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.