Function to classify the complexity trend between the two parameters as provided by asymptoticComplexityClass

asymptoticComplexityClassifier(df)

Arguments

df

A data frame returned by asymptoticComplexityClass.

Value

A string specifying the resultant complexity class. (Eg: 'Linear', 'Log-linear', 'Quadratic')

Details

For more information regarding its implementation or functionality/usage, please check https://anirban166.github.io//Generalized-complexity/

Examples

# Avoiding for CRAN since computation time might exceed 5 seconds sometimes: if (FALSE) { # Running the quick sort algorithm with sampling against a set of increasing input data sizes: sizes = 10^seq(1, 3, by = 0.5) df <- asymptoticTimings(sort(sample(1:100, data.sizes, replace = TRUE), method = "quick"), sizes) # Classifying the complexity trend between the data contained in the columns # 'Timings' and 'Data sizes' from the data frame obtained above: resultant.df <- data.frame('output' = df$Timings, 'size' = df$`Data sizes`) asymptoticComplexityClassifier(resultant.df) # For quick sort, the log-linear time complexity class is expected. }