scijit.interpolateΒΆ
scipy.interpolate equivalents callable from inside numba.@njit code, backed
by the same Dierckx FITPACK Fortran that SciPy wraps. Each name below links to a
page generated from its docstring: parameters, returns, a runnable @njit
example, and, where it applies, the ways it differs from scipy.
Compute the B-spline representation of a 1-D curve. |
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Compute the B-spline representation of an N-D parametric curve. |
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Evaluate a spline or one of its derivatives. |
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Evaluate the nu-th derivative of a spline. |
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Evaluate the definite integral of a spline. |
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Find the roots of a cubic spline. |
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Evaluate all derivatives of a spline at one point. |
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Evaluate a bivariate spline on a grid. |
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Evaluate a bivariate spline on a grid, FITPACK |
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Evaluate a bivariate spline at scattered points, FITPACK |
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Spline representation of the n-th derivative of a spline. |
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Spline representation of the n-th antiderivative of a spline. |
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Build a univariate smoothing spline. |
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Build an interpolating spline through every data point. |
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Build a least-squares spline on given interior knots. |
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Build a bivariate spline over gridded data. |
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Build a bivariate smoothing spline over scattered data. |
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Build a spline on a spherical grid. |
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Build a smoothing spline on a sphere. |
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Build an _RGI for interpolation on a regular grid. |
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Interpolate on a regular grid. |
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C2 cubic spline interpolator over piecewise-cubic segments. |
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Monotone piecewise-cubic Hermite interpolator (Fritsch-Carlson slopes). |
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Build an _Interp1D for one-dimensional interpolation. |
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Univariate spline in the B-spline basis. |
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Interpolating B-spline through |
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Akima piecewise-cubic interpolator. |