#

# This is part of "python-cluster". A library to group similar items together.

# Copyright (C) 2006 Michel Albert

#

# This library is free software; you can redistribute it and/or modify it

# under the terms of the GNU Lesser General Public License as published by the

# Free Software Foundation; either version 2.1 of the License, or (at your

# option) any later version.

# This library is distributed in the hope that it will be useful, but WITHOUT

# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or

# FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License

# for more details.

# You should have received a copy of the GNU Lesser General Public License

# along with this library; if not, write to the Free Software Foundation,

# Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA

#

class BaseClusterMethod(object):

"""

The base class of all clustering methods.

"""

def __init__(self, input, distance_function):

"""

Constructs the object and starts clustering

PARAMETERS

input - a list of objects

distance_function - a function returning the distance - or

opposite of similarity ( distance =

-similarity ) - of two items from the input.

In other words, the closer the two items are

related, the smaller this value needs to be.

With 0 meaning they are exactly the same.

NOTES

The distance function should always return the absolute distance

between two given items of the list. Say,

distance(input[1], input[4]) = distance(input[4], input[1])

This is very important for the clustering algorithm to work!

Naturally, the data returned by the distance function MUST be a

comparable datatype, so you can perform arithmetic comparisons on

them (< or >)! The simplest examples would be floats or ints. But

as long as they are comparable, it's ok.

"""

self.distance = distance_function

self._input = input # the original input

self._data = input[:] # clone the input so we can work with it

# without distroying the original data.

def topo(self):

"""

Returns the structure (topology) of the cluster.

See Cluster.topology() for information.

"""

return self.data[0].topology()

@property

def data(self):

"""

Returns the data that is currently in process.

"""

return self._data

@property

def raw_data(self):

"""

Returns the raw data (data without being clustered).

"""

return self._input