How to use the tables.FloatCol function in tables

import csv


# Description of events table
class _Event(tb.IsDescription):
    """
    Description of the table /events/eventTable.
    """
    # UIntAtom = uint32
    array_row = tb.UIntCol(pos=0)  # indicates the corresponding row in the
    event_start = tb.UIntCol(itemsize=8, pos=1)  # start index of the event in the data
    event_length = tb.UIntCol(pos=2)
    n_levels = tb.UIntCol(pos=3)
    raw_points_per_side = tb.UIntCol(pos=4)
    baseline = tb.FloatCol(pos=5)
    current_blockage = tb.FloatCol(pos=6)
    area = tb.FloatCol(pos=7)


class EventDatabase(tb.file.File):
    """
    PyTables HDF5 database storing events and corresponding data.
    Inherits from tables.file.File, so you can interact with this
    just as you would a PyTables File object. However, this contains
    some extra convenience methods for storing/reading events
    and event data. Note that EventDatabase allows you to interact
    with this PyTables file in the usual PyTables file manner, so you
    can potentially mangle the data from the original EventDatabase
    format.
    
    Automatically adds a group
    /events

t2 = tables.Float32Col()
    t3 = tables.Float32Col()
    t4 = tables.Float32Col()
    n1 = tables.Float32Col()
    n2 = tables.Float32Col()
    n3 = tables.Float32Col()
    n4 = tables.Float32Col()
    reference_theta = tables.Float32Col()
    reference_phi = tables.Float32Col()
    reconstructed_theta = tables.Float32Col()
    reconstructed_phi = tables.Float32Col()
    min_n134 = tables.Float32Col()

    k_energy = tables.FloatCol()
    k_core_pos = tables.FloatCol(shape=2)
    k_Num_e = tables.FloatCol()
    k_Num_mu = tables.FloatCol()
    k_dens_e = tables.FloatCol(shape=4)
    k_dens_mu = tables.FloatCol(shape=4)
    k_P200 = tables.FloatCol()
    k_T200 = tables.FloatCol()

os.mkdir(output_dir)
except OSError:
    pass

# Open a new empty HDF5 file
hdf5_name = 'links_examples.h5'
filepath_hdf5 = os.path.join(output_dir, hdf5_name)
fileh = tb.open_file(filepath_hdf5, mode = "w")

# Create some groups and add datasets to them
garrays = fileh.create_group('/', 'arrays')
a1 = fileh.create_carray(garrays, 'a1', tb.Int64Atom(shape=(2,)), shape=(100, 3),
    title='A linked array')
gtables = fileh.create_group('/', 'tables')
t1 = fileh.create_table(gtables, 't1',
    {'field1': tb.FloatCol(), 'field2': tb.IntCol()}, title='A linked table')

# Create a group and put some links there
glinks = fileh.create_group('/', 'links')

# Hard link to table t1. If we remove t1 it will still be accessible via ht1.
# Hard links are not a subclass of tables.link.Link so they don't have a
# target attribute. Because hard links behave like regular nodes one can't
# infer if ht1 is a hard link by calling its __str__ method
ht1 = fileh.create_hard_link(glinks, 'ht1', '/tables/t1')
t1.remove()

# Soft link to array a1
sa1 = fileh.create_soft_link(glinks, 'sa1', '/arrays/a1')

# Soft link to table t1. This is a dangling link because it points to a
# non-existing node. In order to get the pointed node the soft links are

class KascadeEvent(tables.IsDescription):

    """Store events from KASCADE"""

    run_id = tables.IntCol()
    event_id = tables.Int64Col()
    timestamp = tables.Time32Col()
    nanoseconds = tables.UInt32Col()
    ext_timestamp = tables.UInt64Col()

    energy = tables.FloatCol()
    core_pos = tables.FloatCol(shape=2)
    zenith = tables.FloatCol()
    azimuth = tables.FloatCol()
    Num_e = tables.FloatCol()
    Num_mu = tables.FloatCol()
    dens_e = tables.FloatCol(shape=4)
    dens_mu = tables.FloatCol(shape=4)
    P200 = tables.FloatCol()
    T200 = tables.FloatCol()


class ReconstructedKascadeEvent(tables.IsDescription):

    """Store information about reconstructed events"""

    # r, phi is core position

    id = tables.UInt32Col()
    station_id = tables.UInt8Col()
    r = tables.Float32Col()

#read the top header and determine the number of histograms
    #and the size of the histograms
    data_buffer= struct.unpack("i",hstfid.read(struct.calcsize("i")))
    nofhists = data_buffer[0]

    if config.VERBOSITY >= config.INFO_ALL:
        print("XU.io.hst2hdf5: number of histograms found: %d" %nofhists)

    #now the table and the EArray
    table_dict = {}
    table_dict["index"] = tables.IntCol()
    table_dict["channels"]  = tables.IntCol()
    table_dict["type"] = tables.IntCol()
    table_dict["name"] = tables.StringCol(itemsize=128)
    table_dict["ExpTime"] = tables.FloatCol()
    table = h5.createTable(h5path,"MCA_info",table_dict,"MCA info table")

    atype = tables.IntAtom()
    array = h5.createEArray(h5path,"MCAarray",atype,(0,nofchannels),
            "MCA data of file %s" %(hstfilename),filters=filters)

    #setup the buffer array for storing a single spectrum
    data = numpy.zeros((nofchannels),numpy.int)

    #loop over all histograms
    for i in range(nofhists):
        #read the header structure
        data_buffer = struct.unpack(fmt_hist,hstfid.read(fmt_hist_size))
        table.row["index"] = i
        table.row["type"] = data_buffer[1]
        table.row["name"]  = (("".join(data_buffer[2:(2+128)])).replace(" ","")).strip()

DETTYPE  = tables.StringCol(72)
    NEXP     = tables.IntCol(shape=(1,5))
    CCDPARM  = tables.FloatCol(shape=(1,5))
    CHEM     = tables.StringCol(72)
    MORPH    = tables.StringCol(72)
    CCOLOR   = tables.StringCol(72)
    CSIZE    = tables.StringCol(72)
    DNSMET   = tables.StringCol(72)
    DARK     = tables.StringCol(72)
    AUTORNG  = tables.FloatCol(shape=(1,5))
    ZEROADJ  = tables.FloatCol(shape=(1,4))
    XTRANS   = tables.FloatCol(shape=(1,3))
    HKL_XY   = tables.FloatCol(shape=(1,5))
    AXES2    = tables.FloatCol(shape=(1,4))
    ENDINGS2 = tables.FloatCol(shape=(1,4))
    FILTER2  = tables.FloatCol(shape=(1,2))

def GetIntArray(string):
    """
    extracts a list of integer values from a string and converts
    it to a integer numpy array.

    input arguments:
        string .............. the string

    return value:
        ia .................. a list with integer values
    """
    string  = blank_remov.sub(' ',string.strip())
    strlist = blank_split.findall(string)

    for i in range(len(strlist)):

run_id = tables.IntCol()
    event_id = tables.Int64Col()
    timestamp = tables.Time32Col()
    nanoseconds = tables.UInt32Col()
    ext_timestamp = tables.UInt64Col()

    energy = tables.FloatCol()
    core_pos = tables.FloatCol(shape=2)
    zenith = tables.FloatCol()
    azimuth = tables.FloatCol()
    Num_e = tables.FloatCol()
    Num_mu = tables.FloatCol()
    dens_e = tables.FloatCol(shape=4)
    dens_mu = tables.FloatCol(shape=4)
    P200 = tables.FloatCol()
    T200 = tables.FloatCol()


class ReconstructedKascadeEvent(tables.IsDescription):

    """Store information about reconstructed events"""

    # r, phi is core position

    id = tables.UInt32Col()
    station_id = tables.UInt8Col()
    r = tables.Float32Col()
    phi = tables.Float32Col()
    alpha = tables.Float32Col()
    t1 = tables.Float32Col()
    t2 = tables.Float32Col()
    t3 = tables.Float32Col()

MAXIMUM  = tables.IntCol()
    NONTIME  = tables.IntCol()
    NLATE    = tables.IntCol()
    FILENAM  = tables.StringCol(72)
    CREATED  = tables.StringCol(72)
    CUMULAT  = tables.FloatCol()
    ELAPSDR  = tables.FloatCol()
    ELAPSDA  = tables.FloatCol()
    OSCILLA  = tables.IntCol()
    NSTEPS   = tables.IntCol()
    RANGE    = tables.FloatCol()
    START    = tables.FloatCol()
    INCREME  = tables.FloatCol()
    NUMBER   = tables.IntCol()
    NFRAMES  = tables.IntCol()
    ANGLES   = tables.FloatCol(shape=(1,4))
    NOVER64  = tables.IntCol(shape=(1,3))
    NPIXELB  = tables.IntCol(shape=(1,2))
    NROWS    = tables.IntCol()
    NCOLS    = tables.IntCol()
    WORDORD  = tables.IntCol()
    LONGORD  = tables.IntCol()
    TARGET   = tables.StringCol(72)
    SOURCEK  = tables.FloatCol()
    SOURCEM  = tables.FloatCol()
    FILTER   = tables.StringCol(72)
    CELL     = tables.FloatCol(shape=(2,6))
    MATRIX   = tables.FloatCol(shape=(2,9))
    LOWTEMP  = tables.IntCol(shape=(1,3))
    ZOOM     = tables.FloatCol(shape=(1,3))
    CENTER   = tables.FloatCol(shape=(1,4))
    DISTANC  = tables.FloatCol(shape=(1,2)) #has to be observed

WORDORD  = tables.IntCol()
    LONGORD  = tables.IntCol()
    TARGET   = tables.StringCol(72)
    SOURCEK  = tables.FloatCol()
    SOURCEM  = tables.FloatCol()
    FILTER   = tables.StringCol(72)
    CELL     = tables.FloatCol(shape=(2,6))
    MATRIX   = tables.FloatCol(shape=(2,9))
    LOWTEMP  = tables.IntCol(shape=(1,3))
    ZOOM     = tables.FloatCol(shape=(1,3))
    CENTER   = tables.FloatCol(shape=(1,4))
    DISTANC  = tables.FloatCol(shape=(1,2)) #has to be observed
    TRAILER  = tables.IntCol()
    COMPRES  = tables.StringCol(72)
    LINEAR   = tables.StringCol(72)
    PHD      = tables.FloatCol(shape=(1,2))
    PREAMP   = tables.FloatCol(shape=(1,2)) #has to be observed
    CORRECT  = tables.StringCol(72)
    WARPFIL  = tables.StringCol(72)
    WAVELEN  = tables.FloatCol(shape=(1,4))
    MAXXY    = tables.FloatCol(shape=(1,2))
    AXIS     = tables.IntCol()
    ENDING   = tables.FloatCol(shape=(1,4))
    DETPAR   = tables.FloatCol(shape=(2,6))
    LUT      = tables.StringCol(72)
    DISPLIM  = tables.FloatCol(shape=(1,2))
    PROGRAM  = tables.StringCol(72)
    ROTATE   = tables.IntCol()
    BITMASK  = tables.StringCol(72)
    OCTMASK  = tables.IntCol(shape=(2,8))
    ESDCELL  = tables.FloatCol(shape=(2,6))
    DETTYPE  = tables.StringCol(72)

event_id = tables.UInt64Col()
    k_event_id = tables.UInt64Col()
    timestamp = tables.Time32Col()
    nanoseconds = tables.UInt32Col()
    ext_timestamp = tables.UInt64Col()
    pulseheights = tables.Int16Col(shape=4, dflt=-9999)
    integrals = tables.Int32Col(shape=4, dflt=-9999)
    n_peaks = tables.Int32Col(shape=4, dflt=-9999)
    traces = tables.Int32Col(shape=4, dflt=-1)
    k_timestamp = tables.Time32Col()
    k_nanoseconds = tables.UInt32Col()
    k_ext_timestamp = tables.UInt64Col()
    k_energy = tables.FloatCol()
    k_core_pos = tables.FloatCol(shape=2)
    k_zenith = tables.FloatCol()
    k_azimuth = tables.FloatCol()
    k_Num_e = tables.FloatCol()
    k_Num_mu = tables.FloatCol()
    k_dens_e = tables.FloatCol(shape=4)
    k_dens_mu = tables.FloatCol(shape=4)
    k_P200 = tables.FloatCol()
    k_T200 = tables.FloatCol()