c c Spectrometer transfer functions based on comm_8_dir.dat for left and c Q3 is mistuned 8.5% low to match conditions during PVDIS running c 11/1/2010 -jjl c c c typical call: answer = function(x,5) c INPUTS: x = 5 or more element array c x(1)=x0 (meters) c x(2)=theta0 (really tan(theta0)) c x(3)=y0 (meters) c x(4)=phi0 (really tan(phi0)) c x(5)=delta (fractional value NOT percent) c M=5 c c OUTPUT: units are the same as inputs c c NOMENCLATURE: function name = prefix + _e_ or _h_ +suffix c prefixes: x means xfinal c t means thetafinal c y means yfinal c p means phifinal c l means pathlength difference from central trajectory c c suffixes: fp means target to focus c dent means target to Dipole entrance (see note below) c dext means target to dipole exit c q3en means target to Q3 entrance c q3ex means target to Q3 exit c c _lm_ is for left arm mistuned c C re the dipole entrance x and theta are in the coordinate system whose origin is at the dipole c exit with x pointing outward (+delta gives +x) 30 degrees from perpendicular to the optic c axis (like the exit face of the dipole itself). This is typical of dent functions. c see the figure at: http://hallaweb.jlab.org/news/minutes/g2p/dipole_coords.JPG function x_lm_fp (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 91) data ncoeff/ 90/ data avdat/ -0.5415396E-01/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.24057E-01,-0.48605E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.61152268E-01,-0.56526884E-01,-0.57909529E-04,-0.84979642E-04, + 0.55575264E+00, 0.43920346E-01,-0.41965563E-01, 0.13960838E-01, + -0.24565769E-01,-0.30734728E-02,-0.18153868E-02, 0.15889872E-01, + -0.23424970E-02,-0.43792287E-02, 0.45366231E-02,-0.72808298E-02, + -0.10531140E-02, 0.21043497E-02, 0.42747037E-03,-0.38144938E-03, + -0.38429405E-03, 0.57632178E-02, 0.72847545E-03,-0.30538242E-02, + -0.10069262E-02,-0.26579138E-02,-0.59799817E-02,-0.46129660E-02, + -0.22232856E-02,-0.60841446E-02,-0.10327377E-02, 0.80203067E-03, + 0.21526106E-02, 0.10545378E-04, 0.35389494E-02,-0.22442121E-03, + -0.21941497E-02, 0.26005723E-02,-0.18609562E-02,-0.13409483E-02, + 0.14833225E-02,-0.61789347E-03,-0.64039219E-03,-0.19083048E-02, + 0.11869399E-01, 0.94443996E-03,-0.79278165E-04,-0.55912272E-02, + 0.33651263E-03, 0.36561289E-02,-0.80025427E-04, 0.25785004E-04, + -0.68402902E-03,-0.98380214E-03,-0.76674105E-03, 0.10618245E-02, + 0.11730153E-03,-0.30905856E-02,-0.11726515E-02, 0.19198059E-03, + 0.21034271E-03, 0.42937365E-02,-0.20828820E-02,-0.67983306E-03, + 0.25451046E-02,-0.26076127E-03, 0.23957854E-02,-0.12330536E-02, + -0.85037136E-04,-0.12195125E-02,-0.15867135E-03, 0.18015962E-03, + -0.21574742E-03, 0.30273522E-03,-0.14993652E-03,-0.36569667E-03, + 0.14205674E-03,-0.80087734E-03, 0.71795665E-04, 0.10117349E-02, + -0.21849477E-03,-0.12907786E-03,-0.59057720E-03, 0.13295344E-03, + 0.13075069E-03, 0.12854086E-02, 0.12486728E-02,-0.38175427E-03, + -0.25564597E-02, 0.88898065E-04, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x24 = x23*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x34 = x33*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x44 = x43*x4 x51 = x5 x52 = x51*x5 x53 = x52*x5 x54 = x53*x5 c c function c x_lm_fp =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x31 4 +coeff( 4) *x41 5 +coeff( 5) *x51 6 +coeff( 6) *x21 *x51 7 +coeff( 7) *x52 8 +coeff( 8) *x22 x_lm_fp =x_lm_fp 9 +coeff( 9) *x21 *x42 1 +coeff( 10) *x31*x41 2 +coeff( 11)*x11 3 +coeff( 12) *x22 *x42 4 +coeff( 13) *x22 *x53 5 +coeff( 14) *x21*x31*x41 6 +coeff( 15) *x53 7 +coeff( 16) *x24 8 +coeff( 17) *x21 *x41 x_lm_fp =x_lm_fp 9 +coeff( 18) *x23 1 +coeff( 19) *x21 *x52 2 +coeff( 20) *x32 3 +coeff( 21) *x21*x32 4 +coeff( 22) *x22 *x51 5 +coeff( 23) *x31*x41*x51 6 +coeff( 24) *x23 *x51 7 +coeff( 25) *x21*x31*x41*x51 8 +coeff( 26) *x22 *x52 x_lm_fp =x_lm_fp 9 +coeff( 27) *x24 *x51 1 +coeff( 28) *x23 *x52 2 +coeff( 29) *x42*x53 3 +coeff( 30) *x24 *x42*x51 4 +coeff( 31) *x42 5 +coeff( 32) *x22 *x41 6 +coeff( 33) *x22*x31*x41 7 +coeff( 34)*x11*x21 8 +coeff( 35) *x23 *x42 x_lm_fp =x_lm_fp 9 +coeff( 36)*x11 *x51 1 +coeff( 37) *x22 *x42*x53 2 +coeff( 38) *x22*x31*x43*x53 3 +coeff( 39) *x42*x51 4 +coeff( 40) *x44 5 +coeff( 41) *x21 *x42*x51 6 +coeff( 42) *x21 *x53 7 +coeff( 43) *x54 8 +coeff( 44) *x21 *x44 x_lm_fp =x_lm_fp 9 +coeff( 45) *x22 *x42*x51 1 +coeff( 46) *x21*x31*x41*x52 2 +coeff( 47)*x11*x22 3 +coeff( 48) *x24 *x42 4 +coeff( 49)*x11*x23 5 +coeff( 50) *x24 *x42*x53 6 +coeff( 51) *x21*x31 7 +coeff( 52) *x32 *x51 8 +coeff( 53) *x31*x41*x52 x_lm_fp =x_lm_fp 9 +coeff( 54) *x42*x52 1 +coeff( 55) *x23*x31*x41 2 +coeff( 56) *x22*x31*x41*x51 3 +coeff( 57) *x31*x43*x51 4 +coeff( 58) *x44*x51 5 +coeff( 59) *x21 *x54 6 +coeff( 60) *x24*x32 7 +coeff( 61)*x11 *x42 8 +coeff( 62) *x22 *x44 x_lm_fp =x_lm_fp 9 +coeff( 63) *x23 *x42*x51 1 +coeff( 64) *x24 *x52 2 +coeff( 65) *x22 *x42*x52 3 +coeff( 66)*x11*x21 *x42 4 +coeff( 67) *x22 *x44*x51 5 +coeff( 68) *x23*x31*x43*x51 6 +coeff( 69) *x34*x41*x53 7 +coeff( 70) *x44*x54 8 +coeff( 71) *x41*x51 x_lm_fp =x_lm_fp 9 +coeff( 72) *x23 *x41 1 +coeff( 73) *x31*x43 2 +coeff( 74) *x22 *x41*x51 3 +coeff( 75) *x23*x32 4 +coeff( 76) *x24 *x41 5 +coeff( 77) *x22*x32 *x51 6 +coeff( 78) *x24*x31*x41 7 +coeff( 79)*x11 *x52 8 +coeff( 80) *x22*x31*x41*x52 x_lm_fp =x_lm_fp 9 +coeff( 81) *x23 *x53 1 +coeff( 82) *x21*x32 *x53 2 +coeff( 83) *x23*x32*x42 3 +coeff( 84)*x11*x22 *x51 4 +coeff( 85)*x11*x21 *x52 5 +coeff( 86) *x24 *x53 6 +coeff( 87) *x23 *x54 7 +coeff( 88) *x22*x33*x43 8 +coeff( 89) *x24 *x44 x_lm_fp =x_lm_fp 9 +coeff( 90)*x11*x23 *x51 c return end function t_lm_fp (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 17) data ncoeff/ 16/ data avdat/ -0.1158309E-01/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.24057E-01,-0.48605E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.12469223E-01,-0.36655936E-01,-0.11025265E-04, 0.19801026E-04, + 0.89652516E-01, 0.33808665E-02,-0.81776241E-02,-0.36451789E-02, + -0.59394911E-03, 0.60111098E-03, 0.16663474E-03, 0.53031277E-03, + -0.36452798E-03, 0.58436085E-03,-0.98630541E-03, 0.20551842E-02, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x21 = x2 x22 = x21*x2 x23 = x22*x2 x24 = x23*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x44 = x43*x4 x51 = x5 x52 = x51*x5 x53 = x52*x5 c c function c t_lm_fp =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x31 4 +coeff( 4) *x41 5 +coeff( 5) *x51 6 +coeff( 6) *x21 *x51 7 +coeff( 7) *x52 8 +coeff( 8) *x21 *x42 t_lm_fp =t_lm_fp 9 +coeff( 9) *x33*x41 1 +coeff( 10) *x44 2 +coeff( 11) *x22 3 +coeff( 12) *x23 4 +coeff( 13) *x21*x31*x41 5 +coeff( 14) *x53 6 +coeff( 15) *x24 7 +coeff( 16) *x22 *x42 c return end function y_lm_fp (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 52) data ncoeff/ 51/ data avdat/ -0.8132035E-03/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.24057E-01,-0.48605E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.13831098E-02,-0.89146355E-02, 0.27851690E-01, 0.69574872E-03, + 0.13444930E-04,-0.20181685E-03,-0.43924851E-02,-0.17202338E-01, + 0.30687179E-02, 0.36326304E-01,-0.38966074E-03,-0.22683314E-03, + -0.75870572E-03,-0.29395178E-02, 0.11544942E-03,-0.73397482E-05, + -0.26823913E-02,-0.20731216E-01,-0.11109614E-01, 0.10152245E-02, + 0.18855504E-03, 0.42527327E-02,-0.44510150E-02,-0.19205980E-04, + -0.29837686E-03,-0.13563678E-02,-0.26553273E-02,-0.12477771E-02, + 0.65006543E-03, 0.28261342E-02, 0.19691694E-02,-0.39975476E-02, + -0.19912552E-02, 0.10684992E-02, 0.37758323E-03,-0.57794095E-03, + -0.89872815E-03,-0.31400200E-02, 0.10727204E-02,-0.17876810E-02, + -0.14912343E-03,-0.62762127E-04,-0.15686093E-03, 0.39385413E-04, + -0.11264563E-03,-0.45798917E-03, 0.26830842E-03, 0.13152767E-03, + 0.91169123E-03, 0.59723610E-03, 0.10250671E-02, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x24 = x23*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x44 = x43*x4 x51 = x5 x52 = x51*x5 x53 = x52*x5 x54 = x53*x5 c c function c y_lm_fp =avdat 1 +coeff( 1) 2 +coeff( 2) *x31 3 +coeff( 3) *x41 4 +coeff( 4) *x51 5 +coeff( 5) *x32 6 +coeff( 6) *x42 7 +coeff( 7) *x21*x31 8 +coeff( 8) *x21 *x41 y_lm_fp =y_lm_fp 9 +coeff( 9) *x31 *x51 1 +coeff( 10) *x41*x51 2 +coeff( 11) *x22 3 +coeff( 12) *x21 *x51 4 +coeff( 13) *x31*x42 5 +coeff( 14) *x43 6 +coeff( 15) *x21 *x42 7 +coeff( 16) *x31*x41*x51 8 +coeff( 17) *x22*x31 y_lm_fp =y_lm_fp 9 +coeff( 18) *x22 *x41 1 +coeff( 19) *x21 *x41*x51 2 +coeff( 20) *x31 *x52 3 +coeff( 21) *x41*x52 4 +coeff( 22) *x23 *x41 5 +coeff( 23) *x22 *x41*x51 6 +coeff( 24) *x21*x33 *x51 7 +coeff( 25) *x21 8 +coeff( 26) *x21*x31 *x51 y_lm_fp =y_lm_fp 9 +coeff( 27) *x43*x51 1 +coeff( 28) *x22*x31 *x51 2 +coeff( 29) *x21 *x41*x52 3 +coeff( 30) *x23 *x41*x51 4 +coeff( 31) *x22 *x41*x52 5 +coeff( 32) *x41*x54 6 +coeff( 33) *x21 *x43*x53 7 +coeff( 34) *x21 *x43 8 +coeff( 35)*x11*x21 *x41 y_lm_fp =y_lm_fp 9 +coeff( 36) *x31 *x53 1 +coeff( 37) *x41*x53 2 +coeff( 38) *x43*x52 3 +coeff( 39) *x24 *x41 4 +coeff( 40) *x21 *x41*x53 5 +coeff( 41) *x22*x32*x43 6 +coeff( 42) *x52 7 +coeff( 43) *x32*x41 8 +coeff( 44)*x11 *x31 y_lm_fp =y_lm_fp 9 +coeff( 45) *x22 *x51 1 +coeff( 46) *x31*x42*x51 2 +coeff( 47) *x23*x31 3 +coeff( 48)*x11 *x41*x51 4 +coeff( 49) *x21*x31*x42*x51 5 +coeff( 50) *x21*x31*x44 6 +coeff( 51) *x22*x31*x42*x52 c return end function p_lm_fp (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 22) data ncoeff/ 21/ data avdat/ 0.9997183E-03/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.24057E-01,-0.48605E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + -0.20147741E-02, 0.29766708E-03,-0.14671579E-02,-0.50688401E-01, + 0.15279272E-01,-0.22213976E-02,-0.48582526E-02, 0.60109445E-02, + -0.27023169E-03, 0.25558558E-02, 0.15617425E-02,-0.10525103E-03, + 0.69807231E-03, 0.39118758E-03, 0.46957924E-03, 0.12037336E-03, + -0.16105257E-03,-0.21025335E-03,-0.90413191E-03,-0.42503333E-03, + -0.44271091E-03, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x31 = x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x51 = x5 x52 = x51*x5 c c function c p_lm_fp =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x31 4 +coeff( 4) *x41 5 +coeff( 5) *x21 *x41 6 +coeff( 6) *x31 *x51 7 +coeff( 7) *x41*x51 8 +coeff( 8) *x22 *x41 p_lm_fp =p_lm_fp 9 +coeff( 9) *x23*x31 1 +coeff( 10) *x21*x31 2 +coeff( 11) *x22*x31 3 +coeff( 12) *x51 4 +coeff( 13) *x31*x42 5 +coeff( 14) *x43 6 +coeff( 15) *x31 *x52 7 +coeff( 16) *x22 8 +coeff( 17)*x11 *x41 p_lm_fp =p_lm_fp 9 +coeff( 18) *x21 *x41*x51 1 +coeff( 19) *x23 *x41 2 +coeff( 20) *x21*x31*x42 3 +coeff( 21) *x22 *x41*x51 c return end function l_lm_fp (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 10) data ncoeff/ 9/ data avdat/ -0.3759167E-01/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.24057E-01,-0.48605E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.36156062E-01,-0.30996361E+00,-0.30916817E-01,-0.35213411E-01, + -0.17274685E-01, 0.31797227E-02,-0.48669223E-02,-0.81195580E-02, + 0.10217958E-01, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x41 = x4 x42 = x41*x4 x51 = x5 x52 = x51*x5 c c function c l_lm_fp =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x51 4 +coeff( 4) *x22 5 +coeff( 5) *x52 6 +coeff( 6)*x11 7 +coeff( 7) *x21 *x51 8 +coeff( 8) *x42 l_lm_fp =l_lm_fp 9 +coeff( 9) *x21 *x42 c return end function x_lm_q3ex (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 91) data ncoeff/ 90/ data avdat/ -0.2072053E-01/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.24057E-01,-0.48605E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.25307413E-01, 0.48539910E-01,-0.31025105E-04,-0.10433911E-03, + 0.29763651E+00, 0.33366352E-01,-0.18893292E-01, 0.12802833E-01, + -0.12662685E-01,-0.17307276E-02,-0.18361934E-02,-0.24374765E-02, + -0.13172420E-02,-0.38690884E-02,-0.20827501E-03,-0.49033243E-03, + 0.20722281E-02, 0.93701864E-02,-0.38096739E-04,-0.32008273E-03, + -0.22860151E-02, 0.11272432E-02,-0.20693887E-03, 0.38715682E-02, + -0.31230941E-02,-0.32142893E-03,-0.19885741E-03,-0.13812210E-04, + 0.20531181E-03, 0.62048720E-03, 0.12998861E-02,-0.13316071E-02, + -0.50770008E-03,-0.10899514E-02,-0.15038501E-02,-0.10630169E-02, + -0.11270356E-03, 0.54279943E-02,-0.23444129E-04,-0.91481220E-03, + -0.21748161E-02,-0.32714335E-03,-0.41791601E-02,-0.60750437E-04, + 0.42765084E-03,-0.10203188E-02,-0.74560819E-04,-0.17230106E-03, + -0.37771440E-03,-0.27695813E-03,-0.73334452E-03, 0.86677133E-03, + 0.84181887E-03,-0.75474964E-04,-0.21860246E-02,-0.29401499E-03, + -0.52602252E-03, 0.10180679E-03, 0.33482251E-03, 0.14546368E-03, + -0.63030166E-03, 0.52657479E-03, 0.96261298E-03, 0.17026196E-03, + -0.52429526E-03,-0.24585366E-04,-0.67084067E-04,-0.73387113E-04, + -0.11846991E-03, 0.16237643E-03,-0.23228112E-03,-0.98158460E-04, + -0.41252184E-04, 0.29030902E-03,-0.48573120E-03,-0.43886053E-03, + -0.25039333E-04,-0.17395227E-03,-0.87669956E-04,-0.49120554E-03, + 0.53290674E-03, 0.75301854E-04,-0.50653081E-04,-0.50505441E-04, + -0.15961826E-03, 0.58067948E-04,-0.46564263E-03,-0.21370254E-03, + 0.64700888E-03,-0.50255541E-04, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x24 = x23*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x44 = x43*x4 x51 = x5 x52 = x51*x5 x53 = x52*x5 x54 = x53*x5 c c function c x_lm_q3ex =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x31 4 +coeff( 4) *x41 5 +coeff( 5) *x51 6 +coeff( 6) *x21 *x51 7 +coeff( 7) *x52 8 +coeff( 8) *x22 x_lm_q3ex =x_lm_q3ex 9 +coeff( 9) *x21 *x42 1 +coeff( 10)*x11 2 +coeff( 11) *x31*x41 3 +coeff( 12) *x21*x31*x41 4 +coeff( 13) *x22 *x53 5 +coeff( 14) *x24 6 +coeff( 15) *x23 *x42 7 +coeff( 16) *x21 *x41 8 +coeff( 17) *x53 x_lm_q3ex =x_lm_q3ex 9 +coeff( 18) *x22 *x42 1 +coeff( 19) *x32*x42 2 +coeff( 20) *x44 3 +coeff( 21) *x42 4 +coeff( 22) *x23 5 +coeff( 23) *x21*x32 6 +coeff( 24) *x22 *x51 7 +coeff( 25) *x24 *x51 8 +coeff( 26) *x24 *x52 x_lm_q3ex =x_lm_q3ex 9 +coeff( 27) *x32 1 +coeff( 28) *x21*x31 *x51 2 +coeff( 29) *x31*x41*x51 3 +coeff( 30) *x21 *x52 4 +coeff( 31) *x22*x31*x41 5 +coeff( 32) *x23 *x51 6 +coeff( 33) *x21*x31*x41*x51 7 +coeff( 34) *x22 *x52 8 +coeff( 35) *x23*x31*x41 x_lm_q3ex =x_lm_q3ex 9 +coeff( 36) *x21 *x44 1 +coeff( 37)*x11 *x51 2 +coeff( 38) *x22 *x42*x51 3 +coeff( 39) *x32*x42*x51 4 +coeff( 40) *x44*x51 5 +coeff( 41) *x23 *x52 6 +coeff( 42) *x42*x53 7 +coeff( 43) *x24 *x42 8 +coeff( 44) *x21*x31 x_lm_q3ex =x_lm_q3ex 9 +coeff( 45) *x22 *x41 1 +coeff( 46) *x42*x51 2 +coeff( 47) *x31*x43 3 +coeff( 48) *x31*x41*x52 4 +coeff( 49) *x21 *x53 5 +coeff( 50) *x54 6 +coeff( 51) *x21*x31*x43 7 +coeff( 52) *x22*x31*x41*x51 8 +coeff( 53) *x21 *x42*x52 x_lm_q3ex =x_lm_q3ex 9 +coeff( 54)*x11*x22 1 +coeff( 55) *x24 *x42*x51 2 +coeff( 56) *x23*x32 3 +coeff( 57) *x21*x32*x42 4 +coeff( 58) *x22*x32 *x51 5 +coeff( 59) *x21*x31*x41*x52 6 +coeff( 60) *x24*x32 7 +coeff( 61) *x24*x31*x41 8 +coeff( 62) *x22 *x42*x52 x_lm_q3ex =x_lm_q3ex 9 +coeff( 63) *x24 *x53 1 +coeff( 64)*x11 *x42*x52 2 +coeff( 65) *x44*x54 3 +coeff( 66)*x11*x21 *x42*x52 4 +coeff( 67) *x41*x51 5 +coeff( 68) *x22*x32 6 +coeff( 69) *x21 *x43 7 +coeff( 70) *x22 *x41*x51 8 +coeff( 71) *x24 *x41 x_lm_q3ex =x_lm_q3ex 9 +coeff( 72) *x21*x33*x41 1 +coeff( 73) *x33*x42 2 +coeff( 74) *x21*x31*x42*x51 3 +coeff( 75) *x21 *x54 4 +coeff( 76) *x22*x31*x43 5 +coeff( 77) *x24*x31 *x51 6 +coeff( 78) *x23*x31*x41*x51 7 +coeff( 79) *x22*x32*x41*x51 8 +coeff( 80) *x23 *x42*x51 x_lm_q3ex =x_lm_q3ex 9 +coeff( 81) *x21 *x44*x51 1 +coeff( 82)*x11*x23 2 +coeff( 83)*x11*x21*x32 3 +coeff( 84)*x11*x21*x31*x41 4 +coeff( 85)*x11*x21 *x42 5 +coeff( 86)*x11*x22 *x51 6 +coeff( 87) *x24*x31*x41*x51 7 +coeff( 88) *x21*x33*x42*x51 8 +coeff( 89) *x23 *x54 x_lm_q3ex =x_lm_q3ex 9 +coeff( 90)*x11*x21*x32*x41 c return end function t_lm_q3ex (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 17) data ncoeff/ 16/ data avdat/ -0.1158322E-01/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.24057E-01,-0.48605E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.12469501E-01,-0.36655784E-01,-0.10991054E-04, 0.19735033E-04, + 0.89652352E-01, 0.33808323E-02,-0.81778392E-02,-0.36433446E-02, + -0.59385644E-03, 0.59799780E-03, 0.16676378E-03, 0.53012214E-03, + -0.36440027E-03, 0.58662583E-03,-0.98664581E-03, 0.20563276E-02, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x21 = x2 x22 = x21*x2 x23 = x22*x2 x24 = x23*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x44 = x43*x4 x51 = x5 x52 = x51*x5 x53 = x52*x5 c c function c t_lm_q3ex =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x31 4 +coeff( 4) *x41 5 +coeff( 5) *x51 6 +coeff( 6) *x21 *x51 7 +coeff( 7) *x52 8 +coeff( 8) *x21 *x42 t_lm_q3ex =t_lm_q3ex 9 +coeff( 9) *x33*x41 1 +coeff( 10) *x44 2 +coeff( 11) *x22 3 +coeff( 12) *x23 4 +coeff( 13) *x21*x31*x41 5 +coeff( 14) *x53 6 +coeff( 15) *x24 7 +coeff( 16) *x22 *x42 c return end function y_lm_q3ex (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 27) data ncoeff/ 26/ data avdat/ -0.3689669E-02/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.24057E-01,-0.48605E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.71116597E-02,-0.48388829E-02, 0.17383529E+00,-0.11462025E-01, + -0.60301863E-01, 0.87208105E-02, 0.49082287E-01,-0.17667311E-04, + -0.36660958E-01,-0.10696000E-01,-0.19079953E-03,-0.11183618E-02, + 0.96836296E-03,-0.34909819E-04,-0.37522737E-02,-0.67905765E-02, + -0.29899797E-02, 0.58637159E-02,-0.65307802E-03,-0.24924001E-02, + -0.13807489E-02,-0.36321417E-02,-0.82058460E-03, 0.43982774E-03, + 0.10418684E-02, 0.55982044E-03, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x51 = x5 x52 = x51*x5 c c function c y_lm_q3ex =avdat 1 +coeff( 1) 2 +coeff( 2) *x31 3 +coeff( 3) *x41 4 +coeff( 4) *x21*x31 5 +coeff( 5) *x21 *x41 6 +coeff( 6) *x31 *x51 7 +coeff( 7) *x41*x51 8 +coeff( 8) *x21*x32 y_lm_q3ex =y_lm_q3ex 9 +coeff( 9) *x22 *x41 1 +coeff( 10) *x21 *x41*x51 2 +coeff( 11) *x22*x33 3 +coeff( 12) *x21 4 +coeff( 13) *x51 5 +coeff( 14) *x33 6 +coeff( 15) *x43 7 +coeff( 16) *x22*x31 8 +coeff( 17) *x41*x52 y_lm_q3ex =y_lm_q3ex 9 +coeff( 18) *x23 *x41 1 +coeff( 19) *x22 2 +coeff( 20) *x31*x42 3 +coeff( 21) *x21*x31 *x51 4 +coeff( 22) *x22 *x41*x51 5 +coeff( 23) *x32*x41 6 +coeff( 24)*x11 *x41 7 +coeff( 25) *x23*x31 8 +coeff( 26)*x11*x21 *x41 c return end function p_lm_q3ex (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 22) data ncoeff/ 21/ data avdat/ 0.9996260E-03/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.24057E-01,-0.48605E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + -0.20146493E-02, 0.29777951E-03,-0.14668435E-02,-0.50685767E-01, + 0.15277427E-01,-0.22207720E-02,-0.48589921E-02, 0.60080346E-02, + -0.26986859E-03, 0.25551289E-02, 0.15618667E-02,-0.10523954E-03, + 0.69766818E-03, 0.39258733E-03, 0.46803258E-03, 0.12027180E-03, + -0.16078124E-03,-0.21283918E-03,-0.90302282E-03,-0.42380995E-03, + -0.44537050E-03, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x31 = x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x51 = x5 x52 = x51*x5 c c function c p_lm_q3ex =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x31 4 +coeff( 4) *x41 5 +coeff( 5) *x21 *x41 6 +coeff( 6) *x31 *x51 7 +coeff( 7) *x41*x51 8 +coeff( 8) *x22 *x41 p_lm_q3ex =p_lm_q3ex 9 +coeff( 9) *x23*x31 1 +coeff( 10) *x21*x31 2 +coeff( 11) *x22*x31 3 +coeff( 12) *x51 4 +coeff( 13) *x31*x42 5 +coeff( 14) *x43 6 +coeff( 15) *x31 *x52 7 +coeff( 16) *x22 8 +coeff( 17)*x11 *x41 p_lm_q3ex =p_lm_q3ex 9 +coeff( 18) *x21 *x41*x51 1 +coeff( 19) *x23 *x41 2 +coeff( 20) *x21*x31*x42 3 +coeff( 21) *x22 *x41*x51 c return end function l_lm_q3ex (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 8) data ncoeff/ 7/ data avdat/ -0.3237712E-01/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.24057E-01,-0.48605E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.30044172E-01,-0.30826840E+00,-0.31695299E-01,-0.32675937E-01, + -0.15122359E-01, 0.31152717E-02,-0.54650055E-02, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x51 = x5 x52 = x51*x5 c c function c l_lm_q3ex =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x51 4 +coeff( 4) *x22 5 +coeff( 5) *x21 *x51 6 +coeff( 6)*x11 7 +coeff( 7) *x52 c return end function x_lm_q3en (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 91) data ncoeff/ 90/ data avdat/ 0.3483866E-02/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.27668E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + -0.12354727E-02, 0.21105893E+00, 0.61754108E-04, 0.13850728E+00, + 0.18858271E-01, 0.36398076E-01,-0.58336155E-02,-0.26537799E-02, + -0.54740617E-02,-0.47333795E-02,-0.13058472E-02,-0.14634226E-02, + 0.29848567E-02, 0.53398672E-03, 0.50258805E-03,-0.18443799E-02, + -0.22961012E-03,-0.15590757E-02, 0.17050671E-03, 0.42801086E-03, + -0.30084199E-03,-0.57159588E-02,-0.19593272E-03, 0.35523548E-03, + -0.36359953E-02, 0.75994220E-04,-0.12251239E-03, 0.13335056E-03, + 0.73144771E-03, 0.56310499E-03, 0.28404654E-02, 0.17394492E-03, + -0.28398733E-02,-0.27630534E-02,-0.31722193E-04, 0.18948817E-02, + -0.12812273E-03,-0.14736062E-02,-0.58311218E-03,-0.12048015E-02, + -0.26487457E-03,-0.24352073E-03, 0.46373348E-03, 0.52687991E-03, + -0.44370268E-03,-0.10540504E-02,-0.58216380E-03, 0.21509225E-03, + -0.10735399E-04,-0.10037120E-03,-0.15095016E-03,-0.83732455E-04, + -0.18888686E-03, 0.18189347E-04,-0.34333294E-03, 0.11833984E-03, + -0.55807061E-03,-0.10434839E-03, 0.22271084E-04,-0.41657797E-04, + 0.34837893E-04, 0.46488032E-03, 0.37997866E-04,-0.30218291E-04, + -0.76374105E-04,-0.93082263E-05,-0.25887499E-04, 0.14314920E-04, + 0.14344350E-03, 0.24442232E-03,-0.32934782E-04, 0.21803514E-02, + 0.42996944E-04,-0.70538110E-04, 0.15591313E-03,-0.95627554E-04, + -0.28532752E-03, 0.39107152E-03, 0.27643095E-03, 0.58659678E-03, + 0.17087690E-03, 0.14365788E-03,-0.62091177E-03,-0.34113189E-02, + 0.10899445E-03,-0.13509185E-03,-0.12851642E-03, 0.14358925E-03, + 0.22858717E-03, 0.47859675E-03, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x24 = x23*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x34 = x33*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x44 = x43*x4 x51 = x5 x52 = x51*x5 x53 = x52*x5 x54 = x53*x5 c c function c x_lm_q3en =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x31 4 +coeff( 4) *x51 5 +coeff( 5) *x22 6 +coeff( 6) *x21 *x51 7 +coeff( 7) *x52 8 +coeff( 8)*x11 x_lm_q3en =x_lm_q3en 9 +coeff( 9) *x42 1 +coeff( 10) *x21 *x42 2 +coeff( 11) *x31*x41 3 +coeff( 12) *x21*x31*x41 4 +coeff( 13) *x22 *x51 5 +coeff( 14) *x41 6 +coeff( 15) *x21 *x41 7 +coeff( 16) *x24 8 +coeff( 17) *x21*x32 x_lm_q3en =x_lm_q3en 9 +coeff( 18) *x42*x51 1 +coeff( 19) *x23*x31 2 +coeff( 20) *x23 *x51 3 +coeff( 21)*x11*x21 4 +coeff( 22) *x23 *x42 5 +coeff( 23) *x21 *x52 6 +coeff( 24) *x53 7 +coeff( 25) *x23*x31*x41 8 +coeff( 26) *x21*x31 x_lm_q3en =x_lm_q3en 9 +coeff( 27) *x32 1 +coeff( 28) *x41*x51 2 +coeff( 29) *x23 3 +coeff( 30) *x23 *x41 4 +coeff( 31) *x22 *x42 5 +coeff( 32) *x21 *x42*x51 6 +coeff( 33) *x21*x31*x43 7 +coeff( 34) *x21 *x44 8 +coeff( 35) *x33*x41*x51 x_lm_q3en =x_lm_q3en 9 +coeff( 36) *x22 *x42*x51 1 +coeff( 37)*x11*x22 2 +coeff( 38) *x24 *x42 3 +coeff( 39) *x23*x32*x42 4 +coeff( 40) *x24 *x42*x51 5 +coeff( 41) *x22 *x41 6 +coeff( 42) *x31*x41*x51 7 +coeff( 43) *x21*x31*x42 8 +coeff( 44) *x21 *x43 x_lm_q3en =x_lm_q3en 9 +coeff( 45) *x23*x32 1 +coeff( 46) *x21*x32*x42 2 +coeff( 47) *x24 *x51 3 +coeff( 48) *x22*x31*x41*x51 4 +coeff( 49) *x21*x32*x41 5 +coeff( 50) *x22 *x41*x51 6 +coeff( 51) *x22 *x52 7 +coeff( 52) *x21 *x53 8 +coeff( 53) *x21*x33*x41 x_lm_q3en =x_lm_q3en 9 +coeff( 54)*x11 *x51 1 +coeff( 55) *x23 *x52 2 +coeff( 56) *x21 *x42*x52 3 +coeff( 57) *x24*x31*x41 4 +coeff( 58) *x24*x32 *x51 5 +coeff( 59) *x21*x31 *x51 6 +coeff( 60) *x22*x32 7 +coeff( 61) *x21*x33 8 +coeff( 62) *x22*x31*x41 x_lm_q3en =x_lm_q3en 9 +coeff( 63) *x21*x32 *x51 1 +coeff( 64) *x21*x31 *x52 2 +coeff( 65) *x21 *x41*x52 3 +coeff( 66) *x42*x52 4 +coeff( 67) *x54 5 +coeff( 68) *x24*x31 6 +coeff( 69) *x24 *x41 7 +coeff( 70) *x23*x32*x41 8 +coeff( 71) *x22*x31*x43 x_lm_q3en =x_lm_q3en 9 +coeff( 72) *x22 *x44 1 +coeff( 73)*x11*x23 2 +coeff( 74)*x11*x21 *x42 3 +coeff( 75) *x21*x34*x42 4 +coeff( 76) *x23*x33 *x51 5 +coeff( 77) *x24*x31*x41*x51 6 +coeff( 78) *x22*x33*x41*x51 7 +coeff( 79) *x23*x31*x42*x51 8 +coeff( 80) *x23 *x42*x52 x_lm_q3en =x_lm_q3en 9 +coeff( 81) *x22*x31*x42*x52 1 +coeff( 82) *x23 *x54 2 +coeff( 83) *x24*x31*x43 3 +coeff( 84) *x24 *x44 4 +coeff( 85) *x21*x34*x41*x52 5 +coeff( 86) *x44*x54 6 +coeff( 87)*x11*x23*x31*x41 7 +coeff( 88)*x11*x21*x31*x43 8 +coeff( 89) *x24*x34 *x51 x_lm_q3en =x_lm_q3en 9 +coeff( 90) *x24 *x42*x53 c return end function t_lm_q3en (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 14) data ncoeff/ 13/ data avdat/ -0.9424038E-02/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.27668E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.86697014E-02,-0.76674134E-01, 0.22877010E-01,-0.47609224E-02, + -0.56456681E-02, 0.68147999E-03, 0.13619399E-02,-0.14661918E-02, + 0.87767816E-03,-0.17224305E-03, 0.76769298E-03,-0.41119428E-03, + 0.12512093E-02, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x31 = x3 x41 = x4 x42 = x41*x4 x51 = x5 x52 = x51*x5 c c function c t_lm_q3en =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x51 4 +coeff( 4) *x22 5 +coeff( 5) *x21 *x51 6 +coeff( 6)*x11 7 +coeff( 7) *x42 8 +coeff( 8) *x52 t_lm_q3en =t_lm_q3en 9 +coeff( 9) *x23 *x52 1 +coeff( 10) *x41 2 +coeff( 11) *x21*x31*x41 3 +coeff( 12) *x22 *x51 4 +coeff( 13) *x22 *x42 c return end function y_lm_q3en (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 32) data ncoeff/ 31/ data avdat/ -0.4912966E-02/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.27668E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + -0.60082888E-02, 0.81803458E-03, 0.22132754E+00, 0.37048492E-03, + -0.10878676E-01,-0.70552491E-01, 0.95019508E-02, 0.45109693E-01, + -0.76608907E-04,-0.91761911E-04,-0.35342500E-01,-0.81801731E-02, + -0.17821192E-03,-0.38080158E-04,-0.23439017E-03, 0.34961046E-02, + -0.21800722E-02, 0.17210845E-02,-0.20661306E-04,-0.68378802E-02, + -0.38330357E-02,-0.32753493E-02,-0.43495260E-02, 0.49133813E-02, + 0.62337593E-03,-0.90654497E-03, 0.67276636E-03,-0.12854667E-02, + -0.90743991E-03,-0.24269903E-02, 0.49049692E-03, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x51 = x5 x52 = x51*x5 x53 = x52*x5 c c function c y_lm_q3en =avdat 1 +coeff( 1) 2 +coeff( 2) *x31 3 +coeff( 3) *x41 4 +coeff( 4) *x31*x41 5 +coeff( 5) *x21*x31 6 +coeff( 6) *x21 *x41 7 +coeff( 7) *x31 *x51 8 +coeff( 8) *x41*x51 y_lm_q3en =y_lm_q3en 9 +coeff( 9) *x21*x32 1 +coeff( 10) *x32 *x51 2 +coeff( 11) *x22 *x41 3 +coeff( 12) *x21 *x41*x51 4 +coeff( 13) *x23 5 +coeff( 14) *x53 6 +coeff( 15) *x22*x33 7 +coeff( 16) *x21 8 +coeff( 17) *x51 y_lm_q3en =y_lm_q3en 9 +coeff( 18) *x22 1 +coeff( 19) *x33 2 +coeff( 20) *x22*x31 3 +coeff( 21) *x41*x52 4 +coeff( 22) *x31*x42 5 +coeff( 23) *x43 6 +coeff( 24) *x23 *x41 7 +coeff( 25) *x42 8 +coeff( 26) *x32*x41 y_lm_q3en =y_lm_q3en 9 +coeff( 27)*x11 *x41 1 +coeff( 28) *x21*x31 *x51 2 +coeff( 29) *x31 *x52 3 +coeff( 30) *x22 *x41*x51 4 +coeff( 31) *x23 *x51 c return end function p_lm_q3en (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 34) data ncoeff/ 33/ data avdat/ -0.7478998E-03/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.27668E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + -0.81101933E-03, 0.57001278E-03,-0.23001232E-02, 0.31615745E-01, + -0.24040989E-02,-0.12435142E-01, 0.10835092E-03, 0.18663227E-02, + 0.10694352E-01,-0.88401381E-02, 0.33465622E-04,-0.25142743E-02, + -0.81208695E-04,-0.53371547E-03, 0.43190151E-03,-0.14362308E-02, + -0.10458924E-02, 0.15930849E-02, 0.84830514E-04,-0.55686530E-03, + -0.24439284E-03,-0.60437236E-03,-0.37770026E-03, 0.14612892E-02, + 0.72623685E-03, 0.16151670E-03,-0.14912765E-03, 0.14812280E-03, + 0.12308365E-03, 0.11913767E-03,-0.21394122E-03,-0.41190584E-03, + 0.71357418E-03, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x24 = x23*x2 x31 = x3 x32 = x31*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x51 = x5 x52 = x51*x5 c c function c p_lm_q3en =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x31 4 +coeff( 4) *x41 5 +coeff( 5) *x21*x31 6 +coeff( 6) *x21 *x41 7 +coeff( 7) *x21 *x51 8 +coeff( 8) *x31 *x51 p_lm_q3en =p_lm_q3en 9 +coeff( 9) *x41*x51 1 +coeff( 10) *x22 *x41 2 +coeff( 11) *x22 *x51 3 +coeff( 12) *x21 *x41*x51 4 +coeff( 13) *x24*x31 5 +coeff( 14) *x51 6 +coeff( 15) *x22 7 +coeff( 16) *x22*x31 8 +coeff( 17) *x43 p_lm_q3en =p_lm_q3en 9 +coeff( 18) *x23 *x41 1 +coeff( 19)*x11 *x41 2 +coeff( 20) *x31*x42 3 +coeff( 21) *x21*x31 *x51 4 +coeff( 22) *x41*x52 5 +coeff( 23) *x22 *x41*x51 6 +coeff( 24) *x23 *x41*x51 7 +coeff( 25) *x23 *x41*x52 8 +coeff( 26) *x42 p_lm_q3en =p_lm_q3en 9 +coeff( 27) *x32*x41 1 +coeff( 28) *x23*x31 2 +coeff( 29)*x11*x21 *x41 3 +coeff( 30) *x22*x31*x41 4 +coeff( 31) *x22*x31 *x51 5 +coeff( 32) *x21 *x43*x51 6 +coeff( 33) *x22 *x41*x52 c return end function l_lm_q3en (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 7) data ncoeff/ 6/ data avdat/ -0.2636300E-01/ data xmin/ 1 -0.99984E-03,-0.64721E-01,-0.19971E-01,-0.27668E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.24649356E-01,-0.30751455E+00,-0.32492463E-01,-0.27808396E-01, + -0.23282740E-01, 0.30767957E-02, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x51 = x5 c c function c l_lm_q3en =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x51 4 +coeff( 4) *x22 5 +coeff( 5) *x21 *x51 6 +coeff( 6)*x11 c return end function x_lm_dext (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 84) data ncoeff/ 83/ data avdat/ 0.1657284E-01/ data xmin/ 1 -0.99984E-03,-0.65005E-01,-0.19971E-01,-0.27668E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + -0.15917601E-01, 0.33428055E+00, 0.13298850E+00, 0.46707768E-01, + 0.12151210E-01,-0.38441578E-02,-0.62617436E-02,-0.33858872E-02, + -0.19947430E-02,-0.38347610E-02, 0.59563946E-03, 0.41288370E-03, + -0.14619137E-02,-0.49745844E-03,-0.30048442E-03,-0.82729693E-03, + -0.19339250E-02,-0.94413403E-02, 0.68426576E-04,-0.13342714E-02, + -0.19669656E-03,-0.48333476E-02, 0.70238551E-04,-0.13171819E-03, + 0.94368489E-03, 0.16266217E-02, 0.62229612E-03, 0.40754466E-03, + -0.34080520E-02,-0.46044621E-02, 0.87436383E-04,-0.11242256E-02, + 0.10836364E-03,-0.33263175E-03, 0.11332442E-03, 0.26352194E-03, + 0.82511856E-03, 0.77487441E-03,-0.63930673E-03,-0.13750450E-02, + -0.11185960E-03,-0.15410493E-03,-0.58832371E-04,-0.88114270E-04, + 0.97073469E-04,-0.18413323E-03,-0.36638160E-03,-0.48340840E-03, + -0.10085374E-03, 0.11411394E-02, 0.44512566E-04, 0.49128288E-04, + 0.19184490E-05,-0.90460986E-03, 0.13421448E-03,-0.58353166E-02, + 0.23473869E-03, 0.61287465E-04, 0.50672359E-03, 0.52389256E-04, + -0.37300670E-04, 0.19676439E-03, 0.16991711E-03,-0.41209333E-03, + 0.22130043E-03,-0.76425989E-04, 0.34869006E-02,-0.14849385E-03, + -0.86507737E-03, 0.73560528E-04,-0.21474725E-02, 0.11206791E-02, + 0.45333829E-03,-0.42591154E-03,-0.19389969E-03, 0.74408838E-03, + 0.27363171E-03,-0.45590656E-03, 0.45547725E-03,-0.49158779E-03, + 0.11748498E-03, 0.70025068E-03,-0.11999618E-02, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x24 = x23*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x34 = x33*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x44 = x43*x4 x51 = x5 x52 = x51*x5 x53 = x52*x5 x54 = x53*x5 c c function c x_lm_dext =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x51 4 +coeff( 4) *x21 *x51 5 +coeff( 5) *x22 6 +coeff( 6)*x11 7 +coeff( 7) *x42 8 +coeff( 8) *x52 x_lm_dext =x_lm_dext 9 +coeff( 9) *x21*x31*x41 1 +coeff( 10) *x21 *x42 2 +coeff( 11) *x41 3 +coeff( 12) *x21 *x41 4 +coeff( 13) *x31*x41 5 +coeff( 14) *x23 6 +coeff( 15) *x21*x32 7 +coeff( 16) *x21 *x52 8 +coeff( 17) *x24 x_lm_dext =x_lm_dext 9 +coeff( 18) *x23 *x42 1 +coeff( 19) *x21*x31 2 +coeff( 20) *x42*x51 3 +coeff( 21)*x11*x21 4 +coeff( 22) *x23*x31*x41 5 +coeff( 23) *x31 6 +coeff( 24) *x32 7 +coeff( 25) *x23 *x41 8 +coeff( 26) *x22 *x42 x_lm_dext =x_lm_dext 9 +coeff( 27) *x23 *x51 1 +coeff( 28) *x21 *x42*x51 2 +coeff( 29) *x21*x31*x43 3 +coeff( 30) *x21 *x44 4 +coeff( 31)*x11 *x51 5 +coeff( 32) *x23*x32*x42 6 +coeff( 33) *x41*x51 7 +coeff( 34) *x31*x41*x51 8 +coeff( 35) *x53 x_lm_dext =x_lm_dext 9 +coeff( 36) *x23*x31 1 +coeff( 37) *x21*x31*x42 2 +coeff( 38) *x21 *x43 3 +coeff( 39) *x23*x32 4 +coeff( 40) *x21*x32*x42 5 +coeff( 41)*x11*x22 6 +coeff( 42) *x24 *x42 7 +coeff( 43) *x23*x31*x41*x51 8 +coeff( 44) *x22 *x41 x_lm_dext =x_lm_dext 9 +coeff( 45) *x21*x32*x41 1 +coeff( 46) *x22 *x52 2 +coeff( 47) *x21*x33*x41 3 +coeff( 48) *x24 *x51 4 +coeff( 49) *x22*x32 *x51 5 +coeff( 50) *x22 *x42*x51 6 +coeff( 51) *x22 *x53 7 +coeff( 52)*x11*x21 *x51 8 +coeff( 53) *x24*x31*x41*x51 x_lm_dext =x_lm_dext 9 +coeff( 54) *x24 *x42*x51 1 +coeff( 55)*x11*x22 *x42 2 +coeff( 56) *x24 *x44 3 +coeff( 57) *x22 *x51 4 +coeff( 58) *x21*x33 5 +coeff( 59) *x22*x31*x41 6 +coeff( 60) *x21*x32 *x51 7 +coeff( 61) *x22 *x41*x51 8 +coeff( 62) *x21*x31*x41*x51 x_lm_dext =x_lm_dext 9 +coeff( 63) *x21*x31*x42*x51 1 +coeff( 64) *x24*x31*x41 2 +coeff( 65) *x23*x32*x41 3 +coeff( 66) *x22*x33*x41 4 +coeff( 67) *x22 *x44 5 +coeff( 68) *x23 *x41*x52 6 +coeff( 69) *x21*x31*x42*x52 7 +coeff( 70)*x11*x23 8 +coeff( 71) *x23*x31*x43 x_lm_dext =x_lm_dext 9 +coeff( 72) *x23 *x44 1 +coeff( 73) *x22*x33*x41*x51 2 +coeff( 74)*x11*x22*x31*x41 3 +coeff( 75) *x24*x32*x41*x51 4 +coeff( 76) *x21*x31*x42*x54 5 +coeff( 77) *x24*x34 *x51 6 +coeff( 78) *x23*x33*x42*x51 7 +coeff( 79)*x11*x22*x33*x41 8 +coeff( 80)*x11*x24 *x42 x_lm_dext =x_lm_dext 9 +coeff( 81)*x11*x24*x32 *x52 1 +coeff( 82)*x11*x22*x31*x41*x54 2 +coeff( 83)*x11*x24*x33*x41*x54 c return end function t_lm_dext (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 17) data ncoeff/ 16/ data avdat/ 0.5247108E+00/ data xmin/ 1 -0.99984E-03,-0.65005E-01,-0.19971E-01,-0.27668E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.98795360E-02,-0.76407187E-01, 0.22773834E-01,-0.34093836E-02, + -0.44398215E-02,-0.46970607E-02, 0.67840394E-03,-0.11845483E-02, + 0.35088563E-02, 0.40155847E-03, 0.12797834E-02,-0.14731036E-02, + -0.37044156E-03,-0.30795130E-03, 0.45152081E-03, 0.12904104E-02, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x31 = x3 x41 = x4 x42 = x41*x4 x51 = x5 x52 = x51*x5 c c function c t_lm_dext =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x51 4 +coeff( 4) *x22 5 +coeff( 5) *x21 *x51 6 +coeff( 6) *x42 7 +coeff( 7)*x11 8 +coeff( 8) *x52 t_lm_dext =t_lm_dext 9 +coeff( 9) *x21 *x42 1 +coeff( 10) *x41 2 +coeff( 11) *x21*x31*x41 3 +coeff( 12) *x42*x51 4 +coeff( 13) *x21 *x41 5 +coeff( 14) *x22 *x51 6 +coeff( 15) *x21 *x52 7 +coeff( 16) *x22 *x42 c return end function y_lm_dext (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 30) data ncoeff/ 29/ data avdat/ -0.3728473E-02/ data xmin/ 1 -0.99984E-03,-0.65005E-01,-0.19971E-01,-0.27668E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + -0.56740362E-02, 0.31151460E-02, 0.19107053E+00,-0.91374470E-02, + -0.53205911E-01, 0.75679705E-02, 0.36879081E-01,-0.10802776E-03, + -0.71047049E-04,-0.28388502E-01,-0.17018910E-03, 0.21659558E-04, + -0.15207462E-03, 0.27001111E-02,-0.17981094E-02, 0.13948454E-02, + -0.21391621E-04,-0.58518592E-02,-0.43643760E-02, 0.60336030E-03, + -0.23141564E-02,-0.38429839E-02, 0.55922818E-03,-0.93612581E-03, + -0.69123961E-03,-0.26720571E-02, 0.59962744E-03, 0.22342256E-02, + -0.23680627E-02, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x44 = x43*x4 x51 = x5 x52 = x51*x5 x53 = x52*x5 c c function c y_lm_dext =avdat 1 +coeff( 1) 2 +coeff( 2) *x31 3 +coeff( 3) *x41 4 +coeff( 4) *x21*x31 5 +coeff( 5) *x21 *x41 6 +coeff( 6) *x31 *x51 7 +coeff( 7) *x41*x51 8 +coeff( 8) *x21*x32 y_lm_dext =y_lm_dext 9 +coeff( 9) *x32 *x51 1 +coeff( 10) *x22 *x41 2 +coeff( 11) *x23 3 +coeff( 12) *x53 4 +coeff( 13) *x22*x33 5 +coeff( 14) *x21 6 +coeff( 15) *x51 7 +coeff( 16) *x22 8 +coeff( 17) *x33 y_lm_dext =y_lm_dext 9 +coeff( 18) *x22*x31 1 +coeff( 19) *x21 *x41*x51 2 +coeff( 20) *x43*x52 3 +coeff( 21) *x31*x42 4 +coeff( 22) *x43 5 +coeff( 23)*x11 *x41 6 +coeff( 24) *x21*x31 *x51 7 +coeff( 25) *x31 *x52 8 +coeff( 26) *x41*x52 y_lm_dext =y_lm_dext 9 +coeff( 27) *x44 1 +coeff( 28) *x23 *x41 2 +coeff( 29) *x22 *x41*x51 c return end function p_lm_dext (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 35) data ncoeff/ 34/ data avdat/ -0.6274078E-03/ data xmin/ 1 -0.99984E-03,-0.65005E-01,-0.19971E-01,-0.27668E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + -0.62732550E-03, 0.66725677E-03,-0.27765979E-02, 0.25574507E-01, + -0.13482695E-01, 0.13654251E-03, 0.16617248E-02, 0.94719315E-02, + -0.12402907E-02,-0.80008702E-02,-0.52635983E-03, 0.55165452E-04, + -0.35324339E-02, 0.25571539E-03,-0.54610573E-05, 0.25507705E-04, + -0.47423501E-03, 0.38722641E-03,-0.21262937E-02, 0.18632336E-02, + -0.47140650E-03,-0.29306035E-03,-0.64689928E-03,-0.10537421E-02, + 0.13103166E-02, 0.97257209E-04, 0.66216552E-03, 0.55172099E-04, + 0.70189868E-04,-0.82967759E-04,-0.13267413E-03,-0.78147525E-04, + 0.10388607E-03,-0.15908999E-03, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x24 = x23*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x51 = x5 x52 = x51*x5 c c function c p_lm_dext =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x31 4 +coeff( 4) *x41 5 +coeff( 5) *x21 *x41 6 +coeff( 6) *x21 *x51 7 +coeff( 7) *x31 *x51 8 +coeff( 8) *x41*x51 p_lm_dext =p_lm_dext 9 +coeff( 9) *x22*x31 1 +coeff( 10) *x22 *x41 2 +coeff( 11) *x31*x42 3 +coeff( 12) *x22 *x51 4 +coeff( 13) *x21 *x41*x51 5 +coeff( 14) *x23*x31 6 +coeff( 15) *x21*x33 7 +coeff( 16) *x23*x33 8 +coeff( 17) *x51 p_lm_dext =p_lm_dext 9 +coeff( 18) *x22 1 +coeff( 19) *x21*x31 2 +coeff( 20) *x23 *x41 3 +coeff( 21) *x43 4 +coeff( 22) *x21*x31 *x51 5 +coeff( 23) *x41*x52 6 +coeff( 24) *x22 *x41*x51 7 +coeff( 25) *x23 *x41*x51 8 +coeff( 26)*x11 *x41 p_lm_dext =p_lm_dext 9 +coeff( 27) *x24 *x41*x52 1 +coeff( 28) *x31*x41 2 +coeff( 29) *x42 3 +coeff( 30) *x23 4 +coeff( 31) *x32*x41 5 +coeff( 32) *x31 *x52 6 +coeff( 33)*x11*x21 *x41 7 +coeff( 34) *x22*x31 *x51 c return end function l_lm_dext (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 7) data ncoeff/ 6/ data avdat/ -0.3839632E-01/ data xmin/ 1 -0.99984E-03,-0.65005E-01,-0.19971E-01,-0.27668E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99947E-03, 0.65048E-01, 0.19925E-01, 0.25045E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.38501065E-01,-0.47409254E+00,-0.99198952E-01,-0.30243071E-01, + -0.49286313E-01, 0.50282110E-02, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x51 = x5 c c function c l_lm_dext =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x51 4 +coeff( 4) *x22 5 +coeff( 5) *x21 *x51 6 +coeff( 6)*x11 c return end function x_lm_dent (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 84) data ncoeff/ 83/ data avdat/ -0.5101643E+01/ data xmin/ 1 -0.99984E-03,-0.65005E-01,-0.19978E-01,-0.28029E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99999E-03, 0.65048E-01, 0.19925E-01, 0.27110E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.15463416E-02,-0.12214330E+00,-0.77268486E-02, 0.35178172E-02, + 0.10567644E-02, 0.29545221E-02, 0.24920583E-03, 0.47610977E-03, + 0.59557799E-03,-0.20692058E-03, 0.93271234E-03, 0.63377095E-03, + 0.15780374E-02,-0.10496776E-03,-0.14469148E-05,-0.57039404E-04, + 0.28107237E-04,-0.73440788E-04,-0.28391628E-03,-0.28112190E-04, + -0.23485984E-04,-0.60157214E-04, 0.11844108E-02, 0.37384123E-03, + -0.24693506E-03,-0.11991197E-03,-0.16791296E-03, 0.23211265E-03, + 0.11027145E-03, 0.13066552E-02, 0.18005234E-04,-0.82849045E-04, + 0.62060353E-05, 0.30204272E-03, 0.11835894E-03, 0.62357872E-05, + -0.15364296E-04,-0.62850871E-04,-0.12699282E-03,-0.51902107E-05, + -0.13329370E-03,-0.22305396E-04, 0.47311513E-03, 0.55664375E-04, + -0.28319082E-04, 0.61129185E-05,-0.14352474E-03,-0.22714465E-04, + -0.17309231E-03, 0.58124979E-05,-0.13881431E-04,-0.56323326E-04, + -0.11358463E-03,-0.42934673E-04, 0.71959325E-05, 0.55239811E-05, + 0.89170200E-04, 0.71107629E-05,-0.91407383E-04, 0.39094157E-04, + 0.26252793E-03, 0.13269439E-04, 0.79862330E-04,-0.35803019E-04, + -0.12424010E-03, 0.18216518E-03,-0.17108831E-03, 0.15152661E-04, + 0.77533194E-04, 0.60541999E-04,-0.44232045E-03, 0.21388145E-03, + 0.10947962E-03,-0.14431373E-03, 0.12514688E-03,-0.23160930E-03, + 0.23415746E-03,-0.43999167E-04, 0.38072598E-03,-0.21144998E-03, + -0.12657061E-03, 0.26524346E-03,-0.30590236E-03, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x24 = x23*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x34 = x33*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x44 = x43*x4 x51 = x5 x52 = x51*x5 x53 = x52*x5 x54 = x53*x5 c c function c x_lm_dent =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x21 *x51 4 +coeff( 4) *x22 5 +coeff( 5)*x11 6 +coeff( 6) *x23 *x42 7 +coeff( 7) *x21*x31*x41 8 +coeff( 8) *x22 *x51 x_lm_dent =x_lm_dent 9 +coeff( 9) *x21 *x52 1 +coeff( 10) *x42 2 +coeff( 11) *x23 3 +coeff( 12) *x21 *x42 4 +coeff( 13) *x23*x31*x41 5 +coeff( 14)*x11 *x51 6 +coeff( 15) *x21 *x41 7 +coeff( 16) *x31*x41 8 +coeff( 17) *x21*x32 x_lm_dent =x_lm_dent 9 +coeff( 18)*x11*x21 1 +coeff( 19) *x23 *x42*x51 2 +coeff( 20) *x51 3 +coeff( 21) *x21*x31 4 +coeff( 22) *x21*x31*x41*x51 5 +coeff( 23) *x21 *x44 6 +coeff( 24) *x23*x31*x43 7 +coeff( 25) *x23*x34*x42 8 +coeff( 26) *x23 *x41 x_lm_dent =x_lm_dent 9 +coeff( 27) *x22 *x42 1 +coeff( 28) *x23*x32 2 +coeff( 29) *x21*x33*x41 3 +coeff( 30) *x21*x31*x43 4 +coeff( 31)*x11*x22 5 +coeff( 32) *x24*x31*x41 6 +coeff( 33) *x23 *x53 7 +coeff( 34) *x23*x32*x42 8 +coeff( 35) *x21*x34*x42 x_lm_dent =x_lm_dent 9 +coeff( 36) *x41 1 +coeff( 37) *x24 2 +coeff( 38) *x22*x31*x41 3 +coeff( 39) *x21 *x43 4 +coeff( 40) *x21*x32 *x51 5 +coeff( 41) *x21 *x42*x51 6 +coeff( 42) *x22 *x52 7 +coeff( 43) *x21*x32*x42 8 +coeff( 44) *x21 *x42*x52 x_lm_dent =x_lm_dent 9 +coeff( 45) *x24*x32 1 +coeff( 46)*x11 *x42 2 +coeff( 47) *x23*x31*x42 3 +coeff( 48) *x23*x32 *x51 4 +coeff( 49) *x23*x31*x41*x51 5 +coeff( 50) *x41*x51 6 +coeff( 51) *x42*x51 7 +coeff( 52) *x21*x32*x41 8 +coeff( 53) *x23 *x51 x_lm_dent =x_lm_dent 9 +coeff( 54) *x21 *x53 1 +coeff( 55) *x33*x42 2 +coeff( 56)*x11 *x31*x41 3 +coeff( 57) *x21*x32*x43 4 +coeff( 58)*x11 *x52 5 +coeff( 59) *x22*x31*x41*x52 6 +coeff( 60) *x24 *x43 7 +coeff( 61) *x23 *x44 8 +coeff( 62)*x11*x22 *x42 x_lm_dent =x_lm_dent 9 +coeff( 63) *x24*x32*x41*x51 1 +coeff( 64)*x11*x21 *x42*x51 2 +coeff( 65) *x22*x32*x43*x51 3 +coeff( 66) *x24*x31*x41*x52 4 +coeff( 67) *x21*x31*x43*x53 5 +coeff( 68) *x23 *x41*x54 6 +coeff( 69) *x24*x33*x42 7 +coeff( 70)*x11*x22 *x42*x51 8 +coeff( 71) *x23*x31*x43*x52 x_lm_dent =x_lm_dent 9 +coeff( 72)*x11*x24*x31*x41 1 +coeff( 73)*x11*x24 *x42 2 +coeff( 74) *x23*x34*x42*x51 3 +coeff( 75)*x11*x23 *x41*x52 4 +coeff( 76)*x11*x22*x31*x41*x52 5 +coeff( 77)*x11*x21*x32*x41*x52 6 +coeff( 78)*x11*x21 *x41*x54 7 +coeff( 79) *x23*x33*x43*x52 8 +coeff( 80)*x11*x24*x33*x41 x_lm_dent =x_lm_dent 9 +coeff( 81)*x11*x23*x32*x41*x52 1 +coeff( 82)*x11*x22*x33*x41*x52 2 +coeff( 83)*x11*x21*x32*x41*x54 c return end function t_lm_dent (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 18) data ncoeff/ 17/ data avdat/ 0.1301045E+01/ data xmin/ 1 -0.99984E-03,-0.65005E-01,-0.19978E-01,-0.28029E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99999E-03, 0.65048E-01, 0.19925E-01, 0.27110E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + -0.29613664E-02, 0.54711830E-01, 0.43964400E-02, 0.34626520E-02, + 0.58670499E-03,-0.64154499E-03, 0.28723755E-02, 0.73632685E-03, + -0.21854599E-02,-0.85518649E-03,-0.94894943E-03,-0.81356178E-04, + 0.19736734E-03, 0.23911276E-03,-0.34711132E-03,-0.75248169E-03, + -0.65526139E-03, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x24 = x23*x2 x31 = x3 x41 = x4 x42 = x41*x4 x51 = x5 x52 = x51*x5 c c function c t_lm_dent =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x22 4 +coeff( 4) *x21 *x51 5 +coeff( 5) *x51 6 +coeff( 6)*x11 7 +coeff( 7) *x42 8 +coeff( 8) *x31*x41 t_lm_dent =t_lm_dent 9 +coeff( 9) *x21 *x42 1 +coeff( 10) *x23 2 +coeff( 11) *x21*x31*x41 3 +coeff( 12) *x41 4 +coeff( 13) *x22 *x51 5 +coeff( 14) *x42*x51 6 +coeff( 15) *x21 *x52 7 +coeff( 16) *x24 8 +coeff( 17) *x22 *x42 c return end function y_lm_dent (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 15) data ncoeff/ 14/ data avdat/ -0.1283624E-02/ data xmin/ 1 -0.99984E-03,-0.65005E-01,-0.19978E-01,-0.28029E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99999E-03, 0.65048E-01, 0.19925E-01, 0.27110E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + -0.12186439E-02, 0.21534903E-01, 0.15051925E+00, 0.11737648E-01, + 0.20372600E-02, 0.21319420E-02,-0.39582383E-02,-0.11971015E-04, + -0.20336406E-03, 0.11582013E-02,-0.85291365E-03,-0.10171494E-02, + -0.54086506E-03,-0.80123346E-03, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x21 = x2 x22 = x21*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x51 = x5 x52 = x51*x5 c c function c y_lm_dent =avdat 1 +coeff( 1) 2 +coeff( 2) *x31 3 +coeff( 3) *x41 4 +coeff( 4) *x41*x51 5 +coeff( 5) *x21 *x41 6 +coeff( 6) *x31 *x51 7 +coeff( 7) *x22 *x41 8 +coeff( 8) *x21*x33 y_lm_dent =y_lm_dent 9 +coeff( 9) *x51 1 +coeff( 10) *x21*x31 2 +coeff( 11) *x43 3 +coeff( 12) *x22*x31 4 +coeff( 13) *x21 *x41*x51 5 +coeff( 14) *x41*x52 c return end function p_lm_dent (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 34) data ncoeff/ 33/ data avdat/ -0.2104334E-03/ data xmin/ 1 -0.99984E-03,-0.65005E-01,-0.19978E-01,-0.28029E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99999E-03, 0.65048E-01, 0.19925E-01, 0.27110E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.64400327E-03, 0.35943324E-03,-0.16823323E-01,-0.22543883E-01, + -0.22438686E-01, 0.11767704E-01,-0.17077370E-01, 0.20631685E-04, + 0.30017853E-04,-0.26529364E-03,-0.13194067E-05, 0.45403792E-03, + -0.24436313E-05,-0.57652961E-02, 0.26812616E-02,-0.19491139E-03, + 0.23776482E-03,-0.35486370E-02,-0.18255132E-02,-0.81666879E-03, + 0.19779655E-02,-0.10851376E-02, 0.28163418E-02,-0.44962453E-04, + 0.82726945E-03,-0.14614556E-04, 0.20369561E-03,-0.11324153E-02, + 0.61556850E-04,-0.24959358E-03,-0.22504061E-03, 0.24298189E-03, + 0.32438352E-03, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x3 =1.+(x( 3)-xmax( 3))*scale( 3) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x24 = x23*x2 x31 = x3 x32 = x31*x3 x33 = x32*x3 x41 = x4 x42 = x41*x4 x43 = x42*x4 x51 = x5 x52 = x51*x5 c c function c p_lm_dent =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x31 4 +coeff( 4) *x41 5 +coeff( 5) *x21 *x41 6 +coeff( 6) *x41*x51 7 +coeff( 7) *x22 *x41 8 +coeff( 8) *x23*x31 p_lm_dent =p_lm_dent 9 +coeff( 9) *x21*x33 1 +coeff( 10) *x22*x31 *x51 2 +coeff( 11) *x33 *x51 3 +coeff( 12) *x24*x31 4 +coeff( 13) *x23*x33 5 +coeff( 14) *x21*x31 6 +coeff( 15) *x31 *x51 7 +coeff( 16) *x51 8 +coeff( 17) *x22 p_lm_dent =p_lm_dent 9 +coeff( 18) *x22*x31 1 +coeff( 19) *x43 2 +coeff( 20) *x41*x52 3 +coeff( 21) *x23 *x41 4 +coeff( 22) *x22 *x41*x51 5 +coeff( 23) *x24 *x41 6 +coeff( 24) *x33*x42 7 +coeff( 25) *x23 *x41*x51 8 +coeff( 26) *x33 p_lm_dent =p_lm_dent 9 +coeff( 27)*x11 *x41 1 +coeff( 28) *x31*x42 2 +coeff( 29)*x11 *x31 3 +coeff( 30) *x32*x41 4 +coeff( 31) *x31 *x52 5 +coeff( 32)*x11*x21 *x41 6 +coeff( 33) *x21 *x43 c return end function l_lm_dent (x,m) dimension x(m) dimension xmin(10),xmax(10),scale(10),xmean(10) dimension coeff( 8) data ncoeff/ 7/ data avdat/ -0.1493386E-02/ data xmin/ 1 -0.99984E-03,-0.65005E-01,-0.19978E-01,-0.28029E-01,-0.49930E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data xmax/ 1 0.99999E-03, 0.65048E-01, 0.19925E-01, 0.27110E-01, 0.49901E-01, 2 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00, 0.00000E+00/ data scale /10*0./ data coeff/ + 0.12317417E-02, 0.23449549E+00,-0.17015114E-01, 0.15429468E-01, + -0.20743525E-02,-0.36474732E-02,-0.68251356E-02, + 0. / data ientry/0/ c if (ientry.ne.0) go to 10 ientry=1 do 5 i=1,m if (xmin(i).eq.xmax(i)) go to 5 scale(i)=2./(xmax(i)-xmin(i)) 5 continue c 10 continue c normalize variables between -1 and +1 x1 =1.+(x( 1)-xmax( 1))*scale( 1) x2 =1.+(x( 2)-xmax( 2))*scale( 2) x4 =1.+(x( 4)-xmax( 4))*scale( 4) x5 =1.+(x( 5)-xmax( 5))*scale( 5) c set up monomials functions x11 = x1 x21 = x2 x22 = x21*x2 x23 = x22*x2 x41 = x4 x42 = x41*x4 x51 = x5 c c function c l_lm_dent =avdat 1 +coeff( 1) 2 +coeff( 2) *x21 3 +coeff( 3) *x22 4 +coeff( 4) *x21 *x51 5 +coeff( 5)*x11 6 +coeff( 6) *x42 7 +coeff( 7) *x23 *x42 c return end