Interpolation (scipy.interpolate
)#
Sub-package for objects used in interpolation.
As listed below, this sub-package contains spline functions and classes, 1-D and multidimensional (univariate and multivariate) interpolation classes, Lagrange and Taylor polynomial interpolators, and wrappers for FITPACK and DFITPACK functions.
Univariate interpolation#
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Interpolate a 1-D function. |
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Interpolating polynomial for a set of points. |
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Interpolating polynomial for a set of points. |
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Convenience function for polynomial interpolation. |
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Convenience function for polynomial interpolation. |
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Convenience function for pchip interpolation. |
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Piecewise-cubic interpolator matching values and first derivatives. |
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PCHIP 1-D monotonic cubic interpolation. |
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Akima interpolator |
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Cubic spline data interpolator. |
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Piecewise polynomial in terms of coefficients and breakpoints |
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Piecewise polynomial in terms of coefficients and breakpoints. |
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Floater-Hormann barycentric rational interpolation. |
Multivariate interpolation#
Unstructured data:
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Interpolate unstructured D-D data. |
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Piecewise linear interpolator in N > 1 dimensions. |
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NearestNDInterpolator(x, y). |
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CloughTocher2DInterpolator(points, values, tol=1e-6). |
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Radial basis function (RBF) interpolation in N dimensions. |
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A class for radial basis function interpolation of functions from N-D scattered data to an M-D domain. |
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For data on a grid:
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Multidimensional interpolation on regular or rectilinear grids. |
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Interpolator on a regular or rectilinear grid in arbitrary dimensions. |
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Bivariate spline approximation over a rectangular mesh. |
See also
Tensor product polynomials:
1-D Splines#
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Univariate spline in the B-spline basis. |
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Compute the (coefficients of) interpolating B-spline. |
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Compute the (coefficients of) an LSQ (Least SQuared) based fitting B-spline. |
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Compute the (coefficients of) smoothing cubic spline function using |
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Replicate FITPACK's constructing the knot vector. |
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Find the B-spline representation of a 1D function. |
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Find a smoothed B-spline representation of a parametric N-D curve. |
Functional interface to FITPACK routines:
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Find the B-spline representation of a 1-D curve. |
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Find the B-spline representation of an N-D curve. |
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Evaluate a B-spline or its derivatives. |
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Evaluate the definite integral of a B-spline between two given points. |
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Find the roots of a cubic B-spline. |
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Evaluate a B-spline and all its derivatives at one point (or set of points) up to order k (the degree of the spline), being 0 the spline itself. |
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Compute the spline representation of the derivative of a given spline |
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Compute the spline for the antiderivative (integral) of a given spline. |
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Insert knots into a B-spline. |
Object-oriented FITPACK interface:
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1-D smoothing spline fit to a given set of data points. |
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1-D interpolating spline for a given set of data points. |
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1-D spline with explicit internal knots. |
2-D Splines#
For data on a grid:
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Bivariate spline approximation over a rectangular mesh. |
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Bivariate spline approximation over a rectangular mesh on a sphere. |
For unstructured data:
Base class for bivariate splines. |
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Smooth bivariate spline approximation. |
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Smooth bivariate spline approximation in spherical coordinates. |
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Weighted least-squares bivariate spline approximation. |
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Weighted least-squares bivariate spline approximation in spherical coordinates. |
Low-level interface to FITPACK functions:
Rational Approximation#
Additional tools#
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Return a Lagrange interpolating polynomial. |
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Estimate the Taylor polynomial of f at x by polynomial fitting. |
See also
scipy.ndimage.map_coordinates
,
scipy.ndimage.spline_filter
,
scipy.signal.resample
,
scipy.signal.bspline,
scipy.signal.gauss_spline
,
scipy.signal.qspline1d
,
scipy.signal.cspline1d
,
scipy.signal.qspline1d_eval
,
scipy.signal.cspline1d_eval
,
scipy.signal.qspline2d
,
scipy.signal.cspline2d
.
pchip
is an alias of PchipInterpolator
for backward compatibility
(should not be used in new code).