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https://github.com/titanscouting/tra-analysis.git
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2605f7c29f
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data analysis/config/competition.config
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data analysis/config/competition.config
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2020ilch
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data analysis/config/database.config
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data analysis/config/database.config
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data analysis/config/keys.config
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data analysis/config/keys.config
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mongodb+srv://api-user-new:titanscout2022@2022-scouting-4vfuu.mongodb.net/test?authSource=admin&replicaSet=2022-scouting-shard-0&readPreference=primary&appname=MongoDB%20Compass&ssl=true
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UDvKmPjPRfwwUdDX1JxbmkyecYBJhCtXeyVk9vmO2i7K0Zn4wqQPMfzuEINXJ7e5
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@ -1,4 +1,3 @@
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2020ilch
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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-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-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-teleop,basic_stats,historical_analysis,regression_linear,regression_logarithmic,regression_exponential,regression_polynomial,regression_sigmoidal
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# Notes:
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# Notes:
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# setup:
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# setup:
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__version__ = "0.0.4.002"
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__version__ = "0.0.5.000"
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# changelog should be viewed using print(analysis.__changelog__)
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# changelog should be viewed using print(analysis.__changelog__)
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__changelog__ = """changelog:
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__changelog__ = """changelog:
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0.0.5.000:
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improved user interface
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0.0.4.002:
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0.0.4.002:
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- removed unessasary code
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- removed unessasary code
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0.0.4.001:
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0.0.4.001:
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@ -83,6 +85,8 @@ from analysis import analysis as an
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import data as d
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import data as d
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import numpy as np
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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from os import system, name
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from pathlib import Path
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import time
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import time
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import warnings
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import warnings
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@ -91,16 +95,16 @@ def main():
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while(True):
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while(True):
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current_time = time.time()
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current_time = time.time()
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print("time: " + str(current_time))
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print("[OK] time: " + str(current_time))
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print(" loading config")
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start = time.time()
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competition, config = load_config("config.csv")
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config = load_config(Path("config/stats.config"))
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print(" config loaded")
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competition = an.load_csv(Path("config/competition.config"))[0][0]
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print("[OK] configs loaded")
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print(" loading database keys")
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apikey = an.load_csv(Path("config/keys.config"))[0][0]
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apikey = an.load_csv("keys.txt")[0][0]
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tbakey = an.load_csv(Path("config/keys.config"))[1][0]
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tbakey = an.load_csv("keys.txt")[1][0]
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print("[OK] loaded keys")
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print(" loaded keys")
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previous_time = d.get_analysis_flags(apikey, "latest_update")
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previous_time = d.get_analysis_flags(apikey, "latest_update")
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@ -113,38 +117,55 @@ def main():
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previous_time = previous_time["latest_update"]
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previous_time = previous_time["latest_update"]
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print(" analysis backtimed to: " + str(previous_time))
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print("[OK] analysis backtimed to: " + str(previous_time))
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print(" loading data")
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print("[OK] loading data")
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start = time.time()
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data = d.get_match_data_formatted(apikey, competition)
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data = d.get_match_data_formatted(apikey, competition)
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pit_data = d.pit = d.get_pit_data_formatted(apikey, competition)
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pit_data = d.pit = d.get_pit_data_formatted(apikey, competition)
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print(" loaded data")
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print("[OK] loaded data in " + str(time.time() - start) + " seconds")
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print(" running tests")
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print("[OK] running tests")
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start = time.time()
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results = simpleloop(data, config)
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results = simpleloop(data, config)
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print(" finished tests")
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print("[OK] finished tests in " + str(time.time() - start) + " seconds")
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print(" running metrics")
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print("[OK] running metrics")
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start = time.time()
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metricsloop(tbakey, apikey, competition, previous_time)
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metricsloop(tbakey, apikey, competition, previous_time)
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print(" finished metrics")
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print("[OK] finished metrics in " + str(time.time() - start) + " seconds")
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print(" running pit analysis")
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print("[OK] running pit analysis")
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start = time.time()
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pit = pitloop(pit_data, config)
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pit = pitloop(pit_data, config)
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print(" finished pit analysis")
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print("[OK] finished pit analysis in " + str(time.time() - start) + " seconds")
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d.set_analysis_flags(apikey, "latest_update", {"latest_update":current_time})
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d.set_analysis_flags(apikey, "latest_update", {"latest_update":current_time})
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print(" pushing to database")
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print("[OK] pushing to database")
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start = time.time()
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push_to_database(apikey, competition, results, pit)
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push_to_database(apikey, competition, results, pit)
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print(" pushed to database")
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print("[OK] pushed to database in " + str(time.time() - start) + " seconds")
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clear()
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def clear():
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# for windows
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if name == 'nt':
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_ = system('cls')
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# for mac and linux(here, os.name is 'posix')
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else:
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_ = system('clear')
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def load_config(file):
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def load_config(file):
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config_vector = {}
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config_vector = {}
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file = an.load_csv(file)
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file = an.load_csv(file)
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for line in file[1:]:
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for line in file:
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config_vector[line[0]] = line[1:]
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config_vector[line[0]] = line[1:]
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return (file[0][0], config_vector)
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return config_vector
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def simpleloop(data, tests): # expects 3D array with [Team][Variable][Match]
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def simpleloop(data, tests): # expects 3D array with [Team][Variable][Match]
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