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DOC: Update docstrings in interp.jl to follow style guide #329

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DOC: Update docstrings in interp.jl to follow style guide #329

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Copilot Oct 4, 2025
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Update docstrings in interp.jl to follow style guide
Copilot Oct 4, 2025
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DOC: Minor edits in interp.jl
oyamad Oct 4, 2025
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65 changes: 42 additions & 23 deletions src/interp.jl
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Original file line number Diff line number Diff line change
@@ -1,26 +1,31 @@
"""
Linear interpolation in one dimension
LinInterp

##### Fields
Linear interpolation in one dimension.

- `breaks::AbstractVector` : A sorted array of grid points on which to interpolate
# Fields

- `vals::AbstractVector` : The function values associated with each of the grid points
- `breaks::AbstractVector`: A sorted array of grid points on which to interpolate.
- `vals::AbstractVector`: The function values associated with each of the grid points.

##### Examples
# Examples

```julia
breaks = cumsum(0.1 .* rand(20))
vals = 0.1 .* sin.(breaks)
li = LinInterp(breaks, vals)
julia> breaks = cumsum(0.1 .* rand(20));

# do interpolation via `call` method on a LinInterp object
li(0.2)
julia> vals = 0.1 .* sin.(breaks);

# use broadcasting to evaluate at multiple points
li.([0.1, 0.2, 0.3])
```
julia> li = LinInterp(breaks, vals);

julia> li(0.2) # do interpolation via `call` method on a LinInterp object
0.019866933079506122

julia> li.([0.1, 0.2, 0.3]) # use broadcasting to evaluate at multiple points
3-element Vector{Float64}:
0.009983341664682815
0.019866933079506122
0.02955202066613396
```
"""
struct LinInterp{TV<:AbstractArray,TB<:AbstractVector}
breaks::TB
Expand Down Expand Up @@ -133,22 +138,36 @@ end
(li::LinInterp{<:AbstractMatrix})(xp::Number) = li(xp, 1:li._ncol)

"""
interp(grid::AbstractVector, function_vals::AbstractVector)
interp(grid, function_vals)

Linear interpolation in one dimension.

# Arguments

Linear interpolation in one dimension
- `grid::AbstractVector`: A vector of grid points (will be sorted if not already sorted).
- `function_vals::AbstractVector`: The function values associated with each grid point.

##### Examples
# Returns

- `LinInterp`: A LinInterp object that can be called to perform linear interpolation.

# Examples

```julia
breaks = cumsum(0.1 .* rand(20))
vals = 0.1 .* sin.(breaks)
li = interp(breaks, vals)
julia> breaks = cumsum(0.1 .* rand(20));

julia> vals = 0.1 .* sin.(breaks);

julia> li = interp(breaks, vals);

# Do interpolation by treating `li` as a function you can pass scalars to
li(0.2)
julia> li(0.2) # Do interpolation by treating `li` as a function you can pass scalars to
0.019866933079506122

# use broadcasting to evaluate at multiple points
li.([0.1, 0.2, 0.3])
julia> li.([0.1, 0.2, 0.3]) # use broadcasting to evaluate at multiple points
3-element Vector{Float64}:
0.009983341664682815
0.019866933079506122
0.02955202066613396
```
"""
function interp(grid::AbstractVector, function_vals::AbstractVector)
Expand Down