New distribution

Include WindowData

Project.toml

@@ -1,7 +1,7 @@
 name = "EntropyHub"
 uuid = "3938faea-3bfa-4bc3-8092-0c6746ff9af1"
 authors = ["Matthew W. Flood <[email protected]>"]
-version = "1.0.0"
+version = "1.0.1"
 
 [deps]
 Clustering = "aaaa29a8-35af-508c-8bc3-b662a17a0fe5"

docs/src/index.md

@@ -88,7 +88,7 @@ __________________________________________________________________
 If you find this package useful, please consider starring it on [GitHub](https://github.com/MattWillFlood/EntropyHub.jl) 
 and Julia Packages (or MatLab File Exchange and PyPI). This helps us to gauge user satisfaction.
 
-## Functions
+## Function List
 
 EntropyHub functions fall into 5 categories: 
 

src/EntropyHub.jl

@@ -49,7 +49,9 @@ export
     hXMSEn,
 
     EMD,
-    ExampleData
+    ExampleData,
+    WindowData
+
 
 # using Reexport
 
@@ -85,6 +87,7 @@ include("./_XPermEn.jl"),
 
 include("./_MSobject.jl"),
 include("./_ExampleData.jl"),
+include("./_WindowData.jl"),
 
 include("./_MSEn.jl"),
 include("./_XMSEn.jl"),
@@ -156,6 +159,7 @@ using ._rXMSEn: rXMSEn
 using ._hXMSEn: hXMSEn
 
 using ._ExampleData: ExampleData
+using ._WindowData: WindowData
 
 greet() = print(raw"""  
      ___  _   _  _____  _____  ____  ____  _     _

src/_WindowData.jl

@@ -0,0 +1,84 @@
+module _WindowData
+export WindowData
+    """    
+        WinData, Log = WindowData(Data) 
+
+    Windows the sequence(s) given in `Data` into a collection of subsequnces  
+    of floor(N/5) elements with no overlap, excluding any remainder
+    elements that do not fill the final window.
+    If `Data` is a univariate sequence (vector), `Windata` is a vector of 5
+    vectors. If `Data` is a set of multivariate sequences (NxM matrix), 
+    each of M columns is treated as a sequence with N elements 
+    and `WinData` is a vector of 5 matrices of size [(floor*N,5), M]. 
+    The `Log` dictionary contains information about the windowing process, including:
+    `DataType`      - The type of data sequence passed as `Data`\n
+    `DataLength`    - The number of sequence elements in `Data`\n
+    `WindowLength`  - The number of elements in each window of `WinData`\n
+    `WindowOverlap` - The number of overlapping elements between windows\n
+    `TotalWindows`  - The number of windows extracted from `Data`\n
+    `Mode`          - Decision to include or exclude any remaining sequence 
+                        elements (`< WinLen`) that do not fill the window.\n
+
+        WinData, Log = WindowData(Data::AbstractArray{T} where T<:Real, WinLen::Union{Nothing,Int}=nothing, Overlap::Int=0, Mode::String="exclude")
+
+    Windows the sequence(s) given in `Data` into a collection of subsequnces
+    using the specified keyword arguments: 
+
+    # Arguments:
+    `WinLen`  - Number of elements in each window, a positive integer (>10)\n
+    `Overlap` - Number of overlapping elements between windows, a positive integer (< WinLen)\n
+    `Mode`    - Decision to include or exclude any remaining sequence
+                    elements (< `WinLen`) that do not fill the window,
+                    a string - either `"include"` or `"exclude"` (default).\n
+
+    # See also  `ExampleData`
+    """
+    function WindowData(Data::AbstractArray{T} where T<:Real;
+                            WinLen::Union{Nothing,Int}=nothing, Overlap::Int=0, Mode::String="exclude")
+
+    if ndims(Data)==1 
+        DataType =  "single univariate vector (1 sequence)"
+        N = length(Data)
+        Dn = 0 
+    elseif ndims(Data)==2 
+        N, Dn = size(Data)
+        DataType = "multivariate matrix ("*string(Dn)*" vectors)"
+    else
+        error("Only a vector or a Matrix can be passed as Data!")
+    end
+    (N>10) ? nothing : error("Data:   must be a numpy Vector (length N) or an NxM numpy matrix where N>10 and M>1")
+    (isnothing(WinLen)) ? WinLen = Int(floor(N/5)) : nothing
+    (10<WinLen<N) ? nothing : error("WinLen: must be an integer such that 10 < WinLen < N")
+    (0<=Overlap<WinLen) ? nothing : error("Overlap: The number of overlapping window samples such that 0 <= Overlap < WinLen")
+    (lowercase(Mode) in ["exclude","include"]) ? nothing : error("Mode: Option to include/exclude samples that do not fill final window, either 'exclude' or 'include'") 
+
+    M = Int(floor((N - Overlap)/(WinLen - Overlap)))
+    Step = Int(WinLen-Overlap)
+    Xout = []
+    map(k -> push!(Xout, Data[k:k+WinLen-1,:]), 1:Step:M*Step)        
+    (lowercase(Mode)=="include" && (length(Xout)-1)*Step+WinLen!=N) ? (push!(Xout, Data[1+M*Step:end,:]); M+=1) : nothing
+
+    Log = Dict("DataType" => DataType, "DataLength" => N, "WindowLength" => WinLen,
+               "WindowOverlap" => Overlap,  "TotalWindows" => M,   "Mode" => Mode)
+
+    return Xout, Log
+    end
+end
+
+"""
+    Copyright 2024 Matthew W. Flood, EntropyHub
+    
+    Licensed under the Apache License, Version 2.0 (the "License");
+    you may not use this file except in compliance with the License.
+    You may obtain a copy of the License at
+    
+     http://www.apache.org/licenses/LICENSE-2.0
+    
+    Unless required by applicable law or agreed to in writing, software
+    distributed under the License is distributed on an "AS IS" BASIS,
+    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+    See the License for the specific language governing permissions and
+    limitations under the License.
+    
+    For Terms of Use see https://github.com/MattWillFlood/EntropyHub
+"""