tra-analysis/data-analysis/config.json
Arthur Lu f9fd61e8a5 superscript.py v 0.8.1
Signed-off-by: Arthur Lu <learthurgo@gmail.com>
2020-09-21 07:38:18 +00:00

46 lines
1.7 KiB
JSON

{
"max-threads": 1,
"team": "",
"competition": "2020ilch",
"key":{
"database":"",
"tba":""
},
"statistics":{
"match":{
"balls-blocked":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-collected":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-lower-teleop":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-lower-auto":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-started":["basic_stats","historical_analyss","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-upper-teleop":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-upper-auto":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"]
},
"metric":{
"elo":{
"score":1500,
"N":400,
"K":24
},
"gl2":{
"score":1500,
"rd":250,
"vol":0.06
},
"ts":{
"mu":25,
"sigma":8.33
}
},
"pit":{
"wheel-mechanism":true,
"low-balls":true,
"high-balls":true,
"wheel-success":true,
"strategic-focus":true,
"climb-mechanism":true,
"attitude":true
}
}
}