Commit 03d17864 authored by Joanne Hugé's avatar Joanne Hugé

Update the report description

parent 394d746c
...@@ -13,11 +13,11 @@ import matplotlib.pyplot as plt ...@@ -13,11 +13,11 @@ import matplotlib.pyplot as plt
class MeasureSetHandler: class MeasureSetHandler:
report_description = ("This report was generated with the measure-analysis.py script. json formated measures " report_description = ("This report was generated with the measure-analysis.py script.\nJSON formated measures "
"were imported in the measures folder using the import functionnality of the script. This report was then " "were imported in the measures folder using the import functionnality of the script, this report was then "
"generated using these measures. Metadatas are included with the measures, such as the kernel " "generated using these measures.\nMetadata is included with the measures, such as the kernel "
"version used, the boot parameters passed, various others parameters specific to the measure, etc... " "version used, the boot parameters passed, various others parameters specific to the measure, etc... "
"Measures measuring the same propriety are grouped together in tables and graphs, and are identified " "\nMeasures measuring the same propriety are grouped together in tables and graphs, and are identified "
"by their diverging metadatas. This is useful to analyse the effect of specific parameters on the " "by their diverging metadatas. This is useful to analyse the effect of specific parameters on the "
"measured propriety.") "measured propriety.")
......
## Measurements ## Measurements
This report was generated with the measure-analysis.py script. json formated measures were imported in the measures folder using the import functionnality of the script. This report was then generated using these measures. Metadatas are included with the measures, such as the kernel version used, the boot parameters passed, various others parameters specific to the measure, etc... Measures measuring the same propriety are grouped together in tables and graphs, and are identified by their diverging metadatas. This is useful to analyse the effect of specific parameters on the measured propriety. This report was generated with the measure-analysis.py script.
JSON formated measures were imported in the measures folder using the import functionnality of the script, this report was then generated using these measures.
Metadata is included with the measures, such as the kernel version used, the boot parameters passed, various others parameters specific to the measure, etc...
Measures measuring the same propriety are grouped together in tables and graphs, and are identified by their diverging metadatas. This is useful to analyse the effect of specific parameters on the measured propriety.
### Abbreviations used ### Abbreviations used
......
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