Data Fitting Computational Routines

Data Fitting computational routines are functions used to perform spline-based computations, such as:

  • spline construction

  • computation of values, derivatives, and integrals of the predefined order

  • cell search

Once you create a Data Fitting task and initialize the required parameters, you can call computational routines as many times as necessary.

The table below lists the available computational routines:

Data Fitting Computational Routines

Routine

Description

df?construct1d

Constructs a spline for a one-dimensional Data Fitting task.

df?interpolate1d

Computes spline values and derivatives.

df?interpolateex1d

Computes spline values and derivatives by calling user-provided interpolants.

df?integrate1d

Computes spline-based integrals.

df?integrateex1d

Computes spline-based integrals by calling user-provided integrators.

df?searchcells1d

Finds indices of cells containing interpolation sites.

df?searchcellsex1d

Finds indices of cells containing interpolation sites by calling user-provided cell searchers.

If a Data Fitting computation completes successfully, the computational routines return the DF_STATUS_OK code. If an error occurs, the routines return an error code specifying the origin of the failure. Some possible errors are the following:

  • The task pointer is NULL.
  • Memory allocation failed.
  • The computation failed for another reason.

For the list of available status codes, see "Task Status and Error Reporting".

Note

Data Fitting computational routines do not control errors for floating-point conditions, such as overflow, gradual underflow, or operations with Not a Number (NaN) values.

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