When CPU numbers are shown, the tooltip looks like this:

So it's something like this:
Category: [] Layout...
CPU Usage: 97% (...)
Stack:
parse_into()...
...
I'm concerned that we're mixing two "domains" of information, and it may give the wrong impression, e.g.: "Wow, this parse_into in layout is taking 97% of a CPU!".
But in fact, all we can say from this data is: Since the previous sample and now, we have used 97% of a CPU; And at this exact sample time we were calling parse_into in layout.
So I think we should clarify the difference.
Suggestion:
CPU Usage since previous sample: 97% (...)
.....................................................................................
Sample at time: 0.8465s
Category: [] Layout...
Stack:
parse_into()...
...
This clearly separates the more continuous CPU numbers from the point-like sample data.
As a bonus it shows the precise timestamp. I don't know how valuable that is, but for example it could help find markers at that time in the Marker Table.
┆Issue is synchronized with this Jira Task
When CPU numbers are shown, the tooltip looks like this:

So it's something like this:
I'm concerned that we're mixing two "domains" of information, and it may give the wrong impression, e.g.: "Wow, this parse_into in layout is taking 97% of a CPU!".
But in fact, all we can say from this data is: Since the previous sample and now, we have used 97% of a CPU; And at this exact sample time we were calling parse_into in layout.
So I think we should clarify the difference.
Suggestion:
This clearly separates the more continuous CPU numbers from the point-like sample data.
As a bonus it shows the precise timestamp. I don't know how valuable that is, but for example it could help find markers at that time in the Marker Table.
┆Issue is synchronized with this Jira Task