Spitfire97
Regular
where do you recognize these cases from?
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Hang on. You're not counting the extra moves required to solve PLL (instead of CPLL) if you got a skipped CO. And, if you're talking about pure OCELL, you'd have to learn CP-ignoring EP algs for this case (just U and T perms thankfully), which would add roughly (7.667 * 1/27) to this figure.H | 11.33 | 2/27
Pi | 10.5 | 4/27
Hlight| 10 | 4/27
T | 9.67 | 4/27
Bowtie| 9.33 | 4/27
A-Sune| 8.5 | 4/27
Sune | 8.5 | 4/27
Solved| 0 | 1/27
Total for OCELL (htm)
= ((11+1/3)*2 + 10.5*4 + 10*4 + (9+2/3)*4 + (9+1/3)*4 + 8.5*8)/27
= 9 + 17/81
= 9.21
He does? It seems consistent with "inverse Sune," the accepted standard.Lars Petrus for example has a third definition http://lar5.com/cube/fas6.html![]()
He does? It seems consistent with "inverse Sune," the accepted standard.
Yeah, it does. It performs an "AntiSune" starting with F'.citing Lars site:
"At left: Doing Sune™ backwards (AntiSune) twists corners the same way as Sune™, but moves the edges differently"
If you take a look at the cube applet, it get's 100% clear.
does this preserve corner permutation?This is an alternative system for completing the last layer with edges pre-oriented. Suitable for ZZ, Petrus, VH or ZBF2L users. OCELL stands for: Orient Corners [permute] Edges Last Layer. It could also be called OCEPLL, but that would be a bit of a mouthfull :rolleyes:
The system is designed to do most of the work with 2-gen algorithms. Since edge permutation and corner orientation can both be solved 2-gen, combining them also can. It does it with a surprisingly low move count, when compared to COLL (the most similar alternative). I've generated all the 2-Gen algorithms for the system and calculated the move count statistics. Doing it non 2-gen is perfectly possible but takes away the system's principal advantage. After OCELL its CPLL (corner permute last layer). ~67% of the cases are A-perm, the rest are H-perm and E-perm, with a 1 in 12 chance of CPLL skip.
Case Recognition
The main issue with this method is recognition. Initial recognition of OCLL is extremely easy, but recognition of edge permutation is a little more challenging. The method I use is:
Look at two opposite edges, are they opposite colours?
... its a bit of a long winded explanation, but hopefully it makes sense!
- IF YES: its either SOLVED or OPPOSITE SWAP
Differentiating between solved, or opposite swap simply involves looking at any two adjacent edges. If they are positioned correctly relative to each other then its the SOLVED case, otherwise SWAP
- IF NO: Then there are 1 of 4 adjacent swap cases to choose from. First find two adjacent edges of opposite colour (the adjacent edges diagonally opposite will also have opposite colours). If your opposite coloured adjacent edges are in BL and FR then either UF/UL or UB/UR will need to be swapped, otherwise the swap will take place between either UB/UL or UF/UR.
To choose between the two options look at two opposite coloured edges of your choice, and then the non opposite coloured edge adjacent to each one. If they are correct relative to each other then its the other two which need swapped
2-Gen Algorithms
All move counts are FTM.
H (on side):
Solved 15 - R U R' U R U2 R' U' R' U2 R U R' U R
UF/UB: 13 - (y) R U2 R2 U2 R' U2 R U2 R' U2 R2 U2 R
UF/UL: 11 - (y) R' U2 R U R' U' R U R' U R
UF/UR: 11 - R U R' U R U' R' U R U2 R'
Avg: 12.0
Pi
Solved 15 - R U R2 U' R2 U' R2 U2 R2 U' R' U R U2 R'
. . . . . 15 - R U2 R2 U' R' U R2 U' R' U' R' U2 R' U2 R
UF/UB: 13 - R U R' U' R' U2 R U R' U R2 U2 R'
UF/UL: 13 - (y) R U R' U R U2 R2 U2 R U R' U R
UB/UL: 13 - (y) R U2 R' U' R U' R2 U' R U' R' U2 R
. . . . . 13 - (y') R' U' R U' R' U2 R2 U2 R' U' R U' R'
UF/UR: 9 - R U2 R2 U' R2 U' R2 U2 R
UB/UR: 9 - R' U2 R2 U R2 U R2 U2 R'
Avg: 12.0
Headlights
Solved 15 - (y) R2 U R U' R U R2 U' R2 U' R' U R' U' R2
UF/UB: 13 - R' U' R U' R' U2 R2 U R' U R U2 R'
UF/UL: 15 - R U2 R' U2 R2 U R' U R' U' R U R U2 R2
UB/UL: 13 - (y2) R U R' U R' U2 R2 U R2 U R2 U' R'
UF/UR: 15 - (y) R U' R U' R2 U2 R2 U R U' R2 U' R U2 R
UB/UR: 13 - R' U' R U' R U2 R2 U' R2 U' R2 U R
Avg: 14.0
T
Solved 15 - R U R' U R U2 R' U2 R' U' R U' R' U2 R
UF/UB: 13 - (y) R U2 R' U' R U' R2 U2 R U R' U R
UF/UL: 13 - R' U' R2 U R2 U R2 U2 R' U R' U R
UB/UL: 13 - R U R2 U' R2 U' R2 U2 R U' R U' R'
UF/UR: 15 - R U R' U' R2 U2 R' U R' U2 R U2 R U R2
UB/UR: 15 - R' U' R U R2 U2 R U' R U2 R' U2 R' U' R2
Avg: 14.0
Bowtie
Solved 15 - R U R' U R U' R' U R U' R' U R U2 R'
UF/UB: 15 - (y) R' U2 R U R' U R U2 R' U' R U' R' U2 R
UF/UL: 15 - R2 U R' U R' U2 R' U' R' U R2 U R U' R2
UB/UL: 15 - R U' R2 U R U2 R2 U R U2 R U2 R U' R2
UF/UR: 15 - (y) R U' R U' R2 U2 R2 U R U' R2 U' R U2 R
UB/UR: 15 - R U R2 U' R2 U' R U2 R U2 R' U2 R2 U2 R
Avg: 15.0
Anti-Sune
Solved 11 - R U R' U R' U' R2 U' R2 U2 R
UF/UB: 13 - (y') R U2 R2 U' R' U' R' U R U R2 U' R'
UF/UL: 7 - (y') R U2 R' U' R U' R'
UB/UL: 13 - (y') R2 U' R' U R U R' U2 R' U R2 U R2
UF/UR: 7 - (y2) R' U' R U' R' U2 R
UB/UR: 11 - (y2) R U2 R2 U2 R2 U R2 U R2 U' R'
Avg: 10.33
Sune
Solved 11 - (y2) R' U' R U' R U R2 U R2 U2 R'
UF/UB: 13 - R U R' U R2 U R U R2 U' R' U' R2
UF/UL: 7 - R U R' U R U2 R'
UB/UL: 11 - R' U2 R2 U2 R2 U' R2 U' R2 U R
UF/UR: 7 - (y') R' U2 R U R' U R
UB/UR: 13 - R2 U' R2 U' R U R2 U' R2 U R' U R2
. . . . . 13 - (y') R2 U R U' R' U' R U2 R U' R2 U' R2
Avg: 10.33
Total cases: 40
Move Count
Remember this is using only 2-gen algs for OCELL. The average optimal move count will be lower without these restrictions.
OCELL:
Case | Moves | Prob Occurance
------+-------+----------------
H | 12 | 2/27
Pi | 12 | 4/27
Hlight| 14 | 4/27
T | 14 | 4/27
Bowtie| 15 | 4/27
A-Sune| 10.33 | 4/27
Sune | 10.33 | 4/27
Solved| 10 | 1/27
Avg moves = (6*12 + 8*14 + 4*15 + 8*10.33 + 10)/27 ~= 12.47
CPLL:
Case | Moves | Prob Occurance
-------+-------+---------------
A(a) | 9 | 4/12
A(b) | 9 | 4/12
E | 14 | 2/12
H | 10 | 1/12
Solved | 0 | 1/12
Avg moves = (9*4*2 + 14*2 + 10)/12 ~= 9.17
To calculate average move counts the number of EP cases was counted as follows:
Total: 4! = 24, broken dowin into:
Solved: 4/24
Opposite Swap: 4/24
Adjacent Swap: 4 * 4/24 (16/24)
Total moves for OCELL = (6*12 + 8*14 + 4*15 + 8*10.33 + 10)/27 + (9*4*2 + 14*2 + 10)/12 + 0.75 ~= 22.38
does this preserve corner permutation?
If we got it to preserve corner permutation then we have a 1LLL from a 2-gen state.
I had an idea a while back of doing this but instead of solving the edges phasing them. Recognition is much easier(minimum number of sides to look at: 2 for phasing, and OCLL recog is trivial.), and the algorithm count is 14 new algs(and 7 OCLL that preserve phasing), and you also get 9 PLL algorithms, making it a good method for beginners.Thanks
With regards to move count:
COLL: 9.78 (source: http://www.ai.univ-paris8.fr/~bh/cube/)
EPLL: 8.75
2G EPLL: 10.75
AUF: 0.75
COLL/EPLL: 19.28
COLL/2G-EPLL: 21.28
2G OCELL/CPLL:
(see above for explanation)
Total: 22.38
Using optimal algs for COLL/EPLL gives a move count advantage of 2.73 over using 2G OCELL. If 2-gen algs are used for EPLL, then the move-count advantage is only 0.73. I haven't generated optimal algs for OCELL but I'd imagine the total move count wouldn't be a huge amount more than COLL.
The rationale behind using this method, however, is not to lower move counts. As we all know the order of about 20 moves can be significantly quicker if they are 2Gen. The problem with COLL is that its not 2-gen and some of the algs suffer as a result. Although its not 2G, CPLL is very quick, and easily comparable in speed to EPLL, however I'd argue that 2G OCELL could be executed faster than COLL by a competent speedcuber. The main problem (in my opinion) lies in the recognition...
Interesting, I don't know how I missed that!
I personally don't mind E perm, for me its about the same speed as Z. They also occur with the same probability in their respective sets.
I've not learned COLL so can't comment on how nice the algs are for me personally, but I've deffo heard bad things about them from other COLL users..