Index: fact/tools/pyscripts/pyfact/pyfact.py
===================================================================
--- fact/tools/pyscripts/pyfact/pyfact.py	(revision 12812)
+++ fact/tools/pyscripts/pyfact/pyfact.py	(revision 12812)
@@ -0,0 +1,302 @@
+#!/usr/bin/python
+#
+# Werner Lustermann
+# ETH Zurich
+#
+from ctypes import *
+import numpy as np
+
+# 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
+    """
+    # constructor of the classe
+    def __init__( self, dfname,  calfname, bslfname='' ):
+        """
+        open data file and calibration data file
+        get basic information about the data in dfname
+        allocate buffers for data access
+
+        dfname   : fits or fits.gz file containing the data including the path
+        calfname : fits or fits.gz file containing DRS calibration data
+        bslfname : npy file containing the baseline values
+        """
+        self.dfname   = dfname
+        self.calfname = calfname
+        self.bslfname = bslfname
+        
+        # baseline correction: True / False
+        if len( bslfname ) == 0:
+            self.correct_baseline = False
+        else:
+            self.correct_baseline = True
+        
+        # access data file
+        try:
+            df = fits( self.dfname )
+        except IOError:
+            print 'problem accessing data file: ', dfname
+            raise # stop ! no data
+        self.df = df
+        
+        # get basic information about the data file
+        self.NROI    = df.GetUInt( 'NROI' ) # region of interest (length of DRS pipeline read out)
+        self.NPIX    = df.GetUInt( 'NPIX' ) # number of pixels (should be 1440)
+        self.NEvents = df.GetNumRows()      # find number of events
+        # allocate the data memories
+        self.evNum = c_ulong()
+        self.Data  = np.zeros( self.NPIX * self.NROI, np.int16 ) 
+        self.startCells = np.zeros( self.NPIX, np.int16 )
+        # set the pointers to the data++
+        df.SetPtrAddress( 'EventNum', self.evNum )
+        df.SetPtrAddress( 'StartCellData', self.startCells ) # DRS readout start cell
+        df.SetPtrAddress( 'Data', self.Data ) # this is what you would expect
+        # df.GetNextRow() # access the first event
+        
+        # access calibration file
+        try:
+            calf = fits( self.calfname )
+        except IOError:
+            print 'problem accessing calibration file: ', calfname
+            raise
+        self.calf = calf
+        #
+        BaselineMean      = calf.GetN('BaselineMean')
+        GainMean          = calf.GetN('GainMean')
+        TriggerOffsetMean = calf.GetN('TriggerOffsetMean')
+
+        self.blm = np.zeros( BaselineMean, np.float32 )
+        self.gm  = np.zeros( GainMean, np.float32 )
+        self.tom = np.zeros( TriggerOffsetMean, np.float32 )
+
+        self.Nblm = BaselineMean / self.NPIX
+        self.Ngm  = GainMean / self.NPIX
+        self.Ntom  = TriggerOffsetMean / self.NPIX
+
+        calf.SetPtrAddress( 'BaselineMean', self.blm )
+        calf.SetPtrAddress( 'GainMean', self.gm )
+        calf.SetPtrAddress( 'TriggerOffsetMean', self.tom )
+        calf.GetRow(0)
+
+        self.v_bsl = np.zeros( self.NPIX ) # array with baseline values (all ZERO)
+
+
+    def next( self ):
+        """
+        load the next event from disk and calibrate it
+        """
+        self.df.GetNextRow()
+        self.calibrate_drsAmplitude()
+
+        
+    def calibrate_drsAmplitude( self ):
+        """
+        perform amplitude calibration for the event 
+        """
+        tomV = 2000./4096.
+        acalData = self.Data * tomV # convert into mV
+
+        # reshape arrays: row = pixel, col = drs_slice
+        acalData = np.reshape( acalData, (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 ', acalData.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.startCells[pixel] )
+            acalData[pixel,:] -= blm_pixel[0:self.NROI]
+            acalData[pixel,:] -= tom[pixel, 0:self.NROI]
+            acalData[pixel,:] /= gm[pixel,  0:self.NROI]
+            
+	self.acalData = acalData * 1907.35
+    
+        # print 'acalData ', self.acalData[0:2,0:20]
+
+    def ReadBaseline( 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 CorrectBaseline( self ):
+        """
+        apply baseline correction
+        """
+        for pixel in range( self.NPIX ):
+            self.acalData[pixel,:] -= self.v_bsl[pixel]
+            
+        
+    def info( self ):
+        """
+        print information
+        """
+        print 'data file:  ', dfname
+        print 'calib file: ', calfname
+        print 'calibration file'
+        print 'N BaselineMean: ', self.Nblm
+        print 'N GainMean: ', 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/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
+    """
+    dfname = '/data03/fact-construction/raw/2011/11/24/20111124_121.fits'
+    calfname = '/data03/fact-construction/raw/2011/11/24/20111124_111.drs.fits'
+    rd = rawdata( dfname, calfname )
+    rd.info()
+    rd.next()
+    
+# for i in range(10):
+#    df.GetNextRow() 
+
+#    print 'evNum: ', evNum.value
+#    print 'startCells[0:9]: ', startCells[0:9]
+#    print 'evData[0:9]: ', evData[0:9]