4d5d9239cc
git-svn-id: svn://svn.cy55.de/Zope3/src/cybertools/trunk@1257 fd906abe-77d9-0310-91a1-e0d9ade77398
79 lines
2.5 KiB
Python
79 lines
2.5 KiB
Python
#
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# Copyright (c) 2006 Helmut Merz helmutm@cy55.de
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#
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation; either version 2 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program; if not, write to the Free Software
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# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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#
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"""
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Interfaces for a sort of neural network.
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$Id$
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"""
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from zope.interface import Interface, Attribute
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class ISynapsis(Interface):
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""" A synapsis connects two neurons.
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"""
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sender = Attribute("The sender neuron for this synapsis")
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reciever = Attribute("The receiver neuron for this synapsis")
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transformation = Attribute("A transformation is used to transform "
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"the sender neuron's state.")
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class INeuron(Interface):
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state = Attribute("The current state of the neuron")
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senders = Attribute("The sender synapses")
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receivers = Attribute("The receiver synapses")
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stateMerger = Attribute("Merges a state with a list of other states "
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"in order to create a new state.")
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def trigger():
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""" Notifies the neuron that something has happened. This method
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should get the transformed states from all sender synapses
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and merge them in order to calculate the neuron's new state;
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then it should call the trigger() method on all downstream
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(receiver)neurons.
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In addition it may perform side effects like changing
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transition properties of adjacent synapses or even create new
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synapses or neurons; this side effects should happen before
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triggering the receiver neurons.
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"""
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class IState(Interface):
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""" The state of a neuron.
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"""
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class IStateTransformation(Interface):
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def transform(state):
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""" Transform state to a new state value and return it.
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"""
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class IStateMerger(Interface):
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def merge(state, senderStates):
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""" Transform state to a new value by taking into account a list
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of sender neurons' states. This modifies state in-place.
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"""
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