plotStateTransition: Creating State Transition Plot

In HVT: Constructing Hierarchical Voronoi Tessellations and Overlay Heatmaps for Data Analysis

Creating State Transition Plot

Description

This is the main function to create a state transition plot from a data frame. A state transition plot is a type of data visualization used to represent the changes or transitions in states over time for a given system. State refers to a particular condition or status of a cell at a specific point in time. Transition refers to the change of state for a cell from one condition to another over time.

Usage

plotStateTransition(
  df,
  sample_size = NULL,
  line_plot = NULL,
  cellid_column,
  time_column,
  v_intercept = NULL,
  time_periods = NULL
)

Arguments

df	Data frame. The Input data frame should contain two columns. Cell ID from scoreHVT function and time stamp of that dataset.
sample_size	Numeric. An integer indicating the fraction of the data frame to visualize in the plot. Default value is 0.2
line_plot	Logical. A logical value indicating to create a line plot. Default value is NULL.
cellid_column	Character. Name of the column containing cell IDs.
time_column	Character. Name of the column containing time stamps.
v_intercept	Numeric. A numeric value indicating the time stamp to draw a vertical line on the plot.
time_periods	List. A list of vectors, each containing start and end times for highlighting time periods.

Value

A plotly object representing the state transition plot for the given data frame.

Author(s)

PonAnuReka Seenivasan <[e-mail]>, Vishwavani <[e-mail]>

Examples

dataset <- data.frame(date = as.numeric(time(EuStockMarkets)),
DAX = EuStockMarkets[, "DAX"],
SMI = EuStockMarkets[, "SMI"],
CAC = EuStockMarkets[, "CAC"],
FTSE = EuStockMarkets[, "FTSE"])

hvt.results<- trainHVT(dataset,n_cells = 60, depth = 1, quant.err = 0.1,
                       distance_metric = "L1_Norm", error_metric = "max",
                       normalize = TRUE,quant_method = "kmeans")
scoring <- scoreHVT(dataset, hvt.results)
cell_id <- scoring$scoredPredictedData$Cell.ID
time_stamp <- dataset$date
dataset <- data.frame(cell_id, time_stamp)
plotStateTransition(dataset, sample_size = 1, cellid_column = "cell_id",time_column = "time_stamp")

HVT documentation built on April 3, 2025, 8:45 p.m.