| 1 | import sys
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| 2 | import numpy as np
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| 3 | import matplotlib as mpl
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| 4 | mpl.use('Agg')
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| 5 | import matplotlib.pyplot as plt
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| 6 | import pandas as pd
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| 7 | from astropy.io import fits
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| 8 | from calculate_burst_ratio_file import get_trigger_rates, fjd
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| 9 |
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| 10 |
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| 11 | night_string = sys.argv[1]
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| 12 | night_int = int(night_string)
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| 13 | OFFSET=719163
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| 14 |
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| 15 | runs = pd.DataFrame.from_csv(
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| 16 | 'foo.bar',
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| 17 | infer_datetime_format=True,
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| 18 | parse_dates=['fRunStart', 'fRunStop']
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| 19 | ).dropna()
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| 20 |
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| 21 | runs = runs.loc[runs.fNight==night_int]
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| 22 |
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| 23 | trigger_rates = get_trigger_rates(night_int,
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| 24 | base_path='/fact/aux/')
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| 25 |
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| 26 | fig, ax1 = plt.subplots(figsize=(16, 9))
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| 27 | ax1.set_xlabel("Time")
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| 28 | ax1.set_yscale('log')
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| 29 | ax1.set_ylabel("Rate [Hz]")
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| 30 | ax1.grid()
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| 31 |
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| 32 | plt.title("basic Ratescan information from: " + night_string)
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| 33 |
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| 34 | plot_0 = ax1.plot_date(
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| 35 | trigger_rates['Time']+OFFSET,
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| 36 | np.median(trigger_rates['BoardRate'], axis=1),
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| 37 | 'r.', ms=4.,
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| 38 | label="median BoardRate"
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| 39 | )
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| 40 |
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| 41 | plot_1 = ax1.plot_date(
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| 42 | trigger_rates['Time']+OFFSET,
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| 43 | trigger_rates['TriggerRate'],
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| 44 | 'g.', ms=4.,
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| 45 | label="Camera TriggerRate"
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| 46 | )
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| 47 |
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| 48 | for runs_index in range(len(runs)):
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| 49 | this_run = runs.iloc[runs_index]
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| 50 | run_number = this_run['fRunID']
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| 51 |
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| 52 | a = fjd(this_run['fRunStart'])+OFFSET
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| 53 | e = fjd(this_run['fRunStop'])+OFFSET
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| 54 |
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| 55 | ax1.axvline(a, color='g', linestyle='dashed')
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| 56 | ax1.axvline(e, color='r', linestyle='dashed')
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| 57 | ax1.text(a + (e-a)/2., 900,
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| 58 | "{0}".format(run_number),
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| 59 | horizontalalignment='center',
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| 60 | verticalalignment='center',
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| 61 | fontsize=7,
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| 62 | )
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| 63 |
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| 64 | med = this_run['median_of_board_rates']
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| 65 | std_dev = this_run['std_dev_of_board_rates']
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| 66 |
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| 67 | ax1.plot_date(
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| 68 | [a, e],
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| 69 | [med+3*std_dev, med+3*std_dev],
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| 70 | 'm-')
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| 71 |
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| 72 |
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| 73 |
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| 74 | plt.xlim((
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| 75 | fjd(runs.iloc[0]['fRunStart'])+OFFSET,
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| 76 | fjd(runs.iloc[-1]['fRunStop'])+OFFSET
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| 77 | ))
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| 78 | plt.ylim(1e-1, 1e6)
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| 79 |
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| 80 | plt.legend(
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| 81 | handles=[plot_0[0], plot_1[0]],
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| 82 | loc='lower left')
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| 83 |
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| 84 | plt.tight_layout()
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| 85 | plt.savefig("board_rate_overview_"+night_string+'.png',
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| 86 | dpi=300)
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| 87 |
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| 88 | plt.figure()
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| 89 | plt.title("fHighBoardTriggerRateRatio distribution from {0}".format(night_int))
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| 90 | plt.hist(runs.fBoardTriggerRateRatioAboveThreshold.values,
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| 91 | bins=np.arange(0,0.6,1./60.),
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| 92 | log=True )
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| 93 | plt.grid()
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| 94 | plt.xlabel("fHighBoardTriggerRateRatio")
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| 95 | plt.savefig("ratio_dist_"+night_string+'.png')
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