OptimizeLatticeForCellType dialog.
Table of Contents
| Name | Direction | Type | Default | Description |
|---|---|---|---|---|
| PeaksWorkspace | InOut | PeaksWorkspace | Mandatory | An input PeaksWorkspace with an instrument. |
| CellType | Input | string | Cubic | Select the cell type. Allowed values: [‘Cubic’, ‘Tetragonal’, ‘Orthorhombic’, ‘Hexagonal’, ‘Rhombohedral’, ‘Monoclinic’, ‘Monoclinic ( a unique )’, ‘Monoclinic ( b unique )’, ‘Monoclinic ( c unique )’, ‘Triclinic’] |
| Apply | Input | boolean | False | Re-index the peaks |
| PerRun | Input | boolean | False | Make per run orientation matrices |
| Tolerance | Input | number | 0.12 | Indexing Tolerance |
| EdgePixels | Input | number | 0 | Remove peaks that are at pixels this close to edge. |
| OutputChi2 | Output | number | Returns the goodness of the fit | |
| OutputDirectory | Input | string | . | The directory where the per run peaks files and orientation matrices will be written. |
This does a least squares fit between indexed peaks and Q values for a set of runs producing an overall leastSquare orientation matrix.
Get estimates of the standard deviations of the parameters, by approximating chisq by a quadratic polynomial through three points and finding the change in the parameter that would cause a change of 1 in chisq. (See Bevington, 2nd ed., pg 147, eqn: 8.13 ) In this version, we calculate a sequence of approximations for each parameter, with delta ranging over 10 orders of magnitude and keep the value in the sequence with the smallest relative change.
Example:
ws=LoadIsawPeaks("TOPAZ_3007.peaks")
FindUBUsingFFT(ws,MinD=8.0,MaxD=13.0)
print "Before Optimization:"
print ws.sample().getOrientedLattice().getUB()
OptimizeLatticeForCellType(ws,CellType="Monoclinic ( a unique )")
print "\nAfter Optimization:"
print ws.sample().getOrientedLattice().getUB()
Output:
Before Optimization:
[[ 0.01223576 0.00480107 0.08604016]
[-0.11654506 0.00178069 -0.00458823]
[-0.02737294 -0.08973552 -0.02525994]]
After Optimization:
[[-0.04772517 0.04134355 -0.00058175]
[-0.0055954 -0.00905383 0.12507404]
[ 0.06103109 0.03149982 0.01101201]]
Categories: Algorithms | Crystal