interp1

interp1#

Piecewise interpolation with various methods (linear, nearest, next, previous, spline).

template<typename OpX, typename OpV, typename OpXQ>
auto matx::interp1(const OpX &x, const OpV &v, const OpXQ &xq, InterpMethod method = InterpMethod::LINEAR)#

Interpolation operator with specified method

Template Parameters:

  • OpX – Type of sample points vector

  • OpV – Type of sample values vector

  • OpXQ – Type of query points

Parameters:

  • x – Sample points (must be sorted in ascending order)

  • v – Sample values (must be the same size as x)

  • xq – Query points where to interpolate

  • method – Interpolation method (LINEAR, NEAREST, NEXT, PREV, SPLINE)

Returns:

Operator that interpolates values at query points

Interpolation Methods#

enum class matx::InterpMethod#

Interpolation method enumeration.

Specifies the algorithm to use when performing interpolation between sample points.

Values:

enumerator LINEAR#

Linear interpolation between adjacent points.

enumerator NEAREST#

Uses the value at the nearest sample point.

enumerator NEXT#

Uses the value at the next sample point.

enumerator PREV#

Uses the value at the previous sample point.

enumerator SPLINE#

Cubic spline interpolation, using not-a-knot boundary conditions.

Examples#

Linear Interpolation (default):

auto x = make_tensor<TestType>({5});
x.SetVals({0.0, 1.0, 3.0, 3.5, 4.0});

auto v = make_tensor<TestType>({5});
v.SetVals({0.0, 2.0, 1.0, 3.0, 4.0});

auto xq = make_tensor<TestType>({6});
xq.SetVals({-1.0, 0.0, 0.25, 1.0, 1.5, 5.0});

auto out_linear = make_tensor<TestType>({xq.Size(0)});
(out_linear = interp1(x, v, xq, InterpMethod::LINEAR)).run(exec);

Nearest Neighbor Interpolation:

auto out_nearest = make_tensor<TestType>({xq.Size(0)});
(out_nearest = interp1(x, v, xq, InterpMethod::NEAREST)).run(exec);