destiny Castillo", "Morgan Bentley",
"Jordyn Showers", "Jasmyn Dorsey", "Christon Kingcade", "Samarah Hill",
"Ashantae Harvey", "Jaela Hollie", "Natiya James", "Saniah Fuller",
"Mackenzie Forrest", "Ameion Hamlet", "Gabriele Matthews", "Jiya Hastings"
), Age = c("FR", "SR", "SO", "SR", "11", "JR", "JR", "SR", "SR",
"JR", "SR", "JR", "SR", "JR", "JR", "JR", "SO"), Team = c("Miami Southridge",
"Episcopal", "St. Thomas Aquinas", "Hallandale", "Brookwood",
"Calvary Chri", "Mainland", "Miami Northwestern", "Trinity Prep",
"Hallandale", "Jones", "Eastside", "Windermere", "Forest", "Godby",
"Dr. Phillips", "DeLand"), Finals_Result = c("6.05m", "5.92m",
"5.83m", "5.80m", "5.66m", "5.65m", "5.41m", "5.38m", "5.36m",
"5.30m", "5.28m", "5.14m", "5.10m", "5.01m", "4.94m", "4.52m",
"4.50m"), DQ = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0), Event = c("Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School"), Round_1 = c("5.90m", "FOUL",
"FOUL", "FOUL", "5.53m", "5.64m", "FOUL", "5.38m", "FOUL", "5.12m",
"5.28m", "4.98m", "FOUL", "4.61m", "4.94m", "4.52m", "4.50m"),
Round_1_Wind = c("0.2", "1.9", "1.7", "2.7", "0.5", "1.4",
"+0.0", "0.6", "0.5", "0.7", "0.3", "0.6", "2.3", "+0.0",
"3.4", "1.9", "0.5"), Round_2 = c("6.05m", "5.65m", "FOUL",
"5.80m", "FOUL", "5.65m", "5.41m", "ND", "5.24m", "5.30m",
"5.09m", "5.14m", "4.85m", "ND", "FOUL", "ND", "ND"), Round_2_Wind = c("2.2",
"+0.0", "0.2", "2.3", "1.7", "1.6", "+0.0", "2.1", "0.8",
"1.0", "1.2", "0.7", "1.5", "1.7", "+0.0", "1.0", "0.2"),
Round_3 = c("5.93m", "FOUL", "5.83m", "ND", "5.49m", "5.26m",
"FOUL", "ND", "5.36m", "5.23m", "ND", "ND", "5.10m", "5.01m",
"FOUL", "ND", "FOUL"), Round_3_Wind = c("0.2", "0.2", "2.1",
"+0.0", "1.1", "0.2", "1.1", "0.2", "1.9", "1.2", "1.7",
"2.2", "0.5", "+0.0", "2.2", "0.3", "1.0"), Round_4 = c("5.93m",
"5.72m", "5.29m", "FOUL", "FOUL", "5.43m", "5.23m", "5.18m",
"5.29m", NA, NA, NA, NA, NA, NA, NA, NA), Round_4_Wind = c("1.7",
"0.8", "1.2", "0.2", "0.9", "0.6", "2.4", "0.9", "2.2", NA,
NA, NA, NA, NA, NA, NA, NA), Round_5 = c("5.74m", "5.72m",
"5.81m", "FOUL", "FOUL", "5.46m", "5.14m", "FOUL", "5.16m",
NA, NA, NA, NA, NA, NA, NA, NA), Round_5_Wind = c("1.5",
"0.9", "+0.0", "+0.0", "0.9", "1.2", "+0.0", "+0.0", "+0.0",
NA, NA, NA, NA, NA, NA, NA, NA), Round_6 = c("5.82m", "5.92m",
"FOUL", "FOUL", "5.66m", "5.24m", "5.13m", "5.06m", "5.14m",
NA, NA, NA, NA, NA, NA, NA, NA), Round_6_Wind = c("2.1",
"3.0", "1.4", "1.5", "3.4", "1.6", "+0.0", "1.9", "1.4",
NA, NA, NA, NA, NA, NA, NA, NA)), row.names = c(NA, -17L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("hytek_parse long jump with wind speeds by round/attempt, missing speeds", {
skip_on_cran()
file <- "http://results.deltatiming.com/tf/2019-tiger-track-classic/190405F032"
df_test <- file %>%
read_results() %>%
tf_parse(rounds = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", NA, NA, NA, NA), Name = c("Brandon Roulhac",
"Jamie Brown", "Michael Pichay", "Elijah White", "Willington Wright",
"Jacob Patten", "Benjamin Okafor", "Tyler Hanks", "Jordan Wallace",
"Marcus Cade", "DeAndre Baker", "Jordan Simons", "Nicholas Lyons",
"Eric Durham", "Philippe St-Hilaire", "John Warren", "Fabian Edoki",
"Devonta Brassell"), Age = c(NA, "SR", "SO", "SO", "FR", "SR",
"FR", "SO", "FR", "FR", "SR", "SO", "JR", "SR", NA, "SR", "JR",
"SR"), Team = c("Unattached", "Alabama State", "Holy Cross",
"Maine", "Mid. Tenn. State", "Mid. Tenn. State", "Western Carolina",
"Western Carolina", "Troy", "Alabama State", "Alabama A&M", "Alabama A&M",
"Western Carolina", "Troy", "Unattached", "Southern Miss.", "Mid. Tenn. State",
"Southern Miss."), Finals_Result = c("16.01m", "14.93m", "14.73m",
"14.69m", "14.64m", "14.60m", "14.45m", "13.84m", "13.79m", "13.77m",
"13.74m", "13.64m", "13.44m", "13.30m", "DNS", "DNS", "DNS",
"DNS"), Wind_Speed = c("+0.0", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, "NWI", "NWI", "NWI", "NWI"), DQ = c(0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Event = c("Men Triple Jump",
"Men Triple Jump", "Men Triple Jump", "Men Triple Jump", "Men Triple Jump",
"Men Triple Jump", "Men Triple Jump", "Men Triple Jump", "Men Triple Jump",
"Men Triple Jump", "Men Triple Jump", "Men Triple Jump", "Men Triple Jump",
"Men Triple Jump", "Men Triple Jump", "Men Triple Jump", "Men Triple Jump",
"Men Triple Jump"), Round_1 = c("15.75m", "X", "X", "14.64m",
"14.33m", "14.40m", "14.09m", "13.50m", "X", "13.31m", "13.74m",
"13.62m", "13.44m", "X", NA, NA, NA, NA), Round_1_Wind = c("+0.0",
"+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "-0.3", "-0.1",
"+0.0", "+0.0", "+0.0", "+0.0", "+0.0", NA, NA, NA, NA), Round_2 = c("16.01m",
"X", "14.73m", "14.66m", "14.31m", "14.60m", "14.45m", "13.84m",
"13.39m", "X", "X", "13.64m", "13.15m", "13.30m", NA, NA, NA,
NA), Round_2_Wind = c("+0.0", "+0.0", "+0.0", "+0.0", "+0.0",
"+0.0", "+0.0", "+0.0", "-0.1", "-0.6", "+0.0", "-1.4", "-0.8",
"-1.1", NA, NA, NA, NA), Round_3 = c("X", "14.91m", "X", "14.69m",
"14.28m", "X", "14.25m", "X", "13.79m", "13.77m", "X", "X", "X",
"X", NA, NA, NA, NA), Round_3_Wind = c(NA, "+0.0", "+0.0", "+0.0",
"+0.0", "+0.0", "-0.9", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0",
"+0.0", "+0.0", NA, NA, NA, NA), Round_4 = c("15.91m", "14.34m",
"14.34m", "13.43m", "14.64m", "14.18m", "13.52m", "13.74m", "13.21m",
NA, NA, NA, NA, NA, NA, NA, NA, NA), Round_4_Wind = c("+0.0",
"+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "0.3",
NA, NA, NA, NA, NA, NA, NA, NA, NA), Round_5 = c("15.85m", "X",
"14.14m", "14.56m", "14.60m", "13.94m", "X", "13.68m", "13.76m",
NA, NA, NA, NA, NA, NA, NA, NA, NA), Round_5_Wind = c("+0.0",
"0.2", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0",
NA, NA, NA, NA, NA, NA, NA, NA, NA), Round_6 = c("14.74m", "14.93m",
"14.31m", "X", "14.62m", "14.48m", "13.53m", "X", "X", NA, NA,
NA, NA, NA, NA, NA, NA, NA), Round_6_Wind = c("+0.0", "+0.0",
"+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", NA, NA,
NA, NA, NA, NA, NA, NA, NA)), row.names = c(NA, -18L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
# testthat::test_file("tests/testthat/test-tf_parse.R")
gpilgrim2670/JumpeR documentation built on March 25, 2023, 4:57 p.m.
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test_that("tf_parse heat sheet - no results", {
skip_on_cran()
file <- "http://tfresultsdata.deltatiming.com/2018-hurricane-invitational/180316F028.htm"
expect_message(out <- file %>%
read_results() %>%
tf_parse(), "No results found in file")
expect_equivalent(out, data.frame())
})
test_that("long jump with prelims/finals on the same page, missing wind and X instead of FOUL", {
skip_on_cran()
file <- "http://tfresultsdata.deltatiming.com/2019-sun-belt-outdoor-championships/190510F029.htm"
df_test <- file %>%
read_results() %>%
tf_parse(
relay_athletes = TRUE,
rounds = TRUE,
round_attempts = TRUE,
split_attempts = TRUE,
splits = TRUE
)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", "15", "1", "2", "3", "4",
"5", "6", "7", "8", "9", "10", "11", "12", "13", "14", NA), Bib_Number = c("73",
"163", "76", "231", "309", "299", "214", "377", "288", "164",
"107", "171", "352", "380", "276", "241", "248", "207", "92",
"87", "351", "200", "186", "194", "262", "360", "333", "190",
"110", "128"), Name = c("Erewele, Osereme", "Lodge, Detrich",
"Givens, Johnaya", "Vaikla, Hanna-Mai", "Cowans, Kaprecia", "Trawick, Brittany",
"Griffin, Elysa", "Matthews, Chante", "Middlebrooks, JaM", "Lynch, Meagan",
"Allen, Bria", "Seymour, Jakeeyah", "Simpson, Payton", "Obikudu, Chineme",
"Gordon, Amber", "Ferdinand, Naomi", "Hilton, Live", "Berge, Emilie",
"Nwofor, Emma", "Mack, Arabriaun", "Scott-Kilgo, Jasm", "Shaw, Alexus",
"Harrison, Ra'Bree", "Moore, Na'ilah", "Smith, Kylah", "Billingsley, Imun",
"Dendy, Micaiah", "Hunt, Jaeda", "Edison, Nicole", "Briggs, Kelsey"
), Age = c("FR", "SR", "FR", "SO", "FR", "FR", "JR", "SO", "JR",
"FR", "FR", "FR", "SR", "SR", "FR", "JR", "FR", "JR", "JR", "JR",
"FR", "SR", "JR", "FR", "SR", "SO", "JR", "FR", "JR", "JR"),
Team = c("Arkansas State", "Georgia Southern", "Arkansas State",
"South Alabama", "UL-Lafayette", "Troy", "South Alabama",
"UT-Arlington", "Troy", "Georgia Southern", "Arkansas-Lit",
"Georgia Southern", "UL-Monroe", "UT-Arlington", "Troy",
"Texas State", "Texas State", "South Alabama", "Arkansas State",
"Arkansas State", "UL-Monroe", "Georgia State", "Georgia State",
"Georgia State", "Texas State", "UT-Arlington", "UL-Monroe",
"Georgia State", "Arkansas-Lit", "Coastal Carolina"), Finals_Result = c("5.85m",
"5.64m", "5.62m", "5.47m", "5.43m", "5.42m", "5.32m", "5.31m",
"5.24m", "5.18m", "5.03m", "4.96m", "4.95m", "4.92m", "4.61m",
"6.11m", "6.06m", "5.92m", "5.88m", "5.88m", "5.86m", "5.71m",
"5.61m", "5.56m", "5.56m", "5.53m", "5.50m", "5.49m", "5.32m",
"FOUL"), Wind_Speed = c("0.6", "+0.0", "1.8", "0.2", "0.3",
"1.6", "1.2", "1.4", "1.2", "1.3", "1.1", "+0.0", "+0.0",
"+0.0", "0.1", "0.6", "+0.0", "1.8", "+0.0", "+0.0", "+0.0",
"+0.0", "+0.0", "+0.0", "+0.0", "0.1", "+0.0", "0.2", "0.2",
NA), DQ = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1), Event = c("Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump", "Women Long Jump",
"Women Long Jump", "Women Long Jump"), Round_1 = c("X", "5.41m",
"5.62m", "X", "5.41m", "X", "5.12m", "5.27m", "5.00m", "5.18m",
"5.03m", "X", "4.82m", "4.92m", "X", "5.78m", "5.77m", "5.59m",
"5.70m", "5.59m", "5.53m", "5.53m", "5.30m", "X", "5.24m",
"5.53m", "X", "5.37m", "5.30m", "X"), Round_1_Wind = c(NA,
"0.3", "1.8", NA, "1.9", NA, "+0.0", "0.9", "+0.0", "1.3",
"1.1", NA, "+0.0", "+0.0", NA, "0.1", "+0.0", "+0.0", "+0.0",
"0.8", "+0.0", "-0.6", "+0.0", NA, "+0.0", "0.1", NA, "0.3",
"+0.0", NA), Round_2 = c("5.79m", "5.64m", "5.36m", "X",
"5.42m", "X", "5.32m", "5.31m", "X", "5.13m", "5.00m", "X",
"4.95m", "4.71m", "4.61m", "X", "5.80m", "5.47m", "5.77m",
"5.13m", "5.51m", "5.63m", "5.29m", "5.50m", "5.35m", "5.31m",
"5.50m", "5.32m", "5.15m", "X"), Round_2_Wind = c("0.8",
"+0.0", "0.1", NA, "1.1", NA, "1.2", "1.4", NA, "1.4", "0.7",
NA, "1.2", "+0.0", "0.1", NA, "0.1", "0.9", "0.3", "+0.0",
"+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0",
"+0.0", NA), Round_3 = c("X", "X", "5.56m", "5.47m", "5.43m",
"5.42m", "X", "5.16m", "5.24m", "X", "5.03m", "4.96m", "4.95m",
"4.89m", "X", "5.77m", "6.06m", "X", "X", "5.88m", "5.77m",
"5.71m", "5.61m", "5.56m", "5.56m", "X", "5.47m", "5.49m",
"5.32m", "X"), Round_3_Wind = c(NA, NA, "1.9", "0.2", "0.3",
"1.6", NA, "+0.0", "1.2", NA, "0.8", "+0.0", "+0.0", "+0.0",
NA, "0.3", "+0.0", NA, NA, "+0.0", "+0.0", "+0.0", "+0.0",
"+0.0", "+0.0", NA, "+0.0", "0.2", "0.2", NA), Round_4 = c("5.85m",
"X", "5.38m", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "5.81m", "5.76m", "5.80m", "5.86m", "X", "5.70m", "5.60m",
NA, NA, NA, NA, NA, NA, NA, NA), Round_4_Wind = c("0.6",
NA, "+0.0", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
"0.3", "0.9", "0.9", "0.7", NA, "+0.0", "1.0", NA, NA, NA,
NA, NA, NA, NA, NA), Round_5 = c("X", "5.47m", "X", NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "X", "X", "5.83m",
"5.88m", "5.55m", "X", "5.58m", NA, NA, NA, NA, NA, NA, NA,
NA), Round_5_Wind = c(NA, "+0.0", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, "1.1", "+0.0", "+0.0",
NA, "0.3", NA, NA, NA, NA, NA, NA, NA, NA), Round_6 = c("X",
"X", "5.56m", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "6.11m", "5.72m", "5.92m", "5.87m", "X", "5.86m", "X",
NA, NA, NA, NA, NA, NA, NA, NA), Round_6_Wind = c(NA, NA,
"0.3", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "0.6",
"+0.0", "1.8", "1.4", NA, "+0.0", NA, NA, NA, NA, NA, NA,
NA, NA, NA)), row.names = c(NA, -30L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("triple jump with attempts_split and split_attempts", {
skip_on_cran()
file <- "http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F031.htm"
df_test <- file %>%
read_results() %>%
tf_parse(
relay_athletes = TRUE,
rounds = TRUE,
round_attempts = TRUE,
split_attempts = TRUE,
splits = TRUE
)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19",
"20", NA, NA), Name = c("Raqib, Nisa", "Britt, Kaylah", "Austin, Nikeela",
"Taub, Shannon", "Lewis, Aaliyah", "Phoennik, Courtney", "Seto, Maris",
"McQueeney, Hope", "Holmberg, Gabby", "DeLuca, Maria", "Horrell, Rachel",
"Billone, Caroline", "Streeter, Quintasia", "Adams, Katlyn",
"Ketterman, Stefanie", "Latoza, Kayla", "Hershberger, Faith",
"Collins, Abbey", "Lodge, Emily", "Douglas, Jill", "Wagner, Alexis",
"Swartzbaugh, Lydia"), Age = c("SO", "FR", "SR", "SR", "SO",
"JR", "SR", "FR", "JR", "JR", "SO", "JR", "FR", "SR", "SO", "SO",
"FR", "SO", "FR", "SO", "JR", "SR"), Team = c("Buffalo", "Buffalo",
"Indiana (Pa.)", "Unattached", "California (Pa.)", "John Carroll",
"Duquesne", "Clarion", "Duquesne", "John Carroll", "Indiana (Pa.)",
"Duquesne", "California (Pa.)", "Grove City", "Indiana (Pa.)",
"California (Pa.)", "Indiana (Pa.)", "Grove City", "Clarion",
"Westminster (Pa.)", "California (Pa.)", "Geneva"), Finals_Result = c("12.77m",
"12.02m", "11.79m", "11.39m", "11.17m", "11.15m", "11.12m", "11.09m",
"11.06m", "11.01m", "10.93m", "10.90m", "10.82m", "10.53m", "10.17m",
"10.13m", "10.02m", "9.75m", "9.13m", "8.97m", "FOUL", "FOUL"
), DQ = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 1), Event = c("Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump", "Women Triple Jump",
"Women Triple Jump", "Women Triple Jump"), Round_1 = c("12.33m",
"11.02m", "11.46m", "11.39m", "11.04m", "10.89m", "X", "11.09m",
"X", "10.75m", "X", "10.79m", "X", "10.35m", "10.17m", "X", "10.02m",
"9.75m", "9.13m", "8.97m", "X", "X"), Round_2 = c("12.36m", "X",
"11.44m", "-", "11.07m", "11.04m", "X", "10.66m", "11.06m", "ND",
"10.93m", "10.90m", "10.47m", "10.53m", "ND", "10.13m", "ND",
"ND", "ND", "ND", "X", "X"), Round_3 = c("12.38m", "X", "11.26m",
"-", "X", "10.86m", "11.06m", "ND", "X", "11.01m", "10.65m",
"10.81m", "10.82m", "10.43m", "X", "X", "ND", "X", "ND", "ND",
"X", "X"), Round_4 = c("12.13m", "X", "11.72m", "-", "X", "11.13m",
"X", "10.82m", "-", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA), Round_5 = c("12.77m", "12.02m", "11.79m", "-", "11.13m",
"10.76m", "X", "10.71m", "-", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), Round_6 = c("12.27m", "X", "11.77m", "-",
"11.17m", "11.15m", "11.12m", "10.87m", "-", NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA)), row.names = c(NA, -22L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("tf_parse_round_attempts", {
file <-
system.file("extdata",
"Results-IVP-Track-Field-Championship-2019-20-v2.pdf",
package = "JumpeR")
raw_results <- read_results(file)
df <-
tf_parse(
raw_results,
rounds = TRUE,
round_attempts = TRUE,
relay_athletes = TRUE
)
total_O_round_1 <-
sum(df$Round_1_Attempts == "O", na.rm = TRUE) # should be 17
expect_equal(total_O_round_1, 17)
})
test_that("tf_parse mapping hytek", {
skip_on_cran()
links <-
c(
"http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F022.htm",
"http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F036.htm",
"http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F035.htm"
)
df_test <- links %>%
map(read_results) %>%
map(tf_parse) %>%
map(head, 3) %>%
bind_rows()
df_standard <-
structure(list(Place = c("1", "2", "3", "1", "2", "3", "1", "2",
"3"), Team = c("Pittsburgh", "Pittsburgh", "Kent State", "Buffalo",
"Youngstown St.", "Walsh", "Buffalo", "Pittsburgh", "Pittsburgh"
), Finals_Result = c("3:16.26", "3:21.54", "3:21.77", "18.91m",
"17.95m", "17.57m", "17.41m", "16.47m", "16.27m"), DQ = c(0,
0, 0, 0, 0, 0, 0, 0, 0), Event = c("Men 4x400 Meter Relay", "Men 4x400 Meter Relay",
"Men 4x400 Meter Relay", "Men Weight Throw", "Men Weight Throw",
"Men Weight Throw", "Women Weight Throw", "Women Weight Throw",
"Women Weight Throw"), Name = c(NA, NA, NA, "Wray, Samuel", "Gutzky, Ben",
"Ott, Jacob", "Hoyte, Asia", "Mallett, Shannah", "Gyles, Antoinette"
), Age = c(NA, NA, NA, "SR", "SR", "SO", "JR", "FR", "JR")), row.names = c(NA,
-9L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("tf_parse safely mapping hytek", {
skip_on_cran()
links <-
c(
"http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F022.htm",
"http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F036.htm",
"http://tfresultsdata.deltatiming.com/2019-ysu-icebreaker/191206F035.htm"
)
df_test <- links %>%
map(read_results) %>%
map(
purrr::safely(tf_parse, otherwise = NA),
relay_athletes = TRUE,
rounds = TRUE,
round_attempts = TRUE,
split_attempts = TRUE,
splits = TRUE
) %>%
SwimmeR::discard_errors() %>%
map(head, 3) %>%
bind_rows()
df_standard <-
structure(list(Place = c("1", "2", "3", "1", "2", "3", "1", "2",
"3"), Team = c("Pittsburgh", "Pittsburgh", "Kent State", "Buffalo",
"Youngstown St.", "Walsh", "Buffalo", "Pittsburgh", "Pittsburgh"
), Finals_Result = c("3:16.26", "3:21.54", "3:21.77", "18.91m",
"17.95m", "17.57m", "17.41m", "16.47m", "16.27m"), DQ = c(0,
0, 0, 0, 0, 0, 0, 0, 0), Event = c("Men 4x400 Meter Relay", "Men 4x400 Meter Relay",
"Men 4x400 Meter Relay", "Men Weight Throw", "Men Weight Throw",
"Men Weight Throw", "Women Weight Throw", "Women Weight Throw",
"Women Weight Throw"), Name = c(NA, NA, NA, "Wray, Samuel", "Gutzky, Ben",
"Ott, Jacob", "Hoyte, Asia", "Mallett, Shannah", "Gyles, Antoinette"
), Age = c(NA, NA, NA, "SR", "SR", "SO", "JR", "FR", "JR"), Round_1 = c(NA,
NA, NA, "17.01m", "ND", "17.57m", "ND", "16.47m", "15.36m"),
Round_2 = c(NA, NA, NA, "18.06m", "17.43m", "ND", "ND", "16.12m",
"16.27m"), Round_3 = c(NA, NA, NA, "ND", "17.59m", "15.98m",
"14.71m", "16.42m", "ND"), Round_4 = c(NA, NA, NA, "18.91m",
"17.39m", "ND", "17.41m", "16.31m", "ND"), Round_5 = c(NA,
NA, NA, "18.33m", "17.68m", "17.29m", "15.01m", "15.17m",
"ND"), Round_6 = c(NA, NA, NA, "18.86m", "17.95m", "ND",
"ND", "15.37m", "15.68m")), row.names = c(NA, -9L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("tf_parse_rounds", {
file <-
system.file("extdata", "underdistance-2020-result.pdf", package = "JumpeR")
raw_results <- read_results(file)
df <-
tf_parse(
raw_results,
rounds = TRUE,
round_attempts = TRUE,
relay_athletes = TRUE
)
total_FOUL_round_1 <-
sum(df$Round_1 == "FOUL", na.rm = TRUE) # should be 8
total_FOUL_round_2 <-
sum(df$Round_2 == "FOUL", na.rm = TRUE) # should be 9
total_FOUL_round_3 <-
sum(df$Round_3 == "FOUL", na.rm = TRUE) # should be 6
total_FOUL_round_4 <-
sum(df$Round_4 == "FOUL", na.rm = TRUE) # should be 10
total_FOUL_round_5 <-
sum(df$Round_5 == "FOUL", na.rm = TRUE) # should be 11
total_FOUL_round_6 <-
sum(df$Round_6 == "FOUL", na.rm = TRUE) # should be 9
FOUL_list <-
c(
total_FOUL_round_1,
total_FOUL_round_2,
total_FOUL_round_3,
total_FOUL_round_4,
total_FOUL_round_5,
total_FOUL_round_6
)
expect_equal(FOUL_list, c(8, 9, 6, 10, 11, 9))
})
test_that("tf_parse_standard", {
skip_on_cran() # due to time, risk of external resources failing
# import standard
df_standard <- readRDS(system.file("extdata", "df_standard.rds", package = "JumpeR"))
# import test files
file_1 <-
system.file("extdata", "Results-IVP-Track-Field-Championship-2019-20-v2.pdf", package = "JumpeR") # good
file_2 <- system.file("extdata", "underdistance-2020-result.pdf", package = "JumpeR") # good
file_3 <-
system.file("extdata", "SMTFA-2019-Full-Results.pdf", package = "JumpeR") # good
file_4 <-
system.file("extdata", "sa-performance-trial-1-day-1-results.pdf", package = "JumpeR") # good
url_1 <- "http://results.yentiming.com/2019/Indoor/12-21-18-west.htm" # good
# url_2 <- "http://leonetiming.com/2019/Indoor/GregPageRelays/Results.htm"
# test external links
# if(sum(sapply(c(url_1, url_2), is_link_broken)) > 0.9){
raw_data <- try(read_results(url_1), silent = TRUE)
if(any(grep("error", class(raw_data)))){
skip("Link to external data is broken")
suppressWarnings(closeAllConnections())
} else {
# list of sources
sources <- c(file_1,
file_2,
file_3,
file_4)
# url_2)
# helper function to apply read_results across list of links
Read_Map <- function(links) {
scrape_test_all <-
purrr::map(links, read_results, node = "pre")
names(scrape_test_all) <- links
return(scrape_test_all)
}
# helper function to apply swim_parse across all files
Parse_Map <- function(links) {
all_results <-
purrr::map(links, tf_parse)
return(all_results)
}
# get test data to compare with standard
suppressWarnings(df_test <- Read_Map(sources))
suppressWarnings(df_test$url_1 <- raw_data)
df_test <- Parse_Map(df_test)
df_test <- dplyr::bind_rows(df_test, .id = "source") %>%
dplyr::select(-source)
# to regenerate df_standard if df_test is more correct
# windows
# readr::write_rds(df_test, "~/JumpeR/inst/extdata/df_standard.rds")
# mac
# readr::write_rds(df_test, "inst/extdata/df_standard.rds")
# to compare results
# df <- dplyr::anti_join(df_standard, df_test)
# compare standard to test
expect_equivalent(df_standard,
df_test)
}
})
test_that("tf_parse_attempts_splits_works", {
skip_on_cran() # due to risk of external resources failing
url_2 <- "http://leonetiming.com/2019/Indoor/GregPageRelays/Results.htm"
raw_data <- try(read_results(url_2), silent = TRUE)
if(any(grep("error", class(raw_data)))){
skip("Link to external data is broken")
suppressWarnings(closeAllConnections())
} else {
df_standard_polevault_hytek <- readRDS(system.file("extdata", "df_standard_polevault_hytek.rds", package = "JumpeR"))
df <-
tf_parse(
raw_data,
rounds = TRUE,
round_attempts = TRUE,
split_attempts = TRUE
)
df_test <- df %>%
dplyr::filter(Event == "Men Pole Vault")
expect_equivalent(df_test, df_standard_polevault_hytek)
# to regenerate df_standard if df_test is more correct
# windows
# readr::write_rds(df_test, "~/JumpeR/inst/extdata/df_standard_polevault_hytek.rds")
# mac
# readr::write_rds(df_test, "inst/extdata/df_standard_polevault_hytek.rds")
# to compare results
# df <- dplyr::anti_join(df_standard_polevault, df_test)
}
})
test_that("tf_parse high jump with team scores", {
skip_on_cran()
file <-
"http://tfresultsdata.deltatiming.com/2019-horizon-outdoor-championships/190503F026.htm"
raw_results <- read_results(file)
df_test <-
tf_parse(
raw_results,
rounds = TRUE,
round_attempts = TRUE,
relay_athletes = TRUE
)
df_standard <-
structure(
list(
Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10"),
Bib_Number = c(
"410",
"370",
"413",
"422",
"463",
"464",
"314",
"290",
"355",
"414"
),
Name = c(
"Alex Hugh-Plott",
"Brady Irwin",
"Salvatore Narusch",
"Chase VanSickle",
"Terron Taylor",
"Daiquain Watson",
"Bryan Keubeng",
"Joseph Lietzow",
"Trevor Coenen",
"Marcus Nellum"
),
Age = c("FR", "JR", "FR", "FR", "FR", "SO",
"FR", "SO", "JR", "FR"),
Team = c(
"OAKLAND",
"MILWAUKEE",
"OAKLAND",
"OAKLAND",
"YOUNGSTOWN ST.",
"YOUNGSTOWN ST.",
"ILLINOIS-CHICAGO",
"DETROIT MERCY",
"MILWAUKEE",
"OAKLAND"
),
Prelims_Result = c(
"2.03m",
"2.01m",
"1.95m",
"2.00m",
"2.03m",
"1.87m",
"1.90m",
"1.80m",
"1.96m",
"1.80m"
),
Finals_Result = c(
"2.03m",
"2.00m",
"1.97m",
"1.97m",
"1.94m",
"1.94m",
"1.91m",
"1.88m",
"1.88m",
"1.85m"
),
DQ = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
Event = c(
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump",
"Men High Jump"
),
Round_1 = c(
"1.75",
"1.75",
"1.75",
"1.75",
"1.75",
"1.75",
"1.75",
"1.75",
"1.75",
"1.75"
),
Round_1_Attempts = c("-",
"-", "-", "-", "-", "O", "-", "O", "-", "O"),
Round_10 = c("2.06",
NA, NA, NA, NA, NA, NA, NA, NA, NA),
Round_10_Attempts = c("XXX",
NA, NA, NA, NA, NA, NA, NA, NA, NA),
Round_2 = c(
"1.80",
"1.80",
"1.80",
"1.80",
"1.80",
"1.80",
"1.80",
"1.80",
"1.80",
"1.80"
),
Round_2_Attempts = c("O", "-", "O", "O", "-", "O", "-", "O",
"O", "XO"),
Round_3 = c(
"1.85",
"1.85",
"1.85",
"1.85",
"1.85",
"1.85",
"1.85",
"1.85",
"1.85",
"1.85"
),
Round_3_Attempts = c("-",
"-", "-", "-", "O", "O", "O", "XXO", "O", "XXO"),
Round_4 = c(
"1.88",
"1.88",
"1.88",
"1.88",
"1.88",
"1.88",
"1.88",
"1.88",
"1.88",
"1.88"
),
Round_4_Attempts = c("O", "-", "O", "O", "-", "XO",
"-", "O", "XO", "XXX"),
Round_5 = c(
"1.91",
"1.91",
"1.91",
"1.91",
"1.91",
"1.91",
"1.91",
"1.91",
"1.91",
NA
),
Round_5_Attempts = c("-",
"O", "XO", "XO", "O", "XO", "O", "XXX", "XXX", NA),
Round_6 = c(
"1.94",
"1.94",
"1.94",
"1.94",
"1.94",
"1.94",
"1.94",
NA,
NA,
NA
),
Round_6_Attempts = c("XO", "XXO", "O", "XXO", "O", "O",
"XXX", NA, NA, NA),
Round_7 = c("1.97", "1.97", "1.97",
"1.97", "1.97", "1.97", NA, NA, NA, NA),
Round_7_Attempts = c("O",
"XXO", "XO", "XO", "XXX", "XXX", NA, NA, NA, NA),
Round_8 = c("2.00",
"2.00", "2.00", "2.00", NA, NA, NA, NA, NA, NA),
Round_8_Attempts = c("O",
"XXO", "XXX", "XXX", NA, NA, NA, NA, NA, NA),
Round_9 = c("2.03",
"2.03", NA, NA, NA, NA, NA, NA, NA, NA),
Round_9_Attempts = c("XO",
"XXX", NA, NA, NA, NA, NA, NA, NA, NA)
),
row.names = c(NA,-10L),
class = "data.frame"
)
expect_equivalent(df_test, df_standard)
})
test_that("tf_parse pass through", {
skip_on_cran()
#### Hept Shot Put ####
file <- "https://www.flashresults.com/2021_Meets/Indoor/03-11_NCAA/033-3_compiledSeries.htm"
df_test <- file %>%
read_results() %>%
tf_parse()
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", "15", NA), Name = c("Karel TILGA",
"Max VOLLMER", "Kyle GARLAND", "Leo NEUGEBAUER", "Daniel SPEJCHER",
"Felix WOLTER", "Ayden OWENS", "Jacob SPOTSWOOD", "Alex SPYRIDONIDIS",
"Peyton HAACK", "Isaiah MARTIN", "Kristo SIMULASK", "Austin WEST",
"Etamar BHASTEKAR", "Denim ROGERS", "Markus BALLENGEE"), Event = c("Hept Shot Put",
"Hept Shot Put", "Hept Shot Put", "Hept Shot Put", "Hept Shot Put",
"Hept Shot Put", "Hept Shot Put", "Hept Shot Put", "Hept Shot Put",
"Hept Shot Put", "Hept Shot Put", "Hept Shot Put", "Hept Shot Put",
"Hept Shot Put", "Hept Shot Put", "Hept Shot Put"), Gender = c("Men",
"Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men"), Finals_Result = c("16.04m",
"15.82m", "15.41m", "14.95m", "14.86m", "14.13m", "14.07m", "13.58m",
"13.47m", "13.44m", "13.33m", "13.03m", "12.92m", "12.32m", "12.22m",
"DNS"), Event_Date = structure(c(18698, 18698, 18698, 18698,
18698, 18698, 18698, 18698, 18698, 18698, 18698, 18698, 18698,
18698, 18698, 18698), class = "Date"), Team = c("Georgia", "Oregon",
"Georgia", "Texas", "Arkansas", "Pittsburgh", "Michigan", "Alabama",
"Auburn", "Iowa", "Purdue", "Oklahoma", "Iowa", "Arkansas", "Houston Baptist",
"Arkansas"), Round_1 = c("15.52", "15.45", "14.95", "14.95",
"14.86", "12.97", "12.26", "13.01", "13.47", "X", "13.24", "13.03",
"12.92", "10.73", "12.22", "DNS"), Round_2 = c("14.86", "15.70",
"15.41", "13.47", "14.73", "X", "12.93", "13.58", "13.19", "12.22",
"13.11", "12.54", "X", "11.22", "12.19", NA), Round_3 = c("16.04",
"15.82", "13.94", "14.71", "X", "14.13", "14.07", "12.27", "13.11",
"13.44", "13.33", "X", "12.60", "12.32", "X", NA), Age = c("SO",
"SO", "SO", "SO", "SO", "SR", "SO", "JR", "JR", "JR", "JR", "JR",
"SO", "SR", "SR", "SR")), row.names = c(NA, -16L), class = "data.frame")
expect_equivalent(df_test, df_standard)
#### Long Jump ####
file <-
"https://www.flashresults.com/2019_Meets/Outdoor/06-05_NCAAOTF-Austin/015-1_compiled.htm"
df_test <- file %>%
read_results() %>%
tf_parse()
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19",
"20", "21", NA, NA, NA), Name = c("JuVaughn HARRISON", "Trumaine JEFFERSON",
"Yann RANDRIANASOLO", "Justin HALL", "Jacob FINCHAM-DUKES", "Jamie BROWN",
"Kemonie BRIGGS", "Jordan LATIMER", "Odaine LEWIS", "Steffin MCCARTER",
"Chris MCBRIDE", "Grant HOLLOWAY", "Charles BROWN", "Carter SHELL",
"Samory FRAGA", "R'Lazon BRUMFIELD", "Allen GORDON", "Kenan JONES",
"Jullane WALKER", "DaJuan SEWARD", "Rayvon GREY", "Keshun MCGEE",
"Jalen SEALS", "Derrick MONROE"), Event = c("Long Jump", "Long Jump",
"Long Jump", "Long Jump", "Long Jump", "Long Jump", "Long Jump",
"Long Jump", "Long Jump", "Long Jump", "Long Jump", "Long Jump",
"Long Jump", "Long Jump", "Long Jump", "Long Jump", "Long Jump",
"Long Jump", "Long Jump", "Long Jump", "Long Jump", "Long Jump",
"Long Jump", "Long Jump"), Gender = c("Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men",
"Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men", "Men",
"Men", "Men"), Wind = c("+0.7", "+1.6", "+2.3", "+0.7", "+2.0",
"+1.8", "+2.1", "+3.2", "+2.1", "+1.3", "+1.0", "+1.3", "+3.1",
"+2.8", "+2.7", "+1.6", "+1.4", "+1.7", "+2.0", "+2.6", "+1.6",
NA, NA, NA), Finals_Result = c("8.20m", "8.18m", "8.12m", "8.05m",
"8.00m", "7.88m", "7.87m", "7.83m", "7.78m", "7.76m", "7.73m",
"7.72m", "7.70m", "7.67m", "7.65m", "7.62m", "7.61m", "7.54m",
"7.44m", "7.38m", "7.38m", "FOUL", "DNS", "DNS"), Event_Date = structure(c(18053,
18053, 18053, 18053, 18053, 18053, 18053, 18053, 18053, 18053,
18053, 18053, 18053, 18053, 18053, 18053, 18053, 18053, 18053,
18053, 18053, 18053, 18053, 18053), class = "Date"), Team = c(NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_)), row.names = c(NA,
-24L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("tf_parse 1600m with team scores at bottom", {
skip_on_cran()
file <- "http://results.deltatiming.com/tf/2019-hurricane-invitational/190315F076"
df_test <- file %>%
read_results() %>%
tf_parse()
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13"), Name = c("Robert Pedroza", "Sukeil Foucha",
"Will Noonan", "Alec Collado", "Humberto Ramirez", "Zachary Vincennie",
"Kevin Kergean", "James Cusack", "George Stark", "Pedro Garcia",
"Tomas Esber", "Lucas Nolasco", "Lucas Batista"), Age = c("JR",
"SR", "SR", "SR", "SO", "JR", "JR", "SR", "FR", "JR", "JR", "JR",
"SR"), Team = c("Key West HS", "Piper", "Spanish River", "Miami Coral Park",
"Piper", "Spanish River", "Miami Columbus", "Ransom Everglades",
"Palmer Trinity", "Braddock", "Ransom Everglades", "Cypress Bay",
"Miami Coral Park"), Finals_Result = c("4:19.69", "4:25.06",
"4:25.56", "4:27.56", "4:28.72", "4:29.69", "4:32.37", "4:33.01",
"4:34.06", "4:38.01", "4:42.45", "4:42.76", "5:23.53"), DQ = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Event = c("Boys 1600m Run Invitational High School",
"Boys 1600m Run Invitational High School", "Boys 1600m Run Invitational High School",
"Boys 1600m Run Invitational High School", "Boys 1600m Run Invitational High School",
"Boys 1600m Run Invitational High School", "Boys 1600m Run Invitational High School",
"Boys 1600m Run Invitational High School", "Boys 1600m Run Invitational High School",
"Boys 1600m Run Invitational High School", "Boys 1600m Run Invitational High School",
"Boys 1600m Run Invitational High School", "Boys 1600m Run Invitational High School"
)), row.names = c(NA, -13L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("hytek_parse long jump with wind speeds by round/attempt", {
skip_on_cran()
file <- "http://results.deltatiming.com/ncaa/tf/2019-florida-relays/print/190328F005"
df_test <- file %>%
read_results() %>%
tf_parse(rounds = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", "15", "16", "17"), Name = c("Alyssa Jones",
"Caroline Johnston", "Eddiyah Frye", "Destiny Castillo", "Morgan Bentley",
"Jordyn Showers", "Jasmyn Dorsey", "Christon Kingcade", "Samarah Hill",
"Ashantae Harvey", "Jaela Hollie", "Natiya James", "Saniah Fuller",
"Mackenzie Forrest", "Ameion Hamlet", "Gabriele Matthews", "Jiya Hastings"
), Age = c("FR", "SR", "SO", "SR", "11", "JR", "JR", "SR", "SR",
"JR", "SR", "JR", "SR", "JR", "JR", "JR", "SO"), Team = c("Miami Southridge",
"Episcopal", "St. Thomas Aquinas", "Hallandale", "Brookwood",
"Calvary Chri", "Mainland", "Miami Northwestern", "Trinity Prep",
"Hallandale", "Jones", "Eastside", "Windermere", "Forest", "Godby",
"Dr. Phillips", "DeLand"), Finals_Result = c("6.05m", "5.92m",
"5.83m", "5.80m", "5.66m", "5.65m", "5.41m", "5.38m", "5.36m",
"5.30m", "5.28m", "5.14m", "5.10m", "5.01m", "4.94m", "4.52m",
"4.50m"), DQ = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0), Event = c("Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School", "Girls Long Jump High School",
"Girls Long Jump High School"), Round_1 = c("5.90m", "FOUL",
"FOUL", "FOUL", "5.53m", "5.64m", "FOUL", "5.38m", "FOUL", "5.12m",
"5.28m", "4.98m", "FOUL", "4.61m", "4.94m", "4.52m", "4.50m"),
Round_1_Wind = c("0.2", "1.9", "1.7", "2.7", "0.5", "1.4",
"+0.0", "0.6", "0.5", "0.7", "0.3", "0.6", "2.3", "+0.0",
"3.4", "1.9", "0.5"), Round_2 = c("6.05m", "5.65m", "FOUL",
"5.80m", "FOUL", "5.65m", "5.41m", "ND", "5.24m", "5.30m",
"5.09m", "5.14m", "4.85m", "ND", "FOUL", "ND", "ND"), Round_2_Wind = c("2.2",
"+0.0", "0.2", "2.3", "1.7", "1.6", "+0.0", "2.1", "0.8",
"1.0", "1.2", "0.7", "1.5", "1.7", "+0.0", "1.0", "0.2"),
Round_3 = c("5.93m", "FOUL", "5.83m", "ND", "5.49m", "5.26m",
"FOUL", "ND", "5.36m", "5.23m", "ND", "ND", "5.10m", "5.01m",
"FOUL", "ND", "FOUL"), Round_3_Wind = c("0.2", "0.2", "2.1",
"+0.0", "1.1", "0.2", "1.1", "0.2", "1.9", "1.2", "1.7",
"2.2", "0.5", "+0.0", "2.2", "0.3", "1.0"), Round_4 = c("5.93m",
"5.72m", "5.29m", "FOUL", "FOUL", "5.43m", "5.23m", "5.18m",
"5.29m", NA, NA, NA, NA, NA, NA, NA, NA), Round_4_Wind = c("1.7",
"0.8", "1.2", "0.2", "0.9", "0.6", "2.4", "0.9", "2.2", NA,
NA, NA, NA, NA, NA, NA, NA), Round_5 = c("5.74m", "5.72m",
"5.81m", "FOUL", "FOUL", "5.46m", "5.14m", "FOUL", "5.16m",
NA, NA, NA, NA, NA, NA, NA, NA), Round_5_Wind = c("1.5",
"0.9", "+0.0", "+0.0", "0.9", "1.2", "+0.0", "+0.0", "+0.0",
NA, NA, NA, NA, NA, NA, NA, NA), Round_6 = c("5.82m", "5.92m",
"FOUL", "FOUL", "5.66m", "5.24m", "5.13m", "5.06m", "5.14m",
NA, NA, NA, NA, NA, NA, NA, NA), Round_6_Wind = c("2.1",
"3.0", "1.4", "1.5", "3.4", "1.6", "+0.0", "1.9", "1.4",
NA, NA, NA, NA, NA, NA, NA, NA)), row.names = c(NA, -17L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
test_that("hytek_parse long jump with wind speeds by round/attempt, missing speeds", {
skip_on_cran()
file <- "http://results.deltatiming.com/tf/2019-tiger-track-classic/190405F032"
df_test <- file %>%
read_results() %>%
tf_parse(rounds = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"9", "10", "11", "12", "13", "14", NA, NA, NA, NA), Name = c("Brandon Roulhac",
"Jamie Brown", "Michael Pichay", "Elijah White", "Willington Wright",
"Jacob Patten", "Benjamin Okafor", "Tyler Hanks", "Jordan Wallace",
"Marcus Cade", "DeAndre Baker", "Jordan Simons", "Nicholas Lyons",
"Eric Durham", "Philippe St-Hilaire", "John Warren", "Fabian Edoki",
"Devonta Brassell"), Age = c(NA, "SR", "SO", "SO", "FR", "SR",
"FR", "SO", "FR", "FR", "SR", "SO", "JR", "SR", NA, "SR", "JR",
"SR"), Team = c("Unattached", "Alabama State", "Holy Cross",
"Maine", "Mid. Tenn. State", "Mid. Tenn. State", "Western Carolina",
"Western Carolina", "Troy", "Alabama State", "Alabama A&M", "Alabama A&M",
"Western Carolina", "Troy", "Unattached", "Southern Miss.", "Mid. Tenn. State",
"Southern Miss."), Finals_Result = c("16.01m", "14.93m", "14.73m",
"14.69m", "14.64m", "14.60m", "14.45m", "13.84m", "13.79m", "13.77m",
"13.74m", "13.64m", "13.44m", "13.30m", "DNS", "DNS", "DNS",
"DNS"), Wind_Speed = c("+0.0", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, "NWI", "NWI", "NWI", "NWI"), DQ = c(0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Event = c("Men Triple Jump",
"Men Triple Jump", "Men Triple Jump", "Men Triple Jump", "Men Triple Jump",
"Men Triple Jump", "Men Triple Jump", "Men Triple Jump", "Men Triple Jump",
"Men Triple Jump", "Men Triple Jump", "Men Triple Jump", "Men Triple Jump",
"Men Triple Jump", "Men Triple Jump", "Men Triple Jump", "Men Triple Jump",
"Men Triple Jump"), Round_1 = c("15.75m", "X", "X", "14.64m",
"14.33m", "14.40m", "14.09m", "13.50m", "X", "13.31m", "13.74m",
"13.62m", "13.44m", "X", NA, NA, NA, NA), Round_1_Wind = c("+0.0",
"+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "-0.3", "-0.1",
"+0.0", "+0.0", "+0.0", "+0.0", "+0.0", NA, NA, NA, NA), Round_2 = c("16.01m",
"X", "14.73m", "14.66m", "14.31m", "14.60m", "14.45m", "13.84m",
"13.39m", "X", "X", "13.64m", "13.15m", "13.30m", NA, NA, NA,
NA), Round_2_Wind = c("+0.0", "+0.0", "+0.0", "+0.0", "+0.0",
"+0.0", "+0.0", "+0.0", "-0.1", "-0.6", "+0.0", "-1.4", "-0.8",
"-1.1", NA, NA, NA, NA), Round_3 = c("X", "14.91m", "X", "14.69m",
"14.28m", "X", "14.25m", "X", "13.79m", "13.77m", "X", "X", "X",
"X", NA, NA, NA, NA), Round_3_Wind = c(NA, "+0.0", "+0.0", "+0.0",
"+0.0", "+0.0", "-0.9", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0",
"+0.0", "+0.0", NA, NA, NA, NA), Round_4 = c("15.91m", "14.34m",
"14.34m", "13.43m", "14.64m", "14.18m", "13.52m", "13.74m", "13.21m",
NA, NA, NA, NA, NA, NA, NA, NA, NA), Round_4_Wind = c("+0.0",
"+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "0.3",
NA, NA, NA, NA, NA, NA, NA, NA, NA), Round_5 = c("15.85m", "X",
"14.14m", "14.56m", "14.60m", "13.94m", "X", "13.68m", "13.76m",
NA, NA, NA, NA, NA, NA, NA, NA, NA), Round_5_Wind = c("+0.0",
"0.2", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0",
NA, NA, NA, NA, NA, NA, NA, NA, NA), Round_6 = c("14.74m", "14.93m",
"14.31m", "X", "14.62m", "14.48m", "13.53m", "X", "X", NA, NA,
NA, NA, NA, NA, NA, NA, NA), Round_6_Wind = c("+0.0", "+0.0",
"+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", "+0.0", NA, NA,
NA, NA, NA, NA, NA, NA, NA)), row.names = c(NA, -18L), class = "data.frame")
expect_equivalent(df_test, df_standard)
})
# testthat::test_file("tests/testthat/test-tf_parse.R")
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