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