#!/usr/bin/python # # Werner Lustermann # ETH Zurich # from ctypes import * import numpy as np from scipy import signal # get the ROOT stuff + my shared libs from ROOT import gSystem # fitslib.so is made from fits.h and is used to access the data gSystem.Load('~/py/fitslib.so') from ROOT import * class RawData( object ): """ raw data access and calibration - open raw data file and drs calibration file - performs amplitude calibration - performs baseline substraction if wanted - provides all data in an array: row = number of pixel col = length of region of interest """ def __init__(self, data_file_name, calib_file_name, baseline_file_name=''): """ initialize object open data file and calibration data file get basic information about the data in data_file_name allocate buffers for data access data_file_name : fits or fits.gz file of the data including the path calib_file_name : fits or fits.gz file containing DRS calibration data baseline_file_name : npy file containing the baseline values """ self.data_file_name = data_file_name self.calib_file_name = calib_file_name self.baseline_file_name = baseline_file_name # baseline correction: True / False if len(baseline_file_name) == 0: self.correct_baseline = False else: self.correct_baseline = True # access data file try: data_file = fits(self.data_file_name) except IOError: print 'problem accessing data file: ', data_file_name raise # stop ! no data #: data file (fits object) self.data_file = data_file # get basic information about the data file #: region of interest (number of DRS slices read) self.nroi = data_file.GetUInt('NROI') #: number of pixels (should be 1440) self.npix = data_file.GetUInt('NPIX') #: number of events in the data run self.nevents = data_file.GetNumRows() # allocate the data memories self.event_id = c_ulong() self.trigger_type = c_ushort() #: 1D array with raw data self.data = np.zeros( self.npix * self.nroi, np.int16 ) #: slice where drs readout started self.start_cells = np.zeros( self.npix, np.int16 ) # set the pointers to the data++ data_file.SetPtrAddress('EventNum', self.event_id) data_file.SetPtrAddress('TriggerType', self.trigger_type) data_file.SetPtrAddress('StartCellData', self.start_cells) data_file.SetPtrAddress('Data', self.data) # open the calibration file try: calib_file = fits(self.calib_file_name) except IOError: print 'problem accessing calibration file: ', calib_file_name raise #: drs calibration file self.calib_file = calib_file baseline_mean = calib_file.GetN('BaselineMean') gain_mean = calib_file.GetN('GainMean') trigger_offset_mean = calib_file.GetN('TriggerOffsetMean') self.blm = np.zeros(baseline_mean, np.float32) self.gm = np.zeros(gain_mean, np.float32) self.tom = np.zeros(trigger_offset_mean, np.float32) self.Nblm = baseline_mean / self.npix self.Ngm = gain_mean / self.npix self.Ntom = trigger_offset_mean / self.npix calib_file.SetPtrAddress('BaselineMean', self.blm) calib_file.SetPtrAddress('GainMean', self.gm) calib_file.SetPtrAddress('TriggerOffsetMean', self.tom) calib_file.GetRow(0) self.v_bsl = np.zeros(self.npix) # array of baseline values (all ZERO) self.data_saverage_out = None self.pulse_time_of_maximum = None self.pulse_amplitude = None def __iter__(self): """ iterator """ return self def next(self): """ used by __iter__ """ if self.data_file.GetNextRow() == False: raise StopIteration else: self.calibrate_drs_amplitude() #print 'nevents = ', self.nevents, 'event_id = ', self.event_id.value return self.acal_data, self.start_cells, self.trigger_type.value def next_event(self): """ load the next event from disk and calibrate it """ self.data_file.GetNextRow() self.calibrate_drs_amplitude() def calibrate_drs_amplitude(self): """ perform the drs amplitude calibration of the event data """ to_mV = 2000./4096. #: 2D array with amplitude calibrated dat in mV acal_data = self.data * to_mV # convert ADC counts to mV # make 2D arrays: row = pixel, col = drs_slice acal_data = np.reshape(acal_data, (self.npix, self.nroi) ) blm = np.reshape(self.blm, (self.npix, self.Nblm) ) tom = np.reshape(self.tom, (self.npix, self.Ntom) ) gm = np.reshape(self.gm, (self.npix, self.Ngm) ) for pixel in range( self.npix ): # rotate the pixel baseline mean to the Data startCell blm_pixel = np.roll( blm[pixel,:], -self.start_cells[pixel] ) acal_data[pixel,:] -= blm_pixel[0:self.nroi] acal_data[pixel,:] -= tom[pixel, 0:self.nroi] acal_data[pixel,:] /= gm[pixel, 0:self.nroi] self.acal_data = acal_data * 1907.35 def baseline_read_values(self, file, bsl_hist='bsl_sum/hplt_mean'): """ open ROOT file with baseline histogram and read baseline values file name of the root file bsl_hist path to the histogram containing the basline values """ try: f = TFile(file) except: print 'Baseline data file could not be read: ', file return h = f.Get(bsl_hist) for i in range(self.npix): self.v_bsl[i] = h.GetBinContent(i+1) f.Close() def baseline_correct(self): """ subtract baseline from the data """ for pixel in range(self.npix): self.acal_data[pixel,:] -= self.v_bsl[pixel] def info(self): """ print run information """ print 'data file: ', data_file_name print 'calib file: ', calib_file_name print 'calibration file' print 'N baseline_mean: ', self.Nblm print 'N gain mean: ', self.Ngm print 'N TriggeroffsetMean: ', self.Ntom # ----------------------------------------------------------------------------- class fnames( object ): """ organize file names of a FACT data run """ def __init__(self, specifier = ['012', '023', '2011', '11', '24'], rpath = '/scratch_nfs/res/bsl/', zipped = True): """ specifier : list of strings defined as: [ 'DRS calibration file', 'Data file', 'YYYY', 'MM', 'DD'] rpath : directory path for the results; YYYYMMDD will be appended to rpath zipped : use zipped (True) or unzipped (Data) """ self.specifier = specifier self.rpath = rpath self.zipped = zipped self.make( self.specifier, self.rpath, self.zipped ) def make( self, specifier, rpath, zipped ): """ create (make) the filenames names : dictionary of filenames, tags { 'data', 'drscal', 'results' } data : name of the data file drscal : name of the drs calibration file results : radikal of file name(s) for results (to be completed by suffixes) """ self.specifier = specifier if zipped: dpath = '/data00/fact-construction/raw/' ext = '.fits.gz' else: dpath = '/data03/fact-construction/raw/' ext = '.fits' year = specifier[2] month = specifier[3] day = specifier[4] yyyymmdd = year + month + day dfile = specifier[1] cfile = specifier[0] rpath = rpath + yyyymmdd + '/' self.rpath = rpath self.names = {} tmp = dpath + year + '/' + month + '/' + day + '/' + yyyymmdd + '_' self.names['data'] = tmp + dfile + ext self.names['drscal'] = tmp + cfile + '.drs' + ext self.names['results'] = rpath + yyyymmdd + '_' + dfile + '_' + cfile self.data = self.names['data'] self.drscal = self.names['drscal'] self.results = self.names['results'] def info( self ): """ print complete filenames """ print 'file names:' print 'data: ', self.names['data'] print 'drs-cal: ', self.names['drscal'] print 'results: ', self.names['results'] # end of class definition: fnames( object ) def _test_iter(): """ test for function __iter__ """ data_file_name = '/data00/fact-construction/raw/2011/11/24/20111124_111.fits.gz' calib_file_name = '/data00/fact-construction/raw/2011/11/24/20111124_111.drs.fits.gz' run = RawData( data_file_name, calib_file_name ) for data, scell, tt in run: print 'data[0,0] = ', data[0,0], "start_cell[0] =", scell[0], "trigger type = ", tt if __name__ == '__main__': """ tests """ _test_iter()