Script

sim08-make-index-table.py - generates lookup table and a few plots as shown below.

Unit cell

Try to understand crystal symmetry for two unit-cells

Unit cell 1: a=18, b=26, gamma=77

Unit cell 1
# file name: ./v01-sim-lut-cxifsimu-r0123-2017-04-25T09:52:17.txt
# photon energy = 6003.0000 eV
# wavelength = 2.0654 A
# wave number/Evald radius k = 1/lambda = 0.484172 1/A
# sigma_ql = 0.001453 1/A (approximately = k * <pixel size>/
# sigma_qt = 0.000484 1/A (approximately = k * <pixel size>/<sample-to-detector distance> = k*100um/100mm)
# 3*sigma_ql = 0.004358 1/A
# 3*sigma_qt = 0.001453 1/A
# Triclinic crystal cell parameters:
#   a = 18.36 A
#   b = 26.65 A
#   c = 4.81 A
#   alpha = 90.00 deg
#   beta  = 90.00 deg
#   gamma = 77.17 deg

# 3-d space primitive vectors:
#   a1 = ( 18.360000,   0.000000,   0.000000)
#   a2 = (  5.917874,  25.984635,   0.000000)
#   a3 = (  0.000000,   0.000000,   4.810000)
# reciprocal space primitive vectors:
#   b1 = (  0.054466,  -0.012404,   0.000000)
#   b2 = (  0.000000,   0.038484,   0.000000)
#   b3 = (  0.000000,   0.000000,   0.207900)

Unit cell 2: a=26, b=18, gamma=77

Unit cell 2
# file name: ./v01-sim-lut-cxifsimu-r0123-2017-04-25T10:18:21.txt
# photon energy = 6003.0000 eV
# wavelength = 2.0654 A
# wave number/Evald radius k = 1/lambda = 0.484172 1/A
# sigma_ql = 0.001453 1/A (approximately = k * <pixel size>/
# sigma_qt = 0.000484 1/A (approximately = k * <pixel size>/<sample-to-detector distance> = k*100um/100mm)
# 3*sigma_ql = 0.004358 1/A
# 3*sigma_qt = 0.001453 1/A
# Triclinic crystal cell parameters:
#   a = 26.65 A
#   b = 18.36 A
#   c = 4.81 A
#   alpha = 90.00 deg
#   beta  = 90.00 deg
#   gamma = 77.17 deg
# 3-d space primitive vectors:
#   a1 = ( 26.650000,   0.000000,   0.000000)
#   a2 = (  4.077004,  17.901610,   0.000000)
#   a3 = (  0.000000,   0.000000,   4.810000)
# reciprocal space primitive vectors:
#   b1 = (  0.037523,  -0.008546,   0.000000)
#   b2 = (  0.000000,   0.055861,   0.000000)
#   b3 = (  0.000000,   0.000000,   0.207900)

 

Presumably maps (qh vs omega) should be the same up to rotations.

Lookup table and maps

Unit cell 1

beta = 0 and 180

 

Unit cell 2

beta = 0 and 180

Indexing script

./sim09-indexing.py -p

Reconstruct simulated data, plot for hq vs omega

Comparison of look-up table and reconstructed sample

  • All maps are consistent after appropriate rotation
  • almost all lattice nodes can be reconstructed (are included in 2-peak events)

Friquency distributions at indexing

Reconstructed omega vs simulated

Reconstructed lattice

  1. lattice for reconstructed angle omega
  2. lattice for simulated angle omega

l=1 lattice for phi, beta, omega reconstructed for l=0, take the l=1 slice from Fraser's plot and transform it to reciprocal space.

This is a mess and not clear why...

To do

  • lower threshold for peakfinder
  • reason for bad phi-beta fits

 

 

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