removed all unessasary files,

moved important files to folder "competition" Former-commit-id: 59becb22abc3305a36e2876351e6c7306e3f551e
2025-09-26 07:10:18 +00:00 · 2022-03-14 01:33:24 +00:00
parent 4836f48a34
commit 8c28c24d60
20 changed files with 0 additions and 232 deletions
--- a/competition/module.py
+++ b/competition/module.py
@@ -0,0 +1,321 @@
+import abc
+import data as d
+import signal
+import numpy as np
+from tra_analysis import Analysis as an
+
+class Module(metaclass = abc.ABCMeta):
+
+	@classmethod
+	def __subclasshook__(cls, subclass):
+		return (hasattr(subclass, '__init__') and 
+				callable(subclass.__init__) and 
+				hasattr(subclass, 'validate_config') and 
+				callable(subclass.validate_config) and
+				hasattr(subclass, 'run') and 
+				callable(subclass.run)
+				)
+	@abc.abstractmethod
+	def __init__(self, config, apikey, tbakey, timestamp, competition, *args, **kwargs):
+		raise NotImplementedError
+	@abc.abstractmethod
+	def validate_config(self, *args, **kwargs):
+		raise NotImplementedError
+	@abc.abstractmethod
+	def run(self, *args, **kwargs):
+		raise NotImplementedError
+
+class Match (Module):
+
+	config = None
+	apikey = None
+	tbakey = None
+	timestamp = None
+	competition = None
+
+	data = None
+	results = None
+	
+	def __init__(self, config, apikey, tbakey, timestamp, competition):
+		self.config = config
+		self.apikey = apikey
+		self.tbakey = tbakey
+		self.timestamp = timestamp
+		self.competition = competition
+
+	def validate_config(self):
+		return True, ""
+
+	def run(self):
+		self._load_data()
+		self._process_data()
+		self._push_results()
+
+	def _load_data(self):
+		self.data = d.load_match(self.apikey, self.competition)
+
+	def _simplestats(self, 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 _process_data(self):
+
+		tests = self.config["tests"]
+		data = self.data
+
+		input_vector = []
+
+		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]))
+
+		self.data = input_vector
+		self.results = []
+		for test_var_data in self.data:
+			self.results.append(self._simplestats(test_var_data))
+
+	def _push_results(self):
+
+		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
+
+		result_filtered = self.results
+		input_vector = self.data
+
+		return_vector = AutoVivification()
+
+		i = 0
+
+		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
+
+		self.results = return_vector
+
+		d.push_match(self.apikey, self.competition, self.results)
+
+class Metric (Module):
+
+	config = None
+	apikey = None
+	tbakey = None
+	timestamp = None
+	competition = None
+
+	data = None
+	results = None
+	
+	def __init__(self, config, apikey, tbakey, timestamp, competition):
+		self.config = config
+		self.apikey = apikey
+		self.tbakey = tbakey
+		self.timestamp = timestamp
+		self.competition = competition
+
+	def validate_config(self):
+		return True, ""
+
+	def run(self):
+		self._load_data()
+		self._process_data()
+		self._push_results()
+
+	def _load_data(self):
+		self.data = d.pull_new_tba_matches(self.tbakey, self.competition, self.timestamp)
+
+	def _process_data(self):
+
+		elo_N = self.config["tests"]["elo"]["N"]
+		elo_K = self.config["tests"]["elo"]["K"]
+
+		matches = self.data
+
+		red = {}
+		blu = {}
+
+		for match in matches:
+
+			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"])
+	
+			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)
+
+			d.push_metric(self.apikey, self.competition, temp_vector)
+
+	def _push_results(self):
+		pass
+
+class Pit (Module):
+
+	config = None
+	apikey = None
+	tbakey = None
+	timestamp = None
+	competition = None
+
+	data = None
+	results = None
+	
+	def __init__(self, config, apikey, tbakey, timestamp, competition):
+		self.config = config
+		self.apikey = apikey
+		self.tbakey = tbakey
+		self.timestamp = timestamp
+		self.competition = competition
+	
+	def validate_config(self):
+		return True, ""
+
+	def run(self):
+		self._load_data()
+		self._process_data()
+		self._push_results()
+
+	def _load_data(self):
+		self.data = d.load_pit(self.apikey, self.competition)
+
+	def _process_data(self):
+		tests = self.config["tests"]
+		return_vector = {}
+		for team in self.data:
+			for variable in self.data[team]:
+				if variable in tests:
+					if not variable in return_vector:
+						return_vector[variable] = []
+					return_vector[variable].append(self.data[team][variable])
+
+		self.results = return_vector
+
+	def _push_results(self):
+		d.push_pit(self.apikey, self.competition, self.results)
+
+class Rating (Module):
+	pass
+
+class Heatmap (Module):
+	pass
+
+class Sentiment (Module):
+	pass