ostk.mathematics.curve_fitting.interpolator.CubicSpline

class CubicSpline(*args, **kwargs)

Bases: Interpolator

Overloaded function.

1. __init__(self: ostk.mathematics.curve_fitting.interpolator.CubicSpline, x: numpy.ndarray[numpy.float64[m, 1]], y: numpy.ndarray[numpy.float64[m, 1]]) -> None

   Create a cubic spline interpolator with data points.

   Args:

   x (numpy.array): The x-coordinates of data points. y (numpy.array): The y-coordinates of data points.

   Example:

   >>> x = numpy.array([0.0, 1.0, 2.0, 3.0])
   >>> y = numpy.array([0.0, 1.0, 4.0, 9.0])
   >>> interpolator = CubicSpline(x, y)
   

2. __init__(self: ostk.mathematics.curve_fitting.interpolator.CubicSpline, y: numpy.ndarray[numpy.float64[m, 1]], x_0: ostk.core.type.Real, h: ostk.core.type.Real) -> None

   Create a cubic spline interpolator with uniform spacing.

   Args:

   y (numpy.array): The y-coordinates of data points. x_0 (float): The starting x-coordinate. h (float): The uniform spacing between x-coordinates.

   Example:

   >>> y = numpy.array([0.0, 1.0, 4.0, 9.0])
   >>> interpolator = CubicSpline(y, 0.0, 1.0)  # x = [0, 1, 2, 3]
   

Methods

compute_derivative	Overloaded function.
evaluate	Overloaded function.
generate_interpolator	Generate an interpolator of specified type with data points.
get_interpolation_type	Get the interpolation type of this interpolator.

class Type(self: ostk.mathematics.curve_fitting.Interpolator.Type, value: int)

Bases: pybind11_object

Members:

BarycentricRational

CubicSpline

Linear

property name

compute_derivative(*args, **kwargs)

Overloaded function.

1. compute_derivative(self: ostk.mathematics.curve_fitting.interpolator.CubicSpline, x: float) -> float

   Compute the derivative of the cubic spline at a single point.

   Args:

   x (float): The x-coordinate to compute derivative at.

   Returns:

   float: The derivative value.

   Example:

   >>> interpolator = CubicSpline([0.0, 1.0, 2.0], [0.0, 1.0, 4.0])
   >>> derivative = interpolator.compute_derivative(0.5)
   

2. compute_derivative(self: ostk.mathematics.curve_fitting.interpolator.CubicSpline, x: numpy.ndarray[numpy.float64[m, 1]]) -> numpy.ndarray[numpy.float64[m, 1]]

   Compute the derivative of the cubic spline at multiple points.

   Args:

   x (numpy.array): The x-coordinates to compute derivatives at.

   Returns:

   (numpy.array): The derivative values.

   Example:

   >>> interpolator = CubicSpline([0.0, 1.0, 2.0], [0.0, 1.0, 4.0])
   >>> derivatives = interpolator.compute_derivative([0.2, 0.8])
   

evaluate(*args, **kwargs)

Overloaded function.

1. evaluate(self: ostk.mathematics.curve_fitting.interpolator.CubicSpline, x: numpy.ndarray[numpy.float64[m, 1]]) -> numpy.ndarray[numpy.float64[m, 1]]

   Evaluate the cubic spline interpolation at multiple points.

   Args:

   x (numpy.array): The x-coordinates to evaluate at.

   Returns:

   (numpy.array): The interpolated y-values.

   Example:

   >>> interpolator = CubicSpline([0.0, 1.0, 2.0], [0.0, 1.0, 4.0])
   >>> result = interpolator.evaluate([0.5, 1.5])
   

2. evaluate(self: ostk.mathematics.curve_fitting.interpolator.CubicSpline, x: float) -> float

   Evaluate the cubic spline interpolation at a single point.

   Args:

   x (float): The x-coordinate to evaluate at.

   Returns:

   float: The interpolated y-value.

   Example:

   >>> interpolator = CubicSpline([0.0, 1.0, 2.0], [0.0, 1.0, 4.0])
   >>> result = interpolator.evaluate(0.5)
   

static generate_interpolator(

interpolation_type: ostk.mathematics.curve_fitting.Interpolator.Type,

x: numpy.ndarray[numpy.float64[m, 1]],

y: numpy.ndarray[numpy.float64[m, 1]],

) → ostk.mathematics.curve_fitting.Interpolator

Generate an interpolator of specified type with data points.

Parameters:

• interpolation_type (Interpolator.Type) -- The type of interpolation.

• x (numpy.array) -- The x-coordinates of data points.

• y (numpy.array) -- The y-coordinates of data points.

Returns:

The created interpolator.

Return type:

Interpolator

Example

>>> x = numpy.array([0.0, 1.0, 2.0])
>>> y = numpy.array([0.0, 2.0, 4.0])
>>> interpolator = Interpolator.generate_interpolator(
...     Interpolator.Type.CubicSpline, x, y
... )

get_interpolation_type(

self: ostk.mathematics.curve_fitting.Interpolator,

) → ostk.mathematics.curve_fitting.Interpolator.Type

Get the interpolation type of this interpolator.

Returns:

The interpolation type.

Return type:

Interpolator.Type

Example

>>> interpolator = Interpolator(Interpolator.Type.CubicSpline)
>>> type = interpolator.get_interpolation_type()