Hi Graeme,
Are you aware of the
mtz.object.as_miller_arrays(..., merge_equivalents=False) option?
If this is too high-level for your purposes, you can loop over the columns
and call:
column.extract_values(not_a_number_substitute=0.0)
You may also want to look at column.extract_valid_values() and
column.column.selection_valid() as an alternative. There are other
medium-level methods such as mtz_object.extract_integers() or
.extract_reals(). All the extract methods run in C++ and produce C++ arrays.
Ralf
On Tue, Apr 24, 2012 at 8:03 AM,
Hi Folks,
I have been writing very bad Python code to handle unmerged MTZ files using CCTBX - in essence copying all of the measurements to lists for each Miller index. Inefficient. Has anyone looked a neater way of handling these files perhaps with doing the "hard work" from C++? Reading the file is very easy, but managing the data is harder.
Essentially I would like to be able to read in a scaled-summed-but-unmerged MTZ file (equivalent to unmerged scale pack no-merge-original-index) and get back all observations of a given HKL, which I can then subsequently analyse…
I could crack on and write something but it strikes me as a good idea to ask first.
Thanks,
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