| 1 | #!/usr/bin/python -tt
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| 2 | #
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| 3 | # Example
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| 4 | # * looping over RawData class object
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| 5 | #
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| 6 | import matplotlib.pyplot as plt
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| 7 | import numpy as np
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| 8 | import matplotlib.patches as patches
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| 9 |
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| 10 | from pyfact import RawData
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| 11 | #from plotters import Plotter
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| 12 | from plotters import CamPlotter
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| 13 |
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| 14 |
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| 15 |
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| 16 | from drs_spikes import DRSSpikes
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| 17 | from fir_filter import SlidingAverage
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| 18 | from extractor import GlobalMaxFinder
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| 19 | from cleaners import AmplitudeCleaner
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| 20 | from image_extractors import HillasParameter
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| 21 | from image_extractors import SimpleArea
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| 22 | from image_extractors import SimpleSize
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| 23 | import sys
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| 24 |
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| 25 | data_filename = 'data/20120223_210.fits.gz'
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| 26 | calib_filename = 'data/20120223_206.drs.fits.gz'
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| 27 |
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| 28 | run = RawData(data_filename, calib_filename, return_dict = True)
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| 29 | despike = DRSSpikes()
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| 30 | sa = SlidingAverage(8)
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| 31 | gmf = GlobalMaxFinder(30,230)
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| 32 | clean = AmplitudeCleaner(45,18)
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| 33 | clean.return_bool_mask = False
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| 34 | hillas = HillasParameter( source_pos=(1,-1) )
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| 35 |
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| 36 | p = CamPlotter('cleaned')
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| 37 |
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| 38 |
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| 39 | print 'Source Position for HillasParameter class is:'
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| 40 | print hillas.source_pos
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| 41 | print 'change it in line 34 if you like'
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| 42 |
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| 43 | for event in run:
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| 44 | # trigger_type 4 means 'physical data'
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| 45 | if event['trigger_type'].value == 4:
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| 46 |
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| 47 | print 'event number:', int(event['event_id'].value)
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| 48 |
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| 49 | #remark:
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| 50 | # currently one needs a quite long expression for getting the event id
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| 51 | # out of the event-dictionary:
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| 52 | # it looks like this: int(event['event_id'].value
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| 53 | #
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| 54 | # I will change it, such that it looks like this:
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| 55 | # event['event_id']
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| 56 | # or maybe:
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| 57 | # event['id']
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| 58 | #
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| 59 | # what do you think, dear reader?? :-)
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| 60 |
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| 61 | data = event['acal_data']
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| 62 | unspiked_data = despike(data)
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| 63 | data = sa(data)
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| 64 | amp, time = gmf(data)
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| 65 | survivors= clean(amp)
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| 66 |
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| 67 | # the cleaner also sorts all pixels into groups of islands
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| 68 | # clean.islands is a list of lists of pixel_ids
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| 69 | # the number of lists is simply the number of islands...
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| 70 | num_islands = len(clean.islands)
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| 71 |
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| 72 | # if nothing survived the cleaning, just go on
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| 73 | if num_islands == 0:
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| 74 | continue
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| 75 |
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| 76 |
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| 77 | if num_islands == 1:
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| 78 |
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| 79 | hillaspar = hillas(survivors, amp)
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| 80 |
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| 81 | print 'size', hillaspar['size']
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| 82 | print 'alpha', hillaspar['alpha']
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| 83 | print 'delta', hillaspar['delta']
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| 84 | print 'width', hillaspar['width']
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| 85 | print 'length', hillaspar['length']
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| 86 | print 'COG in euclidic coordinates:'
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| 87 | print hillaspar['cog_euc']
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| 88 |
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| 89 |
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| 90 | p ( amp, survivors )
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| 91 | plt.figure( p.fig_id )
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| 92 |
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| 93 | # paint arrow to COG
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| 94 | plt.gca().add_patch(
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| 95 | patches.Polygon(
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| 96 | [
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| 97 | (hillaspar['source_pos'][0], hillaspar['source_pos'][1]),
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| 98 | (hillaspar['cog_euc'][0], hillaspar['cog_euc'][1])
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| 99 | ] ) )
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| 100 | # paint copy of x-axis through COG
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| 101 | plt.axhline( hillaspar['cog_euc'][1] )
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| 102 |
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| 103 | plt.gca().add_patch(
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| 104 | patches.Ellipse(
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| 105 | ( hillaspar['cog_euc'][0], hillaspar['cog_euc'][1] ),
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| 106 | 2*hillaspar['length'],
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| 107 | 2*hillaspar['width'],
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| 108 | hillaspar['delta'] /np.pi * 180,
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| 109 | facecolor='none' ) )
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| 110 |
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| 111 | plt.gca().add_patch(
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| 112 | patches.Circle(
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| 113 | (hillaspar['source_pos'][0], hillaspar['source_pos'][1] ),
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| 114 | 0.5 ) )
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| 115 |
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| 116 | answer = raw_input('hit <Enter> to go on .... hit "q" to quit')
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| 117 | if 'q' in answer:
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| 118 | break
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| 119 | print 'good bye'
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