Formatting

src/interpolation_caches.jl

@@ -136,7 +136,7 @@ end
 """
     AkimaInterpolation(u, t; extrapolate = false, safetycopy = true)
 
-It is a spline interpolation built from cubic polynomials. It forms a continuously differentiable function. For more details, refer: <https://en.wikipedia.org/wiki/Akima_spline>.
+It is a spline interpolation built from cubic polynomials. It forms a continuously differentiable function. For more details, refer: [https://en.wikipedia.org/wiki/Akima_spline](https://en.wikipedia.org/wiki/Akima_spline).
 Extrapolation extends the last cubic polynomial on each side.
 
 ## Arguments
@@ -420,7 +420,7 @@ end
 """
     BSplineInterpolation(u, t, d, pVecType, knotVecType; extrapolate = false, safetycopy = true)
 
-It is a curve defined by the linear combination of `n` basis functions of degree `d` where `n` is the number of data points. For more information, refer <https://pages.mtu.edu/~shene/COURSES/cs3621/NOTES/spline/B-spline/bspline-curve.html>.
+It is a curve defined by the linear combination of `n` basis functions of degree `d` where `n` is the number of data points. For more information, refer [https://pages.mtu.edu/~shene/COURSES/cs3621/NOTES/spline/B-spline/bspline-curve.html](https://pages.mtu.edu/%7Eshene/COURSES/cs3621/NOTES/spline/B-spline/bspline-curve.html).
 Extrapolation is a constant polynomial of the end points on each side.
 
 ## Arguments
@@ -550,7 +550,7 @@ end
     BSplineApprox(u, t, d, h, pVecType, knotVecType; extrapolate = false, safetycopy = true)
 
 It is a regression based B-spline. The argument choices are the same as the `BSplineInterpolation`, with the additional parameter `h < length(t)` which is the number of control points to use, with smaller `h` indicating more smoothing.
-For more information, refer <http://www.cad.zju.edu.cn/home/zhx/GM/009/00-bsia.pdf>.
+For more information, refer [http://www.cad.zju.edu.cn/home/zhx/GM/009/00-bsia.pdf](http://www.cad.zju.edu.cn/home/zhx/GM/009/00-bsia.pdf).
 Extrapolation is a constant polynomial of the end points on each side.
 
 ## Arguments
@@ -745,7 +745,7 @@ end
     PCHIPInterpolation(u, t; extrapolate = false, safetycopy = true)
 
 It is a PCHIP Interpolation, which is a type of `CubicHermiteSpline` where
-the derivative values `du` are derived from the input data in such a way that 
+the derivative values `du` are derived from the input data in such a way that
 the interpolation never overshoots the data. See also [here](https://www.mathworks.com/content/dam/mathworks/mathworks-dot-com/moler/interp.pdf),
 section 3.4.
 

src/interpolation_utils.jl

@@ -142,7 +142,7 @@ function du_PCHIP(u, t)
         elseif k == lastindex(t)
             s[end - 1], s[end]
         else
-           s[k - 1], s[k] 
+            s[k - 1], s[k]
         end
 
         if sₖ₋₁ == 0 && sₖ == 0
@@ -152,7 +152,7 @@ function du_PCHIP(u, t)
                 ((2 * h[1] + h[2]) * δ[1] - h[1] * δ[2]) / (h[1] + h[2])
             elseif k == lastindex(t)
                 ((2 * h[end] + h[end - 1]) * δ[end] - h[end] * δ[end - 1]) /
-                   (h[end] + h[end - 1])
+                (h[end] + h[end - 1])
             else
                 w₁ = 2h[k] + h[k - 1]
                 w₂ = h[k] + 2h[k - 1]