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November 13, 2018 22:20
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identifies higher and lower high/low tides
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| assignTide <- function(data, timeCol = "time", levelCol = "level", tideCol = "tide") { | |
| ### this works well with output from HL() | |
| ### arguments: | |
| ### data = the data frame | |
| ### timeCol = name of column with time stamp data, in format "YYYY-MM-DD ..." | |
| ### levelCol = name of column with water level data (numeric) | |
| ### tideCol = name of column with tide indicator (H/L) - this is tailored to HL() output | |
| data[, "day"] <- substr(data[, timeCol], 1, 10) # weak point - assumes YYYY-MM-DD format | |
| data[, "tide2"] <- NA | |
| for (i in 1:length(unique(data[, "day"]))) { | |
| numLowTides <- sum(!is.na(data[, levelCol][(data[, "day"] == unique(data[, "day"])[i]) & (data[, tideCol] %in% "L")])) | |
| numHighTides <- sum(!is.na(data[, levelCol][(data[, "day"] == unique(data[, "day"])[i]) & (data[, tideCol] %in% "H")])) | |
| if (numHighTides == 2) { | |
| # find higher & lower high tides | |
| hh <- which.max(data[, levelCol][(data[, "day"] == unique(data[, "day"])[i]) & (data[, tideCol] %in% "H")]) | |
| lh <- which.min(data[, levelCol][(data[, "day"] == unique(data[, "day"])[i]) & (data[, tideCol] %in% "H")]) | |
| # define new tides | |
| data[, "tide2"][(data[, "day"] == unique(data[, "day"])[i]) & (data[, tideCol] %in% "H")][hh] <- "HH" | |
| data[,"tide2"][(data[, "day"] == unique(data[, "day"])[i]) & (data[, tideCol] %in% "H")][lh] <- "LH" | |
| } else if (numHighTides == 1) { | |
| ### define value based on previous or subsequent values | |
| data[,"tide2"][(data[, "day"] == unique(data[, "day"])[i]) & (data[, tideCol] %in% "H")] <- rev(data[,"tide2"][(data[, tideCol] %in% "H") & (!is.na(data[,"tide2"]))])[2] # copy the second most recent HH/LH value (may bewrong if there's a gap in the data) | |
| } | |
| if (numLowTides == 2) { | |
| hl <- which.max(data[, levelCol][(data[, "day"] == unique(data[, "day"])[i]) & (data[, tideCol] %in% "L")]) | |
| ll <- which.min(data[, levelCol][(data[, "day"] == unique(data[, "day"])[i]) & (data[, tideCol] %in% "L")]) | |
| data[,"tide2"][(data[, "day"] == unique(data[, "day"])[i]) & (data[, tideCol] %in% "L")][hl] <- "HL" | |
| data[,"tide2"][(data[, "day"] == unique(data[, "day"])[i]) & (data[, tideCol] %in% "L")][ll] <- "LL" | |
| } else if (numLowTides == 1) { | |
| ### define value based on previous or subsequent values | |
| data[,"tide2"][(data[, "day"] == unique(data[, "day"])[i]) & (data[, tideCol] %in% "L")] <- rev(data[,"tide2"][(data[, tideCol] %in% "L") & (!is.na(data[,"tide2"]))])[2] | |
| } | |
| } | |
| invisible(data) | |
| } | |
| ### an example: | |
| library(VulnToolkit) | |
| data(NL_6min_2013) | |
| nl.hl <- HL(level = NL_6min_2013[, 2], time = NL_6min_2013[, 1]) | |
| nl.hl <- assignTide(data = nl.hl) | |
| head(nl.hl) |
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