#############################################################
##                     phenix.xtriage                      ##
##                                                         ##
##     P.H. Zwart, R.W. Grosse-Kunstleve & P.D. Adams      ##
##                                                         ##
#############################################################
#phil __OFF__
  This cryptic code, together with the tags __ON__ and __OFF__
  allows one to use the log file as an input file for xtriage.
  Try : phenix.xtriage  <logfile> to give it a try!

Date 2008-03-22 Time 22:47:56 PDT -0700 (1206251276.86 s)


##-------------------------------------------##
## WARNING:                                  ##
## Number of residues unspecified            ##
##-------------------------------------------##


Effective parameters: 
#phil __ON__
scaling.input {
  parameters {
    asu_contents {
      n_residues = None
      n_bases = None
      n_copies_per_asu = None
    }
    misc_twin_parameters {
      missing_symmetry {
        tanh_location = 0.08
        tanh_slope = 50
      }
      twinning_with_ncs {
        perform_analyses = False
        n_bins = 7
      }
      twin_test_cuts {
        low_resolution = 10
        high_resolution = None
        isigi_cut = 3
        completeness_cut = 0.85
      }
    }
    reporting {
      verbose = 1
      log = "logfile.log"
      ccp4_style_graphs = True
    }
  }
  xray_data {
    file_name = "h4-p321.sca"
    obs_labels = None
    calc_labels = None
    unit_cell = 43.261 43.261 123.928 90 90 120
    space_group = "P 3 2 1"
    high_resolution = None
    low_resolution = None
    reference {
      data {
        file_name = None
        labels = None
        unit_cell = None
        space_group = None
      }
    }
  }
}
#phil __END__


Symmetry, cell and reflection file content summary

Miller array info: h4-p321.sca:i_obs,sigma
Observation type: xray.amplitude
Type of data: double, size=4825
Type of sigmas: double, size=4825
Number of Miller indices: 4825
Anomalous flag: False
Unit cell: (43.261, 43.261, 123.928, 90, 90, 120)
Space group: P 3 2 1 (No. 150)
Systematic absences: 0
Centric reflections: 1015
Resolution range: 37.4651 2.50107
Completeness in resolution range: 0.94999
Completeness with d_max=infinity: 0.949429

##----------------------------------------------------##
##                    Basic statistics                ##
##----------------------------------------------------##

Number of residues unknown, assuming 50% solvent content

----------------------------------------------------------------
|              Best guess :  122  residues in the asu          |
----------------------------------------------------------------


Completeness and data strength analyses 

  The following table lists the completeness in various resolution
  ranges, after applying a I/sigI cut. Miller indices for which
  individual I/sigI values are larger than the value specified in
  the top row of the table, are retained, while other intensities
  are discarded. The resulting completeness profiles are an indication
  of the strength of the data.

----------------------------------------------------------------------------------------
| Res. Range   | I/sigI>1  | I/sigI>2  | I/sigI>3  | I/sigI>5  | I/sigI>10 | I/sigI>15 |
----------------------------------------------------------------------------------------
| 37.47 - 6.16 | 93.0%     | 92.5%     | 91.8%     | 90.8%     | 89.3%     | 86.0%     |
|  6.16 - 4.89 | 98.1%     | 96.7%     | 96.1%     | 95.0%     | 92.5%     | 89.7%     |
|  4.89 - 4.28 | 97.1%     | 97.1%     | 96.5%     | 96.2%     | 91.9%     | 89.2%     |
|  4.28 - 3.88 | 96.1%     | 95.8%     | 95.0%     | 93.5%     | 91.4%     | 85.5%     |
|  3.88 - 3.61 | 96.4%     | 96.1%     | 95.0%     | 92.6%     | 87.5%     | 81.0%     |
|  3.61 - 3.39 | 96.6%     | 96.0%     | 95.4%     | 93.1%     | 86.5%     | 79.1%     |
|  3.39 - 3.22 | 94.0%     | 91.6%     | 91.3%     | 88.0%     | 78.7%     | 70.6%     |
|  3.22 - 3.08 | 93.7%     | 91.5%     | 89.9%     | 87.4%     | 80.8%     | 72.3%     |
|  3.08 - 2.97 | 91.9%     | 89.2%     | 87.2%     | 83.7%     | 75.3%     | 65.7%     |
|  2.97 - 2.86 | 93.4%     | 91.2%     | 89.0%     | 81.4%     | 68.1%     | 55.8%     |
|  2.86 - 2.77 | 91.9%     | 89.6%     | 86.5%     | 77.5%     | 65.4%     | 50.7%     |
|  2.77 - 2.69 | 89.0%     | 84.1%     | 79.2%     | 68.8%     | 56.8%     | 44.2%     |
|  2.69 - 2.62 | 87.3%     | 79.3%     | 73.4%     | 64.2%     | 47.3%     | 36.4%     |
|  2.62 - 2.56 | 89.6%     | 81.4%     | 73.9%     | 65.1%     | 45.9%     | 31.4%     |
----------------------------------------------------------------------------------------

  The completeness of data for which I/sig(I)>3.00, exceeds  85% for
  for resolution ranges lower than 2.77A.
  The data are cut at this resolution for the potential twin tests 
  and intensity statistics.
ML estimate of overall B_cart value of None:
62.07,  0.00,  0.00
       62.07,  0.00
              33.98
Equivalent representation as U_cif: 
 0.79,  0.39, -0.00
        0.79,  0.00
               0.43

Eigen analyses of B-cart:
                 Value   Vector
Eigenvector 1 :  62.068  ( 0.52,  0.85,  0.00)
Eigenvector 2 :  62.068  ( 0.85, -0.52, -0.00)
Eigenvector 3 :  33.979  (-0.00, -0.00,  1.00)

ML estimate of  -log of scale factor of None:
-1.16


Low resolution completeness analyses 

 The following table shows the completeness
 of the data to 5 Angstrom.
unused:         - 37.4661 [ 0/3 ] 0.000
bin  1: 37.4661 - 10.7436 [77/89] 0.865
bin  2: 10.7436 -  8.5610 [71/74] 0.959
bin  3:  8.5610 -  7.4887 [68/71] 0.958
bin  4:  7.4887 -  6.8084 [65/70] 0.929
bin  5:  6.8084 -  6.3229 [63/64] 0.984
bin  6:  6.3229 -  5.9517 [77/78] 0.987
bin  7:  5.9517 -  5.6547 [63/64] 0.984
bin  8:  5.6547 -  5.4093 [50/51] 0.980
bin  9:  5.4093 -  5.2016 [75/77] 0.974
bin 10:  5.2016 -  5.0225 [69/70] 0.986
unused:  5.0225 -         [ 0/0 ]



Mean intensity analyses 
 Analyses of the mean intensity. 
 Inspired by: Morris et al. (2004). J. Synch. Rad.11, 56-59.
 The following resolution shells are worrisome: 
------------------------------------------------
| d_spacing | z_score | compl. | <Iobs>/<Iexp> |
------------------------------------------------
|    9.980  |   6.18  |   0.98 |     0.421     |
|    4.302  |   5.70  |   0.98 |     0.631     |
|    4.151  |   4.55  |   0.97 |     0.688     |
|    3.891  |   4.73  |   0.98 |     0.694     |
|    3.675  |   6.39  |   0.95 |     0.622     |
------------------------------------------------

 Possible reasons for the presence of the reported
 unexpected low or elevated mean intensity in
 a given resolution bin are : 
 - missing overloaded or weak reflections
 - suboptimal data processing
 - satellite (ice) crystals
 - NCS
 - translational pseudo symmetry (detected elsewhere)
 - outliers (detected elsewhere)
 - ice rings (detected elsewhere)
 - other problems
 Note that the presence of abnormalities 
 in a certain region of reciprocal space might
 confuse the data validation algorithm throughout
 a large region of reciprocal space, even though
 the data are acceptable in those areas. 


Possible outliers 
  Inspired by: Read, Acta Cryst. (1999). D55, 1759-1764

 Acentric reflections:

-----------------------------------------------------------------
| d_space |      H     K     L |  |E|  | p(wilson) | p(extreme) |
-----------------------------------------------------------------
|   3.112 |      3,    1,   38 |  3.32 |  1.65e-05 |   6.07e-02 |
|   3.531 |      3,    2,   32 |  3.81 |  5.07e-07 |   1.92e-03 |
|   3.331 |      3,    3,   33 |  3.45 |  6.71e-06 |   2.51e-02 |
|   7.030 |      4,    1,    9 |  4.10 |  5.12e-08 |   1.94e-04 |
|   3.329 |      4,    1,   34 |  3.64 |  1.71e-06 |   6.47e-03 |
|   3.753 |      4,    2,   28 |  4.17 |  2.78e-08 |   1.05e-04 |
-----------------------------------------------------------------

 p(wilson)  : 1-(1-exp[-|E|^2]) 
 p(extreme) : 1-(1-exp[-|E|^2])^(n_acentrics)
 p(wilson) is the probability that an E-value of the specified
 value would be observed if it were selected at random
 the given data set.
 p(extreme) is the probability that the largest |E| value is 
 larger or equal than the observed largest |E| value.

 Both measures can be used for outlier detection. p(extreme)
 takes into account the size of the dataset.


 Centric reflections:

-----------------------------------------------------------------
| d_space |      H     K     L |  |E|  | p(wilson) | p(extreme) |
-----------------------------------------------------------------
|   3.596 |      3,    0,  -33 |  3.91 |  9.25e-05 |   8.59e-02 |
-----------------------------------------------------------------

 p(wilson)  : 1-(erf[|E|/sqrt(2)]) 
 p(extreme) : 1-(erf[|E|/sqrt(2)])^(n_acentrics)
 p(wilson) is the probability that an E-value of the specified
 value would be observed when it would selected at random from
 the given data set.
 p(extreme) is the probability that the largest |E| value is 
 larger or equal than the observed largest |E| value.

 Both measures can be used for outlier detection. p(extreme)
 takes into account the size of the dataset.

Ice ring related problems

 The following statistics were obtained from ice-ring 
 insensitive resolution ranges 
  mean bin z_score      : 2.10
      ( rms deviation   : 1.65 )
  mean bin completeness : 0.96
     ( rms deviation   : 0.03 )

 The following table shows the z-scores 
 and completeness in ice-ring sensitive areas.
 Large z-scores and high completeness in these 
 resolution ranges might be a reason to re-assess
 your data processsing if ice rings were present.

------------------------------------------------
| d_spacing | z_score | compl. | Rel. Ice int. |
------------------------------------------------
|    3.897  |   4.73  |   0.98 |     1.000     |
|    3.669  |   2.20  |   0.94 |     0.750     |
|    3.441  |   3.97  |   0.98 |     0.530     |
|    2.671  |   0.80  |   0.91 |     0.170     |
------------------------------------------------

 Abnormalities in mean intensity or completeness at
 resolution ranges with a relative ice ring intensity
 lower than 0.10 will be ignored.

 No ice ring related problems detected.
 If ice rings were present, the data does not look
 worse at ice ring related d_spacings as compared
 to the rest of the data set 






$TABLE: Intensity plots:
$GRAPHS
:Intensity plots 
:A:1,2,3,4:
$$
1/resol^2   <I>_smooth_approximation   <I>_via_binning   <I>_expected   $$ 
$$
0.010040   35020.625611   31588.056107   75109.306542
0.014040   37504.235930   35287.994607   59059.768408
0.018040   37949.987989   44029.850942   43395.449147
0.022040   39391.174991   41758.292440   37242.358616
0.026040   42327.356066   33462.985076   37259.129224
0.030040   46472.170080   42604.054973   41037.421495
0.034040   51366.535256   62120.591388   49888.826364
0.038040   56541.297150   56833.502011   63933.554247
0.042040   61539.516968   58701.135163   79794.889731
0.046040   65906.342244   68995.785972   92781.887149
0.050040   69210.430610   72514.731997   100027.270766
0.054040   71124.402783   64123.373015   101686.451113
0.058040   71535.306307   68762.669289   99963.086084
0.062040   70614.763238   75327.737619   97313.877020
0.066040   68791.624426   66040.404218   95162.151086
0.070040   66631.665490   77348.296497   93626.325129
0.074040   64684.323598   57216.968107   92014.926236
0.078040   63359.352597   74166.035367   89542.172160
0.082040   62856.625884   61559.926324   85826.773925
0.086040   63135.485103   59362.730699   81015.716157
0.090040   63906.562178   65830.111896   75614.106691
0.094040   64655.497566   54257.063941   70206.237269
0.098040   64735.928071   69138.665940   65231.230112
0.102040   63558.471071   70722.750228   60890.901136
0.106040   60831.543053   65164.029571   57181.257813
0.110040   56724.674334   60355.463204   53989.570353
0.114040   51830.367431   51155.133794   51192.744407
0.118040   46933.576111   42585.755549   48715.772409
0.122040   42736.708431   37334.444636   46540.845909
0.126040   39687.245490   41415.082334   44682.041277
0.130040   37935.411081   39797.424260   43150.123678
0.134040   37350.525892   35851.820261   41928.152468
0.138040   37531.156706   36279.962507   40967.298036
0.142040   37840.030040   42903.966257   40200.510702
0.146040   37594.370633   32815.855478   39564.271215
0.150040   36477.415244   37182.832879   39017.265514
0.154040   34922.501809   35920.881631   38548.343504
0.159863   34133.237258   33247.790056   38038.136826
$$


$TABLE: Z scores and completeness:
$GRAPHS
:Data sanity and completeness check 
:A:1,2,3:
$$
1/resol^2   Z_score   Completeness   $$ 
$$
0.010040   6.175277   0.984127
0.014040   4.362576   0.942029
0.018040   0.105655   0.923077
0.022040   0.918223   0.974359
0.026040   0.985745   0.988095
0.030040   0.325087   0.977011
0.034040   1.858127   0.979167
0.038040   1.126884   0.988889
0.042040   3.336988   0.971154
0.046040   3.279716   0.964286
0.050040   3.482618   0.980198
0.054040   5.696100   0.982906
0.058040   4.554277   0.974359
0.062040   2.939679   0.956140
0.066040   4.733010   0.984375
0.070040   2.286609   1.000000
0.074040   6.389395   0.953846
0.078040   2.198545   0.944882
0.082040   4.397760   0.971429
0.086040   3.970648   0.976923
0.090040   1.699403   0.944828
0.094040   3.481095   0.961290
0.098040   0.655801   0.952055
0.102040   1.551939   0.955224
0.106040   1.474752   0.887574
0.110040   1.252984   0.954248
0.114040   0.008804   0.949045
0.118040   1.611841   0.970149
0.122040   3.114903   0.922652
0.126040   0.973936   0.945783
0.130040   1.070768   0.976608
0.134040   2.021472   0.936709
0.138040   1.586839   0.892655
0.142040   0.799062   0.912568
0.146040   2.486400   0.974843
0.150040   0.621648   0.912088
0.154040   0.904494   0.924419
0.159863   1.831999   0.928177
$$


$TABLE: <I/sigma_I>:
$GRAPHS
:Signal to noise 
:N:1,2:
$$
1/resol^2   <I/sigma_I>;_Signal_to_noise   $$ 
$$
0.002712   41.558514
0.006712   48.210668
0.010712   55.111410
0.014712   58.094531
0.018712   50.842331
0.022712   53.970565
0.026712   50.709842
0.030712   49.937942
0.034712   52.158748
0.038712   56.680222
0.042712   54.795525
0.046712   48.885322
0.050712   46.172199
0.054712   49.943605
0.058712   50.288807
0.062712   46.858021
0.066712   44.134868
0.070712   41.963730
0.074712   39.615144
0.078712   40.241414
0.082712   39.536438
0.086712   34.678416
0.090712   33.532391
0.094712   30.659793
0.098712   37.052083
0.102712   32.530150
0.106712   33.803838
0.110712   30.135997
0.114712   26.415375
0.118712   23.356197
0.122712   22.880738
0.126712   18.835880
0.130712   19.479908
0.134712   18.247018
0.138712   16.084521
0.142712   16.266695
0.146712   13.029576
0.150712   12.608841
0.154712   13.484375
0.158712   9.904316
$$

##----------------------------------------------------##
##                   Twinning Analyses                ##
##----------------------------------------------------##



Using data between 10.00 to 2.77 Angstrom.

Determining possible twin laws.

The following twin laws have been found:

-------------------------------------------------------------------------------
| Type | Axis   | R metric (%) | delta (le Page) | delta (Lebedev) | Twin law |
-------------------------------------------------------------------------------
|   M  | 2-fold | 0.000        | 0.000           | 0.000           | -h,-k,l  |
-------------------------------------------------------------------------------
M:  Merohedral twin law
PM: Pseudomerohedral twin law

  1 merohedral twin operators found
  0 pseudo-merohedral twin operators found
In total,   1 twin operator were found




Details of automated twin law derivation
----------------------------------------
Below, the results of the coset decomposition are given. 
Each coset represents a single twin law, and all symmetry equivalent twin laws are given.
For each coset, the operator in (x,y,z) and (h,k,l) notation are given. 
The direction of the axis (in fractional coordinates), the type and possible offsets are given as well.
Furthermore, the result of combining a certain coset with the input space group is listed.  
This table can be usefull when comparing twin laws generated by xtriage with those listed in lookup tables
In the table subgroup H denotes the *presumed intensity symmetry*. Group G is the symmetry of the lattice.

Left cosets of :
  subgroup  H: P 3 2 1
  and group G: P 6 2 2

  Coset number :     0   (all operators from H)

               x,y,z                 h,k,l   Rotation:    1 ; direction:  (0, 0, 0) ; screw/glide:    (0,0,0)
           x-y,-y,-z             h,-h-k,-l   Rotation:    2 ; direction:  (1, 0, 0) ; screw/glide:    (0,0,0)
          -x,-x+y,-z             -h-k,k,-l   Rotation:    2 ; direction:  (0, 1, 0) ; screw/glide:    (0,0,0)
              y,x,-z                k,h,-l   Rotation:    2 ; direction:  (1, 1, 0) ; screw/glide:    (0,0,0)
            -y,x-y,z              k,-h-k,l   Rotation:    3 ; direction:  (0, 0, 1) ; screw/glide:    (0,0,0)
           -x+y,-x,z              -h-k,h,l   Rotation:    3 ; direction:  (0, 0, 1) ; screw/glide:    (0,0,0)

  Coset number :     1   (H+coset[1] = P 6 2 2)

             -x,-y,z               -h,-k,l   Rotation:    2 ; direction:  (0, 0, 1) ; screw/glide:    (0,0,0)
            x,x-y,-z             h+k,-k,-l   Rotation:    2 ; direction:  (2, 1, 0) ; screw/glide:    (0,0,0)
            -y,-x,-z              -k,-h,-l   Rotation:    2 ; direction: (-1, 1, 0) ; screw/glide:    (0,0,0)
           -x+y,y,-z             -h,h+k,-l   Rotation:    2 ; direction:  (1, 2, 0) ; screw/glide:    (0,0,0)
             x-y,x,z              h+k,-h,l   Rotation:    6 ; direction:  (0, 0, 1) ; screw/glide:    (0,0,0)
            y,-x+y,z              -k,h+k,l   Rotation:    6 ; direction:  (0, 0, 1) ; screw/glide:    (0,0,0)

Note that if group H is centered (C,P,I,F), elements corresponding to centering operators are omitted.
(This is because internally the calculations are done with the symmetry of the reduced cell)






Splitting data in centrics and acentrics
  Number of centrics  : 790
  Number of acentrics : 2735

 Patterson analyses
------------------

 Largest Patterson peak with length larger than 15 Angstrom 

 Frac. coord.        :   0.327   -0.337    0.335
 Distance to origin  :  48.415
 Height (origin=100) :  25.223
 p_value(height)     :   3.302e-03

   The reported p_value has the following meaning: 
     The probability that a peak of the specified height 
     or larger is found in a Patterson function of a 
     macro molecule that does not have any translational
     pseudo symmetry is equal to  3.302e-03 
     p_values smaller than 0.05 might indicate 
     weak translational pseudo symmetry, or the self vector of 
     a large anomalous scatterer such as Hg, whereas values 
     smaller than 1e-3 are a very strong indication for 
     the presence of translational pseudo symmetry.


The full list of Patterson peaks is: 

  x      y      z            height   p-value(height)
( 0.327,-0.337, 0.335 ) :   25.223   (3.302e-03)
( 0.199, 0.394,-0.088 ) :    7.530   (4.073e-01)

 If the observed pseudo translationals are crystallographic
 the following spacegroups and unit cells are possible: 

 space group                operator         unit cell of reference setting  
   R 3 2 :h (-a,-b,c)   x+1/3, y-1/3, z+1/3  (43.26, 43.26, 123.93,  90.00, 90.00, 120.00)




Systematic absences
-------------------

The following table gives informaton about systematic absences.
For each operator, the reflections are split in three classes:
  Absent    : Reflections that are absent for this operator.
  Non Absent: Reflection of the same type (i.e. (0,0,l)) as above, but they should be present.
  Complement: All other reflections.
For each class, the <I/sigI> is reported, as well as the number of 'violations'. A 'violation'
is designated as a reflection for which a I/sigI criterion is not met. The criteria are

  Absent violation     : I/sigI > 3.0
  Non Absent violation : I/sigI < 3.0
  Complement violation : I/sigI < 3.0

Operators with low associated violations for *both* absent and non absent reflections, are likely to
be true screw axis or glide planes. Both the number of violations and their percentages are given.
The number of violations within the 'complement' class, can be used as a comparison for the number
of violations in the non-absent class.

This table is not used in determining the most suitable space group and is for reporting purposes only.


--------------------------------------------------------------------------------------------------------------------------------
| Operator | absent under operator  |          | not absent under operator  |              | all other reflections  |          |
|          |  <I/sigI> (violations) | n absent |  <I/sigI> (violations)     | n not absent |  <I/sigI> (violations) | n compl  |
--------------------------------------------------------------------------------------------------------------------------------
| 3_1 (c)  |     1.32  (0,  0.0%)   |        6 |    19.45  (0,  0.0%)       |        7     |    39.10  (128,  3.6%) |     3512 |
| 3_2 (c)  |     1.32  (0,  0.0%)   |        6 |    19.45  (0,  0.0%)       |        7     |    39.10  (128,  3.6%) |     3512 |
--------------------------------------------------------------------------------------------------------------------------------




Wilson ratio and moments 

Acentric reflections 
   <I^2>/<I>^2    :2.546   (untwinned: 2.000; perfect twin 1.500)
   <F>^2/<F^2>    :0.734   (untwinned: 0.785; perfect twin 0.885)
   <|E^2 - 1|>    :0.834   (untwinned: 0.736; perfect twin 0.541)


Centric reflections 
   <I^2>/<I>^2    :4.056   (untwinned: 3.000; perfect twin 2.000)
   <F>^2/<F^2>    :0.582   (untwinned: 0.637; perfect twin 0.785)
   <|E^2 - 1|>    :1.034   (untwinned: 0.968; perfect twin 0.736)



NZ test (0<=z<1) to detect twinning and possible translational NCS


-----------------------------------------------
|  Z  | Nac_obs | Nac_theo | Nc_obs | Nc_theo |
-----------------------------------------------
| 0.0 |   0.000 |    0.000 |  0.000 |   0.000 |
| 0.1 |   0.121 |    0.095 |  0.300 |   0.248 |
| 0.2 |   0.230 |    0.181 |  0.403 |   0.345 |
| 0.3 |   0.315 |    0.259 |  0.468 |   0.419 |
| 0.4 |   0.385 |    0.330 |  0.516 |   0.474 |
| 0.5 |   0.445 |    0.394 |  0.573 |   0.520 |
| 0.6 |   0.497 |    0.451 |  0.608 |   0.561 |
| 0.7 |   0.554 |    0.503 |  0.653 |   0.597 |
| 0.8 |   0.607 |    0.551 |  0.682 |   0.629 |
| 0.9 |   0.645 |    0.593 |  0.711 |   0.657 |
| 1.0 |   0.677 |    0.632 |  0.737 |   0.683 |
-----------------------------------------------
| Maximum deviation acentric      :  0.056    |
| Maximum deviation centric       :  0.057    |
|                                             |
| <NZ(obs)-NZ(twinned)>_acentric  : +0.044    |
| <NZ(obs)-NZ(twinned)>_centric   : +0.047    |
-----------------------------------------------


 L test for acentric data

 using difference vectors (dh,dk,dl) of the form: 
(3hp,3kp,3lp)
  where hp, kp, and lp are random signed integers such that 
  2 <= |dh| + |dk| + |dl| <= 8 

  Mean |L|   :0.534  (untwinned: 0.500; perfect twin: 0.375)
  Mean  L^2  :0.370  (untwinned: 0.333; perfect twin: 0.200)

  The distribution of |L| values indicates a twin fraction of
  0.00. Note that this estimate is not as reliable as obtained
  via a Britton plot or H-test if twin laws are available. 




$TABLE: NZ test:
$GRAPHS
:NZ test, acentric and centric data 
:A:1,2,3,4,5:
$$
z   Acentric_observed   Acentric_untwinned   Centric_observed   Centric_untwinned   $$ 
$$
0.000000   0.000000   0.000000   0.000000   0.000000
0.100000   0.121024   0.095200   0.300000   0.248100
0.200000   0.229616   0.181300   0.402532   0.345300
0.300000   0.315174   0.259200   0.468354   0.418700
0.400000   0.385375   0.329700   0.516456   0.473800
0.500000   0.445338   0.393500   0.573418   0.520500
0.600000   0.497258   0.451200   0.607595   0.561400
0.700000   0.553931   0.503400   0.653165   0.597200
0.800000   0.606947   0.550700   0.682278   0.628900
0.900000   0.644607   0.593400   0.711392   0.657200
1.000000   0.676782   0.632100   0.736709   0.683300
$$


$TABLE: L test,acentric data:
$GRAPHS
:L test, acentric data 
:A:1,2,3,4:
$$
|l|   Observed   Acentric_theory   Acentric_theory,_perfect_twin   $$ 
$$
0.000000   0.004787   0.000000   0.000000
0.020000   0.019681   0.020000   0.029996
0.040000   0.035638   0.040000   0.059968
0.060000   0.059043   0.060000   0.089892
0.080000   0.079255   0.080000   0.119744
0.100000   0.096809   0.100000   0.149500
0.120000   0.114362   0.120000   0.179136
0.140000   0.129787   0.140000   0.208628
0.160000   0.147340   0.160000   0.237952
0.180000   0.162766   0.180000   0.267084
0.200000   0.178191   0.200000   0.296000
0.220000   0.190957   0.220000   0.324676
0.240000   0.210638   0.240000   0.353088
0.260000   0.225532   0.260000   0.381212
0.280000   0.240957   0.280000   0.409024
0.300000   0.259043   0.300000   0.436500
0.320000   0.273936   0.320000   0.463616
0.340000   0.296277   0.340000   0.490348
0.360000   0.312766   0.360000   0.516672
0.380000   0.335106   0.380000   0.542564
0.400000   0.353723   0.400000   0.568000
0.420000   0.371277   0.420000   0.592956
0.440000   0.387766   0.440000   0.617408
0.460000   0.411170   0.460000   0.641332
0.480000   0.429255   0.480000   0.664704
0.500000   0.443617   0.500000   0.687500
0.520000   0.462234   0.520000   0.709696
0.540000   0.478191   0.540000   0.731268
0.560000   0.496809   0.560000   0.752192
0.580000   0.514362   0.580000   0.772444
0.600000   0.537234   0.600000   0.792000
0.620000   0.564894   0.620000   0.810836
0.640000   0.584574   0.640000   0.828928
0.660000   0.606383   0.660000   0.846252
0.680000   0.626064   0.680000   0.862784
0.700000   0.644149   0.700000   0.878500
0.720000   0.671809   0.720000   0.893376
0.740000   0.696277   0.740000   0.907388
0.760000   0.720745   0.760000   0.920512
0.780000   0.740957   0.780000   0.932724
0.800000   0.763298   0.800000   0.944000
0.820000   0.788830   0.820000   0.954316
0.840000   0.808511   0.840000   0.963648
0.860000   0.835106   0.860000   0.971972
0.880000   0.858511   0.880000   0.979264
0.900000   0.877128   0.900000   0.985500
0.920000   0.903723   0.920000   0.990656
0.940000   0.933511   0.940000   0.994708
0.960000   0.955319   0.960000   0.997632
0.980000   0.979255   0.980000   0.999404
$$

---------------------------------------------
 Analysing possible twin law :  -h,-k,l
---------------------------------------------


Results of the H-test on acentric data: 

 (Only 50.0% of the strongest twin pairs were used)

mean |H| : 0.470   (0.50: untwinned; 0.0: 50% twinned)
mean H^2 : 0.313   (0.33: untwinned; 0.0: 50% twinned)
Estimation of twin fraction via mean |H|: 0.030
Estimation of twin fraction via cum. dist. of H: 0.052



Britton analyses

  Extrapolation performed on  0.00 < alpha < 0.495 
  Estimated twin fraction: 0.000
  Correlation: 0.9992

R vs R statistic:
  R_abs_twin = <|I1-I2|>/<|I1+I2|>
  Lebedev, Vagin, Murshudov. Acta Cryst. (2006). D62, 83-95

   R_abs_twin observed data   : 0.532

  R_sq_twin = <(I1-I2)^2>/<(I1+I2)^2>
   R_sq_twin observed data    : 0.363
  No calculated data available.
  R_twin for calculated data not determined.


Maximum Likelihood twin fraction determination
    Zwart, Read, Grosse-Kunstleve & Adams, to be published.


   The estimated twin fraction is equal to 0.022



$TABLE: Britton plot for twin law -h,-k,l:
$GRAPHS
:percentage negatives 
:A:1,2,3:
$$
alpha   percentage_negatives   fit   $$ 
$$
0.000000   0.000000   0.000000
0.009901   0.004849   0.008680
0.019802   0.011563   0.017726
0.029703   0.021261   0.026771
0.039604   0.029467   0.035817
0.049505   0.039164   0.044863
0.059406   0.051100   0.053908
0.069307   0.057814   0.062954
0.079208   0.069750   0.072000
0.089109   0.079821   0.081045
0.099010   0.087281   0.090091
0.108911   0.096233   0.099137
0.118812   0.106304   0.108182
0.128713   0.116374   0.117228
0.138614   0.124953   0.126274
0.148515   0.136143   0.135319
0.158416   0.143976   0.144365
0.168317   0.151809   0.153411
0.178218   0.162999   0.162456
0.188119   0.178292   0.171502
0.198020   0.187990   0.180548
0.207921   0.198433   0.189593
0.217822   0.205147   0.198639
0.227723   0.213726   0.207685
0.237624   0.223051   0.216730
0.247525   0.230138   0.225776
0.257426   0.238717   0.234822
0.267327   0.248415   0.243867
0.277228   0.258486   0.252913
0.287129   0.268184   0.261959
0.297030   0.275643   0.271004
0.306931   0.284595   0.280050
0.316832   0.293547   0.289096
0.326733   0.302126   0.298141
0.336634   0.312570   0.307187
0.346535   0.321149   0.316233
0.356436   0.330101   0.325278
0.366337   0.339426   0.334324
0.376238   0.344648   0.343370
0.386139   0.353599   0.352415
0.396040   0.361059   0.361461
0.405941   0.367773   0.370507
0.415842   0.376352   0.379552
0.425743   0.383812   0.388598
0.435644   0.392018   0.397644
0.445545   0.397986   0.406689
0.455446   0.404327   0.415735
0.465347   0.416263   0.424781
0.475248   0.426706   0.433827
0.485149   0.437523   0.442872
$$


$TABLE: H test for possible twin law -h,-k,l:
$GRAPHS
:H test for Acentric data 
:A:1,2,3:
$$
H   Observed_S(H)   Fitted_S(H)   $$ 
$$
0.000000   0.089552   0.000000
0.020000   0.100000   0.022319
0.040000   0.119403   0.044638
0.060000   0.129851   0.066957
0.080000   0.158209   0.089275
0.100000   0.174627   0.111594
0.120000   0.180597   0.133913
0.140000   0.194030   0.156232
0.160000   0.204478   0.178551
0.180000   0.220896   0.200870
0.200000   0.244776   0.223188
0.220000   0.259701   0.245507
0.240000   0.274627   0.267826
0.260000   0.283582   0.290145
0.280000   0.302985   0.312464
0.300000   0.328358   0.334783
0.320000   0.341791   0.357101
0.340000   0.362687   0.379420
0.360000   0.382090   0.401739
0.380000   0.405970   0.424058
0.400000   0.425373   0.446377
0.420000   0.452239   0.468696
0.440000   0.468657   0.491014
0.460000   0.489552   0.513333
0.480000   0.507463   0.535652
0.500000   0.529851   0.557971
0.520000   0.541791   0.580290
0.540000   0.553731   0.602609
0.560000   0.577612   0.624928
0.580000   0.592537   0.647246
0.600000   0.611940   0.669565
0.620000   0.634328   0.691884
0.640000   0.661194   0.714203
0.660000   0.691045   0.736522
0.680000   0.710448   0.758841
0.700000   0.725373   0.781159
0.720000   0.737313   0.803478
0.740000   0.756716   0.825797
0.760000   0.782090   0.848116
0.780000   0.795522   0.870435
0.800000   0.823881   0.892754
0.820000   0.837313   0.915072
0.840000   0.858209   0.937391
0.860000   0.874627   0.959710
0.880000   0.894030   0.982029
0.900000   0.911940   1.000000
0.920000   0.931343   1.000000
0.940000   0.944776   1.000000
0.960000   0.974627   1.000000
0.980000   0.986567   1.000000
$$


$TABLE: Likelihood based twin fraction estimation for possible twin law -h,-k,l:
$GRAPHS
:Likelihood based twin fraction estimate 
:A:1,2:
$$
alpha   NLL_(acentric_data)   $$ 
$$
0.021739   7020.977159
0.043478   11760.012695
0.065217   16947.867573
0.086957   23543.797336
0.108696   31688.262064
0.130435   37528.493926
0.152174   44530.922921
0.173913   51673.406517
0.195652   58823.308852
0.217391   67457.153880
0.239130   75854.389098
0.260870   84429.779719
0.282609   91872.270240
0.304348   99286.722894
0.326087   107328.571565
0.347826   115128.181742
0.369565   123202.124071
0.391304   131242.202476
0.413043   139439.538050
0.434783   146479.738219
0.456522   153465.474153
0.478261   160008.890192
$$


Exploring higher metric symmetry

The point group of data as dictated by the space group is P 3 2 1
  the point group in the niggli setting is P 3 2 1
The point group of the lattice is P 6 2 2
A summary of R values for various possible point groups follow.

----------------------------------------------------------------------------------
| Point group | mean R_used | max R_used | mean R_unused | min R_unused | choice |
----------------------------------------------------------------------------------
| P 6 2 2     | 0.532       | 0.532      | None          | None         |        |
| P 3 2 1     | None        | None       | 0.532         | 0.532        | <---   |
----------------------------------------------------------------------------------

R_used: mean and maximum R value for symmetry operators *used* in this point group
R_unused: mean and minimum R value for symmetry operators *not used* in this point group
 The likely point group of the data is:  P 3 2 1

Possible space groups in this point groups are:
   Unit cell: (43.261, 43.261, 123.928, 90, 90, 120)
   Space group: P 3 2 1 (No. 150)

   Unit cell: (43.261, 43.261, 123.928, 90, 90, 120)
   Space group: P 31 2 1 (No. 152)

   Unit cell: (43.261, 43.261, 123.928, 90, 90, 120)
   Space group: P 32 2 1 (No. 154)

Note that this analysis does not take into account the effects of twinning.
If the data are (almost) perfectly twinned, the symmetry will appear to be
higher than it actually is.





-------------------------------------------------------------------------------
Twinning and intensity statistics summary (acentric data):

Statistics independent of twin laws
  - <I^2>/<I>^2 : 2.546
  - <F>^2/<F^2> : 0.734
  - <|E^2-1|>   : 0.834
  - 
, <L^2>: 0.534, 0.370
       Multivariate Z score L-test: 4.492 
       The multivariate Z score is a quality measure of the given
       spread in intensities. Good to reasonable data are expected
       to have a Z score lower than 3.5. 
       Large values can indicate twinning, but small values do not
       necessarily exclude it. 


Statistics depending on twin laws
-----------------------------------------------------------------
| Operator | type | R obs. | Britton alpha | H alpha | ML alpha |
-----------------------------------------------------------------
| -h,-k,l  |   M  | 0.532  | 0.000         | 0.052   | 0.022    |
-----------------------------------------------------------------

Patterson analyses
  - Largest peak height   : 25.223
   (corresponding p value : 0.00330)


The analyses of the Patterson function reveals a significant off-origin
peak that is 25.22 % of the origin peak, indicating pseudo translational symmetry.
The chance of finding a peak of this or larger height by random in a 
structure without pseudo translational symmetry is equal to the 3.3019e-03.
The detected tranlational NCS is most likely also responsible for the elevated intensity ratio.
See the relevant section of the logfile for more details.
The results of the L-test indicate that the intensity statistics
Show more centric character than is expected for acentric data.
This behavoir might be explained by the presence of the detected pseudo translation.

-------------------------------------------------------------------------------