80 lines
2.6 KiB
Python
80 lines
2.6 KiB
Python
import logging
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from group import Group
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from letter import Letter
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class WorkspaceString(object):
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def __init__(self, ctx, s):
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slipnet = ctx.slipnet
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workspace = ctx.workspace
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self.ctx = ctx
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self.string = s
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self.bonds = []
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self.objects = []
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self.letters = []
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self.length = len(s)
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self.intraStringUnhappiness = 0.0
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for position, c in enumerate(self.string.upper(), 1):
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value = ord(c) - ord('A')
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letter = Letter(self, position, self.length)
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letter.workspaceString = self
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letter.addDescription(slipnet.objectCategory, slipnet.letter)
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letter.addDescription(slipnet.letterCategory, slipnet.letters[value])
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letter.describe(position, self.length)
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workspace.buildDescriptions(letter)
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self.letters += [letter]
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def __repr__(self):
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return '<WorkspaceString: %s>' % self.string
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def __str__(self):
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return '%s with %d letters, %d objects, %d bonds' % (
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self.string, len(self.letters), len(self.objects), len(self.bonds))
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def log(self, heading):
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s = '%s: %s - ' % (heading, self)
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for l in self.letters:
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s += ' %s' % l
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s += '; '
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for o in self.objects:
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s += ' %s' % o
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s += '; '
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for b in self.bonds:
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s += ' %s' % b
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s += '.'
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logging.info(s)
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def __len__(self):
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return len(self.string)
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def __getitem__(self, i):
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return self.string[i]
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def updateRelativeImportance(self):
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"""Update the normalised importance of all objects in the string"""
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total = sum(o.rawImportance for o in self.objects)
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if not total:
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for o in self.objects:
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o.relativeImportance = 0.0
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else:
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for o in self.objects:
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logging.info('object: %s, relative: %d = raw: %d / total: %d',
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o, o.relativeImportance * 1000, o.rawImportance,
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total)
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o.relativeImportance = o.rawImportance / total
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def updateIntraStringUnhappiness(self):
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if not len(self.objects):
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self.intraStringUnhappiness = 0.0
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return
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total = sum(o.intraStringUnhappiness for o in self.objects)
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self.intraStringUnhappiness = total / len(self.objects)
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def equivalentGroup(self, sought):
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for objekt in self.objects:
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if isinstance(objekt, Group):
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if objekt.sameGroup(sought):
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return objekt
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return None
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