Asymptotic Complexity Classification function — asymptoticComplexityClass • testComplexity

Function to classify the complexity trend between two selected parameters from the data frame provided as input here

asymptoticComplexityClass(df, output.size, data.size)

Arguments

df	A data frame composing for two columns at the least, where one should be the contain the output-parameter sizes and one should contain the data sizes.
output.size	A string specifying the column name in the passed data frame to be used as the output size.
data.size	A string specifying the column name in the passed data frame to be used as the data size.

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:
asymptoticComplexityClass(df, output.size = "Timings", data.size = "Data sizes")
# For quick sort, the log-linear time complexity class is expected.
}