Add CubicSplineMonotone to Interpolate.

src/Numerics/Interpolate.cs

@@ -201,7 +201,7 @@ namespace MathNet.Numerics
         }
 
         /// <summary>
-        /// Create an piecewise cubic Akima spline interpolation based on arbitrary points.
+        /// Create a piecewise cubic Akima spline interpolation based on arbitrary points.
         /// Akima splines are robust to outliers.
         /// </summary>
         /// <param name="points">The sample points t.</param>
@@ -221,6 +221,27 @@ namespace MathNet.Numerics
             return Interpolation.CubicSpline.InterpolateAkima(points, values);
         }
 
+        /// <summary>
+        /// Create a piecewise cubic monotone spline interpolation based on arbitrary points.
+        /// This is a shape-preserving spline with continuous first derivative.
+        /// </summary>
+        /// <param name="points">The sample points t.</param>
+        /// <param name="values">The sample point values x(t).</param>
+        /// <returns>
+        /// An interpolation scheme optimized for the given sample points and values,
+        /// which can then be used to compute interpolations and extrapolations
+        /// on arbitrary points.
+        /// </returns>
+        /// <remarks>
+        /// if your data is already sorted in arrays, consider to use
+        /// MathNet.Numerics.Interpolation.CubicSpline.InterpolatePchipSorted
+        /// instead, which is more efficient.
+        /// </remarks>
+        public static IInterpolation CubicSplineMonotone(IEnumerable<double> points, IEnumerable<double> values)
+        {
+            return Interpolation.CubicSpline.InterpolatePchip(points, values);
+        }
+
         /// <summary>
         /// Create a piecewise cubic Hermite spline interpolation based on arbitrary points
         /// and their slopes/first derivative.

src/Numerics/Interpolation/CubicSpline.cs

@@ -244,7 +244,9 @@ namespace MathNet.Numerics.Interpolation
                 var mIs0 = m[i].AlmostEqual(0.0);
 
                 if (mIs0 || mPrevIs0 || Math.Sign(m[i]) != Math.Sign(m[i - 1]))
+                {
                     dd[i] = 0;
+                }
                 else
                 {
                     // Weighted harmonic mean of each slope.
@@ -272,10 +274,14 @@ namespace MathNet.Numerics.Interpolation
             var d = ((2 * h0 + h1) * m0 - h0 * m1) / (h0 + h1);
 
             if (Math.Sign(d) != Math.Sign(m0))
+            {
                 return 0.0;
+            }
 
             if (Math.Sign(m0) != Math.Sign(m1) && (Math.Abs(d) > 3 * Math.Abs(m0)))
+            {
                 return 3 * m0;
+            }
 
             return d;
         }