Suggestions

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Batch correct multiple entries in the same timeline

Long train rides are usually recorded as many small items with different activity types (16min cycling, 19min train, 8min running, …) I had a train ride with 20 segments recently. A batch correction (mark them all, set them to “train”) would help.

13 votes

Tagged as Suggestion

Suggested 15 April 2019 by user moritz

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  • 15 April 2019 moritz suggested this task

  • avatar

    Typically what should happen is that as soon as you confirm the first segment (the first segment that Arc asks you to confirm), some of the other segments should auto correct, based on that new information.

    So it might start out as 20, but after the first confirm it might drop to 10, then after the second confirm it might drop to 5, etc.

    So the intention is that instead of having to confirm/correct all of them, Arc will do most of that work for you, based on the new information you provide.

    16 April 2019
  • 16 April 2019 Matt Greenfield approved this task

  • avatar

    Basically my thinking is that the current approach is better than a batch confirm approach, because it means that you only need to confirm a fraction of the unconfirmed items. With a batch confirm system, you’d have to confirm all of them, because you’d be multi selecting them at the start, so the processing engine wouldn’t get a chance to reduce the burden for you.

    16 April 2019
  • avatar

    Your approach is better, but takes more time when processing is as slow as it is right now. Sometimes it takes me half an hour to clean up a long car ride because I have to wait for the processing to merge the next items before doing the next correction… If this could be fixed, I’m with you.

    04 July 2019
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    Hmm. Processing shouldn’t be taking that long. So yeah, that’s something that needs looking into, and needs to be fixed.

    05 July 2019
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    Over the several years of using arc, i have perhaps thousands if not more of arc detailing “cycling” instead of “motorbike”. It would be nice if I could just batch correct every single “cycle” to “motorbike” as I have never cycled once in these years.

    Re correcting them as they were initially happening. It is just too inconvenient, especially when doing month long motorbike trips.

    01 August 2019
  • avatar

    Benjamin, if you’re experiencing Arc making repeated mistakes for a common route, then please contact me via the “Feedback & Support” button in the app, so that we can debug the problem! That shouldn’t be happening, so we should gather up the necessary data and find out what’s going wrong on your phone.

    02 August 2019
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    Adding to this, sometimes I have erroneous “stops” all through a trip, basically whenever I’ve been stuck at a traffic light for 2 minutes or more. I’d like to be able to batch select stops and change them to “motorcycle”, rather than processing separately.

    20 November 2019
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    Noah, for those it’s better to delete the visit rather than change it to motorcycle. That way the correct “stationary” state is retained, but by deleting it you get it merged into the surrounding trip items. From there you still have the stationary segment inside the trip item, to indicate that you weren’t going anywhere at that time. That also allows you to extract that back out as a visit later on, if you want.

    That doesn’t invalidate the idea of a batch correction feature though. Just a tangential thing that I thought I’d point out 😉

    22 November 2019
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    This is kinda fixed now with the Clean up timeline action, right?

    07 November 2023
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    True! As long as the problem is the segments inside a timeline item, rather than actual messes of timeline items themselves.

    08 November 2023
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    The initial problem was multiple timeline items. Travelling over longer distances, you’re passing through different models and I typically get dozens of timeline items which I need to merge (by confirming each one separately). Just had thos happen two days ago.

    08 November 2023
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    Hmm. Hopefully that can be resolved by improvements to the shared models / fixing of the bug in the shared models / addition of local CD1 and CD0 models. Will have to see how it shakes out.

    09 November 2023