from pprint import pprint import matplotlib as mpl import matplotlib.pyplot as plt import matplotlib.colors as mcolors from matplotlib.colors import LogNorm from scipy.integrate import quad import tinydb as db import argparse from pygama import DataSet from pygama.analysis.calibration import * from pygama.analysis.histograms import * import pygama.utils as pgu from matplotlib.lines import Line2D from pygama.utils import set_plot_style set_plot_style("clint") def main(): """ Code for varying bias runs: 1174-1176 """ run_db, cal_db = "runDB.json", "calDB.json" par = argparse.ArgumentParser(description="A/E cut for MJ60") arg, st, sf = par.add_argument, "store_true", "store_false" arg("-ds", nargs='*', action="store", help="load runs for a DS") arg("-r", "--run", nargs=1, help="load a single run") arg("-db", "--writeDB", action=st, help="store results in DB") args = vars(par.parse_args())
#!/usr/bin/env python3 import argparse import numpy as np import pandas as pd import tinydb as db import matplotlib.pyplot as plt import itertools as it from scipy.stats import mode from pprint import pprint from pygama import DataSet from pygama.utils import set_plot_style, peakdet set_plot_style('clint') def main(): """ perform automatic calibration of pygama DataSets. command line options to specify the DataSet are the same as in processing.py save results in a JSON database for access by other routines. """ run_db, cal_db = "runDB.json", "calDB.json" par = argparse.ArgumentParser(description="calibration suite for MJ60") arg, st, sf = par.add_argument, "store_true", "store_false" arg("-ds", nargs='*', action="store", help="load runs for a DS") arg("-r", "--run", nargs=1, help="load a single run") arg("-s", "--spec", action=st, help="print simple spectrum") arg("-p1", "--pass1", action=st, help="run pass-1 (linear) calibration") arg("-p2", "--pass2", action=st, help="run pass-2 (peakfit) calibration") arg("-e", "--etype",