Add a new performance-log-progressive-coalesce.py tool, which
coalesces partial address maps in progressive performacne logs into
a single global address map, suitable for processing by the rest of
the tools.
Use the new tool as part of the pipeline in performance-log-viewer.
Add a new performance-log-close-tags.py tool, which closes unclosed
tags in incomplete performance logs, allowing the rest of the
perofmance-log tools to process them. This is necessary for
unfinished progressive logs.
Use the new tool as part of the pipeline in performance-log-viewer.
Add a new performance-log-coalesce.py tool, which groups together
performance-log address-map entries belonging to the same function
into a single symbol, by filling-in missing base symbol addresses.
The addresses are grouped such that each set of addresses
corresponding to a symbol of the same name, in the same source
file, are given the same (unique, but arbitrary) base address.
See the previous commit for why this is necessary.
This should work fine in most cases, however, for logs produced on
Windows, it can over-coalesce addresses belonging to different C++
lambda-functions in the same source file, since they all seem to be
given the same _FUN symbol name.
Use the new tool as part of the pipeline in performance-log-viewer.
performance-log-viewer.py is a viewer for GIMP performance logs.
The viewer is made up of two parts: a sample-selection area at the
top, and an information area at the bottom.
The sample-selection area visualizes the sampled variables and
markers using a simultaneous set of plots, and displays the
currently selected samples. Samples can be selected directly
through the sample-selection area, or by other means, such as
searching for all samples satisfying a certain condition, or
containing a certain function.
The information area shows global information stored in the log, as
well as information specific to the currently selected samples,
including variable listing and statistics, full backtrace, and
profile/call-graph information.
Note that performance-log-viewer.py takes its input from STDIN,
like the rest of the performance-log tools, and is therefore
suitable for use as part of a pipeline. For standalone use, the
performance-log-viewer driver is also included, which takes the log
file as a command-line argument, and processes it through an
appropriate pipeline before feeding it to the viewer.
Ell