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# scipy.interpolate.PchipInterpolator

class `scipy.interpolate.``PchipInterpolator`(x, y, axis=0)

  PCHIP 1-d monotonic cubic interpolation

  x and y are arrays of values used to approximate some function f, with `y = f(x)`. The interpolant uses monotonic cubic splines to find the value of new points.

  Parameters : | x : ndarray A 1-D array of monotonically increasing real values. x cannot include duplicate values (otherwise f is overspecified) y : ndarray A 1-D array of real values. y‘s length along the interpolation axis must be equal to the length of x. axis : int, optional Axis in the yi array corresponding to the x-coordinate values.

  Notes

  Assumes x is sorted in monotonic order (e.g. `x[1] > x[0]`).

  Methods

  `__call__`(x) | Evaluate the interpolant
  `append`(xi, yi[, order]) | Append a single point with derivatives to the PiecewisePolynomial
  `derivative`(x[, der]) | Evaluate one derivative of the polynomial at the point x
  `derivatives`(x[, der]) | Evaluate many derivatives of the polynomial at the point x
  `extend`(xi, yi[, orders]) | Extend the PiecewisePolynomial by a list of points

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