15 September 2021 8:27:04.003 AM LAGRANGE_APPROX_1D_TEST: FORTRAN90 version Test the LAGRANGE_APPROX_1D library. The R8LIB library is needed. The QR_SOLVE library is needed. These tests need the TEST_INTERP_1D library. TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.339102 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.166452 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.419666E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.240598 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.123596 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.314490E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.185693 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.887418E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.220189E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.152878 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.797787E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.201210E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.123213 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.615409E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.155226E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.967979E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.539803E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.136472E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.530875E-07 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.355190E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.922048E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.310855 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.150322 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.376630E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.148928 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.695370E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.172370E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.596755E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.281495E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.703260E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.303801E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.134775E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.331813E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.290094E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.130200E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.322334E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.102938E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.421490E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.102749E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.418655E-08 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.178635E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.420427E-03 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.177248 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.922974E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.235056E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.177000 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.922593E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.234966E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.149408 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.741944E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.187020E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.130175 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.585046E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.141420E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.130135 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.572512E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.134738E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.321602E-13 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.239830E-13 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.132519E-13 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.908536E-14 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.217641E-13 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.167861E-13 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.340274 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.168469 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.425116E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.155149 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.763902E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.193000E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.128058 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.619788E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.155615E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.103655 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.503747E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.127081E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.759665E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.362640E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.909271E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.440258E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.207858E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.523983E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.182235E-07 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.822644E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.208625E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 2.43702 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.912461 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.225184 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 2.42567 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.905658 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.223450 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 2.36481 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.901398 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.223330 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 2.34275 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.881055 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.217365 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 2.08849 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.807521 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.203694 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 1.74483 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.683562 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.173257 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.104484E-06 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.545175 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.139144 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.921699E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.465450E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.118098E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.556998E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.259941E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.642064E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.521267E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.247449E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.614395E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.199070E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.951932E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.236086E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.138423E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.624733E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.150203E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.409900E-03 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.229333E-03 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.548379E-04 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.695432E-13 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.125779E-06 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.310301E-07 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.494804 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.253188 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.643879E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.441869 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.224636 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.569630E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.395849 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.202045 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.512808E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.332983 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.170909 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.433248E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.320653 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.165044 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.418670E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.228126 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.124149 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.315679E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.175707E-06 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.888552E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.228763E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.703311E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.355130E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.900535E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.703311E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.355130E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.900535E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.484293E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.241573E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.609318E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.484293E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.241573E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.609318E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.327928E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.163536E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.410558E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.137692E-01 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.744795E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.185906E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.721535E-09 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.150129E-02 TEST02: Approximate evenly spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.380259E-03 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.318305 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.160822 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.407328E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.230506 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.113552 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.287151E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.148050 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.796243E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.203639E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.140191 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.715261E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.181930E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.955066E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.522266E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.133735E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.767570E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.456383E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.116871E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.109641E-08 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.296050E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 1 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.776060E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.340570 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.167920 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.423124E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.154471 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.759758E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.191486E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.543997E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.268106E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.679881E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.270610E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.128587E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.326353E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.250760E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.119402E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.303726E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.841292E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.355330E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.916116E-03 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.950536E-10 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.136302E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 2 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.364291E-03 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.177223 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.907263E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.231162E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.176219 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.901604E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.229676E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.137846 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.693248E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.175505E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.125120 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.616308E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.154744E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.124111 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.614471E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.154485E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.261791E-13 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.178437E-13 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.205113E-13 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.583920E-14 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.153546E-13 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 3 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.127504E-13 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.356674 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.176934 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.447012E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.136798 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.689368E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.175008E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.116671 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.573157E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.145350E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.879200E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.440168E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.111852E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.665821E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.319644E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.811682E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.355498E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.175110E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.445076E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.353840E-09 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.706498E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 4 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.178664E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 2.25184 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 1.03734 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.259468 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 2.22633 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 1.02421 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.256098 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 1.39124 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.939476 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.237080 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 1.38146 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.934329 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.235678 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 1.05544 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.763755 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.194242 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.560417 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.601717 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.153004 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.633002E-08 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.477064 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 5 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.121421 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.875275E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.442992E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.112476E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.561389E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.278538E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.702225E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.501106E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.250774E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.633981E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.180685E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.910691E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.230689E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.129296E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.644693E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.162578E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.437963E-03 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.220659E-03 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.558002E-04 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.361725E-13 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.132703E-06 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 6 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.334887E-07 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.420380 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.217436 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.553576E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.375603 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.194947 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.496105E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.326203 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.170254 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.433771E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.267661 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.142739 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.364144E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.256093 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.136782 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.349068E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.169738 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.100825 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.258736E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.198051E-08 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.706409E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 7 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.185153E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 0 Number of data points = 16 L2 approximation error averaged per data node = 0.601819E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 0 Number of data points = 64 L2 approximation error averaged per data node = 0.313150E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 0 Number of data points = 1000 L2 approximation error averaged per data node = 0.795798E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 1 Number of data points = 16 L2 approximation error averaged per data node = 0.601819E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 1 Number of data points = 64 L2 approximation error averaged per data node = 0.313150E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 1 Number of data points = 1000 L2 approximation error averaged per data node = 0.795798E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 2 Number of data points = 16 L2 approximation error averaged per data node = 0.395650E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 2 Number of data points = 64 L2 approximation error averaged per data node = 0.210442E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 2 Number of data points = 1000 L2 approximation error averaged per data node = 0.534839E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 3 Number of data points = 16 L2 approximation error averaged per data node = 0.395650E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 3 Number of data points = 64 L2 approximation error averaged per data node = 0.210442E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 3 Number of data points = 1000 L2 approximation error averaged per data node = 0.534839E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 4 Number of data points = 16 L2 approximation error averaged per data node = 0.255343E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 4 Number of data points = 64 L2 approximation error averaged per data node = 0.141421E-01 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 4 Number of data points = 1000 L2 approximation error averaged per data node = 0.359453E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 8 Number of data points = 16 L2 approximation error averaged per data node = 0.922841E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 8 Number of data points = 64 L2 approximation error averaged per data node = 0.638682E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 8 Number of data points = 1000 L2 approximation error averaged per data node = 0.162361E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 16 Number of data points = 16 L2 approximation error averaged per data node = 0.161300E-10 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 16 Number of data points = 64 L2 approximation error averaged per data node = 0.130271E-02 TEST03: Approximate Chebyshev-spaced data from TEST_INTERP_1D problem # 8 Use polynomial approximant of degree 16 Number of data points = 1000 L2 approximation error averaged per data node = 0.331254E-03 LAGRANGE_APPROX_1D_TEST: Normal end of execution. 15 September 2021 8:27:04.060 AM