"""Small but quite comprehensive example showing the use of PyTables.
The program creates an output file, 'tutorial1.h5'. You can view it
with any HDF5 generic utility.
"""
from numpy import *
from tables import *
#'-**-**-**-**-**-**- user record definition -**-**-**-**-**-**-**-'
# Define a user record to characterize some kind of particles
class Particle(IsDescription):
name = StringCol(16) # 16-character String
idnumber = Int64Col() # Signed 64-bit integer
ADCcount = UInt16Col() # Unsigned short integer
TDCcount = UInt8Col() # unsigned byte
grid_i = Int32Col() # integer
grid_j = Int32Col() # integer
pressure = Float32Col() # float (single-precision)
energy = Float64Col() # double (double-precision)
print
print '-**-**-**-**-**-**- file creation -**-**-**-**-**-**-**-'
# The name of our HDF5 filename
filename = "tutorial1.h5"
print "Creating file:", filename
# Open a file in "w"rite mode
h5file = openFile(filename, mode = "w", title = "Test file")
print
print '-**-**-**-**-**- group and table creation -**-**-**-**-**-**-**-'
# Create a new group under "/" (root)
group = h5file.createGroup("/", 'detector', 'Detector information')
print "Group '/detector' created"
# Create one table on it
table = h5file.createTable(group, 'readout', Particle, "Readout example")
print "Table '/detector/readout' created"
# Print the file
print h5file
print
print repr(h5file)
# Get a shortcut to the record object in table
particle = table.row
# Fill the table with 10 particles
for i in xrange(10):
particle['name'] = 'Particle: %6d' % (i)
particle['TDCcount'] = i % 256
particle['ADCcount'] = (i * 256) % (1 << 16)
particle['grid_i'] = i
particle['grid_j'] = 10 - i
particle['pressure'] = float(i*i)
particle['energy'] = float(particle['pressure'] ** 4)
particle['idnumber'] = i * (2 ** 34)
particle.append()
# Flush the buffers for table
table.flush()
print
print '-**-**-**-**-**-**- table data reading & selection -**-**-**-**-**-'
# Read actual data from table. We are interested in collecting pressure values
# on entries where TDCcount field is greater than 3 and pressure less than 50
pressure = [ x['pressure'] for x in table.iterrows()
if x['TDCcount'] > 3 and 20 <= x['pressure'] < 50 ]
print "Last record read:"
print repr(x)
print "Field pressure elements satisfying the cuts:"
print repr(pressure)
# Read also the names with the same cuts
names = [ x['name'] for x in table
if x['TDCcount'] > 3 and 20 <= x['pressure'] < 50 ]
print "Field names elements satisfying the cuts:"
print repr(names)
print
print '-**-**-**-**-**-**- array object creation -**-**-**-**-**-**-**-'
print "Creating a new group called '/columns' to hold new arrays"
gcolumns = h5file.createGroup(h5file.root, "columns", "Pressure and Name")
print "Creating an array called 'pressure' under '/columns' group"
h5file.createArray(gcolumns, 'pressure', array(pressure),
"Pressure column selection")
print repr(h5file.root.columns.pressure)
print "Creating another array called 'name' under '/columns' group"
h5file.createArray(gcolumns, 'name', names, "Name column selection")
print repr(h5file.root.columns.name)
print "HDF5 file:"
print h5file
# Close the file
h5file.close()
print "File '"+filename+"' created"
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