R/indPeriodogramAct.R

In phase: Analyse Biological Time-Series Data

#' Periodogram plot for activity data of individual flies
#'
#' @description
#' This function generates a periodogram for the activity data of a single fly. Input for this function must be an output from the trimData() function. The output of this function is a plotly object.
#'
#' @param data Input data file. If the method for analysis is "ChiSquare", then the input for this function must be the output of the function trimData(). See ??trimData(). Otherwise, the input for this function must be the output of the function binData(). See ??binData().
#' @param bin Intervals in which data are sampled (in minutes). This defaults to 1. This must be changed appropriately depending on method of analysis and the input data set.
#' @param method Choose the method for performing time-series analysis. Currently, three methods are implemented for analysis - "ChiSquare", "Autocorrelation", and "LombScargle". This defaults to "ChiSquare".
#' @param low.per Choose the lowest period (in hours) for analysis. This defaults to 16.
#' @param high.per Choose the highest period (in hours) for analysis. This defaults to 32.
#' @param alpha Choose the significance level for periodogram analysis. This defaults to 0.05.
#' @param time.res Resolution of periods (in minutes) to analyse while using the ChiSquare periodogram. For instance, if users wish to scan periods from low.per to high.per in the following manner: 16, 16.5, 17, 17.5, and so on, then time.res must be 30. This defaults to 20.
#' @param ind The channel number (or individual) whose periodogram must be plotted.
#'
#' @importFrom zeitgebr chi_sq_periodogram ac_periodogram ls_periodogram
#' @importFrom behavr hours mins
#' @importFrom plotly plot_ly add_trace layout %>% subplot
#' @importFrom grDevices rgb
#' @importFrom stats aggregate fitted lm na.omit sd
#' 
#' @return A \code{plotly} \code{htmlwidget} with the individual periodogram of a user defined fly.
#'
#' @export indPeriodogramAct
#'
#' @examples
#' td <- trimData(data = df, start.date = "19 Dec 20", start.time = "21:00",
#' n.days = 10, bin = 1, t.cycle = 24)
#' ind.periodogram.act <- indPeriodogramAct(data = td, ind = 13)

indPeriodogramAct <- function(data, bin = 1, method = "ChiSquare", low.per = 16, high.per = 32, alpha = 0.05, time.res = 20, ind = 1) {

  requireNamespace("zeitgebr")
  requireNamespace("behavr")
  requireNamespace("plotly")
  
  if (requireNamespace("plotly", quietly = T)) {
    # library(zeitgebr)
    # library(behavr)
    # library(plotly)
    
    if ("ChiSquare" %in% method){
      raw <- data[,(10+ind)]
      sr <- 1/behavr::mins(bin)
      
      x <- as.matrix(zeitgebr::chi_sq_periodogram(as.vector(raw),
                                                  period_range = as.integer(c(behavr::hours(low.per),
                                                                              behavr::hours(high.per))),
                                                  sampling_rate = sr, alpha = alpha,
                                                  time_resolution = behavr::mins(time.res)))
      
      adj.power <- matrix(x[,"power"] - x[,"signif_threshold"], ncol = 1)
      y <- cbind(x, adj.power)
      colnames(y)[5] <- c("adj.power")
      
      ind_data <- y
      
    } else if ("Autocorrelation" %in% method) {
      raw <- data[,(1+ind)]
      sr <- 1/behavr::mins(bin)
      
      x <- as.matrix(zeitgebr::ac_periodogram(as.vector(raw),
                                              period_range = as.integer(c(behavr::hours(low.per),
                                                                          behavr::hours(high.per))),
                                              sampling_rate = sr, alpha = alpha))
      
      adj.power <- matrix(x[,"power"] - x[,"signif_threshold"], ncol = 1)
      y <- cbind(x, adj.power)
      colnames(y)[5] <- c("adj.power")
      
      ind_data <- y
      
    } else if ("LombScargle" %in% method) {
      raw <- data[,(1+ind)]
      sr <- 1/behavr::mins(bin)
      
      x <- as.matrix(zeitgebr::ls_periodogram(as.vector(raw),
                                              period_range = as.integer(c(behavr::hours(low.per),
                                                                          behavr::hours(high.per))),
                                              sampling_rate = sr, alpha = alpha))
      
      adj.power <- matrix(x[,"power"] - x[,"signif_threshold"], ncol = 1)
      y <- cbind(x, adj.power)
      colnames(y)[5] <- c("adj.power")
      
      ind_data <- y
      
    }
    
    f1 <- list(
      family = "Arial, sans-serif",
      size = 24,
      color = "black"
    )
    f2 <- list(
      family = "Arial, sans-serif",
      size = 20,
      color = "black"
    )
    ax <- list(
      showgrid = F,
      showline = T,
      titlefont = f1,
      tickfont = f2,
      title = "Period (h)",
      linecolor = "black",
      linewidth = 4,
      mirror = TRUE,
      autotick = FALSE,
      ticks = "inside",
      tick0 = low.per,
      dtick = 4,
      ticklen = 7,
      tickcolor = "black",
      tickwidth = 4,
      range = c(low.per-1, high.per+1)
    )
    ay <- list(
      showgrid = F,
      showline = T,
      titlefont = f1,
      tickfont = f2,
      title = "Power",
      linecolor = "black",
      linewidth = 4,
      mirror = TRUE,
      autotick = TRUE,
      ticks = "inside",
      ticklen = 7,
      tickcolor = "black",
      tickwidth = 4
      # tick0 = 0,
      # dtick = max(ind_data$power)/6
    )
    
    ind.plot <- plot_ly(x = ind_data[,"period"]/3600,
                        y = ind_data[,"adj.power"],
                        name = paste("Channel: ", ind, sep = ""),
                        type = "scatter",
                        mode = "lines",
                        line = list(color = "black", width = 2),
                        source = "period_power_ind_act"
    )%>%
      add_trace(
        y = rep(0, length(ind_data[,1])),
        line = list(
          color = "red",
          width = 2
        )
      )%>%
      layout(
        showlegend = FALSE,
        xaxis = ax,
        yaxis = ay
      )
    
    return(ind.plot) 
  }

}