Add some more documentation

Project.toml

@@ -1,7 +1,7 @@
 name = "TimeAxes"
 uuid = "9a9fc9a6-283d-47e9-a2f6-b3a44e559ea3"
 authors = ["Zachary P. Christensen <[email protected]>"]
-version = "0.1.1"
+version = "0.2.0"
 
 [deps]
 AxisIndices = "f52c9ee2-1b1c-4fd8-8546-6350938c7f11"

README.md

@@ -2,6 +2,8 @@
 
 [![Build Status](https://travis-ci.com/Tokazama/TimeAxes.jl.svg?branch=master)](https://travis-ci.com/Tokazama/TimeAxes.jl)
 [![codecov](https://codecov.io/gh/Tokazama/TimeAxes.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/Tokazama/TimeAxes.jl)
+[![stable-docs](https://img.shields.io/badge/docs-stable-blue.svg)](https://Tokazama.github.io/TimeAxes.jl/stable)
+[![dev-docs](https://img.shields.io/badge/docs-dev-blue.svg)](https://Tokazama.github.io/TimeAxes.jl/dev)
 
 This package utilizes AxisIndices to interface with data that has a time axis.
 

docs/src/index.md

@@ -1,11 +1,88 @@
 # TimeAxes
 
+```@doc
+TimeAxes
+```
+
 ## Examples
 
+A simple array with a time dimension time units along the axis.
+```jldoctest doc_examples
+julia> using TimeAxes
+
+julia> using Unitful: s
+
+julia> A = NamedAxisArray{(:time,)}(collect(1:100), (1:100)s);
+```
+
+### Iteration
+
+One could use the time axis for iteration...
+```jldoctest doc_examples
+julia> sum([A[i] for i in axes(A, 1)])
+5050
+
+```
+
+
+...or windows of the time axis.
+```jldoctest doc_examples
+julia> A2 = sum([A[i] for i in AxisIterator(axes(A, 1), 10)])
+10-element NamedAxisArray{Int64,1}
+ • time - 1 s:1 s:10 s
+
+ 1 s 460
+ 2 s 470
+ 3 s 480
+ 4 s 490
+ 5 s 500
+ 6 s 510
+ 7 s 520
+ 8 s 530
+ 9 s 540
+ 10 s 550
+
+```
+
+Some other basic functions related to time data are also available.
+```jldoctest doc_examples
+julia> lag(A2, 1)
+9-element NamedAxisArray{Int64,1}
+ • time - 2 s:1 s:10 s
+
+ 2 s 460
+ 3 s 470
+ 4 s 480
+ 5 s 490
+ 6 s 500
+ 7 s 510
+ 8 s 520
+ 9 s 530
+ 10 s 540
+
+
+julia> lead(A2, 1)
+9-element NamedAxisArray{Int64,1}
+ • time - 1 s:1 s:9 s
+
+ 1 s 470
+ 2 s 480
+ 3 s 490
+ 4 s 500
+ 5 s 510
+ 6 s 520
+ 7 s 530
+ 8 s 540
+ 9 s 550
+
+```
+
+More time specific methods may be found in the [References](#References)
 
 
-## API
+## References
 
 ```@autodocs
 Modules = [TimeAxes]
+Order = [:type, :function]
 ```

src/timedim.jl

@@ -17,22 +17,26 @@ First time point along the time axis.
 """
 onset(x) = first(time_keys(x))
 
+"""
+ time_step(x)
+
+The time step/interval between each element.
+"""
+time_step(x) = step(time_keys(x))
+
 """
  duration(x)
 
 Duration of the event along the time axis.
 """
-function duration(x)
- out = time_end(x) - onset(x)
- return out + oneunit(out)
-end
+duration(x) = time_end(x) - onset(x) + time_step(x)
 
 """
  sampling_rate(x)
 
 Number of samples per second.
 """
-sampling_rate(x) = 1 / step(time_keys(x))
+sampling_rate(x) = 1 / time_step(x)
 
 """
  assert_timedim_last(x)
@@ -63,8 +67,8 @@ julia> A = NamedAxisArray{(:time,)}(collect(1:5), (1:5)s)
  5 s 5
 
 julia> lead(A, 1)
-4-element AxisArray{Int64,1}
- • dim_1 - 1 s:1 s:4 s
+4-element NamedAxisArray{Int64,1}
+ • time - 1 s:1 s:4 s
 
  1 s 2
  2 s 3
@@ -96,8 +100,8 @@ julia> A = NamedAxisArray{(:time,)}(collect(1:5), (1:5)s)
  5 s 5
 
 julia> lag(A, 1)
-4-element AxisArray{Int64,1}
- • dim_1 - 2 s:1 s:5 s
+4-element NamedAxisArray{Int64,1}
+ • time - 2 s:1 s:5 s
 
  2 s 1
  3 s 2
@@ -112,7 +116,10 @@ lag(A::AbstractArray, n::Int) = _lag(A, timedim(A), n)
 ###
 ### lead
 ###
-_lead(A::NamedAxisArray, dim::Int, n::Int)= _lead(parent(A), dim, n)
+function _lead(A::NamedAxisArray, dim::Int, n::Int)
+ return NamedDimsArray{dimnames(A)}(_lead(parent(A), dim, n))
+end
+
 function _lead(A::AxisArray{T,N}, dim::Int, n::Int) where {T,N}
  axs = axes(A)
  p = parent(A)[_lead_indices(axs, dim, n)...]
@@ -159,7 +166,9 @@ end
 ###
 ### lags
 ###
-_lag(A::NamedAxisArray, dim::Int, n::Int)= _lag(parent(A), dim, n)
+function _lag(A::NamedAxisArray, dim::Int, n::Int)
+ return NamedDimsArray{dimnames(A)}(_lag(parent(A), dim, n))
+end
 function _lag(A::AxisArray{T,N}, dim::Int, n::Int) where {T,N}
  axs = axes(A)
  p = parent(A)[_lag_indices(axs, dim, n)...]