Cold Clear 2 is a modern Tetris versus bot and a complete rewrite and evolution of Cold Clear. It implements the Tetris Bot Protocol for interaction with a frontend, such as Quadspace.
Cold Clear 2 is licensed under either Apache License Version 2.0 or MIT License, at your option.
Warning As with a lot of projects, this one is also a WIP, expect broken code 👍 smoothie-rs Temporary repository hosting the code for Smoothie's futu
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Create book from markdown files. Like Gitbook but implemented in Rust
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I'm not super familiar with rust, so my ability to debug the issue is fairly limited. I tried reading through the source, and it does seem like the deserialization present in CC2 is different than the current tbp-spec. Specifically, with how the start message is represented. Although, tbf, the documentation for the tbp-spec could just be leaving out some information that CC2 accounts for. Anyhow, on to the issue.
I've tried various forms of the start message, followed by a suggest message, all of which end in CC2 sending this suggestion:
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{
"type": "suggestion",
"moves": [],
"move_info": {
"nodes": 0,
"nps": 0.0,
"extra": "0.0% of selections expanded, overall speed: 0.0 Mnps"
}
}
As you can see, the moves list is empty, and the move_info represents that as well.
This could all be just me misinterpreting how start message is supposed to look as well, so if you could offer an example for me to test- that'd be greatly appreciated as well :')
i tried replacing hash map with [[[bool; 4]; 25]; 10] and got some improvement in finding underground locks, no improvement in finding above stack locks.
![faster move gen by replacing hash map with [[[bool; 4]; 25]; 10]](https://avatars.githubusercontent.com/u/79373642?v=4)
empty/I time: [3.9706 us 3.9844 us 3.9999 us]
change: [-0.4758% +0.0272% +0.5738%] (p = 0.92 > 0.05)
No change in performance detected.
Found 14 outliers among 100 measurements (14.00%)
2 (2.00%) high mild
12 (12.00%) high severe
empty/O time: [2.2432 us 2.2508 us 2.2600 us]
change: [-1.2114% -0.5206% +0.0680%] (p = 0.11 > 0.05)
No change in performance detected.
Found 11 outliers among 100 measurements (11.00%)
4 (4.00%) high mild
7 (7.00%) high severe
empty/T time: [4.3354 us 4.3541 us 4.3756 us]
change: [-0.3336% +0.4321% +1.1594%] (p = 0.26 > 0.05)
No change in performance detected.
Found 13 outliers among 100 measurements (13.00%)
8 (8.00%) high mild
5 (5.00%) high severe
empty/L time: [3.6484 us 3.6622 us 3.6776 us]
change: [-0.8810% -0.3863% +0.1238%] (p = 0.14 > 0.05)
No change in performance detected.
Found 15 outliers among 100 measurements (15.00%)
7 (7.00%) high mild
8 (8.00%) high severe
empty/J time: [3.6452 us 3.6559 us 3.6683 us]
change: [-0.5886% -0.1681% +0.3141%] (p = 0.47 > 0.05)
No change in performance detected.
Found 11 outliers among 100 measurements (11.00%)
3 (3.00%) high mild
8 (8.00%) high severe
empty/S time: [3.6630 us 3.6760 us 3.6919 us]
change: [-1.1938% -0.4172% +0.3716%] (p = 0.29 > 0.05)
No change in performance detected.
Found 14 outliers among 100 measurements (14.00%)
4 (4.00%) high mild
10 (10.00%) high severe
empty/Z time: [3.6418 us 3.6553 us 3.6712 us]
change: [-0.6419% -0.0282% +0.5809%] (p = 0.93 > 0.05)
No change in performance detected.
Found 13 outliers among 100 measurements (13.00%)
4 (4.00%) high mild
9 (9.00%) high severe
tspin/I time: [3.5904 us 3.5980 us 3.6066 us]
change: [-0.6264% +0.1900% +1.1189%] (p = 0.67 > 0.05)
No change in performance detected.
Found 15 outliers among 100 measurements (15.00%)
3 (3.00%) high mild
12 (12.00%) high severe
tspin/O time: [1.9749 us 1.9826 us 1.9911 us]
change: [-2.1759% -1.6861% -1.1658%] (p = 0.00 < 0.05)
Performance has improved.
Found 14 outliers among 100 measurements (14.00%)
6 (6.00%) high mild
8 (8.00%) high severe
tspin/T time: [4.4118 us 4.4245 us 4.4386 us]
change: [-10.940% -10.279% -9.6240%] (p = 0.00 < 0.05)
Performance has improved.
Found 12 outliers among 100 measurements (12.00%)
5 (5.00%) high mild
7 (7.00%) high severe
tspin/L time: [3.7636 us 3.7781 us 3.7954 us]
change: [-8.6718% -7.7160% -6.8341%] (p = 0.00 < 0.05)
Performance has improved.
Found 13 outliers among 100 measurements (13.00%)
2 (2.00%) high mild
11 (11.00%) high severe
tspin/J time: [3.7569 us 3.7667 us 3.7787 us]
change: [-8.2669% -7.4324% -6.6021%] (p = 0.00 < 0.05)
Performance has improved.
Found 16 outliers among 100 measurements (16.00%)
4 (4.00%) high mild
12 (12.00%) high severe
tspin/S time: [3.6540 us 3.6684 us 3.6848 us]
change: [+0.2953% +0.8696% +1.5409%] (p = 0.00 < 0.05)
Change within noise threshold.
Found 14 outliers among 100 measurements (14.00%)
5 (5.00%) high mild
9 (9.00%) high severe
tspin/Z time: [3.6600 us 3.6756 us 3.6926 us]
change: [-8.4859% -7.5394% -6.7363%] (p = 0.00 < 0.05)
Performance has improved.
Found 14 outliers among 100 measurements (14.00%)
7 (7.00%) high mild
7 (7.00%) high severe
dtd/I time: [4.0429 us 4.0727 us 4.1086 us]
change: [+0.1255% +0.7642% +1.4466%] (p = 0.02 < 0.05)
Change within noise threshold.
Found 19 outliers among 100 measurements (19.00%)
5 (5.00%) high mild
14 (14.00%) high severe
dtd/O time: [2.1878 us 2.1952 us 2.2049 us]
change: [-0.9129% -0.4554% +0.0186%] (p = 0.06 > 0.05)
No change in performance detected.
Found 16 outliers among 100 measurements (16.00%)
6 (6.00%) high mild
10 (10.00%) high severe
dtd/T time: [5.2238 us 5.2389 us 5.2568 us]
change: [-17.388% -16.791% -16.214%] (p = 0.00 < 0.05)
Performance has improved.
Found 18 outliers among 100 measurements (18.00%)
11 (11.00%) high mild
7 (7.00%) high severe
dtd/L time: [4.0684 us 4.0866 us 4.1099 us]
change: [-6.7258% -6.1156% -5.4530%] (p = 0.00 < 0.05)
Performance has improved.
Found 18 outliers among 100 measurements (18.00%)
7 (7.00%) high mild
11 (11.00%) high severe
dtd/J time: [4.2975 us 4.3066 us 4.3181 us]
change: [-10.494% -10.008% -9.5361%] (p = 0.00 < 0.05)
Performance has improved.
Found 11 outliers among 100 measurements (11.00%)
3 (3.00%) high mild
8 (8.00%) high severe
dtd/S time: [3.8563 us 3.8681 us 3.8824 us]
change: [-0.5871% -0.0810% +0.4407%] (p = 0.77 > 0.05)
No change in performance detected.
Found 15 outliers among 100 measurements (15.00%)
5 (5.00%) high mild
10 (10.00%) high severe
dtd/Z time: [3.8629 us 3.8732 us 3.8856 us]
change: [-11.044% -10.108% -9.3039%] (p = 0.00 < 0.05)
Performance has improved.
Found 10 outliers among 100 measurements (10.00%)
3 (3.00%) high mild
7 (7.00%) high severe
terrible/I time: [13.719 us 13.757 us 13.803 us]
change: [-74.513% -74.267% -74.037%] (p = 0.00 < 0.05)
Performance has improved.
Found 14 outliers among 100 measurements (14.00%)
8 (8.00%) high mild
6 (6.00%) high severe
terrible/O time: [7.6202 us 7.6441 us 7.6708 us]
change: [-54.877% -54.532% -54.187%] (p = 0.00 < 0.05)
Performance has improved.
Found 12 outliers among 100 measurements (12.00%)
3 (3.00%) high mild
9 (9.00%) high severe
terrible/T time: [11.857 us 11.904 us 11.960 us]
change: [-64.749% -64.279% -63.861%] (p = 0.00 < 0.05)
Performance has improved.
Found 16 outliers among 100 measurements (16.00%)
4 (4.00%) high mild
12 (12.00%) high severe
terrible/L time: [10.919 us 10.945 us 10.976 us]
change: [-63.691% -63.411% -63.151%] (p = 0.00 < 0.05)
Performance has improved.
Found 10 outliers among 100 measurements (10.00%)
1 (1.00%) high mild
9 (9.00%) high severe
terrible/J time: [11.059 us 11.088 us 11.121 us]
change: [-59.809% -59.588% -59.365%] (p = 0.00 < 0.05)
Performance has improved.
Found 10 outliers among 100 measurements (10.00%)
6 (6.00%) high mild
4 (4.00%) high severe
terrible/S time: [10.985 us 11.023 us 11.065 us]
change: [-76.858% -76.700% -76.525%] (p = 0.00 < 0.05)
Performance has improved.
Found 11 outliers among 100 measurements (11.00%)
8 (8.00%) high mild
3 (3.00%) high severe
terrible/Z time: [10.796 us 10.832 us 10.871 us]
change: [-72.138% -71.911% -71.706%] (p = 0.00 < 0.05)
Performance has improved.
Found 16 outliers among 100 measurements (16.00%)
8 (8.00%) high mild
8 (8.00%) high severe
I noticed a bug that after few moves, CC2 returns a suggestion message with no moves. (moves.length = 0)
When the piece queue was empty at the start message, CC2 delays the execution of bot.start().
After the first new_piece message, it will append the first piece to the queue and continue starting up.
But this causes a problem if seven_bag randomizer is used because this does not remove the first piece from bag_state. This state is invalid and makes speculation corrupted.
This PR fixes this bug by modifying the code to remove the first piece from bag_state correctly.
(Sorry if my English is unclear)
I got this error,(↓) but I don't know how to fix it. screen shot of the error Also, I would like to know the flags and options for cold clear, if you don't mind.
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