Hi,
When I use an on line code snippet, see below please, I find that
'converged' in class ConvergenceMonitor is seen as a data.
---------
class ConvergenceMonitor(object):
"""Monitors and reports convergence to :data:`sys.stderr`.
Parameters
----------
tol : double
Convergence threshold. EM has converged either if the maximum
number of iterations is reached or the log probability
improvement between the two consecutive iterations is less
than threshold.
n_iter : int
Maximum number of iterations to perform.
verbose : bool
If ``True`` then per-iteration convergence reports are printed,
otherwise the monitor is mute.
Attributes
----------
history : deque
The log probability of the data for the last two training
iterations. If the values are not strictly increasing, the
model did not converge.
iter : int
Number of iterations performed while training the model.
"""
_template = "{iter:>10d} {logprob:>16.4f} {delta:>+16.4f}"
def __init__(self, tol, n_iter, verbose):
self.tol = tol
self.n_iter = n_iter
self.verbose = verbose
self.history = deque(maxlen=2)
self.iter = 0
def __repr__(self):
class_name = self.__class__.__name__
params = dict(vars(self), history=list(self.history))
return "{0}({1})".format(
class_name, _pprint(params, offset=len(class_name)))
def report(self, logprob):
"""Reports convergence to :data:`sys.stderr`.
The output consists of three columns: iteration number, log
probability of the data at the current iteration and convergence
rate. At the first iteration convergence rate is unknown and
is thus denoted by NaN.
Parameters
----------
logprob : float
The log probability of the data as computed by EM algorithm
in the current iteration.
"""
@property
def converged(self):
"""``True`` if the EM algorithm converged and ``False`` otherwise."""
# XXX we might want to check that ``logprob`` is non-decreasing.
return (self.iter == self.n_iter or
(len(self.history) == 2 and
self.history[1] - self.history[0] < self.tol))
/////////
Here is except of the online help content:
| Data descriptors defined here:
|
| __dict__
| dictionary for instance variables (if defined)
|
| __weakref__
| list of weak references to the object (if defined)
|
| converged
| ``True`` if the EM algorithm converged and ``False`` otherwise.
The data conclusion is verified by the following test code:
from hmmlearn.base import ConvergenceMonitor
class TestMonitor(object):
def test_converged_by_iterations(self):
print 'self test0'
m = ConvergenceMonitor(tol=1e-3, n_iter=2, verbose=False)
print 'self test1', m.converged
assert not m.converged
print 'self test2', m.converged
m.report(-0.01)
assert not m.converged
print 'self test3', m.converged
m.report(-0.1)
assert m.converged
print 'self test4', m.converged
tmp_obj=TestMonitor()
print 'ttt', tmp_obj.test_converged_by_iterations()
mm = ConvergenceMonitor(tol=1e-3, n_iter=2, verbose=False)
print 'self test mm', mm.converged
That is, I can only use:
mm.converged
If I use it in this way:
mm.converged()
it will have error:
TypeError Traceback (most recent call last)
C:\Users\rj\Documents\PythonDocPrj0\hmmlearn-master\hmmlearn\tests\test_base1.py
in <module>()
27 print None
28 mm = ConvergenceMonitor(tol=1e-3, n_iter=2, verbose=False)
---> 29 print 'self test mm', mm.converged()
30
TypeError: 'bool' object is not callable
On the other hand, 'play' in the following class is seen as a member
function:
class Engine(object):
def __init__(self, scene_map):
pass
def play(self):
print 'play'
return True
a_game = Engine(scene_map=0.1)
a_game.play()
Why can 'converged' only be seen as a data, while 'play' can be seen as
a function?
Thanks,
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