On Tue, 4 Aug 2020 at 18:45, Robert Oeffner <[email protected]> wrote:

Thanks Aaron, I was aware of the merge_equivalents function. My interest is just for doing some testing on my code which involves reading and writing unmerged data. I guess I could always use the iotbx.mtz functions and write individual mtz columns including separate HKL indices to a file.

Rob

On 04-08-2020 18:03, Aaron Brewster wrote:

Hi Rob, I don't know how to create an unmerged mtz file, but if you want to merge the data you can use the cctbx miller array function merge_equivalents:

mtzobj = millarr.merge_equivalents().as_mtz_dataset(column_root_label="I")

I believe it does simple weighted averaging of the data using the sigmas.

-Aaron

On Tue, Aug 4, 2020 at 6:16 AM Robert Oeffner <[email protected]> wrote:

Hi,

Does anybody know how to convert a miller array of unmerged data to an mtz object? For merged data I do something like this:

mtzobj = millarr.as_mtz_dataset(column_root_label="I")

But if millarr contains multiple observations with the same hkl index. Then the above code fails with the exception

cctbx Error: Duplicate entries in miller_indices array.

Any suggestions?

Many thanks,

Rob