tra-analysis/data analysis/superscript.py

# Titan Robotics Team 2022: Superscript Script
# Written by Arthur Lu & Jacob Levine
# Notes:
# setup:

__version__ = "0.0.0.003"

# changelog should be viewed using print(analysis.__changelog__)
__changelog__ = """changelog:
    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"]))

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()