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ToT Scoring notes
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// INPUT for ToT Planing score (Insights) | |
[ | |
{ | |
"namespace": "com.lumosity.insights.tot.planning.score", | |
"name": "userRecords", | |
"type": "record", | |
"doc": "Set of ToT gameplay records associated to a user", | |
"fields": [ | |
{ "name": "userId", "type": "long" }, | |
{ "name": "UserGameplayRecordArray", | |
"type":{ "type": "array", "items": "com.lumosity.insights.tot.planning.score.UserGameplayRecords" }} | |
] | |
}, | |
{ | |
"namespace": "com.lumosity.insights.tot.planning.score", | |
"name": "userGameplayRecords", | |
"type": "record", | |
"doc": "Information of a ToT gamplay used to calculate a TP (Train of Thought Planning) Score", | |
"fields": [ | |
{ "name": "gameId", "type": "int" }, | |
{ "name": "gameResultId", "type": "long" }, | |
{ "name": "selectedLevel", "type": "int" }, // userLevel is messed up in a few users, selectedLevel seems fine | |
{ "name": "diagram", "type": "string" }, | |
{ "name": "timestamp", "type": "int", "logicalType": "date"}, // client timestamp | |
{ "name": "trialsCsv", "type": { "type": "array", "items": "com.lumosity.insights.tot.planning.score.trainRecords" }}, | |
{ "name": "switchCsv", "type": { "type": "array", "items": "com.lumosity.insights.tot.planning.score.switchRecords" }} | |
] | |
}, | |
{ | |
"namespace": "com.lumosity.insights.tot.planning.score", | |
"name": "trainRecords", | |
"type": "record", | |
"doc": "Events associated to Spawnning trains and train station arrivals", | |
"fields": [ | |
{ "name": "correct", "type": "boolean" }, | |
{ "name": "destination", "type": "int" }, | |
{ "name": "spawnTimeOffset", "type": "long" } | |
] | |
}, | |
{ | |
"namespace": "com.lumosity.insights.tot.planning.score", | |
"name": "switchRecords", | |
"type": "record", | |
"doc": "Switch event information", | |
"fields": [ | |
{ "name": "address", "type": "int" }, | |
{ "name": "timeOffset", "type": "long" } | |
] | |
} | |
] | |
// OUTPUT of ToT Planing score (Insights) | |
[ | |
{ | |
"namespace": "com.lumosity.insights.tot.planning.score", | |
"name": "planningScore", | |
"type": "record", | |
"doc": "Planning score associated to a Train of Thought user", | |
"fields": [ | |
{ "name": "userId", "type": "long" }, | |
{ "name": "planningScores", "type": { "type": "array", "items": "int" }}, // [1, 2, ... , 8], where 1 | |
{ "name": "ageGroupPlanningScores", "type": { "type": "array", "items": "int" }}, // [1, 2, ... , 8] | |
{ "name": "gameLevel", "type": "int" }, // [3, ... , 14] | |
{ "name": "numberGameplaysUsed", "type": "int" }, | |
{ "name": "timestamp", "type": "int", "logicalType": "date"} // client timestamp | |
] | |
} | |
] |
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OK! I think we are close to something. I analyzed 1K records and I turned them into the Dataset shown below (showing only the results of the first 90 records). As I mentioned before, the population table used to calculate the percentiles (the output scores) is read from s3. If these results sounds reasonable, I will do minor refactoring to my code so it's more readable.