Hello,
In order to better understand the data resulting from any analysis, I want to sort them according to a single dimension and listen my fragments one by one. This way I could better understand each analysis parameter/axis.
Is there an easy way to achieve this? I’ve been trying to use the basic corpus-explorer example and transformed the dictionary dumped by the “normalised” dataset into lists to sort the data.
However:
I’ve noticed that the numerical keys in the dictionary are not numerically ordered. Keys 10 to 19 are before key 20, keys 21 to 29 are before key 3, etc. Is it a Max “feature” or is it caused by FluCoMa, and is it possible to reorder the keys to have them numerically ordered?
Whenever I put the dumped data into a dictionary and try to push them into a coll, it doesn’t function. Whenever opening the coll after export, I have Max crashing. What’s wrong?
Thank you in advance.
amundsen:
I’ve noticed that the numerical keys in the dictionary are not numerically ordered. Keys 10 to 19 are before key 20, keys 21 to 29 are before key 3, etc. Is it a Max “feature” or is it caused by FluCoMa, and is it possible to reorder the keys to have them numerically ordered?
This is how things are alphabetized by the OS. polybuffer~
and umenu
will list things in a similar order, which can be really confusing/annoying.
If you specifically want the order to be retained you can make sure the numbers are padded (e.g. “01, 02, 03…09, 10, 11, 12…”).
That being said, numbers in dictionaries (or datatsets (or colls)) can be queried independently of how they are stored, so if you want entry 9 followed by entry 10, you can just request those however you like. For most of my use case I let the order get all weird this way, but then make sure it’s consistent across everything so it doesn’t really matter.
Thank you Rodrigo. However how can one sort the segments according to any specific analysis dimension?
You can push the dict
into a coll
and then sort by any column
Yes but as I have written in the initial message I have an issue with this.
Sorry, missed that. How big is the dataset you’re working with?
That’s the dataset of the corpus-explorer example patcher.
Ok. Not sure about the crashes. But, it looks like push_to_coll
will still treat the IDs as symbols, which isn’t unreasonable, so if you want to sort by IDs as if they were numbers, then you’ll need to iterate through the dictionary converting the IDs and feeding to coll
:
<pre><code>
----------begin_max5_patcher----------
881.3ocyX97aaBCEG+L4uBKNsCoUf4Ggzy6xtOocnZpxAbZcFXivlllU0829
d1ljlt5PQgzjIk.0uX3q+7dO+rcedhm+BwSToO5FzsHOumm34YLoM3001yuh
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SM1yEkkn0LdgXMppUpPK.akBIs.5XApgJpobnwMW8ks5Tx3zbQK2HVbmQVgQ
ZwhUWkh21yZhJ+AF+96Z.ssjEEguNXJBiyz2BSBz2Rgqne18P71JFujpLLF9
pQQqZq0.swWlLQeY5HcVKEM4Z2.+QZijI3ZWz29pDoDHPzEfQjSvwN.OnGvC
SRMDOeevihtbf+CJZkNfulvUlTgBhh3+dpRx5ipXKU1nZGU3KX3TmYiJnxbJ
u.FpnEaPKYM.lELn+5.7PilIo8kFmDYhew3+ShlFtAXI6HGzh1vxIkP57fSg
Sh9XnwymclgthJkj6otgNDE3JqMbqQq1pM0TKE996FtNXDOGuWfMdtsX0gPD
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fW9cDkpgsnUYWKyaGud9TnbpggfocVpggCyLoDrlZLZ7amHu2JAi6v6Emdb4
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U2sdTxrKbsZSXrkWSx+kYuT23.0vrQENwoCIg8SedYC7Zg8K1VU6.wrwNsbt
8LAmsYkGJm8.7MtIjY1EcuvopKKaYEWqSRkT0efS5QJ2HYRWIriMZlDaybOp
RP6GNMOmYCr+ygjMRqs+V+fTzBmrqav1E3PupNbFAEiSTca931c3p6iSO8P0
Q+NB+.cxdyXohUTCaUQIe8nhvdKxv5qwYa+6QNrxFB9YmB9GhRQyNAJEMjPp
deBiVosuj9UJ4TnTxPTJ8TwT3PTJbrJkN.lzmoYzLgiOWJkDdbJYKiQpq69+
MYjQKBT3dknQ2LapoIiaaFYZ1Peb2IkLmexmz.UbUP411Fy.y+oT6Fo7qDEz
FdKqaUC.OPRyhBbBrZGrCE6CnW6XxKS9K7ERBiF
-----------end_max5_patcher-----------
</code></pre>
Meanwhile, the coll
docs are kind of misleading
counting through the dimensions seems to be zero-based
the first argument to sort
is the sorting direction, not the dimension
Also the window has to be closed and opened again to see any change
Thanks a lot @weefuzzy , you saved my day!
1 Like
@weefuzzy I finally had the time to test your code but it doesn’t help: the corpus explorer patcher still crashes as soon as I try to open the coll receiving the dict from the dataset.
Please have a look at the patcher below, modified to include your code.
----------begin_max5_patcher----------
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-----------end_max5_patcher-----------
I can’t make this crash (yet). Does it crash for you with anything you give it? I’m wondering if it’s to do with the number of slices.
If you get a beach ball before your crash, it suggests a threading issue of some sort. Although in the patch above, everything seems to happen on main thread
if it is a threading thing, I’m not sure what could be fighting with what: our code doesn’t know about the coll
Do you have any other patches open, audio on etc? (just trying to get a handle on the conditions needed to reproduce)
Could you remind me of your
max version
OS and version
overrdrive settings
Thank you for having a look to this issue, @weefuzzy .
Max version : 8.5.0.
OS: Windows 10-64bit
Overdrive : on + scheduler in audio interrupt : on
Audio if off.
However, it seems not to be related to FluCoMa: any attempt to open a coll will crash Max!
I’m mailing C74 support immediately!
The issue was linked to Max 8.5.0. An update to Max 8.5.2 has solved it.
So, your code functions @weefuzzy . However, the problem with data sorting in coll is that you can go to the first line by using a “goto” with a dummy index then iterate with next, but then you don’t get the index number itself, so you don’t know which segment the data extracted from the coll matches…
This is a bit discouraging. I am going to have a look at JS but I think this is all too complicated just to have the ability to listen to segments according to some dimension of the analysis.
next
gives me the associated index, but goto
doesn’t. Also goto
uses the associated index for lookup rather than the position (unlike nth
– seems like a bug to me). In any case, I’m slightly amazed that there isn’t a message that will just output the whole entry at a given position: next
works, but it’s an annoying interface.
Less effort than js is just to use jit.cellblock
to explore the coll
:
(Although, once you’re in js you can play with sqllite
and do all sorts of cool stuff)
Didn’t know jit.cellblock could be used with coll data. Nice.