Package mdp :: Package nodes :: Class _OneDimensionalHitParade

Class _OneDimensionalHitParade

Class to produce hit-parades (i.e., a list of the locally largest and smallest values) out of a one-dimensional time-series.

Instance Methods

[hide private]

__init__(self, n, d, real_dtype='d', integer_dtype='l')
Initializes an object of type 'OneDimensionalHitParade'.

tuple

get_maxima(self)
Return the tuple defining the maxima fulfilling specified criteria.

tuple

get_minima(self)
Return the tuple defining the minima fulfilling specified criteria.

update(self, inp)

Inherited from unreachable.newobject: __long__, __native__, __nonzero__, __unicode__, next

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__

Properties

[hide private]

Inherited from object: __class__

Method Details

[hide private]

init(self, n, d, real_dtype=`'d'`, integer_dtype=`'l'`)
(Constructor)

Initializes an object of type 'OneDimensionalHitParade'.

Parameters:

n (int) - Number of maxima and minima to remember.
d (int) - Minimum gap between two hits.
real_dtype (numpy.dtype or str) - Datatype of sequence items
integer_dtype (numpy.dtype or str) - Datatype of sequence indices

Overrides: object.__init__

get_maxima(self)

Return the tuple defining the maxima fulfilling specified criteria.

Returns: tuple: A tuple containing maxima and their corresponding indices as numpy.ndarrays (see example in definition of the method OneDimensionalHitParade.update). The maxima are sorted in descending order.

get_minima(self)

Return the tuple defining the minima fulfilling specified criteria.

Returns: tuple: A tuple containing minima and their corresponding indices as numpy.ndarrays (see example in definition of the OneDimensionalHitParade.update() function). The minima are sorted in descending order.

update(self, inp)

Parameters:

inp (tuple) - A time series, defined by a tuple of numpy.ndarrays with the first element containing the values and the second containing the corresponding index. An example can be given by:
```
>>> indices = numpy.array([0,1,2])
>>> values = numpy.array([100,101,100])
>>> avalidtuple = (indices,values)
```

Class _OneDimensionalHitParade

__init__(self, n, d, real_dtype='d', integer_dtype='l') (Constructor)

get_maxima(self)

get_minima(self)

update(self, inp)

init(self, n, d, real_dtype=`'d'`, integer_dtype=`'l'`)
(Constructor)