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changed: - Introduction This file contains an implementation of rational interpolation, where the data points are element of any integral domain. Questions and Outlook - Maybe this file should be joined with pinterp.spad, where polynomial Lagrange interpolation is implemented. This version parallels the structure of pinterp.spad closely. This also answers comments and questions from wyscc. He remarked - Abbreviations for a constructor should be limited to 7 letters (not 8). The system occasionally adds the 8th character to a package for internal use. - Function names begin with a lower case, so RationalInterpolation should be rationalInterpolation, or better, rationalInterpolate. - Regarding the types I used for the values, wyscc remarked - If we are doing a rational interpolation, presumably the values are rational, so it does not make sense to require the $y$-coordinates of inputs be integral. On the other hand, as in the above example, if one uses 'FRAC INT', problems can arise when this package is combined with other packages that constructs the quotient field of the parameter domain 'F' because Axiom does not like constructing 'FRAC FRAC INT'. Note however, that the package would rather construct the type 'FRAC SUP FRAC INT', so this problem should not occur. Moreover, there are situations - for example in the package [mantepse.spad2], where we want to interpolate values from an IntegralDomain. Of course we could first convert them to the quotient field, however, the current approach seems more natural to me. - Finally, wyscc asked: If <code>p(xx) = interpolate(lx, ly, m, k)</code>, what is the purpose of <code>elt(px, qx) = p(qx)</code>, the composition of <code>p(xx)</code> and <code>qx</code>, especially when <code>qx</code> is from <code>FRAC UP(xx, F)</code> instead of from just <code>F</code>? and why is this function (the composition) also called <code>interpolate</code>? I do not really know - apart from a very superficial level: Clearly, the second function was intended to let the user easily plug in values into the interpolated function. I don't find this sensible and I would be happy to change it. Indeed, this would also get rid of the first parameter to 'RINTERP', which is quite a nuisance. I think we should agree on a general interface for interpolation algorithms, and mark 'PINTERP' as obsolete. By the way, it seems that 'RINTERP' is faster, too. - There are probably better ways to implement rational interpolation. Maybe http://www.cs.ucsb.edu/~omer/personal/abstracts/rational.html contains something useful. In particular, in my package [mantepse.spad2], in 'guessRat' and 'guessExpRat' I generate interpolating polynomials for all possible degrees of numerator and denominator. The above article contains an algorithm that does this in time $O(n^2)$, which would be quite nice. Currently, I need $O(n^2)$ operations for *each* degree! - For polynomial interpolation, there seems to be an algorithm that needs only $O(n\log(n)^2\log\log(n))$ operations. It can be found in van zur Gathen's book "Modern computer algebra", chapter 10. - For those who speak german, http://www.num.math.uni-goettingen.de/schaback/teaching/numath.ps contains quite a bit of information. - This implementation of rational interpolation neither takes care of unattainable points, nor does it check whether the values of the $x$-coordinates are all distinct. - Comments welcome! \begin{spad} )abbrev package RINTERPA RationalInterpolationAlgorithms ++ Description: ++ This package exports rational interpolation algorithms RationalInterpolationAlgorithms(F, P): Cat == Body where F: IntegralDomain P: UnivariatePolynomialCategory(F) Cat == with RationalInterpolation: (List F, List F, NonNegativeInteger, NonNegativeInteger) -> Fraction P +++ We assume that the elements of the first list are all distinct. +++ If they are not, division by zero might occur. Body == add RationalInterpolation(xlist, ylist, m, k) == #xlist ^= #ylist => error "Different number of points and values." #xlist ^= m+k+1 => error "wrong number of points" tempvec: List F := [1 for i in 1..(m+k+1)] collist: List List F := cons(tempvec, [(tempvec := [tempvec.i * xlist.i _ for i in 1..(m+k+1)]) _ for j in 1..max(m, k)]) collist := append([collist.j for j in 1..(m+1)], _ [[- collist.j.i * ylist.i for i in 1..(m+k+1)] _ for j in 1..(k+1)]) resspace: List Vector F := nullSpace((transpose matrix collist) _ ::Matrix F) reslist: List List P := _ [[monomial((resspace.1).(i+1), i) for i in 0..m], _ [monomial((resspace.1).(i+m+2), i) for i in 0..k]] reduce((_+), reslist.1)/reduce((_+), reslist.2) \end{spad} \begin{spad} )abbrev package RINTERP RationalInterpolation ++ Description: ++ This package exports interpolation algorithms RationalInterpolation(xx, F): Cat == Body where xx: Symbol F: IntegralDomain UP ==> UnivariatePolynomial SUP ==> SparseUnivariatePolynomial Cat == with interpolate: (Fraction UP(xx, F), List F, List F, _ NonNegativeInteger, NonNegativeInteger) _ -> Fraction UP(xx, F) interpolate: (List F, List F, NonNegativeInteger, NonNegativeInteger) _ -> Fraction SUP F Body == add RIA ==> RationalInterpolationAlgorithms interpolate(qx, lx, ly, m, k) == px := RationalInterpolation(lx, ly, m, k)$RIA(F, UP(xx, F)) elt(px, qx) interpolate(lx, ly, m, k) == RationalInterpolation(lx, ly, m, k)$RIA(F, SUP F) \end{spad} First we check whether we have the right number of points and values. Clearly the number of points and the number of values must be identical. Note that we want to determine the numerator and denominator polynomials only up to a factor. Thus, we want to determine $m+k+1$ coefficients, where $m$ is the degree of the polynomial in the numerator and $k$ is the degree of the polynomial in the denominator. In fact, we could also leave - for example - $k$ unspecified and determine it as $k=\#xlist-m-1$: I don't know whether this would be better. The next step is to set up the matrix. Suppose that our numerator polynomial is $p(x)=a_0+a_1x+\dots+a_mx^m$ and that our denominator polynomial is $q(x)=b_0+b_1x+\dots+b_mx^m$. Then we have the following equations, writing $n$ for $m+k+1$: \begin{eqnarray*} p(x_1)-y_1q(x_1)&=a_0+a_1x_1+\dots +a_mx_1^m-y_1(b_0+b_1x_1+\dots +b_kx_1^k)=0\\ p(x_2)-y_2q(x_2)&=a_0+a_1x_2+\dots +a_mx_2^m-y_2(b_0+b_1x_2+\dots +b_kx_2^k)=0\\ &\;\;\vdots\\ p(x_n)-y_nq(x_n)&=a_0+a_1x_n+\dots +a_mx_n^m-y_n(b_0+b_1x_n+\dots +b_kx_n^k)=0 \end{eqnarray*} This can be written as \begin{equation*} \begin{bmatrix} 1&x_1&\dots&x_1^m&-y_1&-y_1x_1&\dots&-y_1x_1^k\\ 1&x_2&\dots&x_2^m&-y_2&-y_2x_2&\dots&-y_2x_2^k\\ \vdots\\ 1&x_n&\dots&x_n^m&-y_n&-y_nx_n&\dots&-y_nx_2^k \end{bmatrix} \begin{bmatrix} a_0\\a_1\\\vdots\\a_m\\b_0\\b_1\\\vdots\\b_k \end{bmatrix}=\mathbf 0 \end{equation*} We generate this matrix columnwise, then we can solve the system using 'nullSpace'. Note that it may happen that the system has several solutions. In this case, some of the data points may not be interpolated correctly. However, the solution is often still useful, thus we do not signal an error. Since all the solutions of 'nullSpace' will be equivalent, we can always simply take the first one. Finally, we return the rational function. Examples To conclude we present some examples. To begin with, the following interpolation illustrates the concept of unattainable points: \begin{axiom} interpolate([q,q^2,q^3],[0,x^1,x^2],0,2)$RINTERP(qn, FRAC POLY INT) \end{axiom} \begin{axiom} f(x) == (x^3+5*x-3)/(x^2-3) xlist := [1/2, 4, 1/6, 8, 1/10, 12] ylist := [f(x) for x in xlist] interpolate(xlist, ylist, 3, 2)$RINTERP('x, FRAC INT) interpolate(1/6::FRAC UP(x,FRAC INT), xlist, ylist, 3, 2)$RINTERP('x,FRAC INT) \end{axiom} A harder example: \begin{axiom} dom := DMP([z],INT); g: FRAC dom -> FRAC dom; g(x) == (x^3*z+5*z^2*x -3*z^3)/(z*x^2 - 3) xxlist: List FRAC dom := [1/(2*z), 4*z, 1/(6*z), 8*z, 1/(10*z), 12*z] yylist := [g(x) for x in xxlist] interpolate(xxlist, yylist, 3, 2)$RINTERP('x, FRAC dom) interpolate(4*z::FRAC UP(x,dom), xxlist, yylist, 3, 2)$RINTERP('x, FRAC dom) \end{axiom}
This file contains an implementation of rational interpolation, where the data points are element of any integral domain.
FRAC INT, problems can arise when this package is combined with
other packages that constructs the quotient field of the parameter domain
F because Axiom does not like constructing FRAC FRAC INT. Note however, that the package would rather construct the type FRAC SUP
FRAC INT, so this problem should not occur. Moreover, there are situations
- for example in the package mantepse.spad2, where we want to interpolate values
from an IntegralDomain?. Of course we could first convert them to the
quotient field, however, the current approach seems more natural to me.
p(xx) = interpolate(lx, ly, m, k), what is the purpose of
elt(px, qx) = p(qx), the composition of p(xx) and
qx, especially when qx is from FRAC UP(xx,
F) instead of from just F? and why is this function
(the composition) also called interpolate? I do not really know - apart from a very superficial level: Clearly, the
second function was intended to let the user easily plug in values into the
interpolated function. I don't find this sensible and I would be happy to
change it. Indeed, this would also get rid of the first parameter to
RINTERP, which is quite a nuisance.
I think we should agree on a general interface for interpolation
algorithms, and mark PINTERP as obsolete. By the way, it seems that
RINTERP is faster, too.
guessRat
and guessExpRat I generate interpolating polynomials for all possible degrees
of numerator and denominator. The above article contains an algorithm that does
this in time )abbrev package RINTERPA RationalInterpolationAlgorithms
++ Description:
++ This package exports rational interpolation algorithms
RationalInterpolationAlgorithms(F, P): Cat == Body where
F: IntegralDomain
P: UnivariatePolynomialCategory(F)
Cat == with
RationalInterpolation: (List F, List F, NonNegativeInteger,
NonNegativeInteger)
-> Fraction P
+++ We assume that the elements of the first list are all distinct.
+++ If they are not, division by zero might occur.
Body == add
RationalInterpolation(xlist, ylist, m, k) ==
#xlist ^= #ylist =>
error "Different number of points and values."
#xlist ^= m+k+1 =>
error "wrong number of points"
tempvec: List F := [1 for i in 1..(m+k+1)]
collist: List List F := cons(tempvec,
[(tempvec := [tempvec.i * xlist.i _
for i in 1..(m+k+1)]) _
for j in 1..max(m, k)])
collist := append([collist.j for j in 1..(m+1)], _
[[- collist.j.i * ylist.i for i in 1..(m+k+1)] _
for j in 1..(k+1)])
resspace: List Vector F := nullSpace((transpose matrix collist) _
::Matrix F)
reslist: List List P := _
[[monomial((resspace.1).(i+1), i) for i in 0..m], _
[monomial((resspace.1).(i+m+2), i) for i in 0..k]]
reduce((_+), reslist.1)/reduce((_+), reslist.2)
Compiling FriCAS source code from file
/var/zope2/var/LatexWiki/959208282017174297-25px001.spad using
old system compiler.
RINTERPA abbreviates package RationalInterpolationAlgorithms
------------------------------------------------------------------------
initializing NRLIB RINTERPA for RationalInterpolationAlgorithms
compiling into NRLIB RINTERPA
compiling exported RationalInterpolation : (List F,List F,NonNegativeInteger,NonNegativeInteger) -> Fraction P
Time: 0.83 SEC.
(time taken in buildFunctor: 0)
;;; *** |RationalInterpolationAlgorithms| REDEFINED
;;; *** |RationalInterpolationAlgorithms| REDEFINED
Time: 0 SEC.
Cumulative Statistics for Constructor RationalInterpolationAlgorithms
Time: 0.83 seconds
finalizing NRLIB RINTERPA
Processing RationalInterpolationAlgorithms for Browser database:
--------(RationalInterpolation ((Fraction P) (List F) (List F) (NonNegativeInteger) (NonNegativeInteger)))---------
--->-->RationalInterpolationAlgorithms((RationalInterpolation ((Fraction P) (List F) (List F) (NonNegativeInteger) (NonNegativeInteger)))): Improper first word in comments: +
"+ We assume that the elements of the first list are all distinct. + If they are not,{} division by zero might occur."
--------constructor---------
------------------------------------------------------------------------
RationalInterpolationAlgorithms is now explicitly exposed in frame
initial
RationalInterpolationAlgorithms will be automatically loaded when
needed from /var/zope2/var/LatexWiki/RINTERPA.NRLIB/code)abbrev package RINTERP RationalInterpolation
++ Description:
++ This package exports interpolation algorithms
RationalInterpolation(xx, F): Cat == Body where
xx: Symbol
F: IntegralDomain
UP ==> UnivariatePolynomial
SUP ==> SparseUnivariatePolynomial
Cat == with
interpolate: (Fraction UP(xx, F), List F, List F, _
NonNegativeInteger, NonNegativeInteger) _
-> Fraction UP(xx, F)
interpolate: (List F, List F, NonNegativeInteger, NonNegativeInteger) _
-> Fraction SUP F
Body == add
RIA ==> RationalInterpolationAlgorithms
interpolate(qx, lx, ly, m, k) ==
px := RationalInterpolation(lx, ly, m, k)$RIA(F, UP(xx, F))
elt(px, qx)
interpolate(lx, ly, m, k) ==
RationalInterpolation(lx, ly, m, k)$RIA(F, SUP F)
Compiling FriCAS source code from file
/var/zope2/var/LatexWiki/6898989268314666018-25px002.spad using
old system compiler.
RINTERP abbreviates package RationalInterpolation
processing macro definition UP ==> UnivariatePolynomial
processing macro definition SUP ==> SparseUnivariatePolynomial
------------------------------------------------------------------------
initializing NRLIB RINTERP for RationalInterpolation
compiling into NRLIB RINTERP
processing macro definition RIA ==> RationalInterpolationAlgorithms
compiling exported interpolate : (Fraction UnivariatePolynomial(xx,F),List F,List F,NonNegativeInteger,NonNegativeInteger) -> Fraction UnivariatePolynomial(xx,F)
Time: 0.04 SEC.
compiling exported interpolate : (List F,List F,NonNegativeInteger,NonNegativeInteger) -> Fraction SparseUnivariatePolynomial F
Time: 0.01 SEC.
(time taken in buildFunctor: 0)
;;; *** |RationalInterpolation| REDEFINED
;;; *** |RationalInterpolation| REDEFINED
Time: 0 SEC.
Warnings:
[1] interpolate: not known that (IntegralDomain) is of mode (CATEGORY package (SIGNATURE interpolate ((Fraction (UnivariatePolynomial xx F)) (Fraction (UnivariatePolynomial xx F)) (List F) (List F) (NonNegativeInteger) (NonNegativeInteger))) (SIGNATURE interpolate ((Fraction (SparseUnivariatePolynomial F)) (List F) (List F) (NonNegativeInteger) (NonNegativeInteger))))
Cumulative Statistics for Constructor RationalInterpolation
Time: 0.05 seconds
finalizing NRLIB RINTERP
Processing RationalInterpolation for Browser database:
--->/usr/local/lib/axiom/target/x86_64-unknown-linux/../../src/algebra/RINTERP.spad-->RationalInterpolation((interpolate ((Fraction (UP xx F)) (Fraction (UP xx F)) (List F) (List F) (NonNegativeInteger) (NonNegativeInteger)))): Not documented!!!!
--->/usr/local/lib/axiom/target/x86_64-unknown-linux/../../src/algebra/RINTERP.spad-->RationalInterpolation((interpolate ((Fraction (SUP F)) (List F) (List F) (NonNegativeInteger) (NonNegativeInteger)))): Not documented!!!!
--------constructor---------
------------------------------------------------------------------------
RationalInterpolation is now explicitly exposed in frame initial
RationalInterpolation will be automatically loaded when needed from
/var/zope2/var/LatexWiki/RINTERP.NRLIB/codeFirst we check whether we have the right number of points and values. Clearly
the number of points and the number of values must be identical. Note that we
want to determine the numerator and denominator polynomials only up to a
factor. Thus, we want to determine
coefficients, where
is the degree
of the polynomial in the numerator and
is the degree of the polynomial in
the denominator.
In fact, we could also leave - for example -
unspecified and determine it
as
: I don't know whether this would be better.
The next step is to set up the matrix. Suppose that our numerator polynomial is
and that our denominator polynomial is
. Then we have the following equations, writing
for
:
![]() |
![]() |
We generate this matrix columnwise, then we can solve the system using nullSpace.
Note that it may happen that the system has several solutions. In this case, some of the data points may not be interpolated correctly. However, the solution is often still useful, thus we do not signal an error.
Since all the solutions of nullSpace will be equivalent, we can always
simply take the first one. Finally, we return the rational function.
To conclude we present some examples. To begin with, the following interpolation illustrates the concept of unattainable points:
interpolate([q,q^2,q^3],[0,x^1,x^2],0,2)$RINTERP(qn, FRAC POLY INT)
| (1) |
f(x) == (x^3+5*x-3)/(x^2-3)
xlist := [1/2, 4, 1/6, 8, 1/10, 12]
| (2) |
ylist := [f(x) for x in xlist]
Compiling function f with type Fraction Integer -> Fraction Integer
| (3) |
interpolate(xlist, ylist, 3, 2)$RINTERP('x, FRAC INT)
| (4) |
interpolate(1/6::FRAC UP(x,FRAC INT), xlist, ylist, 3, 2)$RINTERP('x,FRAC INT)
| (5) |
A harder example:
dom := DMP([z],INT);
g: FRAC dom -> FRAC dom;
g(x) == (x^3*z+5*z^2*x -3*z^3)/(z*x^2 - 3)
xxlist: List FRAC dom := [1/(2*z), 4*z, 1/(6*z), 8*z, 1/(10*z), 12*z]
| (6) |
yylist := [g(x) for x in xxlist]
Compiling function g with type Fraction
DistributedMultivariatePolynomial([z],Integer) -> Fraction
DistributedMultivariatePolynomial([z],Integer)![]() | (7) |
interpolate(xxlist, yylist, 3, 2)$RINTERP('x, FRAC dom)
| (8) |
interpolate(4*z::FRAC UP(x,dom), xxlist, yylist, 3, 2)$RINTERP('x, FRAC
dom)
| (9) |