mirror of
https://github.com/titanscouting/tra-analysis.git
synced 2024-09-20 08:57:56 +00:00
116 lines
3.0 KiB
Python
116 lines
3.0 KiB
Python
# Titan Robotics Team 2022: Superscript Script
|
|
# Written by Arthur Lu & Jacob Levine
|
|
# Notes:
|
|
# setup:
|
|
|
|
__version__ = "0.0.0.004"
|
|
|
|
# changelog should be viewed using print(analysis.__changelog__)
|
|
__changelog__ = """changelog:
|
|
0.0.0.004:
|
|
- fixed simpleloop to actually return a vector
|
|
0.0.0.003:
|
|
- added metricsloop which is unfinished
|
|
0.0.0.002:
|
|
- added simpleloop which is untested until data is provided
|
|
0.0.0.001:
|
|
- created script
|
|
- added analysis, numba, numpy imports
|
|
"""
|
|
|
|
__author__ = (
|
|
"Arthur Lu <learthurgo@gmail.com>",
|
|
"Jacob Levine <jlevine@imsa.edu>",
|
|
)
|
|
|
|
__all__ = [
|
|
]
|
|
|
|
# imports:
|
|
|
|
from analysis import analysis as an
|
|
from numba import jit
|
|
import numpy as np
|
|
try:
|
|
from analysis import trueskill as Trueskill
|
|
except:
|
|
import trueskill as Trueskill
|
|
|
|
def main():
|
|
|
|
pass
|
|
|
|
def simpleloop(data, tests): # expects 3D array with [Team][Variable][Match]
|
|
|
|
return_vector = []
|
|
|
|
for team in teams:
|
|
|
|
team_vector = []
|
|
|
|
for variable in teams:
|
|
|
|
variable_vector = []
|
|
|
|
for test in tests:
|
|
|
|
if(test == "basic" or test == "basic_stats" or test == 0):
|
|
|
|
variable_vector.append(an.basic_stats(variable))
|
|
|
|
if(test == "histo" or test == "histo_analysis" or test == 1):
|
|
|
|
variable_vector.append(an.histo_analysis(variable))
|
|
|
|
if(test == "r.lin" or test == "regression.lin" or test == 2):
|
|
|
|
variable_vector.append(an.regression("cpu", range(0, len(variable) - 1), variable, ["lin"]))
|
|
|
|
if(test == "r.log" or test == "regression.log" or test == 3):
|
|
|
|
variable_vector.append(an.regression("cpu", range(0, len(variable) - 1), variable, ["log"]))
|
|
|
|
if(test == "r.exp" or test == "regression.exp" or test == 4):
|
|
|
|
variable_vector.append(an.regression("cpu", range(0, len(variable) - 1), variable, ["exp"]))
|
|
|
|
if(test == "r.ply" or test == "regression.ply" or test == 5):
|
|
|
|
variable_vector.append(an.regression("cpu", range(0, len(variable) - 1), variable, ["ply"]))
|
|
|
|
if(test == "r.sig" or test == "regression.sig" or test == 6):
|
|
|
|
variable_vector.append(an.regression("cpu", range(0, len(variable) - 1), variable, ["sig"]))
|
|
|
|
team_vector.append(variable_vector)
|
|
|
|
return_vector.append(team_vector)
|
|
|
|
return return_vector
|
|
|
|
def metricsloop(team_lookup, data, tests): # expects array with [Match] ([Teams], [Win/Loss])
|
|
|
|
scores = []
|
|
|
|
elo_starting_score = 1500
|
|
N = 1500
|
|
K = 32
|
|
|
|
gl2_starting_score = 1500
|
|
gl2_starting_rd = 350
|
|
gl2_starting_vol = 0.06
|
|
|
|
for team in team_lookup:
|
|
|
|
elo = elo_starting_score
|
|
gl2 = {"score": gl2_starting_score, "rd": gl2_starting_rd, "vol": gl2_starting_vol}
|
|
ts = Trueskill.Rating()
|
|
|
|
scores[str(team)] = {"elo": elo, "gl2": gl2, "ts": ts}
|
|
|
|
for match in data:
|
|
|
|
groups = data[0]
|
|
observations = data[1]
|
|
|
|
main() |