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superscript.py v 0.0.0.007
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@ -3,10 +3,16 @@
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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__ = "0.0.0.006"
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__version__ = "0.0.0.007"
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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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0.0.0.007:
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- added load_config
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- optimized simpleloop for readibility
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- added __all__ entries
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- added simplestats engine
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- pending testing
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0.0.0.006:
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0.0.0.006:
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- fixes
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- fixes
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0.0.0.005:
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0.0.0.005:
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@ -29,6 +35,11 @@ __author__ = (
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)
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)
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__all__ = [
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__all__ = [
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"main",
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"load_config",
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"simpleloop",
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"simplestats",
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"metricsloop"
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]
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]
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# imports:
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# imports:
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@ -45,7 +56,23 @@ except:
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def main():
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def main():
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pass
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while(True):
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config = load_config("config.csv")
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simpleloop(data, config)
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def load_config(file):
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config_vector = {}
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file = an.load_csv(file)
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for line in file:
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config_vector[line[0]] = line[1:]
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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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@ -63,8 +90,6 @@ def simpleloop(data, tests): # expects 3D array with [Team][Variable][Match]
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for test in tests[variable]:
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for test in tests[variable]:
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test_vector[test] = simplestats(variable_data, test)
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test_vector[test] = simplestats(variable_data, test)
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#test_vector[test] = None
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variable_vector[variable] = test_vector
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variable_vector[variable] = test_vector
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@ -78,6 +103,29 @@ def simplestats(data, test):
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return an.basic_stats(data)
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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(data)
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if(test == "regression_linear"):
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return an.regression('cpu', list(range(len(data))), data, ['lin'])
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if(test == "regression_logarithmic"):
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return an.regression('cpu', list(range(len(data))), data, ['log'])
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if(test == "regression_exponential"):
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return an.regression('cpu', list(range(len(data))), data, ['exp'])
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if(test == "regression_polynomial"):
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return an.regression('cpu', list(range(len(data))), data, ['ply'])
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if(test == "regression_sigmoidal"):
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return an.regression('cpu', list(range(len(data))), data, ['sig'])
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def metricsloop(group_data, observations, database, tests): # listener based metrics update
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def metricsloop(group_data, observations, database, tests): # listener based metrics update
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