derivatives

src/derivatives.jl

@@ -19,6 +19,19 @@ function _derivative(A::LinearInterpolation, t::Number, iguess)
     slope
 end
 
+function _derivative(A::SmoothedConstantInterpolation{<:AbstractVector}, t::Number, iguess)
+    idx = get_idx(A, t, iguess)
+    d_lower, d_upper, c_lower, c_upper = get_parameters(A, idx)
+
+    if (t - A.t[idx]) < d_lower
+        -2c_lower * ((t - A.t[idx]) / d_lower - 1) / d_lower
+    elseif (A.t[idx + 1] - t) < d_upper
+        2c_upper * (1 - (A.t[idx + 1] - t) / d_upper) / d_upper
+    else
+        zero(c_upper / oneunit(t))
+    end
+end
+
 function _derivative(A::QuadraticInterpolation, t::Number, iguess)
     idx = get_idx(A, t, iguess)
     Δt = t - A.t[idx]

src/interpolation_caches.jl

@@ -290,7 +290,7 @@ end
         cache_parameters = false, assume_linear_t = 1e-2)
 
 It is a method for interpolating constantly with forward fill, with smoothing around the
-value transitions to make the curve C1 smooth while the integral never drifts far from 
+value transitions to make the curve C1 smooth while the integral never drifts far from
 the integral of constant interpolation.
 
 ## Arguments
@@ -300,10 +300,10 @@ the integral of constant interpolation.
 
 ## Keyword Arguments
 
-  - `d_max`: the maximum distance in `t` from the data points the smoothing is allowed to reach. 
+  - `d_max`: the maximum distance in `t` from the data points the smoothing is allowed to reach.
   - `extrapolate`: boolean value to allow extrapolation. Defaults to `false`.
   - `cache_parameters`: precompute parameters at initialization for faster interpolation computations. Note: if activated, `u` and `t` should not be modified. Defaults to `false`.
-  - `assume_linear_t`: boolean value to specify a faster index lookup behaviour for
+  - `assume_linear_t`: boolean value to specify a faster index lookup behavior for
     evenly-distributed abscissae. Alternatively, a numerical threshold may be specified
     for a test based on the normalized standard deviation of the difference with respect
     to the straight line (see [`looks_linear`](@ref)). Defaults to 1e-2.

src/interpolation_methods.jl

@@ -146,9 +146,9 @@ function _interpolate(A::SmoothedConstantInterpolation{<:AbstractVector}, t::Num
     out = A.u[idx]
 
     if (t - A.t[idx]) < d_lower
-        out -= c_lower * (((t - A.t[idx]) / d_lower - 1))^2
+        out -= c_lower * ((t - A.t[idx]) / d_lower - 1)^2
     elseif (A.t[idx + 1] - t) < d_upper
-        out += c_upper * ((1 - (A.t[idx + 1] - t) / d_upper))^2
+        out += c_upper * (1 - (A.t[idx + 1] - t) / d_upper)^2
     end
 
     out