On 10/12/06, Junio C Hamano <junkio@xxxxxxx> wrote:
apodtele <apodtele@xxxxxxxxx> writes:
> Instead of conditionally scaling the stat graph for large changes,
> always scale it asymptotically: small changes shall appear without any
> distortions.
I am not sure if any non-linear scaling is worth pursuing.
Suppose your change set has three files modified:
A adds 20 lines, deletes 10 lines
B adds 10 lines, deletes 20 lines
C adds 30 lines, deletes 30 lines
For obvious reasons, the total length of A and B exceeds half of
C, which looks quite misleading.
A | ++++++++++++--------
B | ++++++++------------
C | +++++++++++++++---------------
Before my patch is completely forgotten, let me critique the current
approach. Currently everything is great and beautiful unless one
particular change adds a couple of hundred lines, say, to a man page.
With large changes in play, small changes are squashed to a single
character. Would you argue that this scenario correctly represent
importance of man pages? Would you say, that it's not misleading that
1-, 2-, and 5-liners all look the same as long as a man page is
prominently shown? Moreover, 1-, 2-, and 5- liners may look different
depending on the size of that man page. The current approach is not
invariant; it is, however, normalized as needed. "Normalized" is good,
"as needed" is bad.
With asymptotic scaling, 1-, 2-, and 5- liners are correctly
represented by a correct number of characters, regardless of the size
of that man page. 10- and 20- liners are _slightly_ distorted. I
cannot stress it more: the representation will not depend on the size
of changes in other files! You will be able to tell where truly large
changes happened too! The price for this is that you won't be able to
precisely compare the sizes of added man pages.
It is your choice...
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