News and announcements

Spline Library 2.3 Release

Written for SplineLibrary by Lakshmi Krishnamurthy on 2014-01-23

SplineLibrary provides the functionality for building, calibrating, and evaluating different kinds of splines.

SplineLibrary implements the functionality behind spline design, spline constructions, customization, calibration, and evaluation of a wide variety of spline types and basis functions.

SplineLibrary achieves its design goal by implementing its functionality over several packages the perform the following:

Spline Calibration Framework: Schematic spline segment/span partitioning, elastic/inelastic entity-variate separation, mathematical calibration formulation framework with constraints/boundary incorporation, sensitivity Jacobian estimator setup, Hard/Soft (Truthness/Smoothness) partitioning.
Shape Preserving Spline Suite: B-splines, Polynomial Splines and Variants (Bernstein, Kaklis-Pandelis, Manni), Integrated Tension Splines (exponential/hyperbolic), partitioned tension splines (explicit shape control using rational splines).
Space Spline Curves: Hermitian, Catmull-Rom, Cardinal Cubic, Space Loops.
B Splines: Polynomial Koch/Loche/Kvasov Tension B Splines Monic/Multic Sequence Generation and Setup.
Spline Calibration: Explicit segment formulation frame work, Optimizing shape preserving splines, curvature/segment-length (or criterion-defined) penalty minimizing mu-splines, segment/span self-Jacobian, quote-Jacobian, and micro-Jacobian.
Spline Smoothing Schemes: Akima, Bessel, Harmonic, Hyman83, Hyman89, Kruger, Preuss, Hagan-West, and Preuss schemes.
Regression Splines: Curveture/Length Penalizing and Best-Fit Splines.
Spline Evaluation: Metric'ed evaluation of monotonicity, convexity, smoothness, locality, and approximation order.
Spline Extensions: Variational Smoothing, density smoothing technique, alternate smoothener customization extension, multi-dimensional (including thin plate) splines.
Documentation: Literature review, framework description, mathematical and formulation details of the different components, spline library synthetic knowledge unit (SKU) composition, and module and API usage guide.
Regression Tests: Statistical regression analysis and dispersion metric evaluation for the initialization and the iteration components of the different basis spline construction, usage, and span interpolation methodologies.

Spline Library 2.2 Release

Written for SplineLibrary by Lakshmi Krishnamurthy on 2013-08-18

SplineLibrary provides the functionality for building, calibrating, and evaluating different kinds of splines.

SplineLibrary implements the functionality behind spline design, spline constructions, customization, calibration, and evaluation of a wide variety of spline types and basis functions.

SplineLibrary achieves its design goal by implementing its functionality over several packages the perform the following:
· Spline Calibration Framework: Schematic spline segment/span partitioning, elastc/inelastic entity-variate separation, mathematical calibration formulation framework with constriaints/boundary incorporation, sensitivity Jacobian estimator setup, Hard/Soft (Truthness/Smoothness) partitioning.
· Shape Preserving Spline Suite: B-splines, Polynomial Splines and Variants (Bernstein, Kaklis-Pandelis, Manni), Integrated Tension Splines (exponential/hyperbolic), partitioned tension splines (explicit shape control using rational splines)
· Space Spline Curves: Hermitian, Catmull-Rom, Cardinal Cubic, Space Loops
· Spline Calibration: Explicit segment formulation frane work, Optimizing shape preserving splnes, curvature (or criterion-defined) penalty minimizing mu-splines, segment/span self-Jacobian and micro-Jacobian
· Spline Evaluation: Metric'ed evaluation of monotonicity, convexity, smoothness, smoothness, locality, and approximation order.
· Spline Extensions: Variational Smoothing, density smoothing technique, alternate smoothener customization extension, multi-dimensional (including thin plate) splines.

The user Guide, the API Javadoc, and the samples are also available here.

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