| 1 | #!/usr/bin/python
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| 2 | #
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| 3 | # Werner Lustermann
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| 4 | # ETH Zurich
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| 5 | #
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| 6 | from ctypes import *
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| 7 | import numpy as np
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| 8 | from scipy import signal
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| 9 |
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| 10 | # get the ROOT stuff + my shared libs
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| 11 | from ROOT import gSystem
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| 12 | # fitslib.so is made from fits.h and is used to access the data
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| 13 | gSystem.Load('~/py/fitslib.so')
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| 14 | from ROOT import *
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| 15 |
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| 16 |
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| 17 | class RawData( object ):
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| 18 | """ raw data access and calibration
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| 19 |
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| 20 | - open raw data file and drs calibration file
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| 21 | - performs amplitude calibration
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| 22 | - performs baseline substraction if wanted
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| 23 | - provides all data in an array:
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| 24 | row = number of pixel
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| 25 | col = length of region of interest
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| 26 |
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| 27 | """
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| 28 |
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| 29 | def __init__(self, data_file_name,
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| 30 | calib_file_name, baseline_file_name=''):
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| 31 | """ initialize object
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| 32 |
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| 33 | open data file and calibration data file
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| 34 | get basic information about the data in data_file_name
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| 35 | allocate buffers for data access
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| 36 |
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| 37 | data_file_name : fits or fits.gz file of the data including the path
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| 38 | calib_file_name : fits or fits.gz file containing DRS calibration data
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| 39 | baseline_file_name : npy file containing the baseline values
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| 40 |
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| 41 | """
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| 42 |
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| 43 | self.data_file_name = data_file_name
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| 44 | self.calib_file_name = calib_file_name
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| 45 | self.baseline_file_name = baseline_file_name
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| 46 |
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| 47 | # baseline correction: True / False
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| 48 | if len(baseline_file_name) == 0:
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| 49 | self.correct_baseline = False
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| 50 | else:
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| 51 | self.correct_baseline = True
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| 52 |
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| 53 | # access data file
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| 54 | try:
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| 55 | data_file = fits(self.data_file_name)
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| 56 | except IOError:
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| 57 | print 'problem accessing data file: ', data_file_name
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| 58 | raise # stop ! no data
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| 59 | #: data file (fits object)
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| 60 | self.data_file = data_file
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| 61 |
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| 62 | # get basic information about the data file
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| 63 | #: region of interest (number of DRS slices read)
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| 64 | self.nroi = data_file.GetUInt('NROI')
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| 65 | #: number of pixels (should be 1440)
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| 66 | self.npix = data_file.GetUInt('NPIX')
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| 67 | #: number of events in the data run
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| 68 | self.nevents = data_file.GetNumRows()
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| 69 |
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| 70 | # allocate the data memories
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| 71 | self.event_id = c_ulong()
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| 72 | self.trigger_type = c_ushort()
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| 73 | #: 1D array with raw data
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| 74 | self.data = np.zeros( self.npix * self.nroi, np.int16 )
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| 75 | #: slice where drs readout started
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| 76 | self.start_cells = np.zeros( self.npix, np.int16 )
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| 77 |
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| 78 | # set the pointers to the data++
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| 79 | data_file.SetPtrAddress('EventNum', self.event_id)
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| 80 | data_file.SetPtrAddress('TriggerType', self.trigger_type)
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| 81 | data_file.SetPtrAddress('StartCellData', self.start_cells)
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| 82 | data_file.SetPtrAddress('Data', self.data)
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| 83 |
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| 84 | # open the calibration file
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| 85 | try:
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| 86 | calib_file = fits(self.calib_file_name)
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| 87 | except IOError:
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| 88 | print 'problem accessing calibration file: ', calib_file_name
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| 89 | raise
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| 90 | #: drs calibration file
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| 91 | self.calib_file = calib_file
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| 92 |
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| 93 | baseline_mean = calib_file.GetN('BaselineMean')
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| 94 | gain_mean = calib_file.GetN('GainMean')
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| 95 | trigger_offset_mean = calib_file.GetN('TriggerOffsetMean')
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| 96 |
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| 97 | self.blm = np.zeros(baseline_mean, np.float32)
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| 98 | self.gm = np.zeros(gain_mean, np.float32)
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| 99 | self.tom = np.zeros(trigger_offset_mean, np.float32)
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| 100 |
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| 101 | self.Nblm = baseline_mean / self.npix
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| 102 | self.Ngm = gain_mean / self.npix
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| 103 | self.Ntom = trigger_offset_mean / self.npix
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| 104 |
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| 105 | calib_file.SetPtrAddress('BaselineMean', self.blm)
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| 106 | calib_file.SetPtrAddress('GainMean', self.gm)
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| 107 | calib_file.SetPtrAddress('TriggerOffsetMean', self.tom)
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| 108 | calib_file.GetRow(0)
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| 109 |
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| 110 | self.v_bsl = np.zeros(self.npix) # array of baseline values (all ZERO)
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| 111 | self.data_saverage_out = None
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| 112 | self.pulse_time_of_maximum = None
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| 113 | self.pulse_amplitude = None
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| 114 |
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| 115 | def __iter__(self):
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| 116 | """ iterator """
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| 117 | return self
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| 118 |
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| 119 | def next(self):
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| 120 | """ used by __iter__ """
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| 121 | if self.event_id.value == self.nevents:
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| 122 | raise StopIteration
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| 123 | else:
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| 124 | self.data_file.GetNextRow()
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| 125 | self.calibrate_drs_amplitude()
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| 126 | return self.acal_data, self.start_cells, self.trigger_type.value
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| 127 |
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| 128 | def next_event(self):
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| 129 | """ load the next event from disk and calibrate it
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| 130 |
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| 131 | """
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| 132 |
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| 133 | self.data_file.GetNextRow()
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| 134 | self.calibrate_drs_amplitude()
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| 135 |
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| 136 | def calibrate_drs_amplitude(self):
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| 137 | """ perform the drs amplitude calibration of the event data
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| 138 |
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| 139 | """
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| 140 |
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| 141 | to_mV = 2000./4096.
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| 142 | #: 2D array with amplitude calibrated dat in mV
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| 143 | acal_data = self.data * to_mV # convert ADC counts to mV
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| 144 |
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| 145 | # make 2D arrays: row = pixel, col = drs_slice
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| 146 | acal_data = np.reshape(acal_data, (self.npix, self.nroi) )
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| 147 | blm = np.reshape(self.blm, (self.npix, 1024) )
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| 148 | tom = np.reshape(self.tom, (self.npix, 1024) )
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| 149 | gm = np.reshape(self.gm, (self.npix, 1024) )
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| 150 |
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| 151 | for pixel in range( self.npix ):
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| 152 | # rotate the pixel baseline mean to the Data startCell
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| 153 | blm_pixel = np.roll( blm[pixel,:], -self.start_cells[pixel] )
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| 154 | acal_data[pixel,:] -= blm_pixel[0:self.nroi]
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| 155 | acal_data[pixel,:] -= tom[pixel, 0:self.nroi]
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| 156 | acal_data[pixel,:] /= gm[pixel, 0:self.nroi]
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| 157 |
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| 158 | self.acal_data = acal_data * 1907.35
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| 159 |
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| 160 |
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| 161 | def filter_sliding_average(self, window_size=4):
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| 162 | """ sliding average filter
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| 163 |
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| 164 | using:
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| 165 | self.acal_data
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| 166 | filling array:
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| 167 | self.data_saverage_out
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| 168 |
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| 169 | """
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| 170 |
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| 171 | #scipy.signal.lfilter(b, a, x, axis=-1, zi=None)
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| 172 | data_saverage_out = self.acal_data.copy()
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| 173 | b = np.ones( window_size )
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| 174 | a = np.zeros( window_size )
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| 175 | a[0] = len(b)
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| 176 | data_saverage_out[:,:] = signal.lfilter(b, a, data_saverage_out[:,:])
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| 177 |
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| 178 | #: data output of sliding average filter
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| 179 | self.data_saverage_out = data_saverage_out
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| 180 |
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| 181 |
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| 182 | def filter_CFD(self, length=10, ratio=0.75):
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| 183 | """ constant fraction discriminator (implemented as FIR)
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| 184 |
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| 185 | using:
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| 186 | self.data_saverage_out
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| 187 | filling array:
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| 188 | self.data_CFD_out
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| 189 |
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| 190 | """
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| 191 |
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| 192 | if self.data_saverage_out == None:
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| 193 | print """error pyfact.filter_CFD was called without
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| 194 | prior call to filter_sliding_average
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| 195 | variable self.data_saverage_out is needed
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| 196 | """
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| 197 |
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| 198 | data_CFD_out = self.data_saverage_out.copy()
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| 199 | b = np.zeros(length)
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| 200 | a = np.zeros(length)
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| 201 | b[0] = -1. * ratio
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| 202 | b[length-1] = 1.
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| 203 | a[0] = 1.
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| 204 | data_CFD_out[:,:] = signal.lfilter(b, a, data_CFD_out[:,:])
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| 205 |
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| 206 | #: data output of the constant fraction discriminator
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| 207 | self.data_CFD_out = data_CFD_out
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| 208 |
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| 209 | def find_peak(self, min=30, max=250):
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| 210 | """ find maximum in search window
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| 211 |
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| 212 | using:
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| 213 | self.data_saverage_out
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| 214 | filling arrays:
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| 215 | self.pulse_time_of_maximum
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| 216 | self.pulse_amplitude
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| 217 |
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| 218 | """
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| 219 |
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| 220 | if self.data_saverage_out == None:
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| 221 | print """error pyfact.find_peakMax was called without \
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| 222 | prior call to filter_sliding_average
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| 223 | variable self.data_saverage_out is needed"""
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| 224 | pass
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| 225 |
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| 226 | pulse_time_of_maximum = np.argmax( self.data_saverage_out[:,min:max],
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| 227 | 1)
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| 228 | pulse_amplitude = np.max( self.data_saverage_out[:,min:max], 1)
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| 229 | self.pulse_time_of_maximum = pulse_time_of_maximum
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| 230 | self.pulse_amplitude = pulse_amplitude
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| 231 |
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| 232 | def sum_around_peak(self, left=13, right=23):
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| 233 | """ integrate signal in gate around Peak
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| 234 |
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| 235 | using:
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| 236 | self.pulse_time_of_maximum
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| 237 | self.acal_data
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| 238 | filling array:
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| 239 | self.pulse_integral_simple
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| 240 |
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| 241 | """
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| 242 |
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| 243 | if self.pulse_time_of_maximum == None:
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| 244 | print """error pyfact.sum_around_peak was called \
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| 245 | without prior call of find_peak
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| 246 | variable self.pulse_time_of_maximum is needed"""
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| 247 | pass
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| 248 |
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| 249 | # find left and right limit and sum the amplitudes in the range
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| 250 | pulse_integral_simple = np.empty(self.npix)
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| 251 | for pixel in range(self.npix):
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| 252 | min = self.pulse_time_of_maximum[pixel]-left
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| 253 | max = self.pulse_time_of_maximum[pixel]+right
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| 254 | pulse_integral_simple[pixel] = self.acal_data[pixel,min:max].sum()
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| 255 |
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| 256 | self.pulse_integral_simple = pulse_integral_simple
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| 257 |
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| 258 | def baseline_read_values(self, file, bsl_hist='bsl_sum/hplt_mean'):
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| 259 | """
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| 260 |
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| 261 | open ROOT file with baseline histogram and read baseline values
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| 262 | file name of the root file
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| 263 | bsl_hist path to the histogram containing the basline values
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| 264 |
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| 265 | """
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| 266 |
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| 267 | try:
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| 268 | f = TFile(file)
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| 269 | except:
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| 270 | print 'Baseline data file could not be read: ', file
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| 271 | return
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| 272 |
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| 273 | h = f.Get(bsl_hist)
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| 274 |
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| 275 | for i in range(self.npix):
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| 276 | self.v_bsl[i] = h.GetBinContent(i+1)
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| 277 |
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| 278 | f.Close()
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| 279 |
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| 280 | def baseline_correct(self):
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| 281 | """ subtract baseline from the data
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| 282 |
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| 283 | """
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| 284 |
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| 285 | for pixel in range(self.npix):
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| 286 | self.acal_data[pixel,:] -= self.v_bsl[pixel]
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| 287 |
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| 288 | def info(self):
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| 289 | """ print run information
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| 290 |
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| 291 | """
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| 292 |
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| 293 | print 'data file: ', data_file_name
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| 294 | print 'calib file: ', calib_file_name
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| 295 | print 'calibration file'
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| 296 | print 'N baseline_mean: ', self.Nblm
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| 297 | print 'N gain mean: ', self.Ngm
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| 298 | print 'N TriggeroffsetMean: ', self.Ntom
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| 299 |
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| 300 | # -----------------------------------------------------------------------------
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| 301 | class fnames( object ):
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| 302 | """ organize file names of a FACT data run
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| 303 |
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| 304 | """
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| 305 |
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| 306 | def __init__(self, specifier = ['012', '023', '2011', '11', '24'],
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| 307 | rpath = '/scratch_nfs/res/bsl/',
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| 308 | zipped = True):
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| 309 | """
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| 310 | specifier : list of strings defined as:
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| 311 | [ 'DRS calibration file', 'Data file', 'YYYY', 'MM', 'DD']
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| 312 |
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| 313 | rpath : directory path for the results; YYYYMMDD will be appended to rpath
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| 314 | zipped : use zipped (True) or unzipped (Data)
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| 315 |
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| 316 | """
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| 317 |
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| 318 | self.specifier = specifier
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| 319 | self.rpath = rpath
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| 320 | self.zipped = zipped
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| 321 |
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| 322 | self.make( self.specifier, self.rpath, self.zipped )
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| 323 |
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| 324 |
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| 325 | def make( self, specifier, rpath, zipped ):
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| 326 | """ create (make) the filenames
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| 327 |
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| 328 | names : dictionary of filenames, tags { 'data', 'drscal', 'results' }
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| 329 | data : name of the data file
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| 330 | drscal : name of the drs calibration file
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| 331 | results : radikal of file name(s) for results (to be completed by suffixes)
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| 332 | """
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| 333 |
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| 334 | self.specifier = specifier
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| 335 |
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| 336 | if zipped:
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| 337 | dpath = '/data00/fact-construction/raw/'
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| 338 | ext = '.fits.gz'
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| 339 | else:
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| 340 | dpath = '/data03/fact-construction/raw/'
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| 341 | ext = '.fits'
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| 342 |
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| 343 | year = specifier[2]
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| 344 | month = specifier[3]
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| 345 | day = specifier[4]
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| 346 |
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| 347 | yyyymmdd = year + month + day
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| 348 | dfile = specifier[1]
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| 349 | cfile = specifier[0]
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| 350 |
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| 351 | rpath = rpath + yyyymmdd + '/'
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| 352 | self.rpath = rpath
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| 353 | self.names = {}
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| 354 |
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| 355 | tmp = dpath + year + '/' + month + '/' + day + '/' + yyyymmdd + '_'
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| 356 | self.names['data'] = tmp + dfile + ext
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| 357 | self.names['drscal'] = tmp + cfile + '.drs' + ext
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| 358 | self.names['results'] = rpath + yyyymmdd + '_' + dfile + '_' + cfile
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| 359 |
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| 360 | self.data = self.names['data']
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| 361 | self.drscal = self.names['drscal']
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| 362 | self.results = self.names['results']
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| 363 |
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| 364 | def info( self ):
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| 365 | """ print complete filenames
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| 366 |
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| 367 | """
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| 368 |
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| 369 | print 'file names:'
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| 370 | print 'data: ', self.names['data']
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| 371 | print 'drs-cal: ', self.names['drscal']
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| 372 | print 'results: ', self.names['results']
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| 373 |
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| 374 | # end of class definition: fnames( object )
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| 375 |
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| 376 | def _test_iter():
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| 377 | """ test for function __iter__ """
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| 378 |
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| 379 | data_file_name = '/data00/fact-construction/raw/2011/11/24/20111124_111.fits.gz'
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| 380 | calib_file_name = '/data00/fact-construction/raw/2011/11/24/20111124_111.drs.fits.gz'
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| 381 | run = RawData( data_file_name, calib_file_name )
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| 382 |
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| 383 | for data, scell, tt in run:
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| 384 | print 'data[0,0] = ', data[0,0], "start_cell[0] =", scell[0], "trigger type = ", tt
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| 385 |
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| 386 |
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| 387 | if __name__ == '__main__':
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| 388 | """ tests """
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| 389 |
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| 390 | _test_iter()
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