ImageD11.scalem | index /sware/exp/fable/standalone/redhate4-a64/lib/python2.5/site-packages/ImageD11/scalem.py

`Module(s) for scaling peaks
- Read in a series of columnfile type objects
collection of columnfiles
- Read in some symmetry information:
there are 32 crystallographic point groups
11 contain a centre of symmetry and are also laue groups
- For each peak
assign it a unique "key" in a list of reflections
typically h>=k>=l of the symmetry equivalents
Give it a scale factor (or two)
Compute the corrected intensity and derivative w.r.t scale factors
- For each uniq key compute the average group intensity
with or without median style filtering
- Compute the overall R(int) merging statistic and minimise that w.r.t scaling
variables
- Optimise scale factor variables`

Modules
`` |  |
ImageD11.columnfile |  |  |

Classes
`` |  | __builtin__.object data_table scalem
class data_table(__builtin__.object)
`` | `Wraps a columnfile/hklf4/brukerraw file Gives h,k,l - variables [scales per frame, scan, grain etc] - derivatives [of all variables] To constrain grain scale factors across different scans imply we need to have grains in same datafile.`
| Methods defined here: __init__(self) `Initialise some variables` calc(self) get_hkls(self) `Return the hkl indices of the peaks` set_keys(self, keys) `Store a list of uniq keys which go with each peak These are used to group peaks into symmetry equivalents` Data descriptors defined here: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)`
class scalem(__builtin__.object)
`` | `This class holds a series of tables (assumes everything fits in memory) ... and does some fitting`
| Methods defined here: __init__(self) `Holds a list of unmerged data tables These correspond to a single scans containing N grains` add_data(self, filename, format='ImageD11') `Read a columnfile object. Allowed to have format == ImageD11|bruker|hklf4` calc(self) `Compute for each data object: Columns: I_corr, sigma_corr Foreach scaling variable: dI_corr/dvar, dsigma_corr/dvar` set_sym(self, sym) `Set the symmetry to sym - list of matrices (3x3) - list of operators (4x4) - string (eg m3m etc)` Data descriptors defined here: __dict__ `dictionary for instance variables (if defined)` __weakref__ `list of weak references to the object (if defined)`

Functions
`` |  | generate_key(hkl, symmops) `To be redone in C/fortran etc Expect identity to be in symmops All symmetry matrices, not including inversion`