RollingFunctions.jl

This package makes it easy to summarize windowed data.

A function is applied to successive data subsequences.

You give a summarizing function 𝐹𝑢𝑛𝑐, the data𝐷𝑎𝑡𝑎, and a window span 𝑆𝑝𝑎𝑛.

The result 𝑅 is of length 𝑅ᴺ, 𝑅ᴺ = length(𝐷𝑎𝑡𝑎) - 𝑆𝑝𝑎𝑛 + 1.

• the result omits 𝑅ᴼ = 𝑆𝑝𝑎𝑛 - 1 indices into 𝐷𝑎𝑡𝑎.

there are ways for the results match the data in length

Use a single, shared padding value

• rolling(function, data, window_span; padding = missing)

• this will fill the initial result values with the padding value

  • pads these values(result[1], .., result[pad_nindices])

• rolling(function, data, window_span; padding = missing, padlast = true)

• this will fill the final result values with the padding value

  • pads these values(result[n-pad_nindices+1], .., result[n])

Pad with a vector of values with length matching the extra indicies ( 𝑅ᴼ)

• this fills the extra indices with values obtained bycopying

Use an empty vector

• this fills the extra indices with values obtained bytrimming

• trimming evaluates the window function over available data

  • trimmed window spans are less than the specified window_span

Use a vector of𝓃 padding values

• where1 <= 𝓃 < 𝑅ᴼ.

• this first pads then trims to assign the extra indices

  • the first𝓃 indices of the result will match this vector
  • the next 𝑅ᴼ - 𝓃 indices of the result will be trimmed
  • the remaining indices get the rolled results.