curve_handling#

Example Usage#

Full Contents:#

curve_handling.collapseCurves(curv, refcurv, tquery)#

[curv1, curv2, transf] = collapseCurves(curv1, curv2) Optimize for translation of a curve against curv2

Parameters

  • curv (Mx2 numeric) – Curve to be shifted as closely as possible to refcurv

  • refcurv (Nx2 numeric) – curve against which the first curv is collapsed

  • tquery (Q x 1 numeric) – timepoints in fixed (reference) parameterization (t) at which the interpolated, shifted curve is to be evaluated against the reference curve.

Returns

  • curv_transf

  • transf

  • ssr

curve_handling.compareCurves(vars, curv1, curv2, tquery)#

Given two curves, interpolate the first in reference to the second and find the sum squared differences betweeen the two curves as a function of a time offset. This can be used to minimize difference between two time offset curves. The second curve should have a shorter domain so that the first curve’s interpolation covers the seconds’ range.

Parameters

  • vars (a vector containing the variables to be minimized) –

    vars1float

    time to shift curv1 relative to curv2’s t axis to match the two curves

    vars2float

    time dilation factor

  • curv1 (N x 1 float array) – first column is independent variable t, second is a value f(t)

  • curv1 – first column is independent variable t, second is a value f(t)

  • tquery (M x 1 float array) – independent variable values at which to interpolate

Returns

  • ssdiff (float) – the sum of the squared differences between curv1(t2) and curv2(t2), where t2 are the timestamps given in curv2

  • Example usage

  • ————-

NPMitchell 2020

Indices and tables#