10 July 2019 08:22:30 AM
LAGRANGE_INTERP_2D_TEST:
C version
Test the LAGRANGE_INTERP_2D library.
The R8LIB library is needed.
This test also needs the TEST_INTERP_2D library.
LAGRANGE_INTERP_2D_TEST01:
Interpolate data from TEST_INTERP_2D problem #1
Using polynomial interpolant of product degree 1 x 1
Number of data points = 4
X, Y, Z data:
0 0 0 0.766421
1 1 0 0.107558
2 0 1 0.270337
3 1 1 0.0358696
X, Y, Z interpolation:
0 0 0 0.766421
1 1 0 0.107558
2 0 1 0.270337
3 1 1 0.0358696
RMS data interpolation error = 0
RMS data approximation error = 0.0307159
LAGRANGE_INTERP_2D_TEST01:
Interpolate data from TEST_INTERP_2D problem #1
Using polynomial interpolant of product degree 2 x 2
Number of data points = 9
X, Y, Z data:
0 0 0 0.766421
1 0.5 0 0.434914
2 1 0 0.107558
3 0 0.5 0.481806
4 0.5 0.5 0.325762
5 1 0.5 0.161026
6 0 1 0.270337
7 0.5 1 0.145979
8 1 1 0.0358696
X, Y, Z interpolation:
0 0 0 0.766421
1 0.5 0 0.434914
2 1 0 0.107558
3 0 0.5 0.481806
4 0.5 0.5 0.325762
5 1 0.5 0.161026
6 0 1 0.270337
7 0.5 1 0.145979
8 1 1 0.0358696
RMS data interpolation error = 0
RMS data approximation error = 0.184386
LAGRANGE_INTERP_2D_TEST01:
Interpolate data from TEST_INTERP_2D problem #1
Using polynomial interpolant of product degree 3 x 3
Number of data points = 16
X, Y, Z data:
0 0 0 0.766421
1 0.25 0 0.818854
2 0.75 0 0.252062
3 1 0 0.107558
4 0 0.25 0.802583
5 0.25 0.25 1.16528
6 0.75 0.25 0.589359
7 1 0.25 0.230218
8 0 0.75 0.339527
9 0.25 0.75 0.272413
10 0.75 0.75 0.11597
11 1 0.75 0.0503603
12 0 1 0.270337
13 0.25 1 0.22224
14 0.75 1 0.0810474
15 1 1 0.0358696
X, Y, Z interpolation:
0 0 0 0.766421
1 0.25 0 0.818854
2 0.75 0 0.252062
3 1 0 0.107558
4 0 0.25 0.802583
5 0.25 0.25 1.16528
6 0.75 0.25 0.589359
7 1 0.25 0.230218
8 0 0.75 0.339527
9 0.25 0.75 0.272413
10 0.75 0.75 0.11597
11 1 0.75 0.0503603
12 0 1 0.270337
13 0.25 1 0.22224
14 0.75 1 0.0810474
15 1 1 0.0358696
RMS data interpolation error = 0
RMS data approximation error = 0.065489
LAGRANGE_INTERP_2D_TEST01:
Interpolate data from TEST_INTERP_2D problem #1
Using polynomial interpolant of product degree 4 x 4
Number of data points = 25
RMS data interpolation error = 0
RMS data approximation error = 0.0201751
LAGRANGE_INTERP_2D_TEST01:
Interpolate data from TEST_INTERP_2D problem #1
Using polynomial interpolant of product degree 8 x 8
Number of data points = 81
RMS data interpolation error = 0
RMS data approximation error = 0.00171259
LAGRANGE_INTERP_2D_TEST01:
Interpolate data from TEST_INTERP_2D problem #2
Using polynomial interpolant of product degree 1 x 1
Number of data points = 4
X, Y, Z data:
0 0 0 0.111111
1 1 0 3.38444e-09
2 0 1 0.222222
3 1 1 0.111111
X, Y, Z interpolation:
0 0 0 0.111111
1 1 0 3.38444e-09
2 0 1 0.222222
3 1 1 0.111111
RMS data interpolation error = 0
RMS data approximation error = 1.38778e-17
LAGRANGE_INTERP_2D_TEST01:
Interpolate data from TEST_INTERP_2D problem #2
Using polynomial interpolant of product degree 2 x 2
Number of data points = 9
X, Y, Z data:
0 0 0 0.111111
1 0.5 0 2.7421e-05
2 1 0 3.38444e-09
3 0 0.5 0.222195
4 0.5 0.5 0.111111
5 1 0.5 2.7421e-05
6 0 1 0.222222
7 0.5 1 0.222195
8 1 1 0.111111
X, Y, Z interpolation:
0 0 0 0.111111
1 0.5 0 2.7421e-05
2 1 0 3.38444e-09
3 0 0.5 0.222195
4 0.5 0.5 0.111111
5 1 0.5 2.7421e-05
6 0 1 0.222222
7 0.5 1 0.222195
8 1 1 0.111111
RMS data interpolation error = 0
RMS data approximation error = 0.00490804
LAGRANGE_INTERP_2D_TEST01:
Interpolate data from TEST_INTERP_2D problem #2
Using polynomial interpolant of product degree 3 x 3
Number of data points = 16
X, Y, Z data:
0 0 0 0.111111
1 0.25 0 0.00244154
2 0.75 0 3.04657e-07
3 1 0 3.38444e-09
4 0 0.25 0.219781
5 0.25 0.25 0.111111
6 0.75 0.25 2.7421e-05
7 1 0.25 3.04657e-07
8 0 0.75 0.222222
9 0.25 0.75 0.222195
10 0.75 0.75 0.111111
11 1 0.75 0.00244154
12 0 1 0.222222
13 0.25 1 0.222222
14 0.75 1 0.219781
15 1 1 0.111111
X, Y, Z interpolation:
0 0 0 0.111111
1 0.25 0 0.00244154
2 0.75 0 3.04657e-07
3 1 0 3.38444e-09
4 0 0.25 0.219781
5 0.25 0.25 0.111111
6 0.75 0.25 2.7421e-05
7 1 0.25 3.04657e-07
8 0 0.75 0.222222
9 0.25 0.75 0.222195
10 0.75 0.75 0.111111
11 1 0.75 0.00244154
12 0 1 0.222222
13 0.25 1 0.222222
14 0.75 1 0.219781
15 1 1 0.111111
RMS data interpolation error = 0
RMS data approximation error = 0.00143279
LAGRANGE_INTERP_2D_TEST01:
Interpolate data from TEST_INTERP_2D problem #2
Using polynomial interpolant of product degree 4 x 4
Number of data points = 25
RMS data interpolation error = 0
RMS data approximation error = 0.000930276
LAGRANGE_INTERP_2D_TEST01:
Interpolate data from TEST_INTERP_2D problem #2
Using polynomial interpolant of product degree 8 x 8
Number of data points = 81
RMS data interpolation error = 0
RMS data approximation error = 0.000109215
LAGRANGE_INTERP_2D_TEST01:
Interpolate data from TEST_INTERP_2D problem #3
Using polynomial interpolant of product degree
C 代码 定义和计算拉格朗日多项式 p(x,y) 根据 2D 参数插值一组数据 在产品网格上评估.rar
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