Graphs a heatmap of short term fuel trims (STFTs) from a ME7Logger log for use in tuning the ME7.1 KFKHFM
MAF corrections map.
Given a log with nmot
rl
and fr/frm
data, it runs through each data point.
For every datapoint that is preceded by "similar" RPM/load samples (to throw out acceleration/deceleration points), sort it into a KFKFHFM
cell.
For each cell that has enough samples, calculate the average and convert the lambda correction to a trim percentage.
Each of the above filters can be tuned individually - see below.
Check the releases section of this repo. Download the zip file for windows or one of the source archives for MacOS/Linux.
Unzip the zip/tar file into an install directory.
pip3 install argparse matplotlib numpy pandas seaborn
See also requirements.txt
This is a command line utility. It does not have a GUI. If you don't know what cmd.exe
or /bin/sh
is, this tool is not for you.
C:\PATH\TO\HEATMAP\INSTALL\DIR\heatmap.exe log.csv
heatmap.exe C:\PATH\TO_\SV\log.csv
C:\PATH\TO\HEATMAP\INSTALL\DIR\heatmap.exe log.csv log2.csv log3.csv
You can also use the built in filename globbing to do this for you:
C:\PATH\TO\HEATMAP\INSTALL\DIR\heatmap.exe *.csv
chmod +x /path/to/heatmap/dir/src/heatmap.py
/path/to/heatmap/dir/src/heatmap.py log.csv
./heatmap.py /path/to/csv/log.csv
/path/to/heatmap/dir/src/heatmap.py log.csv log2.csv log3.csv
You can also use shell globbing to do this for you:
/path/to/heatmap_dir/src/heatmap.py *.csv
As usual, you can always add heatmap.py
or heatmap.exe
to your PATH
!
For pure text output, use --csv
or --text
- Adjust the "previous samples" amount with the
-w WINDOW
option - Adjust the "similar" load filter with the
-l LOAD_FILTER
option - Adjust the "similar" RPM filter with the
-r RPM_FILTER
option - Adjust the "minimum number of samples" filter with the
-s MIN_SAMPLES
option - Disable the filter entirely with
-n
- Show a continuous heatmap (instead of bucketed for KFKHFM) with
-c
- Choose
frm
instead offr
with the-fr
option - Choose an unweighted median using the
-u
option. The default is to average the samples weighted by their distance from the "center" of their cell (does not apply to-c
). Use-v
to see the difference between the weighted average and the mean.