Developer Reference

  • 2020.2
  • 07/15/2020
  • Public Content
Contents

Data Fitting Usage Model

Consider an algorithm that uses the Data Fitting functions. Typically, such algorithms consist of four steps or stages:
  1. Create a task. You can call the Data Fitting function several times to create multiple tasks.
    status = dfdnewtask1d( task, nx, x, xhint, ny, y, yhint );
  2. Modify the task parameters.
    status = dfdeditppspline1d( task, s_order, c_type, bc_type, bc, ic_type, ic, scoeff, scoeffhint );
  3. Perform Data Fitting spline-based computations. You may reiterate steps 2-3 as needed.
    status = dfdinterpolate1d(task, estimate, method, nsite, site, sitehint, ndorder, dorder, datahint, r, rhint, cell );
  4. Destroy the task or tasks.
    status = dfdeletetask( task );

Product and Performance Information

1

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804