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https://github.com/titanscouting/tra-analysis.git
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Merge pull request #46 from titanscouting/multithread-testing
Implement Multithreading in Superscript
This commit is contained in:
commit
56a5578f35
@ -1,6 +1,7 @@
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{
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"max-threads": 0.5,
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"team": "",
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"competition": "2020ilch",
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"competition": "",
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"key":{
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"database":"",
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"tba":""
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@ -2,3 +2,4 @@ requests
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pymongo
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pandas
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dnspython
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tra-analysis
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@ -3,10 +3,18 @@
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# Notes:
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# setup:
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__version__ = "0.7.0"
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__version__ = "0.8.2"
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# changelog should be viewed using print(analysis.__changelog__)
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__changelog__ = """changelog:
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0.8.2:
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- readded while true to main function
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- added more thread config options
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0.8.1:
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- optimized matchloop further by bypassing GIL
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0.8.0:
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- added multithreading to matchloop
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- tweaked user log
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0.7.0:
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- finished implementing main function
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0.6.2:
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@ -114,16 +122,25 @@ __all__ = [
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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 matplotlib.pyplot as plt
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from concurrent.futures import ThreadPoolExecutor
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import time
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import warnings
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global exec_threads
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def main():
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global exec_threads
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warnings.filterwarnings("ignore")
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while (True):
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@ -138,6 +155,23 @@ def main():
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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("[Err] 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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@ -151,15 +185,15 @@ def main():
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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 tests")
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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 tests in " + str(time.time() - start) + " seconds")
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print("[OK] finished match stats in " + str(time.time() - start) + " seconds")
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print("[OK] running metrics")
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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 metrics in " + str(time.time() - start) + " seconds")
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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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@ -217,14 +251,14 @@ def load_match(apikey, competition):
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return d.get_match_data_formatted(apikey, competition)
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def matchloop(apikey, competition, data, tests): # expects 3D array with [Team][Variable][Match]
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def simplestats(data_test):
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def simplestats(data, test):
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data = np.array(data)
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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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@ -246,19 +280,49 @@ def matchloop(apikey, competition, data, tests): # expects 3D array with [Team][
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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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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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variable_vector = {}
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for variable in data[team]:
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test_vector = {}
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variable_data = data[team][variable]
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if variable in tests:
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for test in tests[variable]:
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test_vector[test] = simplestats(variable_data, test)
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else:
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pass
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variable_vector[variable] = test_vector
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return_vector[team] = variable_vector
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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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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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