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>Multidimensional table cells and automatic
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CONTENT="Modular DocBook HTML Stylesheet Version 1.79"><LINK
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TITLE="PyTables User's Guide"
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HREF="index.html"><LINK
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HREF="c514.html"><LINK
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TITLE="Commiting data to tables and arrays"
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HREF="x921.html"><LINK
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TITLE="Exercising the Undo/Redo feature"
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HREF="x1085.html"></HEAD
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SUMMARY="Header navigation table"
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> User's Guide: Hierarchical datasets in Python - Release 1.3.2</TH
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>Chapter 3. Tutorials</TD
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>3.4. Multidimensional table cells and automatic
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>Now it's time for a more real-life example (i.e. with
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errors in the code). We will create two groups that branch
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directly from the <SAMP
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will put three tables in each group. In
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> we will put tables based on the
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> descriptor and in <SAMP
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the tables based the <SAMP
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> Afterwards, we will provision the tables with a number of
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records. Finally, we will read the newly-created table
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>/Events/TEvent3</SAMP
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> and select some values from it,
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using a comprehension list.
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>Look at the next script (you can find it in
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>examples/tutorial2.py</SAMP
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>). It appears to do all of
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the above, but it contains some small bugs. Note that this
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> class is not directly related to the
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one defined in last tutorial; this class is simpler (note,
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>We also introduce a new manner to describe a <SAMP
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as a dictionary, as you can see in the <SAMP
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description. See section <A
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HREF="x1533.html#createTableDescr"
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> about the different kinds of
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descriptor objects that can be passed to the
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> from numarray import *
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# Describe a particle record
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class Particle(IsDescription):
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name = StringCol(length=16) # 16-character String
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lati = IntCol() # integer
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longi = IntCol() # integer
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pressure = Float32Col(shape=(2,3)) # array of floats (single-precision)
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temperature = FloatCol(shape=(2,3)) # array of doubles (double-precision)
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# Another way to describe the columns of a table
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"name" : StringCol(length=16),
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"pressure" : Float32Col(shape=(2,3)),
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"temperature" : FloatCol(shape=(2,3)),
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# Open a file in "w"rite mode
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fileh = openFile("tutorial2.h5", mode = "w")
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# Get the HDF5 root group
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for groupname in ("Particles", "Events"):
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group = fileh.createGroup(root, groupname)
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# Now, create and fill the tables in the Particles group
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gparticles = root.Particles
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# Create 3 new tables
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for tablename in ("TParticle1", "TParticle2", "TParticle3"):
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table = fileh.createTable("/Particles", tablename, Particle,
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"Particles: "+tablename)
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# Get the record object associated with the table:
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# Fill the table with data for 257 particles
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for i in xrange(257):
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# First, assign the values to the Particle record
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particle['name'] = 'Particle: %6d' % (i)
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particle['longi'] = 10 - i
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########### Detectable errors start here. Play with them!
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particle['pressure'] = array(i*arange(2*3), shape=(2,4)) # Incorrect
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#particle['pressure'] = array(i*arange(2*3), shape=(2,3)) # Correct
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########### End of errors
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particle['temperature'] = (i**2) # Broadcasting
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# This injects the Record values
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# Flush the table buffers
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for tablename in ("TEvent1", "TEvent2", "TEvent3"):
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# Create a table in the Events group
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table = fileh.createTable(root.Events, tablename, Event,
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"Events: "+tablename)
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# Get the record object associated with the table:
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# Fill the table with data on 257 events
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for i in xrange(257):
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# First, assign the values to the Event record
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event['name'] = 'Event: %6d' % (i)
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event['TDCcount'] = i % (1<<8) # Correct range
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########### Detectable errors start here. Play with them!
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#event['xcoord'] = float(i**2) # Correct spelling
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event['xcoor'] = float(i**2) # Wrong spelling
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event['ADCcount'] = i * 2 # Correct type
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#event['ADCcount'] = "sss" # Wrong type
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########### End of errors
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event['ycoord'] = float(i)**4
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# This injects the Record values
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# Read the records from table "/Events/TEvent3" and select some
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table = root.Events.TEvent3
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e = [ p['TDCcount'] for p in table
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if p['ADCcount'] < 20 and 4 <= p['TDCcount'] < 15 ]
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print "Last record ==>", p
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print "Selected values ==>", e
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print "Total selected records ==> ", len(e)
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# Finally, close the file (this also will flush all the remaining buffers)
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NAME="subsection3.4.1"
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>3.4.1. Shape checking</A
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>If you look at the code carefully, you'll see that it
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won't work. You will get the following error:</P
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> $ python tutorial2.py
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Traceback (most recent call last):
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File "tutorial2.py", line 53, in ?
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particle['pressure'] = array(i*arange(2*3), shape=(2,4)) # Incorrect
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File "/usr/local/lib/python2.2/site-packages/numarray/numarraycore.py",
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File "/usr/local/lib/python2.2/site-packages/numarray/generic.py",
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line 530, in setshape
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raise ValueError("New shape is not consistent with the old shape")
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ValueError: New shape is not consistent with the old shape
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>This error indicates that you are trying to assign an
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array with an incompatible shape to a table cell. Looking
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at the source, we see that we were trying to assign an
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> element, which was defined with the
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>In general, these kinds of operations are forbidden, with
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one valid exception: when you assign a <SPAN
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value to a multidimensional column cell, all the cell
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elements are populated with the value of the scalar. For
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> particle['temperature'] = (i**2) # Broadcasting
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> is assigned to all the
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elements of the <SAMP
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capability is provided by the <SAMP
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package and is known as <SPAN
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NAME="subsection3.4.2"
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>3.4.2. Field name checking</A
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>After fixing the previous error and rerunning the
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program, we encounter another error:
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> $ python tutorial2.py
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Traceback (most recent call last):
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File "tutorial2.py", line 74, in ?
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event['xcoor'] = float(i**2) # Wrong spelling
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File "src/hdf5Extension.pyx",
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line 1812, in hdf5Extension.Row.__setitem__
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raise KeyError, "Error setting \"%s\" field.\n %s" % \
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KeyError: Error setting "xcoor" field.
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Error was: "exceptions.KeyError: xcoor"
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>This error indicates that we are attempting to assign a
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value to a non-existent field in the <SPAN
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object. By looking carefully at the <SAMP
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class attributes, we see that we misspelled the
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> field (we wrote <SAMP
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instead). This is unusual behavior for Python, as normally
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when you assign a value to a non-existent instance
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variable, Python creates a new variable with that
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name. Such a feature can be dangerous when dealing with an
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object that contains a fixed list of field names. PyTables
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checks that the field exists and raises a
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> if the check fails.
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NAME="subsection3.4.3"
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>3.4.3. Data type checking</A
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>Finally, in order to test type checking, we will change
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> event.ADCcount = i * 2 # Correct type
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> event.ADCcount = "sss" # Wrong type
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>This modification will cause the following <SAMP
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exception to be raised when the script is executed:
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> $ python tutorial2.py
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Traceback (most recent call last):
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File "tutorial2.py", line 76, in ?
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event['ADCcount'] = "sss" # Wrong type
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File "src/hdf5Extension.pyx",
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line 1812, in hdf5Extension.Row.__setitem__
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raise KeyError, "Error setting \"%s\" field.\n %s" % \
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KeyError: Error setting "ADCcount" field.
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Error was: "exceptions.TypeError: NA_setFromPythonScalar: bad value type."
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>You can see the structure created with this (corrected)
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HREF="x1017.html#tutorial2-tableview"
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In particular, note the multidimensional column cells in
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>/Particles/TParticle2</SAMP
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NAME="tutorial2-tableview"
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>Figure 3.4. Table hierarchy for tutorial 2.</B
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SRC="tutorial2-tableview.png"></P
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SUMMARY="Footer navigation table"
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>Commiting data to tables and arrays</TD
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>Exercising the Undo/Redo feature</TD
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