Interpolation

Class to find intermediate values from those given in a table.

class pymeeus.Interpolation.Interpolation(*args)

Class Interpolation deals with finding intermediate values to those given in a table.

Besides the basic interpolation, this class also provides methods to find the extrema (maximum or minimum value) in a given interval (if present), and it also has methods to find roots (the values of the argument ‘x’ for which the function ‘y’ becomes zero).

Please note that it seems that Meeus uses the Bessel interpolation method (Chapter 3). However, this class uses the Newton interpolation method because it is (arguably) more flexible regarding the number of entries provided in the interpolation table.

The constructor takes pairs of (x, y) values from the table of interest. These pairs of values can be given as a sequence of int/floats, tuples, lists or Angles. It is also possible to provide an Interpolation object to the constructor in order to get a copy.

Note

When using Angles, be careful with the 360-to-0 discontinuity.

If a sequence of int, floats or Angles is given, the values in the odd positions are considered to belong to the ‘x’ set, while the values in the even positions belong to the ‘y’ set. If only one tuple or list is provided, it is assumed that it is the ‘y’ set, and the ‘x’ set is build from 0 onwards with steps of length 1.

Please keep in mind that a minimum of two data pairs are needed in order to carry out any interpolation. If only one value pair is provided, a ValueError exception will be raised.

__call__(x)

Method to interpolate the function at a given ‘x’.

Parameters:x (int, float, Angle) – Point where the interpolation will be carried out. Returns:Resulting value of the interpolation. Return type:float Raises:ValueError if input value is outside of interpolation range. Raises:TypeError if input value is of wrong type.

>>> i = Interpolation([7, 8, 9], [0.884226, 0.877366, 0.870531])
>>> y = round(i(8.18125), 6)
>>> print(y)
0.876125

__init__(*args)

Interpolation constructor.

This takes pairs of (x, y) values from the table of interest. These pairs of values can be given as a sequence of int/floats, tuples, lists or Angles. It is also possible to provide an Interpolation object to the constructor in order to get a copy.

Note

When using Angles, be careful with the 360-to-0 discontinuity

If a sequence of int, floats or Angles is given, the values in the odd positions are considered to belong to the ‘x’ set, while the values in the even positions belong to the ‘y’ set. If only one tuple or list is provided, it is assumed that it is the ‘y’ set, and the ‘x’ set is build from 0 onwards with steps of length 1.

Please keep in mind that a minimum of two data pairs are needed in order to carry out any interpolation. If only one value pair is provided, a ValueError exception will be raised.

Parameters:args (int, float, list, tuple, Angle, Interpolation) – Input tabular values, or another Interpolation object. Returns:Interpolation object. Return type:Interpolation Raises:ValueError if not enough input data pairs are provided. Raises:TypeError if input values are of wrong type.

>>> i = Interpolation([5, 3, 6, 1, 2, 4, 9], [10, 6, 12, 2, 4, 8])
>>> print(i._x)
[1, 2, 3, 4, 5, 6]
>>> print(i._y)
[2, 4, 6, 8, 10, 12]
>>> j = Interpolation([3, -8, 1, 12, 2, 5, 8])
>>> print(j._x)
[0, 1, 2, 3, 4, 5, 6]
>>> print(j._y)
[3, -8, 1, 12, 2, 5, 8]
>>> k = Interpolation(3, -8, 1, 12, 2, 5, 8)
>>> print(k._x)
[1, 2, 3]
>>> print(k._y)
[12, 5, -8]

__len__()

This method returns the number of interpolation points (x, y, pairs) stored in this Interpolation object.

Returns:Number of interpolation points internally stored Return type:int

>>> i = Interpolation([5, 3, 6, 1, 2, 4, 9], [10, 6, 12, 2, 4, 8])
>>> len(i)
6

__repr__()

Method providing the ‘official’ string representation of the object. It provides a valid expression that could be used to recreate the object.

Returns:As string with a valid expression to recreate the object Return type:string

>>> i = Interpolation([5, 3, 6, 1, 2, 4, 9], [10, 6, 12, 2, 4, 8])
>>> repr(i)
'Interpolation([1, 2, 3, 4, 5, 6], [2, 4, 6, 8, 10, 12])'

__str__()

Method used when trying to print the object.

Returns:Internal tabular values as strings. Return type:string

>>> i = Interpolation([5, 3, 6, 1, 2, 4, 9], [10, 6, 12, 2, 4, 8])
>>> print(i)
X: [1, 2, 3, 4, 5, 6]
Y: [2, 4, 6, 8, 10, 12]

__weakref__

list of weak references to the object (if defined)

derivative(x)

Method to compute the derivative from interpolation polynomial.

Parameters:x (int, float, Angle) – Point where the interpolation derivative will be carried out. Returns:Resulting value of the interpolation derivative. Return type:float Raises:ValueError if input value is outside of interpolation range. Raises:TypeError if input value is of wrong type.

>>> m = Interpolation([-1.0, 0.0, 1.0], [-2.0, 3.0, 2.0])
>>> m.derivative(-1.0)
8.0
>>> m.derivative(0.5)
-1.0

get_tolerance()

Gets the internal tolerance value used for comparisons.

Note

The default tolerance value is TOL.

Returns:Internal tolerance. Return type:float

minmax(xl=0, xh=0, max_iter=1000)

Method to find the minimum or maximum inside the [xl, xh] range.

Finding the minimum or maximum (extremum) of a function within a given interval is akin to find the root of its derivative. Therefore, this method creates an interpolation object for the derivative function, and calls the root method of that object. See root() method for more details.

If values xl, xh are not given, the limits of the interpolation table values will be used.

Note

This method returns a ValueError exception if the corresponding derivatives yl’ = f’(xl) and yh’ = f’(xh) values have the same sign. In that case, the method assumes there is no extremum in the [xl, xh] interval.

Note

If any of the xl, xh values is beyond the limits given by the interpolation values, its value will be set to the corresponding limit.

Note

If xl == xh (and not zero), a ValueError exception is raised.

Note

If the method doesn’t converge within max_iter ierations, then a ValueError exception is raised.

Parameters:

• xl (int, float, Angle) – Lower limit of interval where a extremum will be looked for.
• xh (int, float, Angle) – Higher limit of interval where extremum will be looked for.
• max_iter (int) – Maximum number of iterations allowed.

Returns:

Extremum of interpolated function within [xl, xh] interval.

Return type:

int, float, Angle

Raises:

ValueError if yl = f(xl), yh = f(xh) have same sign.

Raises:

ValueError if xl == xh.

Raises:

ValueError if maximum number of iterations is exceeded.

Raises:

TypeError if input value is of wrong type.

>>> m = Interpolation([-1.0, 0.0, 1.0], [-2.0, 3.0, 2.0])
>>> round(m.minmax(), 8)
0.33333333

root(xl=0, xh=0, max_iter=1000)

Method to find the root inside the [xl, xh] range.

This method applies, in principle, the Newton method to find the root; however, if conditions are such that Newton method may not bei properly behaving or converging, then it switches to the linear Interpolation method.

If values xl, xh are not given, the limits of the interpolation table values will be used.

Note

This method returns a ValueError exception if the corresponding yl = f(xl) and yh = f(xh) values have the same sign. In that case, the method assumes there is no root in the [xl, xh] interval.

Note

If any of the xl, xh values is beyond the limits given by the interpolation values, its value will be set to the corresponding limit.

Note

If xl == xh (and not zero), a ValueError exception is raised.

Note

If the method doesn’t converge within max_iter ierations, then a ValueError exception is raised.

Parameters:

• xl (int, float, Angle) – Lower limit of interval where the root will be looked for.
• xh (int, float, Angle) – Higher limit of interval where the root will be looked for.
• max_iter (int) – Maximum number of iterations allowed.

Returns:

Root of the interpolated function within [xl, xh] interval.

Return type:

int, float, Angle

Raises:

ValueError if yl = f(xl), yh = f(xh) have same sign.

Raises:

ValueError if xl == xh.

Raises:

ValueError if maximum number of iterations is exceeded.

Raises:

TypeError if input value is of wrong type.

>>> m = Interpolation([-1.0, 0.0, 1.0], [-2.0, 3.0, 2.0])
>>> round(m.root(), 8)
-0.72075922

set(*args)

Method used to define the value pairs of Interpolation object.

This takes pairs of (x, y) values from the table of interest. These pairs of values can be given as a sequence of int/floats, tuples, lists, or Angles. It is also possible to provide an Interpolation object to this method in order to get a copy.

Note

When using Angles, be careful with the 360-to-0 discontinuity

If a sequence of int, floats or Angles is given, the values in the odd positions are considered to belong to the ‘x’ set, while the values in the even positions belong to the ‘y’ set. If only one tuple or list is provided, it is assumed that it is the ‘y’ set, and the ‘x’ set is build from 0 onwards with steps of length 1.

Please keep in mind that a minimum of two data pairs are needed in order to carry out any interpolation. If only one value pair is provided, a ValueError exception will be raised.

Parameters:args (int, float, list, tuple, Angle) – Input tabular values, or another Interpolation object. Returns:None. Return type:None Raises:ValueError if not enough input data pairs are provided. Raises:TypeError if input values are of wrong type.

>>> i = Interpolation()
>>> i.set([5, 3, 6, 1, 2, 4, 9], [10, 6, 12, 2, 4, 8])
>>> print(i._x)
[1, 2, 3, 4, 5, 6]
>>> print(i._y)
[2, 4, 6, 8, 10, 12]
>>> j = Interpolation()
>>> j.set([3, -8, 1, 12, 2, 5, 8])
>>> print(j._x)
[0, 1, 2, 3, 4, 5, 6]
>>> print(j._y)
[3, -8, 1, 12, 2, 5, 8]
>>> k = Interpolation(3, -8, 1, 12, 2, 5, 8)
>>> print(k._x)
[1, 2, 3]
>>> print(k._y)
[12, 5, -8]
>>> m = Interpolation(k)
>>> print(m._x)
[1, 2, 3]
>>> print(m._y)
[12, 5, -8]

set_tolerance(tol)

Changes the internal tolerance value used for comparisons.

Parameters:tol (int, float) – New tolerance value. Returns:None Return type:None