******************* This email originates from outside Imperial. Do not click on links and attachments unless you recognise the sender. If you trust the sender, add them to your safe senders list https://spam.ic.ac.uk/SpamConsole/Senders.aspx to disable email stamping for this address. ******************* Hello Nektar, Where can I find the indexing convention for field data and how it translates to spatial coordinates, and do I even need this information for postprocessing .fld files with python? I would like to read my velocity field, dealiase it by the cell boundaries, and save it in a new .fld file which I can then convert to .dat or .plt. I had looked at NekPy for this but could only find information about preprocessing when I am interested in postprocessing. So far I have been using the PyTables library to read the field file and .nekg mesh file. I have gained some useful insight from this but I can see it taking a lot of time and effort to decode the indexing and there are several other issues I will encounter along the way before I have full control over the fields. Before I continue down this path, could anyone advise me if this is the best way to go about my postprocessing? I would like to continue using python if possible but am open to other suggestions. Also, how is the data arranged within cells when NUMMODES>2? Thank you, Isaac