commented metrics in module.py

This commit is contained in:
Arthur Lu 2022-03-28 22:02:39 +00:00
parent 82ec2d85cc
commit cdd81295fc

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@ -181,9 +181,9 @@ class Metric (Module):
red = {}
blu = {}
for match in tqdm(matches, desc="Metrics"):
red = d.load_metric(self.apikey, self.competition, match, "red", self.config["tests"])
blu = d.load_metric(self.apikey, self.competition, match, "blue", self.config["tests"])
for match in tqdm(matches, desc="Metrics"): # grab matches and loop through each one
red = d.load_metric(self.apikey, self.competition, match, "red", self.config["tests"]) # get the current ratings for red
blu = d.load_metric(self.apikey, self.competition, match, "blue", self.config["tests"]) # get the current ratings for blue
elo_red_total = 0
elo_blu_total = 0
@ -197,7 +197,7 @@ class Metric (Module):
gl2_red_vol_total = 0
gl2_blu_vol_total = 0
for team in red:
for team in red: # for each team in red, add up the elo score and gl2 score components
elo_red_total += red[team]["elo"]["score"]
@ -205,7 +205,7 @@ class Metric (Module):
gl2_red_rd_total += red[team]["gl2"]["rd"]
gl2_red_vol_total += red[team]["gl2"]["vol"]
for team in blu:
for team in blu: # for each team in blue, add up the elo score and gl2 score components
elo_blu_total += blu[team]["elo"]["score"]
@ -213,35 +213,35 @@ class Metric (Module):
gl2_blu_rd_total += blu[team]["gl2"]["rd"]
gl2_blu_vol_total += blu[team]["gl2"]["vol"]
red_elo = {"score": elo_red_total / len(red)}
blu_elo = {"score": elo_blu_total / len(blu)}
red_elo = {"score": elo_red_total / len(red)} # average the scores by dividing by 3
blu_elo = {"score": elo_blu_total / len(blu)} # average the scores by dividing by 3
red_gl2 = {"score": gl2_red_score_total / len(red), "rd": gl2_red_rd_total / len(red), "vol": gl2_red_vol_total / len(red)}
blu_gl2 = {"score": gl2_blu_score_total / len(blu), "rd": gl2_blu_rd_total / len(blu), "vol": gl2_blu_vol_total / len(blu)}
red_gl2 = {"score": gl2_red_score_total / len(red), "rd": gl2_red_rd_total / len(red), "vol": gl2_red_vol_total / len(red)} # average the scores by dividing by 3
blu_gl2 = {"score": gl2_blu_score_total / len(blu), "rd": gl2_blu_rd_total / len(blu), "vol": gl2_blu_vol_total / len(blu)} # average the scores by dividing by 3
if match["winner"] == "red":
if match["winner"] == "red": # if red won, set observations to {"red": 1, "blu": 0}
observations = {"red": 1, "blu": 0}
elif match["winner"] == "blue":
elif match["winner"] == "blue": # if blue won, set observations to {"red": 0, "blu": 1}
observations = {"red": 0, "blu": 1}
else:
else: # otherwise it was a tie and observations is {"red": 0.5, "blu": 0.5}
observations = {"red": 0.5, "blu": 0.5}
red_elo_delta = an.Metric().elo(red_elo["score"], blu_elo["score"], observations["red"], elo_N, elo_K) - red_elo["score"]
blu_elo_delta = an.Metric().elo(blu_elo["score"], red_elo["score"], observations["blu"], elo_N, elo_K) - blu_elo["score"]
red_elo_delta = an.Metric().elo(red_elo["score"], blu_elo["score"], observations["red"], elo_N, elo_K) - red_elo["score"] # calculate new elo for red using analysis, this is a delta
blu_elo_delta = an.Metric().elo(blu_elo["score"], red_elo["score"], observations["blu"], elo_N, elo_K) - blu_elo["score"] # calculate new elo for blue using analysis, this is a delta
new_red_gl2_score, new_red_gl2_rd, new_red_gl2_vol = an.Metric().glicko2(red_gl2["score"], red_gl2["rd"], red_gl2["vol"], [blu_gl2["score"]], [blu_gl2["rd"]], [observations["red"], observations["blu"]])
new_blu_gl2_score, new_blu_gl2_rd, new_blu_gl2_vol = an.Metric().glicko2(blu_gl2["score"], blu_gl2["rd"], blu_gl2["vol"], [red_gl2["score"]], [red_gl2["rd"]], [observations["blu"], observations["red"]])
new_red_gl2_score, new_red_gl2_rd, new_red_gl2_vol = an.Metric().glicko2(red_gl2["score"], red_gl2["rd"], red_gl2["vol"], [blu_gl2["score"]], [blu_gl2["rd"]], [observations["red"], observations["blu"]]) # calculate new scores for gl2 for red
new_blu_gl2_score, new_blu_gl2_rd, new_blu_gl2_vol = an.Metric().glicko2(blu_gl2["score"], blu_gl2["rd"], blu_gl2["vol"], [red_gl2["score"]], [red_gl2["rd"]], [observations["blu"], observations["red"]]) # calculate new scores for gl2 for blue
red_gl2_delta = {"score": new_red_gl2_score - red_gl2["score"], "rd": new_red_gl2_rd - red_gl2["rd"], "vol": new_red_gl2_vol - red_gl2["vol"]}
blu_gl2_delta = {"score": new_blu_gl2_score - blu_gl2["score"], "rd": new_blu_gl2_rd - blu_gl2["rd"], "vol": new_blu_gl2_vol - blu_gl2["vol"]}
red_gl2_delta = {"score": new_red_gl2_score - red_gl2["score"], "rd": new_red_gl2_rd - red_gl2["rd"], "vol": new_red_gl2_vol - red_gl2["vol"]} # calculate gl2 deltas for red
blu_gl2_delta = {"score": new_blu_gl2_score - blu_gl2["score"], "rd": new_blu_gl2_rd - blu_gl2["rd"], "vol": new_blu_gl2_vol - blu_gl2["vol"]} # calculate gl2 deltas for blue
for team in red:
for team in red: # for each team on red, add the previous score with the delta to find the new score
red[team]["elo"]["score"] = red[team]["elo"]["score"] + red_elo_delta
@ -249,7 +249,7 @@ class Metric (Module):
red[team]["gl2"]["rd"] = red[team]["gl2"]["rd"] + red_gl2_delta["rd"]
red[team]["gl2"]["vol"] = red[team]["gl2"]["vol"] + red_gl2_delta["vol"]
for team in blu:
for team in blu: # for each team on blue, add the previous score with the delta to find the new score
blu[team]["elo"]["score"] = blu[team]["elo"]["score"] + blu_elo_delta
@ -258,10 +258,10 @@ class Metric (Module):
blu[team]["gl2"]["vol"] = blu[team]["gl2"]["vol"] + blu_gl2_delta["vol"]
temp_vector = {}
temp_vector.update(red)
temp_vector.update(red) # update the team's score with the temporay vector
temp_vector.update(blu)
d.push_metric(self.apikey, self.competition, temp_vector)
d.push_metric(self.apikey, self.competition, temp_vector) # push new scores to db
def _push_results(self):
pass