![]() ![]() psydat files, import each into an ExperimentHandler, and then call. So if you want consistent data output despite the differing versions used, (I think) you could iterate over all of the. psydat files are basically freeze-dried representations of your experiment handler objects. Not sure if you’re aware of this (I’ve never done it myself, and perhaps this is the approach you’re already taking), but the. In your case, it sounds like you might have two different installations running in parallel, which is equivalent to changing version in series. Even if those changes improve performance, the inconsistency is undesirable. So our strong recommendation is to never change PsychoPy versions during data collection for a given study, precisely because ongoing development can introduce unexpected changes, in either performance or output. If those installations have different versions of PsychoPy, then yes, the underlying code might differ (due to bug fixes or new features, etc), with the effect that variables might be being written in a different order, or even that entirely new variables are added. Presumably, the order is constant between runs within each installation. Not wanting to belabour the point, but the issue as reported isn’t between experimental runs, but between different installations. This is why we were very surprised to find key ordering change between experimental runs. Yes, although I’d always prefer a more thorough solution which does not involve local forks of an ever-updating environment. ![]() Solution 2: You can monkey-patch any Python function. IMHO, it’s problematic for any software to produce different results with the same input data if no random process is deliberately involved. There are myriads of use cases where data is written to a csv/tsv file and then analyzed by third party software which might rely on a specific order of columns, regardless of there being better options. However, I find this is not the issue here. ![]() You are completely correct that an integrated path of analysis would be preferrable. Solution1: Coding your analysis rather than doing manual imports into an Excel file scales much better. However, since the ExperimentHandler class uses Python dictionaries to store information, the PsychoPy version should not be an issue. It might be dependent on the PsychoPy version. Issue 1: By “depending on the computer”, do you actually mean “depending on the version of PsychoPy”? ![]()
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