plotStateTransition: 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
)

Value

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

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.

Author

PonAnuReka Seenivasan <ponanureka.s@mu-sigma.com>

Examples

Run this code

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")