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79 lines
2.7 KiB
79 lines
2.7 KiB
import os
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import dotenv
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import argparse
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import sys
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import pandas as pd
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import zfit
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from prettytable import PrettyTable
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dotenv.load_dotenv('../properties.env')
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sys.path.insert(0, os.getenv('SYS_PATH'))
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from b2kstll.models.angular import B2Kstll
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from b2kstll.plot import plot_distributions
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from hep_analytics.processing.extract import FileManager
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from hep_analytics.processing.transform import select_feature
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FILE = os.getenv('FILE_GEN')
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument('--q2bin', dest ='q2bin', default = 0)
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args = parser.parse_args()
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Q2BIN = int(args.q2bin)
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bin_ranges = [(0.25, 4.00), (4.00, 8.00), (11.00, 12.50), (15.00, 18.00), (1.10, 6.00), (1.1, 2.5), (2.5, 4.0), (4.0, 6.0), (6.0, 8.0)]
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print(f"Selected Q2 Bin Range is {bin_ranges[Q2BIN]}")
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file_manager = FileManager(file = FILE, tree = "Events",
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branches = ["q2", "costhetak", "costhetal", "phi"])
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data = file_manager.extract_data()
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q2, costhetak, costhetal, phi = data[0], data[1], data[2], data[3]
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q2, indices = select_feature(feature = q2, limits = bin_ranges[Q2BIN])
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costhetak = costhetak[indices]
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costhetal = costhetal[indices]
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phi = phi[indices]
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lower_costhetak_cut = float(os.getenv('LOWER_COSTHETAK_CUT'))
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upper_costhetak_cut = float(os.getenv('UPPER_COSTHETAK_CUT'))
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costhetak, indices = select_feature(feature = costhetak, limits = (lower_costhetak_cut, upper_costhetak_cut))
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q2 = q2[indices]
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costhetal = costhetal[indices]
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phi = phi[indices]
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angular_data = pd.DataFrame({'ctl': costhetal, 'ctk': costhetak, 'phi': phi})
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angular_data.to_csv(f"angular_fit_generator_bin_{Q2BIN}.csv", index = False)
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x = B2Kstll('ctl','ctk','phi')
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obs, pdf, _ = x.get_pdf('PWave')
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datazfit = zfit.Data.from_pandas(df = angular_data, obs = obs)
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nll = zfit.loss.UnbinnedNLL(model = pdf, data = datazfit)
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minimizer = zfit.minimize.Minuit()
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result = minimizer.minimize(nll)
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print(result)
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print(result.params, pdf)
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param_errors, _ = result.errors()
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print(param_errors)
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info_table = PrettyTable(["Variable", "Value", "Lower Error", "Upper Error"])
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fit_labels = ["AFB", "FL", "S3", "S4", "S5", "S7", "S8", "S9"]
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for name in fit_labels:
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value = result.params[name]["value"]
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lower = result.params[name]["minuit_minos"]["lower"]
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upper = result.params[name]["minuit_minos"]["upper"]
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info_table.add_row([name, value, lower, upper])
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print(info_table)
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plot_distributions(result, suffix = f"accPwavePDF_generator_level_bin_{Q2BIN}")
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if __name__ == "__main__":
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main()
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