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本帖最后由 kerb 于 2018-7-22 14:18 编辑
这是我写的一个,希望对你有用
全域拉格朗日插值其实就是多项式插值,只是一般教科书的讲解形式,让很多人忽略了这一点。高阶多项式插值会引起容格现象,也就是说虽然多项式插值会经过已知点,但是会引起数值震荡。
最小二乘法适用于数据拟合,最常见的是那种线性拟合,其实也可以用已知的曲线的组合去拟合给定的数据。曲线可以有多种选择,比如光谱曲线往往用高斯曲线或者洛仑兹曲线的组合去拟合,当然也可以用多项式曲线去拟合,只是缺少了物理意义,但是这个时候,可以把这种拟合的曲线理解为插值曲线,给出数值区间任意点的函数值。
问题描述:已知一组数据点(XT,YT),这些点的总数是M,我们希望用一个N阶的多项式去拟合这些数据,假设这个多项式的系数用数组U表示,记住一个N阶的多项式,有N+1个系数(包括常数项),求的多项式系数,多项式就确定了。
Y(1)=U(1)+U(2)*X(1)+U(3)*X(1)^2+...+U(N+1)*X(1)^N
Y(2)=U(1)+U(2)*X(2)+U(3)*X(2)^2+...+U(N+1)*X(2)^N
......................................................................................
Y(M)=U(1)+U(2)*X(M)+U(3)*X(M)^2+...+U(N+1)*X(M)^N
记
Y=(Y(1),Y(2),...,Y(M))^T,U=(U(1),U(2),...,U(N))
矩阵A的元素是A(i,j)=X(i)^j,1<=i<=M,0<=j<=N,A是MxN的
上面的方程组可以写成:
AU=Y
如果M<N,这个时候有无穷多解,但是无法解释每个解的物理含义;如果M=N,且A非奇异,这个时候可以解得一组数据,这个时候其实就是求多项式插值;当M>N,这是超定方程组,理论上只能求得最小二乘解,记A^T表示矩阵A的转置矩阵
(A^T*A)U=(A^T*Y),解出U就求出多项式系数。
下面的程序中:
POINTS_NUM表示已知点的数目,即上面说的M
POLY_ORDER,表示多项式阶数,即上面说的N
POLY_COEF多项式系数,数组
XT,YT已知点,数组
[Fortran] 纯文本查看 复制代码 003 | INTEGER , PARAMETER :: POINTS_NUM = 15 |
004 | INTEGER , PARAMETER :: POLY_ORDER = 13 |
005 | INTEGER , PARAMETER :: DP = KIND ( 1 .D 0 ) |
006 | REAL ( KIND = DP ) :: A ( POINTS_NUM , POLY_ORDER +1 ) , POLY_COEF ( POLY_ORDER +1 ) |
007 | REAL ( KIND = DP ) :: XT ( POINTS_NUM ) , YT ( POINTS_NUM ) , DX , XN ( POINTS_NUM ) , YN ( POINTS_NUM ) |
011 | XT = ( / 0.1D0 , 0.2D0 , 0.3D0 , 0.4D0 , 0.5D0 , 0.6D0 , 0.7D0 , 0.8D0 , 0.9D0 , 0.92D0 , 0.94D0 , 0.96D0 , 0.98D0 , 0.99D0 , 0.995D0 / ) |
012 | YT = ( / 0.86D0 , 0.78D0 , 0.71D0 , 0.66D0 , 0.59D0 , 0.52D0 , 0.45D0 , 0.36D0 , 0.23D0 , 0.19D0 , 0.16D0 , 0.12D0 , 0.07D0 , 0.04D0 , 0.02D0 / ) |
016 | CALL LSINTERPOLY ( POINTS_NUM , XT , YT , POLY_ORDER , POLY_COEF , INFO ) |
022 | CALL POLY_VALUE ( POLY_ORDER , POLY_COEF , XN ( I ) , YN ( I ) ) |
024 | WRITE ( * , FMT = "(F6.4,2X,G0)" ) YN ( I ) , YN ( I ) - YT ( I ) |
032 | SUBROUTINE LSINTERPOLY ( POINTS_NUM & |
040 | INTEGER , PARAMETER :: DP = KIND ( 1 .D 0 ) |
041 | INTEGER , INTENT ( IN ) :: POINTS_NUM , POLY_ORDER |
042 | REAL ( KIND = DP ) , INTENT ( IN ) :: XT ( POINTS_NUM ) , YT ( POINTS_NUM ) |
043 | REAL ( KIND = DP ) , INTENT ( OUT ) :: POLY_COEF ( POLY_ORDER +1 ) |
044 | INTEGER , INTENT ( OUT ) :: INFO |
046 | REAL ( KIND = DP ) :: A ( POINTS_NUM , POLY_ORDER +1 ) , ATA ( POLY_ORDER +1 , POLY_ORDER +1 ) |
047 | REAL ( KIND = DP ) :: B ( POINTS_NUM ) , C ( POLY_ORDER +1 , POINTS_NUM ) |
049 | IF ( POLY_ORDER +1 > POINTS_NUM ) THEN |
067 | POLY_COEF = MATMUL ( C , B ) |
074 | CALL SOLVE ( ATA , POLY_ORDER +1 , POLY_COEF , SOL_OK ) |
084 | SUBROUTINE POLY_VALUE ( POLY_ORDER , POLY_COEF , X , Y ) |
086 | INTEGER , PARAMETER :: DP = KIND ( 1 .D 0 ) |
087 | INTEGER , INTENT ( IN ) :: POLY_ORDER |
088 | REAL ( KIND = DP ) , INTENT ( IN ) :: POLY_COEF ( POLY_ORDER +1 ) , X |
089 | REAL ( KIND = DP ) , INTENT ( OUT ) :: Y |
093 | Y = Y * X + POLY_COEF ( POLY_ORDER +1 - I ) |
098 | SUBROUTINE SOLVE ( A , N , B , SOL_OK ) |
100 | INTEGER , PARAMETER :: DP = KIND ( 1 .D 0 ) |
101 | INTEGER , INTENT ( IN ) :: N |
102 | LOGICAL , INTENT ( OUT ) :: SOL_OK |
103 | REAL ( KIND = DP ) , INTENT ( INOUT ) :: A ( N , N ) |
104 | REAL ( KIND = DP ) , INTENT ( INOUT ) :: B ( N ) |
105 | REAL ( KIND = DP ) :: BIG , DUM , PIVINV , TEMP |
106 | INTEGER I , ICOL , IROW , J , K , L , LL , INDXC ( N ) , INDXR ( N ) , IPIV ( N ) |
116 | IF ( IPIV ( K ) .EQ. 0 ) THEN |
117 | IF ( ABS ( A ( J , K ) ) .GE. BIG ) THEN |
122 | ELSEIF ( IPIV ( K ) .GT. 1 ) THEN |
123 | WRITE ( * , * ) 'SINGULAR MATRIX IN GAUSSJ' |
129 | IPIV ( ICOL ) = IPIV ( ICOL ) +1 |
130 | IF ( IROW .NE. ICOL ) THEN |
142 | TEMP = ABS ( A ( ICOL , ICOL ) ) |
143 | IF ( A ( ICOL , ICOL ) == 0 .D 0 ) THEN |
144 | WRITE ( * , * ) 'SINGULAR MATRIX IN GAUSSJ' |
148 | PIVINV = 1 .D 0 / A ( ICOL , ICOL ) |
151 | A ( ICOL , L ) = A ( ICOL , L ) * PIVINV |
153 | B ( ICOL ) = B ( ICOL ) * PIVINV |
159 | A ( LL , L ) = A ( LL , L ) - A ( ICOL , L ) * DUM |
161 | B ( LL ) = B ( LL ) - B ( ICOL ) * DUM |
166 | IF ( INDXR ( L ) .NE. INDXC ( L ) ) THEN |
169 | A ( K , INDXR ( L ) ) = A ( K , INDXC ( L ) ) |
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