Akima Interpolation

## Project description

Akima is a Python library that implements Akima’s interpolation method described in:

A new method of interpolation and smooth curve fitting based on local procedures. Hiroshi Akima, J. ACM, October 1970, 17(4), 589-602.

A continuously differentiable sub-spline is built from piecewise cubic polynomials. It passes through the given data points and will appear smooth and natural.

This module is no longer being actively developed. Consider using scipy.interpolate.Akima1DInterpolator instead.

Author:

Christoph Gohlke

BSD 3-Clause

Version:

2022.9.12

## Requirements

This release has been tested with the following requirements and dependencies (other versions may work):

## Revisions

2022.9.12

• Remove support for Python 3.7 (NEP 29).

## Examples

>>> from matplotlib import pyplot
>>> from scipy.interpolate import Akima1DInterpolator
>>> def example():
...     '''Plot interpolated Gaussian noise.'''
...     x = numpy.sort(numpy.random.random(10) * 100)
...     y = numpy.random.normal(0.0, 0.1, size=len(x))
...     x2 = numpy.arange(x[0], x[-1], 0.05)
...     y2 = interpolate(x, y, x2)
...     y3 = Akima1DInterpolator(x, y)(x2)
...     pyplot.title('Akima interpolation of Gaussian noise')
...     pyplot.plot(x2, y2, 'r-', label='akima')
...     pyplot.plot(x2, y3, 'b:', label='scipy', linewidth=2.5)
...     pyplot.plot(x, y, 'go', label='data')
...     pyplot.legend()
...     pyplot.show()
>>> example()


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