738 lines
27 KiB
Python
738 lines
27 KiB
Python
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# -*- coding: utf-8 -*-
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# PyMeeus: Python module implementing astronomical algorithms.
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# Copyright (C) 2018 Dagoberto Salazar
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU Lesser General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU Lesser General Public License for more details.
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#
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# You should have received a copy of the GNU Lesser General Public License
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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from math import sqrt, degrees
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from pymeeus.base import TOL
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from pymeeus.Angle import Angle
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"""
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.. module:: Interpolation
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:synopsis: Basic interpolation routines
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:license: GNU Lesser General Public License v3 (LGPLv3)
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.. moduleauthor:: Dagoberto Salazar
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"""
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class Interpolation(object):
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"""
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Class Interpolation deals with finding intermediate values to those given
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in a table.
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Besides the basic interpolation, this class also provides methods to find
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the extrema (maximum or minimum value) in a given interval (if present),
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and it also has methods to find roots (the values of the argument 'x' for
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which the function 'y' becomes zero).
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Please note that it seems that Meeus uses the Bessel interpolation method
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(Chapter 3). However, this class uses the Newton interpolation method
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because it is (arguably) more flexible regarding the number of entries
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provided in the interpolation table.
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The constructor takes pairs of (x, y) values from the table of interest.
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These pairs of values can be given as a sequence of int/floats, tuples,
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lists or Angles. It is also possible to provide an Interpolation object to
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the constructor in order to get a copy.
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.. note:: When using Angles, be careful with the 360-to-0 discontinuity.
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If a sequence of int, floats or Angles is given, the values in the odd
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positions are considered to belong to the 'x' set, while the values in the
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even positions belong to the 'y' set. If only one tuple or list is
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provided, it is assumed that it is the 'y' set, and the 'x' set is build
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from 0 onwards with steps of length 1.
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Please keep in mind that a minimum of two data pairs are needed in order to
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carry out any interpolation. If only one value pair is provided, a
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ValueError exception will be raised.
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"""
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def __init__(self, *args):
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"""Interpolation constructor.
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This takes pairs of (x, y) values from the table of interest. These
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pairs of values can be given as a sequence of int/floats, tuples, lists
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or Angles. It is also possible to provide an Interpolation object to
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the constructor in order to get a copy.
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.. note:: When using Angles, be careful with the 360-to-0 discontinuity
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If a sequence of int, floats or Angles is given, the values in the odd
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positions are considered to belong to the 'x' set, while the values in
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the even positions belong to the 'y' set. If only one tuple or list is
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provided, it is assumed that it is the 'y' set, and the 'x' set is
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build from 0 onwards with steps of length 1.
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Please keep in mind that a minimum of two data pairs are needed in
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order to carry out any interpolation. If only one value pair is
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provided, a ValueError exception will be raised.
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:param args: Input tabular values, or another Interpolation object.
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:type args: int, float, list, tuple, :py:class:`Angle`,
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:py:class:`Interpolation`
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:returns: Interpolation object.
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:rtype: :py:class:`Interpolation`
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:raises: ValueError if not enough input data pairs are provided.
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:raises: TypeError if input values are of wrong type.
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>>> i = Interpolation([5, 3, 6, 1, 2, 4, 9], [10, 6, 12, 2, 4, 8])
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>>> print(i._x)
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[1, 2, 3, 4, 5, 6]
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>>> print(i._y)
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[2, 4, 6, 8, 10, 12]
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>>> j = Interpolation([3, -8, 1, 12, 2, 5, 8])
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>>> print(j._x)
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[0, 1, 2, 3, 4, 5, 6]
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>>> print(j._y)
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[3, -8, 1, 12, 2, 5, 8]
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>>> k = Interpolation(3, -8, 1, 12, 2, 5, 8)
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>>> print(k._x)
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[1, 2, 3]
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>>> print(k._y)
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[12, 5, -8]
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"""
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self._x = []
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self._y = []
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self._table = []
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self._tol = TOL
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self.set(*args) # Let's use 'set()' method to handle the setup
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def _order_points(self):
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"""Method to put the data points in ascending order w.r.t. 'x'."""
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# Let's work with copies of the original lists
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x = list(self._x)
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y = list(self._y)
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xnew = []
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ynew = []
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xmax = max(x) + 1.0
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for _ in range(len(x)):
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# Get the index of the minimum value
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imin = x.index(min(x))
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# Append the current minimum value to the new 'x' list
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xnew.append(x[imin])
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# Store the *position* of the current minimum value to new 'y' list
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ynew.append(imin)
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# The current minimum value will no longer be the minimum
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x[imin] = xmax
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# In the new 'y' list, substitute the positions by the real values
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for i in range(len(x)):
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ynew[i] = y[ynew[i]]
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# Store the results in the corresponding fields
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self._x = xnew
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self._y = ynew
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def set(self, *args):
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"""Method used to define the value pairs of Interpolation object.
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This takes pairs of (x, y) values from the table of interest. These
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pairs of values can be given as a sequence of int/floats, tuples,
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lists, or Angles. It is also possible to provide an Interpolation
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object to this method in order to get a copy.
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.. note:: When using Angles, be careful with the 360-to-0 discontinuity
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If a sequence of int, floats or Angles is given, the values in the odd
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positions are considered to belong to the 'x' set, while the values in
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the even positions belong to the 'y' set. If only one tuple or list is
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provided, it is assumed that it is the 'y' set, and the 'x' set is
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build from 0 onwards with steps of length 1.
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Please keep in mind that a minimum of two data pairs are needed in
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order to carry out any interpolation. If only one value pair is
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provided, a ValueError exception will be raised.
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:param args: Input tabular values, or another Interpolation object.
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:type args: int, float, list, tuple, :py:class:`Angle`
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:returns: None.
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:rtype: None
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:raises: ValueError if not enough input data pairs are provided.
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:raises: TypeError if input values are of wrong type.
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>>> i = Interpolation()
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>>> i.set([5, 3, 6, 1, 2, 4, 9], [10, 6, 12, 2, 4, 8])
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>>> print(i._x)
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[1, 2, 3, 4, 5, 6]
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>>> print(i._y)
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[2, 4, 6, 8, 10, 12]
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>>> j = Interpolation()
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>>> j.set([3, -8, 1, 12, 2, 5, 8])
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>>> print(j._x)
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[0, 1, 2, 3, 4, 5, 6]
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>>> print(j._y)
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[3, -8, 1, 12, 2, 5, 8]
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>>> k = Interpolation(3, -8, 1, 12, 2, 5, 8)
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>>> print(k._x)
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[1, 2, 3]
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>>> print(k._y)
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[12, 5, -8]
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>>> m = Interpolation(k)
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>>> print(m._x)
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[1, 2, 3]
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>>> print(m._y)
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[12, 5, -8]
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"""
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# Clean up the internal data tables
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self._x = []
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self._y = []
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self._table = []
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# If no arguments are given, return. Internal data tables are empty
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if len(args) == 0:
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return
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# If we have only one argument, it can be a single value or tuple/list
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elif len(args) == 1:
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if isinstance(args[0], Interpolation): # Copy constructor
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self._x = args[0]._x
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self._y = args[0]._y
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self._table = args[0]._table
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self._tol = args[0]._tol
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return
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elif isinstance(args[0], (int, float, Angle)):
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# Insuficient data to interpolate. Raise ValueError exception
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raise ValueError("Invalid number of input values")
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elif isinstance(args[0], (list, tuple)):
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seq = args[0]
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if len(seq) < 2:
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raise ValueError("Invalid number of input values")
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else:
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# Read input values into 'y', and create 'x'
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i = 0
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for value in seq:
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self._x.append(i)
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self._y.append(value)
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i += 1
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else:
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raise TypeError("Invalid input value")
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elif len(args) == 2:
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if isinstance(args[0], (int, float, Angle)) or isinstance(
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args[1], (int, float, Angle)
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):
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# Insuficient data to interpolate. Raise ValueError exception
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raise ValueError("Invalid number of input values")
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elif isinstance(args[0], (list, tuple)) and isinstance(
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args[1], (list, tuple)
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):
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x = args[0]
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y = args[1]
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# Check if they have the same length. If not, make them equal
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length_min = min(len(x), len(y))
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x = x[:length_min]
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y = y[:length_min]
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if len(x) < 2 or len(y) < 2:
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raise ValueError("Invalid number of input values")
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else:
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# Read input values into 'x' and 'y'
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for xval, yval in zip(x, y):
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self._x.append(xval)
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self._y.append(yval)
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else:
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raise TypeError("Invalid input value")
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elif len(args) == 3:
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# In this case, no combination of input values is valid
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raise ValueError("Invalid number of input values")
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else:
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# If there is an odd number of arguments, drop the last one
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if len(args) % 2 != 0:
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args = args[:-1]
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# Check that all the arguments are ints, floats or Angles
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all_numbers = True
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for arg in args:
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all_numbers = (all_numbers and
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isinstance(arg, (int, float, Angle)))
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# If any of the values failed the test, raise an exception
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if not all_numbers:
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raise TypeError("Invalid input value")
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# Now, extract the data: Odds are x's, evens are y's
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for i in range(int(len(args) / 2.0)):
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self._x.append(args[2 * i])
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self._y.append(args[2 * i + 1])
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# After self._x is found, confirm that x's are different to each other
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for i in range(len(self._x) - 1):
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for k in range(i + 1, len(self._x)):
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if abs(self._x[i] - self._x[k]) < self._tol:
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raise ValueError("Invalid input: Values in 'x' are equal")
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# Order the data points if needed
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self._order_points()
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# Create table containing Newton coefficientes, only if values given
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if len(self._x) > 0:
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self._compute_table()
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def __str__(self):
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"""Method used when trying to print the object.
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:returns: Internal tabular values as strings.
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:rtype: string
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>>> i = Interpolation([5, 3, 6, 1, 2, 4, 9], [10, 6, 12, 2, 4, 8])
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>>> print(i)
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X: [1, 2, 3, 4, 5, 6]
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Y: [2, 4, 6, 8, 10, 12]
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"""
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xstr = "X: " + str(self._x) + "\n"
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ystr = "Y: " + str(self._y)
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return xstr + ystr
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def __repr__(self):
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"""Method providing the 'official' string representation of the object.
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It provides a valid expression that could be used to recreate the
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object.
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:returns: As string with a valid expression to recreate the object
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:rtype: string
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>>> i = Interpolation([5, 3, 6, 1, 2, 4, 9], [10, 6, 12, 2, 4, 8])
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>>> repr(i)
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'Interpolation([1, 2, 3, 4, 5, 6], [2, 4, 6, 8, 10, 12])'
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"""
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return "{}({}, {})".format(self.__class__.__name__, self._x, self._y)
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def __len__(self):
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"""This method returns the number of interpolation points (x, y, pairs)
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stored in this :class:`Interpolation` object.
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:returns: Number of interpolation points internally stored
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:rtype: int
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>>> i = Interpolation([5, 3, 6, 1, 2, 4, 9], [10, 6, 12, 2, 4, 8])
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>>> len(i)
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6
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"""
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return len(self._x)
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def get_tolerance(self):
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"""Gets the internal tolerance value used for comparisons.
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.. note:: The default tolerance value is TOL.
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:returns: Internal tolerance.
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:rtype: float
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"""
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return self._tol
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def set_tolerance(self, tol):
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"""Changes the internal tolerance value used for comparisons.
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:param tol: New tolerance value.
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:type tol: int, float
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:returns: None
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:rtype: None
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"""
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self._tol = tol
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return
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def _compute_table(self):
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"""Method to compute coefficients of Newton interpolation method."""
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for i in range(len(self._x)):
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self._table.append(self._newton_diff(0, i))
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def _newton_diff(self, start, end):
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|
|
"""Auxiliary method to compute the elements of the Newton table.
|
||
|
|
|
||
|
|
:param start: Starting index
|
||
|
|
:type start: int
|
||
|
|
:param end: Ending index
|
||
|
|
:type end: int
|
||
|
|
|
||
|
|
:returns: Resulting value of the element of the Newton table.
|
||
|
|
:rtype: float
|
||
|
|
"""
|
||
|
|
|
||
|
|
if abs(end - start) < self._tol:
|
||
|
|
val = self._y[start]
|
||
|
|
else:
|
||
|
|
x = list(self._x) # Let's make a copy, just in case
|
||
|
|
val = (self._newton_diff(start, end - 1) -
|
||
|
|
self._newton_diff(start + 1, end)) / (x[start] - x[end])
|
||
|
|
|
||
|
|
return val
|
||
|
|
|
||
|
|
def __call__(self, x):
|
||
|
|
"""Method to interpolate the function at a given 'x'.
|
||
|
|
|
||
|
|
:param x: Point where the interpolation will be carried out.
|
||
|
|
:type x: int, float, :py:class:`Angle`
|
||
|
|
|
||
|
|
:returns: Resulting value of the interpolation.
|
||
|
|
:rtype: 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
|
||
|
|
"""
|
||
|
|
|
||
|
|
# Check if input value is of correct type
|
||
|
|
if isinstance(x, (int, float, Angle)):
|
||
|
|
# Check if 'x' already belongs to the data table
|
||
|
|
for i in range(len(self._x)):
|
||
|
|
if abs(x - self._x[i]) < self._tol:
|
||
|
|
return self._y[i] # We don't need to look further
|
||
|
|
# Check if Newton coefficients table is not empty
|
||
|
|
if len(self._table) == 0:
|
||
|
|
raise RuntimeError("Internal table is empty. Use set().")
|
||
|
|
# Check that x is within interpolation table values
|
||
|
|
if x < self._x[0] or x > self._x[-1]:
|
||
|
|
raise ValueError("Input value outside of interpolation range.")
|
||
|
|
# Horner's method is used to efficiently compute the result
|
||
|
|
val = self._table[-1]
|
||
|
|
for i in range(len(self._table) - 1, 0, -1):
|
||
|
|
val = self._table[i - 1] + (x - self._x[i - 1]) * val
|
||
|
|
|
||
|
|
return val
|
||
|
|
else:
|
||
|
|
raise TypeError("Invalid input value")
|
||
|
|
|
||
|
|
def derivative(self, x):
|
||
|
|
"""Method to compute the derivative from interpolation polynomial.
|
||
|
|
|
||
|
|
:param x: Point where the interpolation derivative will be carried out.
|
||
|
|
:type x: int, float, :py:class:`Angle`
|
||
|
|
|
||
|
|
:returns: Resulting value of the interpolation derivative.
|
||
|
|
:rtype: 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
|
||
|
|
"""
|
||
|
|
|
||
|
|
# Check if input value is of correct type
|
||
|
|
if isinstance(x, (int, float, Angle)):
|
||
|
|
# Check that x is within interpolation table values
|
||
|
|
if x < self._x[0] or x > self._x[-1]:
|
||
|
|
raise ValueError("Input value outside of interpolation range.")
|
||
|
|
# If we only have two interpolation points, derivative is simple
|
||
|
|
if len(self._x) == 2:
|
||
|
|
return (self._y[1] - self._y[0]) / (self._x[1] - self._x[0])
|
||
|
|
else:
|
||
|
|
res = self._table[1]
|
||
|
|
for k in range(len(self._table) - 1, 1, -1):
|
||
|
|
val = 0.0
|
||
|
|
for j in range(k):
|
||
|
|
s = 1.0
|
||
|
|
for i in range(k):
|
||
|
|
if i != j:
|
||
|
|
s *= x - self._x[i]
|
||
|
|
val += s
|
||
|
|
res += val * self._table[k]
|
||
|
|
return res
|
||
|
|
else:
|
||
|
|
raise TypeError("Invalid input value")
|
||
|
|
|
||
|
|
def root(self, 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.
|
||
|
|
|
||
|
|
:param xl: Lower limit of interval where the root will be looked for.
|
||
|
|
:type xl: int, float, :py:class:`Angle`
|
||
|
|
:param xh: Higher limit of interval where the root will be looked for.
|
||
|
|
:type xh: int, float, :py:class:`Angle`
|
||
|
|
:param max_iter: Maximum number of iterations allowed.
|
||
|
|
:type max_iter: int
|
||
|
|
|
||
|
|
:returns: Root of the interpolated function within [xl, xh] interval.
|
||
|
|
:rtype: int, float, :py:class:`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
|
||
|
|
"""
|
||
|
|
|
||
|
|
# Get the limits of the interpolation table
|
||
|
|
xmin = self._x[0]
|
||
|
|
xmax = self._x[-1]
|
||
|
|
# Check if input value is of correct type
|
||
|
|
if (isinstance(xl, (int, float, Angle)) and
|
||
|
|
isinstance(xh, (int, float, Angle))):
|
||
|
|
# Check if BOTH values are zero
|
||
|
|
if xl == 0 and xh == 0:
|
||
|
|
xl = xmin
|
||
|
|
xh = xmax
|
||
|
|
# Check if limits are equal
|
||
|
|
if abs(xl - xh) < self._tol:
|
||
|
|
raise ValueError("Invalid limits: xl and xh values are equal")
|
||
|
|
# Put limits in order. Swap them if necessary
|
||
|
|
if xl > xh:
|
||
|
|
xl, xh = xh, xl
|
||
|
|
# Check limits against interpolation table. Reset if necessary
|
||
|
|
if xl < self._x[0]:
|
||
|
|
xl = xmin
|
||
|
|
if xh < self._x[-1]:
|
||
|
|
xh = xmax
|
||
|
|
yl = self.__call__(xl)
|
||
|
|
yh = self.__call__(xh)
|
||
|
|
# Check for a couple special cases
|
||
|
|
if abs(yl) < self._tol:
|
||
|
|
return xl # xl is a root
|
||
|
|
if abs(yh) < self._tol:
|
||
|
|
return xh # xh is a root
|
||
|
|
# Check if signs of ordinates are the same
|
||
|
|
if (yl * yh) > 0.0:
|
||
|
|
raise ValueError("Invalid interval: Probably no root exists")
|
||
|
|
# We are good to go. First option: Newton's root-finding method
|
||
|
|
x = (xl + xh) / 2.0 # Start in the middle of interval
|
||
|
|
y = self.__call__(x)
|
||
|
|
num_iter = 0 # Count the number of iterations
|
||
|
|
while abs(y) > self._tol:
|
||
|
|
if num_iter >= max_iter:
|
||
|
|
raise ValueError(
|
||
|
|
"Too many iterations: Probably no root\
|
||
|
|
exists"
|
||
|
|
)
|
||
|
|
num_iter += 1
|
||
|
|
yp = self.derivative(x)
|
||
|
|
# If derivative is too small, switch to linear interpolation
|
||
|
|
if abs(yp) < 1e-3:
|
||
|
|
x = (xl * yh - xh * yl) / (yh - yl)
|
||
|
|
y = self.__call__(x)
|
||
|
|
else:
|
||
|
|
x = x - y / yp
|
||
|
|
# Check if x is within limits
|
||
|
|
if x < xmin or x > xmax:
|
||
|
|
# Switch to linear interpolation
|
||
|
|
x = (xl * yh - xh * yl) / (yh - yl)
|
||
|
|
y = self.__call__(x)
|
||
|
|
else:
|
||
|
|
y = self.__call__(x)
|
||
|
|
if (y * yl) >= 0.0:
|
||
|
|
xl = x
|
||
|
|
yl = y
|
||
|
|
else:
|
||
|
|
xh = x
|
||
|
|
yh = y
|
||
|
|
return x
|
||
|
|
else:
|
||
|
|
raise TypeError("Invalid input value")
|
||
|
|
|
||
|
|
def minmax(self, 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 :meth:`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.
|
||
|
|
|
||
|
|
:param xl: Lower limit of interval where a extremum will be looked for.
|
||
|
|
:type xl: int, float, :py:class:`Angle`
|
||
|
|
:param xh: Higher limit of interval where extremum will be looked for.
|
||
|
|
:type xh: int, float, :py:class:`Angle`
|
||
|
|
:param max_iter: Maximum number of iterations allowed.
|
||
|
|
:type max_iter: int
|
||
|
|
|
||
|
|
:returns: Extremum of interpolated function within [xl, xh] interval.
|
||
|
|
:rtype: int, float, :py:class:`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
|
||
|
|
"""
|
||
|
|
|
||
|
|
# Compute the derivatives for the current data
|
||
|
|
x = list(self._x)
|
||
|
|
y = []
|
||
|
|
for xi in x:
|
||
|
|
y.append(self.derivative(xi))
|
||
|
|
# Create a new Interpolation object
|
||
|
|
prime = Interpolation(x, y)
|
||
|
|
# Find the root within that object, and return it
|
||
|
|
return prime.root(xl, xh, max_iter)
|
||
|
|
|
||
|
|
|
||
|
|
def main():
|
||
|
|
|
||
|
|
# Let's define a small helper function
|
||
|
|
def print_me(msg, val):
|
||
|
|
print("{}: {}".format(msg, val))
|
||
|
|
|
||
|
|
# Let's now work with the Interpolation class
|
||
|
|
print("\n" + 35 * "*")
|
||
|
|
print("*** Use of Interpolation class")
|
||
|
|
print(35 * "*" + "\n")
|
||
|
|
|
||
|
|
i = Interpolation([5, 3, 6, 1, 2, 4, 9], [10, 6, 12, 2, 4, 8])
|
||
|
|
print("i = Interpolation([5, 3, 6, 1, 2, 4, 9], [10, 6, 12, 2, 4, 8])")
|
||
|
|
print(i)
|
||
|
|
print("NOTE:")
|
||
|
|
print(" a. They are ordered in 'x'")
|
||
|
|
print(" b. The extra value in 'x' was dropped")
|
||
|
|
|
||
|
|
print("")
|
||
|
|
|
||
|
|
# Use the copy constructor
|
||
|
|
print("We can easily make a copy of an Interpolation object")
|
||
|
|
j = Interpolation(i)
|
||
|
|
print("j = Interpolation(i)")
|
||
|
|
print(j)
|
||
|
|
|
||
|
|
print("")
|
||
|
|
|
||
|
|
# Get the number of interpolation points stored
|
||
|
|
print_me("Number or interpolation points in 'j'", len(j)) # 6
|
||
|
|
|
||
|
|
print("")
|
||
|
|
|
||
|
|
j = Interpolation([0.0, 1.0, 3.0], [-1.0, -2.0, 2.0])
|
||
|
|
print("j = Interpolation([0.0, 1.0, 3.0], [-1.0, -2.0, 2.0])")
|
||
|
|
print(j)
|
||
|
|
print_me("j(2)", j(2))
|
||
|
|
print_me("j(0.5)", j(0.5))
|
||
|
|
# Test with a value already in the data table
|
||
|
|
print_me("j(1)", j(1))
|
||
|
|
|
||
|
|
print("")
|
||
|
|
|
||
|
|
# We can interpolate Angles too
|
||
|
|
k = Interpolation(
|
||
|
|
[27.0, 27.5, 28.0, 28.5, 29.0],
|
||
|
|
[
|
||
|
|
Angle(0, 54, 36.125),
|
||
|
|
Angle(0, 54, 24.606),
|
||
|
|
Angle(0, 54, 15.486),
|
||
|
|
Angle(0, 54, 8.694),
|
||
|
|
Angle(0, 54, 4.133),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
print(
|
||
|
|
"k = Interpolation([27.0, 27.5, 28.0, 28.5, 29.0],\n\
|
||
|
|
[Angle(0, 54, 36.125), Angle(0, 54, 24.606),\n\
|
||
|
|
Angle(0, 54, 15.486), Angle(0, 54, 8.694),\n\
|
||
|
|
Angle(0, 54, 4.133)])"
|
||
|
|
)
|
||
|
|
|
||
|
|
print_me("k(28.278)", Angle(k(28.278)).dms_str())
|
||
|
|
|
||
|
|
print("")
|
||
|
|
|
||
|
|
m = Interpolation([-1.0, 0.0, 1.0], [-2.0, 3.0, 2.0])
|
||
|
|
print("m = Interpolation([-1.0, 0.0, 1.0], [-2.0, 3.0, 2.0])")
|
||
|
|
print(m)
|
||
|
|
# Get interpolated values
|
||
|
|
print_me("m(-0.5)", m(-0.5))
|
||
|
|
print_me("m(0.5)", m(0.5))
|
||
|
|
# Get derivatives
|
||
|
|
print_me("m'(-1.0)", m.derivative(-1.0))
|
||
|
|
print_me("m'(-0.5)", m.derivative(-0.5))
|
||
|
|
print_me("m'(0.0)", m.derivative(0.0))
|
||
|
|
print_me("m'(0.5)", m.derivative(0.5))
|
||
|
|
print_me("m'(1.0)", m.derivative(1.0))
|
||
|
|
# Get the root within the interval
|
||
|
|
print_me("m.root()", m.root())
|
||
|
|
# Get the extremum within the interval
|
||
|
|
print_me("m.minmax()", m.minmax())
|
||
|
|
|
||
|
|
m = Interpolation(
|
||
|
|
[29.43, 30.97, 27.69, 28.11, 31.58, 33.05],
|
||
|
|
[
|
||
|
|
0.4913598528,
|
||
|
|
0.5145891926,
|
||
|
|
0.4646875083,
|
||
|
|
0.4711658342,
|
||
|
|
0.5236885653,
|
||
|
|
0.5453707057,
|
||
|
|
],
|
||
|
|
)
|
||
|
|
|
||
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print_me("sin(29.5)\t", m(29.5))
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print_me("sin(30.0)\t", m(30.0))
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print_me("sin(30.5)\t", m(30.5))
|
||
|
|
# Derivative must be adjusted because degrees were used instead of radians
|
||
|
|
print_me("sin'(29.5)\t", degrees(m.derivative(29.5)))
|
||
|
|
print_me("sin'(30.0)\t", degrees(m.derivative(30.0)))
|
||
|
|
print_me("sqrt(3.0)/2.0\t", sqrt(3.0) / 2.0)
|
||
|
|
print_me("sin'(30.5)\t", degrees(m.derivative(30.5)))
|
||
|
|
|
||
|
|
|
||
|
|
if __name__ == "__main__":
|
||
|
|
|
||
|
|
main()
|