Oct2Py will create methods for you on the fly, which correspond to Octave functions. For example:
>>> from oct2py import octave
>>> octave.ones(3)
array([[ 1., 1., 1.],
[ 1., 1., 1.],
[ 1., 1., 1.]])
If you pass keyword arguments to the function, they will be treated as Octave keywords, for example, octave.plot(x, y, linewidth=3) becomes plot(x, y, ‘linewidth’, 3). Arguments that are integer type will be converted to floats unless you set convert_to_float=False.
Additionally, you can look up the documentation for one of these methods using help()
>>> help(octave.ones)
'ones' is a built-in function
...
Oct2Py supports code completion in IPython, so once you have created a method, you can recall it on the fly, so octave.one<TAB> would give you ones. Structs (mentioned below) also support code completion for attributes.
You can share data with an Octave session explicitly using the push and pull methods. When using other Oct2Py methods, the variable names in Octave start with underscores because they are temporary (you would only see this if you were using logging).
>>> from oct2py import octave
>>> octave.push('a', 1)
>>> octave.pull('a')
1
In order to use an m-file in Oct2Py you must first call addpath for the directory containing the script. You can then use it as a dynamic function or use the eval function to call it. Alternatively, you can call feval with the full path.
>>> from oct2py import octave
>>> octave.addpath('/path/to/')
>>> octave.myscript(1, 2)
>>> # or
>>> octave.eval("myscript(1, 2)")
>>> # as feval
>>> octave.feval('/path/to/myscript', 1, 2)
Oct2Py supports the Octave keyboard function which drops you into an interactive Octave prompt in the current session. This also works in the IPython Notebook. Note: If you use the keyboard command and the session hangs, try opening an Octave session from your terminal and see if the keyboard command hangs there too. You may need to update your version of Octave.
Oct2Py supports logging of session interaction. You can provide a logger to the constructor or set one at any time.
>>> import logging
>>> from oct2py import Oct2Py, get_log
>>> oc = Oct2Py(logger=get_log())
>>> oc.logger = get_log('new_log')
>>> oc.logger.setLevel(logging.INFO)
All Oct2Py methods support a verbose keyword. If True, the commands are logged at the INFO level, otherwise they are logged at the DEBUG level.
If you’d like to call an Octave function that is also an Oct2Py method, you must add a trailing underscore. For example:
>>> from oct2py import octave
>>> octave.eval_('a=1')
'a = 1'
The methods that shadow Octave builtins are: exit and eval.
Oct2Py sessions have a timeout attribute that determines how long to wait for a command to complete. The default is 1e6 seconds (indefinite). You may either set the timeout for the session, or as a keyword argument to an individual command. The session is closed in the event of a timeout.
>>> from oct2py import octave
>>> octave.timeout = 3
>>> octave.sleep(2)
>>> octave.sleep(2, timeout=1)
Traceback (most recent call last):
...
oct2py.utils.Oct2PyError: Session timed out
Oct2Py uses the gnuplot graphics toolkit by default. Fltk has been known not to work on some systems. To change toolkits:
>>> from oct2py import octave
>>> octave.available_graphics_toolkits()
[u'fltk', u'gnuplot']
>>> octave.graphics_toolkit('fltk')
Oct2Py can be used as a Context Manager. The session will be closed and the temporary m-files will be deleted when the Context Manager exits.
>>> from oct2py import Oct2Py
>>> with Oct2Py() as oc:
>>> oc.ones(10)
Struct is a convenience class that mimics an Octave structure variable type. It is a dictionary with attribute lookup, and it creates sub-structures on the fly of arbitrary nesting depth. It can be pickled. You can also use tab completion for attributes when in IPython.
>>> from oct2py import Struct
>>> test = Struct()
>>> test['foo'] = 1
>>> test.bizz['buzz'] = 'bar'
>>> test
{'foo': 1, 'bizz': {'buzz': 'bar'}}
>>> import pickle
>>> p = pickle.dumps(test)
Oct2Py supports Unicode characters, so you may feel free to use m-files that contain them.
There is a performance penalty for passing information using MAT files. If you have a lot of calculations, it is probably better to make an m-file that does the looping and data aggregation, and pass that back to Python for further processing. To see an example of the speed penalty on your machine, run:
>>> import oct2py
>>> oct2py.speed_check()
If you want to use threading, you must create a new Oct2Py instance for each thread. The octave convenience instance is in itself not threadsafe. Each Oct2Py instance has its own dedicated Octave session and will not interfere with any other session.
Oct2Py provides OctaveMagic for IPython, including inline plotting in notebooks. This requires IPython >= 1.0.0.