Index: fact/tools/pyscripts/pyfact/pyfact_rename.py
===================================================================
--- fact/tools/pyscripts/pyfact/pyfact_rename.py	(revision 12895)
+++ fact/tools/pyscripts/pyfact/pyfact_rename.py	(revision 12895)
@@ -0,0 +1,423 @@
+#!/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('Event ID', 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.maxPos = None
+        self.maxAmp = None
+
+
+    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, 1024) )
+        tom = np.reshape(self.tom, (self.npix, 1024) )
+        gm  = np.reshape(self.gm,  (self.npix, 1024) )
+        
+        # print 'acal Data ', acal_data.shape
+        # print 'blm shape ', blm.shape
+        # print 'gm shape  ', gm.shape
+        
+        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 filter_sliding_average(self, window_size=4):
+        """ sliding average filter
+
+        using:
+            self.acal_data
+        filling array:
+            self.data_saverage_out
+
+        """
+
+        #scipy.signal.lfilter(b, a, x, axis=-1, zi=None)
+        data_saverage_out = self.acal_data.copy()
+        b = np.ones( window_size )
+        a = np.zeros( window_size )
+        a[0] = len(b)
+        data_saverage_out[:,:] = signal.lfilter(b, a, data_saverage_out[:,:])
+
+        #: data output of sliding average filter
+        self.data_saverage_out = data_saverage_out
+
+        
+    def filter_CFD(self, length=10, ratio=0.75):
+        """ constant fraction filter
+        
+        using:
+            self.data_saverage_out
+        filling array:
+            self.data_CFD_out
+
+        """
+        
+        if self.data_saverage_out == None:
+            print ('error pyfact.filter_CFD was called without
+            prior call to filter_sliding_average')
+            print ' variable self.data_saverage_out is needed '
+            pass
+
+        data_CFD_out = self.data_saverage_out.copy()
+        b = np.zeros(length)
+        a = np.zeros(length)
+        b[0] = -1. * ratio
+        b[length-1] = 1.
+        a[0] = 1.
+        data_CFD_out[:,:] = signal.lfilter(b, a, data_CFD_out[:,:])
+        
+        #: data output of the constant fraction discriminator
+        self.data_CFD_out = data_CFD_out
+ 
+    def find_peak(self, min=30, max=250):
+        """ find maximum in search window
+        
+        using: 
+            self.data_saverage_out
+        filling arrays:
+            self.maxPos
+            self.maxAmp
+
+        """
+
+        if self.data_saverage_out == None:
+            print 'error pyfact.find_peakMax was called without prior call to filter_sliding_average'
+            print ' variable self.data_saverage_out is needed '
+            pass
+
+        maxPos = np.argmax( self.data_saverage_out[:,min:max], 1)
+        maxAmp = np.max( self.data_saverage_out[:,min:max], 1)
+        self.maxPos = maxPos
+        self.maxAmp = maxAmp
+
+    def sum_around_peak(self, left=13, right=23):
+        """ integrate signal in gate around Peak
+
+        using:
+            self.maxPos
+            self.acal_data
+        filling array:
+            self.sums
+            
+        """
+        
+        if self.maxPos == None:
+            print 'error pyfact.sum_around_peak was called without prior call of find_peak'
+            print ' variable self.maxPos is needed'
+            pass
+
+        # find left and right limit and sum the amplitudes in the range
+        sums = np.empty(self.npix)
+        for pixel in range(self.npix):
+            min = self.maxPos[pixel]-left
+            max = self.maxPos[pixel]+right
+            sums[pixel] = self.acal_data[pixel,min:max].sum()
+        
+        self.sums = sums
+        
+    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 )
+    # end of def __init__
+
+    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']
+
+    # end of make
+
+    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 def info
+
+# end of class definition: fnames( object )
+
+
+
+class histogramList( object ):
+
+    def __init__( self, name ):
+        """ set the name and create empty lists """
+        self.name  = name         # name of the list
+        self.list  = []           # list of the histograms
+        self.dict  = {}           # dictionary of histograms
+        self.hList = TObjArray()  # list a la ROOT of the histograms
+
+    def add( self, tag, h ):
+        self.list.append( h )
+        self.dict[tag] = h
+        self.hList.Add( h )
+
+
+class pixelHisto1d ( object ):
+
+    def __init__( self, name, title, Nbin, first, last, xtitle, ytitle, npix ):
+        """
+        book one dimensional histograms for each pixel
+        """
+        self.name = name
+
+        self.list = [ x for x in range( npix ) ]
+        self.hList = TObjArray()
+
+        for pixel in range( npix ):
+
+            hname  = name + ' ' + str( pixel )
+            htitle = title + ' ' + str( pixel )
+            self.list[pixel] = TH1F( hname, htitle, Nbin, first, last )
+
+            self.list[pixel].GetXaxis().SetTitle( xtitle )
+            self.list[pixel].GetYaxis().SetTitle( ytitle )
+            self.hList.Add( self.list[pixel] )
+
+# simple test method
+if __name__ == '__main__':
+    """
+    create an instance
+    """
+    data_file_name = '/data03/fact-construction/raw/2011/11/24/20111124_121.fits'
+    calib_file_name = '/data03/fact-construction/raw/2011/11/24/20111124_111.drs.fits'
+    rd = rawdata( data_file_name, calib_file_name )
+    rd.info()
+    rd.next()
+    
+# for i in range(10):
+#    df.GetNextRow() 
+
+#    print 'evNum: ', evNum.value
+#    print 'start_cells[0:9]: ', start_cells[0:9]
+#    print 'evData[0:9]: ', evData[0:9]