Fit piecewise cubic polynomials, given vectors x and y. The interpolation method by Akima uses a continuously differentiable sub-spline built from piecewise cubic polynomials. The resultant curve passes through the given data points and will appear smooth and natural.
Use only for precise data, as the fitted curve passes through the given points exactly. This routine is useful for plotting a pleasingly smooth curve through a few given points for purposes of plotting.
1-D array of monotonically increasing real values.
N-D array of real values. The length of y
along the first axis must be equal to the length of x
.
Specifies the axis of y
along which to interpolate. Interpolation defaults to the first axis of y
.
Akima interpolator
CubicSpline
Cubic spline data interpolator.
PPoly
Piecewise polynomial in terms of coefficients and breakpoints
PchipInterpolator
PCHIP 1-D monotonic cubic interpolator.
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.interpolate._cubic.PchipInterpolator
scipy.interpolate._cubic.CubicSpline
scipy.interpolate._cubic.CubicHermiteSpline
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