mirror of
https://github.com/titanscouting/tra-superscript.git
synced 2024-11-10 06:54:45 +00:00
fixed merge changes
This commit is contained in:
Arthur Lu
parent
9279311664
commit
6b070c7b08
@ -1,2 +0,0 @@
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FROM titanscout2022/tra-analysis-base:latest
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WORKDIR /
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@ -1,7 +1,7 @@
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{
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"name": "TRA Analysis Development Environment",
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"build": {
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"dockerfile": "dev-dockerfile",
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"dockerfile": "Dockerfile",
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},
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"settings": {
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"terminal.integrated.shell.linux": "/bin/bash",
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@ -149,25 +149,9 @@ __author__ = (
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# imports:
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<<<<<<< HEAD
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import os, sys, time
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import pymongo # soon to be deprecated
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import traceback
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=======
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from tra_analysis import analysis as an
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import data as d
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from collections import defaultdict
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import json
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import math
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import numpy as np
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import os
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from os import system, name
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from pathlib import Path
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from multiprocessing import Pool
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import platform
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import sys
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import time
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>>>>>>> master
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import warnings
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from config import Configuration, ConfigurationError
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from data import get_previous_time, set_current_time, check_new_database_matches
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@ -175,15 +159,10 @@ from interface import Logger
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from module import Match, Metric, Pit
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import zmq
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<<<<<<< HEAD
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config_path = "config.json"
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=======
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global exec_threads
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>>>>>>> master
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def main(logger, verbose, profile, debug, socket_send = None):
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<<<<<<< HEAD
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def close_all():
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if "client" in locals():
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client.close()
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@ -239,95 +218,10 @@ def main(logger, verbose, profile, debug, socket_send = None):
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socket_send(m + " module finished in " + str(time.time() - start) + " seconds")
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if debug:
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logger.save_module_to_file(m, current_module.data, current_module.results) # logging flag check done in logger
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=======
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global exec_threads
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sys.stderr = open("errorlog.txt", "w")
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warnings.filterwarnings("ignore")
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splash()
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while (True):
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try:
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current_time = time.time()
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print("[OK] time: " + str(current_time))
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config = load_config("config.json")
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competition = config["competition"]
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match_tests = config["statistics"]["match"]
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pit_tests = config["statistics"]["pit"]
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metrics_tests = config["statistics"]["metric"]
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print("[OK] configs loaded")
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print("[OK] starting threads")
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cfg_max_threads = config["max-threads"]
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sys_max_threads = os.cpu_count()
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if cfg_max_threads > -sys_max_threads and cfg_max_threads < 0 :
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alloc_processes = sys_max_threads + cfg_max_threads
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elif cfg_max_threads > 0 and cfg_max_threads < 1:
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alloc_processes = math.floor(cfg_max_threads * sys_max_threads)
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elif cfg_max_threads > 1 and cfg_max_threads <= sys_max_threads:
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alloc_processes = cfg_max_threads
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elif cfg_max_threads == 0:
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alloc_processes = sys_max_threads
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else:
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print("[ERROR] Invalid number of processes, must be between -" + str(sys_max_threads) + " and " + str(sys_max_threads))
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exit()
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exec_threads = Pool(processes = alloc_processes)
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print("[OK] " + str(alloc_processes) + " threads started")
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apikey = config["key"]["database"]
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tbakey = config["key"]["tba"]
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print("[OK] loaded keys")
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previous_time = get_previous_time(apikey)
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print("[OK] analysis backtimed to: " + str(previous_time))
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print("[OK] loading data")
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start = time.time()
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match_data = load_match(apikey, competition)
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pit_data = load_pit(apikey, competition)
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print("[OK] loaded data in " + str(time.time() - start) + " seconds")
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print("[OK] running match stats")
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start = time.time()
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matchloop(apikey, competition, match_data, match_tests)
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print("[OK] finished match stats in " + str(time.time() - start) + " seconds")
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print("[OK] running team metrics")
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start = time.time()
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metricloop(tbakey, apikey, competition, previous_time, metrics_tests)
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print("[OK] finished team metrics in " + str(time.time() - start) + " seconds")
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print("[OK] running pit analysis")
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start = time.time()
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pitloop(apikey, competition, pit_data, pit_tests)
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print("[OK] finished pit analysis in " + str(time.time() - start) + " seconds")
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set_current_time(apikey, current_time)
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print("[OK] finished all tests, looping")
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print_hrule()
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except KeyboardInterrupt:
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print("\n[OK] caught KeyboardInterrupt, killing processes")
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exec_threads.terminate()
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print("[OK] processes killed, exiting")
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exit()
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else:
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pass
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#clear()
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>>>>>>> master
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set_current_time(client, loop_start)
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close_all()
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<<<<<<< HEAD
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logger.info("closed threads and database client")
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logger.info("finished all tasks in " + str(time.time() - loop_start) + " seconds, looping")
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socket_send("closed threads and database client")
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@ -335,41 +229,6 @@ def main(logger, verbose, profile, debug, socket_send = None):
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if profile:
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return 0
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=======
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def print_hrule():
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print("#"+38*"-"+"#")
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def print_box(s):
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temp = "|"
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temp += s
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temp += (40-len(s)-2)*" "
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temp += "|"
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print(temp)
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def splash():
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print_hrule()
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print_box(" superscript version: " + __version__)
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print_box(" os: " + platform.system())
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print_box(" python: " + platform.python_version())
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print_hrule()
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def load_config(file):
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config_vector = {}
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try:
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f = open(file)
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except:
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print("[ERROR] could not locate config.json, generating blank config.json and exiting")
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f = open(file, "w")
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f.write(sample_json)
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exit()
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config_vector = json.load(f)
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>>>>>>> master
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if debug:
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return 0
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@ -457,7 +316,6 @@ def start(pid_path, verbose, profile, debug):
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else:
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<<<<<<< HEAD
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logfile = "logfile.log"
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f = open(logfile, 'w+')
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@ -505,119 +363,6 @@ def stop(pid_path):
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if err.find("No such process") > 0:
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if os.path.exists(pid_path):
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os.remove(pid_path)
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=======
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previous_time = previous_time["latest_update"]
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return previous_time
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def set_current_time(apikey, current_time):
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d.set_analysis_flags(apikey, "latest_update", {"latest_update":current_time})
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def load_match(apikey, competition):
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return d.get_match_data_formatted(apikey, competition)
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def simplestats(data_test):
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data = np.array(data_test[0])
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data = data[np.isfinite(data)]
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ranges = list(range(len(data)))
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test = data_test[1]
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if test == "basic_stats":
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return an.basic_stats(data)
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if test == "historical_analysis":
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return an.histo_analysis([ranges, data])
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if test == "regression_linear":
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return an.regression(ranges, data, ['lin'])
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if test == "regression_logarithmic":
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return an.regression(ranges, data, ['log'])
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if test == "regression_exponential":
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return an.regression(ranges, data, ['exp'])
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if test == "regression_polynomial":
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return an.regression(ranges, data, ['ply'])
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if test == "regression_sigmoidal":
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return an.regression(ranges, data, ['sig'])
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def matchloop(apikey, competition, data, tests): # expects 3D array with [Team][Variable][Match]
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global exec_threads
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short_mapping = {"regression_linear": "lin", "regression_logarithmic": "log", "regression_exponential": "exp", "regression_polynomial": "ply", "regression_sigmoidal": "sig"}
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class AutoVivification(dict):
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def __getitem__(self, item):
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try:
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return dict.__getitem__(self, item)
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except KeyError:
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value = self[item] = type(self)()
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return value
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return_vector = {}
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team_filtered = []
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variable_filtered = []
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variable_data = []
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test_filtered = []
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result_filtered = []
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return_vector = AutoVivification()
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for team in data:
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for variable in data[team]:
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if variable in tests:
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for test in tests[variable]:
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team_filtered.append(team)
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variable_filtered.append(variable)
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variable_data.append((data[team][variable], test))
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test_filtered.append(test)
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result_filtered = exec_threads.map(simplestats, variable_data)
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i = 0
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result_filtered = list(result_filtered)
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for result in result_filtered:
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filtered = test_filtered[i]
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try:
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short = short_mapping[filtered]
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return_vector[team_filtered[i]][variable_filtered[i]][test_filtered[i]] = result[short]
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except KeyError: # not in mapping
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return_vector[team_filtered[i]][variable_filtered[i]][test_filtered[i]] = result
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i += 1
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push_match(apikey, competition, return_vector)
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def load_metric(apikey, competition, match, group_name, metrics):
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group = {}
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for team in match[group_name]:
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db_data = d.get_team_metrics_data(apikey, competition, team)
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if d.get_team_metrics_data(apikey, competition, team) == None:
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elo = {"score": metrics["elo"]["score"]}
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gl2 = {"score": metrics["gl2"]["score"], "rd": metrics["gl2"]["rd"], "vol": metrics["gl2"]["vol"]}
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ts = {"mu": metrics["ts"]["mu"], "sigma": metrics["ts"]["sigma"]}
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group[team] = {"elo": elo, "gl2": gl2, "ts": ts}
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>>>>>>> master
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else:
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traceback.print_exc(file = sys.stderr)
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sys.exit(1)
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@ -654,156 +399,5 @@ if __name__ == "__main__":
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sys.exit(2)
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sys.exit(0)
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else:
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<<<<<<< HEAD
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print("usage: %s start|stop|restart|verbose|profile|debug" % sys.argv[0])
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sys.exit(2)
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=======
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observations = {"red": 0.5, "blu": 0.5}
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red_elo_delta = an.Metric().elo(red_elo["score"], blu_elo["score"], observations["red"], elo_N, elo_K) - red_elo["score"]
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blu_elo_delta = an.Metric().elo(blu_elo["score"], red_elo["score"], observations["blu"], elo_N, elo_K) - blu_elo["score"]
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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"]])
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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"]])
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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"]}
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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"]}
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for team in red:
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red[team]["elo"]["score"] = red[team]["elo"]["score"] + red_elo_delta
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red[team]["gl2"]["score"] = red[team]["gl2"]["score"] + red_gl2_delta["score"]
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red[team]["gl2"]["rd"] = red[team]["gl2"]["rd"] + red_gl2_delta["rd"]
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red[team]["gl2"]["vol"] = red[team]["gl2"]["vol"] + red_gl2_delta["vol"]
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for team in blu:
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blu[team]["elo"]["score"] = blu[team]["elo"]["score"] + blu_elo_delta
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blu[team]["gl2"]["score"] = blu[team]["gl2"]["score"] + blu_gl2_delta["score"]
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blu[team]["gl2"]["rd"] = blu[team]["gl2"]["rd"] + blu_gl2_delta["rd"]
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blu[team]["gl2"]["vol"] = blu[team]["gl2"]["vol"] + blu_gl2_delta["vol"]
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temp_vector = {}
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temp_vector.update(red)
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temp_vector.update(blu)
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push_metric(apikey, competition, temp_vector)
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def load_pit(apikey, competition):
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return d.get_pit_data_formatted(apikey, competition)
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def pitloop(apikey, competition, pit, tests):
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return_vector = {}
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for team in pit:
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for variable in pit[team]:
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if variable in tests:
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if not variable in return_vector:
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return_vector[variable] = []
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return_vector[variable].append(pit[team][variable])
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push_pit(apikey, competition, return_vector)
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def push_match(apikey, competition, results):
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for team in results:
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d.push_team_tests_data(apikey, competition, team, results[team])
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def push_metric(apikey, competition, metric):
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for team in metric:
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d.push_team_metrics_data(apikey, competition, team, metric[team])
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def push_pit(apikey, competition, pit):
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for variable in pit:
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d.push_team_pit_data(apikey, competition, variable, pit[variable])
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def get_team_metrics(apikey, tbakey, competition):
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metrics = d.get_metrics_data_formatted(apikey, competition)
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elo = {}
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gl2 = {}
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for team in metrics:
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elo[team] = metrics[team]["metrics"]["elo"]["score"]
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gl2[team] = metrics[team]["metrics"]["gl2"]["score"]
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elo = {k: v for k, v in sorted(elo.items(), key=lambda item: item[1])}
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gl2 = {k: v for k, v in sorted(gl2.items(), key=lambda item: item[1])}
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elo_ranked = []
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for team in elo:
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elo_ranked.append({"team": str(team), "elo": str(elo[team])})
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gl2_ranked = []
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for team in gl2:
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gl2_ranked.append({"team": str(team), "gl2": str(gl2[team])})
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return {"elo-ranks": elo_ranked, "glicko2-ranks": gl2_ranked}
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sample_json = """{
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"max-threads": 0.5,
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"team": "",
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"competition": "2020ilch",
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"key":{
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"database":"",
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"tba":""
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},
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"statistics":{
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"match":{
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"balls-blocked":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
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"balls-collected":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
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"balls-lower-teleop":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
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"balls-lower-auto":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
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"balls-started":["basic_stats","historical_analyss","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
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"balls-upper-teleop":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
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"balls-upper-auto":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"]
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},
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"metric":{
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"elo":{
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"score":1500,
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"N":400,
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"K":24
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},
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"gl2":{
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"score":1500,
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"rd":250,
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"vol":0.06
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},
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"ts":{
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"mu":25,
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"sigma":8.33
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}
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},
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"pit":{
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"wheel-mechanism":true,
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"low-balls":true,
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"high-balls":true,
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"wheel-success":true,
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"strategic-focus":true,
|
||||
"climb-mechanism":true,
|
||||
"attitude":true
|
||||
}
|
||||
}
|
||||
}"""
|
||||
|
||||
if __name__ == "__main__":
|
||||
if sys.platform.startswith('win'):
|
||||
multiprocessing.freeze_support()
|
||||
main()
|
||||
>>>>>>> master
|
||||
sys.exit(2)
|
||||
@ -1,37 +0,0 @@
|
||||
# -*- mode: python ; coding: utf-8 -*-
|
||||
|
||||
block_cipher = None
|
||||
|
||||
|
||||
a = Analysis(['superscript.py'],
|
||||
pathex=['/workspaces/tra-data-analysis/src'],
|
||||
binaries=[],
|
||||
datas=[],
|
||||
hiddenimports=[
|
||||
"dnspython",
|
||||
"sklearn.utils._weight_vector",
|
||||
"requests",
|
||||
],
|
||||
hookspath=[],
|
||||
runtime_hooks=[],
|
||||
excludes=[],
|
||||
win_no_prefer_redirects=False,
|
||||
win_private_assemblies=False,
|
||||
cipher=block_cipher,
|
||||
noarchive=False)
|
||||
pyz = PYZ(a.pure, a.zipped_data,
|
||||
cipher=block_cipher)
|
||||
exe = EXE(pyz,
|
||||
a.scripts,
|
||||
a.binaries,
|
||||
a.zipfiles,
|
||||
a.datas,
|
||||
[('W ignore', None, 'OPTION')],
|
||||
name='superscript',
|
||||
debug=False,
|
||||
bootloader_ignore_signals=False,
|
||||
strip=False,
|
||||
upx=True,
|
||||
upx_exclude=[],
|
||||
runtime_tmpdir=None,
|
||||
console=True )
|
||||
Loading…
Reference in New Issue
Block a user