******************************************************************************* Tue Mar 19 15:56:57 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($9 >0.05 && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Tue Mar 19 15:56:58 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.7462044664e-05 0.00e+00 2.17e-01 5.800000e-04 5 3.0911175607e-32 0.00e+00 2.17e-06 5.818044e-04 After 5 iterations the fit converged. final sum of squares of residuals : 3.09112e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000581804 ******************************************************************************* Tue Mar 19 15:57:12 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):($11/$13*$8*f) format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = a*x**2+b*x+c + a2*cos(b2*x) +d*x**3 +e*x**4 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d e 0 6.7370626304e+01 0.00e+00 1.43e-02 1.000000e+00 1.000000e-02 1.000000e-02 1.000000e-02 1.000000e-02 7 1.0358538009e-03 -2.97e-09 1.43e-09 5.118010e+00 -4.018597e-02 -9.988089e-01 2.600221e-01 -1.151199e+02 After 7 iterations the fit converged. final sum of squares of residuals : 0.00103585 rel. change during last iteration : -2.97256e-14 degrees of freedom (FIT_NDF) : 55 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.00433978 variance of residuals (reduced chisquare) = WSSR/ndf : 1.88337e-05 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 5.11801 +/- 0.08384 (1.638%) b = -0.040186 +/- 0.0167 (41.55%) c = -0.998809 +/- 0.0006925 (0.06934%) d = 0.260022 +/- 0.3916 (150.6%) e = -115.12 +/- 1.553 (1.349%) correlation matrix of the fit parameters: a b c d e a 1.000 b -0.534 1.000 c -0.395 0.069 1.000 d 0.627 -0.943 -0.078 1.000 e -0.927 0.697 0.223 -0.821 1.000 ******************************************************************************* Tue Mar 19 15:57:12 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):(f($8))*1.e6 format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: n(x) n(x) =a3*cos(b3*x)-a3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a3 b3 0 7.8605662223e-06 0.00e+00 1.24e+00 2.279070e+02 4.753540e-01 3139 2.9069956092e-06 -9.56e-02 1.24e-03 3.668102e+02 3.745732e-01 After 3139 iterations the fit converged. final sum of squares of residuals : 2.907e-06 rel. change during last iteration : -9.56047e-07 degrees of freedom (FIT_NDF) : 58 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.000223876 variance of residuals (reduced chisquare) = WSSR/ndf : 5.01206e-08 Final set of parameters Asymptotic Standard Error ======================= ========================== a3 = 366.81 +/- 48.36 (13.18%) b3 = 0.374573 +/- 0.0247 (6.594%) correlation matrix of the fit parameters: a3 b3 a3 1.000 b3 -1.000 1.000 ******************************************************************************* Tue Mar 19 15:57:40 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):($11/$13*$8*f) format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = a*x**2+b*x+c + a2*cos(b2*x) +d*x**3 +e*x**4 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d e 0 6.7370626304e+01 0.00e+00 1.43e-02 1.000000e+00 1.000000e-02 1.000000e-02 1.000000e-02 1.000000e-02 7 1.0358538009e-03 -2.97e-09 1.43e-09 5.118010e+00 -4.018597e-02 -9.988089e-01 2.600221e-01 -1.151199e+02 After 7 iterations the fit converged. final sum of squares of residuals : 0.00103585 rel. change during last iteration : -2.97256e-14 degrees of freedom (FIT_NDF) : 55 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.00433978 variance of residuals (reduced chisquare) = WSSR/ndf : 1.88337e-05 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 5.11801 +/- 0.08384 (1.638%) b = -0.040186 +/- 0.0167 (41.55%) c = -0.998809 +/- 0.0006925 (0.06934%) d = 0.260022 +/- 0.3916 (150.6%) e = -115.12 +/- 1.553 (1.349%) correlation matrix of the fit parameters: a b c d e a 1.000 b -0.534 1.000 c -0.395 0.069 1.000 d 0.627 -0.943 -0.078 1.000 e -0.927 0.697 0.223 -0.821 1.000 ******************************************************************************* Tue Mar 19 15:57:40 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):(f($8))*1.e6 format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: n(x) n(x) =a3*cos(b3*x)-a3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a3 b3 0 7.8605662223e-06 0.00e+00 1.24e+00 2.279070e+02 4.753540e-01 3139 2.9069956092e-06 -9.56e-02 1.24e-03 3.668102e+02 3.745732e-01 After 3139 iterations the fit converged. final sum of squares of residuals : 2.907e-06 rel. change during last iteration : -9.56047e-07 degrees of freedom (FIT_NDF) : 58 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.000223876 variance of residuals (reduced chisquare) = WSSR/ndf : 5.01206e-08 Final set of parameters Asymptotic Standard Error ======================= ========================== a3 = 366.81 +/- 48.36 (13.18%) b3 = 0.374573 +/- 0.0247 (6.594%) correlation matrix of the fit parameters: a3 b3 a3 1.000 b3 -1.000 1.000 ******************************************************************************* Mon Apr 8 13:17:49 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:17:49 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:20:38 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:20:39 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:21:23 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:21:27 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:22:44 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:22:44 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:23:23 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:24:38 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:24:38 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:26:10 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:26:42 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:27:51 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:28:27 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:28:31 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:29:25 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:29:26 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:29:46 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:29:47 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:30:34 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:30:35 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:32:52 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:32:53 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:37:47 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:37:48 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:40:38 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:40:39 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:41:33 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:41:35 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:42:40 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:42:41 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:44:35 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:44:36 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:45:01 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:45:02 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:45:29 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:45:32 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:45:33 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 13:45:35 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 13:48:13 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):($11/$13*$8*f) format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = a*x**2+b*x+c + a2*cos(b2*x) +d*x**3 +e*x**4 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d e 0 6.7370626304e+01 0.00e+00 1.43e-02 1.000000e+00 1.000000e-02 1.000000e-02 1.000000e-02 1.000000e-02 7 1.0358538009e-03 -2.97e-09 1.43e-09 5.118010e+00 -4.018597e-02 -9.988089e-01 2.600221e-01 -1.151199e+02 After 7 iterations the fit converged. final sum of squares of residuals : 0.00103585 rel. change during last iteration : -2.97256e-14 degrees of freedom (FIT_NDF) : 55 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.00433978 variance of residuals (reduced chisquare) = WSSR/ndf : 1.88337e-05 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 5.11801 +/- 0.08384 (1.638%) b = -0.040186 +/- 0.0167 (41.55%) c = -0.998809 +/- 0.0006925 (0.06934%) d = 0.260022 +/- 0.3916 (150.6%) e = -115.12 +/- 1.553 (1.349%) correlation matrix of the fit parameters: a b c d e a 1.000 b -0.534 1.000 c -0.395 0.069 1.000 d 0.627 -0.943 -0.078 1.000 e -0.927 0.697 0.223 -0.821 1.000 ******************************************************************************* Mon Apr 8 13:48:13 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):(f($8))*1.e6 format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: n(x) n(x) =a3*cos(b3*x)-a3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a3 b3 0 7.8605662223e-06 0.00e+00 1.24e+00 2.279070e+02 4.753540e-01 3139 2.9069956092e-06 -9.56e-02 1.24e-03 3.668102e+02 3.745732e-01 After 3139 iterations the fit converged. final sum of squares of residuals : 2.907e-06 rel. change during last iteration : -9.56047e-07 degrees of freedom (FIT_NDF) : 58 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.000223876 variance of residuals (reduced chisquare) = WSSR/ndf : 5.01206e-08 Final set of parameters Asymptotic Standard Error ======================= ========================== a3 = 366.81 +/- 48.36 (13.18%) b3 = 0.374573 +/- 0.0247 (6.594%) correlation matrix of the fit parameters: a3 b3 a3 1.000 b3 -1.000 1.000 ******************************************************************************* Mon Apr 8 13:51:09 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):($11/$13*$8*f) format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = a*x**2+b*x+c + a2*cos(b2*x) +d*x**3 +e*x**4 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d e 0 6.7370626304e+01 0.00e+00 1.43e-02 1.000000e+00 1.000000e-02 1.000000e-02 1.000000e-02 1.000000e-02 7 1.0358538009e-03 -2.97e-09 1.43e-09 5.118010e+00 -4.018597e-02 -9.988089e-01 2.600221e-01 -1.151199e+02 After 7 iterations the fit converged. final sum of squares of residuals : 0.00103585 rel. change during last iteration : -2.97256e-14 degrees of freedom (FIT_NDF) : 55 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.00433978 variance of residuals (reduced chisquare) = WSSR/ndf : 1.88337e-05 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 5.11801 +/- 0.08384 (1.638%) b = -0.040186 +/- 0.0167 (41.55%) c = -0.998809 +/- 0.0006925 (0.06934%) d = 0.260022 +/- 0.3916 (150.6%) e = -115.12 +/- 1.553 (1.349%) correlation matrix of the fit parameters: a b c d e a 1.000 b -0.534 1.000 c -0.395 0.069 1.000 d 0.627 -0.943 -0.078 1.000 e -0.927 0.697 0.223 -0.821 1.000 ******************************************************************************* Mon Apr 8 13:51:09 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):(f($8))*1.e6 format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: n(x) n(x) =a3*cos(b3*x)-a3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a3 b3 0 7.8605662223e-06 0.00e+00 1.24e+00 2.279070e+02 4.753540e-01 3139 2.9069956092e-06 -9.56e-02 1.24e-03 3.668102e+02 3.745732e-01 After 3139 iterations the fit converged. final sum of squares of residuals : 2.907e-06 rel. change during last iteration : -9.56047e-07 degrees of freedom (FIT_NDF) : 58 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.000223876 variance of residuals (reduced chisquare) = WSSR/ndf : 5.01206e-08 Final set of parameters Asymptotic Standard Error ======================= ========================== a3 = 366.81 +/- 48.36 (13.18%) b3 = 0.374573 +/- 0.0247 (6.594%) correlation matrix of the fit parameters: a3 b3 a3 1.000 b3 -1.000 1.000 ******************************************************************************* Mon Apr 8 13:52:53 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):($11/$13*$8*f) format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = a*x**2+b*x+c + a2*cos(b2*x) +d*x**3 +e*x**4 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d e 0 6.7370626304e+01 0.00e+00 1.43e-02 1.000000e+00 1.000000e-02 1.000000e-02 1.000000e-02 1.000000e-02 7 1.0358538009e-03 -2.97e-09 1.43e-09 5.118010e+00 -4.018597e-02 -9.988089e-01 2.600221e-01 -1.151199e+02 After 7 iterations the fit converged. final sum of squares of residuals : 0.00103585 rel. change during last iteration : -2.97256e-14 degrees of freedom (FIT_NDF) : 55 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.00433978 variance of residuals (reduced chisquare) = WSSR/ndf : 1.88337e-05 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 5.11801 +/- 0.08384 (1.638%) b = -0.040186 +/- 0.0167 (41.55%) c = -0.998809 +/- 0.0006925 (0.06934%) d = 0.260022 +/- 0.3916 (150.6%) e = -115.12 +/- 1.553 (1.349%) correlation matrix of the fit parameters: a b c d e a 1.000 b -0.534 1.000 c -0.395 0.069 1.000 d 0.627 -0.943 -0.078 1.000 e -0.927 0.697 0.223 -0.821 1.000 ******************************************************************************* Mon Apr 8 13:52:53 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):(f($8))*1.e6 format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: n(x) n(x) =a3*cos(b3*x)-a3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a3 b3 0 4.7274259590e-02 0.00e+00 1.24e+00 2.279070e+02 4.753540e-01 ******************************************************************************* Mon Apr 8 13:53:05 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):($11/$13*$8*f) format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = a*x**2+b*x+c + a2*cos(b2*x) +d*x**3 +e*x**4 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d e 0 6.7370626304e+01 0.00e+00 1.43e-02 1.000000e+00 1.000000e-02 1.000000e-02 1.000000e-02 1.000000e-02 7 1.0358538009e-03 -2.97e-09 1.43e-09 5.118010e+00 -4.018597e-02 -9.988089e-01 2.600221e-01 -1.151199e+02 After 7 iterations the fit converged. final sum of squares of residuals : 0.00103585 rel. change during last iteration : -2.97256e-14 degrees of freedom (FIT_NDF) : 55 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.00433978 variance of residuals (reduced chisquare) = WSSR/ndf : 1.88337e-05 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 5.11801 +/- 0.08384 (1.638%) b = -0.040186 +/- 0.0167 (41.55%) c = -0.998809 +/- 0.0006925 (0.06934%) d = 0.260022 +/- 0.3916 (150.6%) e = -115.12 +/- 1.553 (1.349%) correlation matrix of the fit parameters: a b c d e a 1.000 b -0.534 1.000 c -0.395 0.069 1.000 d 0.627 -0.943 -0.078 1.000 e -0.927 0.697 0.223 -0.821 1.000 ******************************************************************************* Mon Apr 8 13:53:05 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):(f($8))*1.e6 format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: n(x) n(x) =a3*cos(b3*x)-a3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a3 b3 0 4.7274259590e-02 0.00e+00 1.24e+00 2.279070e+02 4.753540e-01 3064 2.7097125226e-06 -9.37e-01 1.24e-03 3.532229e+02 3.748174e-01 After 3064 iterations the fit converged. final sum of squares of residuals : 2.70971e-06 rel. change during last iteration : -9.37021e-06 degrees of freedom (FIT_NDF) : 58 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.000216146 variance of residuals (reduced chisquare) = WSSR/ndf : 4.67192e-08 Final set of parameters Asymptotic Standard Error ======================= ========================== a3 = 353.223 +/- 46.57 (13.18%) b3 = 0.374817 +/- 0.02472 (6.594%) correlation matrix of the fit parameters: a3 b3 a3 1.000 b3 -1.000 1.000 ******************************************************************************* Mon Apr 8 15:07:13 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):(($9-zero)/zero*1.e6 > -5. && abs($8)<0.0001 ? (($9-zero)/zero*1.e6):1/0) format = x:z #datapoints = 33 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x) = -a*x**2 +b*x +c + d*x**3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d 0 9.8792894937e+07 0.00e+00 8.65e+02 5.800000e-03 1.000000e-01 1.000000e-01 1.000000e-01 7 1.3304449118e-04 -1.48e-02 8.65e-05 5.449704e-04 3.567394e-03 -1.568241e-02 -3.128446e-07 After 7 iterations the fit converged. final sum of squares of residuals : 0.000133044 rel. change during last iteration : -1.48334e-07 degrees of freedom (FIT_NDF) : 29 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.0021419 variance of residuals (reduced chisquare) = WSSR/ndf : 4.58774e-06 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 0.00054497 +/- 9.603e-07 (0.1762%) b = 0.00356739 +/- 5.002e-05 (1.402%) c = -0.0156824 +/- 0.0004485 (2.86%) d = -3.12845e-07 +/- 5.02e-08 (16.05%) correlation matrix of the fit parameters: a b c d a 1.000 b -0.198 1.000 c 0.546 -0.060 1.000 d 0.335 -0.887 0.101 1.000 ******************************************************************************* Mon Apr 8 15:07:14 2019 FIT: data read from 'compile_spin_data.dat' u ($4*1000):($26 != 0 ? (-$4**2 / (betay)**2/4. * 1.e6):1/0) format = x:z #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = -a1*x**2 fitted parameters initialized with current variable values iter chisq delta/lim lambda a1 0 2.4247274654e-03 0.00e+00 2.17e-01 5.800000e-04 6 3.1224139223e-32 0.00e+00 2.17e-01 5.630448e-04 After 6 iterations the fit converged. final sum of squares of residuals : 3.12241e-32 abs. change during last iteration : 0 Hmmmm.... Sum of squared residuals is zero. Can't compute errors. Final set of parameters ======================= a1 = 0.000563045 ******************************************************************************* Mon Apr 8 15:07:26 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):($11/$13*$8*f) format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x) = a*x**2+b*x+c + a2*cos(b2*x) +d*x**3 +e*x**4 fitted parameters initialized with current variable values iter chisq delta/lim lambda a b c d e 0 6.7370626304e+01 0.00e+00 1.43e-02 1.000000e+00 1.000000e-02 1.000000e-02 1.000000e-02 1.000000e-02 7 1.0358538009e-03 -2.97e-09 1.43e-09 5.118010e+00 -4.018597e-02 -9.988089e-01 2.600221e-01 -1.151199e+02 After 7 iterations the fit converged. final sum of squares of residuals : 0.00103585 rel. change during last iteration : -2.97256e-14 degrees of freedom (FIT_NDF) : 55 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.00433978 variance of residuals (reduced chisquare) = WSSR/ndf : 1.88337e-05 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 5.11801 +/- 0.08384 (1.638%) b = -0.040186 +/- 0.0167 (41.55%) c = -0.998809 +/- 0.0006925 (0.06934%) d = 0.260022 +/- 0.3916 (150.6%) e = -115.12 +/- 1.553 (1.349%) correlation matrix of the fit parameters: a b c d e a 1.000 b -0.534 1.000 c -0.395 0.069 1.000 d 0.627 -0.943 -0.078 1.000 e -0.927 0.697 0.223 -0.821 1.000 ******************************************************************************* Mon Apr 8 15:07:26 2019 FIT: data read from 'compile_spin_data.dat' u ($8*100):(f($8))*1.e6 format = x:z x range restricted to [-0.350000 : 0.350000] #datapoints = 60 residuals are weighted equally (unit weight) function used for fitting: n(x) n(x) =a3*cos(b3*x)-a3 fitted parameters initialized with current variable values iter chisq delta/lim lambda a3 b3 0 3.9503242171e-02 0.00e+00 1.24e+00 2.279070e+02 4.753540e-01 3071 2.7264158770e-06 -8.80e-01 1.24e-03 3.543947e+02 3.747950e-01 After 3071 iterations the fit converged. final sum of squares of residuals : 2.72642e-06 rel. change during last iteration : -8.79657e-06 degrees of freedom (FIT_NDF) : 58 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.000216811 variance of residuals (reduced chisquare) = WSSR/ndf : 4.70072e-08 Final set of parameters Asymptotic Standard Error ======================= ========================== a3 = 354.395 +/- 46.72 (13.18%) b3 = 0.374795 +/- 0.02471 (6.594%) correlation matrix of the fit parameters: a3 b3 a3 1.000 b3 -1.000 1.000