mirror of
https://github.com/titanscouting/tra-superscript.git
synced 2024-09-20 00:47:56 +00:00
module replaces processing
This commit is contained in:
Arthur Lu
parent
bd87111e08
commit
d798bfe7d2
@ -1,188 +0,0 @@
|
||||
import numpy as np
|
||||
|
||||
from tra_analysis import Analysis as an
|
||||
from data import pull_new_tba_matches, push_metric, load_metric
|
||||
|
||||
import signal
|
||||
|
||||
def simplestats(data_test):
|
||||
|
||||
signal.signal(signal.SIGINT, signal.SIG_IGN)
|
||||
|
||||
data = np.array(data_test[3])
|
||||
data = data[np.isfinite(data)]
|
||||
ranges = list(range(len(data)))
|
||||
|
||||
test = data_test[2]
|
||||
|
||||
if test == "basic_stats":
|
||||
return an.basic_stats(data)
|
||||
|
||||
if test == "historical_analysis":
|
||||
return an.histo_analysis([ranges, data])
|
||||
|
||||
if test == "regression_linear":
|
||||
return an.regression(ranges, data, ['lin'])
|
||||
|
||||
if test == "regression_logarithmic":
|
||||
return an.regression(ranges, data, ['log'])
|
||||
|
||||
if test == "regression_exponential":
|
||||
return an.regression(ranges, data, ['exp'])
|
||||
|
||||
if test == "regression_polynomial":
|
||||
return an.regression(ranges, data, ['ply'])
|
||||
|
||||
if test == "regression_sigmoidal":
|
||||
return an.regression(ranges, data, ['sig'])
|
||||
|
||||
def matchloop(client, competition, data, tests, exec_threads):
|
||||
|
||||
short_mapping = {"regression_linear": "lin", "regression_logarithmic": "log", "regression_exponential": "exp", "regression_polynomial": "ply", "regression_sigmoidal": "sig"}
|
||||
|
||||
class AutoVivification(dict):
|
||||
def __getitem__(self, item):
|
||||
try:
|
||||
return dict.__getitem__(self, item)
|
||||
except KeyError:
|
||||
value = self[item] = type(self)()
|
||||
return value
|
||||
|
||||
input_vector = []
|
||||
return_vector = AutoVivification()
|
||||
|
||||
for team in data:
|
||||
|
||||
for variable in data[team]:
|
||||
|
||||
if variable in tests:
|
||||
|
||||
for test in tests[variable]:
|
||||
|
||||
input_vector.append((team, variable, test, data[team][variable]))
|
||||
|
||||
result_filtered = exec_threads.map(simplestats, input_vector)
|
||||
|
||||
i = 0
|
||||
|
||||
result_filtered = list(result_filtered)
|
||||
|
||||
for result in result_filtered:
|
||||
|
||||
filtered = input_vector[i][2]
|
||||
|
||||
try:
|
||||
short = short_mapping[filtered]
|
||||
return_vector[input_vector[i][0]][input_vector[i][1]][input_vector[i][2]] = result[short]
|
||||
except KeyError: # not in mapping
|
||||
return_vector[input_vector[i][0]][input_vector[i][1]][input_vector[i][2]] = result
|
||||
|
||||
i += 1
|
||||
|
||||
return return_vector
|
||||
|
||||
def metricloop(client, competition, data, metrics): # listener based metrics update
|
||||
|
||||
elo_N = metrics["elo"]["N"]
|
||||
elo_K = metrics["elo"]["K"]
|
||||
|
||||
matches = data
|
||||
#matches = pull_new_tba_matches(tbakey, competition, timestamp)
|
||||
|
||||
red = {}
|
||||
blu = {}
|
||||
|
||||
for match in matches:
|
||||
|
||||
red = load_metric(client, competition, match, "red", metrics)
|
||||
blu = load_metric(client, competition, match, "blue", metrics)
|
||||
|
||||
elo_red_total = 0
|
||||
elo_blu_total = 0
|
||||
|
||||
gl2_red_score_total = 0
|
||||
gl2_blu_score_total = 0
|
||||
|
||||
gl2_red_rd_total = 0
|
||||
gl2_blu_rd_total = 0
|
||||
|
||||
gl2_red_vol_total = 0
|
||||
gl2_blu_vol_total = 0
|
||||
|
||||
for team in red:
|
||||
|
||||
elo_red_total += red[team]["elo"]["score"]
|
||||
|
||||
gl2_red_score_total += red[team]["gl2"]["score"]
|
||||
gl2_red_rd_total += red[team]["gl2"]["rd"]
|
||||
gl2_red_vol_total += red[team]["gl2"]["vol"]
|
||||
|
||||
for team in blu:
|
||||
|
||||
elo_blu_total += blu[team]["elo"]["score"]
|
||||
|
||||
gl2_blu_score_total += blu[team]["gl2"]["score"]
|
||||
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_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)}
|
||||
|
||||
|
||||
if match["winner"] == "red":
|
||||
|
||||
observations = {"red": 1, "blu": 0}
|
||||
|
||||
elif match["winner"] == "blue":
|
||||
|
||||
observations = {"red": 0, "blu": 1}
|
||||
|
||||
else:
|
||||
|
||||
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"]
|
||||
|
||||
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"]])
|
||||
|
||||
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"]}
|
||||
|
||||
for team in red:
|
||||
|
||||
red[team]["elo"]["score"] = red[team]["elo"]["score"] + red_elo_delta
|
||||
|
||||
red[team]["gl2"]["score"] = red[team]["gl2"]["score"] + red_gl2_delta["score"]
|
||||
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:
|
||||
|
||||
blu[team]["elo"]["score"] = blu[team]["elo"]["score"] + blu_elo_delta
|
||||
|
||||
blu[team]["gl2"]["score"] = blu[team]["gl2"]["score"] + blu_gl2_delta["score"]
|
||||
blu[team]["gl2"]["rd"] = blu[team]["gl2"]["rd"] + blu_gl2_delta["rd"]
|
||||
blu[team]["gl2"]["vol"] = blu[team]["gl2"]["vol"] + blu_gl2_delta["vol"]
|
||||
|
||||
temp_vector = {}
|
||||
temp_vector.update(red)
|
||||
temp_vector.update(blu)
|
||||
|
||||
push_metric(client, competition, temp_vector)
|
||||
|
||||
def pitloop(client, competition, pit, tests):
|
||||
|
||||
return_vector = {}
|
||||
for team in pit:
|
||||
for variable in pit[team]:
|
||||
if variable in tests:
|
||||
if not variable in return_vector:
|
||||
return_vector[variable] = []
|
||||
return_vector[variable].append(pit[team][variable])
|
||||
|
||||
return return_vector
|
||||
@ -165,7 +165,6 @@ import zmq
|
||||
from interface import splash, log, ERR, INF, stdout, stderr
|
||||
from data import get_previous_time, set_current_time, get_database_config, set_database_config, check_new_database_matches
|
||||
from module import Match, Metric, Pit
|
||||
#from processing import matchloop, metricloop, pitloop
|
||||
|
||||
config_path = "config.json"
|
||||
sample_json = """{
|
||||
|
||||
Loading…
Reference in New Issue
Block a user