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-   -   ecm-toy now called ecm-effort (https://www.mersenneforum.org/showthread.php?t=23548)

fivemack 2018-08-02 10:08

ecm-toy now called ecm-effort
 
I've pushed ecm-toy to my GitHub, [url]https://github.com/fivemack/factorisation-tools[/url]

Happy to hear feature requests!

WraithX 2018-08-10 03:48

1 Attachment(s)
I ran the script with the example line: [c]ecm-effort.py G174 1000@11 tractor[/c] It ran for a while and then produced the following output:
[code]
And now NFS beats them
[[43, 15400], [110, 1400], [260, 1500]]
30..34 0.0000 0.0000
35..39 0.0000 0.0000
40..44 0.0000 0.0000
45..49 0.0006 0.0006
50..54 0.0594 0.0599
55..59 0.1709 0.2308
60..64 0.1844 0.4152
65..69 0.1645 0.5797
70..74 0.1434 0.7231
75..79 0.1255 0.8486
80..84 0.1107 0.9593
85..89 0.0407 1.0000
[/code]
When I plot the given recommended curves 15400@43e6, 1400@110e6, and 1500@260e6 on [URL="http://www.wraithx.net/math/ecmprobs/ecmprobs.html"]my ecm probabilities webpage[/URL] I get the attached plot, which has much different probability curves. Maybe we're not plotting the same thing? Or, if we are, then I'm not understanding why our numbers are different. Can you help me understand what the numbers in the above table mean?

fivemack 2018-08-10 07:57

[QUOTE=WraithX;493547]I ran the script with the example line: [c]ecm-effort.py G174 1000@11 tractor[/c] It ran for a while and then produced the following output:
[code]
And now NFS beats them
[[43, 15400], [110, 1400], [260, 1500]]
30..34 0.0000 0.0000
35..39 0.0000 0.0000
40..44 0.0000 0.0000
45..49 0.0006 0.0006
50..54 0.0594 0.0599
55..59 0.1709 0.2308
60..64 0.1844 0.4152
65..69 0.1645 0.5797
70..74 0.1434 0.7231
75..79 0.1255 0.8486
80..84 0.1107 0.9593
85..89 0.0407 1.0000
[/code]
When I plot the given recommended curves 15400@43e6, 1400@110e6, and 1500@260e6 on [URL="http://www.wraithx.net/math/ecmprobs/ecmprobs.html"]my ecm probabilities webpage[/URL] I get the attached plot, which has much different probability curves. Maybe we're not plotting the same thing? Or, if we are, then I'm not understanding why our numbers are different. Can you help me understand what the numbers in the above table mean?[/QUOTE]

The second column is the probability of a *remaining* factor of the given size for the given input after following the recipe, whilst I think you're plotting the probability, given that a number has a factor of some size, of finding it using the recipe.

So if you try the same recipe on larger and larger inputs with my code you will find the probability shifts towards the large factors, which are entirely intractable by ECM but exist with higher probability for larger inputs.


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