stats.py 文件源码

def match_matrix(event: Event):
    """Returns a numpy participation matrix for the qualification matches in this event, used for calculating OPR.

        Each row in the matrix corresponds to a single alliance in a match, meaning that there will be two rows (one for
    red, one for blue) per match. Each column represents a single team, ordered by team number. If a team participated
    on a certain alliance, the value at that row and column would be 1, otherwise, it would be 0. For example, an
    event with teams 1-7 that featured a match that pitted teams 1, 3, and 5 against 2, 4, and 6 would have a match
    matrix that looks like this (sans labels):

                                #1  #2  #3  #4  #5  #6  #7
                    qm1_red     1   0   1   0   1   0   0
                    qm1_blue    0   1   0   1   0   1   0
    """
    match_list = []
    for match in filter(lambda match: match['comp_level'] == 'qm', event.matches):
        matchRow = []
        for team in event.teams:
            matchRow.append(1 if team['key'] in match['alliances']['red']['teams'] else 0)
        match_list.append(matchRow)
        matchRow = []
        for team in event.teams:
            matchRow.append(1 if team['key'] in match['alliances']['blue']['teams'] else 0)
        match_list.append(matchRow)

    mat = numpy.array(match_list)
    sum_matches = numpy.sum(mat, axis=0)
    avg_team_matches = sum(sum_matches) / float(len(sum_matches))
    return mat[:, numpy.apply_along_axis(numpy.count_nonzero, 0, mat) > avg_team_matches - 2]