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derivabilityMatrix.py
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derivabilityMatrix.py
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#!/usr/bin/python3
# PyElly - rule-based tool for analyzing natural language (Python v3.8)
#
# derivabilityMatrix.py : 12nov2019 CPM
# ------------------------------------------------------------------------------
# Copyright (c) 2019, Clinton Prentiss Mah
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
#
# Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
# -----------------------------------------------------------------------------
"""
bit encoding of derivability relationships between syntax types
"""
import ellyBits
class DerivabilityMatrix(object):
"""
binary transitive closure matrix for derivability of syntax types
attributes:
dm - row matrix
"""
def __init__ ( self , nmax ):
"""
initialization
arguments:
self -
nmax - how many syntactic types to encode
"""
self.dm = [ ] # empty matrix initially
for i in range(nmax):
rw = ellyBits.EllyBits(nmax) # get bit string
rw.set(i) # diagonalize matrix by row
self.dm.append(rw) # and save
def derivable ( self , n , gbs ):
"""
check whether any specified bits are on in specified matrix row
arguments:
self -
n - which row, corresponding to syntactic type
gbs - goal bits to check
returns:
True if specified bit is on, False otherwise
"""
return self.dm[n].intersect(gbs)
def join ( self , left , rght ):
"""
update derivability with information that left->rght or left-> rght x
arguments:
self -
left - syntax type derivable from left of rule
rght - syntax type derived from right of rule
"""
if self.dm[rght].test(left): # derivability already known?
return # if so, done
rw = self.dm[left] # otherwise, get transitive closure of derivability
lm = len(self.dm) # row count for matrix
for i in range(lm): # next row for next syntactic type
if self.dm[i].test(rght): # is right derivable for this type?
self.dm[i].combine(rw) # if so, then everything for left is also derivable
def row ( self , n ):
"""
get row of matrix
arguments:
self -
n - row index, corresponding to syntactic type
returns:
specified row as EllyBits
"""
return self.dm[n]
#
# unit test
#
if __name__ == '__main__':
def dump ( m ):
""" to show bits in matrix for testing
"""
print ( 0 , m.dm[0].hexadecimal() )
print ( 1 , m.dm[1].hexadecimal() )
print ( 2 , m.dm[2].hexadecimal() )
print ( 3 , m.dm[3].hexadecimal() )
print ( 4 , m.dm[4].hexadecimal() )
print ( 5 , m.dm[5].hexadecimal() )
print ()
mtx = DerivabilityMatrix(24)
print ( mtx )
dump(mtx)
mtx.join(0,1)
dump(mtx)
mtx.join(2,3)
dump(mtx)
mtx.join(1,2)
dump(mtx)
mtx.join(3,4)
dump(mtx)
mtx.join(4,5)
dump(mtx)