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Try to understand crystal symmetry for two unit-cells
Unit cell 1: a=18, b=26, gamma=77
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# 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
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# 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 |
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.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
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./sim09-indexing.py -p |
Reconstruct simulated data,
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plot for hq vs omega
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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
- lattice for reconstructed angle omega
- 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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