allPeriodogramsSleep: Periodogram analysis for sleep data

View source: R/allPeriodogramsSleep.R

allPeriodogramsSleepR Documentation

Periodogram analysis for sleep data

Description

This function generates a composite figure with periodogram plots for all flies in a DAM scanned monitor file. Input for this function must be an output from the sleepData() function. The output of this function is a list with two components - (a) large plotly object with periodogram plots for all flies, and (b) a table which has channel wise information of significant period and adjusted power values, from the chosen time-series analysis method. This function requires the packages "plotly" and "zeitgebr".

Usage

allPeriodogramsSleep(
  data,
  bin = 30,
  method = "ChiSquare",
  low.per = 16,
  high.per = 32,
  alpha = 0.05,
  time.res = 20
)

Arguments

data

Input data file. The input for this function must be an output from one of either sleepData(). See ??sleepData().

bin

Intervals in which input data is saved (in minutes). This defaults to 30.

method

Choose the method for performing time-series analysis. Currently, three methods are implemented for analysis - "ChiSquare", "Autocorrelation", and "LombScargle". This defaults to "ChiSquare".

low.per

Choose the lowest period (in hours) for analysis. This defaults to 16.

high.per

Choose the highest period (in hours) for analysis. This defaults to 32.

alpha

Choose the significance level for periodogram analysis. This defaults to 0.05.

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.

Value

A list with two items:

Plots

A plotly htmlwidget with all periodograms in a 4-by-8 array.

Data

A matrix array with 32 rows (one for each fly) and 2 columns (Period and Adjusted Power).

Examples

td <- trimData(data = df, start.date = "19 Dec 20", start.time = "21:00",
n.days = 5, bin = 1, t.cycle = 24)
sd <- sleepData(td)
all.periodograms.sleep <- allPeriodogramsSleep(data = sd[,1:6])

phase documentation built on April 1, 2023, 12:10 a.m.