Christopher D. Long octonion
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octonion
/ GAME_MASTER_v0_1.protobuf
Created
July 17, 2016 03:38
— forked from anonymous/GAME_MASTER_v0_1.protobuf
Pokemon Go decoded GAME_MASTER protobuf file v0.1
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| Result: 1 | |
| Items { | |
| TemplateId: "BADGE_BATTLE_ATTACK_WON" | |
| Badge { | |
| BadgeType: BADGE_BATTLE_ATTACK_WON | |
| BadgeRanks: 4 | |
| Targets: "\nd\350\007" | |
| } | |
| } | |
| Items { |
octonion
/ GAME_MASTER_POKEMON_v0_2.tsv
Created
July 17, 2016 03:37
— forked from anonymous/GAME_MASTER_POKEMON_v0_2.tsv
Pokemon from GAME_MASTER protobuf file v0.2 in a .tsv
We can make this file beautiful and searchable if this error is corrected: It looks like row 3 should actually have 27 columns, instead of 12 in line 2.
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| PkMn BaseStamina BaseAttack BaseDefense Type1 Type2 BaseCaptureRate BaseFleeRate CollisionRadiusM CollisionHeightM CollisionHeadRadiusM MovementType MovementTimerS JumpTimeS AttackTimerS QuickMoves CinematicMoves AnimTime Evolution EvolutionPips PokemonClass PokedexHeightM PokedexWeightKg HeightStdDev WeightStdDev FamilyId CandyToEvolve | |
| 1 90 126 126 HoloPokemonType.POKEMON_TYPE_GRASS HoloPokemonType.POKEMON_TYPE_POISON 0.1599999964237213 0.10000000149011612 0.3815000057220459 0.6539999842643738 0.27250000834465027 HoloPokemonMovementType.POKEMON_ENC_MOVEMENT_JUMP 10.0 1.149999976158142 29.0 d601dd01 5a3b76 6d56d53fdaac2a3f6d56d53f93a9ea3f0000000036ab0a403333b33fbfbbbb3f 02 HoloPokemonClass.POKEMON_CLASS_NORMAL 1 0.699999988079071 6.900000095367432 0.08749999850988388 0.862500011920929 HoloPokemonFamilyId.V0001_FAMILY_BULBASAUR 25 | |
| 2 120 156 158 HoloPokemonType.POKEMON_TYPE_GRASS HoloPokemonType.POKEMON_TYPE_POISON 0.07999999821186066 0.07000000029802322 0.3187499940395355 0.637499988079071 0.2549999952316284 H |
octonion
/ cbse_2013_subjects.txt
Created
February 27, 2015 04:46
Difficulty ranking and number of students for 2013 CBSE exams
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| subject | diff | n | |
| --------------------+--------+-------- | |
| SPANISH | -2.872 | 1 | |
| PHILOSOPHY | -2.278 | 150 | |
| MATHEMATICS | -1.622 | 518181 | |
| JAPANESE | -1.544 | 13 | |
| GERMAN | -1.481 | 38 | |
| FRENCH | -1.394 | 63 | |
| BUSINESS STUDIES | -1.166 | 8110 | |
| ECONOMICS | -1.155 | 351796 |
octonion
/ pbe_funding.txt
Created
February 10, 2015 22:46
California PBE and Public/Private/Charter: Output
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| > joined$Funding <- as.factor(joined$Funding) | |
| > joined$Public.Private <- as.factor(joined$Public.Private) | |
| > | |
| > summary(joined$Funding) | |
| aPublic Directly funded Locally funded | |
| 5153 382 172 | |
| Not in CS funding model Private | |
| 7 1667 | |
| > summary(joined$Public.Private) | |
| PRIVATE PUBLIC |
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| library(lme4) | |
| rates <- read.csv("data/cakd1314.csv", header=TRUE, stringsAsFactors=FALSE) | |
| poverty <- read.csv("data/frpm1314.csv", header=TRUE, stringsAsFactors=FALSE) | |
| dim(rates) | |
| dim(poverty) | |
| joined <- merge(rates, poverty, by="School.Code", all.x=TRUE) | |
| dim(joined) | |
| joined$School <- as.factor(paste(joined$County, ":" , joined$City, ":", joined$School.Name.x, sep="")) |
octonion
/ public_private_fixef.txt
Created
February 8, 2015 02:54
California Public vs Private PBE Rates: Fixed Effect Estimates
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| Fixed effects: | |
| Estimate Std. Error z value Pr(>|z|) | |
| (Intercept) -3.11319 0.14830 -20.99 <2e-16 *** | |
| PUBLIC.PRIVATEPUBLIC -0.60601 0.04971 -12.19 <2e-16 *** | |
| --- | |
| Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 |
octonion
/ public_private_anova.txt
Created
February 8, 2015 02:48
California PBE Public vs Private ANOVA
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| > anova(fit0,fit1) | |
| Data: rates | |
| Models: | |
| fit0: cbind(PBE., ENROLLMENT - PBE.) ~ (1 | COUNTY) + (1 | CITY) + | |
| fit0: (1 | SCHOOL) | |
| fit1: cbind(PBE., ENROLLMENT - PBE.) ~ (1 | COUNTY) + (1 | CITY) + | |
| fit1: (1 | SCHOOL) + PUBLIC.PRIVATE | |
| Df AIC BIC logLik deviance Chisq Chi Df Pr(>Chisq) | |
| fit0 4 25964 25991 -12978 25956 | |
| fit1 5 25841 25875 -12915 25831 124.95 1 < 2.2e-16 *** |
octonion
/ public_private.R
Created
February 8, 2015 02:44
California Public vs Private Schools and Personal Belief Exemptions
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| library(lme4) | |
| rates <- read.csv("data/cakd1314.csv", header=TRUE) | |
| head(rates) | |
| summary(rates) | |
| colnames(rates) | |
| rates$SCHOOL <- paste(rates$COUNTY, ":" , rates$CITY, ":", rates$SCHOOL.NAME, sep="") | |
| rates$CITY <- paste(rates$COUNTY, ":" , rates$CITY, sep="") |
octonion
/ waldo69.sol
Created
February 7, 2015 23:13
Where's Waldo as a Traveling Salesman Problem: Solution
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| 68 | |
| 0 7 5 1 2 6 4 8 48 46 | |
| 45 42 43 55 44 47 50 51 49 3 | |
| 34 33 35 36 41 38 37 39 40 52 | |
| 54 53 58 57 61 66 67 65 64 63 | |
| 62 56 59 60 28 29 31 32 30 24 | |
| 25 19 17 18 15 16 14 13 20 22 | |
| 21 23 26 27 9 10 11 12 |
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| NAME : waldo68 | |
| COMMENT : 68 locations of Waldo | |
| TYPE : TSP | |
| DIMENSION : 68 | |
| EDGE_WEIGHT_TYPE : EUC_2D | |
| NODE_COORD_SECTION | |
| 0 0.625000000 7.708333333 | |
| 1 4.944444444 6.569444444 | |
| 2 5.430555556 6.402777778 | |
| 3 5.902777778 6.083333333 |
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