data_AUTOMATIC[NATIVE] _entry.id AUTOMATIC _diffrn.id NATIVE _audit.creation_date 2010-12-27T20:24:42+00:00 _software.classification 'data reduction' _software.contact_author 'P.R. Evans' _software.contact_author_email pre@mrc-lmb.cam.ac.uk _software.description 'scale together multiple observations of reflections' _software.name Scala _software.version 'CCP4_3.3.16 2010/01/06' _cell.length_a 101.720 _cell.length_b 101.720 _cell.length_c 101.720 _cell.angle_alpha 90.000 _cell.angle_beta 90.000 _cell.angle_gamma 90.000 _Symmetry.Int_Tables_number 197 _Symmetry.space_group_name_H-M 'I 2 3 ' _reflns.data_reduction_method ; data reduction merge and scaling used SCALA (CCP4) ; _reflns.merge_reject_criterion ; sd multiplier for max deviation from weighted mean I : sdref = 6.000 special value for reflections measured twice : sdrej2 = 6.000 The test for outliers is as follows: (1) if there are 2 observations (left), then (a) for each observation Ihl, test deviation Delta(hl) = |Chi| |Ihl - ghl Iother| / sqrt[sigIhl**2 + (ghl*sdIother)**2] against sdrej2, where Iother = the other observation (b) if either Delta(hl) > sdrej2, then 1. in scaling, reject reflection. Or: 2. in merging, keep both. (2) if there 3 or more observations left, then (a) for each observation Ihl, 1. calculate weighted mean of all other observations n-1 & its sd(n-1) 2. deviation Delta(hl) = |Ihl - ghl n-1>| / sqrt[sigIhl**2 + (ghl*sd(n-1))**2] 3. find largest deviation max|Delta(hl)| 4. count number of observations for which |Delta(hl)|.ge.0 (ngt), & for which |Delta(hl)| .lt. 0 (nlt) (b) if max|Delta(hl)| > sdrej, then reject one observation, but which one? 1. if ngt == 1 .or. nlt == 1, then one observation is a long way from the others and this one is rejected 2. else reject the one with the worst deviation max|Delta(hl)| (3) iterate from beginning ; _reflns.overall_d_res_low 41.53 _reflns.overall_d_res_high 1.27 _reflns.overall_number_observations 546944 _diffrn_reflns.d_res_low 41.53 _diffrn_reflns.d_res_high 1.81 _diffrn_reflns.number_measured_all 406736 _diffrn_reflns.number_unique_all 16192 _diffrn_reflns.number_centric_all 1237 _diffrn_reflns.Rmerge_I_all 0.282 _diffrn_reflns.meanI_over_sigI_all 1.7630 _diffrn_reflns.meanI_over_sd_all 11.0873 _diffrn_reflns.mean_fract_bias 0.0000 _diffrn_reflns.num_fract_bias_in_mean 0 _diffrn_reflns.percent_possible_all 99.99 _diffrn_reflns.multiplicity 25.12 _diffrn_reflns.PCV 0.43 _diffrn_reflns.PCV_mean 0.43 _diffrn_reflns.Rmeas 0.29 _diffrn_reflns.Rmeas_mean 0.29 _diffrn_reflns.min_intensity -10.02 _diffrn_reflns.max_intensity 4469.87 _diffrn_reflns.num_fully_measured 406736 _diffrn_reflns.Intensity_rms_fully_recorded 278.40 _diffrn_reflns.mean_scatter_over_sd_full 0.08 _diffrn_reflns.sigma_scatter_over_sd_full 1.00 loop_ _reflns_shell.d_res_low _reflns_shell.d_res_high _reflns_shell.number_measured_all _reflns_shell.number_unique_all _reflns_shell.number_centric_all _reflns_shell.Rmerge_I_all _reflns_shell.Rmerge_I_all_cumulative _reflns_shell.meanI_over_sigI_all _reflns_shell.meanI_over_sd_all _reflns_shell.percent_possible_all _reflns_shell.cum_percent_possible_all _reflns_shell.multiplicity _reflns_shell.PCV _reflns_shell.PCV_mean _reflns_shell.Rmeas _reflns_shell.Rmeas_mean _reflns_shell.num_fract_bias_in_mean _reflns_shell.mean_fract_bias 41.53 8.08 4708 206 58 0.12 0.12 4.02 21.47 99.55 99.55 22.85 0.21 0.21 0.13 0.13 0 0.00 8.08 5.71 8919 353 64 0.15 0.14 3.52 21.27 100.00 99.84 25.27 0.23 0.23 0.15 0.15 0 0.00 5.71 4.67 11204 446 63 0.16 0.15 3.13 20.97 100.00 99.91 25.12 0.24 0.24 0.16 0.16 0 0.00 4.67 4.04 13040 516 60 0.16 0.15 3.02 21.34 100.00 99.94 25.27 0.27 0.27 0.17 0.17 0 0.00 4.04 3.61 15017 585 62 0.19 0.16 2.74 20.48 100.00 99.96 25.67 0.30 0.30 0.19 0.19 0 0.00 3.61 3.30 16735 651 61 0.22 0.17 2.50 18.25 100.00 99.97 25.71 0.34 0.34 0.22 0.22 0 0.00 3.30 3.05 17695 695 67 0.24 0.18 2.00 16.93 100.00 99.98 25.46 0.38 0.38 0.24 0.24 0 0.00 3.05 2.86 19080 745 61 0.27 0.19 2.24 15.27 100.00 99.98 25.61 0.40 0.40 0.27 0.27 0 0.00 2.86 2.69 20427 788 62 0.29 0.20 2.18 13.74 100.00 99.98 25.92 0.43 0.43 0.30 0.30 0 0.00 2.69 2.56 21269 833 59 0.34 0.21 1.91 12.27 100.00 99.99 25.53 0.49 0.49 0.34 0.34 0 0.00 2.56 2.44 22663 883 64 0.36 0.21 1.85 11.21 100.00 99.99 25.67 0.51 0.51 0.37 0.37 0 0.00 2.44 2.33 23649 916 62 0.38 0.22 1.75 10.76 100.00 99.99 25.82 0.55 0.55 0.39 0.39 0 0.00 2.33 2.24 24781 963 65 0.42 0.23 1.63 10.02 100.00 99.99 25.73 0.58 0.58 0.43 0.43 0 0.00 2.24 2.16 25443 981 64 0.47 0.24 1.48 8.93 100.00 99.99 25.94 0.65 0.65 0.48 0.48 0 0.00 2.16 2.09 25985 1024 58 0.50 0.24 1.40 8.44 100.00 99.99 25.38 0.69 0.69 0.51 0.51 0 0.00 2.09 2.02 27594 1080 64 0.56 0.25 1.28 7.48 100.00 99.99 25.55 0.77 0.77 0.57 0.57 0 0.00 2.02 1.96 27094 1056 61 0.64 0.26 1.12 6.58 100.00 99.99 25.66 0.87 0.87 0.65 0.65 0 0.00 1.96 1.90 28736 1148 64 0.71 0.27 1.00 5.84 100.00 99.99 25.03 0.97 0.97 0.72 0.72 0 0.00 1.90 1.85 27580 1157 56 0.79 0.28 0.87 5.06 100.00 99.99 23.84 1.11 1.11 0.81 0.81 0 0.00 1.85 1.81 25117 1166 62 0.90 0.28 0.79 4.11 100.00 99.99 21.54 1.27 1.27 0.92 0.92 0 0.00