c9ef0f42a6
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| .. | ||
| README.md | ||
| __init__.py | ||
| azav.py | ||
| cell.py | ||
| dataReduction.py | ||
| example_main_salen.py | ||
| example_main_tiox.py | ||
| filters.py | ||
| id9.py | ||
| mask.py | ||
| peaks.py | ||
| utils.py | ||
| xray.py | ||
README.md
xray
Different utilities to work with time resolved solution/powder scattering data They should be extended to absorption soon
The idea is an hierarchical structure of modules
user → beamline → workhorses
Workhorses
azav.py: uses pyFAI to convert images into 1d curves dataReduction.py: works on the normalization, referencing and averaging.
Both modules uses some common utilities in utils.py including file based storage for persistency and convenience (numpy or hdf5 based); Indeed the data_storage class wraps around dictionaries allowing accessing with .attribute syntax. In utils plotfuncitons are presents
beamline
this step is needed to read the diagnostic information (time delay, monitors, etc). An example for current id9 data collection macros is given (id9.py). Essentially it means creating a dictionary where each key will be added to the main data dictionary (that has keys like q, data, files, etc.)
user
at the user level, a rather simple macro like the one provided as an example (example_main_tiox.py) should be sufficient for most needs.