This python project utilizes piecewise linear interpolation and least-squares approximation to analyze CPU temperature readings over time.
First, install the package:
poetry install
This program can then be run with:
poetry run tempgauge [text file]
Alternatively, activate the virtual environment first with poetry shell, then run:
tempgauge [text file]
The text file contains CPU temperature data in the following format, with each new line signifying a new reading at a different time:
[core1 temp] [core2 temp] ... [coreN temp]
...
[core1 temp] [core2 temp] ... [coreN temp]
If this program is run without any arguments, the following usage error
message will be outputted: usage: tempgague [-h] txt_file
Invalid text file formatting will not be checked for and will result in undefined behavior.
When this program is run with tempgauge resources/sample.txt, four output
files will be created, one for each core following the naming convention of core-{core_number}.txt.
As an example, core-0.txt will contain the following:
0 <= x <= 30; y = 61.0000 + 0.6333; interpolation
30 <= x <= 60; y = 98.0000 - 0.6000; interpolation
60 <= x <= 90; y = 20.0000 + 0.7000; interpolation
90 <= x <= 120; y = 128.0000 - 0.5000; interpolation
0 <= x <= 120; y = 67.4000 + 0.0567; least-squares
When this program is run with tempgauge resources/sensors-with-label.txt,
four output files with the aforementioned naming convention will be created.
core-0.txt will be populated with the following lines:
0 <= x <= 30; y = 65.0000 + 0.3667; interpolation
30 <= x <= 60; y = 75.0000 + 0.0333; interpolation
60 <= x <= 90; y = 73.0000 + 0.0667; interpolation
90 <= x <= 120; y = 88.0000 + -0.1000; interpolation
120 <= x <= 150; y = 68.0000 + 0.0667; interpolation
...
0 <= x <= 30690; y = 83.2340 + -0.0008; least-squares