tests/testthat/test-omega.R
In gpilgrim2670/SwimmeR: Data Import, Cleaning, and Conversions for Swimming Results
# testthat::test_file("tests/testthat/test-omega.R")
test_that("Men 400 IM prelims", {
file <-
system.file("extdata", "Omega_OT_400IM_Prelims_2021.pdf", package = "SwimmeR")
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
head(2)
df_standard <- data.frame(
Place = c("1", "2"),
Heat = rep("4", 2),
Lane = c("4", "5"),
Name = c("FOSTER Carson", "KALISZ Chase"),
Team = c("RAYSOH", "ABSC"),
Reaction_Time = c("0.66", "0.69"),
Finals = c("4:10.50", "4:10.61"),
DQ = rep("0", 2),
Exhibition = rep("0", 2),
Event = rep("AM Men's 400m Individual Medley Heats", 2),
Split_50 = c("26.24", "26.48"),
Split_100 = c("29.56", "29.98"),
Split_150 = c("31.76", "32.74"),
Split_200 = c("30.87", "32.10"),
Split_250 = c("35.38", "34.39"),
Split_300 = c("35.69", "34.96"),
Split_350 = c("31.28", "30.94"),
Split_400 = c("29.72", "29.02")
)
expect_equivalent(df_standard,
df_test)
})
test_that("2021 US OT Wave 2 Women 400 Free Heats, swimmers without reaction times", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Omega/Omega_OT_Wave2_W400Fr_Heats_2021.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
filter(Name %in% c("LEDECKY Katie", "NUNAN Amanda", "KILGALLON Abigail", "TWICHELL Ashley"))
df_standard <-
structure(
list(
Place = c("1", "8", "37", "46"),
Heat = c("6",
"6", "2", "1"),
Lane = c("4", "3", "6", "8"),
Name = c(
"LEDECKY Katie",
"TWICHELL Ashley",
"NUNAN Amanda",
"KILGALLON Abigail"
),
Team = c("NCAP",
"TAC-NC", "TNAQ", "UOFM"),
Reaction_Time = c("0.70", "0.77",
NA, NA),
Finals = c("4:03.07", "4:10.51", "4:17.58", "4:23.32"),
DQ = c("0", "0", "0", "0"),
Exhibition = c("0", "0", "0",
"0"),
Event = c(
"AM Women's 400m Freestyle Heats",
"AM Women's 400m Freestyle Heats",
"AM Women's 400m Freestyle Heats",
"AM Women's 400m Freestyle Heats"
),
Split_50 = c("28.10", "29.38", "30.15", "30.96"),
Split_100 = c("30.11",
"31.14", "31.99", "32.38"),
Split_150 = c("30.59", "31.39", "32.53",
"33.15"),
Split_200 = c("30.74", "31.51", "32.79", "32.77"),
Split_250 = c("30.82", "31.79", "32.72", "33.09"),
Split_300 = c("30.98",
"31.98", "32.67", "33.54"),
Split_350 = c("31.13", "32.23",
"32.94", "33.86"),
Split_400 = c("30.60", "31.09", "31.79",
"33.57")
),
row.names = c(NA,-4L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Women 200 fly prelims, need to not remove swimmers for decimal counting", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Omega/Omega_OT_Wave1_W200Fl_Heats_2021.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
head(3)
df_standard <-
structure(
list(
Place = c("1", "2", "3"),
Heat = c("4", "2", "4"),
Lane = c("6", "5", "7"),
Name = c("MASSEY Alex", "STICKLEN Emma",
"CULLEN Casey"),
Team = c("NAC", "KATY", "PWAC"),
Reaction_Time = c("0.73",
"0.72", "0.71"),
Finals = c("2:13.01", "2:13.20", "2:13.76"),
DQ = c("0", "0", "0"),
Exhibition = c("0", "0", "0"),
Event = c(
"AM Women's 200m Butterfly Heats",
"AM Women's 200m Butterfly Heats",
"AM Women's 200m Butterfly Heats"
),
Split_50 = c("29.83", "29.46", "30.67"),
Split_100 = c("33.41",
"33.20", "33.96"),
Split_150 = c("33.99", "34.93", "34.27"),
Split_200 = c("35.78", "35.61", "34.86")
),
row.names = c(NA,
3L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("US OT 2021 Wave I Men 100 Free Heats", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Omega/Omega_OT_Wave1_M100Fr_Heats_2021.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
head(2)
df_standard <-
structure(
list(
Place = c("1", "2"),
Heat = c("3", "4"),
Lane = c("5",
"3"),
Name = c("BENSON Andrew", "MILLER Luke"),
Team = c("WA",
"EA"),
Reaction_Time = c("0.62", "0.62"),
Finals = c("50.10",
"50.13"),
DQ = c("0", "0"),
Exhibition = c("0", "0"),
Event = c("AM Men's 100m Freestyle Heats",
"AM Men's 100m Freestyle Heats"),
Split_50 = c("23.58", "24.22"),
Split_100 = c("26.52", "25.91")
),
row.names = 1:2,
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Women 400m finals", {
file <-
system.file("extdata", "Omega_OT_400m_Finals_2021.pdf", package = "SwimmeR")
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
head(2)
df_standard <- data.frame(
Place = c("1", "2"),
Heat = rep("Final", 2),
Lane = c("4", "5"),
Name = c("LEDECKY Katie", "MADDEN Paige"),
Team = c("NCAP", "UVA"),
Reaction_Time = c("0.65", "0.63"),
Finals = c("4:01.27", "4:04.86"),
DQ = rep("0", 2),
Exhibition = rep("0", 2),
Event = rep("PM Women's 400m Freestyle Final", 2),
Split_50 = c("27.70", "28.10"),
Split_100 = c("29.59", "30.16"),
Split_150 = c("29.95", "30.68"),
Split_200 = c("30.40", "31.06"),
Split_250 = c("30.47", "31.23"),
Split_300 = c("31.24", "31.05"),
Split_350 = c("30.88", "31.24"),
Split_400 = c("31.04", "31.34")
)
expect_equivalent(df_standard,
df_test)
})
test_that("100 br swim off no heat", {
file <-
system.file("extdata", "Omega_OT_100Br_Swimoff_2021.pdf", package = "SwimmeR")
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE)
df_standard <- data.frame(
Place = c("1", "2"),
Heat = rep("Heats", 2),
Lane = c("4", "5"),
Name = c("TYBUR Jonathan", "MASON Mitch"),
Team = c("GSC-FL", "LSU"),
Reaction_Time = c("0.66", "0.68"),
Finals = c("1:00.91", "1:01.93"),
DQ = rep("0", 2),
Exhibition = rep("0", 2),
Event = rep("PM Men's 100m Breaststroke Heats Swim-off", 2),
Split_50 = c("28.17", "29.07"),
Split_100 = c("32.74", "32.86")
)
expect_equivalent(df_standard,
df_test)
})
test_that("wave 1 200 fly", {
file <-
system.file("extdata", "Omega_Wave1_200fly_Finals_2021.pdf", package = "SwimmeR")
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE) %>%
head(2)
df_standard <- data.frame(
Place = c("1", "2"),
Heat = rep("Final", 2),
Lane = c("4", "2"),
Name = c("SUN Eleanor", "THOMAS Luciana"),
Team = c("NCAP", "IA"),
Reaction_Time = c("0.72", "0.76"),
Finals = c("2:13.76", "2:15.32"),
DQ = rep("0", 2),
Exhibition = rep("0", 2),
Event = rep("4 JUN 2021 - 7:23 PM Women's 200m Butterfly Final", 2),
Split_50 = c("29.70", "30.28"),
Split_100 = c("34.09", "33.80"),
Split_150 = c("35.21", "35.20"),
Split_200 = c("34.76", "36.04")
)
expect_equivalent(df_standard,
df_test)
})
test_that("wave 1 1500m", {
file <-
system.file("extdata", "Omega_Wave1_1500_Finals_2021.pdf", package = "SwimmeR")
df <- file %>%
read_results() %>%
swim_parse(splits = TRUE) %>%
filter(Name != "NARVID Jake") # Jake has issues with his reported splits
list_test <- df %>%
dplyr::mutate(dplyr::across(dplyr::starts_with("Split"), sec_format)) %>%
mutate(Split_Total = rowSums(dplyr::across(dplyr::starts_with("Split")), na.rm = TRUE)) %>%
pull(Split_Total)
list_standard <-
c(935.94,
936.24,
940.05,
944.30,
952.72,
954.12,
954.17,
962.61,
964.30,
965.41,
978.49)
expect_equivalent(list_standard,
list_test)
})
test_that("Tokyo 2020 Men 400IM Heat 1", {
skip_on_cran()
file <-
"https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/Tokyo2020/SWMM400MIM_HEAT.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
filter(Heat == "Heat_1")
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5"), Heat = c("Heat_1",
"Heat_1", "Heat_1", "Heat_1", "Heat_1"), Lane = c("5", "4", "3",
"6", "2"), Name = c("LOPES Jose", "PERIBONIO AVILA Tomas", "POLONSKY Ron",
"MEIER Christoph", "VEGA TORRES Luis Emigdio"), Team = c("POR",
"ECU", "ISR", "LIE", "CUB"), Reaction_Time = c("0.66", "0.63",
"0.71", "0.68", "0.69"), Finals = c("4:16.52", "4:18.73",
"4:21.50", "4:25.17", "4:27.65"), DQ = c("0", "0", "0", "0",
"0"), Exhibition = c("0", "0", "0", "0", "0"), Event = c("Men's 400m Individual Medley",
"Men's 400m Individual Medley", "Men's 400m Individual Medley",
"Men's 400m Individual Medley", "Men's 400m Individual Medley"
), Split_50 = c("27.40", "27.11", "27.14", "26.52", "27.65"),
Split_100 = c("30.93", "31.26", "31.90", "30.88", "31.80"
), Split_150 = c("32.52", "33.26", "33.65", "36.28", "34.85"
), Split_200 = c("32.48", "33.00", "33.63", "35.65", "34.26"
), Split_250 = c("37.07", "35.87", "35.44", "36.22", "37.34"
), Split_300 = c("36.66", "36.88", "36.86", "36.84", "38.01"
), Split_350 = c("30.43", "30.75", "31.46", "31.68", "32.24"
), Split_400 = c("29.03", "30.60", "31.42", "31.10", "31.50"
)), row.names = c(NA, -5L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Women 4 x 100m Free Heat 1, checked", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMW4X100MFR_HEAT.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
filter(Heat == "Heat_1")
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7"),
Heat = c("Heat_1", "Heat_1", "Heat_1", "Heat_1", "Heat_1",
"Heat_1", "Heat_1"), Lane = c("5", "4", "2", "6", "3", "7",
"1"), Team = c("GBR - Great Britain", "USA - United States of America",
"DEN - Denmark", "SWE - Sweden", "FRA - France", "BRA - Brazil",
"HKG - Hong Kong, China"), Finals = c("3:34.03", "3:34.80",
"3:35.56", "3:35.93", "3:36.61", "3:39.19", "3:43.52"), DQ = c("0",
"0", "0", "0", "0", "0", "0"), Exhibition = c("0", "0", "0",
"0", "0", "0", "0"), Event = c("Women's 4 x 100m Freestyle Relay",
"Women's 4 x 100m Freestyle Relay", "Women's 4 x 100m Freestyle Relay",
"Women's 4 x 100m Freestyle Relay", "Women's 4 x 100m Freestyle Relay",
"Women's 4 x 100m Freestyle Relay", "Women's 4 x 100m Freestyle Relay"
), Relay_Swimmer_1 = c("HOPE Lucy", "SMOLIGA Olivia", "BLUME Pernille",
"SJOESTROEM Sarah", "GASTALDELLO Beryl", "OLIVEIRA Larissa",
"TAM Hoi Lam"), Relay_Swimmer_2 = c("HOPKIN Anna", "de LOOF Catie",
"BRO Signe", "COLEMAN Michelle", "BONNET Charlotte", "VIEIRA Ana Carolina",
"CHENG Camille Lily Mei"), Relay_Swimmer_3 = c("WOOD Abbie",
"SCHMITT Allison", "JENSEN Julie Kepp", "HANSSON Louise",
"FABRE Margaux", "MEDEIROS Etiene", "AU Hoi Shun Stephanie"
), Relay_Swimmer_4 = c("ANDERSON Freya", "HINDS Natalie",
"OTTESEN Jeanette", "JUNEVIK Sara", "MARTIN Anouchka", "BALDUCCINI Stephanie",
"HO Nam Wai Tinky"), Split_50 = c("26.28", "25.96", "25.33",
"25.47", "25.97", "26.23", "26.50"), Split_100 = c("54.37",
"54.06", "53.15", "52.95", "54.28", "54.79", "55.58"), Split_150 = c("24.87",
"25.02", "25.50", "24.91", "25.35", "26.07", "26.05"), Split_200 = c("52.65",
"53.42", "53.19", "53.44", "53.05", "54.92", "54.61"), Split_250 = c("25.53",
"25.85", "25.56", "25.29", "26.09", "25.95", "26.96"), Split_300 = c("53.55",
"54.04", "54.72", "53.68", "54.83", "55.42", "56.96"), Split_350 = c("25.76",
"25.30", "25.46", "25.87", "25.75", "25.61", "27.43"), Split_400 = c("53.46",
"53.28", "54.50", "55.86", "54.45", "54.06", "56.37")), row.names = c(NA,
-7L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Women 100 Breast Heats, with DNS", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMW100MBR_HEAT.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE,
typo = "RODRIGUEZ VILLANUEVA Byanca MelissaMEX",
replacement = "RODRIGUEZ VILLANUEVA Byanca Melissa MEX")
df_standard <-
structure(
list(
Place = c(
"1",
"2",
"3",
"4",
"5",
"6",
NA,
"1",
"2",
"3",
"4",
"5",
"6",
"7",
NA,
"1",
"2",
"3",
"4",
"5",
"6",
"7",
"8",
"1",
"2",
"3",
"4",
"5",
"6",
"7",
NA,
"1",
"2",
"3",
"4",
"5",
"6",
"7",
NA,
"1",
"2",
"3",
"4",
"5",
"6",
"7",
"8"
),
Heat = c(
"Heat_1",
"Heat_1",
"Heat_1",
"Heat_1",
"Heat_1",
"Heat_1",
"Heat_1",
"Heat_2",
"Heat_2",
"Heat_2",
"Heat_2",
"Heat_2",
"Heat_2",
"Heat_2",
"Heat_2",
"Heat_3",
"Heat_3",
"Heat_3",
"Heat_3",
"Heat_3",
"Heat_3",
"Heat_3",
"Heat_3",
"Heat_4",
"Heat_4",
"Heat_4",
"Heat_4",
"Heat_4",
"Heat_4",
"Heat_4",
"Heat_4",
"Heat_5",
"Heat_5",
"Heat_5",
"Heat_5",
"Heat_5",
"Heat_5",
"Heat_5",
"Heat_5",
"Heat_6",
"Heat_6",
"Heat_6",
"Heat_6",
"Heat_6",
"Heat_6",
"Heat_6",
"Heat_6"
),
Lane = c(
"3",
"5",
"4",
"2",
"7",
"6",
NA,
"3",
"5",
"7",
"4",
"6",
"8",
"2",
NA,
"1",
"2",
"6",
"4",
"5",
"7",
"3",
"8",
"4",
"3",
"2",
"6",
"1",
"7",
"8",
NA,
"5",
"4",
"6",
"3",
"7",
"2",
"1",
NA,
"4",
"5",
"3",
"6",
"8",
"2",
"7",
"1"
),
Name = c(
"GRAND PIERRE Emilie Faith",
"SEMYONOVA Darya",
"PINA Jayla",
"ADAMS Taeyanna",
"BA MATRAF Nooran",
"SAJINA Aishath",
"TOURE Mariama",
"PODMANIKOVA Andrea",
"PHEE Jinq En",
"SCANLAN Tilali",
"RAJIC Ema",
"SANTOS SILVA Emily M",
"FISHER-MARSTERS Kirsten Andrea",
"KOK SHUN Alicia",
"VERDINO Claudia",
"TETEREVKOVA Kotryna",
"ELENDT Anna Charlott Darcel",
"ATKINSON Alia",
"SCHOUTEN Tes",
"LECLUYSE Fanny",
"RODRIGUEZ VILLANUEVA Byanca Melissa",
"SEBASTIAN Julia",
"PETKOVA Diana",
"EFIMOVA Yuliya",
"TANG Qianting",
"WATANABE Kanako",
"AOKI Reona",
"HANSEN Jessica",
"ZMUSHKA Alina",
"WOG Kelsey Lauren",
"PILATO Benedetta",
"SCHOENMAKER Tatjana",
"JACOBY Lydia",
"Mc SHARRY Mona",
"HODGES Chelsea",
"MAMIE Lisa",
"JEFIMOVA Eneli",
"VALL MONTERO Jessica",
"GORBENKO Anastasia",
"KING Lilly",
"HANSSON Sophie",
"CARRARO Martina",
"CHIKUNOVA Evgeniia",
"HULKKO Ida",
"VASEY Sarah",
"SMITH Kierra",
"FAST Emelie"
),
Team = c(
"HAI",
"TKM",
"CPV",
"FSM",
"YEM",
"MDV",
"GUI",
"SVK",
"MAS",
"ASA",
"CRO",
"PAN",
"COK",
"MRI",
"MON",
"LTU",
"GER",
"JAM",
"NED",
"BEL",
"MEX",
"ARG",
"BUL",
"ROC",
"CHN",
"JPN",
"JPN",
"AUS",
"BLR",
"CAN",
"ITA",
"RSA",
"USA",
"IRL",
"AUS",
"SUI",
"EST",
"ESP",
"ISR",
"USA",
"SWE",
"ITA",
"ROC",
"FIN",
"GBR",
"CAN",
"SWE"
),
Reaction_Time = c(
"0.67",
"0.65",
"0.69",
"0.73",
"0.73",
"0.72",
NA,
"0.66",
"0.70",
"0.71",
"0.71",
"0.69",
"0.68",
"0.60",
NA,
"0.70",
"0.72",
"0.67",
"0.66",
"0.71",
"0.65",
"0.66",
"0.74",
"0.69",
"0.73",
"0.69",
"0.62",
"0.72",
"0.70",
"0.63",
NA,
"0.67",
"0.67",
"0.67",
"0.70",
"0.71",
"0.67",
"0.69",
NA,
"0.71",
"0.72",
"0.61",
"0.71",
"0.65",
"0.67",
"0.76",
"0.65"
),
Finals = c(
"1:14.82",
"1:16.37",
"1:16.96",
"1:25.36",
"1:27.79",
"1:33.59",
NA,
"1:08.36",
"1:08.40",
"1:10.01",
"1:10.02",
"1:12.10",
"1:13.98",
"1:15.42",
NA,
"1:06.82",
"1:06.96",
"1:07.70",
"1:07.89",
"1:07.93",
"1:08.76",
"1:09.35",
"1:10.61",
"1:06.21",
"1:06.47",
"1:07.01",
"1:07.29",
"1:07.50",
"1:07.58",
"1:07.73",
NA,
"1:04.82",
"1:05.52",
"1:06.39",
"1:06.70",
"1:06.76",
"1:06.79",
"1:07.07",
NA,
"1:05.55",
"1:05.66",
"1:05.85",
"1:06.16",
"1:06.19",
"1:06.61",
"1:07.87",
"1:07.98"
),
DQ = c(
"0",
"0",
"0",
"0",
"0",
"0",
"1",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"1",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"1",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"1",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0"
),
Exhibition = 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",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0"
),
Event = c(
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke"
),
Split_50 = c(
"34.33",
"34.22",
"34.18",
"39.75",
"41.53",
"44.17",
NA,
"32.10",
"32.50",
"33.22",
"32.10",
"33.18",
"34.16",
"34.60",
NA,
"31.61",
"31.57",
"31.48",
"32.09",
"31.57",
"31.77",
"32.32",
"32.81",
"30.92",
"30.81",
"31.39",
"31.01",
"31.85",
"31.76",
"31.82",
NA,
"30.21",
"30.99",
"31.06",
"30.86",
"31.42",
"31.76",
"32.02",
NA,
"30.74",
"31.01",
"31.06",
"31.63",
"30.55",
"31.30",
"32.09",
"31.23"
),
Split_100 = c(
"40.49",
"42.15",
"42.78",
"45.61",
"46.26",
"49.42",
NA,
"36.26",
"35.90",
"36.79",
"37.92",
"38.92",
"39.82",
"40.82",
NA,
"35.21",
"35.39",
"36.22",
"35.80",
"36.36",
"36.99",
"37.03",
"37.80",
"35.29",
"35.66",
"35.62",
"36.28",
"35.65",
"35.82",
"35.91",
NA,
"34.61",
"34.53",
"35.33",
"35.84",
"35.34",
"35.03",
"35.05",
NA,
"34.81",
"34.65",
"34.79",
"34.53",
"35.64",
"35.31",
"35.78",
"36.75"
)
),
row.names = c(NA,-47L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Men 100 Fly Semis, with ORs broken", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMM100MBF_SFNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c(
"1",
"2",
"3",
"4",
"5",
"6",
"7",
"8",
"1",
"2",
"3",
"4",
"5",
"6",
"7",
"8"
),
Heat = c(
"Semi_1",
"Semi_1",
"Semi_1",
"Semi_1",
"Semi_1",
"Semi_1",
"Semi_1",
"Semi_1",
"Semi_2",
"Semi_2",
"Semi_2",
"Semi_2",
"Semi_2",
"Semi_2",
"Semi_2",
"Semi_2"
),
Lane = c(
"4",
"3",
"5",
"6",
"2",
"7",
"8",
"1",
"4",
"3",
"5",
"6",
"2",
"7",
"8",
"1"
),
Name = c(
"MILAK Kristof",
"MILADINOV Josif",
"MINAKOV Andrei",
"TEMPLE Matthew",
"METELLA Mehdy",
"MIZUNUMA Naoki",
"SUN Jiajun",
"RAMADAN Youssef",
"DRESSEL Caeleb",
"PONTI Noe",
"MAJERSKI Jakub",
"MARTINEZ Luis Carlos",
"LIENDO EDWARDS Joshua",
"KORSTANJE Nyls",
"SZABO Szebasztian",
"SHIELDS Tom"
),
Team = c(
"HUN",
"BUL",
"ROC",
"AUS",
"FRA",
"JPN",
"CHN",
"EGY",
"USA",
"SUI",
"POL",
"GUA",
"CAN",
"NED",
"HUN",
"USA"
),
Reaction_Time = c(
"0.66",
"0.65",
"0.63",
"0.63",
"0.65",
"0.60",
"0.64",
"0.61",
"0.62",
"0.69",
"0.64",
"0.62",
"0.63",
"0.61",
"0.58",
"0.71"
),
Finals = c(
"50.31",
"51.06",
"51.11",
"51.12",
"51.32",
"51.46",
"51.82",
"52.27",
"49.71",
"50.76",
"51.24",
"51.30",
"51.50",
"51.80",
"51.89",
"51.99"
),
DQ = c(
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0"
),
Exhibition = c(
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0"
),
Event = c(
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly"
),
Split_50 = c(
"23.74",
"24.02",
"23.73",
"23.88",
"23.73",
"24.04",
"23.88",
"23.78",
"23.20",
"23.72",
"24.10",
"24.23",
"23.88",
"23.54",
"23.79",
"24.07"
),
Split_100 = c(
"26.57",
"27.04",
"27.38",
"27.24",
"27.59",
"27.42",
"27.94",
"28.49",
"26.51",
"27.04",
"27.14",
"27.07",
"27.62",
"28.26",
"28.10",
"27.92"
)
),
row.names = c(NA, -16L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Women 400MR Finals, with record issues", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMW4X100MMD_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c("1", "2", "3", "4", "5", "6", "7", "8"),
Heat = rep("Final", 8),
Lane = c("3", "5", "4", "8", "2", "6", "1", "7"),
Team = c(
"AUS - Australia",
"USA - United States of America",
"CAN - Canada",
"CHN - People's Republic of China",
"SWE - Sweden",
"ITA - Italy",
"ROC - ROC",
"JPN - Japan"
),
Finals = c(
"3:51.60",
"3:51.73",
"3:52.60",
"3:54.13",
"3:54.27",
"3:56.68",
"3:56.93",
"3:58.12"
),
DQ = c("0", "0", "0", "0", "0", "0", "0", "0"),
Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"),
Event = c(
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay"
),
Relay_Swimmer_1 = c(
"McKEOWN Kaylee",
"SMITH Regan",
"MASSE Kylie",
"PENG Xuwei",
"COLEMAN Michelle",
"PANZIERA Margherita",
"KAMENEVA Mariia",
"KONISHI Anna"
),
Relay_Swimmer_2 = c(
"HODGES Chelsea",
"JACOBY Lydia",
"PICKREM Sydney",
"TANG Qianting",
"HANSSON Sophie",
"CARRARO Martina",
"CHIKUNOVA Evgeniia",
"WATANABE Kanako"
),
Relay_Swimmer_3 = c(
"McKEON Emma",
"HUSKE Torri",
"MACNEIL Margaret",
"ZHANG Yufei",
"HANSSON Louise",
"di LIDDO Elena",
"CHIMROVA Svetlana",
"IKEE Rikako"
),
Relay_Swimmer_4 = c(
"CAMPBELL Cate",
"WEITZEIL Abbey",
"OLEKSIAK Penny",
"YANG Junxuan",
"SJOESTROEM Sarah",
"PELLEGRINI Federica",
"SURKOVA Arina",
"IGARASHI Chihiro"
),
Split_50 = c(
"28.57",
"28.44",
"27.92",
"28.99",
"28.64",
"29.29",
"29.26",
"29.32"
),
Split_100 = c(
"58.01",
"58.05",
"57.90",
"59.63",
"59.75",
"1:00.03",
"59.95",
"59.92"
),
Split_150 = c(
"30.58",
"30.48",
"31.57",
"30.74",
"30.71",
"30.31",
"31.20",
"31.35"
),
Split_200 = c(
"1:05.57",
"1:05.03",
"1:07.17",
"1:06.09",
"1:05.67",
"1:05.88",
"1:05.99",
"1:06.61"
),
Split_250 = c(
"25.86",
"25.42",
"25.58",
"25.48",
"25.86",
"26.63",
"26.21",
"26.81"
),
Split_300 = c(
"55.91",
"56.16",
"55.27",
"55.39",
"56.12",
"56.96",
"56.70",
"57.92"
),
Split_350 = c(
"24.78",
"24.91",
"25.06",
"25.37",
"25.27",
"25.76",
"25.37",
"25.63"
),
Split_400 = c(
"52.11",
"52.49",
"52.26",
"53.02",
"52.73",
"53.81",
"54.29",
"53.67"
)
),
row.names = c(NA, -8L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Mixed 4x100MR Finals, relay swimmer gender", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMX4X100MMD_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c("1", "2", "3", "4", "5", "6", "7", "8"),
Heat = rep("Final", 8),
Lane = c("4", "3", "6", "2", "5", "7", "1", "8"),
Team = c(
"GBR - Great Britain",
"CHN - People's Republic of China",
"AUS - Australia",
"ITA - Italy",
"USA - United States of America",
"NED - Netherlands",
"ROC - ROC",
"ISR - Israel"
),
Finals = c(
"3:37.58",
"3:38.86",
"3:38.95",
"3:39.28",
"3:40.58",
"3:41.25",
"3:42.45",
"3:44.77"
),
DQ = c("0",
"0", "0", "0", "0", "0", "0", "0"),
Exhibition = c("0", "0",
"0", "0", "0", "0", "0", "0"),
Event = c(
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay"
),
Relay_Swimmer_1 = c(
"DAWSON Kathleen",
"XU Jiayu",
"McKEOWN Kaylee",
"CECCON Thomas",
"MURPHY Ryan",
"TOUSSAINT Kira",
"RYLOV Evgeny",
"GORBENKO Anastasia"
),
Relay_Swimmer_1_Gender = c("F",
"M", "F", "M", "M", "F", "M", "F"),
Relay_Swimmer_2 = c(
"PEATY Adam",
"YAN Zibei",
"STUBBLETY-COOK Izaac",
"MARTINENGHI Nicolo",
"JACOBY Lydia",
"KAMMINGA Arno",
"PRIGODA Kirill",
"GOLDFADEN Itay"
),
Relay_Swimmer_2_Gender = c("M",
"M", "M", "M", "F", "M", "M", "M"),
Relay_Swimmer_3 = c(
"GUY James",
"ZHANG Yufei",
"TEMPLE Matthew",
"di LIDDO Elena",
"HUSKE Torri",
"KORSTANJE Nyls",
"CHIMROVA Svetlana",
"COHEN GROUMI Gal"
),
Relay_Swimmer_3_Gender = c("M",
"F", "M", "F", "F", "M", "F", "M"),
Relay_Swimmer_4 = c(
"HOPKIN Anna",
"YANG Junxuan",
"McKEON Emma",
"PELLEGRINI Federica",
"DRESSEL Caeleb",
"HEEMSKERK Femke",
"KAMENEVA Mariia",
"MUREZ Andrea"
),
Relay_Swimmer_4_Gender = c("F",
"F", "F", "F", "M", "F", "F", "F"),
Split_50 = c(
"28.35",
"25.33",
"28.46",
"25.65",
"25.09",
"28.41",
"26.06",
"29.08"
),
Split_100 = c(
"58.80",
"52.56",
"58.14",
"52.23",
"52.23",
"59.45",
"52.79",
"59.55"
),
Split_150 = c(
"26.18",
"26.96",
"27.60",
"27.16",
"29.99",
"26.61",
"27.40",
"27.05"
),
Split_200 = c(
"56.78",
"58.11",
"58.82",
"57.73",
"1:05.09",
"57.89",
"59.15",
"59.86"
),
Split_250 = c(
"23.22",
"25.44",
"23.55",
"26.49",
"25.41",
"22.82",
"26.06",
"23.84"
),
Split_300 = c(
"50.00",
"55.48",
"50.26",
"56.62",
"56.27",
"51.34",
"56.95",
"51.58"
),
Split_350 = c(
"24.66",
"25.04",
"24.88",
"25.29",
"22.15",
"24.91",
"25.74",
"25.91"
),
Split_400 = c(
"52.00",
"52.71",
"51.73",
"52.70",
"46.99",
"52.57",
"53.56",
"53.78"
)
),
row.names = c(NA,-8L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Men 200FR Finals, need to capture swims", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMM200MFR_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c("1", "2", "3", "4", "5", "6", "7", "8"),
Heat = rep("Final", 8),
Lane = c("6", "4", "8", "1", "2", "5", "7", "3"),
Name = c(
"DEAN Tom",
"SCOTT Duncan",
"SCHEFFER Fernando",
"POPOVICI David",
"MALYUTIN Martin",
"SMITH Kieran",
"HWANG Sunwoo",
"RAPSYS Danas"
),
Team = c("GBR",
"GBR", "BRA", "ROU", "ROC", "USA", "KOR", "LTU"),
Reaction_Time = c("0.64",
"0.66", "0.66", "0.68", "0.70", "0.69", "0.58", "0.65"),
Finals = c(
"1:44.22",
"1:44.26",
"1:44.66",
"1:44.68",
"1:45.01",
"1:45.12",
"1:45.26",
"1:45.78"
),
DQ = c("0", "0", "0", "0", "0", "0", "0", "0"),
Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"),
Event = c(
"Men's 200m Freestyle",
"Men's 200m Freestyle",
"Men's 200m Freestyle",
"Men's 200m Freestyle",
"Men's 200m Freestyle",
"Men's 200m Freestyle",
"Men's 200m Freestyle",
"Men's 200m Freestyle"
),
Split_50 = c(
"24.21",
"24.81",
"24.24",
"24.23",
"25.03",
"24.58",
"23.95",
"24.96"
),
Split_100 = c(
"26.25",
"26.57",
"26.01",
"26.50",
"26.62",
"26.36",
"25.83",
"27.00"
),
Split_150 = c(
"26.92",
"26.42",
"27.03",
"27.24",
"26.78",
"26.87",
"26.78",
"26.87"
),
Split_200 = c(
"26.84",
"26.46",
"27.38",
"26.71",
"26.58",
"27.31",
"28.70",
"26.95"
)
),
row.names = c(NA, -8L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Men 4x200FR Finals, need to not capture splits as swims",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMM4X200MFR_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c("1", "2", "3", "4", "5", "6", "7", "8"),
Heat = rep("Final", 8),
Lane = c("4", "6", "5", "2", "3", "7", "1", "8"),
Team = c(
"GBR - Great Britain",
"ROC - ROC",
"AUS - Australia",
"USA - United States of America",
"ITA - Italy",
"SUI - Switzerland",
"GER - Germany",
"BRA - Brazil"
),
Finals = c(
"6:58.58",
"7:01.81",
"7:01.84",
"7:02.43",
"7:03.24",
"7:06.12",
"7:06.51",
"7:08.22"
),
DQ = c("0", "0",
"0", "0", "0", "0", "0", "0"),
Exhibition = c("0", "0", "0",
"0", "0", "0", "0", "0"),
Event = c(
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay"
),
Relay_Swimmer_1 = c(
"DEAN Tom",
"MALYUTIN Martin",
"GRAHAM Alexander",
"SMITH Kieran",
"BALLO Stefano",
"DJAKOVIC Antonio",
"MARTENS Lukas",
"SCHEFFER Fernando"
),
Relay_Swimmer_2 = c(
"GUY James",
"GIREV Ivan",
"CHALMERS Kyle",
"KIBLER Drew",
"CIAMPI Matteo",
"LIESS Nils",
"ZELLMANN Poul",
"SETIN SARTORI Murilo"
),
Relay_Swimmer_3 = c(
"RICHARDS Matthew",
"RYLOV Evgeny",
"INCERTI Zac",
"APPLE Zach",
"MEGLI Filippo",
"PONTI Noe",
"MUHLLEITNER Henning Bennet",
"CORREIA Breno"
),
Relay_Swimmer_4 = c(
"SCOTT Duncan",
"DOVGALYUK Mikhail",
"NEILL Thomas",
"HAAS Townley",
"di COLA Stefano",
"MITYUKOV Roman",
"HEIDTMANN Jacob",
"MELO Luiz Altamir"
),
Split_50 = c(
"24.55",
"24.77",
"24.94",
"24.37",
"24.98",
"24.89",
"25.20",
"24.70"
),
Split_100 = c(
"51.26",
"51.62",
"51.65",
"50.62",
"51.68",
"51.81",
"52.14",
"51.08"
),
Split_150 = c(
"1:18.38",
"1:18.81",
"1:18.80",
"1:17.59",
"1:18.76",
"1:19.22",
"1:19.58",
"1:18.31"
),
Split_200 = c(
"1:45.72",
"1:45.69",
"1:46.00",
"1:44.74",
"1:45.77",
"1:45.77",
"1:46.68",
"1:45.93"
),
Split_250 = c(
"23.84",
"24.26",
"24.01",
"24.29",
"24.62",
"24.17",
"24.23",
"24.63"
),
Split_300 = c(
"50.31",
"50.96",
"50.82",
"50.95",
"51.58",
"51.03",
"51.34",
"51.61"
),
Split_350 = c(
"1:17.31",
"1:18.20",
"1:17.95",
"1:18.18",
"1:18.78",
"1:19.08",
"1:19.06",
"1:18.78"
),
Split_400 = c(
"1:44.40",
"1:45.63",
"1:45.35",
"1:45.51",
"1:45.88",
"1:47.74",
"1:46.30",
"1:46.09"
),
Split_450 = c(
"23.88",
"24.19",
"24.13",
"23.80",
"24.20",
"24.66",
"25.21",
"24.63"
),
Split_500 = c(
"50.70",
"51.06",
"50.84",
"50.54",
"50.78",
"51.85",
"52.52",
"51.93"
),
Split_550 = c(
"1:18.14",
"1:18.54",
"1:18.37",
"1:18.31",
"1:18.26",
"1:19.63",
"1:20.20",
"1:20.04"
),
Split_600 = c(
"1:45.01",
"1:45.26",
"1:45.75",
"1:47.31",
"1:45.33",
"1:46.93",
"1:48.04",
"1:48.11"
),
Split_650 = c(
"23.64",
"23.86",
"23.93",
"23.82",
"23.92",
"24.11",
"24.39",
"23.77"
),
Split_700 = c(
"49.86",
"50.14",
"50.49",
"50.04",
"50.41",
"51.01",
"50.99",
"50.47"
),
Split_750 = c(
"1:16.65",
"1:17.47",
"1:17.65",
"1:17.40",
"1:17.80",
"1:18.48",
"1:17.99",
"1:18.45"
),
Split_800 = c(
"1:43.45",
"1:45.23",
"1:44.74",
"1:44.87",
"1:46.26",
"1:45.68",
"1:45.49",
"1:48.09"
)
),
row.names = c(NA, -8L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Women 4x200FR Heats, relay swimmers with punctuation in name",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMW4X200MFR_HEAT.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"1", "2", "3", "4", "5", "6", "8", "2"), Heat = c("Heat_1", "Heat_1",
"Heat_1", "Heat_1", "Heat_1", "Heat_1", "Heat_1", "Heat_1", "Heat_2",
"Heat_2", "Heat_2", "Heat_2", "Heat_2", "Heat_2", "Heat_2", "Heat_2"
), Lane = c("4", "5", "3", "2", "6", "1", "7", "8", "4", "5",
"3", "6", "7", "1", NA, NA), Team = c("USA - United States of America",
"CHN - People's Republic of China", "GER - Germany", "FRA - France",
"JPN - Japan", "RSA - South Africa", "TUR - Turkey", "KOR - Republic of Korea",
"AUS - Australia", "CAN - Canada", "ROC - ROC", "HUN - Hungary",
"BRA - Brazil", "NZL - New Zealand", "HKG - Hong Kong, China",
"ITA - Italy"), Finals = c("7:47.57", "7:48.98", "7:52.06", "7:55.05",
"7:58.39", "8:01.56", "8:10.96", "8:11.16", "7:44.61", "7:51.52",
"7:52.04", "7:56.16", "7:59.50", "8:06.16", NA, NA), DQ = c("0",
"0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0",
"1", "1"), Exhibition = c("0", "0", "0", "0", "0", "0", "0",
"0", "0", "0", "0", "0", "0", "0", "0", "0"), Event = c("Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay"), Relay_Swimmer_1 = c("SIMS Arabella",
"TANG Muhan", "GOSE Isabel", "BONNET Charlotte", "IGARASHI Chihiro",
"CANNY Aimee", "GUNES Viktoria", "JUNG Hyunyoung", "O'CALLAGHAN Mollie",
"SAVARD Katerine", "GUZHENKOVA Anastasia", "JAKABOS Zsuzsanna",
"RODRIGUES Aline", "FAIRWEATHER Erika", NA, "PIROZZI Stefania"
), Relay_Swimmer_2 = c("MADDEN Paige", "ZHANG Yifan", "KULLMANN Leonie Marlen",
"TOUATI Assia", "SHIRAI Rio", "MEDER Rebecca", "BOCEKLER Beril",
"KIM Seoyeong", "HARRIS Meg", "SMITH Rebecca", "SALAMATINA Valeriia",
"VERES Laura", "OLIVEIRA Larissa", "DOYLE Carina", NA, "MASCOLO Anna Chiara"
), Relay_Swimmer_3 = c("Mc LAUGHLIN Kathryn", "DONG Jie", "PIETRUSCHKA Marie",
"TESSARIOL Lucile", "IKEMOTO Nagisa", "COETZEE Dune", "ERTAN Deniz",
"HAN Dakyung", "THROSSELL Brianna", "HARVEY Mary-Sophie", "ANDRUSENKO Veronika",
"VERRASZTO Evelin", "ALMEIDA Nathalia", "THOMAS Eve", NA, NA),
Relay_Swimmer_4 = c("FORDE Brooke", "LI Bingjie", "BRUHN Annika",
"FABRE Margaux", "MASUDA Aoi", "GALLAGHER Erin", "TUNCEL Merve",
"AN Sehyeon", "COOK Tamsin", "PICKREM Sydney", "EGOROVA Anna",
"KESELY Ajna", "RONCATTO Gabrielle", "GALYER Ali", NA, NA
), Split_50 = c("27.56", "27.13", "27.59", "27.42", "27.52",
"27.66", "28.37", "28.09", "27.25", "27.38", "27.73", "28.18",
"28.04", "27.30", NA, "28.16"), Split_100 = c("57.35", "56.68",
"57.13", "57.46", "57.66", "57.40", "59.39", "58.78", "56.94",
"57.31", "57.45", "58.47", "57.99", "56.97", NA, "58.36"),
Split_150 = c("1:28.05", "1:26.86", "1:27.33", "1:27.81",
"1:28.17", "1:27.38", "1:31.71", "1:30.08", "1:26.70", "1:27.28",
"1:27.36", "1:28.78", "1:29.13", "1:27.34", NA, "1:29.74"
), Split_200 = c("1:58.59", "1:57.29", "1:57.29", "1:57.61",
"1:57.87", "1:58.41", "2:04.42", "2:01.27", "1:55.11", "1:58.18",
"1:57.26", "1:59.19", "2:00.15", "1:57.38", NA, "2:01.64"
), Split_250 = c("27.01", "26.60", "27.59", "27.46", "27.45",
"27.35", "28.33", "27.69", "25.87", "26.59", "27.70", "27.17",
"27.29", "28.01", NA, NA), Split_300 = c("55.94", "56.43",
"57.19", "57.68", "58.18", "57.76", "59.31", "58.08", "55.03",
"55.93", "57.84", "56.74", "57.28", "59.13", NA, NA), Split_350 = c("1:25.60",
"1:27.17", "1:27.69", "1:28.27", "1:29.10", "1:28.84", "1:30.91",
"1:28.87", "1:25.70", "1:25.87", "1:28.78", "1:27.11", "1:28.93",
"1:30.57", NA, NA), Split_400 = c("1:55.96", "1:57.63", "1:59.00",
"1:58.59", "1:59.94", "2:00.53", "2:02.03", "1:59.98", "1:57.01",
"1:55.99", "1:58.87", "1:57.88", "2:01.50", "2:02.18", NA,
NA), Split_450 = c("26.45", "27.15", "27.65", "27.93", "26.88",
"27.32", "28.48", "28.21", "26.11", "26.65", "27.34", "27.94",
"27.62", "28.64", NA, NA), Split_500 = c("55.68", "56.52",
"58.03", "58.38", "57.15", "57.59", "1:00.20", "59.50", "55.61",
"56.28", "57.13", "58.62", "57.44", "59.87", NA, NA), Split_550 = c("1:25.66",
"1:26.74", "1:28.45", "1:28.79", "1:28.43", "1:28.46", "1:32.34",
"1:32.01", "1:25.91", "1:26.66", "1:27.81", "1:29.56", "1:28.39",
"1:30.62", NA, NA), Split_600 = c("1:56.02", "1:57.77", "1:58.73",
"1:59.39", "2:00.25", "1:59.75", "2:04.15", "2:04.38", "1:56.46",
"1:57.53", "1:57.77", "2:00.35", "1:59.18", "2:00.75", NA,
NA), Split_650 = c("27.52", "26.92", "26.58", "27.07", "27.06",
"27.16", "28.54", "28.67", "26.77", "27.27", "27.24", "26.79",
"27.53", "28.44", NA, NA), Split_700 = c("56.73", "56.65",
"55.71", "57.07", "57.22", "57.85", "59.54", "1:00.60", "56.14",
"57.86", "57.24", "56.52", "57.71", "1:00.45", NA, NA), Split_750 = c("1:26.75",
"1:26.76", "1:26.14", "1:28.21", "1:28.56", "1:29.78", "1:30.43",
"1:33.35", "1:26.08", "1:29.54", "1:27.56", "1:27.17", "1:28.31",
"1:33.23", NA, NA), Split_800 = c("1:57.00", "1:56.29", "1:57.04",
"1:59.46", "2:00.33", "2:02.87", "2:00.36", "2:05.53", "1:56.03",
"1:59.82", "1:58.14", "1:58.74", "1:58.67", "2:05.85", NA,
NA)), row.names = c(NA, -16L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo Men 50 Free Final, need to not pull out relay swimmers",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMM50MFR_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c("1", "2", "3", "4", "5", "5", "7", "8"),
Heat = rep("Final", 8),
Lane = c("4", "5", "3", "7", "2", "6", "1", "8"),
Name = c(
"DRESSEL Caeleb",
"MANAUDOU Florent",
"FRATUS Bruno",
"ANDREW Michael",
"PROUD Benjamin",
"GKOLOMEEV Kristian",
"ZAZZERI Lorenzo",
"de BOER Thom"
),
Team = c("USA",
"FRA", "BRA", "USA", "GBR", "GRE", "ITA", "NED"),
Reaction_Time = c("0.63",
"0.61", "0.64", "0.66", "0.58", "0.63", "0.61", "0.63"),
Finals = c(
"21.07",
"21.55",
"21.57",
"21.60",
"21.72",
"21.72",
"21.78",
"21.79"
),
DQ = c("0", "0", "0", "0", "0", "0", "0", "0"),
Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"),
Event = c(
"Men's 50m Freestyle",
"Men's 50m Freestyle",
"Men's 50m Freestyle",
"Men's 50m Freestyle",
"Men's 50m Freestyle",
"Men's 50m Freestyle",
"Men's 50m Freestyle",
"Men's 50m Freestyle"
),
Split_50 = c(
"21.07",
"21.55",
"21.57",
"21.60",
"21.72",
"21.72",
"21.78",
"21.79"
)
),
row.names = c(NA,-8L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
#### Para 2020 ####
test_that("Tokyo Para SM6 200 IM Final, swimmer with long name distorts pdf format",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/SwimmeR%20Test%20Files/PG2020_SWMM200MIM_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8"
), Heat = c("Final", "Final", "Final", "Final", "Final", "Final",
"Final", "Final"), Lane = c("4", "5", "3", "2", "8", "7", "6",
"1"), Name = c("CRISPIN CORZO Nelson", "GRANICHKA Andrei", "JIA Hongguang",
"YANG Hong", "WANG Jingang", "GLOCK Talisson Henrique", "GUTIERREZ BERMUDEZ Juan Jose",
"SHATTUCK Zach"), Para = c("SM6", "SM6", "SM6", "SM6", "SM6",
"SM6", NA, "SM6"), Team = c("COL", "RPC", "CHN", "CHN", "CHN",
"BRA", "MEX", "USA"), Reaction_Time = c("0.66", "0.79", "0.92",
"0.76", "0.90", "0.90", "0.58", "0.52"), Finals = c("2:38.12",
"2:40.92", "2:41.29", "2:41.34", "2:43.74", "2:45.17", "2:48.79",
"2:52.52"), DQ = c("0", "0", "0", "0", "0", "0", "0", "0"), Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"), Event = c("Men's 200m Individual Medley - SM6",
"Men's 200m Individual Medley - SM6", "Men's 200m Individual Medley - SM6",
"Men's 200m Individual Medley - SM6", "Men's 200m Individual Medley - SM6",
"Men's 200m Individual Medley - SM6", "Men's 200m Individual Medley - SM6",
"Men's 200m Individual Medley - SM6"), Split_50 = c("31.62",
"34.54", "33.19", "35.40", "31.81", "34.43", "34.73", "35.15"
), Split_100 = c("42.56", "43.08", "39.76", "40.97", "41.59",
"43.50", "45.60", "47.50"), Split_150 = c("45.97", "46.84", "49.52",
"45.46", "49.97", "51.71", "46.90", "47.10"), Split_200 = c("37.97",
"36.46", "38.82", "39.51", "40.37", "35.53", "41.56", "42.77"
)), row.names = c(NA, -8L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo Para S11 50 Free Heats, DNS",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/SwimmeR%20Test%20Files/PG2020_SWMM50MFR_HEAT.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "1",
"2", "3", "4", "5", "6", "7", NA), Heat = c("Heat_1", "Heat_1",
"Heat_1", "Heat_1", "Heat_1", "Heat_1", "Heat_1", "Heat_2", "Heat_2",
"Heat_2", "Heat_2", "Heat_2", "Heat_2", "Heat_2", "Heat_2"),
Lane = c("4", "6", "5", "3", "7", "2", "1", "4", "5", "3",
"6", "7", "8", "1", "2"), Name = c("BELARMINO PEREIRA Wendell",
"RHEINE CORREA de SOUZA Matheus", "YANG Bozun", "SERBIN Mykhailo",
"MENESES Marco", "SMYRNOV Viktor", "GUNNARSSON Mar", "MATAKAS Edgaras",
"HUA Dongdong", "MAKOWSKI Wojciech", "CABRAJA Matthew", "GARIPOV Ilnur",
"DRAG Przemyslaw", "ARTIUKHOV Oleksandr", "ZUDZILAU Hryhory"
), Para = c("S11", "S11", "S11", "S11", "S11", "S11", "S11",
"S11", "S11", "S11", "S11", "S11", "S11", "S11", "S11"),
Team = c("BRA", "BRA", "CHN", "UKR", "POR", "UKR", "ISL",
"LTU", "CHN", "POL", "CAN", "RPC", "POL", "UKR", "BLR"),
Reaction_Time = c("0.69", "0.69", "0.76", "0.75", "0.87",
"0.84", "0.75", "0.61", "0.75", "0.78", "0.70", "0.68", "0.74",
"0.74", NA), Finals = c("26.47", "27.17", "27.19", "27.44",
"28.07", "28.31", "29.30", "26.16", "26.55", "27.92", "28.13",
"28.39", "29.02", "30.29", NA), DQ = c("0", "0", "0", "0",
"0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "1"), Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0",
"0", "0"), Event = c("Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11"), Split_50 = c("26.47", "27.17",
"27.19", "27.44", "28.07", "28.31", "29.30", "26.16", "26.55",
"27.92", "28.13", "28.39", "29.02", "30.29", NA)), row.names = c(NA,
-15L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo Para Mixed 4x100 Free Relay 49 Points",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/SwimmeR%20Test%20Files/PG2020_SWMX4X100MFR_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6"), Heat = c("Final",
"Final", "Final", "Final", "Final", "Final"), Lane = c("3", "5",
"4", "6", "2", "7"), Team = c("RPC - RPC", "BRA - Brazil", "UKR - Ukraine",
"ESP - Spain", "JPN - Japan", "CHN - People's Republic of China"
), Finals = c("3:53.79", "3:54.95", "3:55.15", "4:03.38",
"4:08.66", "4:18.60"), DQ = c("0", "0", "0", "0", "0", "0"),
Exhibition = c("0", "0", "0", "0", "0", "0"), Event = c("Mixed 4x100m Freestyle Relay - 49 Points",
"Mixed 4x100m Freestyle Relay - 49 Points", "Mixed 4x100m Freestyle Relay - 49 Points",
"Mixed 4x100m Freestyle Relay - 49 Points", "Mixed 4x100m Freestyle Relay - 49 Points",
"Mixed 4x100m Freestyle Relay - 49 Points"), Relay_Swimmer_1 = c("GARIPOV Ilnur",
"BELARMINO PEREIRA Wendell", "PIDDUBNA Maryna", "CANTERO ELVIRA Jose Ramon",
"TOMITA Uchu", "HUA Dongdong"), Relay_Swimmer_1_Gender = c("M",
"M", "F", "M", "M", "M"), Relay_Swimmer_1_Para = c("S11",
"S11", "S11", "S11", "S11", "S11"), Relay_Swimmer_2 = c("KRIVSHINA Anna",
"MATERA Douglas", "VERAKSA Maksym", "DELGADO NADAL Maria",
"SAITO Genki", "LI Guizhi"), Relay_Swimmer_2_Gender = c("F",
"M", "M", "F", "M", "F"), Relay_Swimmer_2_Para = c("S13",
"S13", "S12", "S12", "S13", "S11"), Relay_Swimmer_3 = c("PIKALOVA Daria",
"da SILVA SOUSA Lucilene", "STETSENKO Anna", "EDO BELTRAN Ariadna",
"ISHIURA Tomomi", "CAI Liwen"), Relay_Swimmer_3_Gender = c("F",
"F", "F", "F", "F", "F"), Relay_Swimmer_3_Para = c("S12",
"S12", "S13", "S13", "S11", "S11"), Relay_Swimmer_4 = c("SOTNIKOV Vladimir",
"GOMES SANTIAGO Maria Carolina", "GARASHCHENKO Kyrylo", "SALGUERO OTEIZA Ivan",
"TSUJIUCHI Ayano", "YANG Bozun"), Relay_Swimmer_4_Gender = c("M",
"F", "M", "M", "F", "M"), Relay_Swimmer_4_Para = c("S13",
"S12", "S13", "S13", "S13", "S11"), Split_50 = c("28.78",
"27.28", "32.29", "29.28", "28.14", NA), Split_100 = c("1:01.68",
"58.84", "1:10.18", "1:00.99", "58.62", "58.73"), Split_150 = c("27.82",
"26.17", "25.45", "29.69", "27.01", "32.01"), Split_200 = c("58.60",
"55.60", "53.06", "1:01.73", "56.66", "1:06.13"), Split_250 = c("28.42",
"29.16", "28.73", "30.26", "33.44", "33.43"), Split_300 = c("59.06",
"1:01.86", "59.46", "1:05.48", "1:14.77", "1:09.67"), Split_350 = c("26.04",
"28.23", "25.04", "26.23", "28.17", "29.61"), Split_400 = c("54.45",
"58.65", "52.45", "55.18", "58.61", "1:04.07")), row.names = c(NA,
-6L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo Para men 4x100 Free Relay 34 Points, P in splits",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/SwimmeR%20Test%20Files/PG2020_SWMM4X100MFR_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8"
), Heat = c("Final", "Final", "Final", "Final", "Final", "Final",
"Final", "Final"), Lane = c("3", "4", "5", "2", "6", "1", "7",
"8"), Team = c("AUS - Australia", "ITA - Italy", "UKR - Ukraine",
"BRA - Brazil", "RPC - RPC", "CHN - People's Republic of China",
"ESP - Spain", "USA - United States of America"), Finals = c("3:44.31",
"3:45.89", "3:47.40", "3:52.28", "3:54.34", "4:00.18", "4:00.71",
"4:13.94"), DQ = c("0", "0", "0", "0", "0", "0", "0", "0"), Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"), Event = c("Men's 4x100m Freestyle Relay - 34 Points",
"Men's 4x100m Freestyle Relay - 34 Points", "Men's 4x100m Freestyle Relay - 34 Points",
"Men's 4x100m Freestyle Relay - 34 Points", "Men's 4x100m Freestyle Relay - 34 Points",
"Men's 4x100m Freestyle Relay - 34 Points", "Men's 4x100m Freestyle Relay - 34 Points",
"Men's 4x100m Freestyle Relay - 34 Points"), Relay_Swimmer_1 = c("CROTHERS Rowan",
"FANTIN Antonio", "BOZHYNSKYI Yurii", "GONCALVES SILVA Ruiter Antonio",
"MOZGOVOI Bogdan", "YANG Guanglong", "GARRIDO BRUN Jacobo", "GARCIA-TOLSON Rudy"
), Relay_Swimmer_1_Para = c("S10", "S6", "S9", "S9", "S9", "S8",
"S9", "S7"), Relay_Swimmer_2 = c("MARTIN William", "CIULLI Simone",
"DUBROV Denys", "FILHO Vanilton", "GLADKOV Andrei", "LIU Fengqi",
"MARTOS MINGUET Sergio Salvador", "PEPPERSACK Joseph"), Relay_Swimmer_2_Para = c("S9",
"S9", "S8", "S9", "S7", "S8", "S8", "S8"), Relay_Swimmer_3 = c("LEVY Matthew",
"BARLAAM Simone", "TRUSOV Andrii", "GLOCK Talisson Henrique",
"NIKOLAEV Andrei", "YANG Feng", "LLOPIS SANZ Inigo", "AUSTIN Evan"
), Relay_Swimmer_3_Para = c("S7", "S9", "S7", "S6", "S8", "S8",
"S8", "S7"), Relay_Swimmer_4 = c("POPHAM Ben", "RAIMONDI Stefano",
"KRYPAK Maksym", "MELO RODRIGUES Phelipe Andrews", "BARTASINSKII Dmitrii",
"XU Haijiao", "MARI ALCARAZ Jose Antonio", "HILL Jamal"), Relay_Swimmer_4_Para = c("S8",
"S10", "S10", "S10", "S10", "S8", "S9", "S9"), Split_50 = c("24.71",
"31.99", "28.16", "27.29", "27.80", "28.41", "28.66", "32.85"
), Split_100 = c("51.35", "1:04.20", "1:00.03", "57.77", "57.23",
"59.40", "58.52", "1:08.50"), Split_150 = c("25.72", "26.66",
"28.22", "27.56", "31.43", "28.10", "29.13", "29.93"), Split_200 = c("54.53",
"57.23", "58.94", "57.73", "1:05.55", "58.72", "1:02.84", "1:03.01"
), Split_250 = c("28.97", "25.33", "27.64", "31.40", "27.95",
"29.27", "29.26", "31.36"), Split_300 = c("1:01.30", "53.69",
"58.19", "1:05.38", "57.79", "1:02.56", "1:01.88", "1:04.20"),
Split_350 = c("27.72", "23.76", "23.55", "23.84", "25.50",
"28.23", "27.50", "26.78"), Split_400 = c("57.13", "50.77",
"50.24", "51.40", "53.77", "59.50", "57.47", "58.23")), row.names = c(NA,
-8L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo Para Women 150IM-SM4",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Paralympics2020/raw_files/PG2020_SWMW150MIM_04042_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8"
), Heat = c("Final", "Final", "Final", "Final", "Final", "Final",
"Final", "Final"), Lane = c("4", "5", "3", "6", "7", "8", "1",
"2"), Name = c("LIU Yu", "ZHOU Yanfei", "BUTKOVA Nataliia", "FERNANDEZ INFANTE Marta",
"SMITH Leanne", "MIRANDA HERRERA Nely", "VERBOVA Maryna", "SCHNARNDORF Susana"
), Para = c("SM4", "SM4", "SM4", "SM4", "SM3", "SM4", "SM4",
"SM4"), Team = c("CHN", "CHN", "RPC", "ESP", "USA", "MEX", "UKR",
"BRA"), Reaction_Time = c("0.85", "1.05", "0.85", "0.90", "1.46",
"0.58", "0.75", "0.79"), Finals = c("2:41.91", "2:47.41",
"2:53.25", "2:59.13", "3:07.07", "3:08.71", "3:09.17", "3:11.54"
), DQ = c("0", "0", "0", "0", "0", "0", "0", "0"), Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"), Event = c("Women's 150m Individual Medley - SM4",
"Women's 150m Individual Medley - SM4", "Women's 150m Individual Medley - SM4",
"Women's 150m Individual Medley - SM4", "Women's 150m Individual Medley - SM4",
"Women's 150m Individual Medley - SM4", "Women's 150m Individual Medley - SM4",
"Women's 150m Individual Medley - SM4"), Split_50 = c("45.62",
"50.45", "54.14", "68.59", "59.85", "57.41", "53.92", "61.32"
), Split_100 = c("63.18", "68.72", "68.71", "64.53", "70.97",
"78.58", "72.07", "73.89"), Split_150 = c("53.11", "48.24", "50.40",
"46.01", "56.25", "52.72", "63.18", "56.33")), row.names = c(NA,
-8L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo Para Mixed 4x50m Freestyle Relay - 20 Points",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Paralympics2020/raw_files/PG2020_SWMX4X50MFR_10101_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8"
), Heat = c("Final", "Final", "Final", "Final", "Final", "Final",
"Final", "Final"), Lane = c("6", "4", "7", "5", "3", "2", "8",
"1"), Team = c("CHN - People's Republic of China", "ITA - Italy",
"BRA - Brazil", "UKR - Ukraine", "ESP - Spain", "RPC - RPC",
"TUR - Turkey", "GBR - Great Britain"), Finals = c("2:15.49",
"2:21.45", "2:24.82", "2:24.89", "2:25.66", "2:35.66", "2:42.43",
"2:48.34"), DQ = c("0", "0", "0", "0", "0", "0", "0", "0"), Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"), Event = c("Mixed 4x50m Freestyle Relay - 20 Points",
"Mixed 4x50m Freestyle Relay - 20 Points", "Mixed 4x50m Freestyle Relay - 20 Points",
"Mixed 4x50m Freestyle Relay - 20 Points", "Mixed 4x50m Freestyle Relay - 20 Points",
"Mixed 4x50m Freestyle Relay - 20 Points", "Mixed 4x50m Freestyle Relay - 20 Points",
"Mixed 4x50m Freestyle Relay - 20 Points"), Relay_Swimmer_1 = c("ZHANG Li",
"TERZI Giulia", "PEREIRA dos SANTOS Patricia", "OSTAPCHENKO Denys",
"PERALES Teresa", "BUTKOVA Nataliia", "KUTLU Koral Berkin", "KEARNEY Tully"
), Relay_Swimmer_1_Gender = c("F", "F", "F", "M", "F", "F", "M",
"F"), Relay_Swimmer_1_Para = c("S5", "S7", "S4", "S3", "S5",
"S4", "S5", "S5"), Relay_Swimmer_2 = c("ZHENG Tao", "TRIMI Arjola",
"de FARIA DIAS Daniel", "SEMENENKO Yaroslav", "FERNANDEZ INFANTE Marta",
"PALIAN Ani", "BOYACI Sumeyye", "LONGHORNE Lyndon"), Relay_Swimmer_2_Gender = c("M",
"F", "M", "M", "F", "F", "F", "M"), Relay_Swimmer_2_Para = c("S5",
"S3", "S5", "S5", "S4", "S7", "S5", "S4"), Relay_Swimmer_3 = c("YUAN Weiyi",
"BEGGIATO Luigi", "da SILVA NEVES EUZEBIO J", "HONTAR Anna",
"SANCHEZ SIERRA David", "ZHDANOV Roman", "OZTURK Sevilay", "CHALLIS Ellie"
), Relay_Swimmer_3_Gender = c("M", "M", "F", "F", "M", "M", "F",
"F"), Relay_Swimmer_3_Para = c("S5", "S4", "S5", "S6", "S6",
"S4", "S5", "S3"), Relay_Swimmer_4 = c("LU Dong", "FANTIN Antonio",
"GLOCK Talisson Henrique", "MERESHKO Yelyzaveta", "PONCE BERTRAN Antoni",
"KUBASOV Artur", "EROGLU Beytullah", "PERRY William"), Relay_Swimmer_4_Gender = c("F",
"M", "M", "F", "M", "M", "M", "M"), Relay_Swimmer_4_Para = c("S5",
"S6", "S6", "S6", "S5", "S5", "S5", "S6"), Split_50 = c("36.22",
"32.89", "44.85", "46.46", "38.56", "44.11", "36.03", "35.68"
), Split_100 = c("30.48", "40.39", "31.58", "32.30", "40.43",
"33.47", "43.05", "44.11"), Split_150 = c("31.38", "39.16", "37.72",
"33.20", "31.97", "41.41", "44.08", "55.13"), Split_200 = c("37.41",
"29.01", "30.67", "32.93", "34.70", "36.67", "39.27", "33.42"
)), row.names = c(NA, -8L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
gpilgrim2670/SwimmeR documentation built on March 26, 2023, 5:05 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
# testthat::test_file("tests/testthat/test-omega.R")
test_that("Men 400 IM prelims", {
file <-
system.file("extdata", "Omega_OT_400IM_Prelims_2021.pdf", package = "SwimmeR")
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
head(2)
df_standard <- data.frame(
Place = c("1", "2"),
Heat = rep("4", 2),
Lane = c("4", "5"),
Name = c("FOSTER Carson", "KALISZ Chase"),
Team = c("RAYSOH", "ABSC"),
Reaction_Time = c("0.66", "0.69"),
Finals = c("4:10.50", "4:10.61"),
DQ = rep("0", 2),
Exhibition = rep("0", 2),
Event = rep("AM Men's 400m Individual Medley Heats", 2),
Split_50 = c("26.24", "26.48"),
Split_100 = c("29.56", "29.98"),
Split_150 = c("31.76", "32.74"),
Split_200 = c("30.87", "32.10"),
Split_250 = c("35.38", "34.39"),
Split_300 = c("35.69", "34.96"),
Split_350 = c("31.28", "30.94"),
Split_400 = c("29.72", "29.02")
)
expect_equivalent(df_standard,
df_test)
})
test_that("2021 US OT Wave 2 Women 400 Free Heats, swimmers without reaction times", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Omega/Omega_OT_Wave2_W400Fr_Heats_2021.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
filter(Name %in% c("LEDECKY Katie", "NUNAN Amanda", "KILGALLON Abigail", "TWICHELL Ashley"))
df_standard <-
structure(
list(
Place = c("1", "8", "37", "46"),
Heat = c("6",
"6", "2", "1"),
Lane = c("4", "3", "6", "8"),
Name = c(
"LEDECKY Katie",
"TWICHELL Ashley",
"NUNAN Amanda",
"KILGALLON Abigail"
),
Team = c("NCAP",
"TAC-NC", "TNAQ", "UOFM"),
Reaction_Time = c("0.70", "0.77",
NA, NA),
Finals = c("4:03.07", "4:10.51", "4:17.58", "4:23.32"),
DQ = c("0", "0", "0", "0"),
Exhibition = c("0", "0", "0",
"0"),
Event = c(
"AM Women's 400m Freestyle Heats",
"AM Women's 400m Freestyle Heats",
"AM Women's 400m Freestyle Heats",
"AM Women's 400m Freestyle Heats"
),
Split_50 = c("28.10", "29.38", "30.15", "30.96"),
Split_100 = c("30.11",
"31.14", "31.99", "32.38"),
Split_150 = c("30.59", "31.39", "32.53",
"33.15"),
Split_200 = c("30.74", "31.51", "32.79", "32.77"),
Split_250 = c("30.82", "31.79", "32.72", "33.09"),
Split_300 = c("30.98",
"31.98", "32.67", "33.54"),
Split_350 = c("31.13", "32.23",
"32.94", "33.86"),
Split_400 = c("30.60", "31.09", "31.79",
"33.57")
),
row.names = c(NA,-4L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Women 200 fly prelims, need to not remove swimmers for decimal counting", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Omega/Omega_OT_Wave1_W200Fl_Heats_2021.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
head(3)
df_standard <-
structure(
list(
Place = c("1", "2", "3"),
Heat = c("4", "2", "4"),
Lane = c("6", "5", "7"),
Name = c("MASSEY Alex", "STICKLEN Emma",
"CULLEN Casey"),
Team = c("NAC", "KATY", "PWAC"),
Reaction_Time = c("0.73",
"0.72", "0.71"),
Finals = c("2:13.01", "2:13.20", "2:13.76"),
DQ = c("0", "0", "0"),
Exhibition = c("0", "0", "0"),
Event = c(
"AM Women's 200m Butterfly Heats",
"AM Women's 200m Butterfly Heats",
"AM Women's 200m Butterfly Heats"
),
Split_50 = c("29.83", "29.46", "30.67"),
Split_100 = c("33.41",
"33.20", "33.96"),
Split_150 = c("33.99", "34.93", "34.27"),
Split_200 = c("35.78", "35.61", "34.86")
),
row.names = c(NA,
3L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("US OT 2021 Wave I Men 100 Free Heats", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Omega/Omega_OT_Wave1_M100Fr_Heats_2021.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
head(2)
df_standard <-
structure(
list(
Place = c("1", "2"),
Heat = c("3", "4"),
Lane = c("5",
"3"),
Name = c("BENSON Andrew", "MILLER Luke"),
Team = c("WA",
"EA"),
Reaction_Time = c("0.62", "0.62"),
Finals = c("50.10",
"50.13"),
DQ = c("0", "0"),
Exhibition = c("0", "0"),
Event = c("AM Men's 100m Freestyle Heats",
"AM Men's 100m Freestyle Heats"),
Split_50 = c("23.58", "24.22"),
Split_100 = c("26.52", "25.91")
),
row.names = 1:2,
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Women 400m finals", {
file <-
system.file("extdata", "Omega_OT_400m_Finals_2021.pdf", package = "SwimmeR")
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
head(2)
df_standard <- data.frame(
Place = c("1", "2"),
Heat = rep("Final", 2),
Lane = c("4", "5"),
Name = c("LEDECKY Katie", "MADDEN Paige"),
Team = c("NCAP", "UVA"),
Reaction_Time = c("0.65", "0.63"),
Finals = c("4:01.27", "4:04.86"),
DQ = rep("0", 2),
Exhibition = rep("0", 2),
Event = rep("PM Women's 400m Freestyle Final", 2),
Split_50 = c("27.70", "28.10"),
Split_100 = c("29.59", "30.16"),
Split_150 = c("29.95", "30.68"),
Split_200 = c("30.40", "31.06"),
Split_250 = c("30.47", "31.23"),
Split_300 = c("31.24", "31.05"),
Split_350 = c("30.88", "31.24"),
Split_400 = c("31.04", "31.34")
)
expect_equivalent(df_standard,
df_test)
})
test_that("100 br swim off no heat", {
file <-
system.file("extdata", "Omega_OT_100Br_Swimoff_2021.pdf", package = "SwimmeR")
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE)
df_standard <- data.frame(
Place = c("1", "2"),
Heat = rep("Heats", 2),
Lane = c("4", "5"),
Name = c("TYBUR Jonathan", "MASON Mitch"),
Team = c("GSC-FL", "LSU"),
Reaction_Time = c("0.66", "0.68"),
Finals = c("1:00.91", "1:01.93"),
DQ = rep("0", 2),
Exhibition = rep("0", 2),
Event = rep("PM Men's 100m Breaststroke Heats Swim-off", 2),
Split_50 = c("28.17", "29.07"),
Split_100 = c("32.74", "32.86")
)
expect_equivalent(df_standard,
df_test)
})
test_that("wave 1 200 fly", {
file <-
system.file("extdata", "Omega_Wave1_200fly_Finals_2021.pdf", package = "SwimmeR")
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE) %>%
head(2)
df_standard <- data.frame(
Place = c("1", "2"),
Heat = rep("Final", 2),
Lane = c("4", "2"),
Name = c("SUN Eleanor", "THOMAS Luciana"),
Team = c("NCAP", "IA"),
Reaction_Time = c("0.72", "0.76"),
Finals = c("2:13.76", "2:15.32"),
DQ = rep("0", 2),
Exhibition = rep("0", 2),
Event = rep("4 JUN 2021 - 7:23 PM Women's 200m Butterfly Final", 2),
Split_50 = c("29.70", "30.28"),
Split_100 = c("34.09", "33.80"),
Split_150 = c("35.21", "35.20"),
Split_200 = c("34.76", "36.04")
)
expect_equivalent(df_standard,
df_test)
})
test_that("wave 1 1500m", {
file <-
system.file("extdata", "Omega_Wave1_1500_Finals_2021.pdf", package = "SwimmeR")
df <- file %>%
read_results() %>%
swim_parse(splits = TRUE) %>%
filter(Name != "NARVID Jake") # Jake has issues with his reported splits
list_test <- df %>%
dplyr::mutate(dplyr::across(dplyr::starts_with("Split"), sec_format)) %>%
mutate(Split_Total = rowSums(dplyr::across(dplyr::starts_with("Split")), na.rm = TRUE)) %>%
pull(Split_Total)
list_standard <-
c(935.94,
936.24,
940.05,
944.30,
952.72,
954.12,
954.17,
962.61,
964.30,
965.41,
978.49)
expect_equivalent(list_standard,
list_test)
})
test_that("Tokyo 2020 Men 400IM Heat 1", {
skip_on_cran()
file <-
"https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/Tokyo2020/SWMM400MIM_HEAT.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
filter(Heat == "Heat_1")
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5"), Heat = c("Heat_1",
"Heat_1", "Heat_1", "Heat_1", "Heat_1"), Lane = c("5", "4", "3",
"6", "2"), Name = c("LOPES Jose", "PERIBONIO AVILA Tomas", "POLONSKY Ron",
"MEIER Christoph", "VEGA TORRES Luis Emigdio"), Team = c("POR",
"ECU", "ISR", "LIE", "CUB"), Reaction_Time = c("0.66", "0.63",
"0.71", "0.68", "0.69"), Finals = c("4:16.52", "4:18.73",
"4:21.50", "4:25.17", "4:27.65"), DQ = c("0", "0", "0", "0",
"0"), Exhibition = c("0", "0", "0", "0", "0"), Event = c("Men's 400m Individual Medley",
"Men's 400m Individual Medley", "Men's 400m Individual Medley",
"Men's 400m Individual Medley", "Men's 400m Individual Medley"
), Split_50 = c("27.40", "27.11", "27.14", "26.52", "27.65"),
Split_100 = c("30.93", "31.26", "31.90", "30.88", "31.80"
), Split_150 = c("32.52", "33.26", "33.65", "36.28", "34.85"
), Split_200 = c("32.48", "33.00", "33.63", "35.65", "34.26"
), Split_250 = c("37.07", "35.87", "35.44", "36.22", "37.34"
), Split_300 = c("36.66", "36.88", "36.86", "36.84", "38.01"
), Split_350 = c("30.43", "30.75", "31.46", "31.68", "32.24"
), Split_400 = c("29.03", "30.60", "31.42", "31.10", "31.50"
)), row.names = c(NA, -5L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Women 4 x 100m Free Heat 1, checked", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMW4X100MFR_HEAT.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE) %>%
filter(Heat == "Heat_1")
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7"),
Heat = c("Heat_1", "Heat_1", "Heat_1", "Heat_1", "Heat_1",
"Heat_1", "Heat_1"), Lane = c("5", "4", "2", "6", "3", "7",
"1"), Team = c("GBR - Great Britain", "USA - United States of America",
"DEN - Denmark", "SWE - Sweden", "FRA - France", "BRA - Brazil",
"HKG - Hong Kong, China"), Finals = c("3:34.03", "3:34.80",
"3:35.56", "3:35.93", "3:36.61", "3:39.19", "3:43.52"), DQ = c("0",
"0", "0", "0", "0", "0", "0"), Exhibition = c("0", "0", "0",
"0", "0", "0", "0"), Event = c("Women's 4 x 100m Freestyle Relay",
"Women's 4 x 100m Freestyle Relay", "Women's 4 x 100m Freestyle Relay",
"Women's 4 x 100m Freestyle Relay", "Women's 4 x 100m Freestyle Relay",
"Women's 4 x 100m Freestyle Relay", "Women's 4 x 100m Freestyle Relay"
), Relay_Swimmer_1 = c("HOPE Lucy", "SMOLIGA Olivia", "BLUME Pernille",
"SJOESTROEM Sarah", "GASTALDELLO Beryl", "OLIVEIRA Larissa",
"TAM Hoi Lam"), Relay_Swimmer_2 = c("HOPKIN Anna", "de LOOF Catie",
"BRO Signe", "COLEMAN Michelle", "BONNET Charlotte", "VIEIRA Ana Carolina",
"CHENG Camille Lily Mei"), Relay_Swimmer_3 = c("WOOD Abbie",
"SCHMITT Allison", "JENSEN Julie Kepp", "HANSSON Louise",
"FABRE Margaux", "MEDEIROS Etiene", "AU Hoi Shun Stephanie"
), Relay_Swimmer_4 = c("ANDERSON Freya", "HINDS Natalie",
"OTTESEN Jeanette", "JUNEVIK Sara", "MARTIN Anouchka", "BALDUCCINI Stephanie",
"HO Nam Wai Tinky"), Split_50 = c("26.28", "25.96", "25.33",
"25.47", "25.97", "26.23", "26.50"), Split_100 = c("54.37",
"54.06", "53.15", "52.95", "54.28", "54.79", "55.58"), Split_150 = c("24.87",
"25.02", "25.50", "24.91", "25.35", "26.07", "26.05"), Split_200 = c("52.65",
"53.42", "53.19", "53.44", "53.05", "54.92", "54.61"), Split_250 = c("25.53",
"25.85", "25.56", "25.29", "26.09", "25.95", "26.96"), Split_300 = c("53.55",
"54.04", "54.72", "53.68", "54.83", "55.42", "56.96"), Split_350 = c("25.76",
"25.30", "25.46", "25.87", "25.75", "25.61", "27.43"), Split_400 = c("53.46",
"53.28", "54.50", "55.86", "54.45", "54.06", "56.37")), row.names = c(NA,
-7L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Women 100 Breast Heats, with DNS", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMW100MBR_HEAT.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE,
typo = "RODRIGUEZ VILLANUEVA Byanca MelissaMEX",
replacement = "RODRIGUEZ VILLANUEVA Byanca Melissa MEX")
df_standard <-
structure(
list(
Place = c(
"1",
"2",
"3",
"4",
"5",
"6",
NA,
"1",
"2",
"3",
"4",
"5",
"6",
"7",
NA,
"1",
"2",
"3",
"4",
"5",
"6",
"7",
"8",
"1",
"2",
"3",
"4",
"5",
"6",
"7",
NA,
"1",
"2",
"3",
"4",
"5",
"6",
"7",
NA,
"1",
"2",
"3",
"4",
"5",
"6",
"7",
"8"
),
Heat = c(
"Heat_1",
"Heat_1",
"Heat_1",
"Heat_1",
"Heat_1",
"Heat_1",
"Heat_1",
"Heat_2",
"Heat_2",
"Heat_2",
"Heat_2",
"Heat_2",
"Heat_2",
"Heat_2",
"Heat_2",
"Heat_3",
"Heat_3",
"Heat_3",
"Heat_3",
"Heat_3",
"Heat_3",
"Heat_3",
"Heat_3",
"Heat_4",
"Heat_4",
"Heat_4",
"Heat_4",
"Heat_4",
"Heat_4",
"Heat_4",
"Heat_4",
"Heat_5",
"Heat_5",
"Heat_5",
"Heat_5",
"Heat_5",
"Heat_5",
"Heat_5",
"Heat_5",
"Heat_6",
"Heat_6",
"Heat_6",
"Heat_6",
"Heat_6",
"Heat_6",
"Heat_6",
"Heat_6"
),
Lane = c(
"3",
"5",
"4",
"2",
"7",
"6",
NA,
"3",
"5",
"7",
"4",
"6",
"8",
"2",
NA,
"1",
"2",
"6",
"4",
"5",
"7",
"3",
"8",
"4",
"3",
"2",
"6",
"1",
"7",
"8",
NA,
"5",
"4",
"6",
"3",
"7",
"2",
"1",
NA,
"4",
"5",
"3",
"6",
"8",
"2",
"7",
"1"
),
Name = c(
"GRAND PIERRE Emilie Faith",
"SEMYONOVA Darya",
"PINA Jayla",
"ADAMS Taeyanna",
"BA MATRAF Nooran",
"SAJINA Aishath",
"TOURE Mariama",
"PODMANIKOVA Andrea",
"PHEE Jinq En",
"SCANLAN Tilali",
"RAJIC Ema",
"SANTOS SILVA Emily M",
"FISHER-MARSTERS Kirsten Andrea",
"KOK SHUN Alicia",
"VERDINO Claudia",
"TETEREVKOVA Kotryna",
"ELENDT Anna Charlott Darcel",
"ATKINSON Alia",
"SCHOUTEN Tes",
"LECLUYSE Fanny",
"RODRIGUEZ VILLANUEVA Byanca Melissa",
"SEBASTIAN Julia",
"PETKOVA Diana",
"EFIMOVA Yuliya",
"TANG Qianting",
"WATANABE Kanako",
"AOKI Reona",
"HANSEN Jessica",
"ZMUSHKA Alina",
"WOG Kelsey Lauren",
"PILATO Benedetta",
"SCHOENMAKER Tatjana",
"JACOBY Lydia",
"Mc SHARRY Mona",
"HODGES Chelsea",
"MAMIE Lisa",
"JEFIMOVA Eneli",
"VALL MONTERO Jessica",
"GORBENKO Anastasia",
"KING Lilly",
"HANSSON Sophie",
"CARRARO Martina",
"CHIKUNOVA Evgeniia",
"HULKKO Ida",
"VASEY Sarah",
"SMITH Kierra",
"FAST Emelie"
),
Team = c(
"HAI",
"TKM",
"CPV",
"FSM",
"YEM",
"MDV",
"GUI",
"SVK",
"MAS",
"ASA",
"CRO",
"PAN",
"COK",
"MRI",
"MON",
"LTU",
"GER",
"JAM",
"NED",
"BEL",
"MEX",
"ARG",
"BUL",
"ROC",
"CHN",
"JPN",
"JPN",
"AUS",
"BLR",
"CAN",
"ITA",
"RSA",
"USA",
"IRL",
"AUS",
"SUI",
"EST",
"ESP",
"ISR",
"USA",
"SWE",
"ITA",
"ROC",
"FIN",
"GBR",
"CAN",
"SWE"
),
Reaction_Time = c(
"0.67",
"0.65",
"0.69",
"0.73",
"0.73",
"0.72",
NA,
"0.66",
"0.70",
"0.71",
"0.71",
"0.69",
"0.68",
"0.60",
NA,
"0.70",
"0.72",
"0.67",
"0.66",
"0.71",
"0.65",
"0.66",
"0.74",
"0.69",
"0.73",
"0.69",
"0.62",
"0.72",
"0.70",
"0.63",
NA,
"0.67",
"0.67",
"0.67",
"0.70",
"0.71",
"0.67",
"0.69",
NA,
"0.71",
"0.72",
"0.61",
"0.71",
"0.65",
"0.67",
"0.76",
"0.65"
),
Finals = c(
"1:14.82",
"1:16.37",
"1:16.96",
"1:25.36",
"1:27.79",
"1:33.59",
NA,
"1:08.36",
"1:08.40",
"1:10.01",
"1:10.02",
"1:12.10",
"1:13.98",
"1:15.42",
NA,
"1:06.82",
"1:06.96",
"1:07.70",
"1:07.89",
"1:07.93",
"1:08.76",
"1:09.35",
"1:10.61",
"1:06.21",
"1:06.47",
"1:07.01",
"1:07.29",
"1:07.50",
"1:07.58",
"1:07.73",
NA,
"1:04.82",
"1:05.52",
"1:06.39",
"1:06.70",
"1:06.76",
"1:06.79",
"1:07.07",
NA,
"1:05.55",
"1:05.66",
"1:05.85",
"1:06.16",
"1:06.19",
"1:06.61",
"1:07.87",
"1:07.98"
),
DQ = c(
"0",
"0",
"0",
"0",
"0",
"0",
"1",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"1",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"1",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"1",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0"
),
Exhibition = 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",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0"
),
Event = c(
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke",
"Women's 100m Breaststroke"
),
Split_50 = c(
"34.33",
"34.22",
"34.18",
"39.75",
"41.53",
"44.17",
NA,
"32.10",
"32.50",
"33.22",
"32.10",
"33.18",
"34.16",
"34.60",
NA,
"31.61",
"31.57",
"31.48",
"32.09",
"31.57",
"31.77",
"32.32",
"32.81",
"30.92",
"30.81",
"31.39",
"31.01",
"31.85",
"31.76",
"31.82",
NA,
"30.21",
"30.99",
"31.06",
"30.86",
"31.42",
"31.76",
"32.02",
NA,
"30.74",
"31.01",
"31.06",
"31.63",
"30.55",
"31.30",
"32.09",
"31.23"
),
Split_100 = c(
"40.49",
"42.15",
"42.78",
"45.61",
"46.26",
"49.42",
NA,
"36.26",
"35.90",
"36.79",
"37.92",
"38.92",
"39.82",
"40.82",
NA,
"35.21",
"35.39",
"36.22",
"35.80",
"36.36",
"36.99",
"37.03",
"37.80",
"35.29",
"35.66",
"35.62",
"36.28",
"35.65",
"35.82",
"35.91",
NA,
"34.61",
"34.53",
"35.33",
"35.84",
"35.34",
"35.03",
"35.05",
NA,
"34.81",
"34.65",
"34.79",
"34.53",
"35.64",
"35.31",
"35.78",
"36.75"
)
),
row.names = c(NA,-47L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Men 100 Fly Semis, with ORs broken", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMM100MBF_SFNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c(
"1",
"2",
"3",
"4",
"5",
"6",
"7",
"8",
"1",
"2",
"3",
"4",
"5",
"6",
"7",
"8"
),
Heat = c(
"Semi_1",
"Semi_1",
"Semi_1",
"Semi_1",
"Semi_1",
"Semi_1",
"Semi_1",
"Semi_1",
"Semi_2",
"Semi_2",
"Semi_2",
"Semi_2",
"Semi_2",
"Semi_2",
"Semi_2",
"Semi_2"
),
Lane = c(
"4",
"3",
"5",
"6",
"2",
"7",
"8",
"1",
"4",
"3",
"5",
"6",
"2",
"7",
"8",
"1"
),
Name = c(
"MILAK Kristof",
"MILADINOV Josif",
"MINAKOV Andrei",
"TEMPLE Matthew",
"METELLA Mehdy",
"MIZUNUMA Naoki",
"SUN Jiajun",
"RAMADAN Youssef",
"DRESSEL Caeleb",
"PONTI Noe",
"MAJERSKI Jakub",
"MARTINEZ Luis Carlos",
"LIENDO EDWARDS Joshua",
"KORSTANJE Nyls",
"SZABO Szebasztian",
"SHIELDS Tom"
),
Team = c(
"HUN",
"BUL",
"ROC",
"AUS",
"FRA",
"JPN",
"CHN",
"EGY",
"USA",
"SUI",
"POL",
"GUA",
"CAN",
"NED",
"HUN",
"USA"
),
Reaction_Time = c(
"0.66",
"0.65",
"0.63",
"0.63",
"0.65",
"0.60",
"0.64",
"0.61",
"0.62",
"0.69",
"0.64",
"0.62",
"0.63",
"0.61",
"0.58",
"0.71"
),
Finals = c(
"50.31",
"51.06",
"51.11",
"51.12",
"51.32",
"51.46",
"51.82",
"52.27",
"49.71",
"50.76",
"51.24",
"51.30",
"51.50",
"51.80",
"51.89",
"51.99"
),
DQ = c(
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0"
),
Exhibition = c(
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0",
"0"
),
Event = c(
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly",
"Men's 100m Butterfly"
),
Split_50 = c(
"23.74",
"24.02",
"23.73",
"23.88",
"23.73",
"24.04",
"23.88",
"23.78",
"23.20",
"23.72",
"24.10",
"24.23",
"23.88",
"23.54",
"23.79",
"24.07"
),
Split_100 = c(
"26.57",
"27.04",
"27.38",
"27.24",
"27.59",
"27.42",
"27.94",
"28.49",
"26.51",
"27.04",
"27.14",
"27.07",
"27.62",
"28.26",
"28.10",
"27.92"
)
),
row.names = c(NA, -16L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Women 400MR Finals, with record issues", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMW4X100MMD_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c("1", "2", "3", "4", "5", "6", "7", "8"),
Heat = rep("Final", 8),
Lane = c("3", "5", "4", "8", "2", "6", "1", "7"),
Team = c(
"AUS - Australia",
"USA - United States of America",
"CAN - Canada",
"CHN - People's Republic of China",
"SWE - Sweden",
"ITA - Italy",
"ROC - ROC",
"JPN - Japan"
),
Finals = c(
"3:51.60",
"3:51.73",
"3:52.60",
"3:54.13",
"3:54.27",
"3:56.68",
"3:56.93",
"3:58.12"
),
DQ = c("0", "0", "0", "0", "0", "0", "0", "0"),
Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"),
Event = c(
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay",
"Women's 4 x 100m Medley Relay"
),
Relay_Swimmer_1 = c(
"McKEOWN Kaylee",
"SMITH Regan",
"MASSE Kylie",
"PENG Xuwei",
"COLEMAN Michelle",
"PANZIERA Margherita",
"KAMENEVA Mariia",
"KONISHI Anna"
),
Relay_Swimmer_2 = c(
"HODGES Chelsea",
"JACOBY Lydia",
"PICKREM Sydney",
"TANG Qianting",
"HANSSON Sophie",
"CARRARO Martina",
"CHIKUNOVA Evgeniia",
"WATANABE Kanako"
),
Relay_Swimmer_3 = c(
"McKEON Emma",
"HUSKE Torri",
"MACNEIL Margaret",
"ZHANG Yufei",
"HANSSON Louise",
"di LIDDO Elena",
"CHIMROVA Svetlana",
"IKEE Rikako"
),
Relay_Swimmer_4 = c(
"CAMPBELL Cate",
"WEITZEIL Abbey",
"OLEKSIAK Penny",
"YANG Junxuan",
"SJOESTROEM Sarah",
"PELLEGRINI Federica",
"SURKOVA Arina",
"IGARASHI Chihiro"
),
Split_50 = c(
"28.57",
"28.44",
"27.92",
"28.99",
"28.64",
"29.29",
"29.26",
"29.32"
),
Split_100 = c(
"58.01",
"58.05",
"57.90",
"59.63",
"59.75",
"1:00.03",
"59.95",
"59.92"
),
Split_150 = c(
"30.58",
"30.48",
"31.57",
"30.74",
"30.71",
"30.31",
"31.20",
"31.35"
),
Split_200 = c(
"1:05.57",
"1:05.03",
"1:07.17",
"1:06.09",
"1:05.67",
"1:05.88",
"1:05.99",
"1:06.61"
),
Split_250 = c(
"25.86",
"25.42",
"25.58",
"25.48",
"25.86",
"26.63",
"26.21",
"26.81"
),
Split_300 = c(
"55.91",
"56.16",
"55.27",
"55.39",
"56.12",
"56.96",
"56.70",
"57.92"
),
Split_350 = c(
"24.78",
"24.91",
"25.06",
"25.37",
"25.27",
"25.76",
"25.37",
"25.63"
),
Split_400 = c(
"52.11",
"52.49",
"52.26",
"53.02",
"52.73",
"53.81",
"54.29",
"53.67"
)
),
row.names = c(NA, -8L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Mixed 4x100MR Finals, relay swimmer gender", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMX4X100MMD_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c("1", "2", "3", "4", "5", "6", "7", "8"),
Heat = rep("Final", 8),
Lane = c("4", "3", "6", "2", "5", "7", "1", "8"),
Team = c(
"GBR - Great Britain",
"CHN - People's Republic of China",
"AUS - Australia",
"ITA - Italy",
"USA - United States of America",
"NED - Netherlands",
"ROC - ROC",
"ISR - Israel"
),
Finals = c(
"3:37.58",
"3:38.86",
"3:38.95",
"3:39.28",
"3:40.58",
"3:41.25",
"3:42.45",
"3:44.77"
),
DQ = c("0",
"0", "0", "0", "0", "0", "0", "0"),
Exhibition = c("0", "0",
"0", "0", "0", "0", "0", "0"),
Event = c(
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay",
"Mixed 4 x 100m Medley Relay"
),
Relay_Swimmer_1 = c(
"DAWSON Kathleen",
"XU Jiayu",
"McKEOWN Kaylee",
"CECCON Thomas",
"MURPHY Ryan",
"TOUSSAINT Kira",
"RYLOV Evgeny",
"GORBENKO Anastasia"
),
Relay_Swimmer_1_Gender = c("F",
"M", "F", "M", "M", "F", "M", "F"),
Relay_Swimmer_2 = c(
"PEATY Adam",
"YAN Zibei",
"STUBBLETY-COOK Izaac",
"MARTINENGHI Nicolo",
"JACOBY Lydia",
"KAMMINGA Arno",
"PRIGODA Kirill",
"GOLDFADEN Itay"
),
Relay_Swimmer_2_Gender = c("M",
"M", "M", "M", "F", "M", "M", "M"),
Relay_Swimmer_3 = c(
"GUY James",
"ZHANG Yufei",
"TEMPLE Matthew",
"di LIDDO Elena",
"HUSKE Torri",
"KORSTANJE Nyls",
"CHIMROVA Svetlana",
"COHEN GROUMI Gal"
),
Relay_Swimmer_3_Gender = c("M",
"F", "M", "F", "F", "M", "F", "M"),
Relay_Swimmer_4 = c(
"HOPKIN Anna",
"YANG Junxuan",
"McKEON Emma",
"PELLEGRINI Federica",
"DRESSEL Caeleb",
"HEEMSKERK Femke",
"KAMENEVA Mariia",
"MUREZ Andrea"
),
Relay_Swimmer_4_Gender = c("F",
"F", "F", "F", "M", "F", "F", "F"),
Split_50 = c(
"28.35",
"25.33",
"28.46",
"25.65",
"25.09",
"28.41",
"26.06",
"29.08"
),
Split_100 = c(
"58.80",
"52.56",
"58.14",
"52.23",
"52.23",
"59.45",
"52.79",
"59.55"
),
Split_150 = c(
"26.18",
"26.96",
"27.60",
"27.16",
"29.99",
"26.61",
"27.40",
"27.05"
),
Split_200 = c(
"56.78",
"58.11",
"58.82",
"57.73",
"1:05.09",
"57.89",
"59.15",
"59.86"
),
Split_250 = c(
"23.22",
"25.44",
"23.55",
"26.49",
"25.41",
"22.82",
"26.06",
"23.84"
),
Split_300 = c(
"50.00",
"55.48",
"50.26",
"56.62",
"56.27",
"51.34",
"56.95",
"51.58"
),
Split_350 = c(
"24.66",
"25.04",
"24.88",
"25.29",
"22.15",
"24.91",
"25.74",
"25.91"
),
Split_400 = c(
"52.00",
"52.71",
"51.73",
"52.70",
"46.99",
"52.57",
"53.56",
"53.78"
)
),
row.names = c(NA,-8L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Men 200FR Finals, need to capture swims", {
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMM200MFR_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c("1", "2", "3", "4", "5", "6", "7", "8"),
Heat = rep("Final", 8),
Lane = c("6", "4", "8", "1", "2", "5", "7", "3"),
Name = c(
"DEAN Tom",
"SCOTT Duncan",
"SCHEFFER Fernando",
"POPOVICI David",
"MALYUTIN Martin",
"SMITH Kieran",
"HWANG Sunwoo",
"RAPSYS Danas"
),
Team = c("GBR",
"GBR", "BRA", "ROU", "ROC", "USA", "KOR", "LTU"),
Reaction_Time = c("0.64",
"0.66", "0.66", "0.68", "0.70", "0.69", "0.58", "0.65"),
Finals = c(
"1:44.22",
"1:44.26",
"1:44.66",
"1:44.68",
"1:45.01",
"1:45.12",
"1:45.26",
"1:45.78"
),
DQ = c("0", "0", "0", "0", "0", "0", "0", "0"),
Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"),
Event = c(
"Men's 200m Freestyle",
"Men's 200m Freestyle",
"Men's 200m Freestyle",
"Men's 200m Freestyle",
"Men's 200m Freestyle",
"Men's 200m Freestyle",
"Men's 200m Freestyle",
"Men's 200m Freestyle"
),
Split_50 = c(
"24.21",
"24.81",
"24.24",
"24.23",
"25.03",
"24.58",
"23.95",
"24.96"
),
Split_100 = c(
"26.25",
"26.57",
"26.01",
"26.50",
"26.62",
"26.36",
"25.83",
"27.00"
),
Split_150 = c(
"26.92",
"26.42",
"27.03",
"27.24",
"26.78",
"26.87",
"26.78",
"26.87"
),
Split_200 = c(
"26.84",
"26.46",
"27.38",
"26.71",
"26.58",
"27.31",
"28.70",
"26.95"
)
),
row.names = c(NA, -8L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Men 4x200FR Finals, need to not capture splits as swims",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMM4X200MFR_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c("1", "2", "3", "4", "5", "6", "7", "8"),
Heat = rep("Final", 8),
Lane = c("4", "6", "5", "2", "3", "7", "1", "8"),
Team = c(
"GBR - Great Britain",
"ROC - ROC",
"AUS - Australia",
"USA - United States of America",
"ITA - Italy",
"SUI - Switzerland",
"GER - Germany",
"BRA - Brazil"
),
Finals = c(
"6:58.58",
"7:01.81",
"7:01.84",
"7:02.43",
"7:03.24",
"7:06.12",
"7:06.51",
"7:08.22"
),
DQ = c("0", "0",
"0", "0", "0", "0", "0", "0"),
Exhibition = c("0", "0", "0",
"0", "0", "0", "0", "0"),
Event = c(
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay",
"Men's 4 x 200m Freestyle Relay"
),
Relay_Swimmer_1 = c(
"DEAN Tom",
"MALYUTIN Martin",
"GRAHAM Alexander",
"SMITH Kieran",
"BALLO Stefano",
"DJAKOVIC Antonio",
"MARTENS Lukas",
"SCHEFFER Fernando"
),
Relay_Swimmer_2 = c(
"GUY James",
"GIREV Ivan",
"CHALMERS Kyle",
"KIBLER Drew",
"CIAMPI Matteo",
"LIESS Nils",
"ZELLMANN Poul",
"SETIN SARTORI Murilo"
),
Relay_Swimmer_3 = c(
"RICHARDS Matthew",
"RYLOV Evgeny",
"INCERTI Zac",
"APPLE Zach",
"MEGLI Filippo",
"PONTI Noe",
"MUHLLEITNER Henning Bennet",
"CORREIA Breno"
),
Relay_Swimmer_4 = c(
"SCOTT Duncan",
"DOVGALYUK Mikhail",
"NEILL Thomas",
"HAAS Townley",
"di COLA Stefano",
"MITYUKOV Roman",
"HEIDTMANN Jacob",
"MELO Luiz Altamir"
),
Split_50 = c(
"24.55",
"24.77",
"24.94",
"24.37",
"24.98",
"24.89",
"25.20",
"24.70"
),
Split_100 = c(
"51.26",
"51.62",
"51.65",
"50.62",
"51.68",
"51.81",
"52.14",
"51.08"
),
Split_150 = c(
"1:18.38",
"1:18.81",
"1:18.80",
"1:17.59",
"1:18.76",
"1:19.22",
"1:19.58",
"1:18.31"
),
Split_200 = c(
"1:45.72",
"1:45.69",
"1:46.00",
"1:44.74",
"1:45.77",
"1:45.77",
"1:46.68",
"1:45.93"
),
Split_250 = c(
"23.84",
"24.26",
"24.01",
"24.29",
"24.62",
"24.17",
"24.23",
"24.63"
),
Split_300 = c(
"50.31",
"50.96",
"50.82",
"50.95",
"51.58",
"51.03",
"51.34",
"51.61"
),
Split_350 = c(
"1:17.31",
"1:18.20",
"1:17.95",
"1:18.18",
"1:18.78",
"1:19.08",
"1:19.06",
"1:18.78"
),
Split_400 = c(
"1:44.40",
"1:45.63",
"1:45.35",
"1:45.51",
"1:45.88",
"1:47.74",
"1:46.30",
"1:46.09"
),
Split_450 = c(
"23.88",
"24.19",
"24.13",
"23.80",
"24.20",
"24.66",
"25.21",
"24.63"
),
Split_500 = c(
"50.70",
"51.06",
"50.84",
"50.54",
"50.78",
"51.85",
"52.52",
"51.93"
),
Split_550 = c(
"1:18.14",
"1:18.54",
"1:18.37",
"1:18.31",
"1:18.26",
"1:19.63",
"1:20.20",
"1:20.04"
),
Split_600 = c(
"1:45.01",
"1:45.26",
"1:45.75",
"1:47.31",
"1:45.33",
"1:46.93",
"1:48.04",
"1:48.11"
),
Split_650 = c(
"23.64",
"23.86",
"23.93",
"23.82",
"23.92",
"24.11",
"24.39",
"23.77"
),
Split_700 = c(
"49.86",
"50.14",
"50.49",
"50.04",
"50.41",
"51.01",
"50.99",
"50.47"
),
Split_750 = c(
"1:16.65",
"1:17.47",
"1:17.65",
"1:17.40",
"1:17.80",
"1:18.48",
"1:17.99",
"1:18.45"
),
Split_800 = c(
"1:43.45",
"1:45.23",
"1:44.74",
"1:44.87",
"1:46.26",
"1:45.68",
"1:45.49",
"1:48.09"
)
),
row.names = c(NA, -8L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo 2020 Women 4x200FR Heats, relay swimmers with punctuation in name",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMW4X200MFR_HEAT.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8",
"1", "2", "3", "4", "5", "6", "8", "2"), Heat = c("Heat_1", "Heat_1",
"Heat_1", "Heat_1", "Heat_1", "Heat_1", "Heat_1", "Heat_1", "Heat_2",
"Heat_2", "Heat_2", "Heat_2", "Heat_2", "Heat_2", "Heat_2", "Heat_2"
), Lane = c("4", "5", "3", "2", "6", "1", "7", "8", "4", "5",
"3", "6", "7", "1", NA, NA), Team = c("USA - United States of America",
"CHN - People's Republic of China", "GER - Germany", "FRA - France",
"JPN - Japan", "RSA - South Africa", "TUR - Turkey", "KOR - Republic of Korea",
"AUS - Australia", "CAN - Canada", "ROC - ROC", "HUN - Hungary",
"BRA - Brazil", "NZL - New Zealand", "HKG - Hong Kong, China",
"ITA - Italy"), Finals = c("7:47.57", "7:48.98", "7:52.06", "7:55.05",
"7:58.39", "8:01.56", "8:10.96", "8:11.16", "7:44.61", "7:51.52",
"7:52.04", "7:56.16", "7:59.50", "8:06.16", NA, NA), DQ = c("0",
"0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0",
"1", "1"), Exhibition = c("0", "0", "0", "0", "0", "0", "0",
"0", "0", "0", "0", "0", "0", "0", "0", "0"), Event = c("Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay", "Women's 4 x 200m Freestyle Relay",
"Women's 4 x 200m Freestyle Relay"), Relay_Swimmer_1 = c("SIMS Arabella",
"TANG Muhan", "GOSE Isabel", "BONNET Charlotte", "IGARASHI Chihiro",
"CANNY Aimee", "GUNES Viktoria", "JUNG Hyunyoung", "O'CALLAGHAN Mollie",
"SAVARD Katerine", "GUZHENKOVA Anastasia", "JAKABOS Zsuzsanna",
"RODRIGUES Aline", "FAIRWEATHER Erika", NA, "PIROZZI Stefania"
), Relay_Swimmer_2 = c("MADDEN Paige", "ZHANG Yifan", "KULLMANN Leonie Marlen",
"TOUATI Assia", "SHIRAI Rio", "MEDER Rebecca", "BOCEKLER Beril",
"KIM Seoyeong", "HARRIS Meg", "SMITH Rebecca", "SALAMATINA Valeriia",
"VERES Laura", "OLIVEIRA Larissa", "DOYLE Carina", NA, "MASCOLO Anna Chiara"
), Relay_Swimmer_3 = c("Mc LAUGHLIN Kathryn", "DONG Jie", "PIETRUSCHKA Marie",
"TESSARIOL Lucile", "IKEMOTO Nagisa", "COETZEE Dune", "ERTAN Deniz",
"HAN Dakyung", "THROSSELL Brianna", "HARVEY Mary-Sophie", "ANDRUSENKO Veronika",
"VERRASZTO Evelin", "ALMEIDA Nathalia", "THOMAS Eve", NA, NA),
Relay_Swimmer_4 = c("FORDE Brooke", "LI Bingjie", "BRUHN Annika",
"FABRE Margaux", "MASUDA Aoi", "GALLAGHER Erin", "TUNCEL Merve",
"AN Sehyeon", "COOK Tamsin", "PICKREM Sydney", "EGOROVA Anna",
"KESELY Ajna", "RONCATTO Gabrielle", "GALYER Ali", NA, NA
), Split_50 = c("27.56", "27.13", "27.59", "27.42", "27.52",
"27.66", "28.37", "28.09", "27.25", "27.38", "27.73", "28.18",
"28.04", "27.30", NA, "28.16"), Split_100 = c("57.35", "56.68",
"57.13", "57.46", "57.66", "57.40", "59.39", "58.78", "56.94",
"57.31", "57.45", "58.47", "57.99", "56.97", NA, "58.36"),
Split_150 = c("1:28.05", "1:26.86", "1:27.33", "1:27.81",
"1:28.17", "1:27.38", "1:31.71", "1:30.08", "1:26.70", "1:27.28",
"1:27.36", "1:28.78", "1:29.13", "1:27.34", NA, "1:29.74"
), Split_200 = c("1:58.59", "1:57.29", "1:57.29", "1:57.61",
"1:57.87", "1:58.41", "2:04.42", "2:01.27", "1:55.11", "1:58.18",
"1:57.26", "1:59.19", "2:00.15", "1:57.38", NA, "2:01.64"
), Split_250 = c("27.01", "26.60", "27.59", "27.46", "27.45",
"27.35", "28.33", "27.69", "25.87", "26.59", "27.70", "27.17",
"27.29", "28.01", NA, NA), Split_300 = c("55.94", "56.43",
"57.19", "57.68", "58.18", "57.76", "59.31", "58.08", "55.03",
"55.93", "57.84", "56.74", "57.28", "59.13", NA, NA), Split_350 = c("1:25.60",
"1:27.17", "1:27.69", "1:28.27", "1:29.10", "1:28.84", "1:30.91",
"1:28.87", "1:25.70", "1:25.87", "1:28.78", "1:27.11", "1:28.93",
"1:30.57", NA, NA), Split_400 = c("1:55.96", "1:57.63", "1:59.00",
"1:58.59", "1:59.94", "2:00.53", "2:02.03", "1:59.98", "1:57.01",
"1:55.99", "1:58.87", "1:57.88", "2:01.50", "2:02.18", NA,
NA), Split_450 = c("26.45", "27.15", "27.65", "27.93", "26.88",
"27.32", "28.48", "28.21", "26.11", "26.65", "27.34", "27.94",
"27.62", "28.64", NA, NA), Split_500 = c("55.68", "56.52",
"58.03", "58.38", "57.15", "57.59", "1:00.20", "59.50", "55.61",
"56.28", "57.13", "58.62", "57.44", "59.87", NA, NA), Split_550 = c("1:25.66",
"1:26.74", "1:28.45", "1:28.79", "1:28.43", "1:28.46", "1:32.34",
"1:32.01", "1:25.91", "1:26.66", "1:27.81", "1:29.56", "1:28.39",
"1:30.62", NA, NA), Split_600 = c("1:56.02", "1:57.77", "1:58.73",
"1:59.39", "2:00.25", "1:59.75", "2:04.15", "2:04.38", "1:56.46",
"1:57.53", "1:57.77", "2:00.35", "1:59.18", "2:00.75", NA,
NA), Split_650 = c("27.52", "26.92", "26.58", "27.07", "27.06",
"27.16", "28.54", "28.67", "26.77", "27.27", "27.24", "26.79",
"27.53", "28.44", NA, NA), Split_700 = c("56.73", "56.65",
"55.71", "57.07", "57.22", "57.85", "59.54", "1:00.60", "56.14",
"57.86", "57.24", "56.52", "57.71", "1:00.45", NA, NA), Split_750 = c("1:26.75",
"1:26.76", "1:26.14", "1:28.21", "1:28.56", "1:29.78", "1:30.43",
"1:33.35", "1:26.08", "1:29.54", "1:27.56", "1:27.17", "1:28.31",
"1:33.23", NA, NA), Split_800 = c("1:57.00", "1:56.29", "1:57.04",
"1:59.46", "2:00.33", "2:02.87", "2:00.36", "2:05.53", "1:56.03",
"1:59.82", "1:58.14", "1:58.74", "1:58.67", "2:05.85", NA,
NA)), row.names = c(NA, -16L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo Men 50 Free Final, need to not pull out relay swimmers",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Tokyo2020/SWMM50MFR_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c("1", "2", "3", "4", "5", "5", "7", "8"),
Heat = rep("Final", 8),
Lane = c("4", "5", "3", "7", "2", "6", "1", "8"),
Name = c(
"DRESSEL Caeleb",
"MANAUDOU Florent",
"FRATUS Bruno",
"ANDREW Michael",
"PROUD Benjamin",
"GKOLOMEEV Kristian",
"ZAZZERI Lorenzo",
"de BOER Thom"
),
Team = c("USA",
"FRA", "BRA", "USA", "GBR", "GRE", "ITA", "NED"),
Reaction_Time = c("0.63",
"0.61", "0.64", "0.66", "0.58", "0.63", "0.61", "0.63"),
Finals = c(
"21.07",
"21.55",
"21.57",
"21.60",
"21.72",
"21.72",
"21.78",
"21.79"
),
DQ = c("0", "0", "0", "0", "0", "0", "0", "0"),
Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"),
Event = c(
"Men's 50m Freestyle",
"Men's 50m Freestyle",
"Men's 50m Freestyle",
"Men's 50m Freestyle",
"Men's 50m Freestyle",
"Men's 50m Freestyle",
"Men's 50m Freestyle",
"Men's 50m Freestyle"
),
Split_50 = c(
"21.07",
"21.55",
"21.57",
"21.60",
"21.72",
"21.72",
"21.78",
"21.79"
)
),
row.names = c(NA,-8L),
class = "data.frame"
)
expect_equivalent(df_standard,
df_test)
})
#### Para 2020 ####
test_that("Tokyo Para SM6 200 IM Final, swimmer with long name distorts pdf format",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/SwimmeR%20Test%20Files/PG2020_SWMM200MIM_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8"
), Heat = c("Final", "Final", "Final", "Final", "Final", "Final",
"Final", "Final"), Lane = c("4", "5", "3", "2", "8", "7", "6",
"1"), Name = c("CRISPIN CORZO Nelson", "GRANICHKA Andrei", "JIA Hongguang",
"YANG Hong", "WANG Jingang", "GLOCK Talisson Henrique", "GUTIERREZ BERMUDEZ Juan Jose",
"SHATTUCK Zach"), Para = c("SM6", "SM6", "SM6", "SM6", "SM6",
"SM6", NA, "SM6"), Team = c("COL", "RPC", "CHN", "CHN", "CHN",
"BRA", "MEX", "USA"), Reaction_Time = c("0.66", "0.79", "0.92",
"0.76", "0.90", "0.90", "0.58", "0.52"), Finals = c("2:38.12",
"2:40.92", "2:41.29", "2:41.34", "2:43.74", "2:45.17", "2:48.79",
"2:52.52"), DQ = c("0", "0", "0", "0", "0", "0", "0", "0"), Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"), Event = c("Men's 200m Individual Medley - SM6",
"Men's 200m Individual Medley - SM6", "Men's 200m Individual Medley - SM6",
"Men's 200m Individual Medley - SM6", "Men's 200m Individual Medley - SM6",
"Men's 200m Individual Medley - SM6", "Men's 200m Individual Medley - SM6",
"Men's 200m Individual Medley - SM6"), Split_50 = c("31.62",
"34.54", "33.19", "35.40", "31.81", "34.43", "34.73", "35.15"
), Split_100 = c("42.56", "43.08", "39.76", "40.97", "41.59",
"43.50", "45.60", "47.50"), Split_150 = c("45.97", "46.84", "49.52",
"45.46", "49.97", "51.71", "46.90", "47.10"), Split_200 = c("37.97",
"36.46", "38.82", "39.51", "40.37", "35.53", "41.56", "42.77"
)), row.names = c(NA, -8L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo Para S11 50 Free Heats, DNS",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/SwimmeR%20Test%20Files/PG2020_SWMM50MFR_HEAT.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "1",
"2", "3", "4", "5", "6", "7", NA), Heat = c("Heat_1", "Heat_1",
"Heat_1", "Heat_1", "Heat_1", "Heat_1", "Heat_1", "Heat_2", "Heat_2",
"Heat_2", "Heat_2", "Heat_2", "Heat_2", "Heat_2", "Heat_2"),
Lane = c("4", "6", "5", "3", "7", "2", "1", "4", "5", "3",
"6", "7", "8", "1", "2"), Name = c("BELARMINO PEREIRA Wendell",
"RHEINE CORREA de SOUZA Matheus", "YANG Bozun", "SERBIN Mykhailo",
"MENESES Marco", "SMYRNOV Viktor", "GUNNARSSON Mar", "MATAKAS Edgaras",
"HUA Dongdong", "MAKOWSKI Wojciech", "CABRAJA Matthew", "GARIPOV Ilnur",
"DRAG Przemyslaw", "ARTIUKHOV Oleksandr", "ZUDZILAU Hryhory"
), Para = c("S11", "S11", "S11", "S11", "S11", "S11", "S11",
"S11", "S11", "S11", "S11", "S11", "S11", "S11", "S11"),
Team = c("BRA", "BRA", "CHN", "UKR", "POR", "UKR", "ISL",
"LTU", "CHN", "POL", "CAN", "RPC", "POL", "UKR", "BLR"),
Reaction_Time = c("0.69", "0.69", "0.76", "0.75", "0.87",
"0.84", "0.75", "0.61", "0.75", "0.78", "0.70", "0.68", "0.74",
"0.74", NA), Finals = c("26.47", "27.17", "27.19", "27.44",
"28.07", "28.31", "29.30", "26.16", "26.55", "27.92", "28.13",
"28.39", "29.02", "30.29", NA), DQ = c("0", "0", "0", "0",
"0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "1"), Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0",
"0", "0"), Event = c("Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11", "Men's 50m Freestyle - S11",
"Men's 50m Freestyle - S11"), Split_50 = c("26.47", "27.17",
"27.19", "27.44", "28.07", "28.31", "29.30", "26.16", "26.55",
"27.92", "28.13", "28.39", "29.02", "30.29", NA)), row.names = c(NA,
-15L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo Para Mixed 4x100 Free Relay 49 Points",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/SwimmeR%20Test%20Files/PG2020_SWMX4X100MFR_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6"), Heat = c("Final",
"Final", "Final", "Final", "Final", "Final"), Lane = c("3", "5",
"4", "6", "2", "7"), Team = c("RPC - RPC", "BRA - Brazil", "UKR - Ukraine",
"ESP - Spain", "JPN - Japan", "CHN - People's Republic of China"
), Finals = c("3:53.79", "3:54.95", "3:55.15", "4:03.38",
"4:08.66", "4:18.60"), DQ = c("0", "0", "0", "0", "0", "0"),
Exhibition = c("0", "0", "0", "0", "0", "0"), Event = c("Mixed 4x100m Freestyle Relay - 49 Points",
"Mixed 4x100m Freestyle Relay - 49 Points", "Mixed 4x100m Freestyle Relay - 49 Points",
"Mixed 4x100m Freestyle Relay - 49 Points", "Mixed 4x100m Freestyle Relay - 49 Points",
"Mixed 4x100m Freestyle Relay - 49 Points"), Relay_Swimmer_1 = c("GARIPOV Ilnur",
"BELARMINO PEREIRA Wendell", "PIDDUBNA Maryna", "CANTERO ELVIRA Jose Ramon",
"TOMITA Uchu", "HUA Dongdong"), Relay_Swimmer_1_Gender = c("M",
"M", "F", "M", "M", "M"), Relay_Swimmer_1_Para = c("S11",
"S11", "S11", "S11", "S11", "S11"), Relay_Swimmer_2 = c("KRIVSHINA Anna",
"MATERA Douglas", "VERAKSA Maksym", "DELGADO NADAL Maria",
"SAITO Genki", "LI Guizhi"), Relay_Swimmer_2_Gender = c("F",
"M", "M", "F", "M", "F"), Relay_Swimmer_2_Para = c("S13",
"S13", "S12", "S12", "S13", "S11"), Relay_Swimmer_3 = c("PIKALOVA Daria",
"da SILVA SOUSA Lucilene", "STETSENKO Anna", "EDO BELTRAN Ariadna",
"ISHIURA Tomomi", "CAI Liwen"), Relay_Swimmer_3_Gender = c("F",
"F", "F", "F", "F", "F"), Relay_Swimmer_3_Para = c("S12",
"S12", "S13", "S13", "S11", "S11"), Relay_Swimmer_4 = c("SOTNIKOV Vladimir",
"GOMES SANTIAGO Maria Carolina", "GARASHCHENKO Kyrylo", "SALGUERO OTEIZA Ivan",
"TSUJIUCHI Ayano", "YANG Bozun"), Relay_Swimmer_4_Gender = c("M",
"F", "M", "M", "F", "M"), Relay_Swimmer_4_Para = c("S13",
"S12", "S13", "S13", "S13", "S11"), Split_50 = c("28.78",
"27.28", "32.29", "29.28", "28.14", NA), Split_100 = c("1:01.68",
"58.84", "1:10.18", "1:00.99", "58.62", "58.73"), Split_150 = c("27.82",
"26.17", "25.45", "29.69", "27.01", "32.01"), Split_200 = c("58.60",
"55.60", "53.06", "1:01.73", "56.66", "1:06.13"), Split_250 = c("28.42",
"29.16", "28.73", "30.26", "33.44", "33.43"), Split_300 = c("59.06",
"1:01.86", "59.46", "1:05.48", "1:14.77", "1:09.67"), Split_350 = c("26.04",
"28.23", "25.04", "26.23", "28.17", "29.61"), Split_400 = c("54.45",
"58.65", "52.45", "55.18", "58.61", "1:04.07")), row.names = c(NA,
-6L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo Para men 4x100 Free Relay 34 Points, P in splits",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/SwimmeR%20Test%20Files/PG2020_SWMM4X100MFR_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8"
), Heat = c("Final", "Final", "Final", "Final", "Final", "Final",
"Final", "Final"), Lane = c("3", "4", "5", "2", "6", "1", "7",
"8"), Team = c("AUS - Australia", "ITA - Italy", "UKR - Ukraine",
"BRA - Brazil", "RPC - RPC", "CHN - People's Republic of China",
"ESP - Spain", "USA - United States of America"), Finals = c("3:44.31",
"3:45.89", "3:47.40", "3:52.28", "3:54.34", "4:00.18", "4:00.71",
"4:13.94"), DQ = c("0", "0", "0", "0", "0", "0", "0", "0"), Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"), Event = c("Men's 4x100m Freestyle Relay - 34 Points",
"Men's 4x100m Freestyle Relay - 34 Points", "Men's 4x100m Freestyle Relay - 34 Points",
"Men's 4x100m Freestyle Relay - 34 Points", "Men's 4x100m Freestyle Relay - 34 Points",
"Men's 4x100m Freestyle Relay - 34 Points", "Men's 4x100m Freestyle Relay - 34 Points",
"Men's 4x100m Freestyle Relay - 34 Points"), Relay_Swimmer_1 = c("CROTHERS Rowan",
"FANTIN Antonio", "BOZHYNSKYI Yurii", "GONCALVES SILVA Ruiter Antonio",
"MOZGOVOI Bogdan", "YANG Guanglong", "GARRIDO BRUN Jacobo", "GARCIA-TOLSON Rudy"
), Relay_Swimmer_1_Para = c("S10", "S6", "S9", "S9", "S9", "S8",
"S9", "S7"), Relay_Swimmer_2 = c("MARTIN William", "CIULLI Simone",
"DUBROV Denys", "FILHO Vanilton", "GLADKOV Andrei", "LIU Fengqi",
"MARTOS MINGUET Sergio Salvador", "PEPPERSACK Joseph"), Relay_Swimmer_2_Para = c("S9",
"S9", "S8", "S9", "S7", "S8", "S8", "S8"), Relay_Swimmer_3 = c("LEVY Matthew",
"BARLAAM Simone", "TRUSOV Andrii", "GLOCK Talisson Henrique",
"NIKOLAEV Andrei", "YANG Feng", "LLOPIS SANZ Inigo", "AUSTIN Evan"
), Relay_Swimmer_3_Para = c("S7", "S9", "S7", "S6", "S8", "S8",
"S8", "S7"), Relay_Swimmer_4 = c("POPHAM Ben", "RAIMONDI Stefano",
"KRYPAK Maksym", "MELO RODRIGUES Phelipe Andrews", "BARTASINSKII Dmitrii",
"XU Haijiao", "MARI ALCARAZ Jose Antonio", "HILL Jamal"), Relay_Swimmer_4_Para = c("S8",
"S10", "S10", "S10", "S10", "S8", "S9", "S9"), Split_50 = c("24.71",
"31.99", "28.16", "27.29", "27.80", "28.41", "28.66", "32.85"
), Split_100 = c("51.35", "1:04.20", "1:00.03", "57.77", "57.23",
"59.40", "58.52", "1:08.50"), Split_150 = c("25.72", "26.66",
"28.22", "27.56", "31.43", "28.10", "29.13", "29.93"), Split_200 = c("54.53",
"57.23", "58.94", "57.73", "1:05.55", "58.72", "1:02.84", "1:03.01"
), Split_250 = c("28.97", "25.33", "27.64", "31.40", "27.95",
"29.27", "29.26", "31.36"), Split_300 = c("1:01.30", "53.69",
"58.19", "1:05.38", "57.79", "1:02.56", "1:01.88", "1:04.20"),
Split_350 = c("27.72", "23.76", "23.55", "23.84", "25.50",
"28.23", "27.50", "26.78"), Split_400 = c("57.13", "50.77",
"50.24", "51.40", "53.77", "59.50", "57.47", "58.23")), row.names = c(NA,
-8L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo Para Women 150IM-SM4",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Paralympics2020/raw_files/PG2020_SWMW150MIM_04042_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8"
), Heat = c("Final", "Final", "Final", "Final", "Final", "Final",
"Final", "Final"), Lane = c("4", "5", "3", "6", "7", "8", "1",
"2"), Name = c("LIU Yu", "ZHOU Yanfei", "BUTKOVA Nataliia", "FERNANDEZ INFANTE Marta",
"SMITH Leanne", "MIRANDA HERRERA Nely", "VERBOVA Maryna", "SCHNARNDORF Susana"
), Para = c("SM4", "SM4", "SM4", "SM4", "SM3", "SM4", "SM4",
"SM4"), Team = c("CHN", "CHN", "RPC", "ESP", "USA", "MEX", "UKR",
"BRA"), Reaction_Time = c("0.85", "1.05", "0.85", "0.90", "1.46",
"0.58", "0.75", "0.79"), Finals = c("2:41.91", "2:47.41",
"2:53.25", "2:59.13", "3:07.07", "3:08.71", "3:09.17", "3:11.54"
), DQ = c("0", "0", "0", "0", "0", "0", "0", "0"), Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"), Event = c("Women's 150m Individual Medley - SM4",
"Women's 150m Individual Medley - SM4", "Women's 150m Individual Medley - SM4",
"Women's 150m Individual Medley - SM4", "Women's 150m Individual Medley - SM4",
"Women's 150m Individual Medley - SM4", "Women's 150m Individual Medley - SM4",
"Women's 150m Individual Medley - SM4"), Split_50 = c("45.62",
"50.45", "54.14", "68.59", "59.85", "57.41", "53.92", "61.32"
), Split_100 = c("63.18", "68.72", "68.71", "64.53", "70.97",
"78.58", "72.07", "73.89"), Split_150 = c("53.11", "48.24", "50.40",
"46.01", "56.25", "52.72", "63.18", "56.33")), row.names = c(NA,
-8L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
test_that("Tokyo Para Mixed 4x50m Freestyle Relay - 20 Points",
{
skip_on_cran()
file <-
"https://raw.githubusercontent.com/gpilgrim2670/Pilgrim_Data/master/Paralympics2020/raw_files/PG2020_SWMX4X50MFR_10101_FNL.pdf"
df_test <- file %>%
read_results() %>%
swim_parse(splits = TRUE,
relay_swimmers = TRUE)
df_standard <-
structure(list(Place = c("1", "2", "3", "4", "5", "6", "7", "8"
), Heat = c("Final", "Final", "Final", "Final", "Final", "Final",
"Final", "Final"), Lane = c("6", "4", "7", "5", "3", "2", "8",
"1"), Team = c("CHN - People's Republic of China", "ITA - Italy",
"BRA - Brazil", "UKR - Ukraine", "ESP - Spain", "RPC - RPC",
"TUR - Turkey", "GBR - Great Britain"), Finals = c("2:15.49",
"2:21.45", "2:24.82", "2:24.89", "2:25.66", "2:35.66", "2:42.43",
"2:48.34"), DQ = c("0", "0", "0", "0", "0", "0", "0", "0"), Exhibition = c("0",
"0", "0", "0", "0", "0", "0", "0"), Event = c("Mixed 4x50m Freestyle Relay - 20 Points",
"Mixed 4x50m Freestyle Relay - 20 Points", "Mixed 4x50m Freestyle Relay - 20 Points",
"Mixed 4x50m Freestyle Relay - 20 Points", "Mixed 4x50m Freestyle Relay - 20 Points",
"Mixed 4x50m Freestyle Relay - 20 Points", "Mixed 4x50m Freestyle Relay - 20 Points",
"Mixed 4x50m Freestyle Relay - 20 Points"), Relay_Swimmer_1 = c("ZHANG Li",
"TERZI Giulia", "PEREIRA dos SANTOS Patricia", "OSTAPCHENKO Denys",
"PERALES Teresa", "BUTKOVA Nataliia", "KUTLU Koral Berkin", "KEARNEY Tully"
), Relay_Swimmer_1_Gender = c("F", "F", "F", "M", "F", "F", "M",
"F"), Relay_Swimmer_1_Para = c("S5", "S7", "S4", "S3", "S5",
"S4", "S5", "S5"), Relay_Swimmer_2 = c("ZHENG Tao", "TRIMI Arjola",
"de FARIA DIAS Daniel", "SEMENENKO Yaroslav", "FERNANDEZ INFANTE Marta",
"PALIAN Ani", "BOYACI Sumeyye", "LONGHORNE Lyndon"), Relay_Swimmer_2_Gender = c("M",
"F", "M", "M", "F", "F", "F", "M"), Relay_Swimmer_2_Para = c("S5",
"S3", "S5", "S5", "S4", "S7", "S5", "S4"), Relay_Swimmer_3 = c("YUAN Weiyi",
"BEGGIATO Luigi", "da SILVA NEVES EUZEBIO J", "HONTAR Anna",
"SANCHEZ SIERRA David", "ZHDANOV Roman", "OZTURK Sevilay", "CHALLIS Ellie"
), Relay_Swimmer_3_Gender = c("M", "M", "F", "F", "M", "M", "F",
"F"), Relay_Swimmer_3_Para = c("S5", "S4", "S5", "S6", "S6",
"S4", "S5", "S3"), Relay_Swimmer_4 = c("LU Dong", "FANTIN Antonio",
"GLOCK Talisson Henrique", "MERESHKO Yelyzaveta", "PONCE BERTRAN Antoni",
"KUBASOV Artur", "EROGLU Beytullah", "PERRY William"), Relay_Swimmer_4_Gender = c("F",
"M", "M", "F", "M", "M", "M", "M"), Relay_Swimmer_4_Para = c("S5",
"S6", "S6", "S6", "S5", "S5", "S5", "S6"), Split_50 = c("36.22",
"32.89", "44.85", "46.46", "38.56", "44.11", "36.03", "35.68"
), Split_100 = c("30.48", "40.39", "31.58", "32.30", "40.43",
"33.47", "43.05", "44.11"), Split_150 = c("31.38", "39.16", "37.72",
"33.20", "31.97", "41.41", "44.08", "55.13"), Split_200 = c("37.41",
"29.01", "30.67", "32.93", "34.70", "36.67", "39.27", "33.42"
)), row.names = c(NA, -8L), class = "data.frame")
expect_equivalent(df_standard,
df_test)
})
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.