This is an update on my own python-based cccam tool collection.
Everything is written in python and its only tested with Ubuntu Linux - all major platforms should be possible to support but I expect minor problems here and there.
The package contains a readme txt describing all tools. The tool which is actually useful is ecmstats.py:
ecmstats.py
a tool to collect ecm times and plot graphical statistics for comparison.
You get a nice "histogram-like" distribution plot ( "cumulative distribution function" to be exact) describing an ecm timing in detail.
I believe that this could become a great tool to evaluate peers. However, do not expect too much, its just the first test version. Im not sure how useful this really is, I still need to start playing with it in detail. However, I might not find much time for it in the near future, so feedback would also be great ;-)
See the following example:
see the readme for details.
how to read the plot:
Values at the left end of the plot, at x=0,
represent the best ecm times ever seen for this share, the right end, at x=1 shows the highest ecm times seen.
The X-Axis represents probability between 0 and 1:
(numbers are made up and not connected to the images above...)
A value of 0.8 at position x=0 means:
you have a 0% chance to get ecm times better than 0.8s - its the best value
A value of 0.9 at position x=0.5 means:
you have a 50% chance to get ecm times better than 0.9s - every second sample is worse
A value of 1.2 at position x=0.9 means:
you have a 90% chance to get ecm times better than 1.2s - only every tenth sample is worse
In general, the statistics curve should be as flat as possible.
gracias a phluxx
Everything is written in python and its only tested with Ubuntu Linux - all major platforms should be possible to support but I expect minor problems here and there.
The package contains a readme txt describing all tools. The tool which is actually useful is ecmstats.py:
ecmstats.py
a tool to collect ecm times and plot graphical statistics for comparison.
You get a nice "histogram-like" distribution plot ( "cumulative distribution function" to be exact) describing an ecm timing in detail.
I believe that this could become a great tool to evaluate peers. However, do not expect too much, its just the first test version. Im not sure how useful this really is, I still need to start playing with it in detail. However, I might not find much time for it in the near future, so feedback would also be great ;-)
See the following example:
see the readme for details.
how to read the plot:
Values at the left end of the plot, at x=0,
represent the best ecm times ever seen for this share, the right end, at x=1 shows the highest ecm times seen.
The X-Axis represents probability between 0 and 1:
(numbers are made up and not connected to the images above...)
A value of 0.8 at position x=0 means:
you have a 0% chance to get ecm times better than 0.8s - its the best value
A value of 0.9 at position x=0.5 means:
you have a 50% chance to get ecm times better than 0.9s - every second sample is worse
A value of 1.2 at position x=0.9 means:
you have a 90% chance to get ecm times better than 1.2s - only every tenth sample is worse
In general, the statistics curve should be as flat as possible.
gracias a phluxx